96280 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

1U.S. Congress. (1940) United States Code: Social 

Security Act, 42 U.S.C. 1315a(b)(2)(a). 

DEPARTMENT OF HEALTH AND 

HUMAN SERVICES 

Centers for Medicare & Medicaid 

Services 

42 CFR Part 512 

[CMS–5535–F] 

RIN 0938–AU51 

Medicare Program; Alternative 

Payment Model Updates and the 

Increasing Organ Transplant Access 

(IOTA) Model 

AGENCY: Centers for Medicare & 

Medicaid Services (CMS), Department 

of Health and Human Services (HHS). 

ACTION: Final rule. 

SUMMARY: This final rule describes a 

new mandatory alternative payment 

model, the Increasing Organ Transplant 

Access Model (IOTA Model), that will 

test whether performance-based upside 

risk payments or downside risk 

payments paid to or owed by 

participating kidney transplant 

hospitals increase access to kidney 

transplants for patients with end-stage 

renal disease (ESRD) while preserving 

or enhancing the quality of care and 

reducing Medicare expenditures. This 

final rule also adopts standard 

provisions that will apply to the 

Radiation Oncology Model, the EndStage Renal Disease (ESRD) Treatment 

Choices Model, and mandatory 

Innovation Center models, including the 

IOTA Model, whose first performance 

period begins on or after January 1, 

2025. The finalized standard provisions 

relate to beneficiary protections; 

cooperation in model evaluation and 

monitoring; audits and records 

retention; rights in data and intellectual 

property; monitoring and compliance; 

remedial action; model termination by 

CMS; limitations on review; 

miscellaneous provisions on bankruptcy 

and other notifications; and the 

reconsideration review process. 

DATES: These regulations are effective 

January 3, 2025. 

FOR FURTHER INFORMATION CONTACT: 

Thomas Duvall (410) 786–8887, for 

questions related to the Increasing 

Organ Transplant Access Model. 

Lina Gebremariam, (410) 786–8893, 

for questions related to the Increasing 

Organ Transplant Access Model. 

Christina McCormick (410) 786–4012, 

for questions related to the Increasing 

Organ Transplant Access Model. 

CMMItransplant@cms.hhs.gov for 

questions related to the Increasing 

Organ Transplant Access Model. 

CMMI-StandardProvisions@

cms.hhs.gov for questions related to the 

Standard Provisions for Innovation 

Center Models. 

SUPPLEMENTARY INFORMATION: 

Current Procedural Terminology (CPT) 

Copyright Notice 

Throughout this final rule, we use 

CPT® codes and descriptions to refer to 

a variety of services. We note that CPT®

codes and descriptions are copyright 

2020 American Medical Association 

(AMA). All Rights Reserved. CPT® is a 

registered trademark of the American 

Medical Association. Applicable 

Federal Acquisition Regulations (FAR) 

and Defense Federal Acquisition 

Regulations (DFAR) apply. 

I. Executive Summary 

A. Purpose 

Section 1115A of the Social Security 

Act (the Act) gives the Secretary of the 

Department of Health and Human 

Services the authority to test innovative 

payment and service delivery models to 

reduce program expenditures in 

Medicare, Medicaid, and the Children’s 

Health Insurance Program (CHIP) while 

preserving or enhancing the quality of 

care furnished to individuals covered by 

such programs. Specifically, section 

1115A(b)(2)(a) of the Act states that ‘‘the 

Secretary shall select models to be 

tested from models where the Secretary 

determines that there is evidence that 

the model addresses a defined 

population for which there are deficits 

in care leading to poor clinical 

outcomes or potentially avoidable 

expenditures. The Secretary shall focus 

on models expected to reduce program 

costs under the applicable title while 

preserving or enhancing the quality of 

care received by individuals receiving 

benefits under such title.’’ 1 This final 

rule describes a new mandatory 

Medicare payment model to be tested 

under section 1115A of the Act—the 

Increasing Organ Transplant Access 

Model (IOTA Model)—which will begin 

on July 1, 2025, and end on June 30, 

2031. In this final rule, we address 

payment policies, participation 

requirements, and other provisions to 

test the IOTA Model. We will test 

whether performance-based incentives 

(including both upside and downside 

risk payments) for participating kidney 

transplant hospitals can increase the 

number of functioning kidney 

transplants (including both living donor 

and deceased donor transplants) 

furnished to end stage renal disease 

(ESRD) patients, encourage investments 

in care processes and patterns with 

respect to patients who need kidney 

transplants, encourage investments in 

value-based care and improvement 

activities, and promote greater 

accountability by participating kidney 

transplant hospitals by tying payments 

to the value of the care provided. The 

IOTA Model is also intended to advance 

health equity by improving equitable 

access to the transplantation ecosystem 

for all patients, such as rural and 

underserved populations, through 

design features such as voluntary health 

equity plans to address health outcome 

disparities. 

This final rule also includes standard 

provisions that will apply to the RO 

Model, the ETC model, and all 

mandatory Innovation Center models 

whose first performance periods begin 

on or after January 1, 2025. The 

standard provisions address beneficiary 

protections; cooperation in model 

evaluation and monitoring; audits and 

record retention; rights in data and 

intellectual property; monitoring and 

compliance; remedial action; model 

termination by CMS; limitations on 

review; miscellaneous provisions on 

bankruptcy and other notifications; and 

the reconsideration review process. 

As we stated in the notice of proposed 

rulemaking, the IOTA Model will test 

ways to reduce Medicare expenditures 

while preserving or enhancing the 

quality of care furnished to 

beneficiaries. We are finalizing several, 

but not all, of the provisions discussed 

in the proposed rule, and we intend to 

address certain other provisions 

discussed in the proposed rule in future 

rulemaking. We also note that some of 

the public comments were outside of 

the scope of the proposed rule. These 

out-of-scope public comments are not 

addressed in this final rule. We have 

summarized the public comments that 

are within the scope of the proposed 

rule and have included our responses to 

those public comments. However, we 

note that in this final rule we are not 

addressing most comments received 

with respect to the provisions of the 

proposed rule that we are not finalizing 

at this time. Rather, we will address 

them at a later time, in a subsequent 

rulemaking document, as appropriate. 

We are clarifying and emphasizing our 

intent that if any provision of this final 

rule is held to be invalid or 

unenforceable by its terms, or as applied 

to any person or circumstance, or stayed 

pending further action, it shall be 

severable from other parts of this final 

rule, and from rules and regulations 

currently in effect, and not affect the 

remainder thereof or the application of 

the provision to other persons not 

similarly situated or to other, dissimilar 


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Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96281 

2End-Stage Renal Disease (ESRD) | CMS. (n.d.). 

https://www.cms.gov/medicare/coordinationbenefits-recovery/overview/end-stage-renal-diseaseesrd. 

3United States Renal Data System. 2022 USRDS 

Annual Data Report: Epidemiology of kidney 

disease in the United States. National Institutes of 

Health, National Institute of Diabetes and Digestive 

and Kidney Diseases, Bethesda, MD, 2022. 

4Tonelli, M., Wiebe, N., Knoll, G., Bello, A., 

Browne, S., Jadhav, D., Klarenbach, S., & Gill, J. 

(2011). Systematic Review: Kidney Transplantation 

Compared With Dialysis in Clinically Relevant 

Outcomes. American Journal of Transplantation, 

11(10), 2093–2109. https://doi.org/10.1111/j.1600- 

6143.2011.03686.x. 

5Cheng, X.S., Han, J., Braggs-Gresham, J.L., Held, 

P.J., Busque, S., Roberts, J.P., Tan, J.C., Scandling, 

J.D., Chertow, G.M., & Dor, A. (2022). Trends in 

Cost Attributable to Kidney Transplantation 

Evaluation and Waitlist Management in the United 

States, 2012–2017. JAMA network open, 5(3), 

e221847. https://doi:10.1001/ 

jamanetworkopen.2022.1847. 

6Al Ammary, F., Bowring, M.G., Massie, A.B., 

Yu, S., Waldram, M.M., Garonzik-Wang, J., Thomas, 

A.G., Holscher, C.M., Qadi, M.A., Henderson, M.L., 

Wiseman, A.C., Gralla, J., Brennan, D.C., Segev, 

D.L., & Muzaale, A.D. (2019). The changing 

landscape of live kidney donation in the United 

States from 2005 to 2017. American Journal of 

Transplantation: Official Journal of the American 

Society of Transplantation and the American 

Society of Transplant Surgeons, 19(9), 2614–2621. 

https://doi.org/10.1111/ajt.15368. 

7Mohan, S., Yu, M., King, K.L., & Husain, S.A. 

(2023). Increasing Discards as an Unintended 

Consequence of Recent Changes in United States 

Kidney Allocation Policy. Kidney International 

Reports, 8(5), 1109–1111. 

8https://doi.org/10.1016/j.ekir.2023.02.1081. 

circumstances. Through this rule, we 

adopt provisions that are intended to 

and will operate independently of each 

other, even if each serves the same 

general purpose or policy goal. Where a 

provision is necessarily dependent on 

another, the context generally makes 

that clear. 

B. Summary of the Provisions 

1. Standard Provisions for Innovation 

Center Models 

The standard provisions for 

Innovation Center models will be 

applicable to the RO Model, the ETC 

Model, and all mandatory Innovation 

Center models whose first performance 

periods begin on or after January 1, 

2025. 

We are codifying these standard 

provisions to increase transparency, 

efficiency, and clarity in the operation 

and governance of mandatory 

Innovation Center models, and to avoid 

the need to restate the provisions in 

each model’s governing documentation. 

The standard provisions include terms 

that have been repeatedly memorialized, 

with minimal variation, in existing 

models’ governing documentation. The 

standard provisions are not intended to 

encompass all of the terms and 

conditions that will apply to each 

mandatory Innovation Center model, as 

each model includes unique design 

features and implementation plans that 

may require additional, more tailored 

provisions, including with respect to 

payment methodology, care delivery 

and quality measurement, that will 

continue to be included in each model’s 

governing documentation. We note that 

while we are not finalizing our proposal 

to apply the standard provisions to 

voluntary Innovation Center models, we 

expect to utilize the provisions in 

voluntary models and will incorporate 

them by reference into the models’ 

governing documentation as appropriate 

based on the model’s design. Modelspecific provisions applicable to the 

IOTA Model are described in section III 

of this final rule. 

2. Model Overview—Proposed 

Increasing Organ Transplant Access 

Model 

a. Proposed IOTA Model Overview 

End-Stage Renal Disease (ESRD) is a 

medical condition in which a person’s 

kidneys cease functioning on a 

permanent basis, leading to the need for 

a regular course of long-term dialysis or 

a kidney transplant to maintain life.2

The best treatment for most patients 

with kidney failure is kidney 

transplantation. Nearly 808,000 people 

in the United States are living with 

ESRD, with about 69 percent on dialysis 

and 31 percent with a kidney 

transplant.3 Relative to dialysis, a 

kidney transplant can improve survival, 

reduce avoidable health care utilization 

and hospital acquired conditions, 

improve quality of life, and lower 

Medicare expenditures.4 5 However, 

despite these benefits of kidney 

transplantation, evidence shows low 

rates of ESRD patients placed on kidney 

transplant hospitals’ waitlists, a decline 

in living donors over the past 20 years, 

and underutilization of available donor 

kidneys, coupled with increasing rates 

of donor kidney discards, and wide 

variation in kidney offer acceptance 

rates and donor kidney discards by 

region and across kidney transplant 

hospitals.6 7 Further, there are 

substantial disparities in both deceased 

and living donor transplantation rates 

among structurally disadvantaged 

populations. Strengthening and 

improving the performance of the organ 

transplantation system is a priority for 

the Department of Health and Human 

Services (HHS).8 Consistent with this 

priority, and through joint efforts with 

HHS’ Health Resources and Services 

Administration (HRSA), the IOTA 

Model will aim to reduce Medicare 

expenditures and improve quality 

performance and equity in kidney 

transplantation by creating 

performance-based incentive payments 

for participating kidney transplant 

hospitals tied to kidney transplant] 

access and quality of care for ESRD 

patients on the hospitals’ waitlists. 

The IOTA Model will be a mandatory 

model that will begin on July 1, 2025, 

and end on June 30, 2031, resulting in 

a 6-year model performance period 

comprised of 6 individual performance 

years (‘‘PYs’’). The IOTA Model will test 

whether performance-based incentives 

paid to, or owed by, participating 

kidney transplant hospitals can increase 

access to kidney transplants for patients 

with ESRD, while preserving or 

enhancing quality of care and reducing 

Medicare expenditures. CMS will select 

kidney transplant hospitals to 

participate in the IOTA Model through 

the methodology proposed in section 

III.C.3.d of this final rule. As this will 

be a mandatory model, the selected 

kidney transplant hospitals will be 

required to participate. CMS will 

measure and assess the participating 

kidney transplant hospitals’ 

performance during each PY across 

three performance domains: 

achievement, efficiency, and quality. 

The achievement domain will assess 

each participating kidney transplant 

hospital on the overall number of 

kidney transplants performed during a 

PY, relative to a participant-specific 

target. The efficiency domain will assess 

the kidney organ offer acceptance rate 

ratios of each participating kidney 

transplant hospital relative to a national 

ranking or the participating kidney 

transplant hospital’s past organ offer 

acceptance rate ratio. The quality 

domain will assess the quality of care 

provided by the participating kidney 

transplant hospitals via a composite 

graft survival ratio. Each participating 

kidney transplant hospital’s 

performance score across these three 

domains will determine its final 

performance score and corresponding 

amount for the upside risk payment that 

CMS would pay to the participating 

kidney transplant hospital, or the 

downside risk payment that would be 

owed by the participating kidney 

transplant hospital to CMS. The upside 

risk payment will be a lump sum 

payment paid by CMS after the end of 

a PY to a participating kidney transplant 

hospital with a final performance score 

of 60 or greater. Conversely, beginning 

in PY 2, the downside risk payment will 

be a lump sum payment paid to CMS by 

any participating kidney transplant 

hospital with a final performance score 

of 40 or lower. There is no downside 

risk payment for PY 1 of the model. 


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96282 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

b. Model Scope 

Participation in the IOTA Model will 

be mandatory for approximately 50 

percent of all eligible kidney transplant 

hospitals in the United States. We 

anticipate that a total of approximately 

90 kidney transplant hospitals will be 

selected to participate in the IOTA 

Model. Additionally, we note that we 

intend to publicly post information 

regarding the selection process and how 

it resulted in the list of DSAs and 

kidney transplant hospitals selected to 

participate in the model. As discussed 

in section III.C.3.b. of this final rule, we 

believe that mandatory participation is 

necessary to minimize the potential for 

selection bias and to ensure a 

representative sample size nationally, 

thereby guaranteeing that there will be 

adequate data to evaluate the model test. 

Eligible kidney transplant hospitals 

will be those that: (1) performed at least 

eleven kidney transplants for patients 

18 years of age or older annually 

regardless of payer type during the 

three-year period ending 12 months 

before the model’s start date; and (2) are 

non-pediatric transplant facilities that 

furnished more than 50 percent of the 

hospital’s annual kidney transplants to 

patients 18 years of age or older during 

that same period. CMS will select the 

kidney transplant hospitals that will be 

required to participate in the IOTA 

Model from the group of eligible kidney 

transplant hospitals using a stratified 

random sampling of donation service 

areas (‘‘DSAs’’) to ensure that there is a 

fair selection process and representative 

group of participating kidney transplant 

hospitals. For the purposes of this final 

rule, a DSA has the same meaning given 

to that term at 42 CFR 486.302. 

c. Performance Assessment 

CMS will assess each participating 

kidney transplant hospital’s 

performance across three performance 

domains during each PY of the model, 

with a maximum possible final 

performance score of 100 points. The 

three performance domains will 

include: (1) an achievement domain 

worth up to 60 points, (2) an efficiency 

domain worth up to 20 points, and (3) 

a quality domain worth up to 20 points. 

The achievement domain will assess 

the number of kidney transplants 

performed by each IOTA participant for 

attributed patients, with performance on 

this domain worth up to 60 points. The 

final performance score will be heavily 

weighted on the achievement domain to 

align with the IOTA Model’s goal to 

increase access to kidney transplants to 

improve the quality of care and reduce 

Medicare expenditures. The IOTA 

Model theorizes that improvement 

activities, including those aimed at 

reducing unnecessary deceased donor 

discards and increasing living donors, 

may help increase access to kidney 

transplants. 

CMS will set a target number of 

kidney transplants for each IOTA 

participant for each PY to measure the 

IOTA participant’s performance in the 

achievement domain), as described in 

section III.C.5.c of the final rule. Each 

IOTA participant’s transplant target for 

a given PY will be based on the IOTA 

participant’s historical volume of 

deceased and living donor transplants 

furnished to attributed patients in the 

relevant baseline years, adjusted by the 

national trend rate in the number of 

kidney transplants performed. Section 

III.C.5.c. of this final rule describes the 

variation in the number of kidney 

transplants performed across kidney 

transplant hospitals, which would make 

it challenging to set transplant targets on 

a regional or national basis. The IOTA 

Model will therefore set a transplant 

target that is specific to each IOTA 

participant to address this concern, 

while still accounting for the national 

trend rate in the number of kidney 

transplants performed. It is expected 

that IOTA participants’ transplant 

targets may change from PY to PY due 

to this calculation methodology. 

The efficiency domain will assess the 

kidney organ offer acceptance rate ratio 

for each IOTA participant. The kidney 

organ offer acceptance rate ratio 

measures the number of kidneys an 

IOTA participant accepts for transplant 

over the expected value, based on 

variables such as kidney quality. CMS 

will assess the kidney organ offer 

acceptance rate ratio relative to either 

the kidney organ offer acceptance rate 

ratio across all kidney transplant 

hospitals or the IOTA participant’s own 

past kidney organ offer acceptance rate 

ratio, with CMS using whichever 

method results in the IOTA participant 

receiving the most points, with 

performance on the efficiency domain 

being worth up to 20 points. 

Finally, the quality domain will 

assess IOTA participants’ performance 

on a composite graft survival ratio 

measuring post-transplant outcomes— 

relative to the composite graft survival 

ratio across all kidney transplant 

hospitals, with performance on this 

domain being worth up to 20 points. 

Each IOTA participant’s final 

performance score will be the sum of 

the points earned for each domain: 

achievement, efficiency, and quality. 

The final performance score in a PY will 

determine whether the IOTA participant 

will be eligible to receive an upside risk 

payment from CMS, fall into the neutral 

zone where no upside or downside risk 

payment would apply, or owe a 

downside risk payment to CMS for the 

PY as described in section III.C.6 of this 

final rule. 

d. Performance-Based Upside Risk 

Payment and Downside Risk Payment 

Formula 

Each IOTA participant’s final 

performance score will determine 

whether: (1) CMS will pay an upside 

risk payment to the IOTA participant; 

(2) the IOTA participant will fall into a 

neutral zone where no performancebased incentive payment will be paid to 

or owed by the IOTA participant; or (3) 

the IOTA participant will owe a 

downside risk payment to CMS. For a 

final performance score of 60 and above, 

CMS will apply the formula for the 

upside risk payment, which will be 

equal to the IOTA participant’s final 

performance score minus 60, then 

divided by 40, then multiplied by 

$15,000, then multiplied by the number 

of kidney transplants furnished by the 

IOTA participant to attributed patients 

with Medicare Fee-for-Service (FFS) as 

their primary or secondary payer during 

the PY. Final performance scores below 

60 in PY 1 and final performance scores 

of 41 to 59 (inclusive) in PYs 2–6 will 

fall in the neutral zone where there will 

be no payment owed to the IOTA 

participant or CMS. 

We will phase-in the downside risk 

payment beginning in PY2. We explain 

in section III.C.5.b of this final rule that 

new entrants to value-based payment 

models may need a ramp-up period 

before they are able to accept downside 

risk. Thus, the IOTA Model utilizes an 

upside risk-only approach for PY 1 as an 

incentive in each of the three 

performance domains. This will give 

IOTA participants time to consider, 

invest in, and implement value-based 

care and quality improvement 

initiatives before downside risk 

payments begin. Beginning in PY 2, for 

a final performance score of 40 and 

below, CMS will apply the formula for 

the downside risk payment, which will 

be equal to 40 minus the IOTA 

participant’s final performance score, 

then divided by 40, then multiplied by 

$2,000, then multiplied by the number 

of kidney transplants furnished by the 

IOTA participant to attributed patients 

with Medicare FFS as their primary or 

secondary payer during the PY. 

CMS will pay the upside risk payment 

in a lump sum to the IOTA participant 

after the PY. The IOTA participant will 

pay the downside risk payment to CMS 

in a lump sum after the PY. 


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e. Data Sharing 

CMS will collect certain quality, 

clinical, and administrative data from 

IOTA participants for model monitoring 

and evaluation activities under the 

authority in 42 CFR 403.1110(b). We 

will also share certain data with IOTA 

participants upon request as described 

in section III.C.3.a. of this final rule and 

as permitted by the Health Insurance 

Portability and Accountability Act of 

1996 (HIPAA) Privacy Rule and other 

applicable law. We will offer each IOTA 

participant the opportunity to request 

certain beneficiary-identifiable data for 

their attributed Medicare beneficiaries 

for treatment, case management, care 

coordination, quality improvement 

activities, and population-based 

activities relating to improving health or 

reducing health care costs, as permitted 

by 45 CFR 164.506(c). The data uses and 

sharing will be allowed only to the 

extent permitted by the HIPAA Privacy 

Rule and other applicable law and CMS 

policies. We will also share certain 

aggregate, de-identified data with IOTA 

participants. 

f. Other Requirements 

There are several other model 

requirements for selected transplant 

hospitals, including transparency 

requirements and public reporting 

requirements. IOTA participants may 

also submit a voluntary health equity 

plan during the model, as described in 

section III.C.8. of this rule. 

(1) Transparency Requirements 

Patients are often unsure whether 

they qualify for a kidney transplant at a 

given kidney transplant hospital. IOTA 

participants will be required to publish, 

on a public facing website, the criteria 

they use when determining whether or 

not to add a patient to the kidney 

transplant waitlist. 

(2) Health Equity Requirements 

An IOTA participant may submit a 

health equity plan (‘‘HEP’’) to CMS. The 

submission of HEPs will be voluntary 

for IOTA participants for the duration of 

the model. The HEP will identify health 

disparities within the IOTA 

participant’s population of attributed 

patients and outline a course of action 

to address them. 

g. Medicare Payment Waivers and 

Additional Flexibilities 

We believe it is necessary to waive 

certain requirements of title XVIII of the 

Act solely for purposes of carrying out 

the testing of the IOTA Model under 

section 1115A of the Act. We will issue 

these waivers using our waiver 

authority under section 1115A(d)(1) of 

the Act, which states that the Secretary 

may waive such requirements of titles 

XI and XVIII and of sections 1902(a)(1), 

1902(a)(13), 1903(m)(2)(A)(iii), and 1934 

(other than subsections (b)(1)(A) and 

(c)(5) of such section) as may be 

necessary solely for purposes of carrying 

out this section with respect to testing 

models described in section 1115A(b) of 

the Act. Each of the waivers is discussed 

in detail in section III.C.11.i. of this final 

rule. 

h. Overlaps With Other Innovation 

Center Models and CMS Programs 

We expect that there could be 

situations where a Medicare beneficiary 

attributed to an IOTA participant is also 

assigned, aligned, or attributed to 

another Innovation Center model or 

CMS program. Overlap could also occur 

among providers and suppliers at the 

individual or organization level, such as 

where an IOTA participant or one of 

their providers participates in multiple 

Innovation Center models. We believe 

that the IOTA Model will be compatible 

with existing models and programs that 

provide opportunities to improve care 

and reduce spending. The IOTA Model 

will not be replacing any covered 

services or changing the payments that 

participating hospitals receive through 

the inpatient prospective payment 

system (IPPS) or outpatient prospective 

payment system (OPPS). Rather, the 

IOTA Model implements performancebased payments separate from what 

participants will be paid by CMS for 

furnishing kidney transplants to 

Medicare beneficiaries. Additionally, 

we will work to resolve any potential 

overlaps between the IOTA Model and 

other Innovation Center models or CMS 

programs that could result in 

duplicative payments for services, or 

duplicative counting of savings or other 

reductions in expenditures. Therefore, 

we are allowing overlaps between the 

IOTA Model and other Innovation 

Center models and CMS programs. 

i. Monitoring 

We will closely monitor the 

implementation and outcomes of the 

IOTA Model throughout its duration 

consistent with the monitoring 

requirements in the Standard Provisions 

for Innovation Center models in section 

II of this final rule and the requirements 

in section III.C.13. of this final rule. The 

purpose of this monitoring will be to 

ensure that the IOTA Model is 

implemented safely and appropriately, 

that the quality and experience of care 

for beneficiaries is not harmed, and that 

adequate patient and program integrity 

safeguards are in place. 

j. Beneficiary Protections 

As mentioned in section III.C.10. of 

this final rule, CMS will not allow 

beneficiaries or patients to opt out of 

attribution to an IOTA participant; 

however, the IOTA Model will not 

restrict a beneficiary’s freedom to 

choose another kidney transplant 

hospital or any other provider or 

supplier for healthcare services, and 

IOTA participants will be subject to the 

Standard Provisions for Innovation 

Center Models outlined in section II of 

this final rule protecting Medicare 

beneficiary freedom of choice and 

access to medically necessary services. 

We also require that IOTA participants 

notify Medicare beneficiaries of the 

IOTA participant’s participation in the 

IOTA Model by, at a minimum, 

prominently displaying informational 

materials in offices or facilities where 

beneficiaries receive care. 

C. Summary of Costs and Benefits 

The IOTA Model aims to incentivize 

transplant hospitals to overcome 

system-level barriers to kidney 

transplantation. The chronic shortfall in 

kidney transplants results in poorer 

outcomes for patients and increases the 

burden on Medicare in terms of 

payments for dialysis and dialysis-based 

enrollment in the program. Based on 

quantitative and qualitative analyses, 

there is reasonable evidence that the 

savings to Medicare resulting from an 

incremental growth in transplantation 

as a result of the IOTA Model will 

potentially exceed the payments 

projected under the model’s incentive 

structure. 

II. Standard Provisions for Innovation 

Center Models 

A. Introduction 

Section 1115A of the Act authorizes 

the Center for Medicare and Medicaid 

Innovation (the ‘‘Innovation Center’’) to 

‘‘test innovative payment and service 

delivery models to reduce program 

expenditures under the applicable titles 

[Medicare, Medicaid, and CHIP] while 

preserving or enhancing the quality of 

care furnished to individuals under 

such titles . . . In selecting such 

models, the Secretary shall give 

preference to models that also improve 

the coordination, quality, and efficiency 

of health care services . . .’’ We have 

designed and tested both voluntary 

Innovation Center models—governed by 

participation agreements, cooperative 

agreements, and model-specific 

addenda to existing contracts with 

CMS—and mandatory Innovation 

Center models that are governed by 

regulations. Each voluntary and 


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96284 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

9 In the autumn of 2020, due to the Secretary of 

Health and Human Services’ Determination that a 

Public Health Emergency Exists for the Coronavirus 

disease 2019 (COVID–19) (https://aspr.hhs.gov/ 

legal/PHE/Pages/2019-nCoV.aspx), CMS revised the 

RO Model’s performance period to begin on July 1, 

2021, and to end on December 31, 2025, in the CY 

2021 Hospital Outpatient Prospective Payment 

(OPPS) and Ambulatory Surgical Center (ASC) 

Payment Systems and Quality Reporting Programs 

final rule with comment period (85 FR 85866). 

Section 133 of the Consolidated Appropriations Act 

(CAA), 2021 (Pub. L. 116–260) (hereinafter referred 

to as ‘‘CAA, 2021’’), enacted on December 27, 2020, 

included a provision that prohibited 

implementation of the RO Model before January 1, 

2022. This congressional action superseded the July 

1, 2021, start date that we had established in the 

CY 2021 OPPS/ASC IFC. To align the RO Model 

regulations with the requirements of the CAA, 2021, 

we proposed to modify the definition of ‘‘model 

performance period’’ in 42 CFR 512.205 to provide 

for a 5-year model performance period starting on 

January 1, 2022, unless the RO Model was 

prohibited by law from starting on January 1, 2022, 

in which case the model performance period would 

begin on the earliest date permitted by law that is 

January 1, April 1, or July 1. We also proposed other 

modifications both related and unrelated to the 

timing of the RO Model in the proposed rule that 

appeared in the August 4, 2021, Federal Register 

titled ‘‘Medicare Program: Hospital Outpatient 

Prospective Payment and Ambulatory Surgical 

Center Payment Systems and Quality Reporting 

Programs; Price Transparency of Hospital Standard 

Charges; Radiation Oncology Model; Request for 

Information on Rural Emergency Hospitals’’ (86 FR 

42018). These provisions were finalized in a final 

rule with comment period titled ‘‘Medicare 

Program: Hospital Outpatient Prospective Payment 

and Ambulatory Surgical Center Payment Systems 

and Quality Reporting Programs; Price 

Transparency of Hospital Standard Charges; 

Radiation Oncology Model’’ that appeared in the 

November 16, 2021 Federal Register (86 FR 63458) 

(hereinafter referred to as the ‘‘CY 2022 OPPS/ASC 

FC’’). 

On December 10, 2021, the Protecting Medicare 

and American Farmers from Sequester Cuts Act 

(Pub. L. 117–71) was enacted, which included a 

provision that prohibits implementation of the RO 

Model prior to January 1, 2023. The CY 2022 OPPS/ 

ASC final rule with comment period specified that 

if the RO Model was prohibited by law from 

beginning on January 1, 2022, the model 

performance period would begin on the earliest 

date permitted by law that is January 1, April 1, or 

July 1. As a result, under the current definition for 

model performance period at § 512.205, the RO 

Model would have started on January 1, 2023, 

because that date is the earliest date permitted by 

law. However, given the multiple delays to date, 

and because both CMS and RO participants must 

invest operational resources in preparation for 

implementation of the RO Model, we have 

considered how best to proceed under these 

circumstances. In a final rule titled ‘‘Radiation 

Oncology (RO) Model,’’ which appeared in the 

Federal Register on August 29, 2022 (87 FR 52698), 

we delayed the start date of the RO Model to a date 

to be determined through future rulemaking, and 

modified the definition of the model performance 

period at § 512.205 to provide that the start and end 

dates of the model performance period for the RO 

Model would be established in future rulemaking. 

We have not undertaken rulemaking to determine 

the start date for the RO Model and, thus, the model 

is not active at this time. 

mandatory model features its own 

specific payment methodology, quality 

metrics, and certain other applicable 

policies, but each model also features 

numerous provisions of a similar or 

identical nature, including provisions 

regarding cooperation in model 

evaluation; monitoring and compliance; 

and beneficiary protections. 

On September 29, 2020, we published 

in the Federal Register a final rule titled 

‘‘Medicare Program; Specialty Care 

Models To Improve Quality of Care and 

Reduce Expenditures’’ (85 FR 61114) 

(hereinafter the ‘‘Specialty Care Models 

final rule’’), in which we adopted 

General Provisions Related to 

Innovation Center models at 42 CFR 

part 512 subpart A that apply to the 

End-Stage Renal Disease Treatment 

Choices (ETC) Model and the Radiation 

Oncology (RO) Model.9 The Specialty 

Care Models final rule codified general 

provisions regarding beneficiary 

protections, cooperation in model 

evaluation and monitoring, audits and 

record retention, rights in data and 

intellectual property, monitoring and 

compliance, remedial action, model 

termination by CMS, limitations on 

review, and bankruptcy and other 

notifications. These general provisions 

were adopted only for the ETC and RO 

Models (and, in practice, applied only 

to the ETC Model). However, in the 

notice of proposed rulemaking, we 

explained that we now believe the 

general provisions should apply to 

Innovation Center models more broadly. 

As we noted, the Innovation Center 

models share numerous similar 

provisions, and we explained that we 

believed codifying the general 

provisions in regulation to expand their 

applicability across models, except 

where otherwise explicitly specified in 

a model’s governing documentation, 

would promote transparency, efficiency, 

clarity, and ensure consistency across 

models to the extent appropriate, while 

avoiding the need to restate the 

provisions in each model’s governing 

documentation. 

We also proposed a new provision 

pertaining to the reconsideration review 

process that would apply to Innovation 

Center models that waive the appeals 

processes provided under section 1869 

of the Act. 

B. General Provisions Codified in the 

Code of Federal Regulations That Would 

Apply to Innovation Center Models 

Each Innovation Center model 

features many unique aspects that must 

be memorialized in its governing 

documentation, but each model also 

includes certain provisions that are 

common to most or all models. We 

explained that we believe codifying 

these common provisions would 

facilitate their uniform application 

across models (except where the 

governing documentation for a 

particular model dictates otherwise) and 

promote program efficiency and 

consistency that would benefit CMS’ 

program administration and model 

participants. 

As such, we proposed to expand the 

applicability of the 42 CFR part 512 

subpart A ‘‘General Provisions Related 

to Innovation Center Models’’ to all 

Innovation Center models whose first 

performance periods begin on or after 

January 1, 2025, unless otherwise 

specified in the models’ governing 

documentation, and also to any 

Innovation Center models whose first 

performance periods begin prior to 

January 1, 2025 if incorporated by 

reference into the models’ governing 

documentation. To accomplish this, we 

proposed that the provisions codified at 

42 CFR part 512 subpart A for the ETC 

and RO Models, including those with 

respect to definitions, beneficiary 

protections, cooperation in model 

evaluation and monitoring, audits and 

record retention, rights in data and 

intellectual property, monitoring and 

compliance, remedial action, Innovation 

Center model termination by CMS, and 

limitations on review, would be 

designated as the newly defined 

‘‘standard provisions for Innovation 

Center models’’ and would apply to all 

Innovation Center models as described 

previously. We proposed specific 

revisions that would be necessary to 

expand the scope of several of the 

current general provisions, but 

otherwise proposed that the general 

provisions (which would be referred to 

as the ‘‘standard provisions for 

Innovation Center models’’) would not 

change. In particular, we proposed that 

the substance of the following 

provisions would not change, except 

that they would apply to all Innovation 

Center Models as opposed to just the 

ETC and RO Models: § 512.120 

Beneficiary protections; § 512.130 

Cooperation in model evaluation and 

monitoring; § 512.135 Audits and record 

retention; § 512.140 Rights in data and 

intellectual property: § 512.150 

Monitoring and compliance; § 512.160 

Remedial action; § 512.165 Innovation 

center model termination by CMS; 

§ 512.170 Limitations on review; and 

§ 512.180 Miscellaneous provisions on 

bankruptcy and other notifications. 

C. Revisions to the Titles, Basis and 

Scope Provision, and Effective Date 

We proposed to amend the title of 

part 512 to read ‘‘Standard Provisions 

for Innovation Center Models and 

Specific Provisions for the Radiation 

Oncology Model and the End Stage 

Renal Disease Model’’ so that it more 


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closely aligns with the other changes we 

proposed and to ensure that the title 

indicates that part 512 includes both 

standard provisions for Innovation 

Center models and specific provisions 

for the RO and ETC Models. We also 

proposed to amend the title of subpart 

A to read ‘‘Standard Provisions for 

Innovation Center Models’’ to use the 

term we proposed to define the 

provisions codified at 42 CFR part 512 

subpart A. 

Additionally, we proposed to amend 

§ 512.100(a) and (b) so that the standard 

provisions would take effect on January 

1, 2025, and would apply to each 

Innovation Center model where that 

model’s first performance period begins 

on or after January 1, 2025, unless the 

model’s governing documentation 

indicates otherwise, as well as any 

Innovation Center model that begins 

testing its first performance period prior 

to January 1, 2025, if the model’s 

governing documentation incorporates 

the provisions by reference in whole or 

in part. We proposed to determine on a 

case-by-case basis, based on each 

model’s unique features and design, 

whether the standard provisions would 

apply to a particular model, or whether 

we would specify alternate terms in the 

model’s governing documentation. 

We noted in the proposed rule that 

these standard provisions are necessary 

for the testing of the IOTA Model. As 

such, as an alternative to the previous 

proposal, we proposed making these 

standard provisions for Innovation 

Center models applicable to, and 

effective for, the IOTA Model beginning 

on January 1, 2025, absent extending the 

standard provisions to all Innovation 

Center models. Under such an 

alternative, the general provisions in the 

Specialty Care Models final rule would 

also still be applicable to the ETC Model 

and the RO Model. 

We specified in the proposed rule that 

these proposed standard provisions 

would not, except as specifically noted 

in section II of the proposed rule, affect 

the applicability of other provisions 

affecting providers and suppliers under 

Medicare fee-for-service (FFS). We 

invited public comment on these 

proposed changes. 

Comment: We received a comment 

that emphasized that the proposed 

standard provisions should not affect 

the applicability of other provisions 

affecting providers and suppliers under 

Medicare fee-for-service. The 

commenter believed that 

standardization of provisions across 

models would decrease administrative 

burden for providers and simplify 

understanding of complex models. 

Response: We thank the commenter 

for their comment. We agree. We are 

finalizing the proposed regulation text 

at § 512.100(b)(3) to provide that, except 

as specifically noted in subpart A of Part 

512, the standard provisions will not 

affect the applicability of other 

provisions affecting providers and 

suppliers under Medicare fee-forservice, including provisions regarding 

payment, coverage, and program 

integrity. We agree with the commenter 

that the standardization of provisions 

across models will decrease 

administrative burden and simplify 

understanding of our Innovation Center 

models. 

After consideration of the public 

comment we received, we are finalizing 

the proposed revisions to the titles for 

42 CFR part 512 and for subpart A as 

described later in this section. Further, 

we are finalizing the proposed revisions 

to the basis and scope provision at 42 

CFR 512.100 with modification to apply 

the standard provisions to mandatory 

Innovation Center models that begin 

their performance periods on or after 

January 1, 2025, rather than to both 

mandatory and voluntary Innovation 

Center models. After further 

consideration, we do not believe it is 

necessary to adopt the standard 

provisions for voluntary models because 

we can include those provisions, or 

other provisions, if necessary, in the 

models’ governing documentation. We 

also are not including in the final 

regulation text the reference to applying 

the standard provisions ‘‘unless 

otherwise specified in the Innovation 

Center model’s governing 

documentation’’ at proposed 

§ 512.100(b)(ii) because we are able to 

include the standard provisions, or 

other provisions as appropriate, in 

voluntary Innovation Center model 

participation agreements. We anticipate 

utilizing the standard provisions in 

most voluntary Innovation Center model 

participation agreements and will 

reference them or incorporate them by 

reference as appropriate. 

We also are not codifying the 

proposed regulation text at 

§ 512.100(b)(i), which provided that the 

standard provisions would apply to 

each Innovation Center model that 

began its first performance period before 

January 1, 2025, if incorporated by 

reference, in whole or in part, into the 

Innovation Center model’s governing 

documentation. If we believe it is 

appropriate to apply the standard 

provisions, in whole or in part, to an 

Innovation Center model for which the 

first performance period began before 

January 1, 2025, we will amend the 

model’s governing documentation as 

appropriate, including through notice 

and comment rulemaking if necessary. 

We are finalizing that the standard 

provisions will apply to the RO and ETC 

Models as well as all other mandatory 

Innovation Center models, including the 

IOTA model. 

We are finalizing revised titles for 42 

CFR part 512 and subpart A that refer 

to ‘‘Standard Provisions for Mandatory 

Innovation Center Models.’’ We are 

revising § 512.100(a)—‘‘Basis’’—to 

provide that the standard provisions 

apply to ‘‘certain’’ Innovation Center 

models. At § 512.100(b)—‘‘Scope’’—we 

are adding language to provide that the 

standard provisions apply to the RO 

Model, the ETC Model, and to 

Innovation Center Models ‘‘for which 

participation by Model participants is 

mandatory.’’ 

D. Provisions Revising Certain 

Definitions 

We proposed to amend the definition 

of ‘‘Innovation Center model’’ at 42 CFR 

512.110 by replacing the specific 

references to the RO and ETC Models 

with a definition consistent with section 

1115A of the Act and intended to 

encompass all Innovation Center 

models. We proposed to amend the 

definition for ‘‘Innovation Center 

model’’ to read as follows: ‘‘an 

innovative payment and service 

delivery model tested under the 

authority of section 1115A(b) of the Act, 

including a model expansion under 

section 1115A(c) of the Act.’’ 

We proposed to add a new definition 

of the term ‘‘governing documentation’’ 

at § 512.110 to mean, ‘‘the applicable 

Federal regulations, and the modelspecific participation agreement, 

cooperative agreement, and any 

addendum to an existing contract with 

CMS, that collectively specify the terms 

of the Innovation Center model.’’ We 

proposed to add a new definition, 

‘‘standard provisions for Innovation 

Center models,’’ at § 512.110 to mean 

the provisions codified in 42 CFR part 

512 subpart A. We proposed to add a 

new definition, ‘‘performance period,’’ 

at § 512.110 to mean, ‘‘the period of 

time during which an Innovation Center 

model is tested and model participants 

are held accountable for cost and quality 

of care; the performance period for each 

Innovation Center model is specified in 

the governing documentation.’’ 

Further, we proposed to amend the 

definitions of ‘‘Innovation Center model 

activities,’’ ‘‘model beneficiary,’’ and 

‘‘model participant’’ to pertain to all 

‘‘Innovation Center models,’’ as we 

proposed to define that term, instead of 

just the models previously implemented 

under part 512. As such, we proposed 


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to define ‘‘Innovation Center model 

activities’’ to mean ‘‘any activities 

affecting the care of model beneficiaries 

related to the test of the Innovation 

Center model.’’ We proposed to define 

‘‘model beneficiary’’ to mean ‘‘a 

beneficiary attributed to a model 

participant or otherwise included in an 

Innovation Center model.’’ We proposed 

to define ‘‘model participant’’ to mean 

‘‘an individual or entity that is 

identified as a participant in the 

Innovation Center model.’’ 

We invited public comment on these 

proposed changes to the definitions of 

‘‘Innovation Center model,’’ ‘‘Innovation 

Center model activities,’’ ‘‘model 

beneficiary,’’ and ‘‘model participant’’ 

and the proposed definitions of 

‘‘governing documentation,’’ ‘‘standard 

provisions for Innovation Center 

models,’’ and ‘‘performance period.’’ 

Comment: We received a comment 

that was supportive of our proposed 

definitions. 

Response: We appreciate the 

commenter’s support of our proposed 

definitions. 

After consideration of the public 

comment we received, we are finalizing 

the proposed revisions to the definitions 

at § 512.110 without modification. 

E. Proposed Reconsideration Review 

Process 

We proposed to add a new § 512.190 

to part 512 subpart A to codify a 

reconsideration review process, based 

on processes implemented under 

current Innovation Center models. The 

process would enable model 

participants to contest determinations 

made by CMS in certain Innovation 

Center models, where model 

participants would not otherwise have a 

means to dispute determinations made 

by CMS. We proposed at § 512.190(a)(1) 

that such a reconsideration process 

would apply only to Innovation Center 

models that waive section 1869 of the 

Act, which governs determinations and 

appeals in Medicare, or where section 

1869 would not apply because model 

participants are not Medicare-enrolled. 

We proposed at § 512.190(a)(2) that only 

model participants may utilize the 

dispute resolution process, unless the 

governing documentation for the 

Innovation Center model states 

otherwise. Such limitations with respect 

to such models are, we believe, 

appropriate, because with respect to 

such models, model participants do not 

have another means to dispute 

determinations made by CMS. We 

proposed to codify a reconsideration 

review process in regulation in order to 

have a transparent and consistent 

method of reconsideration for model 

participants participating in models that 

do not utilize the standard 

reconsideration process outlined in 

section 1869 of the Act. 

This proposed reconsideration review 

process would be utilized where a 

model-specific determination has been 

made and the affected model participant 

disagrees with, and wishes to challenge, 

that determination. Each Innovation 

Center model features a unique payment 

and service delivery model, and, as 

such, requires its own model-specific 

determination process. Each Innovation 

Center model’s governing 

documentation details the modelspecific determinations made by CMS, 

which may include, but are not limited 

to, model-specific payments, beneficiary 

attribution, and determinations 

regarding remedial actions. Each 

Innovation Center model’s governing 

documentation also includes specific 

details about when a determination is 

final and may be disputed through the 

model’s reconsideration review 

processes. 

We proposed at § 512.190(b) that 

model participants may request 

reconsideration of a determination made 

by CMS in accordance with an 

Innovation Center model’s governing 

documentation only if such 

reconsideration is not precluded by 

section 1115A(d)(2) of the Act, part 512 

subpart A, or the model’s governing 

documentation. A model participant 

may challenge, by requesting review by 

a CMS reconsideration official, those 

final determinations made by CMS that 

are not precluded from administrative 

or judicial review. We proposed at 

§ 512.190(b)(i) that the CMS 

reconsideration official would be 

someone who is authorized to receive 

such requests and was not involved in 

the initial determination issued by CMS 

or, if applicable, the timely error notice 

review process. We proposed at 

§ 512.190(b)(ii) that the reconsideration 

review request would be required to 

include a copy of CMS’s initial 

determination and contain a detailed 

written explanation of the basis for the 

dispute, including supporting 

documentation. We proposed at 

§ 512.190(b)(iii) that the request for 

reconsideration would have to be made 

within 30 days of the date of CMS’ 

initial determination for which 

reconsideration is being requested via 

email to an address as specified by CMS 

in the governing documentation. At 

§ 512.190(b)(2), we proposed that 

requests that do not meet the 

requirements of paragraph (b)(1) would 

be denied. 

We proposed at § 512.190(b)(3) that 

the reconsideration official would send 

a written acknowledgement to CMS and 

to the model participant requesting 

reconsideration within 10 business days 

of receiving the reconsideration request. 

The acknowledgement would set forth 

the review procedures and a schedule 

that would permit each party an 

opportunity to submit position papers 

and documentation in support of its 

position for consideration by the 

reconsideration official. 

We proposed to codify at 

§ 512.190(b)(4) that, to access the 

reconsideration process for a 

determination concerning a modelspecific payment where the Innovation 

Center model’s governing 

documentation specifies an initial 

timely error notice process, the model 

participant must first satisfy those 

requirements before submitting a 

reconsideration request under this 

process. Should a model participant fail 

to timely submit an error notice with 

respect to a particular model-specific 

payment, we proposed that the 

reconsideration review process would 

not be available to the model participant 

with regard to that model-specific 

payment. 

We proposed to codify standards for 

reconsideration at § 512.190(c). First, 

during the course of the reconsideration, 

we proposed that both CMS and the 

party requesting the reconsideration 

must continue to fulfill all 

responsibilities and obligations under 

the governing documentation during the 

course of any dispute arising under the 

governing documentation. Second, the 

reconsideration would consist of a 

review of documentation timely 

submitted to the reconsideration official 

and in accordance with the standards 

specified by the reconsideration official 

in the acknowledgement at 

§ 512.190(b)(3). Finally, we proposed 

that the model participant would bear 

the burden of proof to demonstrate with 

clear and convincing evidence to the 

reconsideration official that the 

determination made by CMS was 

inconsistent with the terms of the 

governing documentation. 

We proposed to codify at § 512.190(d) 

that the reconsideration determination 

would be an on-the-record review. By 

this, we mean a review that would be 

conducted by a CMS reconsideration 

official who is a designee of CMS who 

is authorized to receive such requests 

under proposed § 512.190(b)(1)(i), of the 

position papers and supporting 

documentation that are timely 

submitted and in accordance with the 

schedule specified under proposed 

§ 512.190(b)(3)(ii) and that meet the 

standards of submission under proposed 

§ 512.190(b)(1) as well as any 


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10Mohan, S., Chiles, M.C., Patzer, R.E., Pastan, 

S.O., Husain, S.A., Carpenter, D.J., Dube, G.K., 

Crew, R.J., Ratner, L.E., & Cohen, D.J. (2018). 

Factors leading to the discard of deceased donor 

kidneys in the United States. Kidney International, 

94(1), 187–198. https://doi.org/10.1016/ 

j.kint.2018.02.016. 

documents and data timely submitted to 

CMS by the model participant in the 

required format before CMS made the 

initial determination that is the subject 

of the reconsideration request. We 

proposed at § 512.190(d)(2) that the 

reconsideration official would issue to 

the parties a written reconsideration 

determination. Absent unusual 

circumstances, in which the 

reconsideration official would reserve 

the right to an extension upon written 

notice to the model participant, the 

reconsideration determination would be 

issued within 60 days of CMS’s receipt 

of the timely filed position papers and 

supporting documentation in 

accordance with the schedule specified 

under proposed § 512.190(b)(3)(ii). 

Under proposed § 512.190(d)(3), the 

determination made by the CMS 

reconsideration official would be final 

and binding 30 days after its issuance, 

unless the model participant or CMS 

were to timely request review of the 

reconsideration determination by the 

CMS Administrator in accordance with 

§§ 512.190(e)(1) and (2). 

We proposed to codify at § 512.190(e) 

a process for the CMS Administrator to 

review reconsideration determinations 

made under § 512.190(d). We proposed 

that either the model participant or CMS 

may request that the CMS Administrator 

review the reconsideration 

determination. The request to the CMS 

Administrator would have to be made 

via email, within 30 days of the 

reconsideration determination, to an 

email address specified by CMS. The 

request would have to include a copy of 

the reconsideration determination, as 

well as a detailed written explanation of 

why the model participant or CMS 

disagrees with the reconsideration 

determination. The CMS Administrator 

would promptly send the parties a 

written acknowledgement of receipt of 

the request for review. The CMS 

Administrator would send the parties 

notice of whether the request for review 

was granted or denied. If the request for 

review is granted, the notice would 

include the review procedures and a 

schedule that would permit each party 

to submit a brief in support of the 

party’s positions for consideration by 

the CMS Administrator. If the request 

for review is denied, the reconsideration 

determination would be final and 

binding as of the date of denial of the 

request for review by the CMS 

Administrator. If the request for review 

by the CMS Administrator is granted, 

the record for review would consist 

solely of timely submitted briefs and 

evidence contained in the record of the 

proceedings before the reconsideration 

official and evidence as set forth in the 

documents and data described in 

proposed § 512.190(d)(1)(ii); the CMS 

Administrator would not consider 

evidence other than information set 

forth in the documents and data 

described in proposed 

§ 512.190(d)(1)(ii). The CMS 

Administrator would review the record 

and issue to the parties a written 

determination that would be final and 

binding as of the date the written 

determination is sent. 

We invited public comment on the 

proposed reconsideration review 

process for Innovation Center models. 

We received no comments on this 

proposal and are finalizing this 

provision as proposed with a few 

technical changes for clarity. 

III. Increasing Organ Transplant Access 

(IOTA) Model 

A. Introduction 

In this final rule, we finalize the IOTA 

Model, a new mandatory Medicare 

alternative payment model that will be 

tested under the authority of the 

Innovation Center at section 1115A(b) of 

the Act, that will begin on July 1, 2025, 

and end on June 30, 2031. The IOTA 

Model will test whether using 

performance-based incentive payments 

in the form of upside risk payments and 

downside risk payments to and from 

transplant hospitals selected to 

participate in the model increases the 

number of kidney transplants furnished 

to patients with ESRD, thereby reducing 

Medicare expenditures while preserving 

or enhancing quality of care. 

The goal of the performance-based 

payments is to increase the number of 

kidney transplants furnished to ESRD 

patients placed on a kidney transplant 

hospital’s waitlist; encourage 

investments in value-based care and 

quality improvement activities, 

particularly those that promote an 

equitable kidney transplant process 

prior to, during, and post 

transplantation for all patients; 

encourage better use of the current 

supply of deceased donor organs and 

greater provider and community 

collaborations to address the medical 

and non-medical needs of patients; and 

increased awareness, education, and 

support for living donations. The IOTA 

Model payment structure will also 

promote IOTA participant 

accountability by linking performancebased payments to quality. We theorize 

that increasing the number of kidney 

transplants furnished to ESRD patients 

on the participating hospitals’ waitlists 

will reduce Medicare expenditures by 

reducing dialysis expenditures and 

avoidable health care service utilization 

and will improve the quality of life for 

patients with ESRD. 

As discussed in section III.B of this 

final rule, studies show that kidney 

transplant hospitals are underutilizing 

donor kidneys and have become more 

conservative in accepting organs for 

transplantation, with notable variation 

by region and across transplant 

hospitals.10 The IOTA Model aims to 

address these access and equity 

problems through financial incentives 

that reward IOTA participants that 

improve their kidney organ offer 

acceptance rate ratios over time and 

hold them financially accountable for 

not doing so. The IOTA Model’s 

payment structure includes upside and 

downside performance-based incentive 

payments (‘‘upside risk payment’’ or 

‘‘downside risk payment’’) for kidney 

transplant hospitals selected to 

participate in the IOTA Model (‘‘IOTA 

participant’’) that are tied to 

performance on achievement, efficiency, 

and quality domains. 

The achievement domain will assess 

the number of kidney transplants 

performed relative to a participantspecific target, with performance on this 

domain being worth up to 60 points. 

The efficiency domain will assess 

kidney organ offer acceptance rate ratios 

relative to a national rate for all kidney 

transplant hospitals, including those not 

selected to participate in the model, to 

20 points. or to the IOTA participant’s 

own past kidney organ offer acceptance 

rate ratio, with performance on this 

domain being worth up to 20 points. 

The quality domain will assess 

performance based on post-transplant 

outcomes, with performance on this 

domain being worth up to 20 points. 

The achievement domain will be 

weighted more heavily than the other 

two domains because increasing the 

number of transplants is a key goal of 

the model and will be a primary factor 

in determining the amount of the 

performance-based payment. 

The final performance score for each 

IOTA participant will be the sum of the 

points earned across the achievement 

domain, efficiency domain, and quality 

domain. The final performance score 

will determine whether an upside risk 

payment or downside risk payment 

would be owed and the amount of such 

payment. Specifically: 


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11Moody-Williams, J.D., & Nair, S. (2023, 

September 15). Organ Transplantation Affinity 

Group (OTAG): Strengthening accountability, 

equity, and performance | CMS. BLOG. https://

www.cms.gov/blog/organ-transplantation-affinitygroup-otag-strengthening-accountability-equityand-performance. 

12Penn Medicine News. (2020, December 16). 

Too Many Donor Kidneys Are Discarded in U.S. 

Before Transplantation—Penn Medicine. (2020, 

December 16). www.pennmedicine.org. https://

www.pennmedicine.org/news/news-releases/2020/ 

december/too-many-donor-kidneys-are-discardedin-us-before-transplantation 

www.pennmedicine.org. 

13Hariharan, S., Israni, A.K., & Danovitch, G. 

(2021). Long-Term Survival after Kidney 

Transplantation. New England Journal of Medicine, 

385(8), 729–743. https://doi.org/10.1056/ 

nejmra2014530. 

14Stewart, D.E., Garcia, V.C., Rosendale, J.D., 

Klassen, D.K., & Carrico, B.J. (2017). Diagnosing the 

Decades-Long Rise in the Deceased Donor Kidney 

Discard Rate in the United States. Transplantation, 

101(3), 575–587. https://doi.org/10.1097/ 

tp.0000000000001539. 

15Mohan, S., Chiles, M.C., Patzer, R.E., Pastan, 

S.O., Husain, S.A., Carpenter, D.J., Dube, G.K., 

Crew, R.J., Ratner, L.E., & Cohen, D.J. (2018). 

Factors leading to the discard of deceased donor 

kidneys in the United States. Kidney International, 

94(1), 187–198. https://doi.org/10.1016/ 

j.kint.2018.02.016. 

16Moody-Williams, J.D., & Nair, S. (2023, 

September 15). Organ Transplantation Affinity 

Group (OTAG): Strengthening accountability, 

equity, and performance | CMS. BLOG. https://

www.cms.gov/blog/organ-transplantation-affinitygroup-otag-strengthening-accountability-equityand-performance. 

• For PY 1, if an IOTA participant has 

a final performance score between 60 

and 100 points, it would qualify for the 

upside risk payment in accordance with 

the proposed calculation methodology 

described in section III.C.6.c.(2)(a) of 

this final rule (final performance score 

minus 60, then divided by 40, then 

multiplied by $15,000, then multiplied 

by the number of kidney transplants 

furnished by the IOTA participant to 

beneficiaries with Medicare FFS as a 

primary or secondary payer during the 

PY). 

• For PY 1, if an IOTA participant has 

a final performance score below 60, it 

would fall into a neutral zone where no 

upside risk payment and no downside 

risk payment would apply. 

• For PY 2 and each subsequent PY 

(PYs 2–6), if an IOTA participant 

achieves a final performance score of 41 

to 59 points, it would fall into a neutral 

zone where no upside risk payment and 

no downside risk payment would apply. 

• For PY 2 and each subsequent PY, 

if an IOTA participant achieves a final 

performance score of 40 points or 

below, it would be subject to the 

downside risk payment in accordance 

with the calculation methodology 

described in section III.C.6.c.(2)(b) of 

this final rule (40 minus final 

performance score, then divided by 40, 

then multiplied by $2,000, then 

multiplied by the number of kidney 

transplants furnished by the IOTA 

participant to beneficiaries with 

Medicare FFS as a primary or secondary 

payer during the PY). 

We recognize the complexity of the 

transplant ecosystem, which requires 

coordination between transplant 

hospitals, other health care providers, 

organ procurement organizations 

(OPOs), patients, potential donors, and 

their families. The IOTA Model does not 

prescribe or require specific processes 

or policy approaches that each selected 

IOTA participant must implement for 

purposes of the model test. 

We believe the IOTA Model will 

complement other efforts in relation to 

the transplant ecosystem to enhance 

health and safety outcomes, increase 

transparency, increase the number of 

transplants, and reduce disparities. We 

also believe that the payment 

methodology will act in concert with 

efforts that are currently under 

development by HRSA to increase the 

numbers of both deceased and living 

donor organ transplants. 

This model falls within a larger 

framework of activities initiated by the 

Federal Government during the past 

several years and planned for the 

upcoming year to enhance the donation, 

procurement, and transplantation of 

solid organs. This Federal collaborative, 

called the Organ Transplantation 

Affinity Group (OTAG), is a coordinated 

group working together to strengthen 

accountability, equity, and performance 

in organ donation, procurement, and 

transplantation.11

B. Background 

A review of the literature on kidney 

transplantation shows that the 

increasing numbers of kidney 

transplants is unable to keep pace with 

the increasing need for organs and is 

discussed in section III.B.3.d of this 

final rule.12 While more people die 

waiting for a kidney transplant, the 

short- and long-term outcomes of 

patients who undergo kidney 

transplantation have improved, despite 

both recipients and donors increasing in 

age and adverse health conditions.13

Recent studies show that transplant 

hospitals have become more 

conservative in accepting organs for 

transplantation when offered for 

specific patients, avoiding the use of 

less-than-ideal organs on account of 

perceived risk.14 Wide variation among 

geographic regions and transplant 

hospitals in rates of kidney 

transplantation, along with access and 

equity issues, raises the need to hold 

kidney transplant hospitals accountable 

for performance.15 The IOTA Model 

includes a two-sided performance-based 

payment structure that rewards IOTA 

participants for high performance in the 

achievement, efficiency, and quality 

domains, and imposes financial 

accountability on IOTA participants that 

perform poorly on those domains. We 

proposed the IOTA Model as a 

complement to wider efforts aimed at 

transplant ecosystem performance and 

equity improvements as discussed in 

section III.B of the proposed rule. 

Ultimately, we seek a set of 

interventions that focus on ESRD 

patients in need of a kidney transplant. 

In section III.B of the proposed rule, we 

summarized the transplant ecosystem 

and HHS oversight within CMS and 

HRSA related to kidney transplantation, 

highlight related initiatives and 

priorities nationally, and outlined our 

rationale for the proposed IOTA Model 

informed by literature, data, and 

studies. 

1. The Transplant Ecosystem 

Kidney transplantation occurs within 

an overall organ donation and 

transplantation system (also known and 

referred to as the transplant ecosystem) 

that comprises a vast network of 

institutions dedicated to ensuring that 

patients are evaluated and, if 

appropriate, placed onto the organ 

transplant waitlist, and that those on the 

organ transplant waitlist receive 

lifesaving organ transplants. 

Transplantation of livers, hearts, lungs, 

and other organs is also well established 

within the U.S. health care system. The 

transplant ecosystem includes the Organ 

Procurement and Transplantation 

Network (OPTN); Organ Procurement 

Organizations (OPOs); transplant 

hospitals and providers; 

histocompatibility laboratories that 

provide blood, tissue, and antibody 

testing for the organ matching process; 

and patients, including ESRD patients 

in need of a transplant, their families, 

and caregivers.16 For kidney 

transplantation, it also includes ESRD 

facilities, commonly known as dialysis 

facilities. 

The National Organ Transplant Act of 

1984, referred to herein as NOTA, 

established the OPTN, with HHS 

oversight, to manage and operate the 

national organ transplantation system 

(42 U.S.C. 274). The OPTN is a network 

that coordinates the nation’s organ 

procurement, distribution, and 

transplantation systems. 

Organ Procurement Organizations 

(OPOs) are non-profit organizations 

operating under contract with the 

Federal Government that are charged, 

under section 371(b) of the Public 


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17 Virmani, S., & Asch, W.S. (2020). The Role of 

the General Nephrologist in Evaluating Patients for 

Kidney Transplantation: Core Curriculum 2020. 

American Journal of Kidney Diseases, 76, 567–579. 

https://doi.org/10.1053/j.ajkd.2020.01.001. 

18Chadban, S.J., Ahn, C., Axelrod, D.A., Foster, 

B.J., Kasiske, B.L., Kher, V., Kumar, D., Oberbauer, 

R., Pascual, J., Pilmore, H.L., Rodrigue, J.R., Segev, 

D.L., Sheerin, N.S., Tinckam, K.J., Wong, G., & 

Knoll, G.A. (2020). KDIGO Clinical Practice 

Guideline on the Evaluation and Management of 

Candidates for Kidney Transplantation. 

Transplantation, 104(4S1), S11. https://doi.org/ 

10.1097/TP.0000000000003136. 

19National kidney Foundation. (2017, February 

10). The Kidney Transplant Waitlist—What You 

Need to Know. National Kidney Foundation. 

https://www.kidney.org/atoz/content/transplantwaitlist. 

20The kidney transplant waitlist. (n.d.). 

Transplant Living. https://transplantliving.org/ 

kidney/the-kidney-transplant-waitlist/. 

21National kidney Foundation. (2019, June 12). 

Understanding the transplant waitlist. National 

Kidney Foundation. https://www.kidney.org/ 

content/understanding-transplant-waitlist. 

22National kidney Foundation. (2016, August 4). 

Multiple Listing for Kidney Transplant. National 

Kidney Foundation. https://www.kidney.org/atoz/ 

content/multiple-listing. 

23Transplant Nephrology Fellowship. (n.d.). 

www.hopkinsmedicine.org. Retrieved May 30, 2023, 

from https://www.hopkinsmedicine.org/nephrology/ 

education/transplant-fellowship. 

24On March 22, 2023, HRSA announced an 

initiative that included several actions to strengthen 

accountability and transparency in the OPTN. 

These actions include modernization of the OPTN 

information technology system. 

Health Service Act (PHS Act, 42 U.S.C. 

273(b)) with activities including, but not 

limited to, identifying potential organ 

donors, providing for the acquisition 

and preservation of donated organs, the 

equitable allocation of donated organs, 

and the transportation of donated organs 

to transplant hospitals. Section 371(b) of 

the Public Health Services Act requires 

that an OPO must have a defined service 

area, a concept that is defined at 42 CFR 

part 486 subpart G as the Donation 

Service Area (DSA). Section 1138(b) of 

the Act states that the Secretary may not 

designate more than one OPO to serve 

each DSA. There are currently 56 OPOs 

that serve the United States and Puerto 

Rico. 

Section 1138(b) of the Act lays out the 

requirements that an OPO must meet for 

organ acquisition costs to be payable 

under Title XVIII and Title XIX. 

Separately, CMS sets out the 

components of allowable Medicare 

organ acquisition costs at 42 CFR 

413.402(b). Allowable organ acquisition 

costs are those costs incurred in the 

acquisition of organs intended for 

transplant, and include, but are not 

limited to: costs associated with special 

care services, the surgeon’s fee for 

excising the deceased donor organ from 

the donor patient (limited to $1,250 for 

kidneys), operating room and other 

inpatient ancillary services provided to 

the living or deceased donor, organ 

preservation and perfusion costs, and 

donor and beneficiary evaluation. OPOs 

and transplant hospitals may incur 

organ acquisition costs and include 

these and some additional 

administrative and general costs on the 

Medicare cost report. 

The CMS conditions for coverage for 

OPOs at 42 CFR 486.322 require an OPO 

to have written agreements with 95 

percent of the Medicare and Medicaid 

certified hospitals and critical access 

hospitals in its DSA that have a 

ventilator and an operating room and 

have not been granted a waiver to work 

with another OPO. These hospitals, 

known as donor hospitals, are required 

by the CMS conditions of participation 

for hospitals at 42 CFR 482.45 to have 

an agreement with an OPO under which 

the donor hospital must notify the OPO 

of patients who are expected to die 

imminently and of patients who have 

died in the hospital. (Under the hospital 

conditions of participation, such an 

agreement is required of all hospitals 

that participate in Medicare.) Also, 

under the hospital conditions of 

participation, donor hospitals are 

responsible for informing donor patient 

families of the option to donate organs, 

tissues, and eyes, or to decline to 

donate; and to work collaboratively with 

the OPO to educate hospital staff on 

donation, improve its identification of 

potential donors, and work with the 

OPO to manage the potential donor 

patient while testing and placement of 

the potential donor organ occurs. 

At 42 CFR 482.70, CMS defines a 

transplant hospital as ‘‘a hospital that 

furnishes organ transplants and other 

medical and surgical specialty services 

required for the care of transplant 

patients,’’ and a transplant program as 

‘‘an organ-specific transplant program 

within a transplant hospital,’’ as so 

defined. In accordance with 42 CFR 

482.98(b), a transplant program must 

have a primary transplant surgeon and 

a transplant physician with the 

appropriate training and experience to 

provide transplantation services, who 

are immediately available to provide 

transplantation services when an organ 

is offered for transplantation. The 

transplant surgeon is responsible for 

providing surgical services related to 

transplantation, and the transplant 

physician is responsible for providing 

and coordinating transplantation care. 

In accordance with CMS’ Conditions 

for Coverage (CfC) for ESRD Facilities at 

42 CFR part 494, ESRD facilities are 

charged with delivering safe and 

adequate dialysis to ESRD patients, and, 

among other requirements, informing 

patients of their treatment modalities, 

including dialysis and kidney 

transplantation. The CfCs require ESRD 

facilities to conduct a patient 

assessment that includes evaluation of 

suitability for referral for 

transplantation, based on criteria 

developed by the prospective 

transplantation center and its 

surgeon(s). General nephrologists refer 

patients for evaluation for kidney 

transplants.17 Candidates for kidney 

transplant undergo a rigorous evaluation 

by a transplant program prior to 

placement on a waitlist, involving 

evaluation by a multidisciplinary team 

for conditions pertaining to the 

potential success of the transplant, the 

possibility of recurrence, and surgical 

issues including frailty, obesity, 

diabetes and other causes of ESRD, 

infections, malignancies, cardiac 

disease, pulmonary disease, peripheral 

arterial disease, neurologic disease, 

hematologic conditions, and 

gastrointestinal and liver disease and an 

immunological assessment; a 

psychosocial assessment; assessment of 

adherence behaviors; and tobacco 

counseling.18

Once placed on the waitlist, potential 

recipients must maintain active status to 

be eligible to receive a deceased donor 

transplant.19 An individual may receive 

a status of ‘inactive’ if they are missing 

lab results, contact information, or any 

of the other requirements that would be 

necessary for them to receive an organ 

transplant if offered. An individual may 

only receive an organ offer if they have 

a status of ‘active.’ 20 Each transplant 

hospital has its own waitlist, and 

patients can attempt to be placed on 

multiple waitlists; OPTN maintains a 

national transplant waiting list that 

encompasses the waitlists for all kidney 

transplant hospitals.21 22 Individuals 

already on dialysis continue to receive 

regular dialysis treatments while 

waiting for an organ to become 

available. After surgery, a transplant 

nephrologist manages the possible 

outcomes of organ rejection and 

infection, and other medical 

complications.23

2. HHS Oversight and Priorities 

HRSA, which oversees the OPTN, and 

CMS play a vital role in protecting the 

health and safety of Americans as they 

engage with the U.S. health care 

system.24 The OPTN operates a complex 

network of computerized interactions 

whereby specific deceased donor organs 

get matched to individual patients on 

the national transplant waiting list. The 

Scientific Registry of Transplant 

Recipients (SRTR), operated under 


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25 Mission, Vision, and Values. (n.d.). 

www.srtr.org. https://www.srtr.org/about-srtr/ 

mission-vision-and-values/. 

26U.S. Congress. (1934) United States Code: 

Social Security Act, 42 U.S.C. 301–Suppl. 4 1934. 

27Bylaws–OPTN. (n.d.). 

Optn.transplant.hrsa.gov. Retrieved September 13, 

2024, from https://optn.transplant.hrsa.gov/media/ 

lgbbmahi/optn_bylaws.pdf. 

28The Organ Procurement Organizations Annual 

Public Aggregated Performance Report for 2023 is 

available at https://www.cms.gov/files/document/ 

opo-annual-public-performance-report-2023.pdf. 

29One study—Doby, B. One study—Doby, B. One 

study—Doby, B. One study showed that deceased 

donor organ donation increased during 2019, 

during the period of public debate about regulating 

OPO performance. See Doby, B.L., Ross-Driscoll, K., 

Shuck, M., Wadsworth, M., Durand, C.M., & Lynch, 

R.J. (2021). Public discourse and policy change: 

Absence of harm from increased oversight and 

transparency in OPO Performance. American 

Journal of Transplantation, 21(8), 2646–2652. 

https://doi.org/10.1111/ajt.16527. 

30 In addition, CMS finalized a policy in the final 

rule for FY 2023 for the Medicare Physician Fee 

Schedule that Medicare Part A and Part B payment 

can be made for dental or oral examinations, 

including necessary treatment, performed as part of 

a necessary workup prior to organ transplant 

surgery. In the final rule, CMS describes certain 

dental services as inextricably linked and integral 

to the clinical success of organ transplantation. (87 

FR 69671–69675). 

contract with HRSA, is responsible for 

providing statistical and analytic 

support to the OPTN. Section 373 of the 

PHS Act requires the operation of the 

SRTR to support ongoing evaluation of 

the scientific and clinical status of solid 

organ transplantation.25

CMS oversees and evaluates OPO 

performance. OPOs must meet 

performance measures and participate 

in, and abide by certain rules of, the 

OPTN.26 The PHS Act requires the 

Secretary to establish outcome and 

process performance measures to 

recertify OPOs (Part H section 371; 42 

U.S.C. 273). CMS has promulgated the 

OPO CfCs at 42 CFR part 486 subpart G. 

Additionally, OPTN policies specify 

that OPOs whose observed organ yield 

rates fall below the expected rates by 

more than a specified threshold would 

be reviewed by the OPTN Membership 

Professional Standards Committee 

(MPSC).27 CMS also conducts oversight 

of transplant programs, located within 

transplant hospitals, which must abide 

by both the hospital and the transplant 

program conditions of participation 

(CoPs). CMS contracts with quality 

improvement entities such as the ESRD 

Networks and Quality Improvement 

Organizations to provide technical 

support to providers and patients 

seeking improvements in the transplant 

ecosystem. 

Medicare covers certain transplantrelated services when provided at a 

Medicare-approved facility. Medicare 

Part A covers the costs associated with 

a Medicare kidney transplant procedure 

received in a Medicare-certified hospital 

and any additional inpatient hospital 

care needed following the procedure, 

and kidney acquisition costs including 

kidney registry fees, surgeons’ fees for 

excising a kidney for transplant, and 

laboratory tests associated with the 

evaluation of a Medicare transplant 

candidate. The evaluation or 

preparation of a living kidney donor, the 

living donor’s donation of the kidney, 

and postoperative recovery services 

directly related to the living donor’s 

kidney donation are covered under 

Medicare. In addition, deductible and 

coinsurance requirements do not apply 

to living donors for services furnished to 

an individual in connection with the 

donation of a kidney for transplant 

surgery for a Medicare beneficiary. 

Medicare Part B coverage includes the 

surgeon’s fees for performing the kidney 

transplant procedure and perioperative 

care. Medicare Part B also covers 

physician services for the living kidney 

donor without regard to whether the 

service would otherwise be covered by 

Medicare. Part A and Part B share 

responsibility for covering blood, 

including packed red blood cells, blood 

components and the cost of processing 

and receiving blood. 

Medicare Part B covers 

immunosuppressive drugs following an 

organ transplant for which payment is 

made under Title XVIII. 

Immunosuppressive drugs following an 

organ transplant are covered by Part D 

when an individual did not have Part A 

at the time of the transplant. 

Beneficiaries who have Medicare due to 

ESRD alone lose Medicare coverage 36 

months following a successful kidney 

transplant. Section 402(a) of the 

Consolidated Appropriations Act (CAA) 

of 2021 added section 1836(b) of the Act 

to provide coverage for 

immunosuppressive drugs beginning 

January 1, 2023, for eligible individuals 

whose eligibility for Medicare based on 

ESRD ends by reason of section 

226A(b)(2) of the Act for those threeyears post kidney transplant. Under 

section 1833 of the Act, the amounts 

paid by Medicare for 

immunosuppressive drugs are equal to 

80 percent of the applicable payment 

amount; beneficiaries are thus subject to 

a 20 percent coinsurance for 

immunosuppressive drugs covered by 

both Part B and the Medicare Part B 

Immunosuppressive Drug Benefit (Part 

B–ID). 

3. Federal Government Initiatives To 

Enhance Organ Transplantation 

a. CMS Regulatory Initiatives To 

Enhance Organ Transplantation 

On September 30, 2019, we published 

the final rule, ‘‘Medicare and Medicaid 

Programs; Regulatory Provisions To 

Promote Program Efficiency, 

Transparency, and Burden Reduction; 

Fire Safety Requirements for Certain 

Dialysis Facilities; Hospital and Critical 

Access Hospital (CAH) Changes To 

Promote Innovation, Flexibility, and 

Improvement in Patient Care’’ (84 FR 

51732). The rulemaking, in part, aimed 

to address the concern that too many 

organs are being discarded that could be 

transplanted successfully, including 

hearts, lungs, livers, and kidneys. This 

rule implemented changes to the 

transplant program regulations, 

eliminating requirements for reapproval of transplant programs 

pertaining to data submission, clinical 

experience, and outcomes. We believed 

that the removal of these requirements 

aligned with our goal of increasing 

access to kidney transplants by 

increasing the utilization of organs from 

deceased donors and reducing the organ 

discard rate (84 FR 51732). We sought 

improved organ procurement, greater 

organ utilization, and reduction of 

burden for transplant hospitals, while 

still maintaining the importance of 

safety in the transplant process. 

On December 2, 2020, we issued a 

final rule titled, ‘‘Medicare and 

Medicaid Programs; Organ Procurement 

Organizations Conditions for Coverage: 

Revisions to the Outcome Measure 

Requirements for Organ Procurement 

Organizations’’ (85 FR 77898), which 

revised the OPO CfCs by replacing the 

previous outcome measures with new 

transparent, reliable, and objective 

outcome measures. In modifying the 

metrics used for assessing OPO 

performance, we sought to promote 

greater utilization of organs that might 

not otherwise be recovered or used due 

to perceived organ quality.28

While these regulatory changes went 

into effect with the goal of improving 

the performance of transplant hospitals 

and OPOs and to promote the procuring 

of organs and delivering them to 

prospective transplant recipients, we 

acknowledged the need for 

improvements in health, safety, and 

outcomes across the transplant 

ecosystem, including in transplant 

programs, OPOs, and ESRD 

facilities.29 30 In particular, we recognize 

that further action must be taken to 

address health disparities and lower 

rates of transplantation for underserved 

populations observed across transplant 

hospitals. 

We published a request for 

information in the Federal Register on 


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31The results of the CMS-sponsored evaluation of 

the CEC Model are available at https://

innovation.cms.gov/innovation-models/ 

comprehensive-esrd-care. The 5-year model test 

reduced Medicare expenses by $217 million, or 1.3 

percent relative to the pre-CEC period. These results 

do not account for shared savings payments to the 

model participants. There was a 3 percent decrease 

in the number of hospitalizations and a 0.4 percent 

increase in the number of outpatient dialysis 

sessions for Medicare beneficiaries in CEC 

compared to non-CEC beneficiaries. In addition, the 

CEC Model improved key quality outcomes. 

December 3, 2021, titled ‘‘Request for 

Information: Health and Safety 

Requirements for Transplant Programs, 

Organ Procurement Organizations, and 

End-Stage Renal Facilities’’ (86 FR 

68594) (hereafter known as the 

‘‘Transplant Ecosystem RFI’’). This RFI 

solicited public comments on potential 

changes to the requirements that 

transplant programs, OPOs, and ESRD 

facilities must meet to participate in the 

Medicare and Medicaid programs. 

Specifically, we solicited public 

comments on ways to: 

• Continue to improve systems of 

care for all patients in need of a 

transplant; 

• Increase the number of organs 

available for transplant for all solid 

organ types; 

• Encourage the use of dialysis in 

alternate settings or modalities over incenter hemodialysis where clinically 

appropriate and advantageous; 

• Ensure that the CMS and HHS 

policies appropriately incentivize the 

creation and use of future new 

treatments and technologies; and 

• Harmonize requirements across 

government agencies to facilitate these 

objectives and improve quality across 

the organ donation and transplantation 

ecosystem. 

We also solicited information related 

to opportunities, inefficiencies, and 

inequities in the transplant ecosystem 

and what can be done to ensure all 

segments of our healthcare systems are 

invested and accountable in ensuring 

improvements to organ donation and 

transplantation rates (86 FR 68596). The 

Transplant Ecosystem RFI focused on 

questions in the areas of transplantation, 

kidney health and ESRD facilities, and 

OPOs. For transplant programs, specific 

topics included transplant program 

CoPs, patient rights, and equity in organ 

transplantation and organ donation (86 

FR 68596). For kidney health and ESRD 

facilities, topics included maintaining 

and improving health of patients, ways 

to identify those at risk of developing 

chronic kidney disease (CKD), 

improving detection rates of CKD, and 

ways to close the CKD detection, 

education, and care health equity gap 

(86 FR 68599). Other topics included 

home dialysis, dialysis in alternative 

settings such as nursing homes and 

mobile dialysis, and alternate models of 

care (86 FR 68600). For OPOs, specific 

topics included assessment and 

recertification, organ transport and 

tracking, the donor referral process, 

organ recovery centers, organ discards, 

donation after cardiac death, tissue 

banks, organs for research, and vascular 

composite organs. (86 FR 68601 through 

68606). 

The Transplant Ecosystem RFI 

followed three executive orders 

addressing health equity that were 

issued by President Biden on January 20 

and January 21, 2021— 

• Executive Order on Advancing 

Racial Equity and Support for 

Underserved Communities Through the 

Federal Government (E.O. 13985, 86 FR 

7009, January 20, 2021); 

• Executive Order on Preventing and 

Combating Discrimination on the Basis 

of Gender Identity or Sexual Orientation 

(E.O. 13988, 86 FR 7023, January 25, 

2021); and 

• Executive Order on Ensuring an 

Equitable Pandemic Response and 

Recovery (E.O. 13995, 86 FR 7193, 

January 26, 2021). 

The RFI was among several issued by 

CMS in 2021 to request public comment 

on ways to advance health equity and 

reduce disparities in our policies and 

programs. 

CMS’s regulatory initiatives since 

2018 pertaining to organ donation and 

transplantation have included final 

rules modifying CoPs and CfCs for 

transplant programs (84 FR 51732) and 

OPOs (85 FR 77898), respectively, and 

our recent RFI on transplant program 

CoPs, OPO CfCs, and the ESRD facility 

CfCs (86 FR 68594). These regulations 

and RFIs have sought to foster greater 

health and safety for patients, greater 

transparency for all patients, increases 

in organ donation and transplantation, 

and reduced disparities in organ 

donation and transplantation. Through 

these regulations, we are working to 

attain these goals by designing and 

implementing policies that improve 

health for all people affected by the 

transplant ecosystem. 

b. CMS Innovation Center Payment 

Models 

The Innovation Center is currently 

pursuing complementary alternative 

payment model tests—the ESRD 

Treatment Choices (ETC) Model and the 

Kidney Care Choices (KCC) Model— 

aimed at enhancing kidney 

transplantation and improving healthrelated outcomes for patients with latestage CKD and ESRD, thereby reducing 

costs to the Medicare program. The 

impetus for the ETC and KCC Models 

originated with evaluation findings for 

the earlier Comprehensive ESRD Care 

(CEC) Model, which ran from October 

2015 through March 2021, that showed 

large dialysis organizations achieving 

positive clinical and financial outcomes 

relating to services to Medicare 

beneficiaries receiving dialysis, though 

the CEC Model did not achieve net 

savings to Medicare.31 The CEC Model 

focused on patients being treated in 

ESRD facilities, with no explicit 

incentives to encourage increases in 

kidney transplantation. 

The ETC and KCC Models have 

engaged a broader range of health care 

providers beyond ESRD facilities, 

including nephrology professionals and 

transplant providers, and address 

transplantation. Each model includes 

direct financial incentives for increasing 

the number of kidney transplants. 

The ETC Model, which began January 

1, 2021, and which is scheduled to end 

on June 30, 2027, is a mandatory model 

that tests whether greater use of home 

dialysis and kidney transplantation for 

Medicare beneficiaries with ESRD 

reduces Medicare expenditures while 

preserving or enhancing the quality of 

care furnished to those beneficiaries. We 

established requirements for the ETC 

Model in the Medicare Program; 

Specialty Care Models to Improve 

Quality of Care and Reduce 

Expenditures final rule (85 FR 61114 

through 61381). These requirements are 

codified at 42 CFR subpart C. The ETC 

Model tests the effects of certain 

Medicare payment adjustments to 

participating ESRD facilities and 

Managing Clinicians (clinicians who 

manage ESRD beneficiaries and bill the 

Monthly Capitation Payment (MCP)). 

The payment adjustments are 

designed to encourage greater utilization 

of home dialysis and kidney 

transplantation, support beneficiary 

modality choice, reduce Medicare 

expenditures, and preserve or enhance 

quality of care. Under the ETC Model, 

CMS makes upward adjustments to 

certain payments under the ESRD 

Prospective Payment System (PPS) to 

certain dialysis facilities on home 

dialysis claims, and upward 

adjustments to the MCP paid to certain 

Managing Clinicians on home dialysisrelated claims (85 FR 61117). In 

addition, CMS makes upward and 

downward adjustments to PPS 

payments to participating ESRD 

facilities and to the MCP paid to 

participating Managing Clinicians based 

on the Participant’s home dialysis rate 

and transplant waitlisting and living 


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32Centers for Medicare & Medicaid Services. 

https://innovation.cms.gov/innovation-models/ 

esrd-treatment-choices-model. 

33The evaluation report for the first two years 

(2021, 2022) of the ETC Model is available at 

https://www.cms.gov/priorities/innovation/ 

innovation-models/esrd-treatment-choices-model 

and the evaluation report for the first year (2022) 

of the KCC Model is available at https://

www.cms.gov/priorities/innovation/innovationmodels/kidney-care-choices-kcc-model. 

34HRSA Announces Organ Procurement and 

Transplantation Network Modernization Initiative | 

HRSA. (n.d.). www.hrsa.gov. Retrieved August 20, 

2023, from https://www.hrsa.gov/optnmodernization/march-2023. 

35The White House. (2023, September 22). Bill 

Signed: H.R. 2544. The White House. https://

www.whitehouse.gov/briefing-room/legislation/ 

2023/09/22/bill-signed-h-r-2544/. 

36OPTN. (n.d.). Bylaws. Retrieved September 15, 

2024 from https://optn.transplant.hrsa.gov/media/ 

lgbbmahi/optn_bylaws.pdf. 

donor transplant rate (85 FR 61117). The 

ETC Model’s objectives, as described in 

the final rule, include supporting paired 

donations and donor chains, and 

reducing the likelihood that potentially 

viable organs are discarded (85 FR 

61128). The ETC Model was updated by 

the final rule dated November 8, 2021, 

titled ‘‘Medicare Program; End-Stage 

Renal Disease Prospective Payment 

System, Payment for Renal Dialysis 

Services Furnished to Individuals With 

Acute Kidney Injury, End-Stage Renal 

Disease Quality Incentive Program, and 

End-Stage Renal Disease Treatment 

Choices Model’’ and the final rule dated 

November 7, 2022, titled ‘‘Medicare 

Program; End-Stage Renal Disease 

Prospective Payment System, Payment 

for Renal Dialysis Services Furnished to 

Individuals With Acute Kidney Injury, 

End-Stage Renal Disease Quality 

Incentive Program, and End-Stage Renal 

Disease Treatment Choices Model’’ (87 

FR 67136). We finalized further 

modifications to the ETC Model related 

to the availability of administrative 

review of an ETC Participant’s targeted 

review request in the final rule issued 

on November 6, 2023, titled ‘‘Medicare 

Program; End-Stage Renal Disease 

Prospective Payment System, Payment 

for Renal Dialysis Services Furnished to 

Individuals With Acute Kidney Injury, 

End-Stage Renal Disease Quality 

Incentive Program, and End-Stage Renal 

Disease Treatment Choices Model’’ (88 

FR 76345). As of the second model 

evaluation report covering the first two 

years of the model, the model has not 

shown statistically significant results as 

home dialysis grew similarly across ETC 

areas and the comparison group and no 

statistically significant differences in 

waitlisting and living donor transplant 

rates. As noted earlier, CMS will 

continue to evaluate the effectiveness of 

the ETC Model. 

CMS is also operating the ETC 

Learning Collaborative, which is 

focused on increasing the availability of 

deceased donor organs for 

transplantation.32 The ETC Learning 

Collaborative regularly convenes ETC 

Participants, transplant hospitals, OPOs, 

and large donor hospitals, with the goal 

of using learning and quality 

improvement techniques to 

systematically spread the best practices 

of the highest performing organizations. 

CMS is employing quality improvement 

approaches to improve performance by 

collecting and analyzing data to identify 

the highest performers, and to help 

others to test, adapt and spread the best 

practices of these high performers 

throughout the entire national organ 

recovery system (85 FR 61346). 

The KCC Model, which began its 

performance period on January 1, 2022, 

and is scheduled to end on December 

31, 2026, is a voluntary model that also 

builds upon the CEC Model structure to 

encourage health care providers to 

better manage the care for Medicare 

beneficiaries with CKD stages 4 and 5 

and ESRD, delay the onset of dialysis, 

and incentivize kidney transplantation. 

Various entities are participating in the 

KCC Model, including nephrologists 

and nephrology practices, dialysis 

facilities, and other health care 

providers. The participating entities 

receive a bonus payment for each 

aligned beneficiary who receives a 

kidney transplant, so long as the 

transplant remains successful over a 

certain time period. CMS plans to 

continue to evaluate the effectiveness of 

the ETC and KCC Models in achieving 

clinical goals, improving quality of care, 

and reducing Medicare costs.33

The IOTA Model will complement the 

ETC and KCC Models and expand 

kidney model participation to hospitals, 

which are a key player in the transplant 

ecosystem, to test whether two-sided 

risk payments based on performance 

increase access to kidney transplants for 

ESRD patients placed on the waitlists of 

participating transplant hospitals. 

c. HRSA Initiatives Involving Kidney 

Transplants 

NOTA established the OPTN almost 

40 years ago to coordinate and operate 

the nation’s organ procurement, 

allocation, and transplantation system. 

There are about 400 member 

organizations that comprise the OPTN. 

Section 372(b)(2)(A) of the PHS Act 

charges the OPTN with establishing a 

national list of individuals who need 

organs and a national computer system 

to match organs with individuals on the 

waitlist. HRSA has also undertaken 

efforts in alignment with CMS efforts 

and Federal Government initiatives to 

improve accountability in OPTN 

functions. On March 22, 2023, HRSA 

launched the OPTN Modernization 

Initiative to strengthen accountability, 

equity, and performance in the organ 

donation and transplantation system 

through a focus on five key areas: 

technology, data transparency, 

governance, operations, and quality 

improvement and innovation.34 The 

OPTN Modernization Initiative was 

further supported by the Securing the 

U.S. Organ Procurement and 

Transplantation Network Act (Pub. L. 

118–14), which included several key 

provisions proposed in the President’s 

Fiscal Year 2024 Budget and was signed 

into law on September 22, 2023.35 The 

new law expressly authorizes HHS to 

make multiple awards to different 

entities, which could enable the OPTN 

to benefit from best-in-class vendors and 

provide a more efficient system that 

strengthens oversight and improves 

patient safety. 

Effective July 14, 2022, revisions to 

OPTN policies were made related to the 

Transplant Program Performance to 

establish new criteria for identification 

of transplant programs that enter MPSC 

performance review based on the 

following criteria: 36

• The transplant program’s 90-day 

post-transplant graft survival hazard 

ratio is greater than 1.75 during the 2.5- 

year time period; or 

• The transplant program’s 1-year 

post-transplant graft survival 

conditional on 90-day post-transplant 

graft survival hazard ratio is greater than 

1.75 during a 2.5-year period. 

Transplant programs that meet either 

of the criteria, as reported by the SRTR, 

must participate in the OPTN 

Membership and Professional Standards 

Committee (MPSC) performance review, 

which may require the member to take 

appropriate actions to determine if the 

transplant program has demonstrated 

sustainable improvement, including, but 

not limited to— 

• Providing information about the 

program structure, procedures, 

protocols and quality; 

• Review processes; 

• Adopting and implementing a plan 

for improvement; 

• Participating in an informal 

discussion with MPSC members; and 

• Participating in a peer visit. 

The MPSC would continue to review 

the transplant program under the 

performance review until the MPSC 

determines that the transplant program 

has made sufficient and sustainable 

improvements to avoid risk to public 


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Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96293 

37Moody-Williams, J.D., & Nair, S. (2023, 

December 13). Organ Transplantation Affinity 

Group (OTAG): Strengthening accountability, 

equity, and performance | CMS. BLOG. https://

www.cms.gov/blog/organ-transplantation-affinitygroup-otag-strengthening-accountability-equityand-performance. 

38Moody-Williams, J.D., & Nair, S. (2023, 

December 13). Organ Transplantation Affinity 

Group (OTAG): Strengthening accountability, 

equity, and performance | CMS. BLOG. https://

www.cms.gov/blog/organ-transplantation-affinitygroup-otag-strengthening-accountability-equityand-performance. 

39Pre-transplant/referral practices are inclusive of 

the referring physician’s assessment criteria, patient 

education, and feedback to the referring physician 

from the transplant assessment. 

40United States Renal Data System. 2023. End 

Stage Renal Disease: Chapter 1. Figure 1.5. 

41United States Renal Data System. 2023. End 

Stage Renal Disease: Chapter 1. Figure 1.7. 

42United States Renal Data System. 2023. End 

Stage Renal Disease: Chapter 1. Figure 1.8. 

43United States Renal Data System. 2023. End 

Stage Renal Disease. Chapter 1. Table 1.3. 

44National Kidney Foundation. (2016, January 7). 

Race, Ethnicity and Kidney Disease. National 

Kidney Foundation. https://www.kidney.org/atoz/ 

content/minorities-KD. 

45United States Renal Data System. 2023. End 

Stage Renal Disease. Chapter 1. Figure 1.1. 

health or patient safety. If the MPSC’s 

review determines that a risk to patient 

health or public safety exists, the MPSC 

may request that a member inactivate or 

withdraw a designated transplant 

program, or a specific component of the 

program, to mitigate the risk. Transplant 

programs that do not participate in the 

MPSC performance review process or 

fail to act to improve their performance 

are subject to the policies described in 

Appendix L of OPTN policies, Reviews 

and Actions, including the declaration 

of ‘‘Member Not in Good Standing.’’ 

While being designated ‘‘Member Not in 

Good Standing’’ does not necessarily 

lead to the closure or removal of that 

program from receiving reimbursement 

from Federal health insurance programs, 

the Secretary can, based on a 

recommendation from the OPTN Board 

of Directors, revoke OPTN membership, 

close an OPTN member, or remove the 

ability of the member to receive Federal 

funding from Medicare or Medicaid. 

Additionally, numerous private payers 

align with the MPSC metrics and SRTR 

star rating system that evaluate 

transplant hospitals on post-transplant 

performance to create their Center of 

Excellence (COE) programs. Therefore, 

MPSC reviews and performance on the 

MPSC monitoring measures are a 

powerful regulatory incentive for 

transplant programs. 

In the final rule, dated September 22, 

2020, titled ‘‘Removing Financial 

Disincentives to Living Organ 

Donation’’ (85 FR 59438), HRSA 

expanded the scope of qualified 

reimbursable expenses incurred by 

living donors under the Living Organ 

Donation Reimbursement Program to 

include lost wages and dependent care 

(childcare and elder care) expenses to 

further the goal of reducing financial 

barriers to living organ donation. The 

program previously only allowed for 

reimbursement of travel, lodging, meals, 

and incidental expenses. In the final 

notice, dated September 22, 2020, titled, 

‘‘Reimbursement of Travel and 

Subsistence Expenses Toward Living 

Organ Donation Program Eligibility 

Guidelines,’’ HRSA increased the 

income eligibility threshold under the 

Living Organ Donation Reimbursement 

Program from 300 percent to 350 

percent of the Federal Poverty 

Guidelines (85 FR 59531). 

3. Rationale for the Proposed IOTA 

Model 

a. Alignment With Federal Government 

Initiatives and Priorities 

For decades, patients and health care 

providers have confronted an imbalance 

in the number of transplant candidates 

and the supply of acceptable donor 

organs, including kidneys and other 

organs. Observed variation in access to 

organ transplantation by geography, 

race/ethnicity, disability status, and 

socioeconomic status, as well as the 

overall performance of the organ 

transplantation ecosystem, raised the 

need to make performance 

improvements and address disparities.37

Strengthening and improving the 

performance of the organ 

transplantation ecosystem is a priority 

for HHS. To that end, OTAG was 

established in 2021 by CMS and HRSA 

and has expanded interagency 

coordination and collaboration to ‘‘drive 

improvements in donations, clinical 

outcomes, system improvement, quality 

measurement, transparency, and 

regulatory oversight.’’ 38 Collectively, 

CMS and HRSA seek to— 

• Reduce variation of pre-transplant 

and referral practices; 39

• Increase availability and use of 

donated organs; 

• Increase accountability for organ 

procurement and matching; 

• Promote equitable access to 

transplants; and 

• Empower patients, families, and 

caregivers to actively engage in the 

transplant journey. 

As discussed in section III.C. of the 

proposed rule, we believe the IOTA 

Model has the potential to substantially 

increase the number of kidney 

transplants in a way that enhances 

fairness for all affected individuals, 

regardless of socioeconomic status or 

other factors that limit access to care 

and negatively affect health outcomes, 

thereby improving quality of care, 

reducing costs to Medicare, and 

prolonging lives. The IOTA Model is 

complementary to the ETC and KCC 

Models, and to other CMS and HRSA 

initiatives, with the collective goal of 

achieving improvements in processes 

among transplant hospitals that would 

spur an increase in both deceased donor 

and living donor kidney transplantation 

and reduce population health 

disparities. The IOTA Model is targeted 

to kidney transplant programs, but it 

will test specific modifications for 

Medicare payment and other 

programmatic measures that could 

establish a framework for interventions 

for transplantation that could 

potentially be applied to the other solid 

organ types in the future. 

In the following sections of this final 

rule, we review scientific literature that 

outlines specific ways to enhance 

kidney transplantation. Our analysis is 

focused on kidney transplantation, but 

we also present findings pertaining to 

the transplantation of other organs, 

especially livers. We aim to show how 

the types of interventions that we 

proposed might also apply for any 

future efforts to increase transplant 

numbers for other organ types, and to 

continue to pursue the goal of greater 

equity. We also describe recent efforts 

from CMS and HRSA to enhance organ 

transplantation that complement to the 

IOTA Model’s use of upside risk 

payments and downside risk payments 

as a policy lever to increase the number 

of kidney transplants and achieve a 

fairer distribution. of kidney 

transplants. 

b. End Stage Renal Disease Impact 

According to the United States Renal 

Data System (USRDS), in 2021 about 

808,536 people in the United States 

were living with ESRD, almost double 

the number in 2001.40 Prevalence of 

ESRD varied by Health Service Area 

(HSA) and ESRD Network.41 Stratified 

by age and race/ethnicity, ESRD was 

consistently more prevalent among 

older people (65 and older) and in Black 

people.42 Diabetes and hypertension are 

most often the primary cause of ESRD.43

According to the National Kidney 

Foundation, these diseases 

disproportionately affect minority 

populations, increasing the risk of 

kidney disease.44 Year-over-year, 

incidence of ESRD continues to 

increase, as the number of patients 

newly registered increased from 97,856 

in 2001 to 134,837 in 2019 and 135,972 

in 2021.45 Studies show that people 


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96294 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

46Strohmaier, S., Wallisch, C., Kammer, M., 

Geroldinger, A., Heinze, G., Oberbauer, R., & Haller, 

M.C. (2022). Survival Benefit of First Single-Organ 

Deceased Donor Kidney Transplantation Compared 

With Long-term Dialysis Across Ages in TransplantEligible Patients With Kidney Failure. JAMA 

Network Open, 5(10), e2234971. https://doi.org/ 

10.1001/jamanetworkopen.2022.34971. 

47Tonelli, M., Wiebe, N., Knoll, G., Bello, A., 

Browne, S., Jadhav, D., Klarenbach, S., & Gill, J. 

(2011). Systematic Review: Kidney Transplantation 

Compared With Dialysis in Clinically Relevant 

Outcomes. American Journal of Transplantation, 

11(10), 2093–2109. https://doi.org/10.1111/j.1600- 

6143.2011.03686.x. 

48United States Renal Data System. 2023. End 

Stage Renal Disease: Chapter 7. Figure 7.16. 

49United States Renal Data System. 2023. End 

Stage Renal Disease: Chapter 7. Figures 7.1 and 7.2. 

50United States Renal Data System. 2022. End 

Stage Renal Disease: Chapter 9. 

51According to OPTN data, in 2022, there were 

389 kidney-heart transplants in the U.S. 789 

kidney-liver transplants, 22 kidney-lung 

transplants, and 3 kidney-intestine transplants. See 

https://optn.transplant.hrsa.gov/data/view-datareports/national-data/. 

52Health Resources and Services Administration. 

(2020). Scientific Registry for Transplant 

Recipients. OPTN/SRTR 2020 Annual Data Report: 

Pancreas. https://srtr.transplant.hrsa.gov/annual_

reports/2020/Pancreas.aspx. 

53United States Renal Data System. 2022. USRDS 

Annual Data Report. Volume 2. End-stage Renal 

Disease (ESRD) in the United States, Chapter 7: 

Transplantation. Figure 7.10b. 

54United States Renal Data System. 2022. USRDS 

Annual Data Report. Volume 2. End-stage Renal 

Disease (ESRD) in the United States, Chapter 7: 

Transplantation. Figure 7.10b. 

55 Get the Facts on Kidney Transplantation Before 

You Start Dialysis—Penn Medicine. (2019, July 24). 

www.pennmedicine.org. https://

www.pennmedicine.org/updates/blogs/transplantupdate/2019/july/kidney-transplant-facts-beforedialysis. 

56Organ Procurement and Transplantation 

Network. Kidney Donor Profile Index (KDPI) Guide 

for Clinicians. https://optn.transplant.hrsa.gov/ 

professionals/by-topic/guidance/kidney-donorprofile-index-kdpi-guide-for-clinicians/#:∼:https://

optn.transplant.hrsa.gov/professionals/by-topic/ 

guidance/kidney-donor-profile-index-kdpi-guidefor-clinicians/. 

57Tonelli, M., Wiebe, N., Knoll, G., Bello, A., 

Browne, S., Jadhav, D., Klarenbach, S., & Gill, J. 

(2011). Systematic Review: Kidney Transplantation 

Compared With Dialysis in Clinically Relevant 

Outcomes. American Journal of Transplantation, 

11(10), 2093–2109. https://doi.org/10.1111/j.1600- 

6143.2011.03686.x. 

58 Ibid. 

59United States Renal Data System. 2022. USRDS 

Annual Data Report. 2022. Volume 2. End-stage 

Renal Disease (ESRD) in the United States, Chapter 

5: Hospitalization. Figures 5.1a, 5.9. 

60United States Renal Data System. 2021. USRDS 

Annual Data Report. Volume 2. End-Stage Renal 

Disease (ESRD) in the United States. Chapter 5: 

Hospitalization, Figures 5.1a, 5.6a, 5.8. 

61Nemati, E., Einollahi, B., Lesan Pezeshki, M., 

Porfarziani, V., & Fattahi, M.R. (2014). Does Kidney 

Transplantation With Deceased or Living Donor 

Affect Graft Survival? Nephro-Urology Monthly, 

6(4). https://doi.org/10.5812/numonthly.12182. 

62United States Renal Data System. 2022. USRDS 

Annual Data Report. Volume 2. End-stage Renal 

Disease (ESRD) in the United States, Chapter 7: 

Hospitalization. Figure 7.20.b. 

with kidney transplants live longer than 

those who remain on dialysis.46 47

Despite these positive outcomes, the 

percentage of prevalent ESRD patients 

with a functioning kidney transplant 

remained relatively stable over the past 

decade, increasing only slightly from 

29.7 percent in 2011 to 30.51 percent in 

2021.48 In 2021, 72,864 patients with 

ESRD were on the kidney transplant 

waitlist, of which 27,413 were listed 

during that year.49 The IOTA Model will 

partially focus on the ESRD patients 

who are on the kidney transplant 

waitlists of the kidney transplant 

hospitals that would be required to 

participate in this Model. ESRD patients 

represent a small portion of the U.S. 

population, but the disease burden to 

the patient and to CMS is great in terms 

of health outcomes, survival, quality of 

life, and cost. The ESRD population 

accounted for 6.1% of total Medicare 

expenditures in 2020.50

Due to wide variability across eligible 

kidney transplant hospitals, we are 

unable to estimate the IOTA Model’s 

attributed patient population until the 

IOTA participants are randomly 

selected. 

c. Benefits of Kidney Transplantation 

ESRD, when a person’s kidney 

function has declined to the point of 

requiring regular dialysis or a transplant 

for survival, as the person’s kidneys are 

no longer able to perform life-sustaining 

functions, is the final stage of CKD. 

ESRD is a uniquely burdensome 

condition, with uncertain survival and 

poor quality of life for patients. The 

higher mortality and substantially 

greater expenditures and hospitalization 

rates for ESRD beneficiaries compared 

to the overall Medicare population 

suggest the need to explore policy 

interventions to enhance patients’ 

survival and life experience, as well as 

to reduce the impact to Medicare. The 

IOTA Model aims to improve patient 

outcomes by incentivizing increased 

access to kidney transplantation across 

IOTA participants. Access to this 

lifesaving treatment may delay or avert 

dialysis, reduce costs to the Medicare 

program and to patients, and enhance 

survival and quality of life. 

A kidney transplant involves 

surgically transplanting a kidney from a 

living or deceased donor to a kidney 

transplant recipient. The replacement 

organ is known as a graft. Most kidneys 

are transplanted alone, as kidneys 

transplanted along with other organs are 

very rare.51 Fewer than 1,000 patients 

each year receive a simultaneous 

kidney-pancreas transplant, which is 

generally conducted for patients who 

have kidney failure related to type 1 

diabetes mellitus.52 The kidney in such 

a simultaneous transplant may come 

from a living or deceased donor, but 

other organs mostly come from a 

deceased donor. 

About three-quarters of kidney 

transplants in the U.S. are deceased 

donor kidney transplants.53 For 

deceased donor transplantation, a 

patient needs to contact a transplant 

hospital and arrange for an evaluation to 

assess the feasibility of surgery. The 

patient’s name would then be added to 

a list of individuals who can receive 

organ offers. This is known as the 

kidney transplant hospital’s kidney 

transplant waitlist. Living donation 

occurs when a living person donates an 

organ to a family member, friend, or 

other individual. People unknown to 

one another sometimes take part in 

paired exchanges, which allow the 

switching of recipients based on blood 

type and other biological factors. The 

number of deceased donor kidney 

donations has increased over the past 

decade, while living donor kidney 

donation has remained relatively 

constant, declining in 2020 with the 

COVID–19 pandemic.54

Kidney transplantation is considered 

the optimal treatment option for most 

ESRD patients. Although not a cure for 

kidney disease, a transplant can help a 

person live longer and improve quality 

of life. On average, patients experience 

14 to 16 years of function from a kidney 

from a living kidney donor, while few 

people survive more than a decade on 

dialysis.55 According to one source, the 

majority of deceased donor kidneys are 

expected to function for about 9 years, 

with high quality organs lasting 

longer.56 A systematic review of studies 

worldwide finds significantly lower 

mortality and risk of cardiovascular 

events associated with kidney 

transplantation compared with 

dialysis.57 Additionally, this review 

finds that patients who receive 

transplants experience a better quality 

of life than treatment with dialysis.58

The average dialysis patient is admitted 

to the hospital nearly twice a year, often 

as a result of infection, and more than 

35 percent of dialysis patients who are 

discharged are re-hospitalized within 30 

days of being discharged.59 Among 

transplant recipients, there are lower 

rates of hospitalizations, emergency 

department visits, and readmissions 

compared to those still on dialysis.60 In 

general, from the standpoint of longterm survival and quality of life, a living 

donor kidney transplant is considered 

the best among all kidney transplant 

options for most people with CKD.61 62

A cost advantage also arises with 

kidney transplantation. Per-person perVerDate Sep<11>2014 18:30 Dec 03, 2024 Jkt 265001 PO 00000 Frm 00016 Fmt 4701 Sfmt 4700 E:\FR\FM\04DER2.SGM 04DER2

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Expenditures for Persons with ESRD. Figure 9.11. 

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(2020). Cost-effectiveness of Deceased-donor Renal 

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doi.org/10.1097/txd.0000000000000974. 

65 Khan, S., Tighiouart, H., Kalra, A., Raman, G., 

Rohrer, R.J., & Pereira, B.J.G. (2003). Resource 

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Kidney International, 64(2), 657–664. https://

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84Charnow, J.A. (2021, June 8). Living Donor 

Kidney Transplants Declined in the Last Decade. 

Renal and Urology News. https://www.renaland

urologynews.com/news/living-donor-kidneytransplantation-decreased-after-2010-united-statestrends/. 

year Medicare FFS spending for 

beneficiaries with ESRD with a 

transplant is less than half that for either 

hemodialysis or peritoneal dialysis.63

While the benefits to patient survival 

and quality of life from living donor 

kidney transplantation are more 

pronounced, a recent literature review 

shows that deceased donor kidney 

transplantation generally produced 

better outcomes at a lower cost 

compared to dialysis, although old age 

and a high comorbidity load among 

kidney transplant patients may mitigate 

this advantage.64 An earlier study, based 

on a single hospital, showed rates of 

hospitalization, a substantial factor in 

health care costs, to be lower among 

kidney transplant patients than for those 

on dialysis.65

Despite these positive outcomes 

associated with kidney transplantation, 

in 2020, only about 30 percent of 

prevalent ESRD patients (those with 

existing ESRD diagnoses) in the U.S. 

had a functioning kidney transplant, or 

graft.66 In 2016, only 2.8 percent of 

incident ESRD patients (patients newly 

diagnosed with ESRD) received a 

preemptive kidney transplant, allowing 

them to avoid dialysis.67 These rates are 

substantially below those of other 

developed nations. The U.S. was ranked 

17th out of 42 reporting countries in 

kidney transplants per 1,000 dialysis 

patients in 2020, with 42 transplants per 

1,000 dialysis patients in 2020.68 We 

seek to test policy approaches aimed at 

increasing the number of kidney 

transplants over current levels given 

these relatively low numbers and the 

overall benefit to patients from 

transplantation, as well as the potential 

savings to Medicare. 

d. Kidney Transplant Rates and Unmet 

Needs 

Annually, more than one hundred 

thousand individuals in the U.S. begin 

treatment for ESRD.69 Despite 

transplantation being widely regarded 

as the optimal treatment for people with 

ESRD, as well as being more costeffective in the long term compared to 

dialysis, only a minority of people with 

ESRD (13 percent) are added to the 

waitlist, and even fewer receive a 

transplant. To be added to the kidney 

transplant waitlist, a patient must 

complete an evaluation at a transplant 

hospital, and the patient must be found 

to be a good candidate for a transplant. 

Nearly 5,000 patients on the national 

kidney transplant waiting list die each 

year.70 71 72 These trends have persisted 

for several decades despite increases in 

the number of kidney transplants from 

deceased donors and living donors. 

From 1996 to 2019, the number of 

kidneys made available for 

transplantation from deceased donors 

grew steadily, in part because of organs 

that became available as a result of the 

opioid epidemic.73 74 In 2018 and 2019, 

the total number of kidney transplants 

rose steadily as compared to previous 

years.75 In 2019, almost one third of 

patients received a transplant within 

one year of being placed on the waitlist 

(32.9 percent), and the rate reached 51.8 

percent within 5 years of being placed 

on the waitlist.76 The number of kidney 

transplants increased by 10.2 percent 

from 2018 to 2019, but fell by 2.7 

percent from 2019 to 2020, from 24,511 

to 23,853. The reduction was 

precipitated by a 23.6 percent decline in 

living donor transplants on account of 

the COVID–19 pandemic.77 The overall 

number of patients with a functioning 

graft continued its upward trend, 

reaching 245,846 in 2020, an increase of 

2.7 percent from 2019.78 Nonetheless, 

these gains in kidney transplantation in 

the U.S. have fallen far short of the 

prevailing need among individuals with 

ESRD or facing the prospect of kidney 

failure. The number of individuals with 

ESRD added to the waitlist for a kidney 

transplant reached a high of 28,533 in 

2019, but dropped slightly to 25,136 in 

2020, while rising to 27,413 in 2021.79

At the end of 2021, 72,864 individuals 

were on the waitlist for a kidney 

transplant.80

The increase in deceased donor 

kidney transplantation was 

accompanied by a gradual but steady 

decline in the number of living donor 

transplants as compared to patients 

undergoing dialysis. The total number 

of living donor transplants per year has 

risen moderately over the past two 

decades, from 5,048 in 2000 to 5,241 in 

2020, and 5,971 in 2021.81 82 With the 

overall dialysis population growing, the 

rate of living donor transplants per 100 

patient-years on dialysis declined from 

1.4 to 0.8 transplants from 2010 to 

2020.83 A report states the proportion of 

patients undergoing living donor kidney 

donation to have decreased from 37 

percent in 2010 to 29 percent in 2019.84

A study in 2013 of OPTN data found 

that the decline in living donation 


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85Rodrigue, J.R., Schold, J.D., & Mandelbrot, D.A. 

(2013). The Decline in Living Kidney Donation in 

the United States. Transplantation Journal, 96(9), 

767–773. https://doi.org/10.1097/tp.0b013e

318298fa61. 86 King, K.L., Husain, S.A., Schold, J.D., Patzer, 

R.E., Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., 

Pastan, S.O., & Mohan, S. (2020). Major Variation 

across Local Transplant Centers in Probability of 

Kidney Transplant for Wait-Listed Patients. Journal 

of the American Society of Nephrology, 31(12), 

2900–2911. https://doi.org/10.1681/ASN.20200

30335. 

87Melanson T., Basu M., Plantiga L., Pastan S., 

Mohan S., Patzer R. (2017). Variation in Living 

Donor Kidney Transplantation among U.S. 

Transplant Centers. American Journal of 

Transplantation, 17 (suppl 3). 

88United States Renal Data System. 2022. Annual 

Data Report. Supplements: COVID–19, Racial and 

Ethnic Disparities Figures 14.14 and 14.15. 

89Wesselman, H., Ford, C.G., Leyva, Y., Li, X., 

Chang, C.-C.H., Dew, M.A., Kendall, K., Croswell, 

E., Pleis, J.R., Ng, Y.H., Unruh, M.L., Shapiro, R., 

& Myaskovsky, L. (2021). Social Determinants of 

Health and Race Disparities in Kidney Transplant. 

Clinical Journal of the American Society of 

Nephrology, 16(2), 262–274. https://doi.org/ 

10.2215/cjn.04860420. 

90Ng, Y.-H., Pankratz, V.S., Leyva, Y., Ford, C.G., 

Pleis, J.R., Kendall, K., Croswell, E., Dew, M.A., 

Shapiro, R., Switzer, G.E., Unruh, M.L., & 

Myaskovsky, L. (2019). Does Racial Disparity in 

Kidney Transplant Wait-listing Persist After 

Accounting for Social Determinants of Health? 

Transplantation, 1. https://doi.org/10.1097/ 

tp.0000000000003002. 

91With the enactment of NOTA, CMS designated 

DSAs; generally, each DSA includes an OPO within 

its geographic area. Until March 2021, when OPTN 

implemented the current policy for allocation of 

deceased donor kidneys, the priority for organs 

acquired by an OPO was based, among other 

factors, on an individual’s residence within the 

DSA extending around the OPO. 

92 King, K.L., Husain, S.A., Schold, J.D., Patzer, 

R.E., Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., 

Pastan, S.O., & Mohan, S. (2020). Major Variation 

across Local Transplant Centers in Probability of 

Kidney Transplant for Wait-Listed Patients. Journal 

of the American Society of Nephrology, 31(12), 

2900–2911. https://doi.org/10.1681/ 

ASN.2020030335. 

93 King et al. 2020. 2900. 

94 King et al. 2020. 2903. 

95 King et al., 2020. 2903. 

96 King et al. 2020. 2903–2904. 

97Melanson T., Basu M., Plantiga L., Pastan S., 

Mohan S., Patzer R. (2017). Variation in Living 

Donor Kidney Transplantation among U.S. 

Transplant Centers. American Journal of 

Transplantation, 17 (suppl 3). 

98United States Renal Data System. 2022. Annual 

Data Report. Supplements: COVID–19, Racial and 

Ethnic Disparities Figures 14.14 and 14.15. 

99National Kidney Foundation. (2016, January 7). 

Race, Ethnicity, & Kidney Disease. National Kidney 

Foundation. https://www.kidney.org/atoz/content/ 

minorities-KD. 

100Patzer, R.E., & Pastan, S.O. (2020). Policies to 

promote timely referral for kidney transplantation. 

Seminars in Dialysis, 33(1), 58–67. https://doi.org/ 

10.1111/sdi.12860. 

101Patzer, R. Perryman, J. Schrager, J. Pastan, S. 

Amaral, S. Gazmararian, J. Klein, M. Kutner, N. 

McClellan, W. 2012. Patzer, R.E., Perryman, J.P., 

Schrager, J.D., Pastan, S., Amaral, S., Gazmararian, 

J.A., Klein, M., Kutner, N., & McClellan, W.M. 

(2012). The Role of Race and Poverty on Steps to 

Kidney Transplantation in the Southeastern United 

States. American Journal of Transplantation, 12(2), 

358–368. https://doi.org/10.1111/j.1600- 

6143.2011.03927.x. 

102Wesselman, H., Ford, C.G., Leyva, Y., Li, X., 

Chang, C.-C.H., Dew, M.A., Kendall, K., Croswell, 

E., Pleis, J.R., Ng, Y.H., Unruh, M.L., Shapiro, R., 

& Myaskovsky, L. (2021). Social Determinants of 

Health and Race Disparities in Kidney Transplant. 

Clinical Journal of the American Society of 

Nephrology, 16(2), 262–274. https://doi.org/ 

10.2215/cjn.04860420. 

103Ng, Y.-H., Pankratz, V.S., Leyva, Y., Ford, C.G., 

Pleis, J.R., Kendall, K., Croswell, E., Dew, M.A., 

Shapiro, R., Switzer, G.E., Unruh, M.L., & 

Myaskovsky, L. (2019). Does Racial Disparity in 

Kidney Transplant Wait-listing Persist After 

Accounting for Social Determinants of Health? 

Transplantation, 1. https://doi.org/10.1097/ 

tp.0000000000003002. 

104Schold, J.D., Gregg, J.A., Harman, J.S., Hall, 

A.G., Patton, P.R., & Meier-Kriesche, H.-U. (2011). 

Barriers to Evaluation and Wait Listing for Kidney 

appeared most prominent among men, 

Black/African Americans, and younger 

and lower income adults, potentially 

leading to longer waiting times for 

transplantation, greater dialysis 

exposure, higher death rates on the 

waitlist, lower graft and patient survival 

for recipients, and higher overall 

healthcare costs for the care of patients 

with ESRD.85

e. Disparities 

Kidney transplantation research in the 

U.S. reveals disparities across a number 

of different axes including geography, 

race and ethnicity, disability, 

socioeconomic status, neighborhood 

factors, and availability of health 

insurance.86 87 88 89 90 A 2020 study 

showed substantial disparities in kidney 

transplant rates among transplant 

programs at a national level, as well as 

both among and within donation service 

areas (DSAs).91 92 This study examined 

data from a registry that included all 

U.S. adult kidney transplant candidates 

added to the waitlist in 2011 and 2015, 

comprising 32,745 and 34,728 

individuals, respectively.93 Among 

transplant programs nationwide, in 

2015, the study found that the 

probability of a deceased donor 

transplant within three years for the 

average patient to be up to 16 times 

greater in some transplant hospitals as 

compared to others.94 Substantial 

differences in probability of deceased 

donor transplantation were found even 

within DSAs, where all transplant 

programs utilize the same OPO and 

local organ supply. For the 2015 cohort, 

there was a median 2.3-fold difference 

between the highest and lowest hospital 

in each DSA in the 43 of 58 DSAs with 

more than one transplant hospital. The 

largest absolute difference in probability 

of transplant occurred in a DSA with 

seven transplant programs, with a 

patient on the waitlist at the transplant 

program with the highest probability of 

transplant being 9.8 times more likely to 

receive a transplant than a patient at the 

transplant program with the lowest 

probability of receiving a transplant.95

Factors such as local organ supply, the 

characteristics of individuals on the 

waitlist of a given transplant program, 

the size of the waitlist, and the 

transplant program’s volume of 

transplants may account for the 

differences observed nationally across 

DSAs. However, the variation among 

transplant programs across DSAs is 

significantly associated with organ offer 

acceptance patterns at individual 

transplant hospitals.96 This underscores 

the need to address geographic 

disparities and for more transparency on 

how transplant programs make 

decisions on organ offers for their 

waitlist patients. 

Living donor kidney donation also 

varies widely among transplant 

hospitals. A 2018 report using OPTN 

data from 2015 showed that while most 

transplant hospitals perform few living 

donor kidney transplants, certain 

transplant hospitals have substantially 

higher rates for their waitlist patients 

than the median rate. Differences among 

transplant hospitals were correlated 

with geographic region and the number 

of deceased donor kidney 

transplantations performed.97 This 

underscores the need for initiatives and 

processes among transplant hospitals to 

encourage living donations to reduce 

geographic disparities. 

Disparities in kidney transplantation 

rates for various populations in the U.S. 

have long been documented. Literature 

over the past two decades has focused 

on Non-Hispanic Black patients, who 

experience lower rates of deceased and 

living donor kidney transplantation as 

compared to Non-Hispanic White 

patients, while being four times more 

likely to have kidney failure. Black/ 

African Americans and Hispanics/ 

Latinos with kidney failure experience 

lower rates of kidney transplantation 

compared with White patients.98

Additionally, Black/African Americans 

and Hispanics/Latinos, along with 

Asians, American Indian/Alaskan 

Natives, and other minorities, are at a 

higher risk of illnesses that may 

eventually lead to kidney failure, such 

as diabetes and high blood pressure.99

The literature over several decades 

has also addressed the effect of 

differences in age, gender, 

socioeconomic status (SES), and 

cultural aspects.100 Recent studies have 

emphasized poverty and income 

differentials in analyzing the interplay 

of these and other factors among 

populations referred for kidney 

transplantation at several large 

transplant hospitals.101 102 103 104 This 


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Transplantation. Clinical Journal of the American 

Society of Nephrology, 6(7), 1760–1767. https://

doi.org/10.2215/cjn.08620910. 

105Reed, R.D., & Locke, J.E. (2020). Social 

Determinants of Health: Going Beyond the Basics to 

Explore Racial Disparities in Kidney 

Transplantation. Transplantation, 104, 1324– 

1325.(7), 1324–1325.–1325. https://doi.org/10.1097/ 

TP.0000000000003003. 

106National Academies of Sciences, Engineering, 

and Medicine. (2022). Realizing the Promise of 

Equity in the Organ Transplantation System (K.W. 

Kizer, R.A. English, & M. Hackmann, Eds.; pp. 88– 

93). National Academies Press. https://doi.org/ 

10.17226/26364. 

107Centers for Disease Control and Prevention. 

Social Determinants of Health at CDC. Retrieved 

June 13, 2023, from https://www.cdc.gov/about/ 

priorities/social-determinants-of-health-atcdc.html?CDC_AAref_Val=https://www.cdc.gov/ 

about/sdoh/index.html. 

108Wesselman et al, 2021. 

109Ng et al, 2020. 

110Centers for Disease Control and Prevention. 

Social Determinants of Health at CDC. Retrieved 

June 13, 2023, from https://www.cdc.gov/about/ 

priorities/social-determinants-of-health-atcdc.html?CDC_AAref_Val=https://www.cdc.gov/ 

about/sdoh/index.html. 

111Ng Y et al. 2020. 1453. 

112Wesselman et al, 2021. 271. 

113Wesselman et al. 2021. 262. 

114Schold et al, 2021. 

115Wesselman et al, 2021. 270. 

116United States Renal Data System. 2022. 

Annual Data Report. End Stage Renal Disease 

Chapter 7 Transplantation Figure 7.10a. 

117Purnell, T.S., Hall, Y.N., & Boulware, L.E. 

(2012). Understanding and Overcoming Barriers to 

Living Kidney Donation Among Racial and Ethnic 

Minorities in the United States. Advances in 

Chronic Kidney Disease, 19(4), 244–251. https://

doi.org/10.1053/j.ackd.2012.01.008. 

118Rodrigue, J.R., Kazley, A.S., Mandelbrot, D.A., 

Hays, R., LaPointe Rudow, D., & Baliga, P. (2015). 

Living Donor Kidney Transplantation: Overcoming 

Disparities in Live Kidney Donation in the US— 

Recommendations from a Consensus Conference. 

Clinical Journal of the American Society of 

Nephrology, 10(9), 1687–1695. https://doi.org/ 

10.2215/cjn.00700115. 

119Purnell, T.S., Luo, X., Cooper, L.A., Massie, 

A.B., Kucirka, L.M., Henderson, M.L., Gordon, E.J., 

Crews, D.C., Boulware, L.E., & Segev, D.L. (2018). 

Association of Race and Ethnicity With Live Donor 

Kidney Transplantation in the United States From 

1995 to 2014. JAMA, 319(1), 49. https://doi.org/ 

10.1001/jama.2017.19152. 

120Hall, E.C., James, N.T., Garonzik Wang, J.M., 

Berger, J.C., Montgomery, R.A., Dagher, N.N., Desai, 

N.M., & Segev, D.L. (2012). Center-Level Factors 

and Racial Disparities in Living Donor Kidney 

Transplantation. American Journal of Kidney 

Diseases, 59(6), 849–857. https://doi.org/10.1053/ 

j.ajkd.2011.12.021. 

121 Gore, J.L., Danovitch, G.M., Litwin, M.S., 

Pham, P–T.T., & Singer, J.S. (2009). Disparities in 

the Utilization of Live Donor Renal Transplantation. 

American Journal of Transplantation, 9(5), 1124– 

1133. https://doi.org/10.1111/j.1600- 

6143.2009.02620.x. 

122Rodrigue et al. 2015. 

123Purnell et al. 2015. 58. 

124Purnell et al. 2015. 59. 

research extends in time prior to the 

Kidney Allocation System (KAS) of 

2014, which aimed to lessen the impact 

of racial differences on access to kidney 

transplantation. 

Research findings support the 

proposition that a broad interpretation 

of social determinants of health (SDOH) 

may substantially explain racial 

disparities in both deceased and living 

donor kidney transplantation.105

Recently, a comprehensive survey of the 

literature on disparities in 

transplantation for kidneys and other 

organs found that socioeconomic factors 

may substantially explain 

disproportionately lower transplant 

rates and longer wait times.106 As 

described in recent literature, a person’s 

SDOH may contribute to inequities in 

their prospects for waitlist registration 

and receipt of transplantation.107 108 109

SDOH is defined more broadly than 

socioeconomic status, to include those 

conditions in the places where people 

live, learn, work, and play that affect a 

wide range of health and quality of life 

risks and outcomes.110 More 

specifically, SDOH include variations in 

employment, neighborhood factors, 

education, social support systems, and 

healthcare coverage that impact health 

outcomes. 

A salient group of recent analyses 

focused on a cohort of patients initially 

referred for evaluation for a kidney 

transplant at a large urban transplant 

hospital between 2010 and 2012. These 

studies showed lower waitlist 

registration and transplant rates for 

Black/African Americans, regardless of 

SDOH.111 112 One of the studies reports 

that racial difference showed a weaker 

association with the rate of waitlist 

registration after the introduction of the 

KAS. Another of these studies, focusing 

on transplant rates as the outcome, 

showed that even after accounting for 

social determinants of health, Black 

patients had a lower likelihood of 

kidney transplant and living-donor 

transplant, but not deceased-donor 

transplant. Black race, older age, lower 

income, public insurance, more 

comorbidities, being transplanted before 

changes to the KAS, greater religiosity, 

less social support, less transplant 

knowledge, and fewer learning activities 

were each associated with a lower 

probability of any kidney transplant.113

Similarly, an earlier study of a 

population at a single transplant 

hospital found that income and 

insurance attenuated the association 

between racial difference and placement 

on the waitlist for a kidney 

transplant.114 The findings in these 

studies of the enduring influence of 

cultural, socioeconomic and 

demographic factors apart from racial 

difference underscore the need to 

consider initiatives and improvement 

activities aimed at addressing SDOH for 

ESRD patients to remove barriers to 

access to kidney transplantations. 

Living donor transplantation has 

demonstrated the enduring influence of 

racial disparities, but also the 

importance of SES and neighborhood 

factors. The cohort of patients identified 

previously, initially referred for 

evaluation at a large urban hospital 

between 2010 and 2012, showed that for 

living donor transplantation, Black/ 

African American race and lower 

income held a stronger association with 

a lower probability of living donor 

transplant than with deceased donor 

donation.115 These results accord with 

findings nationwide that White patients 

are more likely to receive a living donor 

transplant, followed by Asian and 

Hispanic/Latino patients. Black/African 

American patients have had lower rates 

of living donor transplants than other 

racial or ethnic groups.116 Explanations 

for these differences have included 

disparate rates of diabetes, obesity, and 

hypertension observed among minority 

populations that may contraindicate 

living donation by a relative; cultural 

differences in willingness to donate or 

ask for a living donation; concerns about 

costs among potential donors; and lack 

of knowledge about living donor 

transplantation on the part of patients, 

their families, and health care 

providers.117 118

Research over several decades 

confirms the relation between health 

care access and SES factors and 

disparities in living donor kidney 

transplantation receipt for Black/African 

American and Hispanic/Latino patients, 

and, additionally, that these disparities 

have increased over time.119 120 121 122

According to one study, between 1995 

and 2014, disparities in the receipt of 

living donor kidney transplantation 

grew more for Black/African Americans 

and Hispanics/Latinos: (1) living in 

poorer (versus wealthier) 

neighborhoods; (2) without (versus 

with) a college degree; and (3) with 

Medicare (versus private insurance).123

The study suggests that delays in the 

receipt of kidney care may contribute to 

reported racial and ethnic differences in 

the quality and timing of discussions 

among patients, families, and clinicians 

about living donor kidney 

transplantation as a treatment option.124

One study also established 

associations between rates of living 

donor kidney transplantation for Black/ 

African Americans and transplant 

hospital characteristics. While 

recognizing the potential effect of 

clinical factors, the study found that 

hospitals with high overall rates of 

living donor kidney transplantation 


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125Hall et al. 2012. 855. 

126Hall et al. 2012. 855. 

127See, for example, National Council on 

Disability. (2019). Organ Transplant Discrimination 

Against People with Disabilities: Part of the 

Bioethics and Disability Series. https://

www.ncd.gov/report/organ-transplantdiscrimination-against-people-with-disabilities. 

128 Id. at 38–40. 

129Am. Soc’y of Transplant Surgeons, Statement 

Concerning Eligibility for Solid Organ Transplant 

Candidacy (Feb. 12, 2021), https://asts.org/ 

advocacy/position-statements.https://asts.org/ 

advocacy/position-statements. 

130United States Renal Data System. 2023. 

Annual Data Report. Volume 2. End Stage Renal 

Disease. Transplantation. Figures 7.19a and 7.19b. 

131United States Renal Data System. 2023. 

Annual Data Report. Volume 2. End Stage Renal 

Disease. Chapter 7. Transplantation. Figures 7.20a 

and 7.20b. 

132United States Renal Data System. 2023. 

Annual Data Report. Volume 2. End Stage Renal 

Disease. Chapter 7. Transplantation. Figure 7.21a. 

133United States Renal Data System. 2023. 

Annual Data Report Volume 2. End Stage Renal 

Disease. Chapter 7. Transplantation. Figure 7.21b. 

134Hariharan, S., Israni, A.K., & Danovitch, G. 

(2021). Long-Term Survival after Kidney 

Transplantation. New England Journal of Medicine, 

385(8), 729–743. https://doi.org/10.1056/ 

nejmra2014530. 

135Hariharan, S., Israni, A.K., & Danovitch, G. 

(2021). Long-Term Survival after Kidney 

Transplantation. New England Journal of Medicine, 

385(8), 729–743. https://doi.org/10.1056/ 

nejmra2014530. 

136Mohan, S., Chiles, M.C., Patzer, R.E., Pastan, 

S.O., Husain, S.A., Carpenter, D.J., Dube, G.K., 

Crew, R.J., Ratner, L.E., & Cohen, D.J. (2018). 

Factors leading to the discard of deceased donor 

kidneys in the United States. Kidney International, 

94(1), 187–198. https://doi.org/10.1016/ 

j.kint.2018.02.016. 

137Aubert, O. Reese. P. Audry, B. Bouatou, B. 

Raynaud, M. Viglietti, D. Legendre, C. Glotz, D. 

Empana, J. Jouben, X. Lefaucheur, C. Jacquelinet, C. 

Loupy, A. (2019). Disparities in Acceptance of 

Deceased Donor Kidneys Between the United States 

and France and Estimated Effects of Increased US 

Acceptance. JAMA Internal Medicine, 179(10), 

1365–1374. https://doi.org/10.1001/ 

jamainternmed.2019.2322. 

138 Ibrahim, M., Vece, G., Mehew, J., Johnson, R., 

Forsythe, J., Klassen, D., Callaghan, C., & Stewart, 

D. (2019). An international comparison of deceased 

donor kidney utilization: What can the United 

States and the United Kingdom learn from each 

other? American Journal of Transplantation, 20(5), 

1309–1322. https://doi.org/10.1111/ajt.15719. 

139Stewart, D.E., Garcia, V.C., Rosendale, J.D., 

Klassen, D.K., & Carrico, B.J. (2017). Diagnosing the 

Decades-Long Rise in the Deceased Donor Kidney 

Discard Rate in the United States. Transplantation, 

101(3), 575–587. https://doi.org/10.1097/ 

tp.0000000000001539. 

140Health Resources and Services 

Administration. OPTN. (2017). Two year analysis 

shows effects of kidney transplantation system. 

Optn. transplant.hrsa.gov. Retrieved May 30, 2023, 

from https://optn.transplant.hrsa.gov/news/twoyear-analysis-shows-effects-of-kidney-allocationsystem/. 

showed significantly decreased racial 

disparities. The authors suggest that 

such high rates reveal commitment to 

living donor kidney transplantation, 

possibly shown in better education 

programs, more formalized procedures 

to reduce failure to complete transplant 

evaluations, increased use of medically 

complex and unrelated donors, and 

more success in reducing financial 

barriers to living donor kidney 

donation.125 The study also notes that 

hospitals with higher percentages of 

Black/African American candidates 

experience greater racial disparities. The 

authors surmise that such a high 

percentage might indicate an urban 

setting exhibiting greater differences in 

access to health care between Black/ 

African Americans and other 

populations.126

Studies have also shown 

discrimination on the basis of disability 

with regard to organ transplantation, 

particularly for individuals with 

intellectual and developmental 

disabilities, who are often assumed by 

transplant providers to be unable to 

manage post-transplantation care 

requirements.127 Discrimination occurs 

even though individuals’ disabilities 

that are not related to the need for an 

organ transplant generally have little or 

no impact on the likelihood that the 

transplant would be successful.128 The 

American Society of Transplant 

Surgeons has recommended that no 

patient be discriminated against or 

precluded from transplant listing solely 

due to the presence of a disability, 

whether physical or psychological.129

CMS kept these concerns in mind 

when developing the IOTA Model 

proposals. The IOTA Model uses 

performance-based payments that hold 

transplant hospitals selected as the 

IOTA participants financially 

accountable for improvements in access 

to both deceased and living donor 

kidney transplantations. To reduce 

disparities and promote health equity, 

CMS proposed that the IOTA 

participants would be required to 

develop and submit a Health Equity 

Plan to CMS. This model design feature 

is aimed at encouraging IOTA 

participants to reassess their processes 

and policies around living and deceased 

donor kidneys and promote investments 

in performance and quality 

improvement activities that address 

barriers to care, including SDOH. The 

sequence of steps that patients need to 

undertake to gain access to kidney 

transplantation is complex, and the 

challenge posed by this process for 

potential recipients may be 

compounded by racial, socioeconomic 

and neighborhood factors. 

f. Post-Transplant Outcomes 

While the need for kidney transplants 

has grown, the rates of patient and graft 

survival have increased. Between 2001 

and 2020, graft survival rates at 1 and 

5 years showed an increasing trend.130

Patient survival at 1 year increased from 

97.5 percent in 2001 to 99.2 percent in 

2018, but then declined to 98.9 percent 

in 2019 and 98.4 percent in 2020; 

patient survival at 5 years rose from 89.8 

percent in 2001 to an all-time high of 

93.6 percent in 2013, dropping slightly 

to 93.2 percent in 2016.131 For living 

donor kidney transplants, the rate of 

graft failure at 3 years decreased from 

3.0 per 100 person years in 2010 to 2.1 

per 100 person years in 2018. The rate 

of death at 3 years with a functioning 

graft also decreased from 1.2 to 1.0 per 

100 person-years.132 For deceased donor 

kidney transplants, the rate of graft 

failure at 3 years decreased from 2010 

(6.3 per 100 patient years) to 2014 (4.9 

per 100 patient years), but increased to 

5.3 per 100 patient years in 2018. The 

same pattern was observed for death 

with a functioning graft, except that the 

rate in the 2018 cohort (2.8 per 100 

patient years) exceeded that of the 2010 

cohort (2.6 per 100 patient years).133

A study published in the New 

England Journal of Medicine in 2021 

shows the advantage of transplantation 

using deceased donor organs over longterm dialysis, even with an increasing 

trend of adverse conditions among 

recipients and donors. Notably, patient 

survival improved between the 1990s 

and the period from 2008 to 2011, 

despite increases in both (a) recipients’ 

age, body-mass index (BMI), frequency 

of diabetes, and length of time 

undergoing dialysis, as well as a higher 

proportion of recipients with a previous 

kidney transplant; and (b) donors’ age 

and in the percentage of donations after 

circulatory death.134 Early referral of 

patients for transplants, kidney 

exchange programs, better diagnostic 

tools to identify early acute rejection, 

innovative therapies for countering 

rejection and infection, and 

optimization of immunosuppressive 

medications may be opportunities to 

enhance kidney graft survival.135

g. Non-Acceptance and Discards in 

Kidney Transplantation 

Studies have documented the 

substantial extent of deceased donor 

kidney non-utilization in the U.S. 

relative to other countries (although 

methods of defining these rates differ 

among countries), as well as a steady 

increase in that trend over the past two 

decades.136 137 138 139 140 A study in 2018 

described donor-specific factors, such as 

biopsy findings and donor history, along 

with an increasing selectivity among 

transplant hospitals in accepting organs 

for transplant and inability to locate a 

recipient as contributing to this increase 


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141Mohan, Chiles et al. (2018). 

142Lentine, K. Smith, J. Hart, A. Miller, J. Skeans, 

M. Larkin, L. Robinson, A. Gauntt, K. Israni, A. 

Hirose, R. Snyder, J. (2022). OPTN/SRTR 2020 

Annual Data Report: Kidney. American Journal of 

Transplantation 22(Suppl 2) 21–136. 

143Following the introduction of certain anti-viral 

drugs, transplanting kidneys from donors infected 

with Hepatitis C has shown promising outcomes in 

recent studies. See Penn Medicine News ‘‘Penn 

Researchers Continue to Advance Transplantation 

of Hepatitis C Virus-infected kidneys into HCVNegative Recipients’’ August 31, 2020 https://

www.pennmedicine.org/news/news-releases/2020/ 

august/penn-researchers-advance-transplantationhepatitis-c-virus-infected-kidneys-hcv-negativerecipients. 

144Cron, D. Husain, S. Adler, J. (2022). The new 

distance-based kidney allocation system: 

Implications for patients, transplant centers, and 

Organ Procurement Organizations. Current 

Transplantation Reports, 9(4), 304. https://doi.org/ 

10.1007/s40472-022-00384-z. 

145OPTN Kidney Transplantation Committee. 

(n.d.). The New Kidney Allocation System (KAS) 

Frequently Asked Questions. Retrieved December 6, 

2023, from https://optn.transplant.hrsa.gov/media/ 

1235/kas_faqs.pdf. p. 4. 

146OPTN. (n.d.) The New Kidney Allocation 

System (KAS) Frequently Asked Questions. https:// 

optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. 

p. 4. 

147OPTN. (n.d.). The New Kidney Allocation 

System Frequently Asked Questions. https://

optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. 

pp. 8–9. 

148OPTN. (n.d.). The New Kidney Allocation 

System Frequently Asked Questions . https://

optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. 

p. 4. 

149OPTN. (n.d.). The New Kidney Allocation 

System Frequently Asked Questions. https://

optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. 

p. 4. 

150OPTN. (2017, July 9). Two Year Analysis 

shows effects of Kidney Allocation System. 

Retrieved June 9, 2023, from https://

optn.transplant.hrsa.gov/news/two-year-analysisshows-effects-of-kidney-allocation-system/. 

151OPTN. (2017, July 9). Two Year Analysis 

shows effects of Kidney Allocation System. 

Retrieved June 9, 2023, from https://

optn.transplant.hrsa.gov/news/two-year-analysisshows-effects-of-kidney-allocation-system/. 

152Potluri, V.S., & Bloom, R.D. (2021). Effect of 

Policy on Geographic Inequities in Kidney 

Transplantation. American Journal of Kidney 

Diseases, 79(6), 897–900. https://doi.org/10.1053/ 

j.ajkd.2021.11.005. 153Penn Medicine. (2021, November 17). Update: 

Change in Organ Allocation Designed to Increase 

Equity in US Kidney and Pancreas Transplantation. 

Penn Medicine Physician Blog. https://

www.pennmedicine.org/updates/blogs/pennphysician-blog/2021/november/change-in-organallocation-designed-to-increase-equity-in-us-kidneyand-pancreas-transplantation. 154Potluri, Bloom. (2021). 897–898. 155Potluri, Bloom. (2021) 898. 156 Gentry, S.E., Chow, E.K.H., Wickliffe, C.E., 

Massie, A.B., Leighton, T., & Segev, D.L. (2014). 

Impact of broader sharing on the transport time for 

deceased donor livers. Liver Transplantation, 

20(10), 1237–1243. https://doi.org/10.1002/lt.23942. 

157Chow, E.M., DiBrito, S.R., Luo, X., Wickliffe, 

C., Massie, A.B., Locke, J.E., Gentry, S.E., GaronzikWang, J., & Segev, D.L. (2018). Long Cold Ischemia 

Times in Same Hospital Deceased Donor 

Transplants. Transplantation, 102(3), 471–477. 

https://doi.org/10.1097/tp.0000000000001957. 

158Adler, J.T., Husain, S.A., King, K.L., & Mohan, 

S. (2021). Greater complexity and monitoring of the 

new Kidney Allocation System: Implications and 

unintended consequences of concentric circle 

kidney allocation on network complexity. American 

Journal of Transplantation, 21(6), 2007–2013. 

https://doi.org/10.1111/ajt.16441. 

in non-utilization.141 Within the context 

of the COVID–19 pandemic, the nonutilization of deceased donor kidneys in 

2020 rose to the highest level up to that 

time, 21.3 percent, despite the decline 

in discard of organs from hepatitis Cpositive donors.142 143 According to one 

analysis, the deceased donor kidney 

discard rate peaked at 27 percent during 

the fourth quarter of 2021.144

Since the KAS went into effect in 

2014, the OPTN has aimed to address 

the high rate of kidneys going unused. 

The new kidney allocation system was 

developed in response to higher than 

necessary discard rates of kidneys, 

variability in access to transplants for 

candidates who are harder to match due 

to biologic reasons, inequities resulting 

from the way waiting time was 

calculated, and a matching system that 

results in unrealized life years and high 

re-transplant rates.145 The KAS also 

revised the system that matched 

waitlisted individuals with available 

organs.146 As part of the KAS, the 

Kidney Donor Profile Index (KDPI) was 

implemented to assess the quality of 

kidneys procured for kidney 

transplants. The KDPI is based on a 

preliminary measurement, the Kidney 

Donor Risk Index (KDRI), which 

estimates the relative risk of posttransplant kidney graft failure based on 

scores for the deceased donor on a set 

of 10 demographic and clinic 

characteristics, including age, height, 

weight, ethnicity, history of 

hypertension, history of diabetes, cause 

of death, serum creatinine, hepatitis C 

virus status, and donation after 

circulatory death status.147 This relative 

risk is determined in relation to the 

overall distribution of a grouping of 

these scores across the overall deceased 

donor population for the previous year. 

The KDPI transforms the KDRI to a zeroto-100 scale. Lower KDPI scores are 

associated with greater expected posttransplant longevity, while higher KDPI 

scores are associated with a worse 

expected outcome in this regard.148

According to these new allocation 

rules, the KDPI of an available organ 

was to be assessed, with donor kidneys 

with low KDPI scores being offered to 

patients scoring high in terms of 

expected longevity. New revisions to the 

KAS also included an individual’s time 

on dialysis prior to waitlisting to assess 

waiting time used for determining 

priority for an available organ, and new 

rules that allowed for greater access for 

candidates with blood type B to donor 

kidneys with other blood types.149

An OPTN data analysis from 2014 to 

2016, the first two years after KAS 

implementation, showed that despite 

substantial increases in both deceased 

kidney donor transplants and deceased 

kidney donation, the kidney discard rate 

increased to 19.9 percent in 2016.150

The OPTN linked the discard rates to 

KDPI scores, with fewer than 3 percent 

of donor kidneys with KDPI between 

zero and 20 percent discarded, 

compared with 60 percent of donor 

kidneys with KDPI between 86 and 100 

percent being discarded.151

In March 2021, OPTN finalized a 

newer allocation policy, which 

eliminated the use of DSAs and regions 

from kidney and pancreas donor 

distribution. These measures were part 

of a framework announced in 2019 that 

also applied to heart, lung, and liver 

donor distribution, with the goal of 

reducing the importance of geography in 

patients’ access to organs, and, instead, 

emphasizing medical urgency.152 153 The 

new system instituted a point system 

with up to 2 points (equal to 2 years on 

the wait list) for patients listed at 

transplant hospitals within 250 nautical 

miles of the donor hospital, and the 

points decreasing linearly from the 

donor hospital to the circle perimeter. 

The more points an individual has, the 

higher their position on the waitlist and 

the more likely they are to receive an 

organ offer. If there is no candidate 

within the designated radius, the kidney 

is offered to patients listed at hospitals 

outside the fixed circle, based on 

separate proximity points that decrease 

linearly as the location of a patient 

approaches 2,500 nautical miles from 

the donor hospital.154

Interested parties within the 

transplant ecosystem commented that 

the new policy might further contribute 

to the increasing rate of donor organ 

non-acceptance. According to one 

review, sharing kidneys over a broader 

geographic region means that OPOs 

would need to work with transplant 

hospitals with which there was no prior 

relationship.155 Concern was also 

expressed about increased 

transportation time and procurement 

costs, risk associated with air transport, 

and a greater number of interactions 

between transplant hospitals and 

OPOs.156 157 158 One study notes that 

policymakers would need to assess the 

extent to which the new kidney 

allocation policy might affect organ offer 

acceptance patterns, organ recovery and 

utilization rates, and wait times both for 

the transplant hospital and broader 


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159Adler et al., 2021. 2012. 

160Cron, D.C., S. Ali Husain, & Adler, J.T. (2022). 

The New Distance-Based Kidney Allocation 

System: Implications for Patients, Transplant 

Centers, and Organ Procurement Organizations. 

Current Transplantation Reports, 9(4), 302–307. 

https://doi.org/10.1007/s40472-022-00384-z. 

161Mohan, Chiles et al. 2018. p. 192. 

162Mohan et al. 2018. p. 195. 

163Mohan et al. 2018. 192. 

164Ojo, A.O., Hanson, J.A., Herwig Ulf MeierKriesche, Chike Nathan Okechukwu, Wolfe, R.R., 

Leichtman, A.B., Agodoa, L.Y., Kaplan, B., & Port, 

F.K. (2001). Survival in Recipients of Marginal 

Cadaveric Donor Kidneys Compared with Other 

Recipients and Wait-Listed Transplant Candidates. 

Journal of the American Society of Nephrology, 

12(3), 589–597. https://doi.org/10.1681/ 

asn.v123589. 

165Massie, A.B., Luo, X., Chow, E.K.H., Alejo, 

J.L., Desai, N.M., & Segev, D.L. (2014). Survival 

Benefit of Primary Deceased Donor Transplantation 

With High-KDPI Kidneys. American Journal of 

Transplantation, 14(10), 2310–2316. https://doi.org/ 

10.1111/ajt.12830. 

166Cohen, J.B., Eddinger, K.C., Locke, J.E., Forde, 

K.A., Reese, P.P., & Sawinski, D. (2017). Survival 

Benefit of Transplantation with a Deceased Diabetic 

Donor Kidney Compared with Remaining on the 

Waitlist. Clinical Journal of the American Society of 

Nephrology, 12(6), 974–982. https://doi.org/ 

10.2215/cjn.10280916. 

167Stewart et al. (2017). 575. 

168Stewart et al. (2017). 585. 

169National kidney Foundation. (2017, February 

10). The Kidney Transplant Waitlist—What You 

Need to Know. National Kidney Foundation. 

https://www.kidney.org/atoz/content/transplantwaitlist. 

170Husain, S.A., King, K.L., Pastan, S., Patzer, 

R.E., Cohen, D.J., Radhakrishnan, J., & Mohan, S. 

(2019). Association Between Declined Offers of 

Deceased Donor Kidney Allograft and Outcomes in 

Kidney Transplant Candidates. JAMA Network 

Open, 2(8), e1910312. https://doi.org/10.1001/ 

jamanetworkopen.2019.10312. 

171Husain et al. 2019. 

172Husain et al. 2019. 

173Wolfe, R.A., Laporte, F., Rodgers, A.M., Roys, 

E., Fant, G., & Leichtman, A.B. (2007). Developing 

Organ Offer and Acceptance Measures: When 

geographic areas.159 Another report 

cited unpublished SRTR data, saying 

that preliminary results suggest an 

increase in the transplant rate overall, 

but a trend toward higher donor kidney 

discard and increased cold ischemia 

time.160

A similar study assessing deceased 

donor kidney discards from 2000 to 

2015 found that 17.3 percent of 212,305 

procured deceased donor kidneys were 

discarded, representing a 91.5 percent 

increase in deceased donor kidney 

discards during the same time period. 

The increase in donor kidney discards 

outpaced the number of organs 

recovered for transplantation, adversely 

impacting transplantation rates and 

waitlist times. Kidneys with higher 

KDPIs and from donors with more 

disadvantageous characteristics were 

more likely to be discarded. The 

estimated 5-year graft survival for even 

the lowest quality kidneys substantially 

exceeds the average 5-year dialysis 

survival rate, making discard patterns 

concerning.161 The study indicates a 

significant overlap in the quality of 

discarded and transplanted deceased 

donor kidneys, and substantial 

geographical variation in the odds of 

donor kidney discards, which, as seen 

previously, would continue to be 

observed in SRTR data for following 

years.162 The study also found patterns 

that indicate factors beyond organ 

quality, including biopsy findings, 

donor history and poor organ function, 

and inability to locate a kidney donor 

recipient, may factor into deceased 

organ acceptance decisions. Other 

factors may be driving the deceased 

donor organ discard rates, as the study 

found that ‘‘discarded organs were more 

likely to come from older, heavier 

donors who were Black, female, 

diabetic, hypertensive, with undesirable 

social behavior and higher terminal 

creatinine.’’ 163 This finding accords 

with observed discard patterns from 

earlier studies whereby recipients of 

marginal kidneys, in terms of advanced 

donor age, hypertension, diabetes, or 

greater cold ischemia time, showed 

lower mortality and greater survival 

benefit for many candidates as 

compared to staying on the transplant 

wait list.164 165 166

Research at this time suggests that 

CMS regulatory requirements and OPTN 

policies may have been contributing to 

transplant hospitals growing more 

selective in choosing organs for their 

waitlisted patients. A study from 2017 

examined OPTN registry data for 

deceased donors from 1987 to 2015, 

showing that changes in the donor pool 

and certain clinical practices explained 

about 80 percent of the increase in nonutilization of deceased donor 

kidneys.167 However, according to the 

study, the remainder of kidney discards, 

not accounted for by these factors, 

suggests that increased risk aversion 

was leading transplant hospitals to be 

more selective about the kidneys they 

accept, regardless of the actual risk 

profile. Furthermore, increasing reliance 

on the part of OPTN, CMS, and private 

insurers on program-specific reports 

that assessed the performance of 

transplant hospitals on transplant graft 

and recipient survival rates might have 

been contributing to the overall trend of 

organs going unused.168

The finding of high rates of non-use 

of organs that could potentially be 

transplanted with positive outcomes has 

led to closer examination of trends 

among transplant hospitals in declining 

the possible use of organs for specific 

patients. Information on each organ that 

is recovered by an OPO is shared with 

the OPTN, which runs the matching 

system that determines which organ 

should be offered to which recipient. If 

an organ is determined to be a good 

match for a particular patient, then the 

OPTN would offer that organ to the 

transplant hospital at which the patient 

is waitlisted on the patient’s behalf.169

A transplant hospital can decline an 

offer without informing the candidate of 

the offer or the reason it was 

declined.170 A study in 2019 focused on 

patient outcomes associated with 

declines in offers of organs by transplant 

hospitals. Using OPTN data, the study 

identified a cohort of 280,041 adults on 

the kidney transplant waitlist (out of 

367,405 candidates on the waitlist from 

2008 through 2015, the study period) 

who received one or more offers for a 

deceased donor kidney during that 

period. More than 80 percent of 

deceased donor kidneys were declined 

on behalf of one or more candidates 

before being accepted for transplant, 

and a mean of 10 candidates who 

previously received an offer died every 

day during the study period.171 As 

reported by transplant hospitals, organ 

or donor quality concerns accounted for 

92.6 percent of all declined offers, 

whereas 2.6 percent of offers were 

refused because of patient-related 

factors, and an even smaller number for 

logistical limitations or other concerns. 

While organ or donor quality concerns 

remained the primary reason for 

declined offers across all KDPI ranges, 

the study observed marked State-level 

variability in the interval between first 

offer and death or transplant and in the 

likelihood of dying while having 

remained on the wait list after receiving 

an offer.172

The methodology and findings of this 

study are notable since they draw a 

correlation between the specific patterns 

among transplant hospitals of organ 

non-acceptance and the longevity of 

patients on the wait list. The tendency 

among certain hospitals to choose to not 

use kidneys for specific patients is 

shown apart from the distinct finding of 

organs going unused and being 

discarded. The study shows the 

potential for a similar effect on patient 

survival from organ offer nonacceptance as for organ non-use. The 

authors of an earlier study commented 

that low acceptance rates of organ offers 

lead to inefficiency, longer ischemia 

time, unequal access to donated 

kidneys, and perhaps to higher rates of 

discarded organs.173 The findings in the 


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‘‘Good’’ Organs Are Turned Down. American 

Journal of Transplantation, 7, 1404–1411. https://

doi.org/10.1111/j.1600-6143.2007.01784.x. 

174OPTN/SRTR 2020 Annual Data Report. 2020. 

Liver. Figures LI 49, 50. 

175OPTN/SRTR 2021 Annual Data Report. 

Pancreas. Figures PA 39, 43. 

176OPTN/SRTR 2021 Annual Data Report. Heart. 

Figure HR 52. 

177Merion, R.M., Schaubel, D.E., Dykstra, D.M., 

Freeman, R.B., Port, F.K., & Wolfe, R.A. (2005). The 

Survival Benefit of Liver Transplantation. American 

Journal of Transplantation, 5(2), 307–313. https:// 

doi.org/10.1111/j.1600-6143.2004.00703.x. 

178Ross, K., Patzer, R.E., Goldberg, D.S., & Lynch, 

R.J. (2017). Sociodemographic Determinants of 

Waitlist and Posttransplant Survival Among EndStage Liver Disease Patients. American Journal of 

Transplantation, 17(11), 2879–2889. https://doi.org/ 

10.1111/ajt.14421. 

179Lai, J.C., Feng, S., & Roberts, J.P. (2012). An 

Examination of Liver Offers to Candidates on the 

Liver Transplant Wait-List. Gastroenterology, 

143(5), 1261–1265. https://doi.org/10.1053/ 

j.gastro.2012.07.105. 

180Moody-Williams, J., Nair, S. Organ 

Transplantation Affinity Group (OTAG): 

Strengthening accountability, equity, and 

performance. CMS Blog, September 15, 2023. 

https://www.cms.gov/blog/organ-transplantationaffinity-group-otag-strengthening-accountabilityequity-and-performance. 

2019 study of a wide range of organ 

offer acceptance rates among transplant 

hospitals nationwide, as well as of the 

relation between organ offer declines 

and patient deaths, suggest the need for 

incentives for transplant hospitals to 

accept earlier offers for their patients, 

which, in turn, could reduce cold 

ischemia time, and, on the whole, 

increase patient survival. 

h. Non-Acceptance and Discards in 

Transplantation for Other Solid Organ 

Types 

SRTR has also tracked the non-use, or 

discard rate, of other solid organ types. 

In 2020, 9.5 percent of livers recovered 

were not transplanted, with livers from 

older donors less likely to be 

transplanted.174 The discard rate for 

pancreases was 23.4 percent in 2020; 

organs from obese donors were highly 

likely not to be transplanted.175 The 

discard rate for hearts in 2020 was one 

percent, having stayed similar over the 

previous decade.176

Liver transplantation shows survival 

benefits for individuals with chronic 

liver disease, but liver transplantation 

suffers from a severe shortage of donor 

organs.177 178 A study from 2012 shows 

organ offer non-acceptance patterns on 

the part of transplant programs affect 

mortality for individuals with end-stage 

liver disease in a similar manner as for 

ESRD patients. According to the study, 

most candidates for a liver transplant 

who died or were removed from the 

wait list had received at least one organ 

offer, suggesting that a substantial 

portion of waitlist mortality results in 

part from declined organ offers.179 As 

the IOTA Model does for kidney 

transplantation, understanding and 

addressing why livers, and possibly 

other organs, are not chosen for specific 

patients also has the potential to lead to 

improved outcomes and longer lives. 

i. Organ Transplant Affinity Group 

On September 15, 2023, CMS 

published a blog post titled ‘‘Organ 

Transplantation Affinity Group (OTAG): 

Strengthening accountability, equity, 

and performance.’’ 180 This blog 

discussed the formation of OTAG, a 

Federal collaborative with staff from 

CMS and HRSA working together to 

strengthen accountability, equity, and 

performance to improve access to organ 

donation, procurement, and 

transplantation for patients, donors, 

families and caregivers, and providers. 

The IOTA Model is a part of this 

coordinated effort from the OTAG and 

relies on input from across CMS and 

HRSA. 

C. Provisions of the Regulation 

1. Implementing the IOTA Model 

In this section III.C of the final rule, 

we discuss our policies for the IOTA 

Model, including model-specific 

definitions and the general framework 

for implementation of the IOTA Model. 

The upside risk payments owed to the 

IOTA participants and the downside 

risk payments owed to CMS are 

designed to increase access to kidney 

transplants for patients with ESRD on 

the IOTA participant’s waitlist. As 

described in section I of this final rule, 

access to kidney transplants varies 

widely by region and across transplant 

hospitals, and disparities by 

demographic characteristics are 

pervasive, raising the need to strengthen 

and improve performance by kidney 

transplant hospitals. We theorize that 

the IOTA Model financial incentives 

will promote improvement activities 

across selected transplant hospitals that 

address access barriers, including 

SDOH, thereby increasing the number of 

transplants, quality of care, and the 

provision of cost-effective treatment. 

Selected transplant hospitals may be 

motivated to revisit processes and 

policies around deceased and living 

donor organ acceptance to identify 

opportunities for improvement. The 

IOTA Model payments incentivize 

selected transplant hospitals to engage 

in care delivery transformation to better 

coordinate and manage patient care and 

needs, invest in infrastructure, improve 

the patient, family, and caregiver 

experience, and engage a care delivery 

team that is tasked with holistic patient 

care. 

a. Model Performance Period 

In section III.C.1.a of the proposed 

rule, we proposed a 6-year ‘‘model 

performance period.’’ We proposed to 

define the model performance period as 

the 72-month period from the model 

start date, comprised of 6 individual 

PYs. The IOTA participants’ 

performance would be measured and 

assessed during the model performance 

period for purposes of determining their 

performance-based payments. We 

proposed to define the ‘‘performance 

year’’ (PY) as a 12-month calendar year 

during the model performance period. 

We proposed to define the start of the 

model performance period as the 

‘‘model start date,’’ and we proposed a 

model start date of January 1, 2025, 

meaning that PY 1 would be January 1, 

2025, to December 31, 2025, and the 

model performance period would end 

on December 31, 2030. We proposed a 

6-year model performance period to 

allow sufficient time for selected 

transplant hospitals to invest in care 

delivery transformation and realize 

returns on investments. 

We alternatively considered a 3- or 5- 

year model performance period; 

however, we believe that a 3-year model 

performance period would be too short 

to allow adequate time for selected 

transplant hospitals to invest in care 

delivery transformations. Additionally, 

our analyses detailed in section V of this 

final rule project that considerable 

savings to Medicare will be achieved 

after the fifth PY, which is another 

reason why we proposed a 6-year model 

performance period. We also considered 

a 10-year model performance period 

similar to some more recent Innovation 

Center models; however, given that this 

is a mandatory model, we felt it was 

important to limit the duration of the 

initial test to a shorter period. 

We alternatively considered 

proposing to begin the IOTA Model on 

April 1, 2025, or July 1, 2025, to allow 

selected transplant hospitals more time 

to prepare to implement the model and 

to better align the model performance 

period with that of our data sources, as 

detailed in section III.C.5.a of this final 

rule. However, we proposed a January 1, 

2025, start date because we believed 

that there would be sufficient time for 

IOTA participants to prepare for the 

model. A proposed start date of January 

1, 2025, also aligned with other CMS 

calendar year rules. We separately 

proposed that in the event the model 

start date is delayed from the proposed 

start date, the model performance 

period for the entire model would be 6 


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181https://www.hrsa.gov/about/news/pressreleases/organ-procurement-transplantationnetwork-modernization-initiative. 

PYs, with each PY being a 12-month 

period that begins on the model start 

date. For example, if the IOTA Model 

were to begin on April 1, 2025, 

‘‘performance year’’ would be defined as 

a 12-month period beginning on the 

model start date, meaning April 1, 2025, 

to March 31, 2026. As a result, the 

model performance period would also 

shift to include a 72-month period from 

the model start date. In this example, 

the model performance period would be 

April 1, 2025, to March 31, 2031. 

We sought comment on the proposed 

model performance period of 6 years 

and the proposed model start date. We 

also sought comment on the alternative 

model performance periods that we 

considered of 3, 5, and 10 years. Finally, 

we sought comment on the alternative 

start dates of April 1, 2025, and July 1, 

2025, and the subsequent adjustments to 

the model performance period if the 

model start date were to change. 

Comment: A few commenters 

supported the proposed model length of 

six years, indicating that is an 

appropriate length of time to be able to 

evaluate a model to determine success. 

Response: We thank the commenters 

for the support and agree a six-year 

model test should provide sufficient 

evidence to determine if the IOTA 

Model is achieving its goals of 

improving quality of care and reducing 

Medicare expenditures. 

Comment: Several commenters 

expressed concern around the six-year 

model performance period. A few 

commenters felt that a post-transplant 

evaluation time horizon of six-years 

contradicts the current OPTN standard 

of one to three years of post-transplant 

follow-up. A few commenters also felt 

that six-years is too long of a model 

performance period as a shorter model 

performance period may allow for more 

immediate assessment and refinement 

and an adjustment period for 

unintended consequences. Finally, a 

commenter felt that the six-year model 

performance period should be 

suspended in the event that CMS 

changes the organ acquisition 

methodology as initially proposed in the 

Fiscal Year 2022 Hospital Inpatient 

Prospective Payment System notice of 

proposed rulemaking in order to first 

evaluate the unintended consequences 

of that proposed change. 

Response: We appreciate commenters 

expressing concern about the six-year 

model performance period. We believe 

a six-year model performance period is 

necessary to allow selected kidney 

transplant hospitals enough time to 

invest in care delivery changes 

necessary for success under the model. 

CMS research also shows that savings to 

the Medicare trust fund occur after at 

least five years of a model performance 

period. We disagree that a six-year 

model performance period contradicts 

current OPTN metrics given that the 

main focus of the model is to increase 

the number of transplants year over 

year, and not to follow post-transplant 

outcomes after six years. We believe the 

composite graft survival ratio discussed 

in section III.C.5.e(1) of this final rule 

does not contradict the OPTN standard 

of one to three years of post-transplant 

follow-up, but rather expands upon 

existing metrics. Furthermore, models 

are constantly evaluated and modified 

even during the model performance 

period through subsequent rulemaking. 

A shorter model performance period is 

not required to make changes 

responsive to IOTA participant 

feedback. 

We recognize that there may be other 

efforts occurring simultaneously with 

the implementation of the IOTA Model, 

such as the OPTN Modernization efforts 

and the implementation of the updated 

OPO Conditions for Coverage. We 

believe these efforts are synergistic 

rather than antagonistic because they 

broadly share the aims of increasing the 

number of successful transplants and 

improve quality outcomes for transplant 

recipients. Therefore, we do not believe 

that we need to make changes to the sixyear model performance period. 

Comment: Several commenters felt 

that the proposed January 1, 2025, 

model start date did not provide 

sufficient time for selected transplant 

hospitals to authorize necessary 

investments, understand updated organ 

offer patterns from the updated kidney 

allocation system, and understand 

model performance goals. A few 

commenters also noted that a January 1, 

2025, start date would fall outside of the 

standard hospital institutional 

budgeting cycle, which would 

complicate implementation 

investments. In response, a few 

commenters supported the alternative 

model start date discussed in the 

proposed rule of July 1, 2025, and a few 

commenters suggested a January 1, 

2026, model start date. 

Response: We appreciate comments 

expressing concerns around the timing 

of this model. We are sensitive to 

commenters’ concerns about the level of 

preparation needed to implement care 

redesign activities and develop 

stakeholder and personnel relationships 

and processes, especially for hospitals 

new to value-based care. As such, we 

are modifying our proposal and 

finalizing a model start date of July 1, 

2025, to allow the selected transplant 

hospitals more time to prepare for 

model implementation, and to allow for 

inclusion of any necessary investments 

as a result of the IOTA Model in the 

annual hospital budget cycle. As 

discussed in section III.C.8 of this final 

rule, several requirements are voluntary 

in this first year to allow IOTA 

participants a grace period to determine 

how they will implement these 

requirements and focus on achieving 

success under the model. 

Comment: A few commenters 

suggested that CMS delay the start of the 

model until after the request for 

proposal process for the OPTN is 

complete, as the possibility of new 

contractors and multiple vendors could 

present a risk for errors to attribution 

which would inhibit beneficiary 

notification and full implementation of 

the program. 

Response: We thank commenters for 

their concern regarding the potential 

overlap between the IOTA Model and 

the OPTN request for proposal process. 

HRSA is in the process of conducting 

their solicitation as part of the OPTN 

Modernization Process. They released 

their first requests for proposals in May 

2024 and are conducting a series of 

procurements to support OPTN 

operations. HRSA has committed to 

ensuring smooth continued operation of 

the transplant system and the OPTN, 

stating that ‘‘while modernization work 

is complex, the integrity of the organ 

matching process is paramount and 

cannot be disrupted.’’ 181 At this time, 

we do not believe that this OPTN 

Modernization Process would disrupt 

the beneficiary attribution process of the 

IOTA Model because attribution status 

is based on waitlisting, which has not 

been subject to any major changes 

during the OPTN modernization 

process. We will continue to monitor 

the operation of the model to determine 

if there are any unforeseen 

circumstances. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

without modification the proposed 

definition of model performance period 

at § 512.402. In light of the public 

comments, we are also finalizing an 

alternative model start date of July 1, 

2025. As such, we are finalizing our 

proposed definition for model start date 

at § 512.402 with slight modification to 

specify a July 1, 2025, model start date, 

and finalizing our proposed definition 

for performance year at § 512.402 with 

modification to specify a 12-month 

period beginning on July 1 and ending 


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the following June 30 of each year 

during the model performance period. 

b. Other Proposals 

We are also finalizing additional 

policies for the IOTA Model, including 

the following: (1) the method for 

selecting transplant hospitals for 

participation; (2) the schedule and 

methodologies for the performancebased payments, and waivers of certain 

Medicare payment requirements solely 

as necessary to test these payment 

methodologies under the model; (3) the 

performance assessment methodology 

for selected transplant hospitals, 

including the proposed methodologies 

for patient attribution, target setting and 

scoring, and calculation of performance 

across the achievement domain, 

efficiency domain, and quality domain; 

(4) monitoring and evaluation; and (5) 

overlap with other Innovation Center 

models and CMS programs. 

We proposed that IOTA participants 

would be subject to the general 

provisions for Innovation Center models 

specified in 42 CFR part 512 subpart A 

and in 42 CFR part 403 subpart K, 

effective January 1, 2025. The general 

provisions at subpart A of part 512 are 

also the subject of revisions in this final 

rule. As described in section II.B. of this 

final rule, we proposed to expand the 

applicability of the general provisions 

for Innovation Center models to provide 

a set of standard provisions for 

Innovation Center models that are 

applicable more broadly across 

Innovation Center models. We believed 

that this approach would promote 

transparency, efficiency, and clarity in 

Innovation Center models and avoid the 

need to restate the provisions in each 

model’s governing documentation. We 

believed that applying these provisions 

to the IOTA Model would also promote 

these purposes. 

We sought comment on our proposal 

to apply the general provisions for 

Innovation Center models, or the 

proposed standard provisions for 

Innovation Center models, to the IOTA 

Model. 

We received no comments on the 

proposal to make IOTA Participants 

subject to the general provisions for 

Innovation Center models, or the 

standard provisions for Innovation 

Center models if they were finalized. 

Therefore, we are finalizing the policy 

as proposed. Since we are finalizing the 

proposed revisions to the standard 

provisions described in section II of this 

final rule with modification, including 

that the standard provisions will apply 

only to the RO Model, the ETC Model, 

and mandatory Innovation Center 

models with performance periods that 

begin on or after January 1, 2025, we are 

also finalizing our proposal to make the 

standard provisions for Innovation 

Center models applicable to the IOTA 

Model. 

2. Definitions 

We proposed at § 512.402 to define 

certain terms for the IOTA Model. We 

describe these proposed definitions in 

context throughout section III of this 

final rule. We proposed to codify the 

definitions and policies of the IOTA 

Model at 42 CFR part 512 subpart D 

(proposed §§ 512.400 through 512.470). 

In addition, we proposed that the 

definitions contained in the general 

provision related to Innovation Center 

models at subpart A of part 512, and the 

revisions to those provisions proposed 

in the notice of proposed rulemaking, 

would also apply to the IOTA Model. 

We sought comment on these proposed 

definitions for the IOTA Model. 

We received no comments on these 

proposals and are therefore finalizing 

the proposed definitions without 

modification at § 512.402. 

3. IOTA Participants 

a. Proposed Participants 

We proposed to define ‘‘IOTA 

participant’’ as a kidney transplant 

hospital, as defined at § 512.402, that is 

required to participate in the IOTA 

Model pursuant to § 512.412. In 

addition, we noted that the definition of 

‘‘model participant’’ contained in 42 

CFR 512.110, as well as the proposed 

revisions to that definition, would 

include an IOTA participant. 

We proposed to define ‘‘transplant 

hospital’’ as a hospital that furnishes 

organ transplants as defined in 42 CFR 

121.2. We proposed this definition to 

align with the definition used by 

Medicare. We proposed to define 

‘‘kidney transplant hospital’’ as a 

transplant hospital with a Medicare 

approved kidney transplant program. A 

transplant program, as defined at 42 

CFR 482.70, is ‘‘an organ-specific 

transplant program within a transplant 

hospital.’’ Kidney transplants are the 

most common form of transplants, but 

not all transplant hospitals have a 

kidney transplant program. As the focus 

of the IOTA Model is kidney 

transplants, we proposed this definition 

of kidney transplant hospital to refer 

specifically to transplant hospitals that 

perform kidney transplants. We 

proposed to define ‘‘kidney transplant’’ 

as the procedure in which a kidney is 

surgically transplanted from a living or 

deceased donor to a transplant 

recipient, either alone or in conjunction 

with any other organ(s). As described in 

section III.B.3.c of this final rule, the 

vast majority of kidney transplants are 

performed alone. However, we believed 

that it is necessary to include in the 

definition of kidney transplant those 

kidney transplants that occur in 

conjunction with other organ 

transplants to avoid creating a 

disincentive for multi-organ transplants 

within the IOTA Model. 

Kidney transplant hospitals are the 

focus of the IOTA Model because they 

are the entities that furnish kidney 

transplants to ESRD patients on the 

waiting list and ultimately decide to 

accept donor recipients as transplant 

candidates. Kidney transplant hospitals 

play a key role in managing transplant 

waitlists and patient, family, and 

caregiver readiness. They are also 

responsible for the coordination and 

planning of kidney transplantation with 

the OPO and donor facilities, staffing 

and preparation for kidney 

transplantation, and oversight of posttransplant patient care, and they are 

largely responsible for managing the 

living donation process. The IOTA 

Model is intended to promote 

improvement activities across selected 

kidney transplant hospitals that reduce 

access barriers, including SDOH, 

thereby increasing the number of 

transplants, quality of care, and costeffective treatment. The IOTA Model 

aims to improve quality of care for 

ESRD patients on the waiting list pretransplant, during transplant, and 

during post-transplant care. As 

described in section III.B.2.a of this final 

rule, kidney transplant access and 

acceptance rates vary nationally across 

kidney transplant hospitals by 

geography and other demographic and 

socioeconomic factors. The Innovation 

Center has implemented models 

targeting dialysis facilities and 

nephrology providers, including in the 

CEC, ETC, and KCC Models. CMS has 

also implemented changes to the OPO 

CfCs to strengthen performance 

accountability for OPOs. However, 

kidney transplant hospitals have not 

been the principal focus of any 

Innovation Center models to date. 

Expanding accountability to kidney 

transplant hospitals—key players in the 

transplantation ecosystem for ESRD 

patients—aligns with the larger efforts 

across CMS and HRSA to improve 

performance and address disparities in 

kidney transplantation. 

We alternatively considered having 

the IOTA participants be accountable 

care organizations (ACOs), such as a 

kidney transplant ACOs, instead of 

individual kidney transplant hospitals. 

In this alternative conception, a kidney 

transplant ACO would form as a 


ddrumheller on DSK120RN23PROD with RULES2
96304 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

182 James. (2024, January 31). FAQ: New Multiorgan polices in effect. UNOS. https://unos.org/ 

news/faq-safety-net-policies-for-multi-organtransplantation/ American Organ Transplant 

Association. (n.d.). Establish eligibility criteria and 

safety net for heart-kidney and lung-kidney 

allocation. U.S. Department of Health and Human 

Services. Retrieved November 9, 2024, from https:// 

optn.transplant.hrsa.gov/policies-bylaws/publiccomment/establish-eligibility-criteria-and-safetynet-for-heart-kidney-and-lung-kidney-allocation/ 

#:∼:text=At%20a%20glance&text=

The%20eligibility%20is%20based%20

on,safety%20net%E2%80%9D%20

for%20these%20patients. 

separate legal entity, potentially 

including kidney transplant hospitals, 

OPOs, transplant surgeons, and other 

provider types. The kidney transplant 

ACO would assume accountability for 

the number of kidney transplants, 

equity in the distribution of transplants, 

and the quality of transplant services 

from the point of a patient being 

waitlisted to after a transplant 

recipient’s condition stabilizes 

following transplantation. This 

alternative would potentially carry some 

advantages in the potential for improved 

coordination among individual 

providers and suppliers in the kidney 

transplant ACO, but we believe that it 

would be administratively burdensome, 

as it would require the formation of an 

ACO governing board distinct from the 

governing boards of individual 

providers. In addition, such an ACO 

arrangement would potentially be 

subject to additional Federal, State, and 

tribal laws with respect to grievance, 

licensure, solvency, and other 

regulations, as well as considerable 

overlap with other ACO-based 

Innovation Center models. We therefore 

proposed to define ‘‘IOTA participant’’ 

as a kidney transplant hospital, as 

defined at § 512.402, that is required to 

participate in the IOTA Model pursuant 

to § 512.412. 

We further alternatively considered 

requiring OPO participation in the IOTA 

Model as the entity charged with 

identifying eligible donors and securing 

organs from deceased donors (89 FR 

43540). However, in 2020, CMS issued 

a final rule that updated OPO CfC 

requirements to receive Medicare and 

Medicaid payment (85 FR 77898). This 

final rule focuses on holding OPOs in 

the transplant ecosystem accountable 

for improving performance, and the 

Innovation Center does not plan further 

interventions regarding OPOs at this 

time. Given the interactions between 

OPOs and transplant hospitals 

throughout the donation process, 

transplant hospitals may wish to 

collaborate or partner with OPOs on 

strategies to increase donation and other 

quality improvement activities. 

We sought public comment on the 

proposal that the IOTA participants 

would be kidney transplant hospitals. 

The following is a summary of the 

comments received on our proposal that 

the IOTA participants would be kidney 

transplant hospitals and our responses: 

Comment: Several commenters 

expressed support for the proposed 

definition of IOTA participants. 

Response: We thank the commenters 

for their support. 

Comment: A commenter sought 

clarification on the definition of 

‘‘kidney transplant’’ and whether safetynet kidney transplants would still be 

counted as kidney transplantations in 

the year following a liver, heart, and/or 

lung transplant(s). 

Response: We thank the commenter 

for their input. As described and 

finalized in this section, kidney 

transplant means the procedure in 

which a kidney is surgically 

transplanted from a living or deceased 

donor to a transplant recipient, either 

alone or in conjunction with any other 

organ(s). 

A September 2023 OPTN proposal 

established criteria for prioritizing 

patients who previously received either 

a heart or lung transplant, and now need 

a kidney transplant. This prioritization 

is referred to as a ‘‘safety net’’ for these 

patients.182 As such, we clarify that 

safety-net kidney transplants will be 

counted as kidney transplantations in 

the year following a liver, heart, or lung 

transplant(s). 

After careful consideration of the 

public comments we received, for the 

reasons set forth in this rule, we are 

finalizing the definitions of IOTA 

participant and kidney transplant at 

§ 512.402 as proposed without 

modification. We did not receive any 

comments on our proposed definitions 

of transplant hospital and kidney 

transplant hospital and are therefore 

finalizing these definitions as proposed 

without modification at § 512.402. 

Additionally, we note that we intend to 

publicly post kidney transplant 

hospitals selected to participate in the 

model and information regarding the 

participant selection process, as 

described and finalized in section 

III.C.3.d(1) of this final rule, and how it 

resulted in the list of DSAs. 

b. Proposed Mandatory Participation 

We proposed that all kidney 

transplant hospitals that meet the 

eligibility requirements contained in 

section III.C.3.c of the proposed rule, 

and that are selected through the 

participation selection process 

contained in section III.C.3.d of the 

proposed rule, would be required to 

participate in the IOTA Model. We 

believe that a mandatory model is 

necessary to ensure that a sufficient 

number of kidney transplant hospitals 

participate in the IOTA Model such that 

CMS will be able to conduct a sound 

evaluation of the model’s effects on cost 

and quality of care in accordance with 

section 1115A(b)(4) of the Act. A 

mandatory model would also minimize 

the potential for selection bias, thereby 

ensuring that the model participants are 

a representative sample of kidney 

transplant hospitals. We believe a 

mandatory model is necessary to obtain 

relevant information about the effects of 

the model’s proposed policies on 

Medicare savings, kidney transplant 

volume, kidney transplant acceptance 

rates, health equity, and quality of care. 

In the proposed rule we stated that, 

nationally, kidney transplant hospitals 

serve diverse patient populations, 

operate in varied organizational and 

market contexts, and differ in size, 

staffing, and capability (89 FR 43541). 

There is also wide variation across 

kidney transplant hospitals on 

performance on kidney transplant 

access and organ offer acceptance rate 

ratios by geography and other 

demographic and socioeconomic 

factors. We believed that selection bias 

would be a challenge in a voluntary 

model because the IOTA Model would 

include financial accountability on 

access to kidney transplants and quality 

of care, as well as downside risk for 

kidney transplant hospitals that score 

poorly on the performance domains. 

Voluntary participation could result in 

certain kidney transplant hospitals 

choosing not to participate in the model 

and ultimately could inhibit the model 

from testing a representative sampling 

of kidney transplant hospitals. We 

explained in the proposed rule that a 

mandatory model would address 

potential selection bias concerns that 

would exist for a voluntary model by 

ensuring that our model reaches ESRD 

patients residing in underserved 

communities and including other 

safeguards against selection bias. 

As described in section III.C.3.b of the 

proposed rule, we alternatively 

considered making participation in the 

IOTA Model voluntary. However, we 

were concerned that a voluntary model 

would not be evaluable, would result in 

insufficient numbers of kidney 

transplant hospital participants, and 

would not be representative of kidney 

transplant hospitals and ESRD patients 

nationally. These concerns reflected our 

expectation that the proposed payment 

approach would disproportionately 

attract kidney transplant hospitals 

already performing well in kidney 

transplant volume, organ offer 


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acceptance rate ratios, and quality of 

care pre- and post-transplantation, as 

they would expect to receive upside risk 

payments. Kidney transplant hospitals 

already positioned to score high in the 

IOTA Model’s achievement, efficiency, 

and quality domains may be more likely 

to join the model than other kidney 

transplant hospitals, as they would 

expect to receive upside risk payments. 

This may be especially true for kidney 

transplant hospitals that would stand to 

benefit the most from a model that 

rewards an increase in the number of 

kidney transplants. We believed that 

selection bias in a voluntary model 

would also limit our ability to assess 

systematic differences in the IOTA 

Model’s effects on kidney transplant 

disparities and may further widen 

disparity gaps for underserved 

communities that stand to lose if the 

model does not reach them. We 

therefore proposed that the IOTA Model 

would be mandatory for all eligible 

kidney transplant hospitals selected for 

participation in the model, as we 

believed this would minimize the risk of 

potential distortions in the model’s 

effects on outcomes resulting from 

hospital self-selection. 

We sought public comment on our 

proposal to make participation in the 

IOTA Model mandatory. 

The following is a summary of the 

comments received on our proposal to 

make participation in the IOTA Model 

mandatory and our responses: 

Comment: Several commenters 

expressed support for requiring 

mandatory participation in the IOTA 

Model. Some commenters expressed 

that mandatory participation would 

help increase access to kidney 

transplants and improve kidney 

transplant outcomes. 

Response: We thank the commenters 

for their support. 

Comment: Several commenters 

expressed concern with making 

participation in the IOTA Model 

mandatory. Commenters shared that 

mandatory participation could 

negatively impact patients. A 

commenter stated that CMS wrongly 

presumes that all IOTA participants 

have the same opportunity for success 

in the model, and that careful analysis 

is required to determine whether IOTA 

Model participation would improve 

quality of care without sacrificing 

financial viability. Moreover, a 

commenter suggested that the nature of 

mandatory models diverts critical 

resources that could be used for patient 

care and instead would redirect 

resources to administrative tasks, 

causing administrative burden, in order 

for transplant hospitals to comply with 

a mandatory model’s unproven and 

experimental requirements. This 

commenter also noted that mandatory 

participation in the IOTA Model could 

be particularly burdensome for hospitals 

operating with small financial margins. 

Response: We thank the commenters 

for their feedback. As described in 

section III.C.3.b of the proposed rule, we 

believe that a mandatory model is 

necessary to ensure that a sufficient 

number of kidney transplant hospitals 

participate in the IOTA Model such that 

CMS will be able to conduct a sound 

evaluation of the model’s effects on cost 

and quality of care. A mandatory model 

would also minimize the potential for 

selection bias, thereby ensuring that the 

model participants are a representative 

sample of kidney transplant hospitals. 

We believe a mandatory model is 

necessary to obtain relevant information 

about the effects of the model’s 

proposed policies on Medicare savings, 

kidney transplant volume, kidney 

transplant acceptance rates, health 

equity, and quality of care. Transplant 

hospitals may have to make upfront 

investments to accommodate the IOTA 

Model’s requirements, but we believe 

that the low volume threshold of 11 

adult kidney transplants performed 

during each of the baseline years, as 

described and finalized in section 

III.C.3.c of this final rule, will 

substantially mitigate the demands 

placed on smaller transplant hospitals. 

Additionally, we do not believe the 

IOTA Model will divert critical or 

financial resources, nor do we believe 

the IOTA Model will negatively impact 

patient care. Rather, we believe the 

incentives of the IOTA Model will 

complement other efforts in relation to 

the transplant ecosystem to enhance 

health and safety outcomes, increase 

transparency, increase the number of 

transplants, and reduce disparities. For 

these reasons, we are finalizing our 

proposal without modification. 

Comment: Multiple commenters 

suggested that introducing a mandatory 

payment model on top of existing 

modernization initiatives would add 

unnecessary disruption, risk, and 

uncertainty to the transplant system. A 

commenter highlighted a specific 

initiative, the OPTN Modernization 

Initiative launched in March 2023, 

which focuses on five key areas: 

technology, data transparency and 

analytics, governance, operations, and 

quality improvement and innovation. A 

commenter also noted that, 

alternatively, a voluntary model would 

minimize disruption for transplant 

programs whose regulatory environment 

is already uncertain. 

Response: We thank the commenters 

for their feedback. We recognize the 

challenges kidney transplant hospitals 

may face as a result of participation in 

the IOTA Model. However, as described 

in section III.C.3.b of the proposed rule, 

we believe that a mandatory model is 

necessary to ensure a sufficient number 

of kidney transplant hospitals 

participate in the IOTA Model such that 

CMS will be able to conduct a sound 

evaluation of the model’s effects on cost 

and quality of care. For these reasons, 

we are finalizing our proposal without 

modification. 

Comment: A commenter suggested 

that the IOTA Model has the same goals 

as the ETC Model, and the commenter 

stated that the ETC Model has not 

indicated any significant increase in 

kidney transplants or significant 

increase in patient placement on kidney 

transplant waitlists or reduced Medicare 

spending. The commenter stated that as 

a result, CMS should not implement a 

similar mandatory model. 

Response: We thank the commenter 

for their feedback. As described in 

section III.A of the proposed rule, this 

model falls within a larger framework of 

activities initiated by the Federal 

Government during the past several 

years and forthcoming in the near future 

to enhance the donation, procurement, 

and transplantation of solid organs. 

Relatedly, as described in section 

III.B.3.b in this final rule, the IOTA 

Model proposes to complement the ETC 

Model and expand kidney model 

participation to kidney transplant 

hospitals, which are a key player in the 

transplant ecosystem, to test whether 

two-sided risk payments based on 

performance increase access to kidney 

transplants for ESRD patients placed on 

the waitlists of participating transplant 

hospitals. We disagree with the 

suggestion that the ETC Model and the 

IOTA Model have the same goals. No 

prior CMS models have focused 

squarely on transplant hospitals in the 

way the IOTA Model does. For these 

reasons, we are finalizing our proposal 

without modification. 

Comment: Several commenters raised 

concerns about bias and disparities as a 

result of mandatory model participation, 

suggesting it could bias the model in 

favor of underperforming transplant 

hospitals or increase disparities for 

underserved populations, such as dualeligible and low-income subsidy 

beneficiaries, or rural transplant 

hospitals already impacted by 

population variability that constricts the 

ease of access to transplant care. 

Response: We thank the commenters 

for their feedback and concern. As 

described in section III.C.3.b of the 


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proposed rule, we believe that a 

mandatory model is necessary to ensure 

that a sufficient number of kidney 

transplant hospitals participate in the 

IOTA Model such that CMS will be able 

to conduct a sound evaluation of the 

model’s effects on cost and quality of 

care. A mandatory model would also 

minimize the potential for selection 

bias, thereby ensuring that the model 

participants are a representative sample 

of kidney transplant hospitals. We 

believe a mandatory model is necessary 

to obtain relevant information about the 

effects of the model’s proposed policies 

on Medicare savings, kidney transplant 

volume, kidney transplant acceptance 

rates, health equity, and quality of care. 

We also believe the burden on smaller 

kidney transplant hospitals will be 

minimized as a result of the low volume 

threshold of 11 adult kidney transplants 

performed during each of the baseline 

years, as described and finalized in 

section III.C.3.c of this final rule. 

Additionally, we do not believe 

mandatory participation in the IOTA 

Model would increase disparities for 

underserved populations such as dualeligibles or low-income subsidy 

beneficiaries, nor for rural transplant 

hospitals. Rather, we believe the IOTA 

Model will incentivize IOTA 

participants to perform a greater number 

of kidney transplants, including those 

for underserved populations. We believe 

that the IOTA Model will encourage 

IOTA participants to address access 

barriers low-income patients often face, 

such as transportation, remaining active 

on the kidney transplant waiting list, 

and making their way through the living 

donation process. Relatedly, while rural 

transplant hospitals face additional 

unique challenges, such as geographic 

difficulties in accessing care, we do not 

believe underserved populations will be 

negatively impacted by the IOTA 

Model’s mandatory nature. Rather, as 

described in section III.B.3.e, differences 

among transplant hospitals in living 

donor kidney donation are correlated 

with geographic region and the number 

of deceased donor kidney 

transplantations performed. This 

underscores the need for initiatives and 

processes among transplant hospitals, 

such as the IOTA Model, to encourage 

living donations to reduce geographic 

disparities. For these reasons, we are 

finalizing our proposal without 

modification. 

Comment: Several commenters 

suggested that a mandatory model has 

financial risks to model participants due 

to high upfront costs related to 

employees and IT support, and that it 

places model participants at significant 

financial risk regardless of their 

readiness for participation. Commenters 

stated that a mandatory model 

effectively cuts compensation for kidney 

transplant hospitals with insufficient 

resources to adequately participate, 

thereby exacerbating resource 

disparities and impacting the viability 

of some transplant programs. 

Commenters also stated that kidney 

transplant hospitals selected to 

participate in the model may opt out of 

performing kidney transplants rather 

than assume the costs of mandatory 

participation. 

Response: We thank the commenters 

for their feedback and concern. As 

described in section III.C.3.b of the 

proposed rule, we believe that a 

mandatory framework is essential to 

ensure that a sufficient number of 

kidney transplant hospitals participate 

in the IOTA Model such that CMS will 

be able to conduct an adequate 

evaluation of the model’s effects on cost 

and quality of care. Kidney transplant 

hospitals selected to participate in the 

model may have to make upfront 

investments to accommodate the IOTA 

Model’s requirements, but we believe 

that the low volume threshold of 11 

adult kidney transplants performed 

during each of the baseline years, as 

described and finalized in section 

III.C.3.c of this final rule, will 

substantially mitigate the demands 

placed on smaller kidney transplant 

hospitals. With several months of lead 

time until the IOTA Model’s start date, 

we believe eligible kidney transplant 

hospitals selected to participate in the 

IOTA Model will be sufficiently 

equipped for participation and success 

in the model. We do not believe 

mandatory participation will cut 

compensation for smaller kidney 

transplant hospitals selected to 

participate in the IOTA Model. Rather, 

mandatory participation in the IOTA 

Model offers a strong financial incentive 

for those transplant hospitals chosen to 

participate. Finally, we believe the twosided performance-based payment 

structure, as described and finalized in 

section III.C.6.a of this final rule, which 

rewards IOTA participants for high 

performance in the achievement, 

efficiency, and quality domains—and 

imposes financial accountability on 

IOTA participants that perform poorly 

on those domains—will encourage 

maximum engagement from IOTA 

participants. For these reasons, we are 

finalizing our proposal without 

modification. 

Comment: Multiple commenters 

showcased the differing opinions 

regarding how the mandatory nature of 

the IOTA Model may impact kidney 

transplant hospitals based on size. Some 

commenters suggested that mandatory 

participation could benefit lowervolume or underperforming kidney 

transplant hospitals that have room to 

grow, while larger-volume kidney 

transplant hospitals with limited 

capacity to grow would incur financial 

and administrative burdens to reach 

their transplant targets. Other 

commenters suggested the IOTA Model 

could negatively impact small kidney 

transplant hospitals financially. or 

increase competition for available 

organs with higher-volume kidney 

transplant hospitals. 

Response: We thank the commenters 

for their support and feedback. IOTA 

participant performance on the 

achievement domain in the IOTA Model 

is measured based on the number of 

transplants performed by the IOTA 

participant in the baseline years and the 

national growth rate as described and 

finalized in section III.C.5.c(1) of this 

final rule. As a result of this metric, we 

believe kidney transplant hospitals— 

including larger-volume programs in the 

IOTA Model—are on equal footing to 

improve their transplant rates in each 

consecutive PY. IOTA participants may 

have to make upfront investments to 

accommodate the IOTA Model’s 

requirements, but we believe that the 

required low volume threshold of 11 

adult kidney transplants performed for 

each kidney transplant hospital in each 

of the baseline years, as described and 

finalized in section III.C.3.c of this final 

rule, will substantially mitigate the 

demands placed on smaller kidney 

transplant hospitals. Additionally, we 

have found that many of these kidney 

transplant hospitals consistently 

perform between 11 and 50 kidney 

transplants annually. We direct readers 

to section III.C.3.c of this final rule for 

a full discussion on why we believe 

provisions within the IOTA Model will 

limit negative impacts to small kidney 

transplant hospitals. 

We recognize that IOTA participants 

face varying challenges based on their 

kidney transplant volumes. However, 

we believe all IOTA participants, 

including high-volume kidney 

transplant hospitals, have opportunities 

to increase the number of kidney 

transplants performed. For example, 

high-volume kidney transplant hospitals 

could focus on improving deceased 

donor organ utilization or supporting 

more living donors. Regardless of each 

IOTA participant’s approach or any 

potential competition, we intend to 

monitor the model for any unintended 

consequences. For these reasons, we are 

finalizing our proposal without 

modification. 


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Comment: A commenter suggested 

that mandatory participation in the 

IOTA Model may be undermined by the 

absence of any meaningful adverse 

consequences when an IOTA 

participant is terminated from the 

model. 

Response: We thank the commenter 

for their feedback. As described and 

finalized in section III.C.16.a of this 

final rule, we may take a variety of one 

or more remedial actions. We believe 

the remedial actions we are finalizing at 

§ 512.464(b) can meaningfully 

discourage noncompliance with the 

IOTA Model requirements. For these 

reasons, we are finalizing our proposal 

without modification. 

Comment: A commenter claimed that 

CMS does not have the authority to 

institute IOTA as a mandatory model, 

while other commenters shared general 

concerns about requiring mandatory 

participation in the model. 

Response: We thank the commenters 

for their feedback and concerns. CMS’ 

testing of innovative payment and 

service delivery models, including the 

IOTA Model, complies with section 

1115A of the Act and other governing 

laws and regulations, including the U.S. 

Constitution. Section 1115A of the Act 

and the Secretary’s authority to operate 

the Medicare program authorize us to 

finalize mandatory participation in the 

IOTA Model for the selected IOTA 

participants. Section 1115A of the Act 

authorizes the Secretary to test 

innovative payment and service 

delivery models expected to reduce 

Medicare costs while preserving or 

enhancing quality of care. The statute 

does not require that models be 

voluntary or be tested first as a 

voluntary model, but rather gives the 

Secretary discretion to design and test 

models that meet certain requirements 

as to spending and quality. Section 

1115A(b)(2)(B) of the Act describes a 

number of payment and service delivery 

models that the Secretary may test, but 

the Secretary is not limited to testing 

just those models. Rather, as specified 

in section 1115A(b)(2) of the Act, 

models to be tested under section 1115A 

of the Act must address a defined 

population for which there are either 

deficits in care leading to poor clinical 

outcomes or potentially avoidable 

expenditures. The IOTA Model 

addresses a defined population (kidney 

transplant waitlist patients) for which 

there are potentially avoidable 

expenditures arising from an inadequate 

number of kidney transplants performed 

each year. 

We chose to make participation in the 

IOTA Model mandatory for the selected 

kidney transplant hospitals to avoid the 

selection bias inherent to any model in 

which providers may choose whether or 

not to participate. Such a design will 

ensure sufficient participation of kidney 

transplant hospitals, which is necessary 

to obtain a diverse, representative 

sample of hospitals that will allow a 

statistically robust test of the model. 

Moreover, the Secretary has the 

authority to establish regulations to 

carry out the administration of the 

Medicare program. Specifically, the 

Secretary has authority under sections 

1102 and 1871 of the Act to implement 

regulations as necessary to administer 

the Medicare program, including testing 

this Medicare payment and service 

delivery model. We note that IOTA is 

not a permanent feature of the Medicare 

program. Rather, IOTA will test 

innovative methods for delivering and 

paying for services covered under the 

Medicare program, which the Secretary 

has clear legal authority to regulate. The 

proposed rule went into detail about the 

provisions of the proposed IOTA Model, 

enabling the public to understand how 

IOTA was designed and could apply to 

affected kidney transplant hospitals. 

and sought comment on the proposed 

model design and policies. As permitted 

by section 1115A of the Act, we are 

testing IOTA within specified 

geographic areas. If the IOTA Model test 

meets the statutory requirements for 

expansion, and the Secretary determines 

that expansion is appropriate, we would 

undertake rulemaking to implement the 

expansion of the scope or duration of 

the IOTA Model to additional 

geographic areas or for additional time 

periods, as required by section 1115A(c) 

of the Act. 

For these reasons, we are finalizing 

our proposal without modification. 

Comment: Multiple commenters 

suggested the IOTA Model should begin 

with a voluntary trial period or be a 

purely voluntary model to minimize 

negative impacts on patients. They 

cautioned that an unintended 

consequence of this mandatory model 

could be a decrease the availability of 

marginal organs for transplantation. 

Several other commenters 

recommended the IOTA Model allow 

self-selection to encourage participation 

from motivated kidney transplant 

hospitals. These commenters suggested 

this would incentivize voluntary 

participation and enable kidney 

transplant hospitals to assess if the 

model is appropriate for their patients. 

Response: We thank the commenters 

for their feedback. As described in 

section III.C.3.b of the proposed rule, we 

believe that a mandatory model is 

necessary to ensure that a sufficient 

number of kidney transplant hospitals 

participate in the IOTA Model such that 

CMS will be able to conduct a sound 

evaluation of the model’s effects on cost 

and quality of care as required by 

section 1115A(b)(4) of the Social 

Security Act. We believe a voluntary 

trial period would inhibit this 

evaluation. 

More specifically, we are concerned 

that a voluntary model would not be 

evaluable, result in insufficient numbers 

of IOTA participants, and not be 

representative of kidney transplant 

hospitals and ESRD patients nationally. 

These concerns reflect our expectation 

that the model’s proposed payment 

approach, as described and finalized in 

section III.C.6 of this final rule, would 

disproportionately attract kidney 

transplant hospitals already performing 

well in kidney transplant volume, organ 

offer acceptance rate ratios, and quality 

of care pre- and post-transplantation. 

Kidney transplant hospitals already 

positioned to score high in the IOTA 

Model’s achievement, efficiency, and 

quality domains may be more likely to 

join the model than other kidney 

transplant hospitals, as they would 

expect to receive upside risk payments. 

In the context of the IOTA Model, we 

believe that a voluntary model could 

result in selection bias and limit our 

ability to assess systematic differences 

in the IOTA Model’s effects on kidney 

transplant disparities. 

As a mandatory model, we also 

believe the IOTA Model will have 

positive impacts on patients and an 

increase in the availability of kidneys. 

Finally, we believe the transplant 

hospitals selected for mandatory 

participation would be motivated to 

increase the number of kidney 

transplants performed due to the 

financial incentives of the model. For 

these reasons, we are finalizing our 

proposal without modification. 

Comment: Several commenters 

expressed concern with making 

participation in the IOTA Model 

mandatory, urging CMS to consider 

geographic factors or the impact of the 

model on smaller kidney transplant 

hospitals. For example, a commenter 

argued that the IOTA Model’s 

mandatory participation component 

must consider geographic location. The 

commenter explained that if the model 

aims to address disparities in transplant 

access for patients of different races, 

ethnicities, socioeconomic statuses, or 

from rural areas, then these factors need 

to be accounted for. The commenter 

stated that they see these factors directly 

impacting their pool of potential living 

donors, who often suffer from the same 

medical and economic conditions as 

their recipients and thus get ruled out. 


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183This example, which appeared in the notice of 

proposed rulemaking, has been clarified to specify 

that the baseline years for each PY would be each 

12-month period beginning January 1, 2021, and 

ending December 31, 2023. 

A commenter from a smaller, rural 

kidney transplant hospital expressed 

concerns about mandatory participation. 

They argued that population density 

varies greatly in their rural state, with 

an uneven distribution. The commenter 

noted this population variation impacts 

both access to transplant care and the 

available donor pool and would require 

additional staffing and resources to 

manage the model effectively. 

Another commenter expressed 

concerns about the impact of the IOTA 

Model on small kidney transplant 

hospitals if participation was made 

mandatory. The commenter suggested 

that a low volume threshold of 100 

kidney transplants, regardless of payer 

type, would be more appropriate. This, 

the commenter believed, would ensure 

small kidney transplant hospitals were 

excluded and protect access to kidney 

transplants in less populated areas. 

Lastly, a commenter recognized that 

the IOTA participants would be kidney 

transplant hospitals. The commenter 

reiterated concerns about the challenges 

that mandatory payment models may 

pose for physician practices. The 

commenter explained that successful 

participation in alternative payment 

models often requires new investments 

in infrastructure and technical 

capabilities, such as sophisticated data 

management, dedicated performance 

assessment resources, and updates to 

electronic medical records. They argued 

that meeting these demands would be 

difficult, if not impossible, for many 

kidney transplant hospitals, especially 

smaller ones. This could set these 

kidney transplant hospitals up for 

failure. The commenter recommended 

that CMS apply exemptions or special 

accommodations, like upside-only risk, 

for small kidney transplant hospitals 

that lack experience with value-based 

payment arrangements, if CMS requires 

future participation in new models. 

Response: We took into consideration 

geographic factors when proposing to 

stratify the DSAs into groups based on 

each DSA’s Census Division and the 

total number of adult kidney transplants 

performed annually across all eligible 

kidney transplant hospitals in each DSA 

during the baseline years for the first 

PY, as described and finalized in section 

III.C.3.d(1). As discussed in the 

proposed rule, we believe selecting 

eligible kidney transplant hospitals from 

these groups of DSAs will ensure that 

the IOTA participants represent eligible 

kidney transplant hospitals nationwide, 

both geographically and in terms of 

annual adult kidney transplant volume 

(89 FR 43542). Additionally, as 

described and finalized in section 

III.C.3.d(1) of this final rule, CMS will 

then select approximately half of all 

DSAs nationwide using a stratified 

sampling methodology, and all eligible 

kidney transplant hospitals in the 

selected DSAs will be required to 

participate in the IOTA Model. 

Additionally, we note that we intend 

to publicly post information regarding 

the selection process and how it 

resulted in the list of DSAs and kidney 

transplant hospitals selected to 

participate in the model. 

Finally, as described and finalized in 

section III.C.3.c of this final rule, we 

will use a low volume threshold of 11 

adult kidney transplants performed 

during each of the baseline years. This 

low volume threshold aligns with the 

minimum requirements for publishing 

CMS data, ensuring the confidentiality 

of Medicare and Medicaid beneficiaries 

by preventing the disclosure of 

information that could identify 

individual beneficiaries. As described at 

89 FR 43541 in the proposed rule, we 

alternatively considered using a higher 

threshold, such as 30 adult kidney 

transplants or 50 adult kidney 

transplants during each of the three 

baseline years. However, we found that 

many kidney transplant hospitals 

consistently perform between 11 and 50 

kidney transplants annually. For these 

reasons, we are finalizing our proposal 

without modification. 

After careful consideration of the 

public comments we received, for the 

reasons set forth in this rule, we are 

finalizing our proposal to make the 

IOTA Model mandatory at § 512.412(c) 

without modification. 

c. Participant Eligibility 

We proposed kidney transplant 

hospital participant eligibility criteria 

that would increase the likelihood that: 

(1) individual kidney transplant 

hospitals selected as IOTA participants 

represent a diverse array of capabilities 

across the performance domains as 

discussed in section III.C.5 of this final 

rule; and (2) the results of the model test 

would be statistically valid, reliable, 

and generalizable to kidney transplant 

hospitals nationwide should the model 

test be successful and considered for 

expansion under section 1115A(c) of the 

Act. 

We proposed that eligible kidney 

transplant hospitals would be those 

that: (1) performed 11 or more kidney 

transplants for patients aged 18 years or 

older annually, regardless of payer type, 

in each of the baseline years (the ‘‘low 

volume threshold’’); and (2) furnished 

more than 50 percent of its kidney 

transplants annually to patients over the 

age of 18 during each of the baseline 

years. We proposed to define ‘‘baseline 

year’’ as a 12-month period within a 3- 

year historical baseline period that 

begins 48 months (or 4 years) before the 

start of each model PY and ends 12 

months (or 1 year) before the start of 

each model PY. For example, if the 

IOTA Model were to start on January 1, 

2025, the 3-year historical baseline 

period would begin January 1, 2021, and 

end on December 31, 2023.183 We 

proposed to define ‘‘non-pediatric 

facility’’ as a kidney transplant hospital 

that furnishes over 50 percent of their 

kidney transplants annually to patients 

18 years of age or older. CMS would 

select approximately half of all DSAs 

nationwide using a stratified sampling 

methodology, and all eligible kidney 

transplant hospitals in the selected 

DSAs would be required to participate 

in the IOTA Model. 

As described in the proposed rule at 

89 FR 43541, the proposed low volume 

threshold of 11 or more kidney 

transplants for ESRD patients aged 18 

years or older during each of the three 

baseline years (as described in section 

I.B.2.b of the proposed rule) would 

exclude low volume kidney transplant 

hospitals from the IOTA Model. We 

believed that these kidney transplant 

hospitals should be excluded from the 

model because they may not have the 

capacity to comply with the model’s 

policies, and because the inclusion of 

this group of kidney transplant hospitals 

in the model would be unlikely to 

significantly alter the overall rates of 

kidney transplantation. We stated that 

we were also proposing a low volume 

threshold of 11 adult kidney transplants 

because it is consistent with the 

minimum thresholds for the display of 

CMS data to protect the confidentiality 

of Medicare and Medicaid beneficiaries 

by avoiding the release of information 

that can be used to identify individual 

beneficiaries. We alternatively 

considered using a higher threshold, 

such as 30 adult kidney transplants or 

50 adult kidney transplants during each 

of the three baseline years. However, we 

found that many kidney transplant 

hospitals consistently perform between 

11 and 50 transplants per year. We 

further believe that using a higher 

threshold would decrease the number, 

size and location of kidney transplant 

hospitals eligible to be selected for 

participation in the IOTA Model, 

thereby limiting the generalizability of 

the model test. We also recognize that 

the number of kidney transplants 


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184A transplant center receives Center of 

Excellence (COE) designation from a private insurer 

when it meets transplant volume and performance 

thresholds. Without this designation, a transplant 

hospital may not be approved by certain private 

insurance companies to complete a transplant 

procedure, which limits the transplant center where 

patients may receive covered care. 

performed by a kidney transplant 

hospital may fluctuate from year to year, 

and looking back three years would help 

determine if a kidney transplant 

hospital has the capacity to consistently 

perform 11 or more transplants per year. 

We sought feedback on this approach 

for determining which kidney 

transplant hospitals would be eligible 

for selection under the model. 

We considered including pediatric 

kidney transplant hospitals as eligible 

participants in the IOTA Model. 

However, pediatric kidney 

transplantation has significantly 

different characteristics, considerations, 

and processes from adult kidney 

transplantation. The number of 

pediatric kidney transplants performed 

each year is also exceedingly small, 

which would present difficulties in 

reliably determining the effects to the 

model in the pediatric population. 

Additionally, a much larger proportion 

of pediatric kidney transplants are 

living donor transplants than in the 

adult population. As such, we do not 

believe the proposed IOTA Model 

would function in the same way for 

both kidney transplant hospitals serving 

primarily adults and those serving 

primarily children, and we believe it is 

necessary to include only non-pediatric 

kidney transplant hospitals in the IOTA 

Model. 

We sought comment on our proposed 

participant eligibility criteria for kidney 

transplant hospitals, including the 

requirement that a kidney transplant 

hospital perform 11 or more kidney 

transplants annually on patients aged 18 

years or older during the baseline years. 

We also sought comment on the 

proposal to include only kidney 

transplant hospitals that meet the 

proposed definition for a non-pediatric 

facility during the baseline years. 

The following is a summary of the 

comments received on our proposed 

participant eligibility criteria for kidney 

transplant hospitals, including the 

requirement that a kidney transplant 

hospital perform 11 or more kidney 

transplants annually on patients aged 18 

years or older during each of the 

baseline years, and the proposal to 

include only kidney transplant hospitals 

that meet the proposed definition for a 

non-pediatric facility during the 

baseline years, and our responses: 

Comment: Several commenters 

expressed support for the IOTA 

participant kidney transplant hospital 

eligibility criteria, as proposed, 

particularly noting the proposed 

eligibility criterion by which a kidney 

transplant hospital must furnish over 50 

percent of their kidney transplants 

annually to patients 18 years of age or 

older. 

Response: We thank the commenters 

for their support. 

Comment: Several commenters 

expressed concern with the proposed 

low-volume kidney transplant threshold 

for IOTA participants. A commenter 

noted that there may be some 

unforeseen or unintended consequences 

of advantaging programs classified as 

‘‘low volume,’’ where the volume is 

close to the dividing line, and vice 

versa. Additional commenters shared 

concerns that the low volume threshold 

of 11 kidney transplants performed will 

disadvantage kidney transplant 

hospitals that furnish a smaller number 

of kidney transplants, as these 

transplant programs do not meet the 

requirements for COE programs and 

have limited contracts with payers, and 

the low volume threshold does not 

ensure statistical significance. Several 

commenters recommended that CMS 

should increase the low volume 

threshold, setting the number of kidney 

transplants at a value such as 25, 50, or 

100, to ensure statistical significance 

and avoid burden on kidney transplant 

hospitals that furnish a smaller number 

of kidney transplants. Finally, a 

commenter suggested CMS should only 

use the number of Medicare kidney 

transplants to determine eligibility, 

rather than 11 kidney transplants across 

all payers. 

Response: We thank the commenters 

for their feedback. To protect the 

confidentiality of Medicare and 

Medicaid beneficiaries, we proposed a 

low volume threshold of 11 adult 

kidney transplants. We believe this lowvolume threshold aligns with the 

minimum standards for CMS data 

display, preventing the release of 

information that could identify 

individual beneficiaries while ensuring 

statistical significance (89 FR 43541). 

We recognize that this could exclude 

smaller kidney transplant programs, 

which may not already meet COE 184

program criteria and have limited 

contact with payers. However, as 

described in the proposed rule, we 

proposed a low volume threshold of 11 

adult kidney transplants to exclude lowvolume kidney transplant hospitals that 

may lack the capacity to comply with 

the model’s policies, as their inclusion 

would be unlikely to significantly 

impact overall kidney transplant rates 

(89 FR 43541). We considered, but did 

not propose, using a higher threshold, 

such as 30 adult kidney transplants or 

50 adult kidney transplants during each 

of the three baseline years (89 FR 

43541). However, we did not propose 

this, as we found that many kidney 

transplant hospitals consistently 

perform between 11 and 50 transplants 

annually. We maintain our belief that a 

higher threshold would reduce the 

number, size, and geographic diversity 

of kidney transplant hospitals eligible 

for the IOTA Model, limiting the 

model’s broader applicability. 

Additionally, we recognize that kidney 

transplant volumes can fluctuate yearto-year. Furthermore, we believe looking 

at a 3-year historical baseline period 

will help assess if a kidney transplant 

hospital has the capacity to consistently 

perform 11 or more kidney transplants 

annually. 

Relatedly, as described in section 

III.C.3.d(2) of this final rule, after the 

IOTA Model’s start date, we do not 

anticipate making any additional 

participant selections, unless 10 percent 

or more of the selected participants are 

terminated during the model’s 

performance period. If that occurs, we 

will address the selection of new IOTA 

participants through future notice and 

comment rulemaking, and we may 

reevaluate the low volume threshold. 

Finally, as described in the proposed 

rule, we considered limiting IOTA 

waitlist and IOTA transplant patients to 

Medicare beneficiaries only, as 

Medicare covers over 50 percent of 

kidney transplants (89 FR 43544). 

However, we ultimately did not propose 

this limitation. We believe restricting 

the IOTA Model assessment to Medicare 

patients would reduce the sample size, 

potentially hindering our ability to 

detect performance changes due to 

model payments. Therefore, we 

proposed, and will be finalizing, that 

the IOTA Model reflect both Medicare 

beneficiaries and non-Medicare patients 

for performance assessment, with 

Medicare beneficiaries being a subset of 

the patient population attributed to each 

model participant. We direct readers to 

section III.C.5 of this final rule for a full 

discussion on the IOTA Model 

performance assessment methodology. 

We believe the same rationale applies 

for kidney transplant hospital eligibility 

criteria. For these reasons, we are 

finalizing our proposal without 

modification. 

Comment: A commenter suggested 

that IOTA participants that furnish a 

smaller volume of kidney transplants 

would have little incentive to engage in 

the model if participant eligibility is 


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based on all kidney transplants, but 

financial incentives and penalties only 

apply to Medicare kidney transplants. 

Response: We thank the commenter 

for their feedback. We considered, 

limiting IOTA waitlist patients and 

IOTA transplant patients to Medicare 

beneficiaries only, as Medicare covers 

more than 50 percent of all kidney 

transplants from both deceased and 

living donors (89 FR 43544). However, 

we believe it’s necessary to include all 

patients, regardless of payer type, in the 

IOTA participant’s performance 

calculations. This protects against 

unintended consequences and 

problematic financial incentives that 

could arise if the IOTA Model only 

applied to specific payer types. 

Additionally, the eligible waitlist and 

transplant patient population attributed 

to each IOTA participant is already 

relatively small, in terms of both 

transplant candidates and recipients. 

Limiting the IOTA Model performance 

assessment, as described in section 

III.C.5 of this final rule, to only 

Medicare beneficiaries would further 

reduce the patient sample size, 

potentially affecting our ability to detect 

changes in performance due to model 

payments. For these reasons, we chose 

not to propose limiting IOTA waitlist 

patients and IOTA transplant patients to 

Medicare beneficiaries only and 

respectfully disagree with the 

commenter. 

Lastly, as described in section III.C.5 

of this final rule, the IOTA Model’s 

performance assessment is inclusive of 

both Medicare and non-Medicare 

patients. We believe this will 

incentivize IOTA participants of all 

sizes and patient populations to fully 

engage in the model regardless of payer 

type. For these reasons, we are 

finalizing our proposal without 

modification. 

Comment: Multiple commenters 

recommended that CMS exclude kidney 

transplant hospitals with high volume, 

high quality, and high efficiency from 

the IOTA Model, and provide additional 

provisions for newer kidney transplant 

hospitals. 

Response: We thank the commenters 

for their feedback. As described in 

section I.B.2.b of the proposed rule, we 

proposed to select the kidney transplant 

hospitals that will be required to 

participate in the IOTA Model from the 

group of eligible kidney transplant 

hospitals using a stratified random 

sampling of DSAs to ensure that there 

is a fair selection process and 

representative group of participating 

kidney transplant hospitals. We believe 

the commenter’s recommendation 

would inhibit a representative sampling 

necessary to the IOTA Model. For these 

reasons, we are finalizing our proposal 

without modification. 

Comment: Several commenters 

suggested CMS should change multiple 

aspects of the proposed participant 

eligibility criteria. Recommendations 

included excluding kidney transplant 

hospitals that have had a transplant 

volume growth of 30 percent or more 

and expanding eligible kidney 

transplant hospitals to include pediatric 

kidney transplant hospitals. 

Response: We thank the commenters 

for their feedback and suggestions. In 

section I.B.2.b of the proposed rule, we 

proposed to select the kidney transplant 

hospitals that will be required to 

participate in the IOTA Model from the 

group of eligible kidney transplant 

hospitals using a stratified random 

sampling of DSAs to ensure that there 

is a fair selection process and 

representative group of participating 

kidney transplant hospitals. We believe 

the commenter’s recommendation 

would inhibit a representative sampling 

necessary to test the proposed model. 

For these reasons, we are finalizing our 

proposal without modification. 

Additionally, regarding the comments 

that CMS consider including pediatric 

kidney transplant hospitals in the IOTA 

Model, we acknowledge the importance 

kidney transplantation for pediatric 

patients. As described at 89 FR 43541 in 

the proposed rule, we considered, 

including pediatric kidney transplant 

hospitals in the IOTA Model. However, 

for the reasons described in section 

III.C.5.c of this final rule, we ultimately 

decided not to propose their inclusion 

as eligible kidney transplant hospitals. 

pediatric kidney transplant hospitals as 

eligible participants in the model. As 

such, we respectfully disagree with 

commenters who argued that pediatric 

kidney transplant hospitals should be 

eligible to participate in the model. 

Finally, as described in the proposed 

rule, we considered offering differential 

credit for transplants by type (89 FR 

43553). With this alternative 

methodology, IOTA participants would 

receive bonus points and score higher 

for transplants that fit into categories 

that lead to more savings, such as living 

donor kidney transplants, high kidney 

donor profile index donors, or preemptive transplants, compared to other 

transplants. However, we chose not to 

propose a methodology that provides 

differential credit for transplants based 

on type, as we believe that counting all 

transplants equally will give IOTA 

participants the flexibility to meet their 

transplant targets. Furthermore, we 

think this approach of treating all 

transplants the same helps minimize the 

potential harm and unintended 

consequences that could arise from a 

methodology that offers differential 

credit based on transplant type. We 

direct readers to section III.C.5.c(2) of 

this final rule for a full discussion on 

alternative methodologies we 

considered for calculating points in the 

achievement domain. For these reasons, 

we are finalizing our proposal without 

modification. 

Comment: A commenter 

acknowledged that CMS proposed to 

define a baseline year as a 12-month 

period within a 3-year historical 

baseline period, that begins 48 months 

(or 4 years) before the start of each 

model PY and ends 12 months (or 1 

year) before the start of each model PY. 

For PY 1 (CY 2025), as proposed, the 

commenter highlighted that the 

proposed 3-year historical baseline 

period consists of CY 2021 through CY 

2023. The commenter supported the 

proposed 3-year historical baseline 

period for PY 1, noting that 2020–2022 

represented a low point in transplant 

activity due to the Public Health 

Emergency (‘‘PHE’’) declared in 

response to the COVID–19 pandemic, 

which reduced the number of kidneys 

transplanted nationally. Additionally, 

the commenter believed that starting 

from this low baseline would help 

ensure more attainable performance 

improvement targets for model 

participants, though they still had 

significant reservations about the 

proposed transplant targets. 

Response: We thank the commenter 

for their support. 

Comment: Multiple commenters 

expressed concern on the inclusion of 

2021 in the baseline years. Specifically, 

a commenter suggested that the 3-year 

historical baseline period should 

exclude transplant data from 2021, as 

the COVID–19 public health emergency 

impacted this performance year. 

Response: We thank the commenters 

for their feedback. As described in 

section III.C.3.c of this final rule, we 

proposed to define ‘‘baseline year’’ as a 

12-month period within a 3-year 

historical baseline period that begins 48 

months (or 4 years) before the start of 

each model PY and ends 12 months (or 

1 year) before the start of each model 

PY. For example, if the IOTA Model 

were to start on July 1, 2025, the 3-year 

historical baseline period would begin 

July 1, 2021, and end on June 30, 2024. 

In this example, the baseline years for 

each PY would be 12-month periods 

beginning July 1, and ending on June 30. 

Relatedly, in response to commenters 

requesting a later start date for the 

model, we are finalizing a July 1, 2025, 

model start date. This will result in the 


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185https://www.srtr.org/reports/opo-specificreports/interactive-report. 

186A complete list of DSAs in the United States 

as of 2022–2023 can be obtained using the data 

reporting tool found on the SRTR website (https:// 

www.srtr.org/reports/opo-specific-reports/ 

interactive-report). 

inclusion of only the latter six months 

of 2021 into the baseline period for the 

first PY. Within the context of the 

COVID–19 pandemic, the nonutilization of deceased donor kidneys in 

2020 rose to the highest level up to that 

time, 21.3 percent. Additionally, the 

number of newly added adult 

candidates to the waitlist increased 11.7 

percent from 2020 to 2021, recovering 

from the pandemic related decline in 

the prior year, and exceeding the 2015– 

2019 CAGR of 9.2 percent. We do not 

believe inclusion of July through 

December of 2021 into the baseline year 

would inhibit the overarching goal of 

the IOTA Model. For these reasons, we 

are finalizing our proposal without 

modification. 

After consideration of the public 

comments we received, we are 

finalizing our proposed provisions for 

participant eligibility criteria for kidney 

transplant hospitals at § 512.412(a) 

without modification. We received no 

comments for the proposed definition of 

non-pediatric facility and are finalizing 

the proposed definitions of nonpediatric facility, and baseline years at 

§ 512.402 without modification. 

d. Participant Selection 

(1) Overview and Process for Participant 

Selection 

In section III.C.c.3.d(1) of the 

proposed rule, we proposed to select 

eligible kidney transplant hospitals for 

participation in the IOTA Model using 

a stratified sampling of approximately 

half of all DSAs nationwide. We stated 

that all kidney transplant hospitals that 

meet the proposed participant eligibility 

criteria described in section III.C.3.c of 

the proposed rule and are located in the 

selected DSAs would be required to 

participate in the IOTA Model. As 

defined in 42 CFR 486.302, a ‘‘Donation 

Service Area (DSA)’’ means a 

geographical area of sufficient size to 

ensure maximum effectiveness in the 

procurement and equitable distribution 

of organs and that either includes an 

entire metropolitan statistical area 

(MSA) or does not include any part of 

such an area and that meets the 

standards of subpart G. A DSA is 

designated by CMS, is served by one 

OPO, contains one or more transplant 

hospitals, and one or more donor 

hospitals. There were 56 DSAs as of 

January 1, 2024. A map of the DSAs can 

be found on the SRTR website.185 CMS 

would use the list of DSAs as it appears 

on January 1, 2024, to select the DSAs, 

and therefore the eligible kidney 

transplant hospitals that would be 

required to participate in the IOTA 

Model. 

We proposed this approach for 

selecting IOTA participants to obtain a 

group of eligible kidney transplant 

hospitals that is representative of kidney 

transplant hospitals from across the 

country in terms of geography and 

kidney transplant volume. We proposed 

to stratify the DSAs into groups based 

on each DSA’s Census Division and the 

total number of adult kidney transplants 

performed annually across all eligible 

kidney transplant hospitals in each DSA 

during the baseline years for the first 

PY. Selecting eligible kidney transplant 

hospitals from these groups of DSAs 

would ensure that the IOTA participants 

are representative of eligible kidney 

transplant hospitals from across the 

nation in terms of geography and the 

volume of adult kidney transplants. 

A second aim of our proposal to select 

eligible kidney transplant hospitals from 

stratified groups of DSAs is to prevent 

distortions on the effects of the model’s 

policies and features on outcomes. Our 

analysis of kidney transplant hospital 

data shows that selecting only some 

eligible kidney transplant hospitals 

within a selected DSA to participate in 

the IOTA Model may shift the supply of 

deceased donor organs from non-IOTA 

participants to IOTA participants within 

the same DSA. The resulting distortions 

would make it difficult to attribute 

changes in outcomes to the model and 

would limit its evaluability. 

Our proposed approach for selecting 

IOTA participants would involve 

stratifying DSAs into groups based on 

the average number of adult kidney 

transplants performed by all eligible 

transplant hospitals located in the DSA 

during the baseline years of PY 1. We 

proposed using this variable to stratify 

the DSAs into groups because increasing 

the total number of adult kidney 

transplants is the primary metric that 

we proposed to use to evaluate the 

IOTA participants’ performance in the 

model. 

The proposed approach for IOTA 

participant selection is as follows: 

• Assign all DSAs to a Census 

Division.186 The Census Bureau 

subdivides the United States into four 

Census Regions (Northeast, Midwest, 

South, and West) which are in turn 

divided into nine Census Divisions. 

CMS would assign each DSA to a single 

Census Division. Due to the New 

England region being both a DSA and a 

Census Division, CMS would combine 

the Middle Atlantic and New England 

Census Divisions for a total of eight 

Census Divisions. If CMS were to keep 

the New England Census Division 

separate, the New England DSA would 

be guaranteed participation in the 

model in subsequent steps. As such, we 

proposed to combine the Middle 

Atlantic and New England Census 

Divisions for the purposes of this 

selection methodology. Some DSAs may 

span several Census Divisions, but most 

DSAs will be assigned to the Census 

Division where the majority of the 

DSA’s population resides according to 

the 2020 Census data. Puerto Rico is the 

only DSA which exists outside of a 

Census Division. This DSA would be 

assigned to the South Atlantic Census 

Division as it is the closest 

geographically. This step would create 

eight Census Division groups, one for 

each Census Division (with the 

exception of the combined Middle 

Atlantic and New England Census 

Divisions, which would be grouped 

together to create one Census Division 

group). 

• Determine the kidney transplant 

hospitals located within each DSA. CMS 

would list out the kidney transplant 

hospitals located within each DSA and 

assigned Census Division group. 

• Identify the eligible kidney 

transplant hospitals located within each 

DSA. CMS would use the criteria noted 

in section III.C.3.c of the proposed rule 

to identify the eligible kidney transplant 

hospitals within each DSA. This step is 

expected to yield approximately 180 to 

200 eligible kidney transplant hospitals 

total across the eight Census Division 

Groups. 

• For each DSA, determine the 

average number of adult kidney 

transplants performed annually across 

all eligible kidney transplant hospitals 

during the baseline years for PY 1. CMS 

would use data from the baseline years 

for PY 1 to determine the average 

number of adult kidney transplants 

performed annually across all of the 

eligible transplant hospitals located in 

each DSA. CMS would sum the number 

of adult kidney transplants performed 

by all of the eligible kidney transplant 

hospitals in a DSA during each of the 

baseline years for PY 1 and divide each 

DSA’s sum by three to determine the 

average number of adult kidney 

transplants furnished annually during 

the baseline years by the eligible kidney 

transplant hospitals located within each 

DSA. 

• Within each Census Division group, 

create two mutually exclusive groups of 

DSAs using the average number of adult 

kidney transplants performed annually 

across the baseline years for PY 1. CMS 


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would separate DSAs assigned to a 

Census Division group into two 

mutually exclusive groups of DSAs 

based on the average number of adult 

kidney transplants performed annually 

across the baseline years for PY 1. The 

two groups within each Census Division 

group would be: (1) DSAs having higher 

numbers of adult kidney transplants 

across the baseline years; and (2) DSAs 

having lower numbers of adult kidney 

transplants across the baseline years. 

Since the average number of adult 

kidney transplants will be different 

across each DSA, each Census Division 

group will have a different cut off to 

create these two groups. To ensure each 

DSA has a 50 percent chance of being 

chosen in step 7, each DSA group 

within a Census Division group should 

have the same number of DSAs. 

However, in the event of an odd number 

of DSAs within a Census Division 

group, CMS would proceed to step six. 

• For groups within a Census Division 

group that contain an odd number of 

DSAs, CMS would randomly select one 

DSA from the group. Each of these 

individual selected DSAs would have a 

50 percent probability of being selected 

for the IOTA Model. For groups within 

a Census Division group that contain an 

odd number of DSAs, CMS would 

randomly select one DSA from the 

group and determine that individual 

DSA’s chance of selection for inclusion 

in the IOTA Model with 50 percent 

probability. Following this step, each 

group within a Census Division group 

would have an even number of DSAs. 

• Randomly select 50 percent of 

remaining DSAs in each group. CMS 

would then take a random sample, 

without replacement, of 50 percent of 

the remaining DSAs in each group (the 

groups being DSAs having higher 

numbers of adult kidney transplants 

across the baseline years and DSAs 

having lower numbers of adult kidney 

transplants across the baseline years) 

within each Census Division group. All 

of the eligible kidney transplant 

hospitals located within the selected 

DSAs would be required to participate 

in the IOTA Model. 

We proposed that CMS would notify 

IOTA participants of their selection to 

participate in the IOTA Model in a form 

and manner chosen by CMS, such as 

public notice and email, at least 3 

months prior to the start of the model 

performance period. As described in 

section III.C.3.b of this final rule, we 

proposed that participation in the IOTA 

Model would be mandatory. As such, if 

an IOTA eligible transplant hospital is 

located within one of the DSAs that 

CMS randomly selects for the IOTA 

Model, the eligible kidney transplant 

hospital would not be able to decline 

participation in this model, nor would 

it be able to terminate its participation 

in the model once selected. Model 

termination policies are further 

discussed in section III.C.16 of this final 

rule. 

We direct readers to section 

III.C.3.d(2) of this final rule for a 

summary of the comments received on 

our proposed approach for selecting 

IOTA participants and our responses. 

(2) Consideration of Alternatives to 

Proposed Participant Selection 

Approach 

We considered using other geographic 

units for stratified random sampling to 

choose IOTA participants, such as Core 

Based Statistical Areas (CBSAs), 

Metropolitan Statistical Areas (MSAs), 

Hospital Referral Regions (HRRs), or 

States (89 FR 43543). CBSAs, MSAs, 

HRRs, and States are commonly known 

geographic units, and have been used as 

part of participant selection for other 

Innovation Center models. We believe 

selecting participants by DSA 

significantly mitigates behavior that 

would artificially inflate the model’s 

effects on kidney transplant volume for 

the reasons described in the preceding 

section. OPOs associated with selected 

DSAs would be expected to benefit from 

consistency in rules across most or all 

of their transplant hospitals. The 

Innovation Center found that selecting 

participants by DSA improved the 

ability to detect changes in kidney 

transplant volume to a level consistent 

with the anticipated change in kidney 

transplant volume associated with the 

model’s payment rules. Participants 

from the same DSA are, for the most 

part, subject to similar levels of kidney 

supply, and, with the exception of 

kidneys from another DSA, the same 

rules for kidney allocation apply. While 

OPTN recently updated its organ 

allocation methodology to allow organs 

to go outside of the DSA in which an 

organ was procured, many kidney 

transplant hospitals still receive a 

plurality of kidneys from the local OPO 

in their DSA, ensuring that this is still 

a meaningful method to group kidney 

transplant hospitals. Using alternative 

geographic units would negate these 

advantages. 

We also considered other random 

sampling techniques, including simple 

random sampling of transplant 

hospitals, simple random sampling of 

DSAs, and cluster sampling of DSAs (89 

FR 43543). Simple random sampling of 

hospitals risks oversampling regions of 

the country where transplant hospitals 

are concentrated and under sampling 

areas with fewer eligible transplant 

hospitals. Using simple random 

sampling of DSAs may result in an 

unrepresentative sample of DSAs with a 

greater risk of oversampling regions 

where DSAs cover small geographic 

areas. We considered cluster random 

sampling where half of all DSAs would 

be sampled in a first step and half of 

eligible kidney transplant hospitals 

within selected DSAs would be 

sampled. However, because this 

approach would retain half of eligible 

kidney transplant hospitals in selected 

DSAs, we expect the model’s effects on 

kidney transplant volume would be 

overstated because kidney supply 

flowing towards non-participant 

hospitals prior to the start of the model 

would be redirected towards IOTA 

participants. In addition, CMS’ analyses 

of these alternative sampling 

approaches indicated the model would 

not be evaluable because these 

approaches were associated with lower 

precision in detecting changes in kidney 

transplant volumes due to the model 

compared to the increase in transplant 

volume anticipated from the model’s 

payment rules. 

As an alternative we also considered 

other variables to create DSA groups for 

stratified sampling of DSAs (89 FR 

43543). Specifically, after assigning each 

DSA to a Census Division, we 

considered stratifying DSAs using the 

following DSA level variables: 

• Number of eligible transplant 

hospitals in DSA. 

• Annual adult kidney transplants 

per eligible transplant hospital in DSA. 

• Average organ offer acceptance rate 

ratio across eligible kidney transplant 

hospitals in DSA. 

• Average percent of Medicare kidney 

transplant recipients dually eligible for 

Medicare and Medicaid or who are LIS 

recipients. 

• Percent of eligible transplant 

hospitals in DSA participating in the 

Kidney Care Choices or ESRD Treatment 

Choices Models. 

• Average percent of kidney 

transplants from a living donor among 

eligible kidney transplant hospitals in 

DSA. 

These variables were given 

consideration in the stratified selection 

approach because their use would create 

groups of DSAs whose eligible 

transplant hospitals are more similar to 

each other on the listed characteristics 

instead of only adult kidney transplant 

volume and Census Division. However, 

we opted to use the simpler stratified 

participant selection approach to 

provide greater transparency in the 

model’s participant selection approach. 

We also considered stratified random 

sampling of individual kidney 


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transplant hospitals using similar 

variables as those described in the 

preceding paragraph (89 FR 43543). 

Although this approach provided 

representativeness of sampled 

transplant hospitals along dimensions 

important for the model, it would be 

expected to result in a subset of eligible 

kidney transplant hospitals in at least a 

portion of DSAs being designated as 

participants. As we have described 

previously, we expect that allowing a 

portion of DSA kidney transplant 

hospitals to be model participants 

would result in an overstatement of the 

model’s effects on kidney transplant 

volume and other outcomes of interest. 

As with the sampling approaches 

considered in the preceding paragraph, 

CMS’ analyses indicated the IOTA 

Model would not be evaluable if 

stratified sampling of individual kidney 

transplant hospitals were used in 

participant selection for the reasons 

described previously. 

As stated at 89 FR 43544 in the 

proposed rule, CMS expects that no 

additional participant selections would 

be made for the IOTA Model after its 

start date unless 10 percent or more of 

selected participants are terminated 

from the model during the model 

performance period. We stated that if 

this were to occur, we would address 

the selection of new participants in 

future rulemaking. 

We sought comment on our proposed 

approach for selecting IOTA 

participants and on the alternative 

approaches considered, including 

perceived advantages and disadvantages 

of our proposed participant selection 

approach relative to alternatives. 

The following is a summary of the 

comments received on our proposed 

approach for selecting IOTA 

participants, on the alternative 

approaches considered, including 

perceived advantages and disadvantages 

of our proposed participant selection 

approach relative to alternatives, and 

our responses: 

Comment: Several commenters shared 

concerns about the participation 

selection method, with a commenter 

suggesting CMS would provide too short 

a notice of selection into the IOTA 

Model prior to the model start date and 

that this poses a challenge to smaller 

transplant programs. Additionally, a 

commenter shared a concern that the 

participant selection criteria highlights 

the significant variance in offer 

acceptance and transplant rates within 

DSAs, suggesting that it would be 

difficult to attribute outcome changes to 

the IOTA Model as a result. 

Response: As described and finalized 

in section III.C.3.d(1) of this final rule, 

we proposed that CMS would notify 

IOTA participants of their selection to 

participate in the IOTA Model in a form 

and manner chosen by CMS, such as 

public notice and email, at least 3 

months prior to the start of the model 

performance period. We believe this is 

in alignment with other Innovation 

Center models and an earlier notice 

would be provided if feasible. For these 

reasons, we are finalizing our proposal 

without modification. 

Additionally, in section III.C.3.d(1) of 

this final rule, we described and 

finalized our approach for selecting 

IOTA participants to obtain a group of 

eligible kidney transplant hospitals that 

is representative of kidney transplant 

hospitals from across the country in 

terms of geography and kidney 

transplant volume. We proposed to 

stratify the DSAs into groups based on 

each DSA’s Census Division and the 

total number of adult kidney transplants 

performed annually across all eligible 

kidney transplant hospitals in each DSA 

during the baseline years for the first 

PY. Selecting eligible kidney transplant 

hospitals from these groups of DSAs 

would ensure that the IOTA participants 

are representative of eligible kidney 

transplant hospitals from across the 

nation in terms of geography and the 

volume of adult kidney transplants. 

A second aim of our proposal to select 

eligible kidney transplant hospitals from 

stratified groups of DSAs is to prevent 

distortions on the effects of the model’s 

policies and features on outcomes. Our 

analysis of kidney transplant hospital 

data showed that selecting only some 

eligible kidney transplant hospitals 

within a selected DSA to participate in 

the IOTA Model may shift the supply of 

deceased donor organs from non-IOTA 

participants to IOTA participants within 

the same DSA. The resulting distortions 

would make it difficult to attribute 

changes in outcomes to the model and 

would limit its evaluability. As a result, 

we do not believe this would cause 

difficulty in attributing resulting 

impacts to the IOTA Model. For these 

reasons, we are finalizing our proposal 

without modification. 

Comment: CMS received several 

comments and recommendations 

regarding participant selection for the 

IOTA Model. Specifically, commenters 

suggested CMS should modify the 

participant selection process in ways 

such as reconsidering the DSA as a 

quantifier, expanding the IOTA Model 

across all transplant programs, and 

providing eligible kidney transplant 

hospitals selected to participate in the 

IOTA Model more than a three-month 

notice prior to the start of the IOTA 

Model. 

Response: We thank the commenters 

for their feedback and suggestions. We 

direct readers to section III.C.3.d(2) of 

this final rule for alternatives that we 

considered. 

We believe that expanding 

accountability to kidney transplant 

hospitals and key stakeholders in the 

transplantation ecosystem for ESRD 

patients, aligns with the larger efforts 

across CMS and HRSA to improve 

performance and address disparities in 

kidney transplantation. As the most 

commonly transplanted organ, and its 

relationship with dialysis, of which 

Medicare is the primary payer, we 

believe focusing this model on kidney 

transplantation is prudent. Relatedly, as 

described in the proposed rule, we 

believe that it is necessary to include in 

the definition of kidney transplant those 

kidney transplants that occur in 

conjunction with other organ 

transplants to avoid creating a 

disincentive for multi-organ transplants 

within the IOTA Model (89 FR 43540). 

Finally, regarding the comments we 

received about providing more than a 

three-month notice to eligible kidney 

transplant hospitals selected to 

participate in the IOTA Model, as 

described and finalized in section 

III.C.3.d(1) of this final rule, we 

proposed that CMS would notify IOTA 

participants of their selection to 

participate in the IOTA Model in a form 

and manner chosen by CMS, such as 

public notice and email, at least three 

months prior to the start of the model 

performance period. We believe this is 

in alignment with other Innovation 

Center models and an earlier notice 

would be provided if feasible. For these 

reasons, we are finalizing our proposal 

without modification at § 512.412(d). 

Comment: Several commenters 

supported the use of stratified sampling 

in selecting IOTA participants. 

Specifically, several commenters 

supported the proposals to use DSAs, to 

group DSAs into Census Divisions, and 

to randomly select 50 percent of all 

eligible kidney transplant hospitals. 

Response: We thank the commenters 

for their support. 

Comment: In the context of the ETC 

Model, a commenter expressed concern 

that the use of stratified DSA sampling 

could penalize IOTA participants based 

on the DSA boundaries. Specifically, the 

commenter suggested that at times in 

the ETC Model, participants were 

penalized for circumstances that were 

largely based on zip code and compared 

to locales on the periphery of their DSA. 

Response: As described and finalized 

in section III.C.3.c of this final rule, 

CMS will select approximately half of 

all DSAs nationwide using a stratified 


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sampling methodology, and all eligible 

kidney transplant hospitals in the 

selected DSAs will be required to 

participate in the IOTA Model. We 

proposed to stratify the DSAs into 

groups based on each DSA’s Census 

Division and the total number of adult 

kidney transplants performed annually 

across all eligible kidney transplant 

hospitals in each DSA during the 

baseline years for the first PY (89 FR 

43542). Within each Census Division 

group, we proposed to create two 

mutually exclusive groups of DSAs 

using the average number of adult 

kidney transplants performed annually 

across the baseline years for PY 1 (89 FR 

43542). Selecting eligible kidney 

transplant hospitals from these groups 

of DSAs would ensure that the IOTA 

participants are representative of 

eligible kidney transplant hospitals from 

across the nation in terms of geography 

and the volume of adult kidney 

transplants. We recognize that kidney 

transplant hospitals in a DSA selected to 

participate in the IOTA Model could be 

adjacent to a DSA not selected to 

participate in the IOTA Model. The 

IOTA Model is looking to measure and 

test whether the provisions of the IOTA 

Model encourage more kidney 

transplants. We do not view this as 

potentially penalizing IOTA 

participants in close proximity to 

kidney transplant hospitals not 

participating in the IOTA Model. 

Rather, we believe this approach 

increases the ability to monitor 

performance improvements in metrics, 

such as an individual IOTA 

participants’ transplant target or its 

organ offer acceptance rate ratio. It also 

helps us distinguish between DSAs and 

other similar geographical regions, 

ensuring accurate comparisons. For 

these reasons, we are finalizing our 

proposal without modification. 

Comment: Several commenters 

asserted that the stratified sampling 

methodology should not use DSAs, as it 

could restrict organ allocation, and that 

average number of kidney transplants in 

a DSA does not provide a true 

representation of kidney transplant 

hospitals. 

Response: We thank the commenters 

for their feedback and suggestions. We 

direct readers to section III.C.3.d(2) of 

this final rule for a full discussion of the 

alternatives that we considered. For 

these reasons, we will be finalizing our 

proposal without modification. 

Comment: Several commenters 

expressed their concerns with the 

proposed stratified sampling 

methodology, suggesting that the 

proposed stratification may advantage 

transplant programs close to the lowvolume threshold. A commenter 

specifically suggested CMS should 

revisit this low volume threshold across 

PYs, since the expectation is that the 

volume of kidney transplants performed 

would progressively increase for kidney 

transplant hospitals selected to 

participate in the IOTA Model. 

Response: We thank the commenters 

for their feedback and 

recommendations. As described and 

finalized in section III.C.5.c(1) of this 

final rule, we proposed that the low 

volume threshold to be 11 kidney 

transplants performed for the purposes 

of calculating the national growth rate. 

We also proposed this approach for 

calculating the national growth rate to 

account for and reflect the growth in 

organ procurement by OPOs that has 

occurred, indicating potential growth in 

the number of available organs. 

Specifically, as described and 

finalized in section III.C.5.c(1) of this 

final rule, we will calculate the national 

growth rate by determining the percent 

increase or decrease of all kidney 

transplants furnished to patients 18 

years of age or older during the relevant 

baseline years, as described and 

finalized in section III.C.3.c of this final 

rule. We direct readers to section 

III.C.5.c(1) of this final rule for a full 

discussion on the calculation of the 

national growth rate. 

Finally, as described in section 

III.C.3.d(2) of the proposed rule, we 

expect that no additional participant 

selections will be made for the IOTA 

Model after its start date unless 10 

percent or more of selected participants 

are terminated from the model during 

the model performance period. If this 

were to occur, we will address the 

selection of new participants in future 

rulemaking and we may revisit the low 

volume threshold of 11 adult kidney 

transplants performed annually in each 

of the baseline years. We would not 

extend the model performance period of 

the IOTA Model. If we were to add any 

new model participants, the IOTA 

participants would participate in the 

model until the end of model 

performance period, as described and 

finalized in section III.C.1.a of this final 

rule. For these reasons, we will be 

finalizing our proposal without 

modification. 

Comment: Several commenters 

requested that CMS provide clarification 

on the stratified sampling methodology. 

Specifically, how CMS would randomly 

select one DSA, the distinction between 

high transplant volume or low 

transplant volume groups, and the 

threshold for dividing DSAs by 

transplant volume. 

Response: We thank the commenters 

for their feedback. As described and 

finalized in section III.C.3.d(1) of this 

final rule, for groups within a Census 

Division group that contain an odd 

number of DSAs, CMS would randomly 

select one DSA from the group. Each of 

these individual selected DSAs would 

have a 50 percent probability of being 

selected for the IOTA Model. For groups 

within a Census Division group that 

contain an odd number of DSAs, CMS 

would randomly select one DSA from 

the group and determine that individual 

DSA’s chance of selection for inclusion 

in the IOTA Model with 50 percent 

probability. Following this step, each 

group within a Census Division group 

would have an even number of DSAs. 

As described and finalized in section 

III.C.3.d(1) of this final rule, CMS would 

then randomly select 50 percent of 

remaining DSAs in each group. CMS 

would then take a random sample, 

without replacement, of 50 percent of 

the remaining DSAs in each group (the 

groups being DSAs having higher 

numbers of adult kidney transplants 

across the baseline years and DSAs 

having lower numbers of adult kidney 

transplants across the baseline years) 

within each Census Division group. All 

of the eligible kidney transplant 

hospitals located within the selected 

DSAs would be required to participate 

in the IOTA Model. For these reasons, 

we are finalizing our proposal without 

modification. 

Comment: Several commenters 

recommended that CMS stratify kidney 

transplant hospitals based on their size 

and reassess the threshold separating 

low-volume and high-volume kidney 

transplant hospitals. 

Response: As described in section 

III.C.3.d(2) of the proposed rule, we 

considered alternatives to the proposed 

participant selection methods. We 

believe selecting model participants by 

DSA significantly mitigates behavior 

that would artificially inflate the 

model’s effects on kidney transplant 

volume for the reasons described in the 

preceding section. OPOs associated with 

selected DSAs would be expected to 

benefit from consistency in rules across 

most or all of their transplant hospitals. 

We considered alternative variables to 

create DSA groups for stratified 

sampling of DSAs. One alternative 

consideration included stratifying DSAs 

by annual adult kidney transplants per 

eligible transplant hospital in DSA (89 

FR 43543). This and other variables 

were given consideration in the 

stratified selection approach, however, 

we opted to use the simpler stratified 

participant selection approach to 

provide greater transparency in the 


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model’s participant selection approach. 

We direct readers to section III.C.3.d(2) 

of this final rule for a full discussion of 

alternative participant selection 

approaches and variables that we 

considered. 

Additionally, as described and 

finalized in section III.C.3.d(1) this final 

rule, two groups within each Census 

Division group would be: (1) DSAs 

having higher numbers of adult kidney 

transplants across the baseline years; 

and (2) DSAs having lower numbers of 

adult kidney transplants across the 

baseline years. Since the average 

number of adult kidney transplants 

would be different across each DSA, 

each Census Division group would have 

a different cut off to create these two 

groups. We believe this is an 

appropriate distinction between lowvolume and high-volume kidney 

transplant hospitals. For these reasons, 

we will be finalizing our proposal 

without modification. 

Comment: Multiple commenters 

suggested that CMS should establish 

control groups within the same 

geographical area in order to increase 

the ability to monitor performance 

improvements and distinguish within 

DSAs to ensure accurate comparisons. 

Response: We thank the commenters 

for their feedback and suggestions. As 

described and finalized in section 

III.C.3.c of this final rule, CMS would 

select approximately half of all DSAs 

nationwide using a stratified sampling 

methodology, and all eligible kidney 

transplant hospitals in the selected 

DSAs would be required to participate 

in the IOTA Model. Selecting eligible 

kidney transplant hospitals from these 

groups of DSAs would ensure that the 

IOTA participants are representative of 

eligible kidney transplant hospitals from 

across the nation in terms of geography 

and the volume of adult kidney 

transplants. As described and finalized 

in section III.C.3.d(1) of this final rule, 

within each Census Division group, we 

would create two mutually exclusive 

groups of DSAs using the average 

number of adult kidney transplants 

performed annually across the baseline 

years for PY 1. CMS would separate 

DSAs assigned to a Census Division 

group into two mutually exclusive 

groups of DSAs based on the average 

number of adult kidney transplants 

performed annually across the baseline 

years for PY 1. We believe this approach 

increases the ability to monitor 

performance improvements and 

distinguish within DSAs and similar 

geographical areas to ensure accurate 

comparisons. For these reasons, we will 

be finalizing our proposal without 

modification. 

After consideration of the public 

comments we received, we are 

finalizing our proposed provisions for 

the sampling methodology, participant 

selection process, and notifying IOTA 

participants of their selection to 

participate in the IOTA Model at 

§§ 512.412(b), 512.412(c) and 512.412(d) 

without modification. We are also 

finalizing as proposed the definition of 

donation service area (DSA) at 

§ 512.402, with a minor technical 

correction to include the complete cross 

reference to subpart G. 

4. Patient Population and Attribution 

a. Proposed Attributed Patient 

Population 

We proposed that the following 

patients who are alive at the time CMS 

conducts attribution would be attributed 

to an IOTA participant: (1) A kidney 

transplant waitlist patient, as defined in 

section III.C.4.a of this final rule, 

regardless of payer type and waitlist 

status, who is alive, 18 years of age or 

older, and is registered on a waitlist, as 

defined in section III.C.4.a of this final 

rule, to one or more IOTA participants, 

as identified by the OPTN computer 

match program (‘‘IOTA waitlist 

patient’’); and (2) A kidney transplant 

patient who receives a kidney transplant 

at the age of 18 years or older from an 

IOTA participant at any time during the 

model performance period (‘‘IOTA 

transplant patient’’). These patients 

would be referred to as IOTA waitlist 

patients and IOTA transplant patients, 

respectively, for purposes of assessing 

each IOTA participant’s performance 

across the achievement domain, 

efficiency domain, and quality domain 

as discussed in section III.C.5 of this 

final rule. IOTA waitlist patients and 

IOTA transplant patients would factor 

into the model’s performance-based 

payments to IOTA participants. 

For the purpose of this model, we 

proposed to define ‘‘waitlist’’ as a list of 

transplant candidates, as defined in 42 

CFR 121.2, registered to the waiting list, 

as defined in § 121.2, and maintained by 

a transplant hospital in accordance with 

42 CFR 482.94(b). We proposed to 

define ‘‘kidney transplant waitlist 

patient’’ as a patient who is a transplant 

candidate, as defined in § 121.2, and 

who is registered to a waitlist for a 

kidney at one or more kidney transplant 

hospitals. 

We understand that many patients on 

the waiting list are registered at multiple 

transplant hospitals. Therefore, we 

proposed attributing each of these 

waitlisted patients to every IOTA 

participant where they are registered on 

a waitlist during a given month in the 

applicable quarter. However, ‘‘kidney 

transplant patient,’’ defined as a patient 

who is a transplant candidate, as 

defined in § 121.2, and received a 

kidney transplant furnished by a kidney 

transplant hospital, regardless of payer 

type, would be attributed to the IOTA 

participant that furnished the kidney 

transplant. 

We proposed attributing kidney 

transplant waitlist patients and kidney 

transplant recipients to IOTA 

participants for two reasons. First, we 

believe that by attributing these patients 

to IOTA participants it would ensure 

the full population of potential and 

actual kidney transplant candidates is 

represented when measuring participant 

performance. The waiting list captures 

most candidates except some living 

donor recipients. Transplant recipients 

include those who received deceased or 

living donor transplants. Second, 

because CMS is proposing to hold IOTA 

participants accountable for furnishing 

kidney organ transplants; focusing on 

kidney transplant waitlist patients and 

kidney transplant patients, and 

attributing them to IOTA participants, 

aligns with the model’s goals of 

improving access to, and quality of, 

kidney transplantation, including posttransplant. 

CMS proposed to determine an IOTA 

participant’s performance across the 

achievement domain, efficiency 

domain, and quality domain based on 

all IOTA waitlist patients and IOTA 

transplant patients, regardless of payer 

type, as described in section III.C.5 of 

this final rule. That is, an IOTA 

participant’s performance in terms of 

both Medicare beneficiaries and nonMedicare patients would be used to 

determine whether the IOTA participant 

would receive an upside risk payment 

from CMS, or owe a downside risk 

payment to CMS. As described in 

section III.C.6.c(2) of this final rule, 

demand for kidney transplants far 

exceeds supply, raising concerns that if 

the IOTA Model were limited to 

Medicare beneficiaries only, the model 

may inadvertently incentivize 

inappropriate diversion of donor organs 

to Medicare beneficiaries to improve 

their performance in the model, thereby 

limiting access to non-Medicare 

beneficiaries and potentially 

disincentivizing pre-emptive kidney 

transplants for patients not already 

covered by Medicare because their CKD 

has not progressed to ESRD. We believe 

that the change in care patterns that 

IOTA participants may undertake to be 

successful in the IOTA Model are 

unlikely to apply solely to Medicare 

beneficiaries under their care. 


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We considered limiting IOTA waitlist 

patients and IOTA transplant patients to 

Medicare beneficiaries only, as 

Medicare covers more than 50 percent 

of all kidney transplants from both 

deceased and living donors. However, 

we believe it is necessary to include all 

patients, regardless of payer type, in the 

IOTA participant’s performance 

calculations to protect against 

unintended consequences and 

problematic financial incentives. 

Moreover, the group of eligible waitlist 

and transplant patients that would be 

attributed to each IOTA participant is 

already relatively small, both in terms of 

transplant candidates and transplant 

recipients. Limiting the IOTA Model 

performance assessment, as described in 

section III.C.5.b of this final rule, to 

Medicare beneficiaries would further 

limit the patient sample size, potentially 

affecting our ability to detect changes in 

performance due to model payments. 

Therefore, we proposed that the IOTA 

Model reflect both Medicare 

beneficiaries and non-Medicare patients 

for performance assessment, with 

Medicare beneficiaries just being a 

subset of the patient population 

attributed to each model participant. 

We sought public comment on our 

proposals to include: (1) all kidney 

transplant waitlist patients, regardless of 

payer type and waitlist status, who are 

alive, 18 years of age or older, and 

registered on a waitlist to an IOTA 

participant, as identified by the OPTN 

computer match program; and (2) all 

kidney transplant patients who receive 

a kidney transplant, at 18 years of age 

or older, from an IOTA participant at 

any time during the model performance 

period, in each IOTA participant’s 

population of attributed patients. We 

also sought public comment on our 

proposal to attribute IOTA waitlist 

patients and IOTA transplant patients, 

respectively, to IOTA participants for 

the purposes of assessing each IOTA 

participant’s performance across the 

achievement domain, efficiency 

domain, and quality domain, and to 

determine performance-based payments 

to and from IOTA participants. 

The following is a summary of the 

comments received and our responses: 

Comment: We received several 

comments in support for the proposed 

attributed patient population, including 

the all-payer attribution approach and to 

allow patients to have multiple 

attributions when on the waitlist for one 

or more transplant hospitals, as this 

provision ensures the most patients can 

benefit from the model. 

Response: We thank the commenters 

for their support. 

Comment: We received a comment 

requesting CMS clarify if multi-organ 

transplants would be counted the same 

as single organ kidney transplants. 

Response: We thank the commenter 

for their feedback. As described in 

section III.B.3.c of the proposed rule, the 

vast majority of kidney transplants are 

performed alone. However, we believe 

that it is necessary to include in the 

definition of kidney transplant those 

kidney transplants that occur in 

conjunction with other organ 

transplants to avoid creating a 

disincentive for multi-organ transplants 

within the IOTA Model. As defined at 

§ 512.402, kidney transplant means the 

procedure in which a kidney is 

surgically transplanted from a living or 

deceased donor to a transplant 

recipient, either alone or in conjunction 

with any other organ(s). 

Comment: We received a comment 

suggesting CMS should monitor for 

unintended consequences, such as 

systemic biases, as a result of including 

all payer types among attributed 

patients. 

Response: We thank the commenter 

for their suggestion. We direct readers to 

comment responses noted previously for 

further discussion. For these reasons, 

we are finalizing our proposal without 

modification. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

these provisions at § 512.414 with slight 

modification. Specifically, we are 

modifying the regulatory text at 

§ 512.414(a)(1)(iii) to specify 

determining performance-based 

payments paid to or by IOTA 

participants. We did not receive any 

comments on the proposed definition of 

IOTA waitlist patient, kidney transplant 

waitlist patient, kidney transplant 

patient or waitlist and therefore are 

finalizing these definitions without 

modification at § 512.402. We are also 

making a minor technical correction to 

the proposed definition of IOTA 

transplant patient at § 512.402 to update 

the cross reference. Specifically, we are 

removing the cross reference to 

§ 512.412(b)(2) and replacing it with 

§ 512.414(b)(2). As such, we are 

finalizing the definition of IOTA 

transplant patient at § 512.402 to mean 

a kidney transplant patient who receives 

a kidney transplant at the age of 18 

years of age or older from an IOTA 

participant at any time during the model 

performance period and meets the 

criteria set forth in § 512.414(b)(2). 

b. Patient Attribution Process 

As described in section III.C.4.a of 

this final rule, we proposed to define 

‘‘attribution’’ as the process by which 

CMS identifies patients for whom each 

IOTA participant is accountable during 

the model performance period. CMS 

would identify and assign a set of 

Medicare and non-Medicare patients to 

the IOTA participant through 

attribution. We proposed to define 

‘‘attributed patient’’ as an IOTA waitlist 

patient or an IOTA transplant patient, as 

described in section III.C.4.a of this final 

rule. We proposed that a patient may 

not opt out of attribution to an IOTA 

participant under the model. 

Section III.C.4.b(1) of this final rule 

outlines in more detail the attribution 

criteria to identify attributable kidney 

transplant waitlist patients and kidney 

transplant patients during initial 

attribution, quarterly attribution, and at 

annual attribution reconciliation using 

Medicare claims data, Medicare 

administrative data, and OPTN data. In 

advance of the model start date, we 

proposed to attribute patients to IOTA 

participants through an initial 

attribution process described in section 

III.C.4.b(2) of this final rule; quarterly 

attribution would be conducted 

thereafter to update the patient 

attribution list, as described in section 

III.C.4.b(3) of this final rule, to include 

the dates in which patient attribution 

changes occur. After the fourth quarter 

of each PY, we proposed to finalize each 

IOTA participant’s annual attribution 

reconciliation list for that PY, including 

removing certain attributed patients, as 

described in section III.C.4.b(4) of this 

final rule. We proposed that once a 

patient is attributed to an IOTA 

participant, that attributed patient 

would remain attributed to the IOTA 

participant for the duration of the 

model, unless the patient is removed 

from the IOTA participant’s list of 

attributed patients during the annual 

attribution reconciliation process, as 

described in section III.C.4.b(4) of this 

final rule. 

We also considered proposing that 

once a patient is attributed to an IOTA 

participant, either through the initial 

attribution process or through quarterly 

attribution, that the patient would 

remain attributed only through the end 

of the PY. Initial attribution would then 

occur prior to the beginning of each PY. 

However, we choose to align with the 

attribution processes of our other kidney 

models to simplify operations. 

We proposed to identify kidney 

waitlist patients and kidney transplant 

patients using SRTR data, OPTN data, 

Medicare claims data, and Medicare 

administrative data. 

We sought comment on our patient 

attribution process proposals and 

alternatives considered. 


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The following is a summary of the 

comments received on our proposed 

patient attribution process proposals 

and alternatives considered and our 

responses: 

Comment: We received several 

comments requesting clarity from CMS 

on certain categories of attributed 

patients, as well as seeking clarity on 

what CMS defines as an attributed 

patient. Specifically, we received 

comments requesting CMS to clarify if 

any patients are excluded from 

calculations related to the IOTA Model 

in the context of kidney/pancreas 

candidates and others such as those 

with a high panel reactive antibody test, 

re-transplanted patients, or safety-net 

kidney recipients. 

Response: As described and finalized 

in section III.C.4.b of this final rule, we 

define attributed patient as an IOTA 

waitlist patient or an IOTA transplant 

patient. As described and finalized in 

section III.C.4.a of this final rule, an 

IOTA waitlist patient is a kidney 

transplant waitlist patient, as defined 

and finalized in section III.C.4.a of this 

final rule, regardless of payer type and 

waitlist status, who is alive, 18 years of 

age or older, and is registered on a 

waitlist, as defined and finalized in 

section III.C.4.a of this final rule, to one 

or more IOTA participants, as identified 

by the OPTN computer match program; 

and an IOTA transplant patient is a 

kidney transplant patient who receives 

a kidney transplant at the age of 18 

years or older from an IOTA participant 

at any time during the model 

performance period. 

Additionally, as described and 

finalized in section III.C.5.d(1)(a) of this 

final rule, we proposed to use and 

calculate the OPTN organ offer 

acceptance rate ratio in accordance with 

OPTN’s measure specifications and 

SRTR’s methodology as the metrics that 

would determine IOTA participants’ 

performance on the efficiency domain 

outlined in equation 1 in paragraph 

(b)(1) of § 512.426. As it pertains to 

kidney/pancreas candidates, included 

in this organ offer acceptance ratio are 

offers to candidates on a single organ 

waitlist (except for kidney/pancreas 

candidates that are also listed for kidney 

alone). Excluded from this measure are 

offers to multi-organ candidates (except 

for kidney/pancreas candidates that are 

also listed for kidney alone). 

In addition, paragraph (b)(1) at 

§ 512.428 describes the composite graft 

survival rate equation used in 

determining the IOTA participant’s 

quality domain score. As it pertains to 

kidney/pancreas candidates and retransplant candidates, CMS excludes 

them from the numerator when 

calculating the composite graft survival 

rate. 

As proposed, we do not exclude any 

patients with high panel reactive 

antibody tests or safety-net kidney 

recipients from IOTA Model measures. 

For these reasons, we are finalizing our 

proposal without modification. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

the patient attribution process at 

§ 512.414(a) and the definitions of 

attribution and attributed patient at 

§ 512.402 as proposed without 

modification. 

(1) Attribution and De-attribution 

Criteria 

(i) IOTA Waitlist Patient Attribution 

We proposed that kidney transplant 

waitlist patients would be attributed as 

IOTA waitlist patients to one or more 

IOTA participants based on where the 

patient is registered on a kidney 

transplant waitlist, regardless of payer 

type and waitlist status, as identified by 

the OPTN computer match program. We 

proposed that CMS would conduct 

attribution on a quarterly basis, before 

each quarter of the model performance 

period. CMS is proposing to attribute a 

kidney transplant waitlist patient as an 

IOTA waitlist patient to an IOTA 

participant if the patient meets all of the 

following criteria: 

• The patient is registered to one or 

more IOTA participant’s kidney 

transplant waitlist during a month in 

the applicable quarter. 

• The patient is 18 years or older at 

the time of attribution. 

• The patient is alive at the time of 

attribution. 

For purposes of attributing IOTA 

waitlist patients to IOTA participants, 

the proposed criteria must be met on the 

date that CMS runs attribution, as 

described in section III.C.4.b(1)(i) of this 

final rule. 

As described in section III.C.4.b(1) of 

this final rule, a kidney transplant 

waitlist patient may be registered to 

more than one waitlist, which is why 

we proposed to attribute kidney 

transplant waitlist patients as IOTA 

waitlist patients to IOTA participants in 

a way that accurately reflects their 

waitlist registrations. A kidney 

transplant hospital should be actively 

engaged in coordinating the transplant 

process for kidney transplant waitlist 

patients on their waitlist, as they are 

responsible for accepting donor organs 

and furnishing transplants. As such, if 

a kidney transplant waitlist patient is 

registered on the waitlist of multiple 

IOTA participants, CMS would attribute 

that kidney transplant waitlist patient as 

an IOTA waitlist patient to all of the 

IOTA participants that have the kidney 

transplant waitlist patient on their 

waitlists. 

We alternatively considered limiting 

IOTA waitlist patient attribution to only 

one IOTA participant based on ‘‘active’’ 

waitlist status. That is, the IOTA waitlist 

patient would be attributed to each 

IOTA participant where the patient is 

registered to a kidney transplant waitlist 

with an ‘‘active’’ status in a given 

quarter. A kidney transplant hospital 

designates patients on its waitlist with 

an ‘‘active’’ status to signal their 

readiness to receive a donor kidney offer 

when one becomes available. However, 

we anticipate that there would be 

operational challenges if CMS were to 

base patient attribution on waitlist 

‘‘active’’ status, as doing so would 

require real-time and accurate 

information regarding each patient’s 

waitlist status. There may be a time 

delay when changing a waitlist status 

from provisionally inactive to active 

once minor issues have been resolved. 

A kidney transplant waitlist patient may 

be made inactive or ineligible to receive 

an organ offer if, for example, they have 

an incomplete transplant evaluation to 

assess medical readiness, their BMI 

exceeds the transplant hospital’s 

established threshold, due to infection 

or patient choice, or because of 

complications presented by other 

medical issues. Additionally, due to our 

inability to recognize differences in the 

contributions between kidney transplant 

hospitals in maintaining a patient’s 

transplant readiness, we believe 

attributing kidney transplant waitlist 

patients as IOTA waitlist patients to all 

the IOTA participants where a kidney 

transplant waitlist patient is registered 

is the most appropriate approach to 

IOTA waitlist patient attribution, 

regardless of waitlist status. 

As indicated in section III.C.3.c of this 

final rule, we are only proposing to 

include non-pediatric facilities as 

eligible participants in the IOTA Model. 

In alignment with this proposal, we 

proposed to exclude pediatric patients 

under 18 years of age from the 

population of attributed patients. 

According to national data from the 

OPTN, children under the age of 18 

make up a small proportion of the 

kidney transplant candidates registered 

on the waiting list. However, pediatric 

patients have greater access to both 

deceased and living donor kidney 

transplant relative to adults. Pediatric 

patients under 18 years of age are also 

infrequently the recipient of organs at 


ddrumheller on DSK120RN23PROD with RULES2
96318 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

187Lentine, K.L., Smith, J.M., Miller, J.M., 

Bradbrook, K., Larkin, L., Weiss, S., Handarova, 

D.K., Temple, K., Israni, A.K., & Snyder, J.J. (2023). 

OPTN/SRTR 2021 Annual Data Report: Kidney. 

American journal of transplantation: official journal 

of the American Society of Transplantation and the 

American Society of Transplant Surgeons, 23(2 

Suppl 1), S21–S120. https://doi.org/10.1016/ 

j.ajt.2023.02.004. 

high risk for non-use.187 Thus, CMS did 

not propose to include pediatric 

patients under the age of 18 as part of 

the population that would be identified 

and attributed to IOTA participants. We 

alternatively considered including 

pediatric patients under the age of 18 in 

the IOTA Model patient population, but 

believe focusing on adults, given their 

unique challenges accessing kidney 

transplants, is a priority. 

The waiting list often has a delay 

between when a patient’s waitlist status 

changes and when that change is 

reflected in the data. For example, 

patients who have died are ineligible for 

transplant and must be removed from 

the waiting list, but there may be a time 

delay between a patient’s death and 

their removal. Thus, we proposed to 

limit IOTA waitlist patient attribution to 

patients who are alive at the time of 

attribution. 

We sought comment on our proposed 

criteria for identifying and attributing 

kidney transplant waitlist patients to 

one or more IOTA participants and 

alternatives considered. 

The following is a summary of the 

comments received on our proposed 

criteria for identifying and attributing 

kidney transplant waitlist patients to 

one or more IOTA participants and 

alternatives considered and our 

responses: 

Comment: A commenter 

recommended CMS change the 

proposed definition of a pediatric 

transplant to include a transplant 

performed on a patient who may be 18 

years or older, but was listed on the 

kidney transplant waiting list prior to 

age 18. Specifically, a commenter 

recommended this change in definition 

because the commenter thought that its 

preferred definition would satisfy 

existing industry standards and better 

reflect the nature of a pediatric patient 

who may not receive a transplant until 

after turning 18 years old, but could 

remain under the care of a pediatric 

transplant program. 

Response: We thank the commenter 

for their suggestion; however, we 

disagree as we did not propose to define 

a pediatric transplant. At 89 FR 43544 

of the proposed rule, we proposed to 

define an IOTA transplant patient as a 

kidney transplant patient who receives 

a kidney transplant at the age of 18 

years or older from an IOTA participant 

at any time during the model 

performance period. As we are 

including only non-pediatric facilities 

in our definition of eligible kidney 

transplant hospitals, as described and 

finalized in section III.C.3.c of this final 

rule, we believe that those that are listed 

prior to the age of 18 under the care of 

a pediatric facility would not be 

included in our definition of an IOTA 

transplant patient. Therefore, we will be 

finalizing our proposed definition of 

IOTA transplant patient without 

modification. 

Comment: A commenter expressed 

support for CMS’s proposal to attribute 

kidney transplant waitlist patients to 

one or more IOTA participants based on 

where the patient is registered on a 

kidney transplant waitlist. 

Response: We thank the commenter 

for their support. 

Comment: We received a comment 

voicing concern with the proposed 

IOTA waitlist patient and patient 

attribution process in that it could 

create competition among transplant 

hospitals due to the cross-listing of 

patients. 

Response: We thank the commenter 

for their feedback. As described in 

section I.B.2.a of this final rule, we 

proposed that the IOTA Model would 

test whether performance-based 

incentive payments paid to or owed by 

participating kidney transplant 

hospitals increase access to kidney 

transplants for patients with ESRD 

while preserving or enhancing the 

quality of care and reducing Medicare 

expenditures. Specifically, we proposed 

to test whether performance based 

incentives (including both upside and 

downside risk) for participating kidney 

transplant hospitals can increase the 

number of kidney transplants (including 

both living donor and deceased donor 

transplants) furnished to ESRD patients, 

encourage investments in care processes 

and patterns with respect to patients 

who need kidney transplants, encourage 

investments in value-based care and 

improvement activities, and promote 

kidney transplant hospital 

accountability by tying payments to 

value. We believe a cross-listing of 

patients through the IOTA waitlist 

patient and patient attribution process is 

beneficial for patients and increases 

their likelihood of receiving a 

transplant. For these reasons, we are 

finalizing our proposal without 

modification. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

our proposed criteria for identifying and 

attributing kidney transplant waitlist 

patients as IOTA waitlist patients to one 

or more IOTA participants at 

§ 512.414(b)(1) without modification. 

(ii) IOTA Transplant Patient Attribution 

We proposed that kidney transplant 

patients would be attributed as IOTA 

transplant patients to the IOTA 

participant that furnished a kidney 

transplant during the model 

performance period, if they meet the 

following criteria: 

• The patient was 18 years of age or 

older at the time of their transplant; and 

• The patient was alive at the time of 

attribution. 

We note that an IOTA transplant 

patient who experiences transplant 

failure and is then de-attributed from an 

IOTA participant, as described in 

section III.C.4.b(1)(iii) of this final rule, 

could become attributed to an IOTA 

participant again at any point during the 

model performance period if they 

rejoined a kidney transplant waitlist for, 

or received a kidney transplant from, 

any IOTA participant and satisfied all of 

the criteria for attribution as described 

in section III.C.4.b(1)(i) or section 

III.C.4.b(1)(ii) of this final rule. 

We proposed to attribute kidney 

transplant patients to the IOTA 

participant that furnished the transplant 

to hold the IOTA participant 

accountable for patient transplant and 

post-transplant outcomes. We 

alternatively considered attributing 

kidney transplant patients based on the 

plurality of post-transplant services, as 

identified in Medicare claims, because it 

would still result in attributing kidney 

transplant patients to only one IOTA 

participant and would base attribution 

on where the majority of services were 

furnished. We recognize that patients 

may choose to receive their pre-and 

post-transplant care from multiple IOTA 

participants in addition to the IOTA 

participant that performed their kidney 

transplant. However, the model’s 

incentives do not support shifting 

accountability for post-transplant 

outcomes away from the IOTA 

participant that furnished the 

transplant. We believe that the IOTA 

participant that performed the 

transplant should remain accountable 

for any surgery related outcomes, both 

successes and failures. 

We proposed not to attribute patients 

who are younger than 18 years of age at 

the time of their kidney transplant or 

who are deceased at the time of 

attribution due to the same reasons 

described in section III.C.4.b(1)(i) of this 

final rule. 

We sought comment on our proposed 

criteria for identifying and attributing 

kidney transplant patients as IOTA 


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transplant patients to the IOTA 

participant that furnished their kidney 

transplant during the model 

performance period. We also sought 

comment on the alternative considered. 

We received no comments on this 

proposal and therefore are finalizing the 

provisions for our proposed criteria for 

identifying and attributing kidney 

transplant patients as IOTA transplant 

patients to the IOTA participant that 

furnished their kidney transplant during 

the model performance period at 

§ 512.414(b)(2) as proposed without 

modification. 

(iii) De-Attribution Criteria 

We proposed that CMS would only 

de-attribute attributed patients from an 

IOTA participant during annual 

attribution reconciliation, as described 

in section III.C.4.b(4) of this final rule. 

We proposed that CMS would deattribute any attributed patient from an 

IOTA participant that meets any of the 

following criteria as of the last day of 

the PY being reconciled, in accordance 

with the annual attribution 

reconciliation list as described in 

section III.C.4.c of this final rule: 

• The IOTA waitlist patient was not 

registered on an IOTA participant’s 

kidney transplant waitlist on the last 

day of the PY being reconciled. 

• The IOTA waitlist patient died at 

any point during the PY. We proposed 

that an IOTA waitlist patient who has 

died during the PY would be removed 

from the list of attributed IOTA waitlist 

patients effective on the last day of the 

PY that the death occurred. 

• The IOTA transplant patient has 

died at any point during the PY. We 

proposed that an IOTA transplant 

patient who has died during the PY 

would be de-attributed from the list of 

attributed IOTA transplant patients 

effective on the last day of the PY that 

the death occurred. 

• The IOTA transplant patient’s 

kidney failed during the PY, and the 

patient is not included on the IOTA 

participant’s waitlist. We proposed that 

an IOTA transplant patient who 

experiences transplant failure at any 

point during the PY and does not rejoin 

an IOTA participant’s kidney transplant 

waitlist or receive another transplant 

from an IOTA participant before the last 

day of the same PY would be listed as 

de-attributed in the annual attribution 

reconciliation list. This IOTA transplant 

patient would no longer be attributed to 

the IOTA participant effective the last 

day of the PY in which the IOTA 

transplant patient’s kidney transplant 

has failed. 

We sought comment on our proposed 

methodology and criteria for identifying 

and de-attributing attributed patients 

from an IOTA participant. 

The following is a summary of the 

comments received on our proposed 

methodology and criteria for identifying 

and de-attributing attributed patients 

from an IOTA participant and our 

responses: 

Comment: A commenter expressed 

support for CMS’s proposed deattribution criteria. 

Response: We thank the commenter 

for their support. 

Comment: A commenter requested 

more information about the source of 

the data that would be used to verify the 

graft loss or death. 

Response: We thank the commenter 

for their feedback. As noted in section 

V.C of the proposed rule, the SRTR data 

source includes data on all transplant 

donors, candidates, and recipients in 

the U.S. As described in the proposed 

rule, section III.C.4.b of the proposed 

rule outlines our proposal to use of 

SRTR data, OPTN data, Medicare claims 

data, and Medicare administrative data 

for the purposes of the IOTA Model. 

Additionally, section III.C.5.e(1) of this 

final rule describes and finalizes our 

proposal to use of OPTN follow-up 

forms to identify graft failure and retransplant dates. We acknowledge that 

for the purposes of measuring graft 

survival using OPTN data, use of either 

concept would generate the same 

outcome measurement because OPTN 

data identify graft status as either 

functioning or failed. However, we aim 

to convey the importance of ongoing 

management to preserve the health of 

the transplanted graft and the health 

and quality of life of the attributed 

patients. 

Finally, as described and finalized in 

section III.C.13.a of this final rule, we 

proposed that CMS, or its approved 

designees, would conduct compliance 

monitoring activities to ensure 

compliance by the IOTA participant and 

IOTA collaborators with the terms of the 

IOTA Model, including to understand 

IOTA participants’ use of model-specific 

payments and to promote the safety of 

attributed patients and the integrity of 

the IOTA Model. One proposed 

monitoring activity would include 

audits of claims data, quality measures, 

medical records, and other data from the 

IOTA participant and its IOTA 

collaborators. For these reasons, we are 

finalizing our proposal without 

modification. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

our proposed methodology and criteria 

for identifying and de-attributing 

attributed patients from an IOTA 

participant at § 512.414(b)(3), as 

proposed without modification. 

(2) Initial Attribution 

We proposed that before the model 

start date, CMS would conduct an 

‘‘initial attribution’’ to identify and 

prospectively attribute waitlist patients 

to an IOTA participant pursuant to 

§ 512.414. The list of IOTA waitlist 

patients identified through initial 

attribution, namely the initial 

attribution list, would prospectively 

apply to the first quarter of PY 1, 

effective on the model start date. The 

purpose of this initial attribution list 

would be to prospectively provide IOTA 

participants with a list of their IOTA 

waitlist patients for the upcoming 

quarter. 

We considered attributing patients to 

IOTA participants at different points in 

time, such as the day that a kidney 

transplant waitlist patient was added to 

the IOTA participant’s kidney 

transplant waitlist, or the day that a 

kidney transplant patient received their 

kidney transplant. This approach would 

be more precise than considering all 

attributed patients to be attributed as of 

the start of the quarter. However, due to 

the limitations of data sources and the 

frequency with which these data are 

updated, we did not see this as a viable 

alternative. 

We sought comment on our proposal 

to conduct initial attribution before the 

model start date and alternatives 

considered. 

We received no comments on this 

proposal and therefore are finalizing the 

provisions as proposed without 

modification at § 512.414(c)(1) and the 

definition of initial attribution at 

§ 512.402, without modification. 

(3) Quarterly Attribution 

We proposed that CMS would 

attribute patients to IOTA participants 

in advance of each quarter, after initial 

attribution, and distribute a ‘‘quarterly 

attribution list’’ to each IOTA 

participant that includes all their 

attributed patients, including newly 

attributed patients, on a quarterly basis 

throughout the model performance 

period, except in the event of 

termination as described in section 

III.C.16(b) of this final rule. 

We considered monthly attribution 

for more frequent updates to the initial 

attribution list, but believe it would be 

operationally burdensome. We also 

considered annual attribution for less 

frequent updates to the initial 

attribution list, which would be less 

operationally burdensome than monthly 

or quarterly attribution. Annual 

attribution is common in other 


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Innovation Center models and CMS 

programs where the participant is 

managing total cost of care for a 

population. The benefits of annual 

attribution would include prospectively 

providing participants a stable list of 

patients for whom they would be held 

accountable, and, as the process would 

occur only once a year, would be 

associated with lower administrative 

burden. The downside of annual 

attribution, however, is that IOTA 

participants would have less frequent 

updates and understanding of their 

attributed population, potentially 

making it hard to plan and budget 

accordingly. We do not believe annual 

attribution would be appropriate for the 

IOTA Model’s goal of improving access 

to kidney transplants and quality of care 

for a patient population that changes 

frequently. For example, kidney 

transplant hospitals add patients to their 

kidney transplant waitlist throughout 

the year. Were we to limit attribution to 

once a year, kidney transplant waitlist 

patients added during the year would 

not be attributed to an IOTA participant 

until the following year, delaying our 

ability to meet the minimum number of 

patients required to evaluate a model 

test. As such, we believe more frequent 

attribution would be necessary. 

We sought comment on our proposal 

to conduct attribution on a quarterly 

basis during the model performance 

period and on the alternatives 

considered. 

The following is a summary of the 

comments received on our proposal to 

conduct attribution on a quarterly basis 

during the model performance period 

and on the alternatives considered and 

our responses: 

Comment: Several commenters voiced 

their support for the proposed quarterly 

attribution provisions, stating that it 

would ensure accuracy and fairness. 

Response: We thank the commenters 

for their support. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

our proposed quarterly attribution 

provisions at § 512.414(c)(2), without 

modification. We received no comments 

on the proposed definition of quarterly 

attribution list and there are finalizing 

this definition without modification at 

§ 512.402. 

(4) Annual Attribution Reconciliation 

We proposed that after the end of 

each PY, CMS would conduct annual 

attribution reconciliation. We proposed 

to define ‘‘annual attribution 

reconciliation’’ as the yearly process by 

which CMS would: (1) create each IOTA 

participant’s final list of attributed 

patients for the PY being reconciled by 

retrospectively de-attributing from each 

IOTA participant any attributed patients 

that satisfied a criterion for deattribution pursuant to § 512.414(c); and 

(2) create a final list of each IOTA 

participant’s attributed patients who 

would remain attributed for the PY 

being reconciled, subject to the 

attribution criteria in §§ 512.414(b)(1) 

and (2). For the purposes of this model, 

we proposed to define ‘‘annual 

attribution reconciliation list’’ as the 

final cumulative record of attributed 

patients that would be generated 

annually for whom each IOTA 

participant was accountable for during 

the applicable PY. 

For example, after PY 1, CMS would 

rerun attribution for the entire PY to 

finalize the list of attributed patients 

that met the criteria specified in 

sections III.C.4.b(1) and (2) of this final 

rule. Once the fourth quarter is 

complete, CMS would use the fourth 

quarter attribution list to determine and 

de-attribute any attributed patients that 

meet a criterion for de-attribution, as 

described in section III.C.4.b(1)(iii) of 

this final rule, from the IOTA 

participant, as described in section 

III.C.4.b(1)(iii) of this final rule, and 

remove those attributed patients from 

the quarterly attribution list to create the 

annual attribution reconciliation list. 

Before the second quarter of the 

following PY, CMS would distribute the 

annual attribution reconciliation list to 

IOTA participants. We proposed that 

these lists, at a minimum, would 

identify each attributed patient, identify 

reasons for de-attribution in the 

previous PY, and the dates in which 

attribution began, changed, or ended, 

where applicable. 

We sought comment on our proposal 

to conduct annual attribution 

reconciliation. 

The following is a summary of the 

comments received on our proposal to 

conduct annual attribution 

reconciliation and our responses: 

Comment: Several commenters 

expressed support for CMS’s proposal to 

conduct annual attribution 

reconciliation. 

Response: We thank the commenters 

for their support. 

After consideration of public 

comments, for the reasons set forth in 

this rule, we are finalizing the policy for 

annual attribution reconciliation as 

proposed in § 512.414(c)(3), with a 

minor technical correction to update the 

cross references in the regulation text at 

§§ 512.414(c)(3)(ii)(A) and 

512.414(c)(3)(ii)(C–F). We are also 

finalizing the definitions of annual 

attribution reconciliation and annual 

attribution reconciliation list at 

§ 512.402 without modification. 

c. IOTA Patient Attribution Lists 

We proposed that no later than 15 

days prior to the start of the first model 

performance period, CMS would 

provide the IOTA participant the 

‘‘initial attribution list.’’ For the 

purposes of the model, we proposed to 

define ‘‘days’’ as calendar days, as 

defined in 42 CFR 512.110, unless 

otherwise specified by CMS. On a 

quarterly basis thereafter, CMS would 

provide the IOTA participant the 

‘‘quarterly attribution list’’ no later than 

15 days prior to the start of the next 

quarter. The annual attribution 

reconciliation list for a given PY would 

be provided to the IOTA participants 

after the conclusion of the PY, before 

the second quarter of the following PY. 

We proposed that the initial, 

quarterly, and annual attribution 

reconciliation lists would be provided 

in a form and manner determined by 

CMS. 

We sought comment on our proposed 

attribution list policies. 

The following is a summary of the 

comments received on our proposed 

attribution list policies and our 

responses: 

Comment: Several commenters 

requested that CMS provide the patient 

attribution lists be provided well in 

advance of the performance period to 

allow IOTA participants to prepare 

accordingly and assess performance 

impacts. Specifically, a commenter 

suggested providing attribution lists at 

least one quarter in advance of the start 

of the performance period. 

Response: We thank the commenters 

for their feedback. As described and 

finalized in section III.C.4.c of this final 

rule, we proposed that 15 days prior to 

the start of the first model performance 

period, CMS would provide the IOTA 

participant the initial attribution list. On 

a quarterly basis thereafter, CMS would 

provide the IOTA participant the 

quarterly attribution list no later than 15 

days prior to the start of the next 

quarter. The annual attribution 

reconciliation list for a given PY would 

be provided to the IOTA participants 

after the conclusion of the PY, before 

the second quarter of the following PY. 

This sequence for patient attribution 

lists follows the same pattern as other 

Innovation Center models—such as the 

KCC Model—and, therefore, we are 

finalizing this provision without 

modification. 

After consideration of public 

comments, for the reasons set forth in 

this rule, we are finalizing, as proposed, 

our provisions at §§ 512.414(c)(1)(ii), 


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188https://optn.transplant.hrsa.gov/about/ 

committees/membership-professional-standardscommittee-mpsc/. 

189https://optn.transplant.hrsa.gov/about/ 

committees/membership-professional-standardscommittee-mpsc/ and Burden Reduction. Federal 

Register. https://www.federalregister.gov/d/2018- 

19599/p-215. 

190https://optn.transplant.hrsa.gov/media/4777/ 

transplant_program_performance_monitoring_

public_comment_aug2021.pdf. 191 Ibid. 

512.414(c)(2)(ii), 512.414(c)(3)(ii) and 

the definition of days at § 512.402 

without modification. 

5. Performance Assessment 

a. Goals and Proposed Data Sources 

As described in section III.B. of the 

proposed rule, CMS and the OPTN each 

have roles in assessing the performance 

of kidney transplant hospitals. CMS’ 

regulations in 42 CFR part 482 subpart 

E require certain conditions of 

participation for kidney transplant 

hospitals to receive approval to perform 

Medicare transplant services. Under 42 

CFR part 121, the OPTN is required to 

implement a peer review process by 

which OPOs and transplant hospitals 

are periodically reviewed for 

compliance with the bylaws of the 

OPTN and the OPTN final rule (63 FR 

16332). The OPTN MPSC is charged 

with performing these evaluations; 

including the identification of threats to 

patient safety and public health.188

As described in section III.C.5.a. of 

the proposed rule, CMS and the OPTN 

have each acknowledged the limitations 

of transplant hospital performance 

assessment based on the one-year 

patient and transplant survival measure 

alone. In 2018, CMS eliminated its 

assessment of one year patient and 

transplant survival for the purposes of 

transplant hospital re-approval in the 

final rule, ‘‘Medicare and Medicaid 

Programs; Regulatory Provisions To 

Promote Program Efficiency, 

Transparency, and Burden Reduction; 

Fire Safety Requirements for Certain 

Dialysis Facilities; Hospital and Critical 

Access Hospital (CAH) Changes To 

Promote Innovation, Flexibility, and 

Improvement in Patient Care’’ (84 FR 

51732), leaving assessment of the one 

year patient and transplant survival 

measure only for initial Medicare 

approval, due to concerns that the 

measure was causing conservative 

behavior in transplant hospitals.189 In 

2021, the OPTN disseminated a 

proposal to enhance the MPSC’s 

performance monitoring process by 

expanding the number of measures used 

to identify transplant hospital 

underperformance.190 In that proposal, 

the OPTN acknowledged the potential 

for transplant hospital risk aversion due 

to the MPSC’s evaluations of 

performance based on the one year 

patient and transplant survival metric 

alone and proposed transplant hospital 

assessment based on a holistic set of 

measures encompassing aspects of care 

across the transplant journey.191

As described in section III.C.5.a. of 

the proposed rule, strengthening and 

improving the performance of the organ 

transplantation system is a priority for 

HHS, including CMS and HRSA. In 

accordance with this priority and joint 

efforts with HRSA, the IOTA Model 

would aim to improve performance and 

equity in kidney transplantation by 

testing whether performance-based 

payments to IOTA participants 

increases access to kidney transplants 

for kidney transplant waitlist and 

kidney transplant patients attributed to 

IOTA participants in the model, thereby 

reducing Medicare program 

expenditures while preserving or 

enhancing quality of care. For the IOTA 

Model, we proposed a broader set of 

metrics which aligns with the trends 

that we believe would encourage IOTA 

participants to meet the model goals as 

described in section III.A of this final 

rule. 

As described in section III.C.5.a of the 

proposed rule, the IOTA Model would 

assess performance on a broad set of 

metrics that were selected to align with 

all of the following model goals: 

• Increase number of, and access to, 

kidney transplants. 

• Improve utilization of available 

deceased donor organs. 

• Support more donors through the 

living donation process. 

• Improve quality of care and equity. 

In section III.C.5.a of the proposed 

rule, we proposed using Medicare 

claims and administrative data about 

beneficiaries, providers, suppliers, and 

data from the OPTN, which contains 

comprehensive information about 

transplants that occur nationally, to 

measure IOTA participant performance 

in the three model domains: (1) 

achievement domain; (2) efficiency 

domain; and (3) quality domain. 

Medicare administrative data refers to 

non-claims data that Medicare uses as 

part of regular operations. This includes 

information about beneficiaries, such as 

enrollment information, eligibility 

information, and demographic 

information. Medicare administrative 

data also refers to information about 

Medicare-enrolled providers and 

suppliers, including Medicare 

enrollment and eligibility information, 

practice and facility information, and 

Medicare billing information. 

We solicited comment on our 

proposal for selecting performance 

metrics and performance domains. We 

also solicited comment on our proposed 

use of Medicare claims data, Medicare 

administrative data, and OPTN data to 

calculate the performance across the 

three proposed domains, as described in 

section III.C.5. of this final rule. 

The following is a summary of 

comments received on our proposal for 

selecting performance metrics and 

performance domains, in addition to our 

proposed use of Medicare claims data, 

Medicare administrative data, and 

OPTN data to calculate the performance 

across the three proposed domains and 

our responses: 

Comment: A commenter conveyed 

their concern that the OPO and 

transplant performance metrics are 

misaligned and as a result will 

minimize the impact of the IOTA 

Model. 

Response: We appreciate the 

commenter’s feedback; however, we do 

not believe that it is appropriate to 

directly compare the performance 

metrics of OPOs and kidney transplant 

hospitals. Both OPOs and kidney 

transplant hospitals have unique roles 

in the transplant ecosystem, requiring 

different focuses, skills sets and 

responsibilities. We acknowledge the 

different responsibilities of these two 

parties along the continuum of care for 

organ transplantation. Overall, 

performance metrics, are meant to 

understand current state, to set goals to 

create improvement, to ensure 

unintended consequences of changes 

are identified, and to allow for analysis 

and evaluation to pivot and modify 

metrics when appropriate. With 

overarching goals to improve kidney 

transplant volume while maintaining 

quality organs and patient care, we 

believe that HRSA and CMS do not have 

misaligned goals. 

Comment: A few commenters stated 

that they believe the three domains will 

lead to a successful solution and are 

acceptable. 

Response: We appreciate the 

commenters’ support. We believe that 

including the achievement, efficiency 

and quality domain are an ideal 

combination to ensure that while IOTA 

participants are increasing kidney 

transplants, we are also monitoring 

acceptance patterns and post-transplant 

outcomes. 

After consideration of public 

comments, for the reasons set forth in 

this rule, we are finalizing the proposed 

provisions for selecting performance 

metrics and performance domains at 

§ 512.422(a), without modification. We 

did not receive any comments regarding 


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our proposed use of Medicare claims 

data, Medicare administrative data, and 

OPTN data to calculate the performance 

across the three proposed domains and 

therefore are finalizing this provision 

without modification at § 512.422(b). 

b. Method and Scoring Overview 

In accordance with our proposed 

goals of the IOTA performance 

assessment, as described in section 

III.C.5.a of the proposed rule, we 

proposed to assess performance across 

three domains: (1) achievement domain; 

(2) efficiency domain; and (3) quality 

domain. We proposed to use one or 

more metrics within each domain to 

assess IOTA participant performance. 

We proposed at § 512.422(a)(2) that 

CMS would assign each set of metrics 

within a domain a maximum point 

value, with the total possible points 

awarded to an IOTA participant being 

100 points. We proposed to define 

‘‘final performance score’’ as the sum 

total of the scores earned by the IOTA 

participant across the achievement 

domain, efficiency domain, and quality 

domain for a given PY. We also 

proposed that the combined sum of total 

possible points would determine 

whether and how the IOTA Model 

performance-based payments, as 

described and finalized in section 

III.C.6.c of this final rule, would apply 

and be calculated. We proposed the 

following point allocations for each of 

these three domains: 

• The achievement domain would 

make up 60 of 100 maximum points. 

The achievement domain would 

measure the number of kidney 

transplants performed relative to a 

participant-specific target, as described 

in section III.C.5.c of the proposed rule. 

The achievement domain would 

represent a large portion (60 percent) of 

the maximum total performance score. 

We weighted the achievement domain 

performance score more than the 

efficiency and quality domain because 

we believe it aligns with the primary 

goal of the IOTA Model, to increase the 

overall number of kidney transplants. 

Additionally, because increasing the 

number of kidney transplants performed 

is the primary goal of the model, we 

believe weighing performance on this 

measure more than the efficiency 

domain and quality domain is necessary 

to directly incentivize participants to 

meet their target. 

• The efficiency domain would make 

up 20 of 100 maximum points. The 

efficiency domain would measure 

performance on a kidney organ offer 

acceptance rate ratio, as described in 

section III.C.5.d of the proposed rule. 

• The quality domain would make up 

20 of 100 maximum points. As 

described in section III.C.5.e. of the 

proposed rule, the quality domain 

would measure performance on a set of 

quality metrics, including posttransplant outcomes, and on three 

proposed quality measures— 

CollaboRATE Shared Decision-Making 

Score, Colorectal Cancer Screening, and 

3-Item Care Transition Measure. 

We believed that many prospective 

IOTA participants may already be 

familiar with the approach of assigning 

points up to a maximum in multiple 

domains. This structure is similar to 

other CMS programs, including the 

Merit-based Incentive Payment System 

(MIPS) track of the Quality Payment 

Program. For MIPS, we assess the 

performance of MIPS eligible clinicians 

(as defined in 42 CFR 414.1305) across 

four performance categories—one of 

which is quality—and then determine a 

positive, neutral, or negative MIPS 

payment adjustment factor that applies 

to the clinician’s Medicare Part B 

payments for professional services. 

Similar to MIPS, we proposed that the 

IOTA Model would use a performance 

scoring scale from zero to 100 points 

across performance domains, and apply 

a specific weight for each domain. We 

believed using wider scales of 0 to 100 

points would allow us to calculate more 

granular performance scores for IOTA 

participants and provide greater 

differentiation between IOTA 

participants’ performance. In the future, 

we believed this methodology for 

assessing performance could be applied 

with minimal adaptation to future IOTA 

participants if CMS adds other types of 

organ transplants to the model through 

rulemaking. We believed that the 

approach of awarding points in the 

achievement, efficiency, and quality 

domains for a score out of 100 points 

represented the best combination of 

flexibility and comparability that would 

allow us to assess participant 

performance in the IOTA Model. 

As discussed in section III.C.5.b of the 

proposed rule, the proposed 

performance domains and scoring 

structure would also allow us to 

combine more possible metric types 

within a single framework. We believed 

that this approach allows for more 

pathways to success than performance 

measurement based on relative or 

absolute quintiles, which were also 

alternatively considered, as it would 

reward efforts made towards achievable 

targets. 

As discussed in section III.C.5.b of the 

proposed rule, we considered more than 

three domains to assess performance, 

which would potentially offer IOTA 

participants more opportunity to 

succeed due to the ability to maximize 

points in different combinations of 

domains. The more domains there are, 

the more the maximum points possible 

in each domain are spread out. 

However, we limited the number of 

domains to three to ensure the model is 

focused and goal-oriented, thus 

promoting, encouraging, and driving 

improvement activity and care delivery 

transformation across IOTA participants 

that evidence suggest may help achieve 

desired outcomes. Desired outcomes 

include delaying or avoiding dialysis, 

improving access to kidney 

transplantation by reducing barriers and 

disparities, reducing unnecessary 

deceased donor discards, increasing 

living donors, and improving care 

coordination and quality of care pre and 

post transplantation. We believed that 

the three domains and the proposed 

performance scoring structure would 

offer IOTA participants multiple paths 

to succeed in the proposed IOTA Model 

due to the ability to maximize points in 

different combinations of domains. 

In section III.C.5.b of the proposed 

rule, we also considered not using the 

three performance domains and scoring 

structure, instead opting for alternative 

methods. We considered a performance 

assessment methodology in which an 

IOTA participant’s performance on a 

metric would be divided by an expected 

value for each metric, which would 

indicate whether an IOTA participant is 

performing better or worse on a given 

measure than expected. We would then 

calculate a weighted average of all 

performance scores to reach a final 

score. However, we believed that setting 

appropriate targets of expected 

performance for each IOTA participant 

for each metric would be unrealistic to 

implement. The additional 

methodological complexity necessary 

for this approach would be difficult for 

an IOTA participant to incorporate into 

its operations and data systems, thereby 

limiting an IOTA participant’s ability to 

understand the care practice changes it 

would need to make to succeed in the 

IOTA Model. 

As discussed in section III.C.5.b of the 

proposed rule, we also considered 

assessing IOTA participant performance 

solely on magnitude of increased 

transplants over expected transplants. 

Under this approach, an IOTA 

participant’s number of transplants 

furnished in a given PY subtracted from 

expected transplants would show a 

numeric net gain or loss in total 

transplants. This net value would be 

multiplied by an IOTA participant’s 

kidney transplant survival rate to 

generate a total score for each IOTA 


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participant. This option would reward 

successfully completed transplants. 

This methodology reflects the goals of 

the IOTA Model and acknowledges that 

kidney transplant failures are an 

undesirable outcome. In addition, the 

methodology is simple to evaluate and 

understand, requiring only two inputs 

and a simple calculation. However, this 

approach does not account for efficiency 

and quality domain metrics, as 

proposed in sections III.C.5.d. and 

III.C.5.e of the proposed rule, which we 

believed to be important goals of the 

model. Thus, we did not propose this 

method to assess IOTA participant 

performance. 

As discussed in section III.C.5.b of the 

proposed rule, we also considered 

directly translating the benefits of a 

kidney transplant by measuring the net 

effect of increased transplants and posttransplant care at the IOTA participant 

level. In a performance scoring 

methodology focused on the net effect of 

increased transplants and posttransplant care, the number of kidney 

transplants performed in a given PY 

would be compared to a benchmark year 

for the IOTA participant. Each 

additional kidney transplant would then 

be multiplied by the expected number 

of years of dialysis treatment the 

transplant averted, based on organ 

quality. Post-transplant care would 

analyze observed versus expected 

kidney transplant failures. For IOTA 

participants that achieved fewer kidney 

transplant failures than expected, the 

difference in volumes would be 

translated into life-years. Each marginal 

additional year of averted dialysis care 

would be used to determine the 

performance-based payment. Because 

calculating expected transplant failures 

is a complicated calculation with 

assumptions based on organ quality, 

donor age, and donor health conditions, 

a scoring system of this type would 

require us to make multiple broad 

assumptions about individual 

transplants or average scores across all 

transplants performed by the IOTA 

participant to create an accurate 

estimate of the total number of years of 

dialysis treatment the kidney transplant 

averted. This level of complexity would 

also introduce operational risks and 

burden. This approach would be aligned 

with the goals of the IOTA Model as it 

relates to increasing the number and 

access to kidney transplants but would 

still require CMS to separately assess 

performance on proposed performance 

measures for the IOTA Model, as 

discussed in sections III.C.5.c, III.C.5.d, 

and III.C.5.e of the proposed rule. 

We solicited feedback from the public 

on our proposal to assess IOTA 

participant performance in three 

domains: (1) achievement domain; (2) 

efficiency domain; and (3) quality 

domain. We also sought feedback on our 

proposed performance scoring approach 

that would weigh the achievement 

domain higher than the efficiency and 

quality domain, and our proposed use of 

a 0 to 100 performance scoring approach 

to determine if and how performancebased payments would apply. 

Additionally, we invited feedback on 

the alternatives considered. 

The following is a summary of the 

comments received on our proposal to 

assess IOTA participant performance in 

three domains (achievement domain, 

efficiency domain and quality domain), 

our proposed performance scoring 

approach, and on our proposed use of 

a 0 to 100 performance scoring approach 

to determine if and how performancebased payments would apply and our 

responses: 

Comment: A few commenters 

supported the three proposed domains 

for assessing an IOTA participant’s 

performance. A commenter specifically 

stated they supported the 100-point 

structure made up of 3 domains and 

another specifically stated their support 

for the emphasis on the achievement 

domain. 

Response: We thank the commenters 

for their support. 

Comment: A commenter stated that 

the performance metrics are conflicting 

because while volume is incentivized, 

achieving a high organ offer acceptance 

rate ratio would require more 

conservative transplants. 

Response: We appreciate the 

commenters feedback. We believe that 

counterbalanced performance metrics 

are needed to create checks and 

balances within the IOTA Model. The 

inclusion of the organ offer acceptance 

rate ratio metric and the composite graft 

survival rate discourages IOTA 

participants from strictly considering 

volume and encourages IOTA 

participants to also prioritize long term 

outcomes. We direct readers to sections 

III.C.5.d(1) and III.C.5.e(1) of this final 

rule for further discussion on the organ 

offer acceptance rate ratio and the 

composite graft survival rate. The 

collection of metrics encourages IOTA 

participants to understand specific 

components of their transplant program 

that may be optimized such as utilizing 

filters, understanding what organs they 

are accepting or deferring and 

identifying what workflows and 

resources may help them optimize their 

transplant program. While IOTA 

participants may believe it is 

contradictory to weight achievement 

higher, we believe that kidney 

transplant volume can be increased 

while being mindful of post-transplant 

outcomes for both living donor and 

deceased donor transplant recipients. 

There are a variety of ways for IOTA 

participants to reach final performance 

point totals that are incentivized (score 

greater than 60). For example, growth of 

a living donor program could increase 

volume without impacting the offer 

acceptance ratio entirely. 

Comment: Many commenters stated 

that the performance should include 

other factors that could impact an IOTA 

participant’s performance, such as the 

IOTA participant’s history. 

Response: We appreciate the 

commenters’ feedback. We believe that 

IOTA participant history is incorporated 

into many features and performance 

measurements of the IOTA Model. An 

IOTA participant’s past performance is 

included in the achievement domain of 

the IOTA Model, by using baseline year 

data to calculate kidney transplant 

volume goals in the IOTA Model. While 

there is not an improvement scoring 

component within the achievement 

domain, we intend to consider this for 

future rulemaking. The organ offer 

acceptance rate ratio performance 

metric, which is part of the efficiency 

domain, is evaluated either through 

overall achievement or improvement. 

Inclusion of an improvement scoring 

system within the efficiency domain, 

takes the IOTA participant’s history into 

consideration. The quality domain 

utilizes composite graft survival over a 

6-year period as a performance metric. 

While use of this metric in the first 1– 

2 years of the model will not take IOTA 

participant history into consideration, 

the latter years will include earlier 

model data years (IOTA participant 

history) in its calculation. 

Comment: Many commenters 

suggested that risk adjustment should be 

included in the performance measures, 

with a couple of commenters stating 

specifically that the lack of adjustment 

incentivizes transplanting healthier 

individuals and avoiding higher risk 

organs. Another commenter relayed 

their concern about the lack of scientific 

validation for the metrics, from the 

transplant community. 

Response: We thank the commenters 

for submitting their concerns. The data 

and methodology utilized for the offer 

acceptance ratio utilizes OPTN data and 

SRTR methodology and is risk adjusted. 

As mentioned in section III.C.5.e(1)(a) of 

this final rule, we considered whether 

donor demographic characteristic risk 

adjustments such as race, gender, age, 

disease condition and geographic 

location would be significant and 

clinically appropriate for our approach 


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192Scientific Registry of Transplant Recipients. 

(n.d.). Risk Adjustment Model: Offer Acceptance. 

Offer acceptance. https://www.srtr.org/tools/offeracceptance/. 193 Ibid. 

in calculating the composite graft 

survival rate measure, however, we are 

unsure which specific adjustments 

would be most appropriate. We believe 

that further analysis of the impact of the 

donor’s characteristics on graft survival 

is necessary prior to incorporating a risk 

adjustment methodology. Additionally, 

given that the IOTA Model is 6 years, 

and the measure is rolling, we want to 

make sure that we continue discussions 

to ensure that this measure eventually 

includes a robust and appropriate risk 

adjustment methodology. We direct 

readers to section III.C.5.e(1)(a) of this 

final rule, for further discussion 

regarding calculation of the composite 

graft survival rate. 

While the achievement domain does 

not utilize risk adjustment, it assigns 

points for volume of kidneys 

transplanted, based on an IOTA 

participant’s prior performance and 

national growth rate. We did not 

originally consider how volume goals 

could be risk adjusted, however, we are 

open to ongoing feedback as to how this 

could be integrated into the 

achievement domain metric. 

We acknowledge the concerns raised 

by a commenter about the scientific 

validity of some performance measures, 

but we do not believe any of the 

measures are entirely novel. For 

example, the OPTN has previously used 

an offer acceptance rate ratio in their 

metrics. Although the proposed 

composite graft survival rate measure is 

new, analyzing 1-year graft survival is 

an established performance metric 

familiar to kidney transplant hospitals. 

We will consider risk-adjusting this 

metric in future rulemaking. The IOTA 

Model intends to closely monitor 

metrics new to the transplant 

community and adjust as indicated 

throughout its performance years. 

Comment: A couple of commenters 

mentioned that performance assessment 

should include a measure of additional 

relevant factors, such as the donor’s risk 

factors. 

Response: We agree and note that the 

SRTR calculation, which is used for the 

organ offer acceptance rate ratio 

calculation, includes numerous donor 

factors that contribute to the acceptance 

predictors.192 While the composite graft 

survival rate metric is not risk adjusted, 

we will stratify the data from the 

composite graft survival rate measure 

and consider public comments to 

inform a risk adjustment methodology 

for this measure and intend to address 

a new or updated policy pursuant to 

future rulemaking. We direct readers to 

section III.C.5.e(1) of this final rule for 

further discussion on the composite 

graft survival metric. 

Comment: Several commenters stated 

that measures of transplant outcomes 

should be a reliable and valid measure 

and that a SRTR metric is an example 

of a metric that should be used. 

Response: We agree and note that the 

SRTR calculation, which is used for the 

organ offer acceptance rate ratio 

calculation, includes numerous donor 

factors that impact the acceptance 

predictors.193 While the composite graft 

survival rate metric is not risk adjusted, 

we will stratify the data from the 

composite graft survival rate measure 

and consider public comments to 

inform a risk adjustment methodology 

for this measure and intend to address 

a new or updated policy pursuant to 

future rulemaking. We direct readers to 

section III.C.5.e(1) of this final rule for 

further discussion on the composite 

graft survival metric. 

Comment: Several commenters 

conveyed concern that CMS should 

exclude hospice patients from the oneyear mortality rate. 

Response: We appreciate the 

commenters’ concern. The IOTA Model 

does not currently include a one-year 

mortality performance measure, and 

therefore discussion about hospice 

patient exclusions from this metric is 

not applicable. For clarification, the 

IOTA Model does include a composite 

graft survival rate metric, but this metric 

is based on graft survival, not patient 

survival. Any specifications on 

exclusions for calculating the composite 

graft survival rate metric would be 

addressed in detail in future IOTA 

Model methodology reports. 

Comment: Several commenters 

conveyed concern that assessment 

scoring places a heavy weight on the 

volume of transplants and the 

subsequent possibility that this may 

incentivize IOTA participants to use 

‘‘sub-par’’ organs and increase 

disparities. 

Response: We agree that there is a 

heavy focus on increasing volume of 

transplants as this is one of the primary 

goals of the IOTA Model. There are a 

variety of ways to increase kidney 

transplant volume (for example, 

expanding a living donor program, 

increasing volume of patients active on 

the kidney transplant list, utilizing 

filters to ensure appropriate offers for 

risk thresholds, or using kidney 

transplants from underutilized 

categories, if reasonable). While some 

kidney transplant hospitals may 

prioritize increasing kidney transplants 

from underutilized categories such 

those with a high KDPI or donation after 

circulatory death (DCD) kidneys, that 

decision may hinge on resources, and is 

not a requirement. 

The IOTA Model was designed to 

create balance by requiring that IOTA 

participants perform well in the 

efficiency and quality domains to reach 

positive performance incentives. This 

ensures that kidney transplant volume 

does not grow unchecked, and IOTA 

participants remain responsible for long 

term outcomes of patients. We believe 

that increasing kidney transplants will 

result in increases in patient access to 

transplant along the continuum of 

care—ranging from being referred for 

transplant, to waitlisting, to transplant. 

Given the disparities that exist in all 

phases of transplant, we believe that 

changes made to increase kidney 

transplant volume will also help reduce 

disparities. Additionally, we believe the 

proposed transparency measures, which 

include publishing the criteria used to 

select transplant patients and reviewing 

the acceptance criteria as described and 

finalized in sections III.C.8.a(1) and (2) 

of this final rule, complement the 

performance-based metrics and will 

help to reduce disparities by increasing 

patient awareness and encouraging 

shared decision-making. We direct 

readers to section III.C.8(a) of this final 

rule for a full discussion on the 

transparency requirements. We intend 

to monitor throughout the entirety of the 

model for any unintended consequences 

that would impact disparities. 

Comment: Numerous commenters 

expressed concern regarding the 

weighting of points for each domain. 

Several commenters stated that the 

point allocation for each performance 

domain should be spread equally across 

domains or that more points should be 

allocated to the quality domain (one 

example specified 50 achievement 

points, 30 quality points, 20 efficiency 

points). A commenter suggested that 

quality should have the highest weight, 

while another recommended equal 

weighting of achievement and quality 

due to resources needed for posttransplant care, which they felt was not 

reimbursed. A commenter suggested 

that during PY 3 or later, CMS should 

consider the point breakdown of 50, 25, 

25 for the achievement, efficiency and 

quality domains. There were many 

specific concerns that there is too much 

incentive placed on volume rather than 

quality and this may incentivize poor 

long-term outcomes for patients. A 

commenter was specifically concerned 


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about the risk of increased performance 

reviews. 

Response: We appreciate the 

commenters’ concerns but respectfully 

disagree. We believe that the domain 

with the heaviest weighting, will also be 

the domain that sees greatest behavioral 

changes. Therefore, the achievement 

domain is more heavily weighted to 

increase access to transplant, a primary 

goal of the IOTA Model. If an IOTA 

participant prioritizes growth of their 

living donor program, for example, this 

would have a high likelihood of better 

post-transplant outcomes, given the 

longer graft lives of living donor kidney 

transplants. IOTA participants that may 

be restricted to expanding living 

donation could consider, for example, 

how to optimize their organ filters to 

ensure that they receive more of the 

transplant offers they are willing to 

accept and transplants they can help 

maintain long term. IOTA participants 

can earn up to 60 points for 

performance in the achievement domain 

and up to 40 combined points for 

performance metrics in the efficiency 

and quality domains. We do not believe 

this is imbalanced given the reasoning 

previously mentioned. Additionally, as 

described and finalized in section 

III.C.5.e of this final rule, we are 

modifying the metrics proposed for 

inclusion in the quality domain. As 

such, we do not believe that weighting 

the quality domain metrics more heavily 

is appropriate at this time. We direct 

readers to section III.C.5.e of this final 

rule for further discussion on the quality 

domain. We will continue to monitor 

our performance assessment strategy 

across all performance domains and 

may consider proposing an updated 

performance scoring approach through 

future rulemaking. We will be finalizing 

our performance scoring approach in 

section III.C.5.b of this final rule, as 

proposed, which designates 3 

performance domains and the 

performance scoring approach as 

follows: 60 points for the achievement 

domain, 20 points for the efficiency 

domain and 20 points for the quality 

domain. 

Comment: A couple of commenters 

stated their concerns that prioritizing 

kidney transplant volume in the 

achievement domain may discourage 

IOTA participants from taking on more 

complex cases, because patients may 

need more assistance throughout 

transplant evaluation or may be at risk 

of worse outcomes. 

Response: We appreciate the 

commenters’ feedback but believe that 

kidney transplant hospitals have 

different skill sets and resources. The 

IOTA Model encourages IOTA 

participants to work at the top of their 

scope and encourages them to identify 

ways that they can optimize their 

program without compromising posttransplant care. Approaches may look 

very different depending on the size, 

location and resources of an IOTA 

participant. For example, wellestablished IOTA participants may 

focus on improving outcomes for 

patients receiving kidneys with a KDPI 

greater than 85, whereas small IOTA 

participants may decide to focus on preemptive transplant or living donation 

transplant. Risk thresholds may also 

vary considerably based on the 

established networks between 

community nephrologists and 

transplant teams. Community 

nephrologists are an extension of the 

transplant team and can have significant 

impact on helping their patients 

successfully receive a transplant and 

maintain graft life, after transplant. The 

IOTA Model challenges the pre-existing 

framework of kidney transplant 

hospitals to evolve. 

While we believe that increasing 

access to transplant and subsequent 

increase in volume is a fundamental 

goal of the IOTA Model, we believe 

there is also opportunity to encourage 

and reward IOTA participants that excel 

in the efficiency and quality domains as 

they adapt their programs for growth. It 

is ideal for IOTA participants to excel 

across all three performance domains 

throughout the model test; however, we 

understand that IOTA participants may 

perform better in specific performance 

domains due to year-to-year variations 

in available resources. The IOTA Model 

scoring was designed to include posttransplant measures to prevent poor 

outcomes from increased kidney 

transplant volume. 

Comment: A commenter 

recommended that CMS include 

nutritional care in their performance 

metrics to address needs of patients. 

Response: While we acknowledge the 

importance of nutrition and nutritional 

resources for patients across the CKD to 

ESRD to transplant care continuum, we 

do not currently believe that that 

nutritional care directly aligns with the 

goals of the IOTA Model or its 

performance metrics. We invite ongoing 

input on how nutritional care may fit 

into an alternative quality metric 

utilized in future iterations of the IOTA 

Model. 

Comment: A commenter stated that 

safety net kidney transplant hospitals in 

remote regions will be disadvantaged by 

the three domains. 

Response: We acknowledge that 

remote and safety net kidney transplant 

hospitals have different challenges in 

their transplant programs than kidney 

transplant hospitals that may be in 

highly populated areas. We encourage 

IOTA participants to consider the 

numerous approaches that they may 

take to increase kidney transplant 

volume. This may be achieved by 

increasing living donor kidney 

transplants (LDKTs), deceased donor 

kidney transplant (DDKTs) or both. If an 

IOTA participant struggles to increase 

their volume initially, there are 

opportunities to excel in the efficiency 

and quality domains. We understand 

that any model can have unintended 

consequences and we intend to monitor 

the model impacts on IOTA 

participants. 

Comment: A couple of commenters 

suggested that the IOTA Model should 

have been weighted to encourage use of 

kidneys with a KDPI greater than 85 and 

improving quality of care for those 

transplant recipients, rather than 

prioritize increasing total number of 

transplants performed. 

Response: Thank you for submitting 

feedback, however, we disagree. While 

there is opportunity to optimize use of 

kidneys with a KDPI greater than 85, we 

believe this may not be the most ideal 

way for all IOTA participants to 

increase volume or general performance. 

Prioritizing an increase in any DDKTs or 

LDKTs of a specific classification allows 

each IOTA participant to have flexibility 

in adapting their program to meet this 

goal. 

While the IOTA Model is not 

finalizing a performance metric 

measuring utilization of kidneys with a 

KDPI greater than 85, we intend to 

assess and monitor the utilization of this 

category of kidney transplants by IOTA 

participants. 

Comment: A commenter was 

concerned that the IOTA Model does 

not account for recovered kidneys that 

are not used for transplant or for nonutilization. 

Response: We thank the commenter 

for their feedback. The organ offer 

acceptance rate ratio is calculated by 

excluding donor kidneys that are not 

utilized. While no metric in the IOTA 

Model specifically looks at the total 

non-utilization number, this may be an 

important metric to further research as 

it may be impacted differently as kidney 

transplant hospitals adjust their offer 

acceptance filters. We believe there may 

be opportunity for future collaboration 

with the OPTN to ensure non-utilization 

data is captured and accessible for 

review. 

Comment: A commenter mentioned 

concern that CMS is basing kidney 

transplant hospital percentile rankings 

against both participating and nonVerDate Sep<11>2014 18:30 Dec 03, 2024 Jkt 265001 PO 00000 Frm 00047 Fmt 4701 Sfmt 4700 E:\FR\FM\04DER2.SGM 04DER2

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194For additional information on SRTR’s 

transplant rate measure, please see https://

www.srtr.org/about-the-data/technical-methods-forthe-program-specific-reports#figurea2. 

195Paul, S., Melanson, T., Mohan, S., RossDriscoll, K., McPherson, L., Lynch, R., Lo, D., 

Pastan, S.O., & Patzer, R.E. (2021). Kidney 

transplant program waitlisting rate as a metric to 

assess transplant access. American Journal of 

Transplantation: Official Journal of the American 

Society of Transplantation and the American 

Society of Transplant Surgeons, 21(1), 314–321. 

https://doi.org/10.1111/ajt.16277. 

196Paul, S., Melanson, T., Mohan, S., RossDriscoll, K., McPherson, L., Lynch, R., Lo, D., 

Pastan, S.O., & Patzer, R.E. (2021). Kidney 

transplant program waitlisting rate as a metric to 

assess transplant access. American Journal of 

Transplantation: Official Journal of the American 

Society of Transplantation and the American 

Society of Transplant Surgeons, 21(1), 314–321. 

https://doi.org/10.1111/ajt.16277. 

participating kidney transplant 

hospitals. 

Response: We thank the commenter 

for submitting their concern. IOTA 

participants are awarded points in the 

achievement domain based on 

performance improvement relative to 

historical performance for volume of 

kidneys transplanted. We direct readers 

to section III.C.5.c of this final rule for 

a full discussion of the achievement 

domain. 

As described and finalized in section 

III.C.5.d.(1).(b). of this final rule, the 

efficiency domain applies a two-scoring 

system (achievement score and 

improvement score) based on its 

performance on the OPTN organ offer 

acceptance rate ratio; awarding points 

equal to the higher of the two scores to 

the IOTA participant. For achievement 

scoring in the quality domain, as 

described and finalized in section 

III.C.5.d.(1).(b). of this final rule, points 

earned will be based on the IOTA 

participants’ performance on the organ 

offer acceptance rate ratio relative to 

national ranking, including all eligible 

kidney transplant hospitals (both those 

selected and not selected as IOTA 

participants), and awarded based on 

national quintiles. For improvement 

scoring in the efficiency domain, as 

described and finalized in section 

III.C.5.d.(1).(b). of this final rule, points 

earned will be based on the IOTA 

participants’ performance on organ offer 

acceptance rate ratio during a PY 

relative to their performance during the 

third baseline year for the PY that is 

being measured. We direct readers to 

section III.C.5.d of this final rule for a 

full discussion on the efficiency 

domain. 

Lastly, as described and finalized in 

section III.C.5.e(1)(b) of this final rule, 

IOTA participants will earn points in 

the quality domain based on its 

performance on the composite graft 

survival rate, as described and finalized 

in section III.C.5.e(1)(a) of this final rule, 

ranked nationally, inclusive of all 

eligible kidney transplant hospitals. 

IOTA participants will be awarded 

points on the composite graft survival 

rate based on the national quintiles, as 

outlined in Table 1 to Paragraph (d) at 

§ 512.428. We direct readers to section 

III.C.5.e of this final rule for a full 

discussion on the quality domain. 

The IOTA Model incentivizes high 

performance through a point-based 

system, which we anticipate will drive 

IOTA participants to outperform nonparticipating kidney transplant 

hospitals, which we view as a notable 

strength of the model. 

Comment: A commenter stated the 

IOTA Model methodology does not 

account for kidney transplant hospitals 

that already perform a high-volume of 

kidney transplants, and instead is based 

solely on improvement. 

Response: We thank the commenter 

for expressing their concern. Many highvolume kidney transplant hospitals 

have a combination of well-developed 

living donor programs, resources such 

as perfusion pumps, and the volume 

that allows higher risk thresholds both 

for accepting certain donors and 

accepting candidates with more comorbidities. These qualities and 

resources allow ongoing opportunity for 

growth. We recognize that IOTA 

participants with varying kidney 

transplant volumes will have unique 

challenges. However, we believe the 

methodology’s built-in flexibility 

enables IOTA participants to adapt their 

kidney transplant hospital to best serve 

their patient populations. We intend to 

closely monitor kidney transplant 

volume growth and outcomes for IOTA 

participants of all kidney transplant 

volume sizes and take this into 

consideration in future rulemaking. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

our proposed provisions to assess IOTA 

participants in the achievement domain, 

efficiency domain and quality domain 

and performance scoring approach at 

§ 512.422(a), without modification. We 

are also codifying the proposed 

definition of final performance score at 

§ 512.402, without modification. We 

direct readers to sections III.C.5.c, 

III.C.5.d, and III.C.5.e of this final rule 

for further discussion on our proposed 

achievement domain, efficiency 

domain, and quality domain. We also 

direct commenters to section III.C.6.c of 

this final rule for further discussion on 

our proposed performance-based 

payment methodology. 

c. Achievement Domain 

In section III.C.5.b of the proposed 

rule, we proposed measuring IOTA 

participant performance across three 

domains, one of which is the 

achievement domain. We proposed to 

define ‘‘achievement domain’’ as the 

performance assessment category in 

which CMS assesses the IOTA 

participant’s performance based on the 

number of transplants performed on 

patients 18 years of age or older, relative 

to a target, subject to a health equity 

performance adjustment, as described in 

section III.C.5.c.(3) of this final rule, 

during a PY. We proposed to use OPTN 

data, regardless of payer, and Medicare 

claims data to calculate the number of 

kidney transplants performed during a 

PY by an IOTA participant on patients 

18 years of age or older at the time of 

transplant, as described in section 

III.C.5.c(2) of this final rule. 

In section III.C.5.c of the proposed 

rule, we proposed to set the participantspecific target for the achievement 

domain based on each IOTA 

participant’s historic number of 

transplants. A central goal of the 

proposed IOTA Model test is to increase 

the number of kidney transplants 

furnished by IOTA participants, which 

we believed would be possible via care 

delivery transformation and 

improvement activities, including donor 

acceptance process improvements to 

reduce underutilization and discards of 

donor kidneys. We believed IOTA 

participants may also increase the 

number of kidney transplants furnished 

to patients by improving or 

implementing greater education and 

support for living donors. 

As discussed in section III.C.5.c of the 

proposed rule, we considered 

constructing and using a transplant 

waitlisting rate measure or using SRTR’s 

transplant rate 194 rather than measuring 

number of transplants performed 

relative to a participant-specific target 

for the achievement domain. Research 

has suggested that including such a 

metric could demonstrate the need for 

both living and deceased donor organs 

for a particular transplant hospital and 

be less reliant on organ availability for 

a particular geographical area.195

Research also suggested that the 

inclusion of a pretransplant measure, 

such as waitlisting rate, may allow for 

a more complete assessment of 

transplant hospital performance and 

provide essential information for patient 

decision-making.196 However, for the 

IOTA Model, we proposed to test the 

effectiveness of the model’s incentives 

to change outcomes, rather than on 

processes. The relevant outcome for 

purposes of the IOTA Model is the 

receipt of a kidney transplant, not 


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197United States Renal Data System. 2022. 

USRDS Annual Data Report. Volume 2. End-stage 

Renal Disease (ESRD) in the United States, Chapter 

7: Transplantation. Figure 7.10b. 

getting on and remaining on the kidney 

transplant waitlist. Additionally, the 

SRTR transplant rate measure calculates 

the number of those transplanted as a 

share of the kidney transplant hospital’s 

waitlist, which we believed does not 

reflect the variety of ways that kidney 

transplant hospitals construct their 

waitlist practices. For example, for some 

kidney transplant hospitals, the number 

of kidneys transplanted as a share of 

their ‘‘active’’ waitlist transplant 

candidates may be a more accurate 

representation of their waitlist practices. 

Thus, we did not believe this was 

appropriate to propose for the IOTA 

Model. 

We sought comment on our proposed 

achievement domain performance 

metric and alternative methodologies 

considered for assessing transplant 

rates. 

The following is a summary of the 

comments received on our proposed 

achievement domain performance 

metric and alternative methodologies 

considered for assessing transplant rates 

and our responses: 

Comment: A couple of commenters 

supported the achievement domain 

performance metric. A commenter 

specifically agreed with not including a 

waitlisting measure. 

Response: We thank the commenters 

for their support of the achievement 

domain. 

Comment: Several commenters stated 

their concern that there is a heavy 

weight placed on the volume of 

transplants and that this may 

incentivize participants to use ‘‘subpar’’ organs and increase disparities. 

Response: We agree that there is a 

heavy focus on increasing volume of 

transplants as this is one of the primary 

goals of the IOTA Model. There are a 

variety of methods that IOTA 

participants may choose to increase 

kidney transplant volume including, but 

not limited to, expanding a living donor 

program, increasing volume of patients 

active on the kidney transplant list, 

utilizing filters to ensure appropriate 

offers for risk thresholds, or using 

kidney transplants from underutilized 

categories. While some kidney 

transplant hospitals may prioritize 

increasing kidney transplants from 

underutilized categories such those 

kidneys with a KDPI greater than 85 or 

DCD kidneys, that decision may hinge 

on resources, and is not a requirement. 

We are unsure if the commenters are 

defining ‘‘sub-par’’ organs as organs that 

should not be offered to any candidates 

or as organs that are only acceptable in 

specific scenarios. We believe it will be 

important for IOTA participants to 

further consider what is a ‘‘sub-par’’ 

kidney. While certain kidneys may not 

be ideal for some waitlist candidates, 

they may be a potential opportunity in 

another scenario. 

Comment: Commenters voiced 

concerns about how the achievement 

domain would impact high performing 

IOTA participants. Some commenters 

worried the proposed scoring system 

would penalize IOTA participants who 

have historically been top performers. 

Another commenter suggested CMS 

credit the top 20 percent of IOTA 

participants to maintain their kidney 

transplant volume, while using different 

incentives for lower-performing IOTA 

participants. 

Additionally, a commenter expressed 

concern that increasing kidney 

transplant volume often involves 

transplanting more high-risk organs. 

While SRTR accounts for how this 

impacts outcomes, the commenter 

argued that it does not consider the 

added strain on resources at high 

performing kidney transplant hospitals. 

Lastly, another commenter worried the 

achievement domain would penalize 

IOTA participants who are already 

operating at full kidney transplant 

capacity, unless they made substantial 

new investments. 

Response: We appreciate the concerns 

that the commenters have submitted, 

and we acknowledge the efforts exerted 

by transplant hospitals to reach their 

status. We believe that IOTA 

participants can potentially become 

‘‘high performing’’ through a variety of 

practices such as utilizing kidneys of all 

KDPI scores when appropriate, 

adjusting filters, or expanding their 

living donor program. We believe that 

with the number of ways that an IOTA 

participant can become more efficient 

and have higher kidney transplant 

volumes, that they have additional 

opportunities to improve their 

performance and to continue increasing 

kidney transplants. We believe that the 

updated methodology for setting 

transplant targets, as described and 

finalized in section III.C.5.c(1) of this 

final rule, and the updated scoring 

methodology in the achievement 

domain, as described and finalized in 

section III.C.5.c(2) of this final rule, will 

make it more achievable for IOTA 

participants of all sizes to achieve 

maximum points in the achievement 

domain. We direct readers to section 

III.C.5.c(1) and III.C.5.c(2) of this final 

rule for a full discussing on the updated 

methodology for calculating the 

transplant target and the updated 

scoring methodology in the achievement 

domain. We also note that, as described 

and finalized in section III.C.6.c(2) of 

this final rule, there is no downside risk 

payment in PY 1 of the IOTA Model. 

Comment: A couple of commenters 

stated that CMS should act to eliminate 

constraints on transplant availability 

due to both kidney transplant hospital 

and hospital capacity and organ 

availability before implementing 

transplant targets in the achievement 

domain. 

Response: We appreciate the 

commenters’ feedback; however, we do 

not have control over the capacity of 

kidney transplant hospitals and 

hospitals or organ availability. We 

encourage kidney transplant hospitals to 

work with their leadership if they have 

concerns about capacity limitations. 

Organ availability is impacted by a 

variety of factors, including, but not 

limited to identification of organ 

donors, allocation practices, location of 

kidney transplant hospitals and donors 

and utilized organs. Improving kidney 

transplant volumes will require multipronged efforts. We believe the IOTA 

Model will help increase the number of 

kidney transplants performed. 

Comment: A few commenters 

suggested that CMS should engage with 

stakeholders to refine goals and focus 

more narrowly on certain aspects of 

increasing transplant volume in the 

achievement domain, especially 

increasing living donation and utilizing 

high-risk kidneys. Similarly, a 

commenter suggested that CMS should 

focus its efforts on increasing kidney 

volume in categories where there is 

opportunity for growth such as high 

KDPI kidneys, donor kidneys with acute 

kidney injury (AKI) and DCD kidneys. 

Response: We thank the commenters 

for their suggestions and believe that 

there are a variety of practices that IOTA 

participants can choose to utilize when 

increasing their kidney transplant 

volume. Because kidney transplant 

hospitals vary significantly, we disagree 

with the commenters, and do not 

believe it would be appropriate to be 

prescriptive about how an IOTA 

participant decides to increase their 

kidney transplant volume. While living 

donation, for example, has had 

relatively unchanged transplant rates 

over the last few years, indicating 

opportunity for improvement, we 

acknowledge that not every kidney 

transplant hospital has the same 

resources or characteristics.197

Furthermore, we believe the IOTA 

Model design provides flexibility that 

enables IOTA participants to increase 


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198Penn Medicine News. (2020, December 16). 

Too Many Donor Kidneys Are Discarded in U.S. 

Before Transplantation—Penn Medicine. 

www.pennmedicine.org. https://

www.pennmedicine.org/news/news-releases/2020/ 

december/too-many-donor-kidneys-are-discardedin-us-before-transplantation. 

their kidney transplant volume in a way 

that best suits their transplant program 

and community. 

Comment: A couple of commenters 

voiced concern that success in the 

achievement domain is contingent upon 

a multitude of uncontrollable factors, 

such as limited organs and matching 

challenges. Additionally, a few 

commenters mentioned concern that 

increasing kidney transplant volume 

requires expansion of many other 

resources for successful post-transplant 

care, which are not reimbursed through 

the Medicare cost report. 

Response: We appreciate the 

commenters’ feedback about their 

concern about limitations of resources. 

We acknowledge the multitude of 

factors that can impact kidney 

transplant hospital volume—from a 

community level to a nationwide level, 

and also acknowledge that kidney 

transplant volume expansion may 

require increased resources, particularly 

staffing. There are intrinsic components 

of the IOTA Model intended to offset 

challenges of the achievement domain, 

such as two other performance domains 

(efficiency and quality). Additionally, 

the achievement domain calculates 

transplant targets for IOTA participants 

based on an IOTA participant’s own 

prior kidney transplant volume in their 

baseline years and based on a national 

growth rate that accounts for changes 

year to year (as described in section 

III.C.5.c.2 of this final rule). We also 

note that there are not prescriptive 

specifications in the achievement 

domain requiring IOTA participants to 

meet transplant volumes in one specific 

way. This flexibility allows IOTA 

participants to identify what method is 

best to optimize their kidney transplant 

volume. Notably, as described and 

finalized in section III.C.6.c(1) of this 

final rule, PY 1 does not include any 

downside risk payments regardless of an 

IOTA participant’s final performance 

score. Furthermore, we believe the 

neutral zone has a reasonable final 

performance score range for PYs 2–6, as 

described and finalized in section 

III.C.6.c(1) of this final rule. As such, we 

believe the absence of downside risk 

payment in of PY 1 creates a buffer for 

IOTA participants to anticipate 

resources needed to succeed in PY 2. 

The achievement domain scoring 

methodology accounts for Medicare and 

non-Medicare patients who receive a 

kidney transplant. We anticipate that 

since IOTA participants will aim to 

increase kidney transplants for all 

kidney transplant waitlist patients, this 

will create opportunities to accumulate 

payment through the IOTA Model 

incentives and through payment by both 

Medicare and private payers for kidney 

transplant related services. We believe 

these payments should assist in costs 

that IOTA participants may encounter 

while participating in the IOTA Model. 

Comment: A commenter conveyed 

concern that the achievement domain, 

which focuses on increasing kidney 

transplant volume, is contradictory 

since the Innovation Center’s goals have 

traditionally been to improve value 

versus volume. A few commenters were 

concerned that volume does not equate 

with better outcomes and even with 

counterbalances in the model, will 

pressure IOTA participants to complete 

riskier transplants, which may have 

worse outcomes. 

Response: We disagree and believe 

that the achievement domain 

simultaneously supports increasing 

kidney transplant volume and value. 

There are almost 5,000 patients who die 

annually while being on the kidney 

transplant waitlist.198 It is well known 

the life span of and lifestyle of those 

patients on dialysis is drastically 

different from those patients who 

receive kidney transplants. Not only 

does the model aim to improve access, 

kidney transplant volumes and quality 

of life, but also reduce spending. The 

cost of yearly dialysis far exceeds the 

average cost of immunosuppression and 

post-transplant care. The IOTA Model is 

not encouraging IOTA participants to 

transplant non-viable organs or organs 

where risks outweigh the benefits. The 

IOTA Model design, does however, 

challenge kidney transplant hospitals to 

optimize all components of care from 

waitlisting to transplant to posttransplant. Growth in living donor 

programs is a prime example of how 

increasing volume should not 

compromise outcomes and should 

improve overall outcomes. As for 

increases in DDKT volume, we plan to 

carefully monitor volume, organ offer 

acceptance ratios and composite graft 

survival independently and collectively 

to monitor for unintended consequences 

and will consider this for future 

rulemaking for PY 2. We encourage 

commenters to provide feedback in the 

future about (1) what they define as 

‘‘riskier’’ transplants from the 

perspective of the donor and recipient 

(2) whether this is specific to KDPI 

values or qualities of the donor kidney 

and (3) if this exceeds the risk of being 

on dialysis. 

Comment: A few commenters believe 

that the achievement domain 

disadvantages smaller transplant 

programs due to their lack of COE 

designation and overlooks challenges to 

gain this designation. Another 

commenter was concerned that small 

transplant programs will have to accept 

higher risk kidneys. A commenter 

suggested that smaller programs should 

have separate performance metrics. 

Response: We thank the commenters 

for their feedback and acknowledge that 

kidney transplant hospitals of different 

sizes, will have different challenges in 

increasing kidney transplant volume. 

Kidney transplant hospitals that fall 

below the low volume threshold would 

be excluded from the IOTA Model, as 

described and finalized in section 

III.C.3(c) of this final rule. Based on the 

updated scoring methodology in the 

achievement domain, as described and 

finalized in section III.C.5.c(2) of this 

final rule, an IOTA participant with 20 

kidney transplants during the baseline 

years (with an example growth rate of 8 

percent) would need a total of 27 kidney 

transplants to earn maximum 

achievement points (60), or 

approximately 23 kidney transplants to 

earn 40 points in the achievement 

domain. We believe that offering wide 

neutral margins for final performance 

scores and offering a variety of 

opportunities to gain points in the 

achievement domain, efficiency domain 

and quality domain creates balances for 

a different size kidney transplant 

hospital. We believe that increasing 

kidney transplant volume will create 

opportunities for smaller kidney 

transplant hospitals to qualify for COE 

designation in the future. 

Comment: A couple of commenters 

raised concerns that the achievement 

domain disproportionately impacts 

large transplant programs due to the 

demand on resources it would require 

and the general volume requirements. 

Response: We thank the commenters 

for submitting their concerns. As stated 

in response to small kidney transplant 

hospital concerns, offering wide neutral 

margins for final performance scores 

and offering a variety of opportunities to 

gain points in the achievement, 

efficiency and quality domains creates 

balances for IOTA participants. Many 

large kidney transplant hospitals have 

significant resources, COE designation, 

and paired donation opportunities that 

may not be available to smaller kidney 

transplant hospitals. We believe that 

while volume goals may be higher, they 

are proportionately similar for kidney 

transplant hospitals of different sizes. 


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Comment: A commenter suggested 

that IOTA participant specific volume 

targets should match local population 

needs along economic lines, racial lines 

and payer sources to increase equitable 

access to underserved groups. 

Response: We thank the commenter 

for their feedback. While this is not a 

specific requirement that we originally 

proposed, we are interested to receive 

more information about this suggestion, 

as we consider future rulemaking. First, 

we would want to consider how to do 

this equitably and how kidney 

transplant hospitals would identify their 

local population needs. 

Comment: A commenter suggested 

that CMS track achievement domain 

volume scores to ensure IOTA 

participants do not utilize the scoring 

system at the expense of patient risk. 

Response: We appreciate the 

commenter’s response. The IOTA Model 

has thoughtfully been designed to create 

counterbalances between measures. For 

example, although the achievement 

score is based on kidney transplant 

volume, the efficiency score is based on 

offer to acceptance ratios and the quality 

domain includes a composite graft 

calculation for a 6-year period posttransplant. While innovation models are 

not perfect, and are corrected for 

optimization over time, we believe that 

IOTA participants that have combined 

accountability for IOTA Model 

requirements, OPTN metrics and 

regulatory and ethical requirements, 

will be mindful of avoiding 

inappropriate patient risk. 

Comment: A commenter 

recommended that CMS differentiate 

between more established kidney 

transplant hospitals and newer kidney 

transplant hospitals with shorter track 

records and transplant volume. 

Established kidney transplant hospitals 

often have decades-long waitlists, 

referral networks, and stable staffing of 

transplant nephrologists. In contrast, 

newer, smaller kidney transplant 

hospitals can experience large swings in 

transplant volume due to growing pains. 

Furthermore, the commenter argued, the 

loss of a single transplant nephrologist 

can halt kidney transplants at these 

newer kidney transplant hospitals while 

they recruit replacements, leading to a 

penalty at a time when the kidney 

transplant hospital can least afford it. 

Response: We thank the commenter 

for their feedback. We acknowledge that 

there are differences between wellestablished and, newer, smaller kidney 

transplant hospitals with smaller 

transplant volume. As described in 

section III.C.5.c(1) of this final rule, the 

updated methodology for measuring 

performance in the achievement domain 

will be based on the average number of 

kidney transplants performed in the 

baseline years trended forward by the 

national growth rate. Therefore, we 

disagree with the commenter and 

believe all IOTA participants can 

improve their kidney transplant rates, 

regardless of size. We recognize that 

some IOTA participants may have to 

make upfront investments, but the low 

volume threshold of 11 adult kidney 

transplants for each kidney transplant 

hospital in every baseline year, as 

described and finalized in section 

III.C.3.c of this final rule, will 

substantially mitigate the demands 

placed on, newer, smaller kidney 

transplant hospitals. 

After consideration of the public 

comments, for the reasons set forth in 

this rule, we are finalizing, as proposed, 

our provisions for setting an IOTA 

participant’s transplant target based on 

each IOTA participant’s historic number 

of transplants at § 512.424(b)(1), as 

described and finalized in section 

III.C.5.c(1) of this final rule. We direct 

readers to section III.C.5.c(1) of this final 

rule for further discussion on the 

transplant target methodology. As 

described and finalized in section 

III.C.5.c(2) of this final rule, we are also 

finalizing our proposed provision for 

identifying kidney transplants 

performed by an IOTA participant using 

OPTN data, regardless of payer, and 

Medicare claims data at § 512.424(d), 

without modification. 

Furthermore, after consideration of 

the public comments we received, we 

will not be finalizing a health equity 

performance adjustment provision, as 

described in section III.C.5.c(3) of this 

final rule. Therefore, we are modifying 

regulatory text for the achievement 

domain definition at § 512.402, to 

remove references to a health equity 

performance adjustment and make 

minor technical corrections in 

punctuation. We direct readers to 

section III.C.5.c(3) of this final rule for 

further discussion on our proposed 

health equity performance adjustment. 

While we are finalizing our provision 

for setting IOTA participants’ transplant 

target based on each IOTA participant’s 

historic number of transplants as 

mentioned in section III.C.5.c, we note 

that the methodology for utilizing an 

IOTA participant’s historic number of 

transplants for calculating transplant 

targets has changed in section 

§ 512.424(b)(1) and is described in detail 

and finalized in section III.C.5.c(1) of 

this final rule. We direct readers to 

section III.C.5.c(1) of this final rule for 

further discussion on the transplant 

target methodology. In addition, as 

described and finalized in section 

III.C.5.c(2) of this final rule, we are 

finalizing our proposed provision for 

identifying kidney transplants 

performed by the IOTA participant 

using OPTN data, regardless of payer, 

and Medicare claims data at 

§ 512.424(d), without modification. 

(1) Calculation of Transplant Target 

In the proposed rule, we proposed 

that for each model PY, CMS would 

calculate a ‘‘transplant target’’ for each 

IOTA participant, which would 

determine performance in the 

achievement domain. For the purposes 

of the model, we proposed to define 

‘‘transplant target’’ as the target number 

of transplants set for each IOTA 

participant to measure performance in 

the achievement domain as described in 

the proposed rule and section III.C.5.c of 

this final rule. We proposed that CMS 

would notify each IOTA participant of 

their transplant target by the first day of 

each PY, in a form and manner 

determined by CMS. 

For each PY, we proposed in section 

III.C.5.c(1) of the proposed rule, that 

CMS would calculate the transplant 

target for the achievement domain by 

first determining the highest number of 

deceased donor kidney transplants and 

living donor kidney transplants 

furnished to patients 18 years of age or 

older in a single year during the 

baseline years, as defined and finalized 

in section III.C.3.c. of this final rule. 

CMS would then sum the highest 

number of deceased donor kidney 

transplants and living donor kidney 

transplants furnished in a single year 

during the baseline years calculate the 

transplant target for an IOTA 

participant, even if those transplant 

numbers were achieved during different 

baseline years. We believed that 

choosing the highest transplant numbers 

during the baseline years would 

illustrate the capabilities and capacities 

of the IOTA participant, and, when 

combined, would be an appropriate 

target for number of transplants 

performed during the PY. We also 

understood that living donation and 

deceased donor donation involve 

different processes by the IOTA 

participant, so we chose each of those 

numbers separately to recognize the 

potential capacity for each IOTA 

participant for both living and deceased 

donor transplantation. 

In section III.C.5.c(1) of the proposed 

rule, we proposed that the sum of the 

highest number of deceased donor and 

living donor transplants across the 

baseline years of the IOTA participant 

would then be projected forward by the 

national growth rate, as described in 

section III.C.5.c(1) of this final rule, or 


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zero should the national growth rate be 

negative, resulting in the transplant 

target for a given PY. We proposed to 

define ‘‘national growth rate’’ as the 

percentage increase or decrease in the 

number of kidney transplants performed 

over a twelve-month period by all 

kidney transplant hospitals except for 

pediatric kidney transplant hospitals 

and kidney transplant hospitals that fall 

below the low volume threshold 

described and finalized in section 

III.C.3. of this final rule. We proposed to 

define ‘‘pediatric kidney transplant 

hospitals’’ as a kidney transplant 

hospital that performs 50 percent or 

more of its transplants in a 12-month 

period on patients under the age of 18. 

We also proposed that the low volume 

threshold to be 11 kidney transplants 

performed for the purposes of 

calculating the national growth rate. We 

also proposed this approach for 

calculating the national growth rate to 

account for and reflect the growth in 

organ procurement by OPOs that has 

occurred, indicating potential growth in 

the number of available organs. 

In section III.C.5.c(1) of the proposed 

rule, we proposed that CMS would 

calculate the national growth rate by 

determining the percent increase or 

decrease of all kidney transplants 

furnished to patients 18 years of age or 

older from two years prior to the PY to 

one year prior to the PY. Because the 

proposed national growth rate includes 

IOTA participants and non-IOTA 

participant kidney transplant hospitals, 

we acknowledge that it could make 

achieving the transplant target number 

harder. This is why, if the national 

growth rate becomes negative for a PY, 

we proposed treating it as zero and CMS 

would not apply the national growth 

rate to project forward the sum of the 

highest number of deceased and living 

donor kidney transplants furnished in a 

single year during the baseline years. In 

other words, an IOTA participant’s 

transplant target would equal the sum of 

its own highest deceased and living 

donor transplants furnished across the 

baseline years if the national growth rate 

were to be negative for a PY. We also 

want to be able to share model 

performance targets with IOTA 

participants before the start of each PY 

and are prioritizing ensuring 

prospectivity over ensuring the most upto-date trend figures. We also proposed 

that if the model begins on an any date 

after January 1, 2025, the trend would 

also be adjusted. 

For example, as described in section 

III.C.5.c(1) of the proposed rule, to 

calculate the national growth rate for PY 

1 using the proposed model start date of 

January 1, 2025, CMS would first 

subtract the total number of kidney 

transplants furnished to patients 18 

years of age or older in 2022 from the 

total number of kidney transplants 

furnished to patients 18 years of age or 

older in 2023. Next, CMS would then 

divide that number by the total number 

of kidney transplants furnished to 

patients 18 years of age or older in 2022 

to determine national growth rate. To 

create the transplant target for each 

IOTA participant for PY 1 CMS would 

do the following: 

• If the national growth rate is 

positive, CMS would trend the national 

growth rate forward for an IOTA 

participant by multiplying the national 

growth rate by the sum of the highest 

number of deceased donor and living 

donor transplants furnished to patients 

18 years of age or older across the 

baseline years for the IOTA participant. 

• CMS would take the product of step 

1 and add it to the sum of the highest 

living donor and deceased donor kidney 

transplants furnished to patients 18 

years of age or old across the baseline 

years for an IOTA participant. 

• The sum of step 2 would be the 

transplant target for an IOTA 

participant. However, if the national 

growth rate were negative, CMS would 

not trend the growth rate forward for PY 

1 and the transplant target would be the 

sum of the highest living donor and 

deceased donor kidney transplants 

across the baseline years. 

In section III.C.5.c(1) of the proposed 

rule, we proposed that when calculating 

the national growth rate for each PY, 

CMS would look to the relevant baseline 

years for that PY, as depicted in Table 

1. This approach would mitigate our 

concern that a static baseline may 

reward a one-time investment, rather 

than continuous improvement. The 

model PYs, as proposed in the proposed 

rule, would not factor into an IOTA 

participant’s transplant target 

calculation until PY 3 of the model 

(January 1, 2027, to December 31, 2027) 

and the baseline years would not be 

based exclusively on PYs until PY 5 of 

the model (January 1, 2029, to December 

31, 2029), which may represent an 

effective phase-in approach to drive 

improved performance and savings for 

the Medicare trust fund. We believe that 

using baseline years to calculate the 

transplant targets would also account 

for kidney transplant hospitals that 

experience changes in strategy or 

staffing that may affect their capacity to 

perform transplants at the level that 

they did in previous years. 


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Should we finalize a model start date 

other than January 1, 2025, we proposed 

in section III.C.5.c(1) of the proposed 

rule that the baseline years, as defined 

and finalized in section III.B.2.c of this 

final rule, would shift accordingly, as 

illustrated in Table 2. 

We stated in section III.C.5.c(1) of the 

proposed rule that we believe that IOTA 

participants could improve on this 

metric in several ways. For example, 

IOTA participants could increase the 

number of kidney organ offers they 

accept, which would also potentially 

lead to greater efficiency domain scores. 

IOTA participants could also invest in 

a living donation program or modify 

their OR schedules to facilitate fewer 

discards due to physician scheduling. 

We considered basing the transplant 

target on the total number of all organ 

transplants performed by the IOTA 

participant over the baseline years (89 

FR 43518). However, we did not believe 

this was appropriate because the total 

would not reflect the specific 

capabilities of the IOTA participant’s 

kidney transplant program. We also 

considered adjusting the transplant 

target by IOTA participant revenue from 

hospital cost reports. In this scenario, 

our consideration was to look at 

historical kidney transplant data as the 

best predictor, since this reveals the 

demonstrated capacity for each IOTA 

participant to complete kidney 

transplants. 

We also considered setting each IOTA 

participant’s transplant target by 

determining the IOTA participant’s 

average total kidney transplant volume 

from the three previous years instead of 

using the sum of the highest living and 

deceased donor kidney transplant 

volumes during the baseline years (89 

FR 43518). We believe that this 

methodology would be simpler and 

result in a transplant target that is 

potentially more attainable for IOTA 

participants, assuming that the average 

kidney transplant volume is lower than 

the sum of the highest volumes of 

deceased and living donor kidney 

transplants. However, we do not believe 

that this would reflect the potential 

highest capacity for transplant that we 

would otherwise like the target to 

reflect. 

We alternatively considered a static or 

fixed baseline approach for purposes of 

determining the transplant target for 

each IOTA participant, as it would 

minimize operational burden for CMS 

due to less frequent updates to the 

transplant target and ensure that the 

model does not set a moving target yearover-year (89 FR 43518). However, we 

believe that a fixed baseline may reward 

a one-time investment, rather than 

continuous improvement, and may not 


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2 

3 

4 

5 

6 

TABLE 1: EXAMPLE - PROPOSED BASELINE YEARS FOR CALCULATION OF 

TRANSPLANT TARGET (FOR PROPOSED MODEL START DATE) 

Jan 1, 2025- CY 2021: January 1, 2021-December 31, 2021 CY 2023/CY 2022 

December 31, 2025 CY 2022: January 1, 2022 - December 31, 2022 

CY 2023: Janu 1, 2023 - December 31, 2023 

Jan 1, 2026- CY 2022: January 1, 2022 - December 31, 2022 CY 2024/CY 2023 

December 31, 2026 CY 2023: January 1, 2023 -December 31, 2023 

CY 2024: Janu 1, 2024 - December 31, 2024 

Jan 1, 2027- CY 2023: January 1, 2023 -December 31, 2023 CY 2025/ CY 2024 

December 31, 2027 CY 2024: January 1, 2024 - December 31, 2024 

CY 2025: Janu 1, 2025 - December 31, 2025 

Jan 1, 2028- CY 2024: January 1, 2024 - December 31, 2024 CY 2026/ CY 2025 

December 31, 2028 CY 2025: January 1, 2025 - December 31, 2025 

CY 2026: Janu 1, 2026 - December 31, 2026 

Jan 1, 2029- CY 2025: January 1, 2025 -December 31, 2025 CY 2027/ CY 2026 

December 31, 2029 CY 2026: January 1, 2026 - December 31, 2026 

CY 2027: Janu 1, 2027-December 31, 2027 

Jan 1, 2030- CY 2026: January 1, 2026 - Decem her 31, 2026 CY 2028/ CY 2027 

December 31, 2030 CY 2027: January 1, 2027-December 31, 2027 

CY 2028: Janua 1, 2028 - December 31, 2028 

TABLE 2: EXAMPLE - PROPOSED BASELINE YEARS FOR CALCULATION OF 

TRANSPLANT TARGET, FOR POTENTIAL ALTERNATIVE MODEL START DATE 

July I, 2025 - July I, 2021-June 30, 2022 July 1, 2023 -June 30, 2024 / July I, 

June 30, 2026 July I, 2022- June 30, 2023 2022 - June 30, 2023 

Jul 1, 2023-June 30 2024 

July I, 2026 - July I, 2022- June 30, 2023 July I, 2024 -June 30, 2025 / July 1, 

June 30, 2027 July I, 2023 - June 30, 2024 2023 - June 30, 2024 

Jul I. 2024 - June 30 2025 

July I, 2027 - July I, 2023 - June 30, 2024 July I, 2025 -June 30, 2026 / July 1, 

June 30, 2028 July 1, 2024- June 30, 2025 2024 - June 30, 2025 

Jul L 2025 - June 30, 2026 

July 1, 2028- July 1, 2024 - June 30, 2025 July 1, 2026-June 30, 2027 /July 1, 

June 30, 2029 July 1, 2025 - June 30, 2026 2025 - June 30, 2026 

Jul 1, 2026-June 30, 2027 

July I, 2029 - July 1, 2025 - June 30, 2026 July 1, 2027 -June 30, 2028 / July I, 

June 30, 2030 July 1, 2026- June 30, 2027 2026 - June 30, 2027 

Jul 1, 2027 - June 30, 2028 

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96332 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

199Potluri, V.S., & Bloom, R.D. (2021). Effect of 

Policy on Geographic Inequities in Kidney 

Transplantation. https://doi.org/10.1053/ 

j.ajkd.2021.11.005; Hanaway, M.J., MacLennan, 

P.A., & Locke, J.E. (2020). Exacerbating Racial 

Disparities in Kidney Transplant. JAMA Surgery, 

155(8), 679. https://doi.org/10.1001/ 

jamasurg.2020.1455. 

account for kidney transplant hospitals 

that experience changes in strategy or 

staffing that may affect their capacity to 

perform transplants at the level that 

they did in historical years. The rolling 

baseline approach we proposed uses 

historical kidney transplant volumes 

pre-dating the model start date through 

the first two model PYs, ensuring a 

phased-in approach before any 

improvements made during the model 

performance period are accounted for in 

the baseline. 

We also considered setting the 

transplant target for IOTA participants 

based on two baseline years, rather than 

the proposed methodology of three (89 

FR 43518). For the proposed model start 

date of January 1, 2025, this approach 

would look at the highest living and 

deceased volumes from 2022 and 2023, 

trended by the national growth rate from 

2024, to set the transplant target for PY 

1. We believe this methodology would 

be more reflective of recent 

transplantation volume and account for 

the changes to the kidney allocation 

system that were implemented in 2021. 

However, we believe that using two 

baseline years to set a transplant target 

would be more susceptible to temporary 

market disruptions or fluctuations that 

may impact IOTA participants 

capability or capacity to furnish kidney 

transplants, such as: if the transplant 

hospital experiences a shortage in 

transplant surgeons or other critical 

staff; if the transplant hospital is 

acquired; or, the occurrence of a natural 

disaster, pandemic, or other public 

health emergency or other extreme and 

uncontrollable circumstance that would 

require the transplant hospital to 

temporarily suspend operations. Any of 

these disruptions or fluctuations could 

result in an inaccurate transplant target 

that would not accurately reflect an 

IOTA participant’s volume capability. 

We considered determining the 

national growth rate by calculating 

separately; (1) the growth rate of the 

deceased donor target number by the 

growth in organs procured, and (2) the 

living donor target number by the 

national growth rate in living donor 

transplants (89 FR 43518). However, 

procurement rates vary nationally 

depending on variables unique to each 

geography and local OPO policies.199

Because we want the model to inspire 

kidney transplant hospitals to expand 

living donor programs, not just match 

national growth rates, we did not 

believe this alternative methodology 

was appropriate to propose. 

We also considered determining the 

national growth rate using the following 

information: (1) the total growth rate in 

kidney transplants; (2) the change in 

rate of organs procured by OPOs; (3) the 

growth rate in kidney transplants in the 

non-selected portions of the country; 

and (4) calculating the average growth 

rate across multiple baseline years (89 

FR 43518). However, we believe that the 

national growth rate in kidney 

transplants makes the most sense to use 

as the basis for the model’s growth 

factor because it best reflects volume 

trends in the kidney transplant 

ecosystem overall, as it considers all 

kidney transplant hospitals, not just 

IOTA participants. 

Finally, we also considered a 

performance assessment methodology 

for IOTA participants already achieving 

higher rates of kidney transplantation by 

assessing each such IOTA participant’s 

total transplant volume as compared to 

all IOTA participants, rather than on an 

IOTA participant specific transplant 

target (89 FR 43518). We believe this 

methodology is both easy to understand 

and simple to administer because it 

rewards IOTA participants for the total 

number of transplants performed. 

However, we thought that this 

methodology would not be fair to IOTA 

participants that are smaller in size or 

achieving lower rates of kidney 

transplantation. 

We solicited comment on our 

proposal to set unique transplant targets 

for each IOTA participant, the 

methodology for setting transplant 

targets, and any alternatives considered. 

The following is a summary of the 

comments received on our proposal to 

set unique transplant targets for each 

IOTA participant, the methodology for 

setting transplant targets, any 

alternatives considered and our 

responses: 

Comment: Commenters expressed 

concern over the proposed methodology 

for calculating unique transplant targets 

each PY for each IOTA. Many 

commenters expressed concern that the 

proposed methodology is impractical as 

it overestimates a transplant programs 

capability to increase transplantation 

throughput unilaterally, such as without 

significant improvements in organ 

procurement and distribution by the 

OPTN and OPOs, factors beyond 

hospitals’ control, does not take into 

consideration year over year variability 

in overall donor volume, and could not 

be achieved without potentially 

compromising the quality of care and 

patient safety. Many commenters stated 

that the proposed transplant target 

methodology was unsustainable 

throughout the model, as increasing 

kidney transplant volume would make 

it increasingly difficult for IOTA 

participants to meet ever-higher targets 

in subsequent PYs, potentially leading 

to penalties. 

Many commenters believed that the 

proposed methodology for calculating 

the transplant target for each IOTA 

participant would be unattainable for 

high performing transplant hospitals. 

For example, while a commenter 

supported comparing a kidney 

transplant hospital’s transplant rates to 

the national average, they believed that 

they would be held to an impractically 

high expectation for growth. The 

commenter also argued that kidney 

transplant hospitals already performing 

in the top 20 percent should not be 

penalized for failing to reach an 

unrealistically high transplant rate. 

Another commenter suggested that they 

would need to increase their annual 

adult transplant numbers by 75 to 150 

each year. They felt that the ability to 

achieve this increase would rely on the 

availability of a sufficient number of 

viable organs and a significantly 

increased waitlist. Consequently, they 

believed that their kidney transplant 

hospital could potentially achieve that 

goal and clear their waiting list in the 

first year; however, this assumption 

relied on the premise that every patient 

could be successfully transplanted with 

an appropriate donor match, which they 

considered highly unlikely. A 

commenter believed that the proposed 

methodology advantages smaller kidney 

transplant hospitals disproportionately. 

The commenter argued that it was 

impractical to require a larger kidney 

transplant hospital, already performing 

over 400 transplants annually, to do an 

additional 200 or more transplants to 

earn full points and could not be done 

without compromising quality of care 

and patient safety. The same commenter 

also noted that acquiring the necessary 

staff, space, and resources to 

accommodate such a rapid and 

significant increase would pose a 

substantial obstacle. 

Commenters also raised specific 

concerns over the proposal to trend the 

transplant target forward by the national 

growth rate, as described in section 

III.C.5.c(1) of this final rule. Many 

commenters indicated that the more an 

IOTA participant increases its 

transplant volume, the harder it will be 

for them to achieve their transplant 

target in the future PY because the 

methodology, as proposed, also trends 

the baseline transplant volume forward 


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each PY. Many commenters suggested 

that IOTA participants may be unfairly 

penalized for responding to the model’s 

goals and incentives. Specifically, that if 

IOTA participants meet their transplant 

target during a performance year, the 

rising national growth rate could make 

transplant targets harder to achieve in 

future PYs. A couple commenters 

suggested that the growth rate should be 

regionally indexed or calculated 

separately by region because regional 

factors affect the potential for increased 

transplantation. Lastly, a commenter 

recommended that CMS determine the 

national growth rate by calculating the 

average growth rate across multiple 

baseline years instead of the proposed 

approach. This commenter believed that 

this alternative approach for calculating 

the national growth rate would take into 

consideration the natural variability in 

the annual volume of both living and 

deceased donor transplants performed 

at kidney transplant hospitals, resulting 

in a transplant target that may be more 

attainable for IOTA participants. 

Response: Given the numerous 

concerns from stakeholders regarding 

the proposed methodology for 

calculating transplant targets, we 

recognized an updated methodology 

may be necessary to strengthen the 

model. As indicated in the proposed 

rule (89 FR 43518) and discussed in the 

preamble of this final rule, we 

considered setting each IOTA 

participant’s transplant target by 

determining the IOTA participant’s 

average total kidney transplant volume 

from the three previous years instead of 

using the sum of the highest living and 

deceased donor kidney transplant 

volumes during the baseline years. 

Ultimately, we decided against this 

approach, as we did not believe it 

would accurately reflect the IOTA 

participants’ full transplant capacity. 

Instead, we constructed, and proposed, 

a methodology to illustrate the 

individual capabilities and capacities of 

the IOTA participants, which when 

combined, would serve as an 

appropriate transplant target for the 

program year. However, we recognize 

that there may be a better balance in 

including a simpler methodology and 

result in a transplant target that is 

potentially more attainable for IOTA 

participants, assuming that the average 

kidney transplant volume is lower than 

the sum of the highest volumes of 

deceased and living donor kidney 

transplants while still limiting 

complexity. 

We conducted additional analysis that 

examined one of the methodologies that 

we considered for calculating the 

transplant target as described in section 

III.C.5.c(1) of the proposed rule. 

Specifically, based on public comment, 

we reexamined setting each IOTA 

participant’s transplant target by 

determining the IOTA participant’s 

average total kidney transplant volume 

from the three previous years instead of 

using the sum of the highest living and 

deceased donor kidney transplant 

volumes during the baseline years (89 

FR 43518). Using historical transplant 

data, we compared this methodology to 

what we proposed, as described in this 

final rule, to determine whether an 

alternative methodology for setting the 

transplant target would be potentially 

more attainable. 

Based on additional analysis and the 

commenters concerns about the 

proposed transplant target methodology, 

we are finalizing an updated 

methodology for setting transplant 

targets as follows: 

For each PY, CMS will calculate the 

transplant target for the achievement 

domain by first determining the mean of 

the total number of deceased donor 

kidney transplants and living donor 

kidney transplants furnished to patients 

18 years of age or older across the 

baseline years, as defined and finalized 

in § 512.402 of this final rule. 

The mean number of deceased donor 

and living donor transplants across the 

baseline years of the IOTA participant 

would then be projected forward by the 

national growth rate, as described in 

section III.C.5.c(1) of this final rule, or 

zero should the national growth rate be 

negative, resulting in the transplant 

target for a given PY. 

For example, to calculate the national 

growth rate for PY 1 using the proposed 

model start date of January 1, 2025, 

CMS would first subtract the total 

number of kidney transplants furnished 

to patients 18 years of age or older in 

2022 from the total number of kidney 

transplants furnished to patients 18 

years of age or older in 2023. Next, CMS 

would then divide that number by the 

total number of kidney transplants 

furnished to patients 18 years of age or 

older in 2022 to determine national 

growth rate. To create the transplant 

target for each IOTA participant for the 

relevant PY CMS would do the 

following: 1. If the national growth rate 

is positive, CMS would trend the 

national growth rate forward for an 

IOTA participant by multiplying the 

national growth rate by the mean 

number of deceased donor and living 

donor transplants furnished to patients 

18 years of age or older across the 

baseline years for the IOTA participant. 

2. CMS would take the product of step 

1 and add it to the mean number of the 

highest living donor and deceased 

donor kidney transplants furnished to 

patients 18 years of age or old across the 

baseline years for an IOTA participant. 

3. The sum of step 2 would be the 

transplant target for an IOTA 

participant. However, if the national 

growth rate were negative, CMS would 

not trend the growth rate forward for PY 

1 and the transplant target would be the 

sum of the mean number of living donor 

and deceased donor kidney transplants 

across the baseline years. For example, 

when determining individual transplant 

targets for PY 1 of the model, if an IOTA 

participant had a mean of 50 living 

donor and deceased donor kidney 

transplants furnished to patients 18 

years of age or older across the relevant 

baseline years, and the national growth 

rate was negative, then the transplant 

target for that IOTA participant would 

be 50. 

However, we will monitor IOTA 

participant performance throughout the 

model performance period and, if 

warranted, will propose alternative or 

updated policies in future notice and 

comment rulemaking. 

Comment: Commenters encouraged 

CMS to reconsider how the proposed 

transplant target is calculated and 

suggested a variety of alternative 

options. Many commenters urged CMS 

to set each IOTA participant’s transplant 

target by determining the IOTA 

participant’s average total kidney 

transplant volume from the three 

previous years. Several of these 

commenters urged CMS to set each 

IOTA participant’s transplant target by 

determining the IOTA participant’s 

average total kidney transplant volume 

from the three previous years across the 

relevant baseline years. Specifically, a 

commenter believed that using the 

average number of transplants across the 

relevant baseline years would ensure 

that transplant programs are not 

penalized for their efforts in increasing 

transplant volumes prior to program 

initiation. Another commenter 

expressed concern that the proposed 

approach does not take into account the 

natural year-to-year variability in overall 

and living donor and deceased donor 

volume of transplants performed within 

a kidney transplant hospital. Thus, they 

recommended that each IOTA 

participant’s transplant target be 

calculated by determining the IOTA 

participant’s average total kidney 

transplant volume from the three 

previous years. The commenter stated 

that the three-year averaging approach is 

frequently used by the Innovation 

Center in other payment methodologies, 

which could help reduce year-to-year 

variability and mitigate the impact of 

potential outliers for transplants from 


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deceased or living donors in a given 

year. 

A couple commenters suggested CMS 

use the average kidney transplant 

volume and a fixed baseline. 

Specifically, a commenter felt that using 

the average kidney transplant volume 

would be more reflective of an IOTA 

participant’s expected performance. A 

commenter also recommended that CMS 

take the average of kidney transplant 

volumes over a 5-year historical period, 

as it would more accurately reflect past 

performance. Another commenter 

believed that the transplant target 

should be calculated based on the 

average number of kidney transplants 

performed during a fixed historical 

period to ensure that IOTA participants 

are not penalized for their success in 

increasing transplant volumes. 

A commenter also suggested that CMS 

select the year with the highest total 

volume of living and deceased donor 

kidney transplants combined in relation 

to the three prior years as the historical 

benchmark. The commenter felt that 

this was especially crucial if the 

historical benchmark is then multiplied 

by a national growth rate, as proposed, 

to ensure IOTA participants have a 

realistic chance of meeting the target. 

This same commenter also suggested 

that CMS could consider identifying in 

the relevant baseline years the highest 

number of combined deceased donor 

and living donor kidney transplants and 

then measure and reward subsequent 

growth in each transplant type, 

deceased donor and living donor. 

However, the commenter acknowledged 

that this methodology would be more 

complex and move away from the 

simplicity originally proposed, which is 

a strength of the model. Finally, a 

commenter recommended that CMS use 

a weighted benchmark based on the 

actual number of kidney transplants for 

three years, with the most recent year 

being weighted the most. 

Response: We appreciate the 

commenters’ suggestions on alternative 

methodologies for setting the transplant 

target. As mentioned in comment 

responses noted previously, we 

recognize that there could be a more 

favorable balance by adopting a simpler 

methodology that could result in a 

transplant target that is more feasible for 

IOTA participants, assuming that the 

average kidney transplant volume is 

lower than the total of the highest 

volumes from both deceased and living 

donor kidney transplants, while still 

keeping complexity to a minimum. As 

such, we are finalizing an updated 

methodology for setting transplant 

targets at § 512.424(b). Specifically, 

CMS will calculate the transplant target 

for the achievement domain by first 

determining the mean of the total 

number of deceased donor kidney 

transplants and living donor kidney 

transplants furnished to patients 18 

years of age or older across the baseline 

years, as defined and finalized in 

section III.C.3.c of the preamble in this 

final rule. 

Comment: A couple commenters 

suggested that CMS create a fixed 

baseline year period, rather than 

changing the baseline every PY. For 

example, one of these commenters 

stated that a permanent baseline would 

be particularly beneficial for larger 

institutions, for which year-over-year 

growth is more difficult. Another 

commenter felt that CMS should use a 

fixed baseline year period of five to ten 

years. The commenter noted that a 

kidney transplant hospital’s annual 

volume is often limited to factors 

beyond their control and may vary year 

to year. Thus, they believed that an 

average of transplant volumes over a 

five-to-ten-year period would more 

accurately reflect a participant’s past 

performance. The same commenter also 

acknowledged that the model 

performance years would not factor into 

an IOTA participant’s transplant target 

calculation until the third PY; however; 

they argued that transplant target 

methodology as proposed penalizes 

IOTA participants for their earlier 

successes by making it more difficult to 

exceed the target in the future. 

Therefore, using a fixed baseline would 

ensure IOTA participants are able to 

realistically meet their transplant targets 

and would not be penalized for 

variations in transplant volumes. 

Response: We thank the commenters 

for their feedback. As described at 89 FR 

43552 in the proposed rule, we 

considered a static or fixed baseline 

approach, as it would minimize 

operational burden for CMS due to less 

frequent updates to the transplant target 

and ensure that the model does not set 

a moving target year-over-year. 

However, for the reasons described in 

section III.C.5.c(1) of this final rule, we 

disagree with the commenters that the 

baseline years should be fixed. We 

maintain our belief that the proposed 

rolling baseline approach, which uses 

historical kidney transplant volumes 

pre-dating the model start date through 

the first two model PYs, ensures a 

phased-in approach before any 

improvements made during the model 

performance period are accounted for in 

the baseline. Thus, we are finalizing our 

proposal to calculate the transplant 

target using the relevant baseline years, 

as defined and finalized in section 

III.C.3.c of the preamble in this final 

rule, as proposed. 

Comment: Several commenters raised 

concerns about using CY 2021 when 

calculating the IOTA participant 

specific transplant target. Given that 

transplant hospitals across the U.S. were 

impacted by COVID–19 at different 

points throughout the year, a couple 

commenters believed that CY 2021 data 

may inadvertently skew the baseline 

performance, either increasing or 

decreasing it, obscuring the true 

performance of programs required to 

participate in the IOTA Model. Another 

commenter conveyed that while they 

recognized the importance of analyzing 

past performance over multiple years, 

they suggested that CMS should 

concentrate exclusively on CY’s 2022 

and 2023. 

A few commenters argued that CY 

2021 was an outlier in various aspects 

and might not reflect the usual 

practices, or the current and anticipated 

practices, of numerous transplant 

hospitals. These aspects included the 

COVID–19 pandemic and the change in 

kidney allocation. These commenters 

specifically noted that the COVID–19 

pandemic had a profound influence on 

kidney transplant volumes during 2021. 

They suggested that some transplant 

hospitals lowered their transplant rates, 

whereas others actually ramped up their 

operations. They believed that this 

situation arose in part because 

transplant hospitals that conducted 

fewer transplants allowed for a greater 

availability of high-quality kidneys for 

the transplant hospitals that remained 

operational. Additionally, 2021 was the 

first year the new KAS250 policy took 

effect, and transplant hospitals were 

still adjusting to the significant increase 

in organ offers. 

Response: We thank commenters for 

their feedback and for raising some 

concerns about the proposed 

methodology for setting specific 

transplant targets. We acknowledge the 

commenters’ concerns regarding the 

inclusion of CY 2021 in the baseline 

years as it pertains to setting specific 

transplant targets. We considered setting 

the transplant target for IOTA 

participants based on two baseline 

years, rather than the proposed 

methodology of three, as described at 89 

FR 43552 in the proposed rule. In light 

of the commenters’ concerns, we 

considered the potential impact of 

including CY 2021 in the proposed 

methodology for setting specific 

transplant targets, as described in 

section III.C.5.c(1) of the proposed rule. 

We still believe that using two baseline 

years to set a transplant target would 

make the target more susceptible to 


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temporary market disruptions or 

fluctuations, such as those discussed at 

89 FR 43552 in the proposed rule, 

which could result in an inaccurate 

transplant target that does not 

accurately reflect the IOTA participant’s 

true volume capabilities. As such, we 

disagree with excluding CY 2021 from 

the relevant baseline years when setting 

specific transplant targets. However, as 

mentioned in comment responses noted 

previously in this section, we are 

finalizing a modified methodology for 

setting specific transplant targets. 

Specifically, we are finalizing at 

§ 512.424(b) that CMS would calculate 

the transplant target for the achievement 

domain by first determining the mean of 

the total number of deceased donor 

kidney transplants and living donor 

kidney transplants furnished to patients 

18 years of age or older across the 

baseline years, as defined and finalized 

in section III.C.3.c of this final rule. We 

will analyze and monitor the 

performance of IOTA participants to 

ensure they are not unfairly 

disadvantaged by the model. If our 

analysis indicates the need for a new or 

revised policy, we will address it 

through future notice and comment 

rulemaking. 

Comment: A commenter requested 

that CMS clarify whether the transplant 

number used for the transplant target 

calculation would be based on kidney 

transplants performed for all payors, or 

just Medicare kidney transplants. 

Response: As discussed in the 

proposed rule at 89 FR 43550, CMS 

would calculate the transplant target for 

the achievement domain by first 

determining the highest number of 

deceased donor kidney transplants and 

living donor kidney transplants 

furnished to patients 18 years of age or 

older in a single year during the 

baseline years, as defined in section 

III.C.3.c. of the proposed rule. We clarify 

that the transplant target would be 

calculated based on the number of 

applicable kidney transplants performed 

across all payors. However, as 

mentioned in comment responses noted 

previously, we are finalizing an updated 

methodology for setting transplant 

targets. Specifically, we will be 

finalizing at § 512.424(b) that CMS 

would calculate the transplant target for 

the achievement domain by first 

determining the mean of the total 

number of deceased donor kidney 

transplants and living donor kidney 

transplants furnished to patients 18 

years of age or older across the baseline 

years, as defined and finalized in 

section III.C.3.c of this final rule. We 

note that this would still be inclusive 

across all payors and not just Medicare. 

Comment: A commenter suggested 

that CMS provide each IOTA participant 

with their transplant target three months 

or at least one month prior to the start 

of a performance year rather than by the 

first day of a performance year. 

Knowing the transplant target ahead of 

time will allow participants to prepare 

for the model. 

Response: We appreciate the 

commenter’s suggestion. We note that it 

is our intent to provide each IOTA 

participant with their transplant target 

prior to the first day of each PY. 

However, we acknowledge that 

operational delays could occur which is 

why we proposed to provide each IOTA 

participant with their transplant target 

by the first day of each PY. Thus, to 

account for potential operational delays, 

we are finalizing as proposed. 

Comment: A commenter stated that 

they did not agree with our proposed 

definition of national growth rate. 

Specifically, the commenter disagreed 

with eliminating low-volume kidney 

transplant hospitals when assessing the 

national growth rate. Given transplant 

programs can close and new transplant 

programs can enter the market, the 

commenter felt that the national growth 

rate should be based on all adult kidney 

transplants performed in the country as 

this represents a true reflection of 

growth in kidney transplants performed. 

The commenter went on to express that 

they agreed with CMS that the national 

growth rate in kidney transplants makes 

the most sense to use as the basis for the 

model’s growth factor but felt that the 

national growth rate should reflect the 

total growth rate in kidney transplants 

as measured across all adult transplants 

performed at adult transplant programs 

(with due consideration of the 

definition of an IOTA transplant 

patient). 

Response: We appreciate the 

commenter’s suggestion and 

acknowledge their concerns for 

excluding kidney transplant hospitals 

that fall below the low volume 

threshold from the proposed national 

growth rate, as defined at 89 FR 43617 

in the proposed rule. We note that at 89 

FR 43550 we proposed that CMS would 

calculate the national growth rate by 

determining the percent increase or 

decrease of all kidney transplants 

furnished to patients 18 years of age or 

older from two years prior to the PY to 

one year prior to the PY. We also stated 

at 89 FR 43550 that because the 

proposed national growth rate includes 

IOTA participants and non-IOTA 

participant kidney transplant hospitals, 

we acknowledged that it could make 

achieving the transplant target number 

harder. This is why, if the national 

growth rate becomes negative for a PY, 

we proposed treating it as zero and CMS 

would not apply the national growth 

rate to project forward the sum of the 

highest number of deceased and living 

donor kidney transplants furnished in a 

single year during the baseline years. 

However, upon further consideration, 

CMS agrees with this commenter’s 

suggestion. As such, we will be 

finalizing a modified definition of 

national growth rate at § 512.402 to 

eliminate the exclusion of kidney 

transplant hospitals that fall below the 

low volume threshold from the national 

growth rate calculation. 

Comment: A commenter indicated 

that CMS proposed to calculate the 

national growth rate by determining the 

percent increase or decrease of all 

kidney transplants furnished to patients 

18 years of age or older from two years 

prior to the PY to one year prior to the 

PY. However, the commenter suggested 

that CMS should provide clarification 

around whether the national growth rate 

would be rounded. Specifically, the 

commenter wanted to know if, when, 

and how rounding would be applied to 

these calculations. Additionally, the 

commenter also wanted to know if the 

national growth rate would be rounded, 

and if so, to what extent. The 

commenter believed that this is 

important for the calculation of each 

IOTA participant’s transplant target. 

The commenter also suggested that 

providing more clarity here could help 

improve understanding as the IOTA 

Model is implemented. 

Response: We thank the commenter 

for highlighting the need for clarity 

regarding whether any of the proposed 

calculations for setting a transplant 

target would be rounded. We clarify that 

once all calculations for setting a 

transplant target have been made, CMS 

would do the following: 

• Round the transplant target down 

for decimals less than 0.500; and 

• Round the transplant target up for 

decimals of 0.500 or greater. 

For example, if an IOTA participants 

transplant target is 57.44, CMS would 

round the transplant target down to 57. 

Whereas, if an IOTA participants 

transplant target was 57.54, CMS would 

round the transplant target up to 58. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

our proposed provisions on setting 

unique transplant targets for each IOTA 

participant and the methodology for 

setting transplant targets, with 

modification. We are codifying in our 

regulation at § 512.424(b) that for each 

PY, CMS will determine the transplant 


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target for the achievement domain, as 

proposed. 

We are codifying in our regulation at 

§ 512.424(b)(1) that CMS analyzes the 

baseline years for the relevant PY, 

without modification. In response to 

comments received, we are replacing 

the methodology for setting unique 

transplant targets we had proposed to 

use for purposes of determining 

performance in the achievement 

domain. Specifically, we are codifying 

in our regulation in sections 

§ 512.424(b)(1)(i) and (ii) that CMS 

identifies the mean number of deceased 

donor kidney transplants furnished by 

the IOTA participant to patients 18 

years of age or older across the relevant 

baseline years, as defined at § 512.402 

and the mean number of living donor 

kidney transplants furnished by the 

IOTA participant to patients 18 years of 

age across the baseline years, as defined 

at § 512.402. 

We are finalizing our regulation at 

§ 512.424(b)(2) that CMS sums the 

numbers in sections §§ 512.424(b)(1)(i) 

and (ii), without modification. We are 

also finalizing as proposed our 

provisions for calculating the national 

growth rate at § 512.424(b)(3), 

calculation of transplant target at 

§ 512.582(b)(4), notification of 

transplant target at § 512.424(c) and the 

definitions of transplant target, and 

pediatric kidney transplant hospitals at 

§ 512.402. In response to public 

comments, we are finalizing our 

proposed definition of national growth 

rate at § 512.402 with slight 

modification to remove the exclusion of 

kidney transplant hospitals that fall 

below a low-volume threshold of 11. 

Specifically, we are codifying at 

§ 512.402 that national growth rate 

means the percentage increase or 

decrease in the number of kidney 

transplants performed over a 12-month 

period by all kidney transplant hospitals 

except for pediatric kidney transplant 

hospitals, as defined at § 512.402. We 

note that we will analyze and monitor 

IOTA participant performance 

throughout the model performance 

period to ensure we do not unduly 

disadvantage IOTA participants. If 

analysis results warrant a new or 

updated policy, we will address it 

pursuant to future notice and comment 

rulemaking. 

(2) Calculation of Points 

In section III.C.5.c(2) of the proposed 

rule, we proposed that the achievement 

domain would be worth 60 points. We 

chose this domain for the highest 

number of points because we believe 

that driving an increase in the number 

of transplants should be the main 

incentive for change in the model. We 

considered allocating fewer points to 

this domain, such as 50 points, but we 

believe that performance in this domain 

should impact the overall performance 

score more than the other domains 

given its centrality to the model. 

In section III.C.5.c(2) of the proposed 

rule, we proposed that an IOTA 

participant’s performance would be 

assessed relative to their transplant 

target, with those performing at less 

than 75 percent of the transplant target 

receiving no points and those 

performing at 150 percent of the 

transplant target or above receiving the 

maximum number of points (60 points). 

That is, at the highest end of the scale, 

IOTA participants performing at or 

above 150 percent of the transplant 

target would earn the maximum 60 

points, while at the lowest end of the 

scale, IOTA participants performing at 

less than 75 percent of the transplant 

target would earn no points for the 

achievement domain; performance that 

falls in between 75 percent and 150 

percent of the transplant target may earn 

the IOTA participant 45, 30, or 15 

points in the achievement domain. 

Table 3 illustrates our proposal for how 

an IOTA participant’s performance 

would be assessed against its transplant 

target. We chose 150 percent as the 

maximum performance level based on 

the theoretical capability of growth in 

one year and analysis in trends of 

transplant over time. We recognized that 

an IOTA participant might exceed 150 

percent of its transplant target, but this 

was not expected given the investment 

needed for substantiable transplant 

infrastructure to consistently support 

that number of transplants over time. 

We stated in the proposed rule that 

we believe that a methodology based on 

performance improvement relative to 

historical performance is important and 

would allow us to test whether the 

model’s performance-based payments 

drive increased behavior from IOTA 

participant, as opposed to just 

rewarding IOTA participants based on 

the status quo (89 FR 43518). IOTA 

participants that are achieving a high 

rate of kidney transplantation, and 

already have robust transplant programs 

at the start, can more easily scale up to 

achieve the additional growth required 

for excellent performance under the 

model. Also, given our statutory 

requirements to achieve savings, the 

CMS Office of the Actuary (OACT) 

estimates, as described in section VI of 

the proposed rule, suggested that 

savings would be driven by the effects 

of increased transplants. We believed 

that the model’s performance-based 

payments need to be tied to a policy that 

aims to create and drive Medicare 

savings. 

We considered offering differential 

credit for transplants by type (89 FR 

43518). With this methodology, IOTA 

participants would receive bonus points 

and score higher for transplants that fit 

into categories that lead to more savings, 

such as living donor kidney transplants 

(LDK), high KDPI donors, or preemptive transplants, compared to other 

transplants. However, we believed that 

counting all transplants the same, 

except for transplants furnished to 

underserved populations, would 

maximize flexibility for IOTA 


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TABLE 3: PROPOSED ASSESSMENT OF ACHIEVEMENT DOMAIN 

Greater than 15 0% 

Less than 150% 45 

Less than 125% 30 

Less than 100% 15 

Less than 75% 0 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96337 

participants in meeting their targets and 

minimize the potential harm and 

unintended consequences the 

alternative system would create. 

As an alternative, we considered 

including gradient points instead of 

points based on bands (that is, between 

X and Y) (89 FR 43518). Scoring closer 

to a performance minimum would result 

in increased points rather than 

remaining static throughout the band. 

We considered the following formula: 

Percent Performance Relative to 

Transplant Target * (100/2.5), not to 

exceed 60 points. However, we decided 

that a narrower range of results would 

better differentiate performance among 

IOTA participants and allow for easier 

comparison across IOTA participants. 

We also considered smaller point 

brackets of improvement, requiring 

IOTA participants to achieve a flat 

number increase of kidney transplants, 

such as to a 140 percent, 125 percent, 

or 120 percent, to achieve the highest 

performance in this category, and 

asymmetric point brackets that would 

make the magnitude of performance 

required to achieve the highest 

performance rate a flat number increase 

in addition to a percentage increase (89 

FR 43518). However, we wanted the 

percentage of the transplant target 

necessary to achieve the highest number 

of points to be large enough to 

incentivize behavior while still being 

achievable. 

We also considered improvementonly scoring, based on year-over-year 

IOTA participant transplant growth, 

without inclusion of national rates (89 

FR 43518). In this methodology, positive 

improvement rates less than 5 percent 

would be scored 15 points, rates over 5 

percent would be scored 30 points, rates 

over 20 percent would be scored 45 

points, and rates over 50 percent would 

be scored 60 points. We also considered 

using combinations of potential 

transplant target or scoring methods, 

with the final score being whichever 

score was highest to ensure low-volume 

IOTA participants are not penalized and 

to mitigate unrealistic transplant targets. 

We considered an improvement-only 

scoring methodology to reflect the 

historical performance of each IOTA 

participant. However, because we want 

a methodology that sets more of a 

national standard for expected growth 

rate to assess volume trends in the 

transplant space overall, we chose not to 

propose improvement-only scoring. As 

organ supply continues to increase yearover-year, we wish to set the 

expectation for IOTA participants to 

grow their transplant volumes at least at 

the cadence of the national growth rate. 

We solicited comment on our 

proposed achievement domain scoring 

methodology and alternative 

methodologies considered. 

The following is a summary of the 

comments received on our proposed 

achievement domain scoring 

methodology, alternative methodologies 

considered and our responses: 

Comment: Numerous commenters 

expressed concerns that the 

achievement domain requires an 

impractically significant increase in 

kidney transplant volume, especially in 

the later PYs of the IOTA Model. In 

particular, they felt it would be virtually 

impossible for IOTA participants to earn 

the maximum points in this domain, 

and that the proposed approach would 

undermine the overall model test. 

Response: We recognize the validity 

of this critique from commenters and 

believe in updating the achievement 

domain in two key areas. The first is 

that the transplant target for each IOTA 

participant will be calculated based on 

a rolling average of transplants, as 

described and finalized in section 

III.C.5.c(a) of this final rule, rather than 

taking the highest number of living and 

deceased transplants across the relevant 

baseline years, as discussed previously. 

The second is to modify our scoring 

methodology for allocating points for 

the achievement domain at Table 1 

under § 512.424(f)(2), as illustrated in 

Table 4 of this section. 

Comment: Several commenters 

expressed concern that the proposed 

thresholds for increasing transplant 

rates are aggressive such that they could 

negatively impact performance score 

metrics for all IOTA participants, 

recommending that CMS set more 

realistic performance goals by lowering 

the points thresholds in the 

achievement domain. For instance, a 

commenter supported the proposed 

methodology of awarding points based 

on percentage relative to transplant 

target thresholds. However, they 

believed the proposed points thresholds 

exceeded reasonable expectations for 

eligible kidney transplant hospitals. The 

commenter recommended that CMS set 

the highest points threshold (60 points) 

at greater than 125 percent of the 

transplant target, and drop the lowest 

points threshold (0 points) to less than 

50 percent of the transplant target. This, 

the commenter felt, would ease IOTA 

participants’ ability to receive 

achievement domain points, help 

alleviate resource disparities between 

participant hospitals, and reduce the 

potential for financial considerations to 

cloud clinical judgment when matching 

organs to recipients. 

Another commenter recommended 

that CMS use a volume growth trend 

that better recognizes the potential 

limits of transplant programs to expand 

capacity in a more reliable, realistic, and 

safe manner. The commenter felt that 

having a transplant goal that is more 

achievable would also incentivize the 

growth the IOTA Model is trying to 

achieve. Setting transplant targets too 

high could discourage IOTA 

participants from growing their kidney 

transplant programs at all if the targets 

are unrealistic and not achievable. As 

such, this same commenter 

recommended that CMS allow IOTA 

participants to achieve the maximum 60 

points for the achievement domain with 

performance equal or greater than 110 

percent of the transplant target. 

Another commenter stated that to 

achieve a 10 percent increase in kidney 

transplants, a large-volume kidney 

transplant hospital performing 400 

transplants annually would need to do 

an additional 40 per year. While the 

increase would be less for smaller 

kidney transplant hospitals, any 

additional transplants may strain their 

personnel and infrastructure. The 

commenter also suggested that kidney 

transplant hospitals of any size need 

appropriate lead time to estimate and 

accommodate the increase in transplant 

volume. Expanding transplant capacity 

requires significant infrastructures 

investments, such as for higher-risk 

candidates and donor organs, infusion 

bays, access to inpatient and outpatient 

dialysis for higher volumes of 

recovering recipients with delayed graft 

function, and additional personnel. The 

commenter warned that disregarding 

these infrastructure needs would put 

undue stress on the healthcare system 

and could prevent IOTA participants 

from meeting mandated targets. For 

these reasons, they recommended that 

the achievement domain points 

thresholds be lowered to a more realistic 

performance metric (for example, 110 to 

125 percent relative to transplant target). 

Lastly, a commenter believed that the 

proposed achievement domain points 

thresholds are too aggressive and would 

sharply curtail the opportunity for IOTA 

participants to achieve more than 30 

points in any PY. The commenter 

suggested an alternative approach that 

would allow IOTA participants to earn 

the maximum 60 points in the 

achievement domain if their 

performance exceeded the transplant 

target by 125 percent or more. 

Response: We thank the commenters 

for expressing their concerns and for 

their suggestions on our proposed 

methodology for awarding points for 

performance in the achievement 


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96338 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

domain. As described in the proposed 

rule at 89 FR 43553, we considered 

smaller point brackets of improvement 

to achieve the highest performance in 

this category but chose not to propose 

smaller point brackets of improvement 

as we wanted the percentage of the 

transplant target necessary to achieve 

the highest number of points to be large 

enough to incentivize behavior while 

still being achievable. However, in 

response to comments received, we are 

updating the methodology for points 

allocation in the achievement domain. 

Specifically, we are finalizing, with 

modification, Table 1 to Paragraph (f)(2) 

at § 512.424(f)(2) to reflect the updated 

points allocation, as illustrated in Table 

4. 

We believe that the updated scoring 

system reflects our partial agreement 

with commenters. Specifically, we are 

lowering the maximum performance 

threshold from 150 percent to 125 

percent of the transplant target. 

Moreover, in combination with the 

updated methodology for setting 

transplant targets, as described and 

finalized section III.C.5.c(1) of this final 

rule, we believe that this revised 

standard is more achievable for IOTA 

participants and strikes a balance—it 

aims to incentivize performance, while 

also recognizing the challenges that 

IOTA participants may face in 

increasing their kidney transplant 

volume. 

Lastly, because we are updating 

achievement domain performance 

thresholds and points allocation, we are 

keeping the performance threshold for 

earning 0 points at 75 percent of the 

transplant target as proposed at 89 FR 

43553. This is to ensure a minimum 

level of performance from IOTA 

participants and keep the focus on 

ensuring that the number of kidney 

transplants performed by IOTA 

participants does not significantly 

decrease. 

Comment: A commenter suggested 

that CMS adopt a more graduated 

scoring scale, providing additional 

opportunities for IOTA participants to 

earn points in the achievement domain. 

Response: We appreciate the feedback 

from the commenter. As mentioned in 

comment responses noted previously, in 

light of the comments received, we are 

updating the methodology for points 

allocation in the achievement domain, 

as illustrated in Table 4 of this section. 

The updated methodology for point 

allocation includes additional 

gradations, which we believe will 

provide IOTA participants with greater 

opportunities to earn points compared 

to the four scoring ranges we originally 

proposed at 89 FR 43553 in the 

proposed rule. 

Comment: A commenter expressed 

concerns that the proposed 

methodology for calculating transplant 

targets would have compounding 

negative effects on performance over 

time, making it increasingly difficult for 

IOTA participants to earn maximum 

points in the achievement domain in 

later years of the model. 

Response: We thank the commenter 

for raising their concern. We recognize 

that the proposed methodology may 

have set a standard that may have been 

too difficult for IOTA participants to 

meet. We believe that our updated 

methodology for setting the transplant 

target, as described and finalized in 

section III.C.5.c(1) of this final rule, sets 

a balance between trying to incentivize 

improvement over time with allowing 

IOTA participants to recognize the 

benefits of investment in increasing 

their number of kidney transplants. 

Moreover, as described in the proposed 

rule at 89 FR 43550, the model PYs 

would not factor into an IOTA 

participant’s transplant target 

calculation until PY 3 of the model and 

the baseline years would not be based 

exclusively on PYs until PY 5 of the 

model. We maintain our belief that 

using baseline years to calculate the 

transplant targets could represent an 

effective phase-in approach to drive 

improved performance and savings for 

the Medicare trust fund, while also 

accounting for kidney transplant 

hospitals that experience changes in 

strategy or staffing that may affect their 

transplant capacity compared to 

previous years. 

Comment: We received a comment 

that the only way that IOTA participants 

can increase their supply is by using 

marginal organs which would result in 

increased rates of graft failure for 

transplanted patients. 

Response: We disagree with this 

commenter and would like to provide 

clarification. We did not specify how 

IOTA participants should increase their 

number of kidney transplants, nor do 

we believe that the only way that IOTA 

participants can increase their number 

of transplants is by using marginal 

organs. In the proposed rule at 89 FR 

43551, we expressed our belief that 

IOTA participants could improve on 

this metric and provided several 

possible ways that they might be able to. 

We acknowledge that some IOTA 

participants may choose to increase 

their utilization of DCD kidneys or 

kidneys with a KDPI greater than 85, 

however, the IOTA Model does not 

prescribe that they do. Additionally, the 

CoPs for transplant hospitals require 

that the transplanting surgeon at the 

transplant program is responsible for 

ensuring the medical suitability of 

donor organs for transplantation into the 

intended recipient (42 CFR 482.92). 


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TABLE 4: ASSESSMENT OF ACHIEVEMENT DOMAIN 

Greater than 125% 

120% oftr Less than 125% 55 

115% oftr Less than 120% 50 

105% oftr Less than 115% 40 

Less than 105% 30 

Less than 95% 20 

75% oftr Less than 85% 10 

75% oftr Less than 75% 0 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96339 

Furthermore, we believe that many 

organs that are not used today have a 

clinical profile similar to organs that are 

ultimately transplanted. As such, we 

expect that IOTA participants will 

exercise their medical judgement 

appropriately when determining 

whether or not to accept a DCD kidney 

organ offer. 

Comment: We received a comment 

that there is not enough available 

transplant supply to increase numbers, 

particularly at the thresholds that CMS 

set in the proposed scoring for the 

achievement domain. 

Response: We believe that the 

updated transplant target methodology 

and scoring methodology make the 

transplant targets more achievable for 

IOTA participants. We also recognize 

the growth in organs being procured by 

OPOs since the 2020 CfC update and 

believe that there is an opportunity for 

transplant hospitals to take advantage of 

the updated supply being procured by 

OPOs. Additionally, we believe that 

living donation represents an untapped 

supply of potential kidney transplants 

that is not dependent on procurement 

practices. 

Comment: A commenter expressed 

their disagreement with the proposed 

achievement domain performance 

thresholds, as they do not take into 

account the inability of transplant 

programs to scale up the volume of the 

number of transplants performed in a 

given year. The commenter believed 

that some transplant programs may have 

excess capacity to perform more 

transplants annually, but others would 

face significant fixed costs to expand 

their transplant operations beyond their 

current volume. Additionally, the 

commenter noted that in the current 

labor market, it would be challenging to 

recruit and retain the highly specialized 

staff, including transplant physicians, 

needed to expand the capacity of their 

transplant program to meet these 

transplant targets. 

Response: We recognize that there 

will be some need for IOTA participants 

to scale up, which is why we are not 

finalizing the proposed model start date 

of January 1, 2025. As described and 

finalized in section III.C.1.a of this final 

rule, we are finalizing a model start date 

of July 1, 2025. We also note that there 

is no downside risk payment in PY 1, 

as described and finalized in section 

III.C.6.c(2)(b) of this final rule. As such, 

it will be over 18 months from the 

publication of this final rule until an 

IOTA participant is held liable for their 

number of transplants with the potential 

for a downside risk payment. 

Furthermore, as mentioned in comment 

responses in this section, we will be 

finalizing an updated methodology for 

points allocation in the achievement 

domain, as illustrated in Table 4 in this 

section, and our methodology for setting 

transplant targets, as described and 

finalized in section III.C.5.c(1) of this 

final rule. For these reasons, we believe 

this will give time for IOTA participants 

to make investments to expand their 

transplant program, resulting in a 

transplant target that is potentially more 

attainable for IOTA participants and 

providing additional opportunities to be 

awarded points. 

Comment: Multiple commenters 

expressed concern that the proposed 

scoring methodology was too difficult 

for large kidney transplant hospitals, 

given that a significant percentage 

increase for them represents a higher 

number of additional transplants. We 

also received comments pointing out 

that the scoring methodology could be 

punitive to IOTA participants that 

already invested to increase their 

number of transplants before the start of 

the model. 

Response: We thank the commenters 

for expressing their concerns regarding 

the proposed scoring methodology. We 

note that, as described and finalized in 

section III.C.5.c(1) of this final rule, that 

we are finalizing an updated 

methodology for setting transplant 

targets. We direct readers to section 

III.C.5.c(1) of this final rule for further 

discussion on our updated methodology 

for setting transplant targets. As such, 

we believe that this updated 

methodology for setting transplant 

targets will make top performance in the 

achievement domain more achievable 

for all kidney transplant hospitals 

participating in the model. We also 

recognize that larger kidney transplant 

hospitals have already invested in 

additional capacity and resources to 

help more patients through the 

transplant process, which means that 

they have experience in increasing their 

transplant numbers that they can 

leverage as IOTA participants. 

Comment: We received comments 

that the proposed scoring methodology 

was too difficult for smaller kidney 

transplant hospitals. Commenters 

pointed out that smaller kidney 

transplant hospitals may experience 

fluctuations in their transplant volume. 

Given their lower volume of kidney 

transplants, a small numerical decrease 

in the number of kidney transplants 

they perform could translate to a large 

percentage drop, potentially resulting in 

a loss of all points in the achievement 

domain. 

Response: We believe that the 

updated methodology for setting 

transplant targets, as described and 

finalized in section III.C.5.c(1) of this 

final rule, will help smaller kidney 

transplant hospitals selected to 

participate in the model deal with 

fluctuations. We direct readers to 

section III.C.5.c(1) of this final rule for 

further discussion on our updated 

methodology for calculating transplant 

targets. The updated scoring 

methodology, as shown in Table 4, will 

provide more gradation in scoring. As 

such, we believe that this should 

prevent small kidney transplant 

hospitals from being significantly 

impacted if they fall short of their 

transplant targets by a small margin. 

The increased number of scoring 

thresholds means IOTA participants 

will have more opportunities to earn 

points, minimizing the effect of minor 

shortfalls. 

Comment: Several commenters 

proposed including a living donor 

performance adjustment, which would 

award additional points for living donor 

kidney transplants. A commenter 

suggested that, in the absence of 

adequate risk adjustment, a performance 

adjustment, similar to the proposed 

health equity adjustment, with a 

weighting greater than 1 should also be 

considered for living donor transplants. 

Another commenter suggested that CMS 

should consider including an incentive 

multiplier in the achievement domain 

point calculation for living donor 

kidney transplants, as this is the optimal 

treatment for patients with end-stage 

kidney disease (ESKD). Lastly, a 

commenter praised CMS’s efforts to 

improve the organ transplantation 

system, but recommended giving greater 

weight to living donor kidney 

transplants over deceased donor 

kidneys for several reasons. For 

example, the commenter cited that 

living donor kidneys typically have a 

lower risk of graft failure compared to 

deceased donor kidneys. This results in 

longer lifespans for living donor kidney 

recipients, fewer complications, better 

post-transplant outcomes, and reduced 

burden on the healthcare system— 

ultimately enhancing overall patient 

health. Additionally, they noted that 

there is a reduced need for 

immunosuppressive medications 

because patients receiving a living 

donor kidney often require less 

immunosuppressive drugs. For these 

reasons, the commenter proposed that 

CMS either assign a larger weight to 

living donor kidney transplants or apply 

a multiplier akin to the proposed health 

equity performance adjustment. 

Response: We thank the commenters 

for their suggestions to include a living 

donor performance adjustment. We 

recognize the benefits of living donor 


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transplantation and views it as an 

important part of the transplant process. 

However, the IOTA Model test 

prioritizes flexibility, allowing IOTA 

participants to determine the best way 

to perform. We also acknowledge that 

IOTA participants may have varying 

comfort levels with promoting living 

donation. As such, we want to prioritize 

flexibility for IOTA participants rather 

than specifically promoting any 

particular transplant type. Additionally, 

we believe that the composite graft 

survival rate measure, as described and 

finalized in section III.C.5.e(1) of this 

final rule, in the quality domain 

accounts for the potential long-term 

survival benefits of living donation for 

patients. 

Comment: A commenter suggested 

that IOTA participants receive 

additional points in the proposed 

achievement domain scoring 

methodology for preemptive kidney 

transplants, as they offer considerable 

survival and quality of life benefits for 

patients, as well as major cost savings. 

Given the substantial benefits to 

patients and the substantial savings as 

compared to dialysis, the commenter 

recommended that CMS consider 

creating a preemptive bonus or 

preemptive multiplier, which could be 

scaled proportionately with savings to 

the Medicare program pre-emptive 

transplants provide relative to 

maintenance dialysis. However, the 

commenter emphasized that carefully 

calibrating and closely monitoring such 

a bonus or multiplier would be crucial. 

Ideally, this process should involve 

input from the community to ensure the 

incentive expands access to pre-emptive 

kidney transplants rather than 

exacerbating existing disparities. 

Response: We thank the commenter 

for their suggestion but disagree with 

the commenter. We recognize the 

benefits of preemptive transplantation. 

However, we are unsure whether the 

inclusion of a preemptive kidney 

transplant performance adjustment 

would be effective at incentivizing 

preemptive transplantation. We plan to 

monitor the effects of the model on 

preemptive transplantation as part of 

the evaluation process and may 

consider potential changes to the model 

through future notice and comment 

rulemaking, depending on performance 

by IOTA participants. 

Comment: A couple commenters 

suggested that CMS should use two 

metrics to score IOTA participants in 

the achievement domain: percentage 

growth in kidney transplants and a flat 

threshold for increased kidney 

transplant volume. For instance, a 

commenter proposed that IOTA 

participants earn maximum points if 

they achieve 150 percent of their 

transplant target or perform 25 

additional kidney transplants. 

Response: We thank the commenters 

for their suggestions to include an 

additional flat threshold scoring 

methodology. We understand the merits 

of this idea as it recognizes that it may 

be more difficult for IOTA participants 

that are already performing more 

transplants to further increase their 

number of transplants. As described at 

89 FR 43553 in the proposed rule, we 

considered a methodology based on 

year-over-year IOTA participant 

transplant growth, excluding national 

growth rates. We also considered using 

combination of potential transplant 

target or scoring methodologies, taking 

the highest resulting score to avoid 

penalizing low-volume IOTA 

participants and prevent unrealistic 

transplant targets. However, for the 

reasons described in section III.C.5.c(2) 

of this final rule, we chose not to 

propose either of the methodologies 

discussed previously. 

We believe that the updated 

methodology for setting transplant 

targets, as described and finalized in 

section III.C.5.c(1) of this final rule, and 

the updated scoring methodology in the 

achievement domain, as illustrated in 

Table 4 in comment responses noted 

previously, will make it more 

achievable for IOTA participants of all 

sizes to achieve maximum points in this 

domain. 

Comment: A commenter expressed 

their concern over the number of 

proposed points for the achievement 

domain (60 points) and quality domain 

(20 points). Specifically, the commenter 

was concerned that, in the context of 

resource scarce kidney transplant 

hospitals, resources would be pulled 

from efforts to help patients succeed in 

the long-term (post one-year) period in 

order to deliver success on increasing 

transplant rates. As such, the 

commenter believed that greater 

emphasis was needed to encourage 

focus on, and investment in, supporting 

patients’ longer-term (post-one-year and 

longer) outcomes post-transplant, 

recommending that CMS allocate a 

maximum of 50 points for the 

achievement domain instead of the 

proposed 60 points. 

Response: We appreciate the 

commenter’s recommendation and 

acknowledge their concerns. The 

achievement domain performance score 

was weighted more heavily than the 

efficiency and quality domains because 

we believe this aligns with the IOTA 

Model’s primary objective of increasing 

the total number of kidney transplants 

(89 FR 43548). Moreover, recognizing 

that the main goal of the model is to 

increase the number of kidney 

transplants performed, we maintain that 

weighing performance on this measure 

more than the efficiency domain and 

quality domain is necessary to directly 

incentivize participants to meet their 

target, as increasing the number of 

kidney transplants performed is the 

primary goal of the model. For these 

reasons, we disagree with the 

commenter that CMS should decrease 

the number of proposed points allocated 

for the achievement domain and are 

finalizing our proposal to allocate 60 out 

of a maximum 100 points to the 

achievement domain, as described and 

finalized in section III.C.5(b) of this final 

rule. Regarding our proposed point 

allocations across the achievement 

domain, efficiency domain, and quality 

domain, and alternatives we considered, 

we direct readers to section III.C.4.b of 

this final rule. We note that we intend 

to monitor the impacts of the quality 

domain and efficiency domain 

throughout the model test and will 

consider whether adjustments in the 

maximum number of points awarded in 

each domain are necessary in future 

notice and comment rulemaking. 

After consideration of the public 

comments, for the reasons set forth in 

this rule, we are finalizing our proposed 

achievement domain scoring 

methodology, with modification. As 

described in section III.C.5.c(3) of the 

preamble in this final rule, we will not 

be finalizing a health equity 

performance adjustment provision. As 

such, we are finalizing the provisions at 

§ 512.424(a) with slight modification. 

Specifically, we are modifying the 

regulatory text at § 512.424(a)(2) to 

remove references to a health equity 

performance adjustment and make 

minor technical corrections in 

punctuation. 

We are codifying in our regulation at 

§ 512.424(f) that for each PY, CMS 

awards the IOTA participant zero to 60 

points for its performance in the 

achievement domain, as proposed. We 

are also making a minor technical 

correction to update the cross reference 

in our regulation at § 512.424(f)(1). In 

particular, we are removing the cross 

reference to the health equity 

performance adjustment and replacing it 

to reflect § 512.424(d)(2). We direct 

readers to section III.C.5.c(3) of this final 

rule for further discussion on the health 

equity performance adjustment. 

We are also finalizing § 512.424(f)(2) 

as proposed, which states that for each 

PY, CMS will calculate the transplant 

target for the achievement domain, as 

proposed. Lastly, in response to 


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200 Gillen, E.M., Ganesan, N., Kyei-Baffour, B., & 

Gooding, M. (2021, August 30). Avalere analysis of 

disparities in Kidney Care Service Utilization. 

Avalere Health. https://avalere.com/insights/ 

avalere-analysis-of-disparities-in-kidney-careservice-utilization. 

201United States Renal Data System. (2020). 2020 

USRDS Annual Data Report: Epidemiology of 

kidney disease in the United States. National 

Institutes of Health, National Institute of Diabetes 

and Digestive and Kidney Diseases. Bethesda, MD. 

202Lentine, K.L., Smith, J.M., Hart, A., Miller, J., 

Skeans, M.A., Larkin, L., Robinson, A., Gauntt, K., 

Israni, A.K., Hirose, R., & Snyder, J.J. (2022). OPTN/ 

SRTR 2020 Annual Data Report: Kidney. American 

Journal of Transplantation, 22(S2), 21–136. https:// 

doi.org/10.1111/ajt.16982. 

203Neighborhood Atlas—Home. (2018). Wisc.edu. 

https://www.neighborhoodatlas.medicine.wisc.edu/. 

204https://www2.census.gov/geo/pdfs/reference/ 

GARM/Ch11GARM.pdf. 

comments received, we are replacing 

the methodology for points allocation in 

the achievement domain. Specifically, 

we are finalizing, with modification, 

Table 1 to Paragraph (f)(2) at 

§ 512.424(f)(2) to reflect the updated 

points allocation, as illustrated in Table 

4 above. However, we will analyze and 

monitor IOTA participant performance 

through the model test to ensure we do 

not unduly disadvantage kidney 

transplant hospitals selected for the 

model. If analysis results indicate that a 

change in policy is warranted, we will 

address it pursuant to future notice and 

comment rulemaking. 

(3) Health Equity Performance 

Adjustment 

Socioeconomic factors impact patient 

access to kidney transplants. Patients 

with limited resources or access to care 

may require more assistance from 

kidney transplant hospitals to overcome 

barriers to transplantation. To 

incentivize IOTA participants to 

decrease disparities in the overall 

transplant rate among patients of 

various income levels, we proposed to 

include a health equity performance 

adjustment in the methodology for 

calculating the overall number of 

transplants furnished to patients 

attributed to an IOTA participant during 

the PY. We proposed to define the 

‘‘health equity performance adjustment’’ 

as the multiplier applied to each kidney 

transplant furnished to a low-income 

population IOTA transplant patient 

when calculating the transplant target 

(as described in § 512.424 of the 

proposed rule). For purposes of the 

model, we proposed to define the ‘‘lowincome population’’ to mean an IOTA 

transplant patient in one or more of the 

following groups: 

• The uninsured. 

• Medicaid beneficiaries. 

• Medicare-Medicaid dually eligible 

beneficiaries. 

• Recipients of the Medicare lowincome subsidy. 

• Recipients of reimbursements from 

the Living Organ Donation 

Reimbursement Program administered 

by the National Living Donor Assistance 

Center (NLDAC). 

In the proposed rule, we proposed to 

apply a health equity performance 

adjustment, a 1.2 multiplier, to each 

kidney transplant furnished by an IOTA 

participant to a patient, 18 years of age 

or older at the time of transplant, that 

meets the low-income population 

definition. That is, each kidney 

transplant that is furnished to a patient 

who meets the low-income population 

definition would be multiplied by 1.2, 

thus counting that transplant as 1.2 

instead of 1. The resulting count of the 

overall number of kidney transplants 

performed during the PY, after the 

health equity performance adjustment is 

applied, would then be compared to the 

transplant target. In effect, the health 

equity performance adjustment would 

be a reward-only adjustment to the 

performance score in the achievement 

domain. We also considered basing the 

multiplier on the difference between 

rates of transplantation for Medicare 

beneficiaries with ESRD who are dual 

eligible and those who are not. In 2019, 

47 percent of Medicare beneficiaries 

with ESRD were dually eligible for 

Medicare and Medicaid. However, only 

41 percent of Medicare transplants 

recipients were dually eligible, which 

would yield a multiplier of 1.1.200

We chose 1.2 as the health equity 

performance adjustment multiplier 

because, according to USRDS data, 78.6 

percent of patients living with ESRD 

have some form of Medicare and or 

Medicaid coverage; however, only 65.1 

percent of patients who received 

transplants in 2020 were on Medicare, 

Medicaid, or both.201 202 The 1.2 

multiplier represents the ratio of those 

living with ESRD and those who 

received transplants. We theorized that 

providing this incentive for IOTA 

participants to increase their transplant 

rate among low-income populations 

would ultimately reduce disparities in 

access to kidney transplants, as it would 

encourage IOTA participants to address 

access barriers low-income patients 

often face, such as transportation, 

remaining active on the kidney 

transplant waiting list, and making their 

way through the living donation 

process. 

We believed that the health equity 

performance adjustment would be a 

strong incentive to promote health 

equity, as the multiplier earned would 

help IOTA participants meet or exceed 

their kidney transplant target, thereby 

potentially resulting in upside risk 

payments given the heavy weighted 

scoring applied to the achievement 

domain. We also believed it would 

ensure IOTA participants that serve 

disproportionately high numbers of lowincome populations are not penalized in 

the achievement performance scoring. 

We considered not applying a health 

equity performance adjustment to the 

achievement performance scoring, 

which would ensure all kidney 

transplants, regardless of the lowincome status of individual patients, are 

counted as one transplant. The concern 

with the health equity performance 

adjustment may be that it may 

incentivize shifting of kidney 

transplants from one type of patient to 

another. However, we believed the 

incentive is to promote improvement 

activities that would increase access to 

all patients while recognizing that lowincome patients may face more barriers 

to care outside of the IOTA participants’ 

control. It also recognizes that 

disparities already exist in access to 

kidney transplants for low-income 

patients, so, by addressing inequities, 

IOTA participants would focus efforts 

on tackling inequities for patients 

outside the Medicare population. 

For purposes of the health equity 

performance adjustment, we also 

considered using the area deprivation 

index (ADI) to define the low-income 

population. ADI ranks neighborhoods 

based on socioeconomic disadvantage in 

the areas of income, education, 

employment, and housing quality. Areas 

with greater disadvantage are ranked 

higher, and they correlate with worse 

health outcomes in measures such as 

life expectancy.203 The areas used in the 

ADI are defined by Census Block Group, 

which presents a number of 

challenges.204 However, because 

address information for Medicare 

beneficiaries may be incomplete, and 

not available at all for patients who have 

private insurance or the uninsured, we 

opted to not use ADI to define the lowincome population. We believed that 

this would leave an incomplete picture 

of the transplant population for a given 

IOTA participant. Furthermore, the 

socioeconomic status of individuals 

within a given ADI can vary greatly. 

Those that are underserved in a Census 

Block Group with a low ADI may be 

overlooked. 

We also considered including ‘‘rural 

resident’’ as one of the groups that 

define a low-income population in the 

IOTA Model, as rural transplant patients 

face numerous barriers to care, 

including transportation, food, housing, 

and income insecurity, and no or 


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limited access to kidney transplant 

hospitals within or close to their rural 

communities. We considered defining 

rural beneficiaries consistent with the 

criteria used for identifying a rural area 

when determining CAH eligibility at 42 

CFR 485.610(b)(1)(i), that is, 

beneficiaries living outside an MSA. 

However, we were unsure if it was 

appropriate to include this group to 

define a low-income population to 

determine if a health equity adjustment 

would apply to the achievement 

performance score, particularly as the 

proposed low-income definition may 

already capture the majority of rural 

kidney transplant patients. 

We sought comment on our proposed 

health equity performance adjustment, 

including on the adjustment multiplier 

and calculation method, the definition 

of low-income population and 

alternatives considered, including 

consideration of ADI as an alternative 

definition, or including rural resident in 

the low-income population definition. 

The following is a summary of the 

comments received on our proposed 

health equity performance adjustment, 

including on the adjustment multiplier 

and calculation method, the definition 

of low-income population and 

alternatives considered, including 

consideration of ADI as an alternative 

definition, or including rural resident in 

the low-income population definition 

and our responses: 

Comment: A couple commenters 

advised CMS against finalizing the 

proposed HEPA provision for a variety 

of reasons, arguing that it prioritizes 

non-medical factors and prompts IOTA 

participants to unfairly favor certain 

patients over others for reasons 

unrelated to clinical needs. 

Response: We appreciate the feedback 

from commenters, but we respectfully 

disagree with their position. We 

originally proposed this provision out of 

concern for the existing disparities in 

access to transplants. The proposed 

HEPA was not intended to incentivize a 

focus on any particular patient group, 

but rather to encourage kidney 

transplant hospitals to identify and 

address the barriers faced by their 

underserved patient populations, with 

the goal of overcoming issues related to 

SDOH. Moreover, we believe that IOTA 

participants will leverage their medical 

expertise to deliver the best outcomes 

for patients. However, in light of all the 

comments we received and about the 

potential for unintended consequences, 

we will not be finalizing the proposed 

HEPA at this time. As part of the 

evaluation process, we intend to 

monitor how the model impacts lowincome individuals’ access to kidney 

transplants and may consider proposing 

a new or updated policy through future 

notice and comment rulemaking. 

Comment: While a commenter 

appreciated CMS’ focus on promoting 

health equity in this model, they did not 

support the proposed HEPA due to 

broader concerns about using transplant 

volume as a performance measure. 

Specifically, the commenter noted that 

although the HEPA aims to encourage 

IOTA participants to provide 

transplants for uninsured patients, the 

bonus payments are insufficient to cover 

the extensive, long-term care required 

for successful transplant outcomes. 

Transplant patients need a wide range 

of services beyond just the surgery itself, 

including preoperative testing and 

monitoring, dietary counseling, and 

ongoing medications. However, a lack of 

insurance coverage presents a major 

challenge for both patients and kidney 

transplant hospitals in achieving better 

kidney care outcomes. For these 

reasons, the commenter argued that 

CMS’ proposed health equity multiplier 

approach to incentivize organ 

transplantation services for underserved 

patients is an inadequate solution to this 

complex issue. 

Response: We appreciate the feedback 

and believe that the increased payment 

amounts in the model could provide 

additional resources for IOTA 

participants to support the necessary 

interventions required to overcome 

barriers for underserved patients. 

However, as mentioned in comment 

responses noted previously in this 

section, we will not be finalizing the 

HEPA as we are concerned about the 

potential for unintended consequences 

and will keep this feedback in mind as 

we consider alternatives in future notice 

and comment rulemaking. 

Comment: A commenter expressed 

concern that the proposed HEPA 

incentivizes out-of-sequence allocation 

of kidneys by IOTA participants, giving 

preferential treatment to low-income 

candidates, in order to maximize the 

number of points they receive in the 

achievement domain. Given these 

concerns and the pressing disparities in 

access to living donor transplants, the 

commenter urged CMS to consider 

increasing the HEPA, but limiting the 

availability of the HEPA to living donor 

transplants. 

Response: We appreciate this 

feedback. As mentioned in commented 

responses previously in this section, we 

will not be finalizing the proposed 

HEPA at this time. Additionally, as 

described and finalized in section 

III.C.13.c of this final rule, we will 

monitor the rates of out-of-sequence 

allocation that may result from the 

model. This is to ensure the model does 

not have unintended consequences. 

Accordingly, we do not anticipate any 

potential impact of out-of-sequence 

allocation as a way to prioritize 

transplants for underserved 

populations. 

Comment: A commenter strongly 

agreed with CMS’ intended goal of using 

financial incentives to encourage IOTA 

participants to improve health equity 

and reduce disparities in overall 

transplant rates for lower-income 

patients. However, the commenter 

expressed significant concerns about the 

potential unintended consequences of 

this design. Specifically, they believed 

that financially incentivizing the use of 

lower-quality kidneys for lower-income 

patients, while also incentivizing more 

transplants for this group, could 

inadvertently link these factors and 

entrench a two-tiered system. The 

commenter stated that this could result 

in lower-income patients being offered 

lower-quality kidneys, further 

exacerbating health disparities among 

kidney transplant recipients. 

Additionally, the commenter was 

concerned that while the proposed 

model would increase kidney 

transplantation rates for those already 

on the waitlist, it overlooked the 

broader barriers in healthcare access 

that prevent low-income patients from 

being placed on the transplant waitlist 

in the first place. As such, the 

commenter recommended that CMS not 

finalize the HEPA. 

Response: We thank the commenter 

for sharing their support and concerns. 

We acknowledge potential concerns 

about the proposed HEPA policy, but 

also recognize the substantial benefits of 

kidney transplantation over dialysis, 

even for complex organs. Furthermore, 

we believe IOTA participants will 

exercise their medical expertise to 

ensure the best possible outcomes for 

patients. However, as mentioned in 

comment responses noted previously in 

this section, we will not be finalizing 

the proposed HEPA provision at this 

time due to the potential for unintended 

consequences. We intend to monitor 

how the model impacts low-income 

individuals’ access to kidney 

transplants and may consider proposing 

a new or updated policy through future 

notice and comment rulemaking. 

Comment: A commenter suggested 

that the proposed HEPA would bias 

IOTA Model results toward larger 

kidney transplant hospitals with the 

financial resources to overcome the 

challenges of serving low-income 

patients. The commenter also believed 

that any effort to shift transplantation 

decisions away from purely clinical 


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considerations would necessarily 

produce adverse results, such as higher 

rates of unsuccessful transplants. 

Specifically, IOTA participants may 

take greater risks by transplanting 

kidneys into HEPA-eligible patients 

rather than better clinically-matched 

recipients, leading to increased failure 

rates. For these reasons, the commenter 

strongly recommended that CMS reduce 

the multiplier for the HEA from 1.2 to 

1.05 or 1.1. Additionally, the 

commenter suggested lowering the 

achievement domain points thresholds 

commensurately, setting the highest 

threshold (sixty points) at greater than 

125% of target and dropping the lowest 

(zero points) to less than 50% of target. 

This, they believed, would help address 

the resource gap between IOTA 

participants. Additionally, the 

commenter felt this change would also 

reduce the potential adverse 

consequences of clouding clinical 

judgment with financial considerations 

when matching organs to recipients. 

Finally, the commenter noted that 

making these suggested changes would 

further recognize the sometimes-severe 

disparity of available organs from one 

PY and its relevant baseline years to the 

next. 

Response: We thank the commenter 

for sharing their concerns; however, we 

disagree that the proposed HEPA would 

bias larger kidney transplant hospitals. 

We believe all transplant hospitals, not 

just larger ones, should focus on 

overcoming barriers for underserved 

populations. Moreover, many of the 

interventions needed to address these 

barriers are covered by organ acquisition 

costs. However, in response to the 

public comments we received on our 

proposed HEPA, we will not be 

finalizing this provision at this time. 

Comment: Several commenters urged 

CMS to include rural residents as a 

population group in the proposed 

definition of low-income population 

that is eligible for the proposed HEPA; 

given the limited access to transplant 

services in rural areas and additional 

challenges that rural residents, 

regardless of income, face throughout 

the transplant process. For example, a 

commenter appreciated that CMS 

considered including rural residents in 

the proposed low-income patient 

definition eligible to receive the 

proposed HEPA. However, the 

commenter urged CMS to reconsider 

this factor, arguing that it would help 

address the unique challenges rural 

residents face throughout the transplant 

process. Another commenter 

recommended that CMS consider 

including ‘‘rural resident’’ as a group in 

the proposed definition of low-income 

population for the purposes of the IOTA 

Model, since rural residency is 

associated with significant barriers to 

transplantation, a situation only made 

worse by the increasingly precarious 

hospital footprint in rural areas of the 

country. Due to the significant barriers 

to transplantation faced by rural 

residents, which are exacerbated by the 

increasingly limited availability of 

hospitals in rural areas, a commenter 

recommended that CMS should include 

rural resident as a group in the proposed 

low-income population definition for 

the IOTA Model. 

A commenter strongly supported the 

proposed HEPA and applauded CMS for 

recognizing that some patients require 

more assistance from kidney transplant 

hospitals to overcome barriers to 

transplantation. This commenter felt 

CMS correctly identified that rural 

transplant patients face barriers to care, 

some of which are income related such 

as food, housing, and income insecurity. 

The commenter believed that patients 

facing these barriers would almost 

certainly qualify for the proposed health 

equity performance adjustment (HEPA) 

through Medicaid eligibility or the 

Medicare Low Income Subsidy (LIS). 

According to the commenter, patients 

confronting these barriers would likely 

qualify for the proposed HEPA through 

Medicaid eligibility or the Medicare 

Low Income Subsidy (LIS). However, 

the commenter stated that they could 

attest that two of the barriers identified 

by CMS—transportation issues and 

‘‘limited access to kidney transplant 

hospitals within or close to rural 

communities’’—complicate transplant 

care for patients, regardless of their 

income level. The commenter argued 

that by including rural residents in the 

groups qualifying for the proposed 

HEPA, CMS would ensure that the 

additional assistance kidney transplant 

hospitals must provide to help rural 

patients of all income levels overcome 

barriers to transplantation is properly 

accounted for. Lastly, this commenter 

stated their belief that the criteria used 

for identifying a rural area when 

determining CAH eligibility at 42 CFR 

485.610(b)(1)(i) would sufficiently 

capture rurality. 

Lastly, a commenter greatly supported 

CMS’ efforts to strengthen health equity 

in value-based care, but believed CMS 

should expand the proposed definition 

of low-income population eligible for 

the HEPA to also include rural 

residents, given the limited access to 

transplant services in rural areas. The 

commenter argued that rural patients 

face significant barriers to accessing 

transplant services, as they are less 

likely to be added to transplant waitlists 

or referred for transplant by dialysis 

providers due to the limited availability 

of transplant services in rural areas. 

Therefore, the commenter felt CMS 

should incentivize IOTA participants to 

care for rural patients through the HEPA 

for low-income populations, in order to 

address the disproportionate challenges 

faced by the rural population in 

accessing transplant care. The 

commenter suggested that if CMS is 

hesitant to label all rural patients as 

low-income, they could rename the 

adjustment to more accurately reflect 

the vulnerable populations it includes. 

Response: We thank the commenters 

for their support and recommendation 

to include rural residents in our 

proposed definition of low-income 

population eligible to receive the 

proposed HEPA. We recognize that rural 

patients may face additional barriers 

and challenges throughout the 

transplant process. However, as 

mentioned in comment responses noted 

previously, we will not be finalizing the 

proposed HEPA at this time. 

Additionally, we will consider 

additional adjustments to the model that 

may account for the barriers faced by 

patients living in rural areas in future 

notice and comment rulemaking. 

Comment: A commenter noted that 

they have dialysis patients that get 

assistance to enroll in commercial 

plans. The commenter argued that these 

individuals should be classified as lowincome, citing their frequent 

socioeconomic barriers, and urged CMS 

to revise the proposed definition of lowincome population to encompass these 

individuals. 

Response: We thank the commenter 

for their suggestion. We chose the 

specific designations in an effort to use 

insurance status as a proxy for 

underserved status for beneficiaries and 

the statuses we proposed at 89 FR 43553 

in the proposed rule (uninsured, 

Medicaid beneficiaries, MedicareMedicaid dually eligible beneficiaries, 

recipients of the Medicare LIS, or 

recipients of reimbursements from the 

Living Organ Donation Reimbursement) 

only apply to lower-income 

beneficiaries, whereas beneficiaries with 

commercial insurance may not be lowincome. As such, we disagree with the 

commenter. 

Comment: A commenter expressed 

strong support for reducing health 

inequities but felt that the proposed 

methodology for identifying low-income 

populations, although clear, may not be 

comprehensive in gathering the 

intended information. Specifically, the 

commenter cited three concerns: (1) The 

commenter was unaware of transplant 

hospitals that would knowingly 


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transplant someone without insurance 

who lacked the means to cover the costs 

out-of-pocket. Therefore, the uninsured 

criteria may identify patients with 

significant means, unless CMS examines 

people who have lost some or all 

insurance after transplant.; (2) 

Transplant hospitals do not know which 

patients receive LIS benefits, and many 

patients are unaware that they receive 

this benefit, based on the commenter’s 

experience.; and (3) NLDAC benefits are 

attached to the donor, not the recipient, 

so CMS may not have access to this 

information. 

Response: We thank the commenter 

for their feedback. We believe that all 

patients with kidney disease deserve 

equitable care and access to the 

transplant process. We urge transplant 

hospitals to think about how to 

overcome barriers for patients, 

regardless of insurance status, and to 

think about how to best care for 

patients’ needs. Although we will not be 

finalizing the proposed HEPA at this 

time, we will consider the comments 

that were received during the public 

comment period and may make future 

proposals during the course of the 

model test in future notice and 

comment rulemaking. 

Comment: Multiple commenters 

supported the proposed HEPA but urged 

CMS to increase the amount of the 

proposed HEPA multiplier. For 

example, a commenter expressed their 

strong support for the proposed HEPA 

and believed that it is an appropriate 

incentive to encourage IOTA 

participants to address barriers that lowincome populations face in the 

transplant process and to help reduce 

disparities in access to transplant. 

Furthermore, the commenter felt that 

the proposed HEPA is also an important 

tool to ensure IOTA participants are not 

unfairly penalized if they serve a high 

number of low-income populations. As 

such, they recommend that CMS 

consider increase the health equity 

performance adjustment. 

Additionally, a commenter 

encouraged CMS to increase the 

proposed HEPA multiplier to 1.25. 

Another commenter supported the 

precision of the IOTA Model’s 

approach, which proposed to apply an 

adjustor for each individual kidney 

transplant furnished to a patient 

meeting the proposed low-income 

population definition. This 

individualized method, they argued, 

would more effectively address health 

equity compared to the broader 

approach used in the ETC Model. 

However, the commenter expressed 

concerns that the proposed 1.2 

multiplier was insufficient to cover the 

increased costs kidney transplant 

hospitals would face in expanding 

transplants for low-income populations. 

Therefore, the commenter believed it is 

critical for CMS to consider increasing 

the multiplier to at least 1.5 in order to 

incentivize and enable greater 

transplant access for this underserved 

group. 

Response: We appreciate the 

commenters’ support and 

recommendations. As described in 

comment responses noted previously, 

we will not be finalizing the proposed 

HEPA. Although we are not finalizing 

the proposed HEPA at this time, we will 

take the comment but will consider the 

appropriate magnitude of any potential 

adjustment via future rulemaking, as we 

are not finalizing this provision. 

Comment: We received multiple 

comments supporting the proposed 

inclusion of a HEPA. For example, 

several commenters commended CMS’s 

emphasis on and approach to 

implement a reward only HEPA. They 

believed the proposed HEPA would be 

a major stride toward promoting equity 

in access to organ transplants and 

motivate IOTA participants to address 

the barriers faced by low-income 

individuals in the transplant process. In 

their comments supporting the 

proposed HEPA, a couple commenters 

also expressed gratitude to CMS. They 

thanked CMS for acknowledging 

inequities in the transplant process and 

recognizing that low-income patients 

may require additional resources to 

receive a transplant and overcome social 

barriers to health. These commenters 

further appreciated CMS for recognizing 

the extra challenges and burden faced 

by transplant programs when treating 

low-income patients, and for its 

continued efforts to improve service 

delivery for this population. Lastly, 

another commenter strongly supported 

the inclusion of a HEPA, asserting that 

it serves as an important mechanism to 

protect IOTA participants from being 

unduly penalized for serving a high 

volume of low-income populations. 

Response: We appreciate the feedback 

from commenters. As mentioned in 

comment responses noted previously in 

this section, we are not finalizing the 

proposed HEPA out of the potential for 

unintended consequences. We plan to 

monitor the effects of the model on lowincome individuals’ access to kidney 

transplants as part of the evaluation 

process and may consider proposing a 

new or updated policy through future 

notice and comment rulemaking, 

depending on performance by IOTA 

participants. 

Comment: Multiple commenters 

suggested that CMS only apply the 

proposed HEPA to living donor 

transplants. For example, a commenter 

commended CMS for including the 

proposed HEPA, noting its structure as 

a reward-only mechanism. The 

commenter further suggested that CMS 

implement a similar ‘‘reward-only’’ 

multiplier based on donor 

characteristics, which could be 

integrated into IOTA participants’ 

transplant counts in a similar way. 

Additionally, the commenter could also 

envision a multiplier for living 

donations from historically 

disadvantaged groups, such as rural and 

underserved areas. To avoid 

incentivizing IOTA participants to 

prioritize deceased donor transplants for 

low-income candidates out-of-sequence, 

a commenter suggested that CMS apply 

the proposed HEPA policy only to living 

donor transplants. 

Response: We thank the commenters 

for their suggestions. We will not be 

finalizing the proposed HEPA at this 

time, as described in comment 

responses noted previously in this 

section, but may consider this idea in 

future notice and comment rulemaking 

as we continue to assess ways to address 

inequities in the transplant process. 

Comment: A commenter expressed 

their appreciation for CMS’ focus on 

low-income patients but noted that 

these individuals frequently arrive at 

transplant hospitals with more 

advanced disease, often due to delayed 

referrals. Accordingly, the commenter 

urged CMS to explore alternative 

models that would facilitate earlier 

kidney health screenings and improve 

primary care access for these 

underserved populations. 

Response: We appreciate the 

commenters’ feedback. However, we 

believe that the IOTA Model works 

alongside other CMS initiatives aimed at 

earlier intervention for patients with 

kidney disease, such as the KCC Model, 

which focuses on managing care for 

Medicare beneficiaries with chronic 

kidney disease and end-stage renal 

disease. 

Comment: Multiple commenters 

agreed with CMS’ decision to not use 

ADI, pointing out many of the 

limitations in using ADI to measure 

inequity in the transplant process. For 

example, a commenter argued that using 

the ADI is less optimal than the 

approach proposed by CMS. The 

commenter stated that the ADI is a more 

difficult criterion for transplant 

hospitals to apply when identifying 

patients who would qualify for and 

benefit from interventions. This added 

complexity would undermine one of the 

key strengths of the IOTA Model— 

simplicity. As a result, the commenter 


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reports/2021/Kidney.aspx. 

206 King, K.L., Husain, S.A., Schold, J.D., Patzer, 

R.E., Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., 

Pastan, S.O., & Mohan, S. (2020). Major Variation 

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Kidney Transplant for Wait-Listed Patients. Journal 

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207 King, K.L., Husain, S.A., Schold, J.D., Patzer, 

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ASN.2020030335. 

208Enhance Transplant Program Performance 

Monitoring System OPTN Membership and 

Professional Standards Committee. (n.d.). https://

optn.transplant.hrsa.gov/media/4777/transplant_

program_performance_monitoring_public_

comment_aug2021.pdf. 

209Schold, J.D., Gregg, J.A., Harman, J.S., Hall, 

A.G., Patton, P.R., & Meier-Kriesche, H.-U. (2011). 

Barriers to Evaluation and Wait Listing for Kidney 

Transplantation. Clinical Journal of the American 

Society of Nephrology, 6(7), 1760–1767. https://

doi.org/10.2215/cjn.08620910; Hod, T., & GoldfarbRumyantzev, A.S. (2014). The role of disparities 

and socioeconomic factors in access to kidney 

transplantation and its outcome. Renal Failure, 

36(8), 1193–1199. https://doi.org/10.3109/ 

0886022x.2014.934179; Stolzmann, K.L., Bautista, 

L.E., Gangnon, R.E., McElroy, J.A., Becker, B.N., & 

Remington, P.L. (2007). Trends in kidney 

transplantation rates and disparities. Journal of the 

National Medical Association, 99(8), 923–932. 

https://www.ncbi.nlm.nih.gov/pmc/articles/ 

PMC2574300/; Paul, S., Melanson, T., Mohan, S., 

Ross-Driscoll, K., McPherson, L., Lynch, R., Lo, D., 

Pastan, S.O., & Patzer, R.E. (2021). Kidney 

transplant program waitlisting rate as a metric to 

assess transplant access. American Journal of 

Transplantation: Official Journal of the American 

Society of Transplantation and the American 

Society of Transplant Surgeons, 21(1), 314–321. 

https://doi.org/10.1111/ajt.16277; Cheng, X.S., 

Busque, S., Lee, J., Discipulo, K., Hartley, C., Tulu, 

Z., Scandling, J.D., & Tan, J.C. (2018). A new 

approach to kidney wait-list management in the 

kidney allocation system era: Pilot implementation 

and evaluation. Clinical Transplantation, 32(11), 

e13406. https://doi.org/10.1111/ctr.13406. 

felt that the ADI would be less effective 

than the clearly defined socioeconomic 

status (SES) eligibility criteria put forth 

by CMS in driving behavioral changes at 

the transplant hospital level. 

Additionally, the commenter noted that 

while the ADI is a valuable tool, 

transplant hospitals typically have a 

more granular understanding of 

individual patients’ SES, allowing them 

to easily and immediately identify those 

who should receive additional support. 

While another commenter accepted the 

proposed low-income population 

definition for this model, recognizing 

the limitations of the ADI, noting that it 

fails to adequately capture low-income 

populations across all regions. 

Response: We thank the commenters 

for their support and do not plan to use 

the ADI as a way to identify 

underserved populations in the IOTA 

Model. 

After consideration of public 

comments received, for the reasons set 

forth in this rule, CMS is not finalizing 

the Health Equity Performance 

Adjustment to the achievement domain, 

due to the potential for unintended 

consequences, some of which were 

pointed out by commenters. We still 

recognize that there are many inequities 

in the transplant process and may 

propose alternative approaches in future 

notice and comment rulemaking that 

could address some of the potential 

consequences laid out by commenters. 

We also plan to monitor and evaluate 

the results of the IOTA Model in an 

effort to see which patients receive 

transplants in an effort to monitor for 

any impact of the model based on 

patient insurance status. However, we 

are finalizing our proposed 

methodology for calculating the number 

of kidney transplants performed during 

the PY at § 512.424(d) with slight 

modification. Specifically, since we are 

not finalizing the proposed health 

equity performance adjustment at this 

time, we are modifying our regulation at 

§§ 512.424(d)(1)(i) and (2) to remove the 

cross reference to the health equity 

performance adjustment. 

d. Efficiency Domain 

At § 512.402 of the proposed rule, we 

proposed to define the ‘‘efficiency 

domain’’ as the performance assessment 

category in which CMS assesses the 

IOTA participant’s performance using 

the organ offer acceptance rate ratio as 

described in § 512.426. In section 

III.C.5.d(1) of the proposed rule, we 

stated that the efficiency domain is 

focused on improving the overall 

efficiency of the transplant ecosystem. 

In section III.C.5.d(1) of the proposed 

rule, we proposed including OPTN’s 

organ offer acceptance rate ratio 

measure in the efficiency domain. The 

organ offer acceptance rate ratio 

measure is a ratio of observed organ 

offer acceptances versus expected organ 

offer acceptances, as described in 

section III.C.5.d.(1) of the proposed rule. 

(1) Organ Offer Acceptance Rate Ratio 

As reviewed in section III.C.5.d(1) of 

the proposed rule, with over 90,000 

unique patients on the waiting list for a 

kidney transplant, the need to 

effectively use every available donor 

organ is critical. However, despite the 

new allocation system introduced in 

2021, and more organs being offered 

over a wider geographic area, the kidney 

discard rate has risen to over 24.6 

percent and continues to trend 

upwards.205 There is a significant 

shortage of organs available for 

transplantation, and many patients die 

waiting for a kidney transplant. 

Moreover, there are large disparities in 

organ offer acceptance ratio 

performance. A 2020 national registry 

study found that the probability of 

receiving a deceased donor kidney 

transplant within three years of 

placement on the waiting list varied as 

much as 16-fold amongst different 

kidney transplant hospitals across the 

U.S.206 The study also found that large 

variations were still present between 

kidney transplant hospitals that utilized 

the same OPO and that the probability 

of transplant was significantly 

associated with transplant hospitals’ 

offer acceptance rates.207 By 

incentivizing kidney organ offer 

acceptance, we aimed to optimize the 

use of available organs, thereby 

reducing underutilization and discards 

of quality donor organs. 

For purposes of assessing the 

performance of IOTA participants in the 

achievement domain, we proposed in 

section III.C.5.d(1) of the proposed rule 

to include the organ offer acceptance 

rate ratio as one of the two metrics of 

performance. We believed that 

including this measure in the efficiency 

domain would encourage IOTA 

participants to increase the utilization of 

available organs. We also believed that 

this measure would encourage IOTA 

participants to improve efficiency in the 

organ offer process, improve acceptance 

practices for offers received, and allow 

for maximal utilization of available 

organs. We believed that the organ offer 

acceptance rate ratio is an important 

system-wide metric, as improved 

performance by an IOTA participant 

would also improve opportunities for 

other kidney transplant hospitals that 

would not have to wait as long for an 

available donor kidney. We recognized 

that all kidney transplant hospitals are 

already assessed on the organ offer 

acceptance rate ratio metric under the 

OPTN, however, we believed that the 

IOTA Model sets a higher bar for 

performance, as discussed in section 

III.C.5.d.(1)(a) of the proposed rule, 

rather than clearing the threshold that 

the OPTN sets at 0.30.208

As stated in section III.C.5.d(1) of the 

proposed rule, in the United States, 

kidney transplant waitlist candidates 

face considerable disparities in access to 

kidney transplant, such as in who is 

referred and placed on the waiting list, 

who remains ‘‘active’’ on the waiting 

list, and how waitlisted patients are 

managed by kidney transplant 

hospitals.209 Additionally, kidney 


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210Husain, S.A., King, K L., Pastan, S., Patzer, 

R.E., Cohen, D.J., Radhakrishnan, J., & Mohan, S. 

(2019). Association Between Declined Offers of 

Deceased Donor Kidney Allograft and Outcomes in 

Kidney Transplant Candidates. JAMA Network 

Open, 2(8), e1910312. https://doi.org/10.1001/ 

jamanetworkopen.2019.10312. 

211 Delmonico, F.L., & McBride, M.A. (2008). 

Analysis of the Wait List and Deaths Among 

Candidates Waiting for a Kidney Transplant. 

Transplantation, 86(12), 1678–1683. https://doi.org/ 

10.1097/tp.0b013e31818fe694. 

212Shepherd, S., & Formica, R.N. (2021). 

Improving Transplant Program Performance 

Monitoring. 8(4), 293–300. https://doi.org/10.1007/ 

s40472-021-00344-z; Wey, A., Gustafson, S.K., 

Salkowski, N., Kasiske, B.L., Skeans, M., 

Schaffhausen, C.R., Israni, A.K., & Snyder, J.J. 

(2019). Association of pretransplant and 

posttransplant program ratings with candidate 

mortality after listing. 19(2), 399–406. https://

doi.org/10.1111/ajt.15032. 

213Paul, S., Plantinga, L.C., Pastan, S.O., Gander, 

J.C., Mohan, S., & Patzer, R.E. (2018). Standardized 

Transplantation Referral Ratio to Assess 

Performance of Transplant Referral among Dialysis 

Facilities. Clinical Journal of the American Society 

of Nephrology, 13(2), 282–289. https://doi.org/ 

10.2215/cjn.04690417; Redeker, S., Massey, E.K., 

van Merweland, R.G., Weimar, W., Ismail, S.Y., & 

Busschbach, J.J.V. (2022). Induced demand in 

kidney replacement therapy. Health Policy, 126(10), 

1062–1068. https://doi.org/10.1016/ 

j.healthpol.2022.07.011; Knight, R.J., Teeter, L.D., 

Graviss, E.A., Patel, S.J., DeVos, J.M., Moore, L.W., 

& Gaber, A.O. (2015). Barriers to Preemptive Renal 

Transplantation. Transplantation, 99(3), 576–579. 

https://doi.org/10.1097/tp.0000000000000357; 

Schold, J.D., Patzer, R.E., Pruett, T.L., & Mohan, S. 

(2019). Quality Metrics in Kidney Transplantation: 

Current Landscape, Trials and Tribulations, Lessons 

Learned, and a Call for Reform. American Journal 

of Kidney Diseases, 74(3), 382–389. https://doi.org/ 

10.1053/j.ajkd.2019.02.020. 

214Shepherd, S., & Formica, R.N. (2021). 

Improving Transplant Program Performance 

Monitoring. 8(4), 293–300. https://doi.org/10.1007/ 

s40472-021-00344-z; Ernst, Z., Wilson, A., Pen ̃ a, A., 

Love, M., Moore, T., & Vassar, M. (2023). Factors 

associated with health inequities in access to 

kidney transplantation in the USA: A scoping 

review. Transplantation Reviews, 100751. https://

doi.org/10.1016/j.trre.2023.100751. 

215Schold, J.D., Patzer, R.E., Pruett, T.L., & 

Mohan, S. (2019). Quality Metrics in Kidney 

Transplantation: Current Landscape, Trials and 

Tribulations, Lessons Learned, and a Call for 

Reform. American Journal of Kidney Diseases, 

74(3), 382–389. https://doi.org/10.1053/ 

j.ajkd.2019.02.020. 

216 Ibid; Alexander, G. Caleb., & Sehgal, A.R. 

(2002). Variation in access to kidney transplantation 

across dialysis facilities: Using process of care 

measures for quality improvement. American 

Journal of Kidney Diseases, 40(4), 824–831. https:// 

doi.org/10.1053/ajkd.2002.35695; Patzer, R.E., 

Plantinga, L.C., Paul, S., Gander, J., Krisher, J., 

Sauls, L., Gibney, E.M., Mulloy, L., & Pastan, S.O. 

(2015). Variation in Dialysis Facility Referral for 

transplant hospital performance is 

commonly measured by post-transplant 

outcomes. We recognized that including 

pre-transplant measures could allow for 

a more thorough evaluation of 

transplant hospital performance and 

provide insight for patient decisionmaking. 

In section III.C.5.d(1) of the proposed 

rule, we considered several waitlist 

management metrics for assessing 

performance in the efficiency domain, 

such as the number of patients 

registered to a waitlist, the number or 

percentage of attributed patients 

registered on a waitlist with an active 

waitlist status, or the number or 

percentage of attributed patients on a 

waitlist with active waitlist status to 

inactive waitlist status. Metrics focused 

on the waitlist could help assess how 

effectively kidney transplant hospitals 

are managing their kidney transplant 

waitlist patients. Organ offers to waitlist 

kidney transplant patients are made 

directly to the kidney transplant 

hospital where they are waitlisted. Once 

a kidney transplant hospital receives an 

organ offer for one of their kidney 

transplant waitlist patients, it is 

ultimately its decision to accept or 

decline an organ offer on the patient’s 

behalf. Kidney transplant hospitals are 

not required to inform kidney transplant 

waitlist patients for whom an offer was 

received when an organ offer was 

received or why an organ offer was 

declined. While we understood the 

importance of a transplant surgeon’s 

clinical decision-making and respected 

the clinical judgement of transplant 

surgeons, declining an offer without 

involving the affected patient in the 

decision-making can be detrimental to 

the patient, as additional time on the 

waitlist can negatively impact the 

patient’s quality of life.210

As stated in section III.C.5.d(1) of the 

proposed rule, we also considered 

including a waitlist mortality metric for 

assessing efficiency domain 

performance, so as to incentivize 

improvements in mortality outcomes of 

attributed patients on a waitlist. On 

average, as many as 20 patients on the 

waitlist for a kidney transplant die each 

day waiting for a kidney transplant in 

the United States.211 While a waitlist 

mortality metric may help assess patient 

outcomes and experience while waiting 

for an organ offer,212 and provide 

insight into differences in waitlist 

management practices across kidney 

transplant hospitals, we recognize that 

waitlist mortality rate is also influenced 

by the insufficient supply of donor 

organs available for transplantation. We 

also recognized that IOTA participants 

may not have a direct effect on, or 

ability to improve, mortality metrics, as 

nephrologists are also closer to the 

direct care of waitlist patients and 

would have a greater ability to affect 

their care and mortality rate. 

Furthermore, we believed that we are 

already testing the ability of 

nephrologists to manage care for 

Medicare beneficiaries with ESRD or 

CKD via the KCC Model. 

We also considered several other 

metrics for assessing efficiency domain 

performance related to time to 

transplant, as outlined in section 

III.C.5.d(1) of the proposed rule, such 

as— 

• Time from initial evaluation to 

transplant; 

• Time from initial referral to 

transplant; 

• Time from initial placement on a 

waitlist to transplant; and 

• Time from when a patient was 

initially referred to time of initial 

evaluation to time of initial placement 

on a waitlist to time to transplant. 

As discussed in section III.C.5.d(1) of 

the proposed rule, before a patient can 

be considered for, and placed on, the 

waiting list for a kidney transplant, they 

must first be referred by either a 

nephrologist or dialysis facility, at 

which point they undergo a 

comprehensive evaluation process by a 

transplant hospital.213 Studies have 

shown long-standing barriers and 

disparities to access to transplantation 

by patient demographics, such as racial/ 

ethnic, sex, socioeconomic, and 

insurance factors.214 Disparities are 

driven by various factors, but we 

recognized that delays or lack of 

referrals for evaluation, evaluation 

criteria that may unintentionally deem a 

patient not eligible to be placed on a 

waitlist, and organ acceptance rate 

variations across kidney transplant 

hospitals, may exacerbate disparities. 

Thus, measuring time to transplant was 

considered an appropriate potential 

performance metric that could 

incentivize IOTA participants to 

improve. However, we chose not to 

propose this type of measure due to 

concerns about how to properly 

measure start and end points and 

unintended consequences that may 

harm patients, as it may create 

opportunities for kidney transplant 

hospitals to manipulate average times 

by only adding patients to the waitlist 

when they are certain of imminent 

transplant, which could exacerbate 

waitlist inequities. 

We also considered including a 

transplantation referral to evaluation 

conversion rate measure, as discussed in 

section III.C.5.d(1) of the proposed rule. 

For patients with ESRD, access to 

transplantation is influenced by both 

referral patterns of pre-transplantation 

providers and transplant hospital 

processes of care and evaluation 

criteria.215 Additionally, some studies 

found considerable variation in referral 

rates to transplantation by dialysis 

facilities, proposing significant regional 

and facility-level variation in care.216


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Kidney Transplantation Among Patients With EndStage Renal Disease in Georgia. JAMA, 314(6), 582. 

https://doi.org/10.1001/jama.2015.8897. 

217Cheng, X.S., Han, J., Braggs-Gresham, J.L., 

Held, P.J., Busque, S., Roberts, J.P., Tan, J.C., 

Scandling, J.D., Chertow, G.M., & Dor, A. (2022). 

Trends in Cost Attributable to Kidney 

Transplantation Evaluation and Waitlist 

Management in the United States, 2012–2017. 

JAMA Network Open, 5(3), e221847. https://doi.org/ 

10.1001/jamanetworkopen.2022.1847. 

218Mohan, S., Yu, M., King, K.L, & Husain, S.A. 

(2023) Increasing discards as an unintended 

consequence of recent changes in United States 

kidney allocation policy. Kidney International 

Reports, 8(5): 1109–1111. https://doi.org/10.1016/ 

j.ekir.2023.02.108. 219Wood, N.L., VanDerwerken, D.N., Segev, D.L., 

& Gentry, SE (2022). Increased logistical burden in 

circle-based kidney allocation. Transplantation, 

106(10): 1885–1887. https://doi.org/10.1097/ 

tp.0000000000004127. 220UNOS. (2023, September 5). Research in focus: 

Examining organ offers. Retrieved October 11, 2024 

from https://unos.org/news/in-focus/organ-offers/ 

#Impact. 

221OPTN. (2023, September 14). New pretransplant performance metric now in effect, offer 

acceptance rate ratio. Retrieved August 15, 2024 

from https://optn.transplant.hrsa.gov/news/newpre-transplant-performance-metric-now-in-effectoffer-acceptance-rate-ratio/. 

However, because dialysis facilities are 

often the primary referrer and are not 

IOTA participants, we did not propose 

this measure. We also had concerns 

about how this data would be collected. 

Finally, we also considered a living 

donor rate as one of the metrics used to 

assess performance in the efficiency 

domain to measure percentage of 

potential living donors who are 

evaluated to donate a kidney and that 

actually donated a kidney. This metric 

could help assess success towards 

addressing living donor concerns and 

improvements in education on the 

living donor process. However, we did 

not propose this metric because we have 

concerns about our ability to access data 

needed for measurement. 

Ultimately, as discussed in section 

III.C.5.d(1) of the proposed rule, we 

chose not to propose to include waitlist 

management metrics when assessing 

IOTA participant performance in the 

efficiency domain because we believed 

that waitlist costs are already accounted 

for in the Medicare cost report. 

Transplant waitlist measures also do not 

capture living donation, which is an 

additional path to a successful kidney 

transplant that CMS already 

incentivizes living donations in the ETC 

Model. Moreover, studies have shown 

that organ acquisition costs have been 

rising and were not solely attributable to 

the cost of procurement, suggesting that 

an increased focus on the waiting list 

could further increase Medicare 

expenditures.217 Also, for some of the 

measures considered (that is, waitlist 

mortality, transplantation referral to 

evaluation rate), nephrologists and 

dialysis facilities play large roles in 

maintaining the patient’s health, and we 

did not believe it is appropriate to 

include a measure that would depend 

largely upon the behavior and actions of 

physicians and facilities other than the 

IOTA participant. We also thought this 

type of measure could distract from 

increasing rates of transplant and 

provide false expectations for time to 

transplant for kidney transplant waitlist 

patients. We are also concerned that a 

waitlist measure could have unintended 

consequences and potentially lead to 

those most in need of transplant not 

being listed to receive a transplant. 

We solicited comment on our 

proposed organ offer acceptance rate 

ratio metric for purposes of assessing 

performance in the efficiency domain, 

and the alternatives considered. 

The following is a summary of the 

comments received on our proposed use 

of the organ offer acceptance rate ratio 

in the efficiency domain and our 

responses: 

Comment: A commenter was 

specifically opposed to including the 

OPTN organ offer acceptance rate 

measure in the efficiency domain. A few 

other commenters were concerned with 

using the organ offer acceptance rate 

ratio because it may be inflated by a 

high use of out-of-sequence kidneys, or 

it may promote kidney transplant 

hospitals to perform more DDKTs. 

Response: We thank the commenters 

for their feedback. While there is no 

downside risk for out-of-sequence 

allocation we acknowledge commenters’ 

concerns that an unintended 

consequence of using the organ offer 

acceptance rate ratio performance 

metric could be a rise in out-of-sequence 

allocation. We encourage the transplant 

community to continue providing 

feedback about appropriately capturing 

out-of-sequence organ offers, as we will 

consider this for future rulemaking and 

performance years. While we agree with 

the commenter who stated that the 

organ offer acceptance rate ratio metric 

may increase DDKTs, we do not believe 

that this automatically means that 

transplants will be of lesser quality. 

There are currently underutilized 

subsets of deceased donor kidneys and 

high rates of organ non-use 218 due to a 

number of reasons including, but not 

limited to, systematic inefficiencies 219

and lack of organ filters.220 We refer 

readers to sections III.B and III.C.5.d(1) 

of this final rule for further discussion 

on organ acceptance patterns. Preexisting OPTN mortality metrics and the 

new composite graft survival metric that 

we mention in section III.C.5.e of this 

final rule discourage transplant 

programs from transplanting kidneys 

that are very obviously not viable. 

Comment: A few commenters 

suggested that if CMS is using the organ 

offer acceptance rate ratio measure, that 

they need to address out-of-sequence 

allocation, should utilize SRTRs risk 

adjustment, and should modify OPTN 

codes to develop more targeted 

responses to the discard rate. 

Response: We thank the commenters 

for their suggestions. As previously 

mentioned in comment responses in 

this section, while there is no downside 

risk for out-of-sequence allocation in the 

IOTA Model, we acknowledge 

commenters concern that an unintended 

consequence of using the organ offer 

acceptance rate ratio performance could 

be an increase in out-of-sequence 

allocation. We encourage the transplant 

community to continue providing 

feedback about appropriately capturing 

out-of-sequence organ offers, as we will 

consider this for future rulemaking and 

performance years. 

We intend to use the SRTR risk 

adjustment model for the offer 

acceptance metric; see section III.C.5.e 

of this final rule for more details. 

Comment: A commenter stated that 

offers should be analyzed via validated 

metrics. 

Response: We thank the commenter 

for their response. The organ offer 

acceptance rate ratio has been utilized 

by SRTR since 2023 and while lacking 

formal validation, is not unknown to the 

transplant community.221 With the use 

of this measure by SRTR and CMS by 

way of the IOTA Model, we believe this 

creates opportunity to better understand 

its validity and adapt risk-adjustment. 

Comment: A commenter requested 

clarification around what is considered 

an ‘‘unsuitable kidney’’ in the list of 

exclusions for the expected organ offer 

acceptance. 

Response: We recommend the 

commenter review Table 6 in section 

III.C.5.d(1)(a) of this final rule, for a full 

list of exclusions from the measure. 

While an ‘‘unsuitable kidney’’ is not 

specifically listed in the exclusion list, 

we believe that the exclusion criteria of 

a kidney having a ‘‘match run with no 

acceptances’’ would apply. 

Comment: A commenter was 

concerned that the organ offer 

acceptance metric was too broad and 

should be calculated based on offers 

within and outside of a 250-mile radius 

given the variation in regional importing 

of organs and the variation in kidney 

transplant hospital wait times. 

Response: We appreciate the 

commenter’s feedback. This was not a 


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consideration made during proposed 

rulemaking in order to align our metric 

with the pre-existing SRTR 

methodology. We are, however, 

interested in considering this for future 

rulemaking. 

Comment: Many commenters stated 

their support for the use of OPTN’s 

organ offer acceptance rate measure in 

the efficiency domain. 

Response: We thank the commenters 

for their support. 

Comment: A commenter conveyed 

concern that listing practices could 

penalize them in the efficiency domain. 

For example, if a transplant program 

listed all patients for high KDPI kidneys, 

resulting in passing on kidneys for 

offers sometimes, their organ offer 

acceptance rate ratio could be impacted. 

Response: We appreciate the 

commenter’s feedback. While IOTA 

participants may choose to encourage 

all their patients to enroll for kidneys 

with a KDPI greater than 85 to increase 

their offer opportunity, as the 

commenter points out, this may have 

risks. The purpose of selecting organ 

offer acceptance rate ratio as a metric is 

to increase utilization of available 

organs. If frequent ‘‘passing’’ is 

occurring for patients listed for kidneys 

with a KDPI greater than 85, there may 

be additional opportunities for utilizing 

filters. We also acknowledge that no 

transplant program will accept every 

offer they receive due to outliers and 

offers that may not be ideal due to 

comorbidities/risks of the donor kidney 

and recipient or both. Results in PY 1 

will be monitored closely, to help 

identify reasonable and achievable 

organ offer acceptance ratio goals for 

future performance years and 

rulemaking. 

Comment: A commenter was 

concerned that organ offer acceptance 

rate metric will encourage more 

conservative choices, which contradicts 

increasing overall kidney transplant 

volume, another goal of the IOTA 

Model. 

Response: We appreciate your 

feedback; however, we believe the three 

performance domains counterbalance 

each other. The three performance 

domains challenge IOTA participants to 

consider if there is opportunity for 

growth in their kidney transplant 

hospital and how to navigate the task of 

increasing volume while offering a good 

quality of life for patients and 

appropriate long-term outcomes while 

minimizing non utilization of organs 

when possible. We would argue that the 

organ offer acceptance rate ratio 

measure does not encourage 

conservative choices but rather choices 

that better align with organs they will 

accept, to prevent overall organ non-use. 

We are asking IOTA participants to 

consider fine-tuning their organ offer 

filters and general processes. 

Comment: A commenter suggested 

that the performance measures include 

a metric assessing performance in 

excluded communities, awarding IOTA 

participants more points who have 

organ offer acceptance rate ratios 

matching population needs and 

showing evidence of improved access to 

underserved populations. Similarly, a 

commenter suggested stratifying organ 

offer acceptance rate ratios by the 

beneficiary’s payer, race, ethnicity and 

the income of the local population. 

Response: Thank you for your 

responses. We did not consider further 

stratifying organ offer acceptance rate 

ratio goals. This approach could aid in 

identifying disparities across kidney 

transplant waitlist patients and organ 

offer acceptance patterns; however, it 

may be challenging to create adjusted 

metrics specific to each IOTA 

participant and their local population 

needs. This would also require IOTA 

participants to annually identify their 

local population to formulate baselines. 

These calculations would then need to 

be utilized to determine how to award 

points to IOTA participants who exceed 

expectations for underserved 

populations. We are interested in 

considering how the organ offer 

acceptance rate ratio could be tailored to 

local populations and underserved 

communities during future rulemaking. 

Comment: A couple of commenters 

suggested CMS use a living donor 

metric. They had specific concerns that 

a domain dependent on DDKTs may not 

help to increase LDKTs. A commenter 

stated that CMS should include a living 

donor metric such as converting 

potential to actual living donors, and 

another stated CMS should implement a 

living donor and pre-emptive transplant 

measure given the significant benefits 

with living donation. 

Response: We thank the commenters 

for their suggestions. We intend to 

further consider how living donor 

metrics could be included in future 

rulemaking. Setting a target number for 

the number of living donor evaluations 

versus the actual number of living donor 

evaluations who proceed with a surgery 

creates numerous risks. This could 

inadvertently cause kidney transplant 

hospitals to change their practices for 

those patients they accept for 

evaluations (potentially lowering 

criteria thresholds) or who they approve 

to be donors. Either result could cause 

reduced access to donation and create 

ethical concerns or both. While we do 

not believe that this would be an 

appropriate metric for the IOTA Model, 

we do however, encourage ongoing 

feedback about other opportunities for 

metrics specific to living donation. 

Comment: A commenter requested 

use of a measure that does not 

incentivize acceptance of organ offers 

for the sole purpose of reaching a target 

number. 

Response: We appreciate the 

commenter’s feedback. We acknowledge 

that almost all metrics are imperfect. 

The purpose of including organ offer 

acceptance rate as a metric is to increase 

utilization of available organs in the 

system. The efficiency domain, as 

proposed, is not dependent on volume 

of kidney transplants performed but 

how well kidney transplant hospitals 

can prevent receiving offers they will 

knowingly decline, how kidney 

transplant hospitals can optimize filters 

to meet their individual needs and 

minimize organ non-use. We believe 

that performing well in the efficiency 

domain will result in more efficient 

utilization of organs, which can impact 

the number of organs transplanted. 

Comment: A commenter 

recommended following adjusted nonuse rates to account for different donor 

pools year-to-year. 

Response: We appreciate the 

commenter’s response. In the context of 

organ offer acceptance rate ratio, as 

described and finalized in III.C.5.d (1)(a) 

of this final rule, we are utilizing a risk 

adjustment model from year-to-year to 

account for consistent measurement 

between PYs. 

Comment: A commenter suggested 

adding a metric that specifically follows 

non-utilization, particularly for kidneys 

with a KDPI greater than 85. 

Response: We thank the commenter 

for their suggestion. While kidneys with 

a KDPI greater than 85 have high nonuse rates, we recognize that there is 

underutilization of kidneys in all 

categories. Furthermore, in PY 1 we 

believe it is ideal to improve utilization 

broadly, which allows IOTA 

participants the flexibility to focus on 

improving access to groups of donors 

and recipients that may vary between 

regions and IOTA participants. 

Comment: A commenter suggested 

routine reviews of the organ offer 

acceptance rate ratio metric to guarantee 

high quality outcomes. 

Response: We thank the commenter 

for their feedback and agree that the 

organ offer acceptance rate ratio 

calculations and goals will need to be 

monitored closely to ensure their use 

improves the performance of IOTA 

participants without unintended 

consequences. If analysis results 

warrant a new or updated policy, we 


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Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96349 

222OPTN. (2022). OPTN Enhanced Transplant 

Program Performance Metrics. https://

optn.transplant.hrsa.gov/media/r5lmmgcl/mpsc_

performancemetrics_3242022b.pdf. 

223 Mpsc-enhance-transplant-programperformance-monitoring-system_srtr-metrics.pdf. 

(n.d.). Retrieved December 28, 2022, from https:// 

optn.transplant.hrsa.gov/media/qfuj3osi/mpscenhance-transplant-program-performancemonitoring-system_srtr-metrics.pdf. 

224 Ibid. 

225Scientific Registry of Transplant Recipients. 

(n.d.). Risk Adjustment Model: Offer Acceptance. 

Offer acceptance. https://www.srtr.org/tools/offeracceptance/. 

226 Ibid. 

227SRTR. (2023). Srtr.org. https://tools.srtr.org/ 

OAModelApp_2205/; Ibid. 

228CMS notes that some risk adjustment factors 

in the SRTR models may only apply in certain 

ranges of a continuous variable. For example, a term 

that applies if the patient’s age at the time of listing 

is >35 may be named ‘‘can_age_at_listing_right_

spline_knot_35’’. In these cases, obtain the product 

using this formula if the patient’s age at listing was 

>35: product = (Age¥35)*(model coefficient). 

Others may apply if the value is less than (<) a 

specified value. For example, for a term like ‘‘can_

age_at_listing_left_spline_knot_18’’, obtain the 

product for a patient younger than 18 as: product 

= (18¥Age)*(model coefficient). 

will address it pursuant to future 

rulemaking. 

After consideration of public 

comments, for the reasons set forth in 

this rule, we are finalizing, as proposed, 

our provisions to assess performance in 

the efficiency domain using the organ 

offer acceptance rate ratio metric at 

§§ 512.426(a) and (b), as described and 

finalized in section III.C.5.d(1) of this 

final rule. We direct readers to section 

III.C.5.d(1)(a) of this final rule for a full 

discussion on the organ offer acceptance 

rate ratio methodology. As described 

and finalized in section III.C.5.d(1)(c) of 

this final rule, we are finalizing the 

proposed provisions for the point 

allocation and calculation methodology 

for the efficiency domain scoring and 

scoring for organ offer acceptance rate 

ratio for the IOTA Model at § 512.426(c), 

with slight modifications. We direct 

readers to section III.C.5.d.(1).(b). of this 

final rule for a full discussion on the 

point allocation and calculation 

methodology for the organ offer 

acceptance rate ratio metric. 

We are also codifying at § 512.402 the 

definition of efficiency domain as the 

performance assessment category in 

which CMS assesses the IOTA 

participant’s performance using the 

organ offer acceptance rate ratio as 

described in § 512.426. We intend to 

analyze and monitor IOTA participant 

performance to ensure we do not 

unduly disadvantage IOTA participants 

selected for the IOTA Model. If analysis 

warrants a new or updated policy, we 

will address it pursuant to future 

rulemaking. 

(a) Calculation of Metric 

In section III.C.5.d(1)(a) of the 

proposed rule, we proposed calculating 

organ offer acceptance rates for an IOTA 

participant using OPTN’s offer 

acceptance rate ratio performance 

metric (see Equation 1). Per OPTN’s new 

offer acceptance rate ratio, a rate ratio 

for a kidney transplant hospital that is 

greater than 1 indicates that the kidney 

transplant hospital usually accepts more 

offers than expected. A rate ratio that is 

less than 1 conveys a kidney transplant 

hospital’s tendency to accept fewer 

offers than expected compared to 

national offer acceptance practices.222

The OPTN MPSC has reported that this 

metric assesses kidney transplant 

hospitals’ rate of observed organ offer 

acceptances to expected acceptances 

and is intended to answer the following 

question: Given the types of offers 

received to the specific candidates, does 

this program accept offers at a rate 

higher/lower than national experience 

for similar offers to similar 

candidates.223

Equation 1: Organ Offer Acceptance 

Rate Ratio 224

As discussed in section III.C.5.d(1)(a) 

of the proposed rule, expected 

acceptances are based solely on kidneys 

that are accepted and transplanted by a 

kidney transplant hospital, so 

unsuitable kidneys are excluded from 

this measure, and are calculated using 

logistic regression models to determine 

the probability that a given organ offer 

will be accepted. The measure, as 

specified by SRTR methodology, is 

inherently risk adjusted as it only 

counts organs that are ultimately 

accepted by a kidney transplant 

hospital.225 We proposed to use SRTR 

data to calculate the OPTN organ offer 

acceptance rate ratio, as described in 

section III.C.5.d.(1)(a) of the proposed 

rule. 

Per the SRTR measure, we proposed 

in section III.C.5.d(1)(a) of the proposed 

rule, dividing the number of kidney 

transplant organs accepted by each 

IOTA participant (numerator) by the 

risk-adjusted number of expected organ 

offer acceptances (denominator).226 This 

measure utilizes a logistic regression 

and risk adjusts for the following: donor 

quality and recipient characteristics; 

donor-candidate interactions, such as 

size and age differences; number of 

previous offers; and, distance of 

potential recipient from the donor.227

We proposed to use SRTR’s adult 

kidney model strata risk adjustment 

methodology and most recently 

available set of coefficients to calculate 

the number of expected organ offer 

acceptances. 

For example, suppose we have a 

model for predicting the probability a 

kidney offer will be accepted, and this 

model adjusts for the number of years 

the candidate has been on dialysis, 

whether the kidney was biopsied, and 

the distance between the donor hospital 

and the candidate’s transplant center 

(89 FR 43557). Consider the offer of a 

biopsied kidney 150 nautical miles 

(NM) away to a candidate who has been 

on dialysis for 2 years. As described in 

section III.C.5.d(1)(a) of the proposed 

rule, to calculate the probability of 

acceptance, we would first multiply 

these values by their respective model 

coefficients and then sum up those 

products with the model’s intercept, as 

illustrated in Table 5.228


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Organ Offer Acceptance Rate Ratio 

Number of Acceptances + 2 

Number of Expected Acceptances + 2 
96350 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

229OPTN. (2023). OPTN Policies. https://

optn.transplant.hrsa.gov/media/eavh5bf3/optn_

policies.pdf. 230Expedited placement has the potential to 

minimize delays in organ allocation by directing 

organs that may not be ideal to transplant centers 

that have demonstrated a willingness to utilize such 

organs. Currently, expedited placement, also known 

as ‘‘accelerated placement’’ or ‘‘out-of-sequence’’ 

allocation, permits OPOs to deviate from the 

standard match run, which determines the priority 

of patients on the waiting list for organ offers, under 

exceptional circumstances. This discretionary tool 

of expedited placement is employed by OPOs when 

there are suboptimal donor characteristics 

associated with donor disease or recovery-related 

issues, in order to prevent the organ from going 

unused. For numerous years, expedited organ 

placement has played a crucial role in organ 

allocation, enabling OPOs to promptly allocate 

organs that they believe are at risk of not being 

utilized for transplantation. 

231 King, K.L., S Ali Husain, Cohen, D.J., Schold, 

J.D., & Mohan, S. (2022). The role of bypass filters 

in deceased donor kidney allocation in the United 

States. American Journal of Transplantation, 22(6), 

1593–1602. https://doi.org/10.1111/ajt.16967; 

Transplant Quality Corner | The New MPSC Metric. 

(n.d.). The Organ Donation and Transplantation 

Alliance. Retrieved February 23, 2024, from https:// 

www.organdonationalliance.org/insights/qualitycorner/new-mpsc-metric/. 

We would then plug that total into the 

following equation (see Equation 2) to 

get that the probability of acceptance is 

approximately 0.119 (that is., 11.9 

percent chance of acceptance). 

Equation 2: Probability of Organ Offer 

Acceptance 

To determine the number of offers a 

transplant program was expected to 

accept, we would add up the probability 

of acceptance for every offer that 

transplant program received (89 FR 

43557). The final organ offer acceptance 

rate ratio (OAR) is then constructed 

from the observed (O) number of 

acceptances and the expected (E) 

number of acceptances using Equation 1 

as described in section III.C.5.d(1)(a) of 

this final rule. In this example we 

showed a simple logistic regression 

model that only included three riskadjusters. The actual models used by the 

SRTR adjust for many more variables, 

but the process demonstrated here is the 

same. 

As discussed in section III.C.5.d(1)(a) 

of the proposed rule, a kidney may be 

transplanted into a candidate who did 

not appear on the match run, usually to 

avoid discard if the intended recipient 

is unable to undergo transplant. If the 

eventual recipient was not a multi-organ 

transplant candidate and was blood type 

compatible per kidney allocation policy, 

then these transplants would be 

included in the organ offer acceptance 

rate. For purposes of the IOTA Model, 

we proposed to define ‘‘match run’’ as 

a computerized ranking of transplant 

candidates based upon donor and 

candidate medical compatibility and 

criteria defined in OPTN policies. 

Per OPTN’s new organ offer 

acceptance rate ratio, as described in 

section III.C.5.d(1)(a) of the proposed 

rule, Table 6 summarizes the types of 

organ offers that we proposed be 

included and excluded in the 

calculation of this metric. For the 

purposes of organ offers excluded from 

the organ offer acceptance rate ratio, we 

proposed to define ‘‘missing responses’’ 

as organ offers that the kidney 

transplant hospital received from the 

OPO but did not submit a response 

(accepting or rejecting) in the allotted 

time frame from the time the offer was 

made per OPTN policy 5.6.B.229 For 

purposes of organ offers excluded from 

the organ offer acceptance rate ratio 

measure, we proposed to define 

‘‘bypassed response’’ as an organ offer 

not received due to expedited 

placement 230 or a decision by a kidney 

transplant hospital to have all of its 

waitlisted candidates skipped during 

the organ allocation process based on a 

set of pre-defined filters matching the 

characteristics of the potential organ to 

be transplanted.231


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TABLE 5: EXAMPLE OF SUMMING UP COEFFICIENTS 

-0.525 

use 1 for interce t -0.225 

Total -2 

Probability of Organ Offer Acceptance 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96351 

232OPTN. (2022). OPTN Enhanced Transplant 

Program Performance Metrics. https://

optn.transplant.hrsa.gov/media/r5lmmgcl/mpsc_

performancemetrics_3242022b.pdf; For Transplant 

Center Professionals. (n.d.). www.srtr.org. Retrieved 

February 22, 2023, from https://www.srtr.org/faqs/ 

for-transplant-center-professionals/ 

#oaconsideration. 

As discussed in section III.C.5.d(1)(a) 

of the proposed rule, we believed that 

IOTA participants could improve on the 

organ offer acceptance rate ratio metric 

in at least two ways. First, IOTA 

participants could increase the number 

of organ offers they accept, which 

would also potentially lead to greater 

performance scores in the achievement 

domain. Second, IOTA participants 

could also decrease the number of 

expected acceptances by adding better 

filters so that they are only receiving 

offers that they are likely to accept. 

Stricter filters may help ensure that an 

IOTA participant is not delaying the 

allocation of organs that they are 

uninterested in that could otherwise be 

accepted by another kidney transplant 

hospital. Since there are multiple ways 

to improve the offer acceptance ratio, 

the IOTA Model is not requiring 

increased utilization of higher KDPI 

kidneys that some IOTA participants 

may not want to use due to their clinical 

protocols. Additionally, the IOTA 

Model is not prescribing or requiring 

specific care delivery transformation or 

improvement activities of IOTA 

participants, so as to allow for flexibility 

and innovation. 

In section III.C.5.d(1)(a) of the 

proposed rule, we considered 

calculating the organ offer acceptance 

rate by dividing the number of organs 

each IOTA participant accepts by the 

number offered to that transplant 

hospital’s patients that are ultimately 

accepted elsewhere; however, the lack 

of risk adjustment in this metric may be 

unfair to some IOTA participants (89 FR 

43558). 

As mentioned in section III.C.5.d(1)(a) 

of the proposed rule, we also considered 

updating the calculation for organ offer 

acceptance rate ratio to account for the 

benefits of living donation by increasing 

the number of organs in the system 

because the proposed organ offer 

acceptance rate ratio only shows 

improvement in deceased donor 

utilization. This modification would 

add a single 1 in the numerator and a 

single 1 in the denominator for each 

living donation a transplant hospital 

completes. However, we did not 

propose updating the organ offer 

acceptance rate ratio because we 

decided to focus on deceased donor 

acceptance to remain aligned with the 

SRTR calculation. We also did not 

believe this was appropriate to propose 

because we believe that IOTA 

participants with an established or high 

performing living donation program 

would be able to gain points more easily 

in the achievement domain, which has 

a larger percent of overall points, which 

we thought may be unfair to IOTA 

participants that do not. 

We sought comment on our proposal 

to use and calculate the OPTN organ 

offer acceptance rate ratio in accordance 

with OPTN’s measure specifications and 

SRTR’s methodology as the metrics that 

would determine IOTA participants’ 

performance on the efficiency domain. 

We also sought comments on the 

alternatives we considered. 

Additionally, we sought comment on 

our proposed definitions. 

The following is a summary of the 

comments received on our proposed 

utilization of the organ offer acceptance 

rate ratio using OPTN measure 

specifications and SRTR metrics for the 

efficiency domain and our responses: 

Comment: Several commenters 

requested clarification for how organ 

offer filters will be used when 

calculating the organ offer acceptance 

rate ratio. They were concerned that 

using filters may create conflicts 

between kidney transplant volume and 

offer acceptances. 

Response: We appreciate the 

commenters’ feedback. Organ offer 

filters allow kidney transplant hospitals 

to specify characteristics of donors or 

donor-recipient matches they would not 

transplant at their transplant program, 

to prevent unnecessary organ offers and 

to allow the organ to go to another 

kidney transplant hospital who may 

accept the offer, more expeditiously. 

Organ filter use does not directly 

contribute to the organ offer acceptance 

rate ratio calculation. Use of filters, 

however, can impact the calculation 

result. Kidney transplant hospitals may 

choose to use less filters, allowing 

increased offers; or they may choose to 

use more strict filters to ensure that they 

are very likely to accept the offers they 

receive. We acknowledge that kidney 

transplant hospitals will not accept 

every organ offer and that they must 

maintain some flexibility to keep some 

filter criteria liberal to meet the needs of 

some of their beneficiaries, however, we 

believe these practices will be relatively 

consistent between kidney transplant 

hospitals to create comparable results. 

We also agree that it may take kidney 

transplant hospitals time to optimize 

their organ offer filters and their 

increase in kidney transplants, which is 

one of the reasons that we ensured that 

PY 1 does not have any downside risk, 

regardless of final performance score. 

Comment: A few commenters 

requested clarification as to whether 

CMS would create a new organ 

acceptance rate measure, stating it must 

be validated, if so. 


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TABLE 6: ORGAN OFFERS INCLUDED AND 

EXCLUDED FROM MEASURE232 

• Organ offers that are ultimately accepted 

and transplanted. 

• Offers to candidates on a single organ 

waitlist ( except for Kidney /Pancreas 

candidates that are also listed for kidney 

alone). 

• Multiple match runs from same donor 

combined and duplicate offers. 

• Match run had no acceptances. 

• Off er occurred after last acceptance in a 

match run. 

• Missing or bypassed response. 

• Offers to multi-organ candidates ( except 

for Kidney/Pancreas candidates that are 

also listed for kidne alone . 
96352 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

233Liyanage, L.N., Akizhanov, D., Patel, S.S., 

Segev, D.L., Massie, A.B., Stewart, D.E., & Gentry, 

S.E. (in press). Contemporary prevalence and 

practice patterns of out-of-sequence kidney 

allocation. American Journal of Transplantation. 

https://doi.org/10.1016/j.ajt.2024.08.016. 

234OPTN. (2023, September 14). New pretransplant performance metric now in effect, offer 

acceptance rate ratio. Retrieved August 15, 2024 

Response: As outlined in section 

III.C.5.d(1)(a) of this final rule, we 

proposed OPTN’s measure 

specifications and SRTR’s methodology. 

Comment: Several commenters stated 

their concerns about the CMS 

calculations for organ offer acceptance 

rate ratio. Each commenter within this 

group had a different concern, including 

the lack of risk adjustment, unfair 

comparison of large and small kidney 

transplant hospitals, how calculations 

are applied to beneficiaries that are 

toward the bottom of the waitlist and if 

the methodology will make a kidney 

transplant hospital’s waitlist criteria 

more strict. 

Response: We thank the commenters 

for their feedback. The SRTR 

methodology outlined in section 

III.C.5.d.(1).(a). of this final rule 

includes a risk-adjusted number of 

expected organ offer acceptances in its 

calculation. 

While we acknowledge the different 

challenges of IOTA participants with 

variable volumes of kidney transplants, 

we also believe that each category of 

IOTA participants has different 

opportunities to impact their organ offer 

acceptance rate ratio. An IOTA 

participant with high volume of kidney 

transplants may focus on accepting 

higher score kidneys, whereas an IOTA 

participant with low volume of kidney 

transplants may be able to have more 

strict filter criteria to ensure the organ 

offers they receive are those that they 

will accept. 

The SRTR methodology is based on a 

match run, if the IOTA participant 

accepts an organ offer and whether the 

IOTA participant was expected to 

accept the offer, based on the 

methodology and risk adjustment as 

described in section III.C.5.d.(1).(a). of 

this final rule. If a kidney transplant 

waitlist patient is not at the top of the 

waiting list and does not match, this 

calculation would not be applicable. 

Finally, we agree that if a kidney 

transplant hospital uses very strict filter 

criteria this could impact their waitlist, 

however, we also believe it is important 

to consider having organ offer filter 

criteria reflect the organ offers that their 

transplant programs actually accept. 

The organ offer acceptance rate ratio 

methodology and subsequent use of 

organ offer filters encourages IOTA 

participants to minimize non-use of 

organs and minimize cold ischemic 

times. 

Comment: A commenter requested 

clarification around what is considered 

an ‘‘unsuitable kidney’’ in the list of 

exclusions for the expected organ offer 

acceptance rate ratio. 

Response: We recommend the 

commenter review III.C.5.d.(1)(a) Table 

6 for a full list of exclusions from the 

measure. If a kidney transplant organ is 

not used by any kidney transplant 

hospital, that kidney is excluded from 

the organ offer acceptance rate ratio 

calculation. 

Comment: A commenter stated they 

agreed with the inclusion and exclusion 

criteria for organ offers included in the 

calculation of the organ offer acceptance 

rate ratio. 

Response: We thank the commenter 

for their support. 

Comment: A commenter was 

concerned that out-of-sequence kidney 

offers are included in the measurement 

of success. Similarly, another 

commenter suggested CMS monitor the 

rate of out-of-sequence allocation that 

occurs. 

Response: We appreciate the 

commenter’s feedback. The commenter 

is correct that the SRTR methodology 

does not account for out-of-sequence 

kidney offers. Given the historic rise of 

out-of-sequence allocation over the last 

few years, we intend to monitor this 

closely.233 If analysis results warrant a 

new or updated policy, we will address 

it pursuant to future rulemaking. 

Comment: A commenter asked that 

CMS clarify filter use and how it would 

impact those patients that remain after 

filtering. 

Response: We appreciate the 

commenter’s feedback. Organ offer 

filters allow kidney transplant hospitals 

to specify characteristics of donors or 

donor-recipient matches they would not 

transplant at their transplant program, 

to prevent unnecessary organ offers and 

to allow the organ to go to another 

kidney transplant hospital who may 

accept the offer, more expeditiously. By 

utilizing filters that more closely match 

what offers a kidney transplant hospital 

is likely to accept for their waitlisted 

patients, the kidney transplant hospital 

will have a higher likelihood of organ 

offer acceptance. Furthermore, this 

would increase their organ offer 

acceptance rate ratio. 

Comment: A commenter was 

concerned that the SRTR methodology 

does not account for non-viable kidneys. 

Response: We appreciate the 

commenters concern and agree that not 

all offers are viable and acknowledges 

this in section III.C.5.d.(1).(a). of this 

final rule, Table 6, where exclusions for 

the organ offer acceptance rate ratio 

metric are included. Kidney match runs 

that have no acceptances are excluded 

in this metric. The calculation leaves 

‘‘viability’’ judgment to the kidney 

transplant hospitals. If the commenter is 

concerned that there are too many nonviable kidney organ offers occurring, 

this would be a matter that may need to 

be discussed with OPOs and is outside 

the scope of the IOTA Model. 

Comment: A commenter disagreed 

with use of the SRTR data because the 

c-statistic of their tool has not been 

published. 

Response: We thank the commenter 

for their feedback. Availability of the 

published c-statistic of the SRTR data is 

not something we took into 

consideration, however, we believe that 

the SRTR methodology and OPTN data 

is appropriate for use in the IOTA 

Model given its risk adjustment, as 

outlined in section III.C.5.d.(1).(a). of 

this final rule. If analysis results warrant 

a new or updated policy, we will 

address it pursuant to future 

rulemaking. 

Comment: A commenter suggested 

CMS modify its organ offer acceptance 

rate ratio calculation methodology by 

dividing accepted organs by organs 

offered elsewhere that are accepted. 

Response: We thank the commenter 

for their suggestion. We previously 

considered this as an option for the 

efficiency domain performance metric; 

however, we were concerned that the 

lack of risk adjustment would be unfair 

to IOTA participants. 

Comment: A few commenters 

suggested that CMS not use the SRTR 

methodology. Each individual 

commenter had a different concern, 

including that this methodology follows 

unproven outcomes, that the UNOS data 

is more up to date than SRTR data, and 

that using SRTR methodology conflicts 

with the achievement domain. 

Response: We appreciate the 

commenters’ suggestions and concerns 

and hope to provide some clarification. 

We are not using SRTR data and note 

that there is not ‘‘UNOS data’’. The 

SRTR methodology is calculated with 

OPTN data. By using the same 

methodology and data as the OPTN’s 

organ offer acceptance rate ratio metric, 

the IOTA Model results will align with 

those tested by OPTN/UNOS, as 

recommended by the MPSC. As 

previously mentioned, the organ offer 

acceptance rate ratio has been utilized 

by SRTR since 2023 and while lacking 

formal validation, is not unknown to the 

transplant community.234 If analysis 


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from https://optn.transplant.hrsa.gov/news/newpre-transplant-performance-metric-now-in-effectoffer-acceptance-rate-ratio/. 

235Subsequent to the publication of the proposed 

rule, we found that. 

236 King, K.L., Husain, S.A., Schold, J.D., Patzer, 

R.E., Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., 

Pastan, S.O., & Mohan, S. (2020). Major Variation 

across Local Transplant Centers in Probability of 

Kidney Transplant for Wait-Listed Patients. Journal 

of the American Society of Nephrology, 31(12), 

2900–2911. https://doi.org/10.1681/ 

ASN.2020030335. 

237 King, K.L., Husain, S.A., Schold, J.D., Patzer, 

R.E., Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., 

Pastan, S.O., & Mohan, S. (2020). Major Variation 

across Local Transplant Centers in Probability of 

Kidney Transplant for Wait-Listed Patients. Journal 

of the American Society of Nephrology, 31(12), 

2900–2911. https://doi.org/10.1681/ 

ASN.2020030335. 

238 Ibid. 

results warrant a new or updated policy, 

we will address it pursuant to future 

rulemaking. 

Additionally, we believe SRTR 

methodology, or more generally the 

organ offer acceptance rate ratio, 

ensures balance in the model. While the 

achievement domain focuses on 

increasing kidney transplant volume, 

the efficiency domain metrics focuses 

on efficient utilization of kidney 

transplants to reduce organ non-use. By 

optimizing filters, IOTA participants are 

ensuring that their kidney transplant 

waitlist patients that are active on the 

transplant waitlist will actually be 

transplanted. Additionally, we believe 

organ filters allow kidneys to be 

directed to the appropriate kidney 

transplant hospital to improve quality of 

organs (lesser cold ischemic time) and 

potentially increase volume of 

transplants due to a more efficient 

process. 

After consideration of public 

comments, for the reasons set forth in 

this rule, we are finalizing, without 

modification, at § 512.426(b)(1) our 

proposals to use and calculate the OPTN 

organ offer acceptance rate ratio in 

accordance with OPTN’s measure 

specifications and SRTR’s methodology 

as the metrics that would determine 

IOTA participants’ performance on the 

efficiency domain. Additionally, we are 

finalizing as proposed the definitions of 

match run, missing responses, and 

bypassed response at § 512.402. 

(b) Calculation of Points 

As described in section III.C.5.b. of 

the proposed rule, we proposed that 

performance on the efficiency domain 

would be worth up to 20 points of 100 

maximum points. As indicated in 

section III.C.5.c.(2). of this final rule, the 

efficiency domain is weighted lower 

than the achievement domain but equal 

to the quality domain to ensure 

performance measurement is primarily 

focused on increasing number of kidney 

transplants, while still incentivizing 

efficiency and quality. Within the 

efficiency domain, we proposed that the 

OPTN organ offer acceptance rate ratio 

would account for the entirety of the 20 

allocated points in that domain. 

In section III.C.5.d.(1).(b) of the 

proposed rule, we proposed applying a 

two-scoring system to award up to 20 

points to the IOTA participant based on 

its performance on the OPTN organ offer 

acceptance rate ratio. Under this twoscoring system, we would determine 

two separate scores for an IOTA 

participant: an ‘‘achievement score’’ 

reflecting its current level of 

performance, and an ‘‘improvement 

score’’ reflecting changes in its 

performance over time. We proposed 

that the IOTA participant would be 

awarded points equal to the higher of 

the two scores, up to a maximum of 20 

points. We believed that this approach 

would recognize both high achievement 

among high performing IOTA 

participants as well as IOTA 

participants that make marked 

improvement in their performance. We 

believe that average or low-performing 

IOTA participants would likely require 

multiple years of transformation to 

catch up with those who have a high 

organ offer acceptance rate ratio. 

In section III.C.5.d.(1).(b). of the 

proposed rule, for achievement scoring, 

we proposed that points earned would 

be based on the IOTA participants’ 

performance on the organ offer 

acceptance rate ratio ranked against a 

national target,235 inclusive of all 

eligible kidney transplant hospitals, 

both those selected and not selected as 

IOTA participants. Currently, there is a 

large disparity in organ offer acceptance 

ratio performance. As previously noted, 

a 2020 national registry study found that 

the probability of receiving a deceased 

donor kidney transplant within 3 years 

of waiting list placement varied 16-fold 

between different kidney transplant 

hospitals across the U.S.236 Large 

variations were still present between 

kidney transplant hospitals that utilized 

the same OPO.237 The probability of 

transplant was significantly associated 

with transplant hospitals’ offer 

acceptance rates.238

We proposed that achievement 

scoring points be awarded based on the 

national quintiles, as outlined in Table 

7 of section III.C.5.d.(1).(b). of this final 

rule. Utilizing quintiles aligns with the 

calculation of the upside and downside 

risk payments in relation to the final 

performance score, as detailed in 

section III.C.6.c.(2). of this final rule, 

where average performance yields half 

the number of points. The scoring is 

normalized, meaning an average 

performing IOTA participant earns 10 

points out of 20, 50 percent of the total 

possible points. We recognized that 

there was an upper limit to the benefits 

of efficiency, and quintiles combine the 

highest 20 percent of performers in a 

point band. Due to the current disparity 

among kidney transplant hospitals on 

this metric, we did not expect every 

IOTA participant to reach top-level 

performance. 

In the proposed rule, we proposed the 

following Organ Offer Acceptance Rate 

Achievement point allocation for IOTA 

participants, as illustrated in Table 7 of 

section III.C.5.d.(1).(b). of this final rule: 

• IOTA participants in the 80th 

percentile and above, 20 points. 

• IOTA participants in the 60th to 

below the 80th percentile of performers, 

15 points. 

• IOTA participants in the 40th to the 

60th percentile of performers, 10 points. 

• IOTA participants in the 20th to 

below the 40th percentile of performers, 

6 points. 

• IOTA participants who are below 

the 20th percentile of performers, 0 

points. 


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As discussed in section 

III.C.5.d.(1).(b). of the proposed rule, we 

considered the approach used by the 

MPSC, that would yield maximum 

points if transplant hospitals have at 

least a .35 organ offer acceptance rate 

ratio. However, we do not believe that 

this approach fits with the IOTA 

Model’s goals. MPSC metrics are more 

focused on highlighting and improving 

performance for the lowest performers, 

whereas the model seeks to improve 

performance across the board, not just 

avoid poor performance. 

For improvement scoring, we 

proposed in section III.C.5.d.(1).(b). of 

the proposed rule, that points earned 

would be based on the IOTA 

participants’ performance on organ offer 

acceptance rate ratio during a PY 

relative to their performance during the 

third baseline year for the PY that is 

being measured. We proposed to use the 

same baseline year definition used for 

participant eligibility, as described in 

section III.C.3. of the proposed rule, 

including the rationale for doing so. We 

separately proposed to calculate an 

‘‘improvement benchmark rate,’’ 

defined as 120 percent of the IOTA 

participants’ performance on the organ 

offer acceptance rate ratio during the 

third baseline year for each PY. We 

would award points by comparing the 

IOTA participant’s organ offer 

acceptance rate ratio during the PY to 

the IOTA participant’s improvement 

benchmark rate to determine the 

improvement scoring points earned. 

Specifically: 

• IOTA participants whose organ 

offer acceptance rate ratio during a PY 

is at or above the improvement 

benchmark rate would receive 12 

points. 

• IOTA participants whose organ 

offer acceptance rate ratio during a PY 

is at or below the organ offer acceptance 

rate ratio during the third baseline year 

for that respective PY would receive no 

points. 

• IOTA participants whose organ 

offer acceptance rate ratio during a PY 

is greater than the organ offer 

acceptance rate ratio during the third 

baseline year for that respective PY, but 

less than the improvement benchmark 

rate, would earn a maximum of 12 

points in accordance with Equation 3. 

Equation 3: Proposed Improvement 

Scoring for Organ Offer Acceptance Rate 

Ratio 

As discussed in section 

III.C.5.d.(1).(b). of the proposed rule, we 

proposed using Equation 3 to mirror the 

methodology used in the Hospital Value 

Based Purchasing (VBP) Program, with 

the only modification being the number 

of points available for this metric. 

Equation 3 would also allow for a 

maximum of 12 points to be earned by 

IOTA participants whose organ offer 

acceptance rate ratio during the PY is 

greater than the baseline year organ offer 

acceptance rate ratio but less than the 

improvement benchmark rate. We did 

not want the improvement score to be 

worth more than, or equal to, the 

achievement score, as proposed for the 

organ offer acceptance rate ratio 

performance scoring, so as to reserve the 

highest number of points (15 points) for 

top performers in the metric. 

Once both the achievement score and 

the improvement score were calculated, 

we proposed, in section III.C.5.d.(1).(b). 

of the proposed rule, comparing the two 

scores and applying the higher of the 

two values as the performance score or 

points earned (of 20 possible points) for 

the organ offer acceptance rate ratio 

metric within the efficiency domain. 

In section III.C.5.d.(1).(b). of the 

proposed rule, we considered setting the 

improvement benchmark rate to be 200 

percent of the IOTA participant’s third 

baseline year for a given PY to measure 

performance on the organ offer 

acceptance rate ratio. The scoring 

structure would be the same, with 12 or 

0 points to be awarded depending on 

whether the benchmark is met. 

However, we believed this would be too 

strict and risk penalizing already highachieving IOTA participants. 

In section III.C.5.d.(1).(b). of the 

proposed rule, we considered 

simplifying the performance scoring for 

the organ offer acceptance rate ratio 

metric within the efficiency domain by 

only awarding performance points 

based on the proposed achievement 

scoring methodology, rather than also 

calculating an improvement score for 

the IOTA participant and comparing the 

scores. However, given the variation 

that is present amongst kidney 

transplant hospitals, we thought it 

might be difficult for some IOTA 

participants to achieve top tier points 

for the first two model PYs. Thus, 

incorporating an improvement scoring 

method would ensure that IOTA 

participants are still rewarded for 

improvements made towards the 

efficiency domain goal. 

We considered using the scoring 

method proposed for the post-transplant 

outcomes metric within the quality 

domain, as described in section 

III.C.5.e.(1)(b) of the proposed rule, as it 

would award full points if the hazard 

ratio or confidence interval of the metric 

includes the number one or higher. We 

believed this scoring method would 

honor the intent of the organ offer 

acceptance rate ratio metric, which is to 

determine if an IOTA participant is 

accepting more organs than expected. 

However, given the variation in 


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TABLE 7: ORGAN OFFER ACCEPTANCE RATE ACHIEVEMENT SCORING 

60th Percentile Less than 80th 15 

40th Percentile Less than 60th 

20th Percentile Less than 40th 6 

20th Percentile Less than 20th 0 

Organ Offer Acceptance Rate Ratio Improvement Scoring = 

Rate Earned in Performance Year - Rate Earned in Third Baseline Year 

12 X . . Benchmark Rate - Third Baseline Year Rate 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96355 

performance on this metric across all 

kidney transplant hospitals, we believe 

improvement opportunities exist in this 

metric. We also believe that our 

proposed approach rewards both 

achievement and improvements and is a 

more rigorous scoring methodology. 

As discussed in section 

III.C.5.d.(1).(b). of the proposed rule, we 

considered a continuous scoring range 

from zero to 20, where IOTA 

participants may earn a score of any 

point value instead of bands. We 

thought that a continuous scoring range 

could provide more flexibility for IOTA 

participants and greater variety of 

scores. However, we believe grading 

using bands provides a more favorable 

scoring system for IOTA participants by 

grouping performance. We also 

recognize there is diminishing marginal 

efficiency for higher and higher organ 

offer acceptance rate ratios. 

We considered using the lower and 

upper bounds of the offer acceptance 

odds ratio within a confidence interval, 

like we proposed in the quality domain 

for post-transplant outcomes, as 

described in section III.C.5.e.(1).(b). of 

the proposed rule. However, the organ 

offer acceptance rate ratio metric, unlike 

post-transplant outcomes, had wider 

disparity in performance than in posttransplant outcomes. We believe that 

there is a clear benefit to patients and 

the transplantation ecosystem overall by 

continuing to increase performance on 

this metric and promoting better 

performance than the national average. 

Under this alternative, IOTA 

participants would be evaluated based 

on whether the lower bound, acceptance 

ratio, and upper bound all crossed 1. 

Doing so would indicate the IOTA 

participant’s true offer acceptance ratio 

with 95 percent probability. We did not 

propose this approach, however, as our 

analyses using SRTR data indicated that 

the majority of kidney transplant 

hospitals had either all three bounds 

cross 1 or all three never cross 1. Thus, 

scoring would largely not have differed 

from utilizing the offer acceptance ratio 

alone. 

Finally, in section III.C.5.d.(1).(b). of 

the proposed rule, we also considered 

stratifying offer acceptance by KDRI 

status, with different score targets based 

on KDRI status ranges, such as KDRI of 

less than 1.05, between 1.05 and 1.75, 

and more than 1.75. We thought that 

this scoring method may potentially 

prevent IOTA participants from 

narrowing their criteria to only receive 

selected offers. However, we believed 

that it was already risk adjusted for 

organ status inherently in the measure 

because only organs that are ultimately 

transplanted are counted in the 

denominator. 

We sought comment on our proposed 

organ offer acceptance rate ratio 

performance scoring methodology for 

purposes of assessing efficiency domain 

performance for each IOTA participant, 

including on the achievement and 

improvement score calculation and 

point allocation method. We also seek 

comments on alternatives considered. 

The following is a summary of 

comments received on our proposed 

scoring methodology for the organ offer 

acceptance rate ratio performance in the 

efficiency domain and our responses: 

Comment: Several commenters 

relayed concern that there may be a typo 

in the proposed rule, which stated the 

highest amount of points for the 

efficiency domain is 15. 

Response: We thank the commenters 

for identifying a typo in the proposed 

rule. The highest amount of points 

available for IOTA participants to earn 

is 20 points if they are in the highest 

quintile of the organ offer acceptance 

rate ratio achievement score. 

Comment: There were numerous 

comments about scoring methodology. 

Several commenters requested 

clarification as to why the improvement 

component of the efficiency domain 

does not provide more than 12 points. 

A couple of commenters had specific 

concerns that quintile methodology is 

not ideal and creates uncertainty. A 

commenter was concerned that 

improvement score of the efficiency 

domain does not account for high 

performers who may have challenges 

improving every year. 

Response: Thank you for seeking 

clarification. An improvement goal was 

selected in addition to an achievement 

goal to account for the variation among 

kidney transplant hospitals and in 

acknowledgement that it may be 

challenging for some kidney transplant 

hospitals to reach high performance 

levels in the achievement component of 

the efficiency domain. In the proposed 

rule, we chose not to provide maximum 

points in the improvement domain, in 

order to reward the top-tiered programs 

in efficiency performance. Additionally, 

if some kidney transplant hospitals 

newly utilize filters, while others have 

already been utilizing filters, this will 

increase their improvement score 

significantly. By limiting improvement 

points, this prevents mismatch in 

recognizing those who newly and 

previously utilize filters. 

We note that we are finalizing these 

policies as proposed but with a minor 

technical correction to update the 

maximum number of points awarded for 

improvement scoring from 12 points to 

15 points. In the proposed rule at 89 FR 

43560, we proposed to award IOTA 

participants whose organ offer 

acceptance rate ratio during a PY is at 

or above the improvement benchmark 

rate would receive 12 points. We also 

proposed at 89 FR 43560 that IOTA 

participants whose organ offer 

acceptance rate ratio during a PY is 

greater than the organ offer acceptance 

rate ratio during the third baseline year 

for that respective PY, but less than the 

improvement benchmark rate, would 

earn a maximum of 12 points in 

accordance with equation 1 to 

paragraph (c)(1)(ii)(B)(1) of § 512.426. 

However, we also stated at 89 FR 43560 

that we did not want the improvement 

score to be worth more than, or equal to, 

the achievement score, as proposed for 

the organ offer acceptance rate ratio 

performance scoring, so as to reserve the 

highest number of points (15 points) for 

top performers in the metric. Thus, we 

are updating the regulation text at 

§ 512.426(c)(1)(ii)(B)(1) to reflect 15 

points instead of 12 points and equation 

1 to paragraph (c)(1)(ii)(B)(1) of 

§ 512.426, as illustrated in equation 4 

below, to reflect a multiplier of 15 

instead of 12. 

Equation 4: Improvement Scoring for 

Organ Offer Acceptance Rate Ratio 

Additionally, the commenters are 

correct that the methodology creates a 

moving target for rankings within the 

scoring quintiles, year to year. This 

method was chosen to ensure that 

targets reflect current practices and 


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Organ Offer Acceptance Rate Ratio Improvement Scoring = 

Rate Earned in Performance Year - Third Baseline Year Rate 

15x------------------------- Improvement Benchmark Rate - Third Baseline Year Rate 
96356 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

trends across kidney transplant 

hospitals. 

We also note that we are finalizing 

this policy as proposed but with a minor 

technical correction to update the 

terminology used to provide points for 

achievement scoring in the efficiency 

domain. In the proposed rule at 89 FR 

43559, we proposed that achievement 

scoring, would be based on the IOTA 

participant’s performance on the organ 

offer acceptance rate ratio ranked 

against a national target, inclusive of all 

eligible kidney transplant hospitals, 

both those selected and not selected as 

IOTA participants. However, we also 

stated at 89 FR 43559 that achievement 

scoring points be awarded based on the 

national quintiles, as outlined in Table 

6 of section III.C.5.d.(1).(b). of the 

proposed rule. Thus, we are updating 

our regulation text at § 512.426(c)(2)(i) 

to remove the reference to performance 

being measured against a national target 

and instead based on national ranking. 

Based on PY 1 and ongoing feedback, 

we will consider in future rulemaking if 

there should be alternative point 

opportunities for the efficiency 

improvement scoring scale in later 

performance years. If analysis results 

warrant a new or updated policy, we 

will address it pursuant to future 

rulemaking. 

Comment: A couple of commenters 

were concerned that IOTA participants 

may accept deceased donor organs more 

aggressively or make their waitlist 

criteria more stringent, to have a high 

score in the efficiency domain due to 

the percentile scoring. 

Response: We agree that some IOTA 

participants with higher risk thresholds 

may accept deceased donor organs more 

aggressively, if they believe they have 

the resources and support for their 

patients post-transplant. While this may 

apply to some kidney transplant 

hospitals, however, we do not believe 

that this will be a common approach. 

IOTA participants have the opportunity 

to consider utilizing filters that more 

closely match their risk threshold and 

waitlist patient population. While we do 

not believe that the efficiency domain 

will make waitlist criteria more 

stringent, we do believe that paired with 

the transparency notification 

requirement in section III.C.8.a(2), IOTA 

participants may be more inclined to 

remove patients from their active 

waitlist who are not potential kidney 

transplant candidates. Should we notice 

an adverse effect of the efficiency 

domain, such as reduction in access to 

waitlisting or being active on the 

waitlist, we will take this into 

consideration for future rulemaking. 

Additionally, as mentioned in the 

comments noted previously in this 

section, we are we are updating our 

regulation text at § 512.426(c)(2)(i) and 

in Table 1 to Paragraph (c)(1)(i) at our 

regulation at § 512.426 to remove 

reference to performance being 

measured against a national target and 

is instead based on national ranking. 

Comment: A few commenters 

suggested considerations for the 

efficiency domain scoring. These 

considerations included ensuring not to 

penalize IOTA participants that are 

already accepting more organs than 

expected, moderating the proposed 

expectations for performance in the 

achievement and improvement scores, 

and aligning the efficiency domain 

point system to SRTR’s upcoming 

method of creating performance tiers. 

Several commenters also provided 

suggestions for alternative criteria for 

kidney transplant hospitals to receive 

the full 20 points in the efficiency 

domain. The suggestions included 

awarding full points for meeting the 

OPTN’s minimum ratio, having an organ 

offer acceptance ratio of 1.0, and 

meeting organ acceptance expectations. 

There were also a few suggestions that 

kidney transplant hospitals that meet 

the improvement component criteria 

should be awarded the full 20 points as 

well; this could potentially be 

accomplished by having programs opt 

in to either an achievement or 

improvement track. Finally, a 

commenter pointed out that because the 

organ offer acceptance rate ratio is 

compared to national performance for 

the achievement component of the 

efficiency domain, a program may 

improve its rate but not its ratio 

depending on the national rate. They 

same commenter suggested considering 

relative acceptance rate. Similarly, a 

commenter stated the scoring system, as 

proposed, is too harsh. 

Response: We thank the commenters 

for their feedback. As mentioned in the 

proposed rule, we do not expect every 

IOTA participant to reach top-level 

performance. If an IOTA participant is 

already accepting more organs than 

expected, they will likely have a high 

scoring ratio as well. An IOTA 

participant that scores in the 50th 

percentile of performance for the organ 

offer acceptance rate achievement score 

would receive 10 out of 20 points. 

Alternatively, if an IOTA participant 

improves their organ offer acceptance 

rate ratio by 120 percent of their 

benchmark rate, as proposed, they can 

earn 15 points. As mentioned in the 

comments noted previously in this 

section, we are finalizing our proposed 

organ offer acceptance rate ratio 

improvement scoring methodology to 

reflect that the maximum number of 

points awarded for improvement 

scoring is 15 points, rather than 12 

points. 

For PY 1, we believe it is appropriate 

to carve out more points for those IOTA 

participants who have the highest 

performance. We do not believe the 

OPTNs minimum ratio is high enough 

to nudge transplant programs to 

continue to improve on this 

performance metric. As mentioned in 

the comments noted previously in this 

section, we are finalizing our proposed 

organ offer acceptance rate ratio 

achievement scoring methodology with 

slight modifications to reflect that 

points earned will be based on national 

ranking rather than a national target. 

Although we did not consider the 

SRTRs performance tier assessment in 

the proposed rule, we are interested to 

learn more about this methodology once 

implemented and to further consider 

this for future rulemaking. We will also 

continue to consider if the improvement 

maximum score should be equivalent to 

the achievement maximum score and if 

achieving upper quintile ranks is too 

challenging. This, in addition to 

ongoing feedback and performance 

during PY 1 will help guide us in future 

rulemaking. 

Comment: A commenter was 

concerned that the organ offer 

acceptance rate ratio would be impacted 

by transplant programs completing dual 

organ transplants, who may receive 

priority offers. 

Response: We thank the commenter 

for their feedback and recommends 

reviewing Table 6 of section 

III.C.5.d(1)(a) of this final rule, which 

includes organ offers included and 

excluded from the organ offer 

acceptance rate ratio metric. This 

specifically identifies that offers to 

multi-organ candidates (except kidney 

pancreas candidates that are also listed 

for kidney alone) are excluded from the 

measure. 

Comment: A few commenters were 

concerned about overall impact of risks 

and costs of the organ offer acceptance 

ratio methodology. A couple of 

commenters were concerned that point 

allocation for the organ offer acceptance 

rate ratio and kidney transplant volume 

will increase marginal kidney use and 

have higher financial costs and risks to 

patients. A commenter specifically 

asked whether there will be subsequent 

increase in reimbursement and SRTR 

adjustments. Similarly, another 

commenter stated that the organ offer 

acceptance ratio incentivizes IOTA 

participants to accept offers they may 

not ordinarily accept and is concerned 

that the IOTA Model needs to minimize 


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the risk of adverse outcomes when 

evaluating participating hospitals fairly. 

Response: We thank the commenters 

for sharing their concerns. We agree that 

some IOTA participants may choose to 

increase their utilization of DCD 

kidneys or kidneys with a KDPI greater 

than 85, however, this is a choice for 

each IOTA participant based on their 

comfort level and resources and is not 

the only way for an IOTA participant to 

perform well in the IOTA Model. 

Regardless of the approach of each 

IOTA participant, we intend to monitor 

for unintended consequences that my 

occur with the model. We bring 

attention to the fact that while IOTA 

participants who achieve a final 

performance score of 60 or more points 

will receive an upside risk payment, as 

described and finalized in section 

III.C.6.c(1) of this final rule, there is also 

a neutral zone for IOTA participants 

who achieve a final performance score 

between 0 and 59 points in PY 1 and a 

final performance score of 40–59 points 

in PY 2 through PY 6, as described and 

finalized in section III.C.6.c(1) of this 

final rule. We direct readers to sections 

III.C.6 of this final rule for a full 

discussion on payment. With increasing 

resources and knowledge such as access 

to timely donor biopsies and research 

on what factors prompt kidneys to be 

designated as high KDPI kidneys, there 

are growing opportunities in the 

transplant ecosystem to identify kidneys 

that may or may not be ideal to 

transplant. 

As for as modifications to SRTR 

adjustments and reimbursement, we 

will continue to collaborate with other 

groups in OTAG to work on aligning 

goals across the transplant ecosystem. 

Comment: A few commenters had 

concerns that IOTA participants may 

change their habits or manipulate their 

listing or transplant practices to 

improve their organ offer acceptance 

rate. Specifically, a couple of 

commenters conveyed their concern 

that kidney transplant hospitals will use 

organ offer filters to have a better offer 

acceptance rate ratio, whereas kidney 

transplant hospitals that utilize 

marginal kidneys and try to have higher 

volumes will have worse performance 

for this ratio. They requested 

clarification on how CMS will prevent 

IOTA participants from being rewarded 

if they choose to use filters for this 

metric. Another commenter stated their 

concern that to achieve a better organ 

offer acceptance ratio, IOTA 

participants may inactivate patients, 

causing subsequent disadvantages. 

Additionally, a commenter was 

concerned that OPOs may start 

bypassing IOTA participants if they 

scrutinize whether the organ is an 

optimal match for a recipient. 

Response: We appreciate the 

commenters’ feedback and believe that 

organ offer filters are often an 

underutilized resource that help 

minimize organ non-use, out-ofsequence allocation, and prolonged cold 

ischemic times. Therefore, we disagree 

with the commenter views and 

encourage kidney transplant hospitals to 

use filters to reduce unnecessary offers 

to their transplant programs, when 

appropriate, for categories of offers that 

the transplant program will definitively 

not accept. We recognize this may be 

challenging due to high thresholds for 

marginal kidneys or different risk 

thresholds for different rotating 

surgeons in the same transplant 

program. However, we believe that 

given the rise in organ offers made by 

OPOs, there is opportunity to reduce 

administrative burden and organ nonuse, by way of using filters and 

impacting their organ offer acceptance 

rate. 

We acknowledge that there are some 

unique cases that are very high risk and 

require specific donor and recipient 

criteria, which may impact acceptance 

practices. We also acknowledge that it is 

unrealistic for kidney transplant 

hospitals to accept every offer they 

receive. 

If OPOs start bypassing IOTA 

participants due to in depth analysis of 

whether an organ is optimal for their 

patients, we believe this would be 

important model feedback for IOTA 

participants to relay to us. If analysis 

results warrant a new or updated policy, 

we will address it pursuant to future 

rulemaking. 

Comment: A commenter suggested 

CMS mandate the use of organ offer 

filters by a certain date. 

Response: We appreciate the 

commenter’s suggestion. Currently, we 

do not believe mandating organ filters is 

appropriate for the IOTA Model. While 

the performance domains and 

performance metrics in the IOTA Model 

do indirectly encourage use of organ 

offer filters, we believe IOTA 

participants should have the 

opportunity to identify what organ offer 

filters are appropriate for their 

transplant program and the populations 

they serve, as they participate. This is a 

topic for the entire transplant ecosystem 

to collectively consider in the future. 

Comment: A few commenters 

conveyed concerns that unique 

situations may impact post-transplant 

outcomes and impact acceptance rates. 

For example, a commenter stated that 

CMS should consider patient 

characteristics and how they impact a 

successful transplant. Another 

commenter is concerned that not all 

offers are viable. A commenter 

conveyed concern that filter settings for 

distance may conflict with allocation 

registered distance. For example, a 

kidney available in Alaska may show as 

local per UNOS assignment but will 

show as 2500 miles away from a kidney 

transplant hospital in Washington per 

filters, which would require liberal 

filters for distance, to capture donors in 

that region. 

Response: We appreciate the 

commenters bringing these concerns to 

our attention. We acknowledge that 

there are unique donor and recipient 

characteristics that may impact offer 

acceptances. We do not expect that any 

IOTA participant will accept every 

organ offer it receives since there are 

scenarios that are difficult to predict. 

We agree with the second commenter 

who stated that not all offers are viable 

and acknowledges this in section 

III.C.5.d.(1)(a), Table 6, where 

exclusions for the organ offer 

acceptance rate ratio metric are 

included. Kidney match runs that have 

no acceptances are excluded in this 

metric. 

We appreciate the commenter 

bringing UNOS and offer filter distance 

criteria mismatch to our attention. This 

was not considered at the time of the 

proposal of the IOTA Model. We plan to 

further discuss this internally and 

analyze how this can appropriately be 

accounted for in future performance 

years. 

Comment: A commenter requested 

that CMS consider how IOTA 

participants using organ offer filters 

prior to the model will be compared to 

IOTA participants that newly utilize 

organ offer filters and receive higher 

scores in the efficiency domain. 

Response: We appreciate the 

commenter’s feedback. The proposed 

organ offer acceptance rate ratio 

achievement scoring methodology is 

independent of pre-existing or new filter 

use and is strictly dependent on a ratio 

compared to national ranking. As 

mentioned in the comments noted 

previously in this section, we are 

finalizing our proposed achievement 

scoring methodology with slight 

modifications to reflect that points 

earned will be based on national 

ranking rather than a national target. 

Additionally, the organ offer acceptance 

rate ratio improvement scoring 

methodology has a ceiling of 15 points, 

which prevents IOTA participants that 

are new to using filters from having an 

unfair advantage over IOTA participants 

who previously utilized this resource. 

As mentioned in the comments noted 


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previously in this section, we are 

finalizing our proposed improvement 

scoring methodology to reflect that the 

maximum number of points awarded for 

improvement scoring is 15 points, rather 

than 12 points. 

Comment: A commenter encouraged 

CMS to consider that not all kidney 

transplant hospitals have the same 

capabilities, and this contradicts the 

achievement component of the 

efficiency domain since kidney 

transplant hospitals are not uniform. 

Response: We appreciate the 

commenter’s concerns and acknowledge 

the differences between kidney 

transplant hospitals but also believe that 

these unique variations create flexibility 

in how an IOTA participant may choose 

to adapt practice to impact their organ 

offer acceptance rate ratio. For those 

IOTA participants who prioritize 

improving their own score year-to year, 

the organ offer acceptance rate ratio 

improvement scoring methodology, as 

described in section III.C.5.d.(1).(b). of 

this final rule, allows them to earn 

points independent of comparison to 

other IOTA participants. 

Comment: A commenter relayed 

concern that keeping track of potential 

offers and acceptances is burdensome. 

Response: We appreciate the 

commenter’s feedback and will take this 

into consideration when planning for 

and implementing the IOTA Model in 

addition to identifying appropriate 

intervals for IOTA participants to have 

access to interim results. The IOTA 

Model does not mandate that IOTA 

participants keep track of their potential 

organ offers and acceptances but 

understands that IOTA participants may 

want to have access to this information 

for personal tracking purposes. 

Comment: A couple commenters 

expressed their support for CMS’ 

proposal to include the organ offer 

acceptance rate ratio as a performance 

measure in the efficiency domain. They 

contended that the organ offer 

acceptance rate ratio metric motivates 

kidney transplant hospitals to utilize 

filters that reflect their acceptance 

practices, while also providing the 

flexibility to modify these filters. 

Furthermore, they suggested that this 

metric would encourage increased 

acceptance rates. 

Response: We appreciate the support 

received from commenters for our 

proposal to include the organ offer 

acceptance rate ratio metric as a 

performance measure in the efficiency 

domain. 

After consideration of the public 

comments, for the reasons set forth in 

this rule, we are finalizing the proposed 

provisions for the point allocation and 

calculation methodology for efficiency 

domain scoring and scoring for organ 

offer acceptance rate ratio for the IOTA 

Model at § 512.426(c), with slight 

modifications. In the proposed rule at 

89 FR 43559, we proposed that 

achievement scoring points be awarded 

based on the national quintiles, as 

outlined in Table 6 of section 

III.C.5.d.(1).(b). of the proposed rule. As 

such, we are updating our regulation 

text at § 512.426(c)(2)(i) and in Table 1 

to Paragraph (c)(1)(i) at our regulation at 

§ 512.426 to remove reference to 

performance being measured against a 

national target and is instead based on 

national ranking. Additionally, we are 

updating the regulation text at 

§ 512.426(c)(1)(ii)(B)(1) to reflect 15 

points instead of 12 points and updating 

the multiplier in equation 1 to 

paragraph (c)(1)(ii)(B)(1) at § 512.426, as 

illustrated in Equation 4 in this section, 

to reflect 15 instead of 12. Lastly, we are 

updating our regulation text language at 

§ 512.402 to clarify our definition for 

improvement benchmark rate, which we 

modified to 120 percent of the IOTA 

participants’ performance on the organ 

offer acceptance rate ratio, as specified 

under § 512.426(c)(1)(ii)(A) rather than 

120 percent of the IOTA participants’ 

performance on organ offer acceptance 

rate ratio, as specified under 

§ 512.426(c)(1)(ii)(A). 

e. Quality Domain 

In the proposed rule, we proposed to 

define ‘‘quality domain’’ as the 

performance assessment category in 

which CMS assesses the IOTA 

participant’s performance using a 

performance measure and quality 

measure set focused on improving the 

quality of transplant care, as described 

in section III.C.5.e of the proposed rule 

and section III.C.5.e. of this final rule. 

We proposed that performance on the 

quality domain would be worth up to 20 

points out of the proposed 100 points. 

The quality domain is focused on 

monitoring post-transplant care and 

quality of life for IOTA transplant 

patients. 

In section III.C.5.e of the proposed 

rule, we stated that our goal for the 

quality domain within the IOTA Model 

is to achieve acceptable post-transplant 

outcomes while incentivizing increased 

kidney transplant volume. We believed 

that transplant hospital accountability 

for patient-centricity and clinical 

outcomes continues posttransplantation. While transplant 

outcomes have historically received the 

most attention, often at the exclusion of 

other factors, we sought to encourage a 

better balance in the system to offer the 

benefits of transplant to more patients. 

Therefore, we proposed to include one 

post-transplant outcome measure, as 

described in section III.C.5.e(1) of this 

final rule, and a quality measure set that 

includes two patient-reported outcomebased performance measures (PRO–PM) 

and one process measure, as described 

in section III.C.5.e(2) of this final rule. 

We sought comment on the proposed 

definition of the quality domain. 

We did not receive any comments on 

the proposed definition of the quality 

domain and are finalizing the proposed 

definition for quality domain at 

§ 512.402, with slight modification to 

remove the following words from the 

definition: and quality measure set. 

Since we are not finalizing our proposal 

to include our proposed quality measure 

set that includes two patient-reported 

outcome-based performance measures 

(PRO–PM) and one process measure, as 

described in the section III.C.5.e(2) of 

this final rule, we modified the quality 

domain definition and removed 

reference to the quality measure set. As 

such, we are also finalizing the general 

provisions for the quality domain as 

proposed, with a minor technical 

correction to update the cross reference 

in the regulation text at § 512.424(a). 

Specifically, we are removing the cross 

reference to the proposed quality 

measure set at § 512.424(a). We direct 

readers to section III.C.5.e(2) of this final 

rule for further discussion on our 

proposed quality measure set 

methodology. We are also finalizing our 

regulation as proposed without 

modification at § 512.424(b) that for 

each PY, CMS assesses each IOTA 

participant using the specified quality 

metrics. Lastly, we direct readers to 

section III.C.5.e(1) of this final rule for 

further discussion on our proposed 

post-transplant outcome measure. 

(1) Post-Transplant Outcomes 

In the proposed rule, we proposed 

using an unadjusted rolling ‘‘composite 

graft survival rate,’’ defined as the total 

number of functioning grafts relative to 

the total number of adult kidney 

transplants performed, as described in 

the proposed rule (89 FR 43518) and 

section III.C.5.e(1)(a) of this final rule, to 

assess IOTA participant performance on 

post-transplant outcomes. In this 

measure, the numerator (observed 

functioning grafts) and denominator 

(number of kidney transplants 

completed) would increase each PY of 

the IOTA Model to include a cumulative 

total. 

In section III.C.5.e(1) of the proposed 

rule, we stated that over the past few 

decades, advances in 

immunosuppressive therapies, surgical 

techniques, and organ preservation 


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Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96359 

239Stewart, D.E., Garcia, V.C., Rosendale, J.D., 

Klassen, D.K., & Carrico, B.J. (2017). Diagnosing the 

Decades-Long Rise in the Deceased Donor Kidney 

Discard Rate in the United States. Transplantation, 

101(3), 575–587. https://doi.org/10.1097/ 

tp.0000000000001539; Vinson, A., Kiberd, B.A., & 

Karthik Tennankore. (2021). In Search of a Better 

Outcome: Opting Into the Live Donor Paired Kidney 

Exchange Program. 8, 205435812110174– 

205435812110174. https://doi.org/10.1177/ 

20543581211017412; Shepherd, S., & Formica, R.N. 

(2021). Improving Transplant Program Performance 

Monitoring. 8(4), 293–300. https://doi.org/10.1007/ 

s40472-021-00344-z. 

240 Gioco, R., Sanfilippo, C., Veroux, P., Corona, 

D., Privitera, F., Brolese, A., Ciarleglio, F., 

Volpicelli, A., & Veroux, M. (2021). Abdominal wall 

complications after kidney transplantation: A 

clinical review. Clinical Transplantation, 35(12), 

e14506. https://doi.org/10.1111/ctr.14506; Wei, H., 

Guan, Z., Zhao, J., Zhang, W., Shi, H., Wang, W., 

Wang, J., Xiao, X., Niu, Y., & Shi, B. (2016). Physical 

Symptoms and Associated Factors in Chinese Renal 

Transplant Recipients. Transplantation 

Proceedings, 48(8), 2644–2649. https://doi.org/ 

10.1016/j.transproceed.2016.06.052; Mehrabi, A., 

Fonouni, H., Wente, M., Sadeghi, M., Eisenbach, C., 

Encke, J., Schmied, B.M., Libicher, M., Zeier, M., 

Weitz, J., Bu ̈ chler, M.W., & Schmidt, J. (2006). 

Wound complications following kidney and liver 

transplantation. Clinical Transplantation, 20(s17), 

97–110. https://doi.org/10.1111/j.1399- 

0012.2006.00608.x. 

241Medicare and Medicaid Programs; Regulatory 

Provisions To Promote Program Efficiency, 

Transparency, and Burden Reduction (September, 

20, 2018) https://www.federalregister.gov/ 

documents/2018/09/20/2018-19599/medicare-andmedicaid-programs-regulatory-provisions-topromote-program-efficiency-transparency-and. 

242Scientific Registry of Transplant Recipients. 

Request for Information. Requested on 05/02/2023. 

https://www.srtr.org/. 

243Mpsc-enhance-transplant-programperformance-monitoring-system_srtr-metrics.pdf. 

(n.d.). Retrieved December 28, 2022, from https:// 

optn.transplant.hrsa.gov/media/qfuj3osi/mpscenhance-transplant-program-performancemonitoring-system_srtr-metrics.pdf. 

methods have resulted in significant 

improvements in kidney transplantation 

outcomes.239 According to the OPTN, 

the overall 1-year survival rate for 

kidney transplantation recipients in the 

United States is over 90 percent, and the 

5-year survival rate is around 75 

percent. However, even with the 

advances that have been made to 

improve kidney outcomes, the success 

of kidney transplantation is still 

dependent upon factors such as the age 

and health of the donor and recipient, 

the presence of comorbidities (for 

example, diabetes), and the 

effectiveness of the immunosuppressive 

regimen. Kidney transplant outcomes 

can also be affected by possible posttransplant complications, including 

infection, cardiovascular disease, and 

kidney failure.240

More recently, CMS received feedback 

from transplant hospitals, patient 

advocacy groups, and transplant 

societies, including on the recent rule 

making (‘‘Medicare and Medicaid 

Programs; Regulatory Provisions To 

Promote Program Efficiency, 

Transparency, and Burden Reduction’’ 

(83 FR 47686)), that the 1-year measure 

was causing transplant centers to be risk 

averse about the patients and organs 

they would transplant while being 

simultaneously topped out (83 FR 

47706).241 Notably, even the lowest 

ranked programs, as measured by the 

SRTR, achieved a result of 90 percent of 

transplanted patients have a functioning 

graft at one year.242

To safeguard patient outcomes under 

the IOTA Model, we proposed to 

include this measure as a checkpoint 

(89 FR 43518). Because there is 

significant variation in post-transplant 

outcomes across kidney transplant 

hospitals, we believed the IOTA Model 

should promote improvement in 

outcomes for the benefit of attributed 

patients. We also believed that this 

measure would build upon, and 

complement, existing OPTN and SRTR 

measures to the maximum extent 

possible. Additionally, we believed that 

this approach could be applied with 

minimal adaptation to other organs were 

they to be added to the model through 

future rulemaking. Furthermore, we 

believed that this measure would 

enhance patient understanding of 

clinically important post-transplant 

outcomes beyond existing 90-day, 1- 

year and 3-year post transplant 

outcomes. 

We considered measuring posttransplant outcomes using SRTR’s 

methodology at 90 days,243 and 

constructing 5-year and 10-year posttransplant measures (89 FR 43518). 

However, we did not select these 

measures because post-transplant 

outcomes are already measured at 90- 

days by SRTR. Additionally, because 

the IOTA Model as proposed spans only 

6 years, we did not believe we could 

appropriately measure post-transplant 

outcomes at 5 or 10 years. 

We considered constructing an 

ongoing post-transplant outcome 

measure that would continuously 

evaluate post-transplant outcomes at 1- 

year throughout the model performance 

period of the IOTA Model. In this 

measure the numerator (observed graft 

failures) and denominator (number of 

transplants completed) would increase 

each PY of the model to a cumulative 

total (89 FR 43518). For example, in PY 

1 of the model an IOTA participant 

could have five 1-year observed graft 

failures and complete 20 transplants, 

resulting in a graft failure rate of 0.25. 

In PY 2 of the model, the same IOTA 

participant could have eight 1-year 

observed graft failures and complete 30 

transplants. To calculate the IOTA 

participant’s graft failure rate for PY 2 

of the model, we would divide the 

cumulative total of 13 1-year observed 

graft failures by the cumulative total of 

50 completed transplants. However, we 

felt it was important to measure posttransplant outcomes in terms of graft 

survival rather than in terms of graft 

failure. We acknowledged that for the 

purposes of measuring graft survival 

using OPTN data, use of either concept 

would generate the same outcome 

measurement because OPTN data 

identify graft status as either functioning 

or failed. However, we aim to convey 

the importance of ongoing management 

to preserve the health of the 

transplanted graft and the health and 

quality of life of the attributed patients. 

We considered constructing a 

continuous patient survival measure 

that would evaluate patient survival 

throughout the entirety of the IOTA 

Model (89 FR 43518). Similar to the 

considered measure mentioned in the 

previous paragraph, the numerator 

(number of patients alive) and 

denominator (number of received 

kidney organ offers) would increase 

each PY of the model to a cumulative 

total. For the denominator, we 

considered only including organ offers 

where the sequence number was less 

than 100 or less than 50. In other words, 

under that rationale we would only 

include offers that came within a certain 

point of time that could have potentially 

benefited the patient or should not have 

been turned down. We believed that this 

type of measure would not 

disincentivize waitlisting and could 

potentially increase equity within this 

population. Additionally, we believed 

that this type of measure would 

indirectly encourage living donor 

transplants because those would only 

hit the numerator (number of people 

alive) but not the denominator (number 

of kidney organ offers received). 

However, we felt that this measure 

would be somewhat duplicative of other 

parts of the model where we are already 

evaluating organ offer acceptance. We 

also chose not to propose this measure 

due to logistical concerns, and felt that 

it could be difficult to determine how 

many people were offered a specific 

organ and determining what an 

appropriate sequence number cutoff 

should be. 

We considered measuring estimated 

glomerular filtration rate (eGFR) at the 

1-year anniversary of the date of 

transplant (89 FR 43518). Glomerular 

filtration rate (GFR) is a way to assess 

renal function, and eGFR is the test used 

to assess renal function in primary 


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96360 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

244Mayne, T.J., Nordyke, R.J., Schold, J.D., Weir, 

M.R., & Mohan, S. (2021). Defining a minimal 

clinically meaningful difference in 12-month 

estimated glomerular filtration rate for clinical trials 

in deceased donor kidney transplantation. Clinical 

Transplantation, 35(7), e14326. https://doi.org/ 

10.1111/ctr.14326. 245 Ibid; Wu, J., Li, H., Huang, H., Wang, R., Wang, 

Y., He, Q., & Chen, J. (2010). Slope of changes in 

renal function in the first year post-transplantation 

and one-yr estimated glomerular filtration rate 

together predict long-term renal allograft survival. 

Clinical Transplantation, 24(6), 862–868. https://

doi.org/10.1111/j.1399-0012.2009.01186.x; Schold, 

J.D., Nordyke, R.J., Wu, Z., Corvino, F., Wang, W., 

& Mohan, S. (2022). Clinical events and renal 

function in the first year predict long-term kidney 

transplant survival. Kidney360, 10.34067/ 

KID.0007342021. https://doi.org/10.34067/ 

kid.0007342021; Hariharan, S., Mcbride, M.A., 

Cherikh, W.S., Tolleris, C.B., Bresnahan, B.A., & 

Johnson, C.P. (2002). Post-transplant renal function 

in the first year predicts long-term kidney 

transplant survival. Kidney International, 62(1), 

311–318. https://doi.org/10.1046/j.1523- 

1755.2002.00424.x. 

246Majerol, M., & Hughes, D.L. (2022, July 5). 

CMS Innovation Center Tackles Implicit Bias. 

Health Affairs. Retrieved January 16, 2024, from 

https://www.healthaffairs.org/content/forefront/ 

cms-innovation-center-tackles-implicit-bias. 

clinical care.244 Despite the fact that 

studies indicate eGFR’s potential as a 

reliable predictor of long-term posttransplant prognosis, our goal is to 

adopt a measure that resonates more 

with the transplant community’s 

evaluation of post-transplant 

outcomes.245 We recognized that the 

equation for calculating eGFR was 

revised in 2021 to not include race, but 

we still have some concerns over the 

potential for bias and inaccurate results 

and the limitations that still exist with 

the updated equation and did not 

believe it was appropriate to propose.246

We considered constructing several 

hospital-based post-transplant outcome 

measures such as those that measure: 

the number of days spent out of the 

hospital post-transplant, how many 

days spent at home post-transplant 

before returning to work, and number of 

hospital readmissions post-transplant 

(89 FR 43518). However, we do not 

want to penalize the use of moderate-tohigh KDPI kidneys, as we recognize that 

utilizing these organs carries an 

increased risk of transplant recipient 

hospitalizations. Additionally, we had 

concerns over how we would assess and 

measure this type of metric. 

We considered proposing a phased-in 

approach to measuring post-transplant 

outcomes, in which no post-transplant 

outcome metrics would be included 

until PY 3 of the model (89 FR 43518). 

In this alternative methodology, the 

quality domain for the first two PYs 

would only include our proposed 

quality measure set, as described in 

section III.C.5.e(2) of the proposed rule 

and this final rule. Starting PY 3 of the 

model, IOTA participants would be 

evaluated on two post-transplant 

outcome measures (SRTR’s 1-year posttransplant outcome conditional on 90- 

day survival measure and 3-year posttransplant outcome measure) in 

addition to our proposed quality 

measure set. This approach incorporates 

a time delay, allowing us to assess the 

post-transplant outcomes of IOTA 

participants using SRTR’s measures. 

Because we felt that it was critical to 

include a post-transplant measure from 

the onset of the model to check for 

unintended consequences throughout 

the entirety of the model performance 

period, we did not believe that this 

alternative was appropriate to propose. 

We also considered using SRTR’s new 

‘‘1-year post-transplant outcome 

conditional on 90-day graft survival’’ 

measure and including a 3-year posttransplant outcome measure, such as the 

one currently used by SRTR (89 FR 

43518). We also considered constructing 

our own 3-year post-transplant outcome 

measure conditional on 1-year survival. 

However we chose not to propose 

SRTR’s conditional 1-year or 3-year 

post-transplant outcome measures or 

our own measure for the following 

reasons: (1) because SRTR’s conditional 

1-year metric has a 2.5 year lookback 

period, it would require us to evaluate 

IOTA participants on post-transplant 

outcomes prior to starting the model for 

at least the first two PYs; (2) because 

SRTR does not currently have a 3-year 

conditional post-transplant outcome 

measure, we would not be in alignment 

with SRTR if we constructed our own; 

(3) including SRTR’s 3-year posttransplant outcome measure would 

include time outside of the model for at 

least the first three PYs and we want to 

evaluate IOTA participants based on 

their performance within the model; 

and (4) we recognize there may be some 

logistical issues and difficulty in 

measuring performance in that time. We 

may consider incorporating a 3-year 

post-transplant outcome measure into 

the model in the future, through 

rulemaking. 

We sought public comment on our 

proposal to evaluate IOTA participants 

on post-transplant outcomes using our 

new composite graft survival rate 

metric, as well as on the alternatives we 

considered. We were also interested in 

public comment on how we may be able 

to use OPTN data to characterize 

different clinical manifestations of graft 

survival, as we understand that not all 

surviving grafts are clinically equivalent 

or have the same impact on the patient 

and graft health. We were further 

interested to hear from the public on 

which factors involved in graft survival 

are modifiable by the care team. 

The following is a summary of the 

comments received on our proposal to 

evaluate IOTA participants on posttransplant outcomes using our new 

composite graft survival rate metric, as 

well as on the alternatives we 

considered and our responses: 

Comment: There were many 

commenters requesting CMS use 

alternative metrics for graft survival rate 

that include risk adjustment 

methodologies in place of the proposed 

composite graft survival rate. For 

example, a commenter suggests that 

CMS develop additional post-transplant 

outcome measures that could be utilized 

to measure the quality of care provided, 

surrogates for long term allograft 

function, in addition to early indicators 

for allograft function. This commenter 

additionally recommended measures of 

kidney function at 12 months or new 

onset albuminuria (for example, urine 

albumin to creatinine ratio [ACR]). A 

couple commenters that suggested that 

CMS reconsider using eGFR at 12 

months. Specifically, a commenter 

stated that, on a population level, the 

data suggests that eGFR at 12 months is 

predictive of long-term outcomes. 

Taking into consideration the dual goals 

of increasing organ utilization and 

patient outcomes, as well as outcomes 

that are superior to the dialysis, the 

same commenter recommended that an 

appropriate gauge of success in such a 

measure could be an eGFR superior to 

dialysis initiation or listing for retransplant (for example, greater than 20 

mL/min) such as 25 or 30 mL/min. 

Another commenter suggested that 

eGFR more accurately conveys longterm patient outcomes and 

incorporating granular measures of 

allograft function into performance 

metrics instead of using a binary 

(functioning/failed) indicator could 

improve patient care by prioritizing 

allograft function as a measure of 

program quality. 

Several commenters urged CMS to 

reconsider current SRTR outcome 

measures. For example, although a 

commenter agreed with CMS that it may 

not be possible to use SRTR’s 1-year 

graft survival conditional on 90-day 

survival or 3-year survival for short term 

evaluations of transplant program 

outcomes, they noted that SRTR has 

available models to assess 90-day 

outcomes along with the first full year 

posttransplant. The same commenter 

suggested that the 90-day models could 

be used to assess near-term success of 

the transplants in a risk-adjusted 

framework, and the full 1-year models 

could be used as the model develops 

and more performance years are 


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Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96361 

247Majerol, M., & Hughes, D.L. (2022, July 5). 

CMS Innovation Center Tackles Implicit Bias. 

Health Affairs. Retrieved January 16, 2024, from https://www.healthaffairs.org/content/forefront/ 

cms-innovation-center-tackles-implicit-bias. 

included to also incorporate risk 

adjustment into the evaluations. 

This commenter also stated that the 

90-day and 1-year models conditional 

on 90-day survival are currently used by 

the MPSC to evaluate transplant 

program outcomes. Therefore, they 

believed that not only is it feasible to 

use the 90-day and 1-year adjusted 

evaluations following the SRTR 

methodology, but it was also imperative 

to achieve the goals of the IOTA Model. 

Several commenters also urged CMS to 

use the outcomes already available from 

the SRTR, as it is well-established. 

Although the data is delayed, these 

commenters argued for CMS to include 

SRTR outcome measures citing reasons 

such as that it is well-established, 

accepted, and tested nationally and 

offers a comprehensive evaluation of 

graft survival that accounts for the 

complexities of both donors and 

recipients. A commenter believed CMS 

should remove the proposed measure 

and instead continue to use the existing 

SRTR post-transplant survival measures 

if CMS wants to increase the number of 

kidney transplants in part by 

encouraging kidney transplant hospitals 

to accept higher risk organs. This would 

also reduce the additional reporting 

burden associated with a new quality 

measure. Alternatively, a commenter 

suggested that CMS could utilize 

SRTR’s CUSUM data as it could provide 

more real-time measurements. 

Response: We thank the commenters 

for their suggestions on additional riskadjusted measures that could be 

considered for measuring posttransplant outcomes in the model. As 

described at 89 FR 43562 in the 

proposed rule, we considered measuring 

eGFR at the 1-year anniversary of the 

date of transplant. However, our goal is 

to adopt a measure that better resonates 

with the transplant community’s 

evaluation of post-transplant outcomes. 

As a result, we did not propose 

including eGFR at the 1-year 

anniversary. Additionally, we have 

ongoing concerns about potential bias, 

inaccurate results, and limitations with 

the updated eGFR equation. Given these 

issues, we did not believe it was 

appropriate to propose using eGFR at 

the 1-year mark.247

We also considered using SRTR’s 1- 

year graft survival conditional on 90-day 

survival or 3-year post-transplant 

outcome measure. However, for the 

reasons stated at 89 FR 43562 in the 

proposed rule, we chose not propose 

using SRTR’s 1-year graft survival 

conditional on 90-day survival or 3-year 

post-transplant outcome measure. As 

such, we will be finalizing our proposed 

composite graft survival rate metric to 

measure post-transplant outcomes in the 

IOTA Model. We will take into 

consideration the suggested posttransplant outcome metrics for IOTA 

and, if we determine that a new measure 

post-transplant outcome measure 

should be included, we would do so 

through future notice and comment 

rulemaking. 

Comment: A commenter opposed the 

proposed graft survival rate measure 

given that the transplant community 

already has statistically valid 

measurements for outcomes utilizing a 

rolling 2.5-year cohort. Thus, the 

commenter felt relying on a raw 

calculation was not a reasonable 

replacement. 

Response: We appreciate commenters 

recommendation to use an existing posttransplant outcome measure in place of 

the proposed composite graft survival 

rate. We will take the recommendation 

into consideration for future rulemaking 

and direct the commenter to comment 

responses noted previously in this 

section for further discussion on 

alternative metrics considered. 

Comment: Several commenters 

expressed support for using the 

unadjusted Composite Graft Survival 

Rate as proposed—notably, that the 

proposed unadjusted composite graft 

survival rate is simple and would be 

easy for the patients to understand. For 

example, a commenter reported that 

their kidney patients frequently 

expressed confusion about transplant 

data metrics and appreciated CMS’s 

efforts to establish a clearer measure for 

assessing graft survival. Furthermore, 

the commenter voiced support for using 

a graft survival metric rather than a graft 

failure metric, citing the reasons 

outlined in the proposed rule. A 

commenter also agreed with using this 

measure as a checkpoint to help ensure 

patient safety and improve 

understanding of post-transplant 

outcomes for patients. Another 

commenter concurred with CMS’s 

proposal to calculate post-transplant 

outcomes using a rolling, unadjusted, 

composite graft survival measure. 

Although they believed that many 

commenters would argue for an urgent 

need to add ‘‘risk adjustment’’ to the 

measure, they felt that the proposed 

measure had the virtues of being 

straightforward, unambiguous, easy to 

understand, and easy to explain to 

patients and their families. This same 

commenter also stated their belief that 

these virtues are, too often, 

underemphasized. 

Response: We thank the commenters 

for their support. 

After consideration of the public 

comments received, for the reasons set 

forth in this rule, we are finalizing our 

proposed provision to assess IOTA 

participant performance on posttransplant outcomes using the 

composite graft survival rate at 

§ 512.428(b)(1), without modification. 

We are also finalizing without 

modification the definition of composite 

graft survival rate at § 512.402. 

(a) Calculation of Metric 

In section III.C.5.e(1)(a) of the 

proposed rule, we proposed that for 

each model PY, CMS would calculate a 

composite graft survival rate for each 

IOTA participant, as defined and 

finalized in section III.C.5.e(1) of this 

final rule, to measure performance in 

the quality domain as described in 

section III.C.5.e. of this final rule. 

In section III.C.5.e(1)(a) of the 

proposed rule, we proposed to use our 

own unadjusted composite graft 

survival rate equation to evaluate posttransplant outcomes. We proposed to 

calculate the composite graft survival 

rate by taking the total number of 

functioning grafts an IOTA participant 

has and dividing that by the total 

number of kidney transplants furnished 

to patients 18 years of age or older at the 

time of the transplant in PY 1 and all 

subsequent PYs (see Equation 4) to 

evaluate post-transplant outcomes 

during the IOTA Model performance 

period. 

For example, as described in section 

III.C.5.e(1)(a) of the proposed rule, if in 

PY 1 of the model, an IOTA participant 

had 20 observed functioning grafts and 

furnished 25 kidney transplants to 

patients 18 years of age or older at the 

time of transplant, the composite graft 

survival rate for that IOTA participant 

would be 0.8 (20 from PY 1 divided by 

25 from PY 1). Continuing this example, 

for PY 2 of the model if the same IOTA 

participant had 30 observed functioning 

grafts and furnished 35 kidney 

transplants to patients 18 years of age or 

older at the time of transplant, and two 

functioning kidney grafts failed from PY 

1, CMS would calculate its composite 

graft survival rate for PY 2 as follows. 

CMS would divide the cumulative total 

of 48 observed functioning grafts (30 

from PY 2 + 20 from PY 1—2 from PY 

1) by the cumulative total of 60 

completed kidney transplants (35 from 

PY 2 + 25 from PY 1), resulting in a 


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248Technical Methods for the Program-Specific 

Reports. (n.d.). www.srtr.org. Retrieved December 3, 

2022, from https://www.srtr.org/about-the-data/ 

technical-methods-for-the-program-specificreports/; OPTN. (2022). OPTN Enhanced 

Transplant Program Performance Metrics. https://

optn.transplant.hrsa.gov/media/r5lmmgcl/mpsc_

performancemetrics_3242022b.pdf. 

249Technical Methods for the Program-Specific 

Reports. (n.d.). www.srtr.org. Retrieved December 3, 

2022, from https://www.srtr.org/about-the-data/ 

technical-methods-for-the-program-specificreports/. 

250https://unos.org/wp-content/uploads/AdultTRF-Kidney.pdf. 

251Zhang, R. (2017). Donor-Specific Antibodies in 

Kidney Transplant Recipients. Clinical Journal of 

the American Society of Nephrology, 13(1), 182– 

192. https://doi.org/10.2215/cjn.00700117. 

composite graft survival rate of 0.8 (48 

divided by 60). 

Equation 4: Composite Graft Survival 

Rate 

In the proposed equation, the 

numerator (number of functioning 

grafts) is defined as the total number of 

living adult kidney transplant patients 

with a functioning graft. The numerator, 

functioning grafts, would exclude grafts 

that have failed, as defined by SRTR. 

SRTR counts a graft as failed when 

follow-up information indicates that one 

of the following occurred before the 

reporting time point: (1) graft failure 

(except for heart and liver, when retransplant dates are used instead); (2) retransplant (for all transplants except 

heart-lung and lung); or 3) death.248

OPTN follow-up forms are used to 

identify graft failure and re-transplant 

dates.249 We also proposed to use OPTN 

adult kidney transplant recipient 

follow-up forms 250 to identify graft 

failure and re-transplant dates for all 

transplants furnished to kidney 

transplant patients 18 years of age or 

older at the time of the transplant. In the 

proposed equation, we noted that the 

numerator and denominator would not 

be limited to the attributed IOTA 

transplant patients. By this, we meant 

that it could include IOTA transplant 

patients who have been de-attributed 

from an IOTA participant due to 

transplant failure. We believed that 

IOTA participants could improve on 

this metric by working with IOTA 

collaborators to coordinate posttransplant care. 

We considered incorporating a risk 

adjustment methodology to our 

proposed composite graft survival 

equation, such as the one used by SRTR 

for 1-year post-transplant outcomes 

conditional on 90-day survival or 

constructing our own (89 FR 43518). 

While we recognized that risk 

adjustment methodologies may help 

account for patient and donor traits, we 

could not find a risk adjustment 

approach that has consensus agreement 

within the kidney transplant 

community. We also believed that our 

proposed measure is inherently risk 

adjusted as it only counts organs that 

are ultimately transplanted to patients 

18 years of age or older by a kidney 

transplant hospital. 

We invited public comment on our 

proposed methodology to calculate posttransplant outcomes in the IOTA Model, 

and on alternatives considered. 

Although we proposed an unadjusted 

composite graft survival rate to measure 

post-transplant outcomes, we were 

interested in comments on whether risk 

risk-adjustments are necessary, and 

which ones, such as donor demographic 

characteristics (i.e., race, gender, age, 

disease condition, geographic location), 

would be significant and clinically 

appropriate in the context of our 

proposed approach. 

The following is a summary of the 

comments received on our proposed 

methodology to calculate posttransplant outcomes in the IOTA Model, 

on whether risk risk-adjustments are 

necessary, and which ones, such as 

donor demographic characteristics (i.e., 

race, gender, age, disease condition, 

geographic location), would be 

significant and clinically appropriate in 

the context of our proposed approach, 

alternatives considered and our 

responses: 

Comment: Commenters expressed 

concern that the lack of risk adjustment 

in the proposed composite graft survival 

rate metric could have adverse 

consequences and would add additional 

administrative burden. Many 

commenters expressed concern that the 

unadjusted composite graft survival rate 

does not account for the clinical risk 

factors of the recipient or the donor, 

therefore, it may inadvertently lead to 

disparities in transplant by 

incentivizing participants to select 

healthier patients. For example, a 

commenter felt that the absence of risk 

adjustment in the IOTA Model was 

problematic and could be detrimental to 

patient care; stating that without 

accounting for the varying complexities 

of patients’ health conditions, hospitals 

might avoid referring higher-risk 

patients who could benefit most from 

transplants. Another commenter 

suggested that the lack of risk 

adjustment to the composite graft 

survival measure would incentivize 

IOTA participants to choose the 

healthiest patients to transplant and 

would reject those who are sensitized. 

Highly sensitized patients have high 

levels of anti-HLA antibodies, making 

them more likely to reject a kidney from 

a donor. These highly sensitized 

patients are more likely to be African 

American. This same commenter cited a 

study published in the Nephrology 

Dialysis Transplantation journal that 

found that highly sensitized kidney 

transplant recipients were more 

frequently African American compared 

to non-sensitized patients.251 Thus, the 

commenter believed that failure to riskadjust this measure could lead to 

outcomes that run counter to CMS’s 

stated desire to reduce disparities. A 

commenter believed that the inclusion 

of a post-transplant graft survival metric 

is innate and relevant to the IOTA 

Model. However, the commenter stated 

that one of the longstanding frustrations 

of transplant programs is that various 

regulatory bodies use different 

definitions and standards for graft 

survival. As proposed, this would 

represent another new definition and 

benchmarking system for kidney graft 

survival. The same commenter also 

found the lack of risk-adjustment 

concerning, as they would be taking on 

donor organs and recipients of 

progressively higher complexity, 

particularly for those programs that 

wish to pursue the greater-than-150 

percent volume target. 

Several commenters felt that the 

proposed measure misaligns with the 

model’s goal of increasing kidney 

transplants in a more complex 

population without risk adjusting for 

allograft and recipient factors. Without 

proper risk adjustment, these 

commenters suggested it could cause 

IOTA participants to be more risk averse 

with the types of organs they accept or 

disincentivizing IOTA participants from 

transplanting candidates who have a 

higher likelihood of graft failure, such as 

older candidates or those with more 

comorbid conditions. 


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Composite Graft Survival Rate 

# of Functioning Grafts 

# of Completed Kidney Transplants 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96363 

252CDC/ATSDR Social Vulnerability Index (CDC/ 

ATSDR SVI). (2024, June 14). cdc.gov. https://

www.atsdr.cdc.gov/placeandhealth/svi/index.html. 

253Poggio, E.D., Augustine, J.J., Arrigain, S., 

Brennan, D.C., & Schold, J.D. (2021). Long-term 

kidney transplant graft survival—Making progress 

when most needed. American Journal of 

Transplantation, 21(8). https://doi.org/10.1111/ 

ajt.16463; Meier-Kriesche, H.U., Schold, J.D., & 

Kaplan, B. (2004). Long-Term Renal Allograft 

Survival: Have we Made Significant Progress or is 

it Time to Rethink our Analytic and Therapeutic 

Strategies? American Journal of Transplantation, 

4(8), 1289–1295. https://doi.org/10.1111/j.1600- 

6143.2004.00515.x. 

Some commenters suggested specific 

donor and recipient characteristics that 

CMS should risk adjust for when 

calculating the proposed composite graft 

survival rate. For example, a commenter 

recommended that CMS risk adjust for 

how sick the patient is or the health of 

the kidney. Another commenter urged 

CMS to use SRTR’s risk adjustment 

methodology, as it undergoes regular 

testing and is updated annually. This 

commenter also stated that the current 

SRTR model recommends adjusting for 

both donor and recipient characteristics, 

including (1) donor and recipient 

demographic characteristics such as age, 

gender, and race, (2) donor and 

recipient clinical characteristics such as 

BMI, past behavior, medication history, 

and (3) history of certain conditions. A 

commenter suggested CMS consider 

risk-adjusting the composite graft rate 

using age, sex, major comorbidities, and 

neighborhood disadvantage index or 

similar (for example, CDC Social 

Vulnerability Index 252). Lastly, a 

commenter appreciated CMS’s emphasis 

on encouraging focus on post-transplant 

outcomes beyond the one- (and three-) 

year time horizon that currently receive 

the most focus. The commenter also 

broadly supported the proposed rolling 

composite graft survival metric as a 

mechanism to do so, and in particular, 

appreciated the simplicity of the 

proposed approach. However, they 

believed that CMS should risk-adjust for 

at least a small number of variables that 

would allow for a simple model that is 

understandable by including the biggest 

drivers for variation in outcomes and 

thereby disincentivize the creation of 

additional hurdles for more complex 

patients. For example, a model that 

includes age, ESRD vintage, and 

diabetes mellitus (y/n) the same 

commenter felt would leverage 

currently available data and remain 

easily measurable and understood. 

Response: We appreciate the concerns 

and suggestions from the commenters. 

We recognize the importance of 

providing a risk adjustment 

methodology, but we disagree with 

modifying how the composite graft 

survival rate, as proposed, is calculated 

for PY 1. As discussed in section 

III.C.5.e(1)(a) of this final rule, we 

proposed to include this measure as a 

checkpoint to safeguard patient 

outcomes under the IOTA Model and 

sought to convey the importance of 

ongoing management to preserve the 

health of the transplanted graft and the 

health and quality of life of the 

attributed patients. As discussed at 89 

FR 43536 in the proposed rule, 1-year 

post-transplant outcomes are markedly 

stable while long term post-transplant 

outcomes have historically been 

unchanged. In addition, research has 

shown that kidney transplant recipients, 

on average, experience one-year graft 

and patient survival rates above 95 

percent.253 As such, we believe the 

composite graft survival rate measure, as 

proposed, will reflect that for PY 1. We 

also maintain our belief that this 

measure would build upon, and 

complement, existing OPTN and SRTR 

measures to the maximum extent 

possible and enhance patient 

understanding of clinically important 

post-transplant outcomes beyond 

existing 90-day, 1-year and 3-year post 

transplant outcomes. 

In light of commenters suggestions, 

we considered finalizing a risk 

adjustment methodology that adjusted 

for donor age, recipient age and 

recipient diabetes. However, we do not 

believe that adjusting for these three 

alone are appropriate. Organ availability 

is affecting the kidney transplantation in 

its entirety, leading to transplant teams 

expanding the criteria for accepting 

organ donors. In these circumstances, 

we believe that analysis of the impact of 

the donor’s characteristics on graft 

survival becomes mandatory before 

incorporating a risk adjustment 

methodology. Additionally, given that 

the IOTA Model is 6 years, and the 

measure is rolling, we want to make 

sure that we continue discussions to 

ensure that this measure eventually 

includes a robust and appropriate risk 

adjustment methodology. Furthermore, 

we believe that the lack of risk 

adjustment for PY 1 will be minimal in 

terms of impacting IOTA participants 

scores and note that IOTA participants 

would not owe a downside risk 

payment in PY 1, as described and 

finalized in section III.C.6 of this final 

rule. 

Therefore, we will be finalizing our 

composite graft survival methodology, 

as proposed, to calculate post-transplant 

outcomes in the IOTA Model. However, 

in light of comments received, we will 

be stratifying the data from the 

composite graft survival rate measure 

and will work with stakeholders to 

inform a risk adjustment methodology 

for this measure and intend to address 

a new or updated policy pursuant to 

future notice and comment rule making. 

We also note that since we are not 

finalizing our proposed quality measure 

set or quality measure set scoring 

methodology, as described in sections 

III.C.5.e(2) and III.C.5.e(2)(e) of this final 

rule, and based on public comment, we 

will be modifying our proposed points 

allocation. We direct readers to section 

III.C.5.e(1)(b) for further discussion on 

the points allocation for the composite 

graft survival rate measure. 

Comment: Several commenters 

expressed concern over the proposed 

composite graft survival rate outcome 

measure. In particular, some 

commenters felt that the measure 

contradicts the primary objective of the 

IOTA Model, which is to increase the 

number of kidney transplants 

performed. For instance, a commenter 

believed that because this proposed 

measure would evaluate post-transplant 

outcomes during the IOTA Model 

performance period that the added 

requirement to provide six-year data 

detracts from what should be an 

unerring and resolute focus on 

increasing transplant volumes. A 

commenter also urged CMS to modify or 

remove this measure from the model in 

order for the model to succeed in 

achieving its primary objective. A 

couple commenters argued that this 

proposed measure would deter IOTA 

participants from transplanting lowerquality organs, which are significantly 

less likely to maintain function for six 

years post-transplant. Therefore, the 

commenters felt that the proposed 

outcome measure is inconsistent with 

the main objectives of the IOTA Model. 

Some commenters also shared that 

they felt collecting the data required for 

the proposed composite graft survival 

rate metric would add additional 

administrative burden for IOTA 

participants. Specifically, a commenter 

suggested that finalizing this measure as 

proposed would significantly increase 

the data collection burden on 

participating transplant programs, as no 

existing database contains six-year posttransplant graft function data. A 

commenter also argued that the 

proposed six-year outcome measure 

conflicts with the existing monitoring 

and reporting framework, and 

introducing a significant unfunded 

change would be illogical, as it is 

incongruent with the model’s strategic 

goals. A few commenters felt that this 

measure, as proposed, increases the 

time horizon for post-transplant graft 

survival accountability for transplant 


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programs that participate. They noted 

that after the first-year post-transplant, 

the recipient’s nephrologist, rather than 

the transplant facility, is primarily 

responsible for the patient’s ongoing 

care. Thus, they felt the six-year 

timeline was unreasonable, as it would 

hold transplant programs accountable 

for ensuring graft function long after the 

period for which they can be held 

responsible. 

Response: We thank commenters for 

their input and acknowledge their 

recommendations and concerns around 

the proposed composite graft survival 

rate. As mentioned in comment 

responses noted previously in this 

section, we will be finalizing the 

composite graft survival rate as 

proposed. However, we will take these 

insights and recommendations into 

consideration as we continue to assess 

our composite graft survival rate 

measure methodology and, if warranted, 

will propose a new or updated policy 

through future notice and comment 

rulemaking. We also note that in light of 

comments received, we intend to 

incorporate a risk adjustment 

methodology into our proposed 

approach for calculating post-transplant 

outcomes in the IOTA Model in future 

notice and comment rulemaking. 

Comment: Several commenters 

expressed support for using the 

unadjusted composite graft survival rate 

as proposed. 

Response: We thank the commenters 

for their support. We direct readers to 

section III.C.5.e(1)(a) of this final rule 

for the full discussion of the comments 

received in support of our proposed 

composite graft survival rate measure. 

After consideration of the public 

comments received, for the reasons set 

forth in this rule, we are finalizing the 

proposed provisions for calculating the 

composite graft survival rate as 

proposed at § 512.428(b)(1), without 

modification. While we are finalizing 

our provision for calculating the 

composite graft survival rate as 

proposed, we will be stratifying the data 

from the composite graft survival rate 

measure to inform a risk adjustment 

methodology for this measure and may 

consider future notice and comment 

rulemaking on this topic. 

(b) Calculation of Points 

As described in section III.C.5.e of the 

proposed rule, performance on the 

quality domain would be worth up to 20 

points. Within the quality domain, we 

proposed that the composite graft 

survival rate would account for 10 of the 

20 allocated points. We proposed that 

the points earned would be based on the 

IOTA participants’ performance on the 

composite graft survival rate metric 

ranked against a national target, 

inclusive of all eligible kidney 

transplant hospitals, both those selected 

and not selected as IOTA participants. 

We believe that using percentiles would 

create even buckets of scores among the 

continuum of IOTA participants. 

We proposed that points would be 

awarded based on the national quintiles, 

as outlined in Table 8, such that IOTA 

participants that perform— 

• At or above the 80th percentile 

would earn 10 points; 

• In the 60th percentile to below the 

80th percentile would earn 8 points; 

• In the 40th to below the 60th 

percentile would earn 5 points; 

• In the 20th percentile to below the 

40th percentile would earn 3 points; 

and 

• Below the 20th percentile would 

receive no points for the composite graft 

survival rate. 

Utilizing quintiles aligns with the 

calculation of the upside and downside 

risk payments in relation to the final 

performance score as detailed and 

finalized in section III.C.6.c(2) of this 

final rule, where average performance 

yields half the number of points. The 

scoring is normalized, meaning an 

average performing IOTA participant 

earns 5 points out of 10, or about 50 

percent of possible points. We recognize 

that there is an upper limit to the 

benefits of efficiency, and quintiles 

combine the highest 20 percent of 

performers in a point band. Due to the 

current disparity among kidney 

transplant hospitals, we do not expect 

every IOTA participant to reach toplevel performance on this metric. 

We considered a strategy similar to 

the proposed organ offer acceptance 

methodology which would apply a twoscoring system in which we would 

determine an achievement score and 

improvement score and award the point 

equivalent to the higher value between 

the two scores. We also considered 

proposing just an improvement score, in 

which we would evaluate IOTA 

participants’ performance on composite 

graft survival during a PY relative to 

their performance the previous CY. We 

considered both approaches because we 

recognize that if an IOTA participant 

does not do well one year in our 

proposed methodology, that it may be 

difficult for it to improve during the 

model performance period. However, 

we chose not to propose either of these 

other methodologies (achievement and 

improvement or just improvement 

scoring) because we had concerns over 

our ability to measure improvement 

year over year due to potentially small 

numbers. 

We sought public comment on the 

proposed point allocation and 

calculation methodology for posttransplant outcomes within the quality 

domain for the IOTA Model and 

alternatives considered. 

The following is a summary of the 

comments received on our proposed 

point allocation and calculation 

methodology for post-transplant 

outcomes within the quality domain for 

the IOTA Model and our responses: 

Comment: A few commenters 

expressed concern over the proposed 

points allocation. Specifically, a 

commenter indicated that, despite 

performing as expected on one-year 

outcomes, they would receive zero 

points based on the proposed points 

allocation, as the observed survival is 


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TABLE 8: COMPOSITE GRAFT SURVIVAL RATE SCORING 

goth Percentile :S 

60th :S and < goth Percentile g 

40th :S and < 60th Percentile 5 

20th :S and < 40th Percentile 3 

< 20th Percentile 0 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96365 

ranked low. The commenter attributed 

this to the transplant hospitals 

willingness to take on riskier waitlist 

patients and accept donors that other 

transplant hospitals may otherwise not. 

A commenter expressed concern that a 

small number of adverse scores could 

significantly skew a transplant 

hospital’s data. They argued that with 

the relatively low volume of transplants, 

just a few outlier scores could make it 

challenging to draw meaningful 

conclusions or implement impactful 

changes. As a result, the commenter 

believed these widely used quality 

metrics were better suited for evaluating 

large patient populations, such as in 

primary care settings. Lastly, a 

commenter also recommended that CMS 

adjust the eligibility to obtain maximum 

points downward in the composite graft 

survival rate points allocation. 

Specifically, the commenter suggested 

that full points be awarded to IOTA 

participants at the 60th percentile and 

above instead of the proposed 80th 

percentile and above. 

Response: We thank the commenters 

for raising concerns around the 

potential difficulties IOTA participants 

may face in achieving a top score on the 

composite graft survival rate metric. 

Regarding the concerns that a small 

number of adverse scores could 

significantly skew a transplant 

hospital’s data, we believe that is 

difficult for us to approach with so little 

data. However, we recognize there have 

been significant improvements in 

kidney transplantation outcomes over 

time due to advances in 

immunosuppressive therapies, surgical 

techniques, and organ preservation 

methods. We also recognize that posttransplant outcomes are already 

incentivized through private payers’ 

COE programs and OPTN metrics. 

Additionally, we acknowledge that 

IOTA participants will need time to 

establish relationships with IOTA 

collaborators, as described and finalized 

in section III.C.11.c of this final rule, 

and we want to allow time for those to 

be established. 

Thus, given this myriad of issues, and 

in light of public comment, we are 

finalizing an alternate scoring system for 

PY 1. Points will be awarded based on 

the national quintiles, as outlined in 

Table 9, such that IOTA participants 

that perform: 

• At or above the 80th percentile 

would earn 20 points; 

• In the 60th percentile to below the 

80th percentile would earn 18 points; 

• In the 40th percentile to below the 

60th percentile would earn 16 points; 

• In the 20th to below the 40th 

percentile would earn 14 points; 

• In the 10th to below the 20th 

percentile would earn 12 points; and 

• Below the 10th percentile would 

receive 10 points for the composite graft 

survival rate. 

We recognize that for PY 2 and future 

PYs there will be more events and a 

longer time horizon and plan to 

implement a more robust methodology 

that can account for both the likelihood 

of graft failure based on the donor and 

the recipient and can account for 

relative benefits of transplantation over 

remaining on dialysis. We will continue 

to assess our quality domain 

methodology and how to best balance 

incentives in the efficiency domain and 

quality domain and address a new or 

updated policy pursuant to future notice 

and comment rule making. 

Comment: A commenter expressed 

support for the proposed point 

allocation and calculation methodology 

for post-transplant outcomes within the 

quality domain for the IOTA Model. 

Response: We thank the commenter 

for their support. As mentioned in 

comment responses noted previously, 

since we are not finalizing our proposed 

quality measure set or quality measure 

set scoring methodology, as described in 

sections III.C.5.e(2) and III.C.5.e(2)(e) of 

this final rule, and based on public 

comment, we will be modifying our 

proposed points allocation, as 

illustrated in Table 9 in this section. We 

will continue to assess our quality 

domain methodology and how to best 

balance incentives in the efficiency 

domain and quality domain and address 

a new or updated policy pursuant to 

future notice and comment rule making 

and provide further specification based 

on commenters suggestions, if 

warranted. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

our proposed composite graft survival 

rate scoring methodology within the 

quality domain at § 512.428(d), as 

proposed with minor technical 

corrections to update language to reflect 

what we proposed at 89 FR 43518 of the 

proposed rule. Specifically, at 

§ 512.428(d) we are updating the 

language to reflect that CMS awards 

points to the IOTA participant based on 

the IOTA participant’s performance on 

the composite graft survival rate, as 

described in paragraph (b)(1) of this 

section, ranked nationally, inclusive of 

all eligible kidney transplant hospitals. 

We are also finalizing our proposal for 

the proposed point allocation for posttransplant outcomes within the quality 

domain for the IOTA Model with slight 

modifications. In section III.C.5.e(2)(e) 

of the proposed rule, we proposed that 

the IOTA participant would receive up 

to 10 points for performance on our 

three proposed measures within the 

quality domain while also noting in the 

proposed rule at 89 FR 43564, that if we 

finalized fewer measures, then we 

proposed to allocate the points 

accordingly within the remaining 

measures. We acknowledge that by not 

finalizing any of the proposed quality 

measures for inclusion in the quality 

measure set of the quality domain, as 

described in section III.C.5.e(2) of this 

final rule, there is a need to account for 


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TABLE 9: COMPOSITE GRAFT SURVIVAL RA TE SCORING 

80th Percentile :S: 20 

60th :s; and < 80th Percentile 18 

40th :S: and < 60th Percentile 16 

20th :s; and < 40th Percentile 14 

10th :s; and < 20th Percentile 12 

< 10th Percentile 10 
96366 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

254 collaboRATE. (2019). Glyn Elwyn. http://

www.glynelwyn.com/collaborate.html. 

255Colorectal Cancer Screening—NCQA. (2018). 

NCQA. https://www.ncqa.org/hedis/measures/ 

colorectal-cancer-screening/ https://www.ncqa.org/ 

hedis/measures/colorectal-cancer-screening/. 

256THE NATIONAL QUALITY FORUM 

Specifications for the Three-Item Care Transition 

Measure—CTM–3. (n.d.). Retrieved May 28, 2023, 

from https://mhdo.maine.gov/_pdf/NQF_CTM_3_

%20Specs_FINAL.pdf. 

257Supplemental Material to the CMS Measures 

Management System (MMS) Hub CMS ConsensusBased Entity (CBE) Endorsement and Maintenance. 

(2022). https://www.cms.gov/files/document/ 

blueprint-nqf-endorsement-maintenance.pdf. 

258 Jacobs, D.B., Schreiber, M., Seshamani, M., 

Tsai, D., Fowler, E., & Fleisher, L.A. (2023). 

Aligning quality measures across CMS—the 

Universal Foundation. New England Journal of 

Medicine, 388(9), 776–779. https://doi.org/10.1056/ 

nejmp2215539. 

259 Jacobs, D.B., Schreiber, M., Seshamani, M., 

Tsai, D., Fowler, E., & Fleisher, L.A. (2023). 

Aligning quality measures across CMS—the 

Universal Foundation. New England Journal of 

Medicine, 388(9), 776–779. https://doi.org/10.1056/ 

nejmp2215539. 

260Pre-Rulemaking | The Measures Management 

System. (n.d.). Mmshub.cms.gov. Retrieved May 12, 

2023, from https://mmshub.cms.gov/measurelifecycle/measure-implementation/pre-rulemaking/ 

overview. 

the points that we proposed to allocate 

to them, as described in section 

III.C.5.e(2)(e) of the preamble in this 

final rule. Therefore, we are finalizing 

our proposal with slight modification in 

Table 1 to paragraph (d) at our 

regulation at § 512.428(d) to allot a 

maximum of 20 points for performance 

on the composite graft survival rate 

measure. 

Additionally, after consideration of 

the public comments we received, we 

are also finalizing, with modification, 

Table 1 to paragraph (d) at § 512.428(d) 

to reflect the updated points allocation, 

such that IOTA participants that 

perform— 

• At or above the 80th percentile 

would earn 20 points; 

• In the 60th percentile to below the 

80th percentile would earn 18 points; 

• In the 40th percentile to below the 

60th percentile would earn 16 points; 

• In the 20th to below the 40th 

percentile would earn 14 points; 

• In the 10th to below the 20th 

percentile would earn 12 points; and 

• Below the 10th percentile would 

receive 10 points for the composite graft 

survival rate. 

(2) Quality Measure Set 

In section III.C.5.e(2) of the proposed 

rule, we proposed to select and use 

quality measures to assess IOTA 

participant performance in the quality 

domain. Performance on the proposed 

IOTA Model quality measure set would 

be used to assess the performance of an 

IOTA participant on aspects of care that 

we believe contribute to a holistic and 

patient-centered journey to receiving a 

kidney transplant. 

In section III.C.5.e(2) of the proposed 

rule, we proposed the following three 

measures for inclusion in the IOTA 

Model quality measure set: (1) 

CollaboRATE Shared Decision-Making 

Score (CBE ID:3327), (2) Colorectal 

Cancer Screening (COL) (CBE ID: 0034), 

and (3) the 3-Item Care Transition 

Measure (CTM–3) (CBE ID: 

0228).254 255 256 The quality measures 

that we proposed share common 

features. We proposed measures that 

have been or are currently endorsed by 

the CMS Consensus-Entity (CBE) 

through the CMS Consensus-Based 

Process. This ensures that the measures 

proposed have been assessed against 

established evaluation criteria of 

importance, acceptability of measure 

properties, feasibility, usability, and 

competing measures.257 Our proposed 

measure set is patient-centered, 

reflecting areas that we have heard from 

patients are important and for which 

there is significant variation in 

performance among transplant 

hospitals. We proposed measures that 

would incentivize improvements in care 

that we would otherwise not expect to 

improve based on the financial 

incentives in the model alone. We are 

also proposing a measure set that would 

allow us to make a comprehensive 

assessment of post-transplant outcomes. 

The composite graft survival rate that 

we proposed in section III.C.5.e(1) of the 

proposed rule and this final rule would 

provide an essential, albeit limited, 

assessment of the success of a kidney 

transplant. Finally, we proposed 

measures that we believe would 

incentivize improvement in aspects of 

post-transplant care that are important 

to patients and modifiable by IOTA 

participants. 

We stated in the proposed rule at 

section III.C.5.e(2) that on March 2, 

2023, Jacobs et al. published Aligning 

Quality Measures across CMS—The 

Universal Foundation, which describes 

CMS leadership’s vision for a set of 

foundational quality measures known as 

the Universal Foundation. This measure 

set would be used by as many CMS 

value-based and quality programs as 

possible, with other measures added 

based on the population or healthcare 

setting.258 CMS selected measures for 

the Universal Foundation that are 

meaningful to a broad population, 

reduce burden by aligning measures, 

advance equity, support automatic and 

digital reporting, and have minimal 

unintended consequences.259

We considered only including two 

measures in the initial quality measure 

set and pre-measure development 

because we were concerned about the 

potential added reporting burden placed 

on IOTA participants (89 FR 43518). 

However, we chose to propose three 

measures and pre-measure development 

because we want to use them to 

incentivize and improve patient care. 

We sought additional feedback on 

which of the proposed measures have 

the highest potential to impact changes 

in behavior, while minimizing provider 

burden. 

We also considered only including 

COL in the quality measure set and 

allotting this measure 4 points, with the 

remaining 16 points allotted to the 

composite graft survival rate (89 FR 

43518). It is worth noting that if we 

choose fewer measures, then we 

proposed allocating the points 

accordingly within the remaining 

measures. 

We considered several alternative 

measures for the quality domain 

performance assessment (89 FR 43518). 

We considered the Hospital Consumer 

Assessment of Healthcare Providers and 

Systems (HCAHPS) survey because 

hospitals are already required to report 

that survey in the Hospital VBP 

Program, thereby reducing or limiting 

burden to IOTA participants burden 

since it is already in use. We did not 

propose the HCAHPS measure for the 

IOTA Model because HCAHPS data is 

based on survey results from a random 

sample of adult patients across medical 

conditions. We believe that the 

HCAHPS would present sample size 

issues for purposes of calculation. 

We considered the Gains in Patient 

Activation Measure (PAM®) (CBE ID: 

2483) (89 FR 43518). The PAM®

measure is being used in the voluntary 

KCC Model and was included on the 

2022 Measures Under Consideration 

(MUC) List for the ESRD Quality 

Incentive Program (QIP) and MIPS.260

We considered whether the PAM®

Measure could encourage IOTA 

participants and IOTA Collaborators, as 

defined and finalized in section 

III.C.11.d of this final rule, to activate 

IOTA waitlist patients to work in 

collaboration with IOTA participants to 

complete requirements to maintain 

active waitlist status; however, we were 

unable to locate any peer-reviewed 

literature to support this hypothesis. 

As described in section III.C.5.e(2) of 

the proposed rule, we also considered 

the Depression Remission at 12 Months 

measure (CBE ID: 0710e). Studies have 

shown that depression and anxiety are 

common amongst people on dialysis 

and suggested that incorporating patient 

reported outcome measures (PROs) that 


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261Feroze, U., Martin, D., Kalantar-Zadeh, K., 

Kim, J.C., Reina-Patton, A., & Kopple, J.D. (2012). 

Anxiety and depression in maintenance dialysis 

patients: Preliminary data of a cross-sectional study 

and brief literature review. Journal of Renal 

Nutrition, 22(1), 207–210. https://doi.org/10.1053/ 

j.jrn.2011.10.009; Mclaren, S., Jhamb, M., & Unruh, 

M. (2021). Using Patient-Reported Measures to 

Improve Outcomes in Kidney Disease. Blood 

Purification, 1–6. https://doi.org/10.1159/ 

000515640; Cukor, D., Donahue, S., Tummalapalli, 

S.L., Bohmart, A., & Silberzweig, J. (2022). Anxiety, 

comorbid depression, and dialysis symptom 

burden. Clinical Journal of the American Society of 

Nephrology, 17(8), 1216–1217. https://doi.org/ 

10.2215/cjn.01210122. 

262Chen, X., Chu, N.M., Basyal, P.S., Vihokrut, 

W., Crews, D., Brennan, D.C., Andrews, S.R., 

Vannorsdall, T.D., Segev, D.L., & McAdamsDeMarco, M.A. (2022). Depressive symptoms at 

kidney transplant evaluation and access to the 

kidney transplant waitlist. Kidney International 

Reports, 7(6), 1306–1317. https://doi.org/10.1016/ 

j.ekir.2022.03.008. 

263Tong, A., Hanson, C.S., Chapman, J.R., 

Halleck, F., Budde, K., Josephson, M.A., & Craig, 

J.C. (2015). ‘suspended in a paradox’—patient 

attitudes to wait-listing for Kidney Transplantation: 

Systematic review and thematic synthesis of 

qualitative studies. Transplant International, 28(7), 

771–787. https://doi.org/10.1111/tri.12575. 

264 Ibid. 

265CMS ESRD Measures Manual for the 2023 

Performance Period. (2022). https://www.cms.gov/ 

files/document/esrd-measures-manual-v81.pdf. 

266Cukor, D., Donahue, S., Tummalapalli, S.L., 

Bohmart, A., & Silberzweig, J. (2022). Anxiety, 

comorbid depression, and dialysis symptom 

burden. Clinical Journal of the American Society of 

Nephrology, 17(8), 1216–1217. https://doi.org/ 

10.2215/cjn.01210122. 

267 Jacobs, D.B., Schreiber, M., Seshamani, M., 

Tsai, D., Fowler, E., & Fleisher, L.A. (2023). 

Aligning quality measures across CMS—the 

Universal Foundation. New England Journal of 

Medicine, 388(9), 776–779. https://doi.org/10.1056/ 

nejmp2215539. 

268Szeifert, L., Bragg-Gresham, J.L., Thumma, J., 

Gillespie, B.W., Mucsi, I., Robinson, B.M., Pisoni, 

R.L., Disney, A., Combe, C., & Port, F.K. (2011). 

Psychosocial variables are associated with being 

wait-listed, but not with receiving a kidney 

transplant in the dialysis outcomes and Practice 

Patterns Study (dopps). Nephrology Dialysis 

Transplantation, 27(5), 2107–2113. https://doi.org/ 

10.1093/ndt/gfr568; Chen, X., Chu, N.M., Basyal, 

P.S., Vihokrut, W., Crews, D., Brennan, D.C., 

Andrews, S.R., Vannorsdall, T.D., Segev, D.L., & 

McAdams-DeMarco, M.A. (2022). Depressive 

symptoms at kidney transplant evaluation and 

access to the kidney transplant waitlist. Kidney 

International Reports, 7(6), 1306–1317. https://

doi.org/10.1016/j.ekir.2022.03.008. 

focus on depression can improve healthrelated quality of life in patients with 

ESRD.261 One study found that, at the 

time of kidney evaluation, over 85 

percent of patients exhibited at least 

minimal depressive symptoms and that 

patients with depressive symptoms 

were less likely to gain access to the 

waitlist.262 Although the waitlist offers 

some hope to patients, being waitlisted 

for a kidney transplant is also 

psychologically distressing, with 

patients reporting disillusionment, 

moral distress, unmet expectations, 

increasing vulnerability, and 

deprivation.263 These factors are likely 

contributors to high rates of stress and 

anxiety observed among waitlisted 

patients.264 The conditions of 

participation (CoPs) for transplant 

hospitals require that prospective 

transplant candidates receive a 

psychosocial evaluation prior to 

placement on a waitlist (42 CFR 

482.90(a)(1)), if possible, and OPTN 

bylaws specify that transplant hospitals 

must include team members to 

coordinate a transplant candidate’s 

psychosocial needs; however, neither 

the CoP nor the OPTN bylaws require 

specific assessment of, or intervention 

into, patients’ behavioral health. The 

ESRD QIP measure set includes the 

Clinical Depression Screening and 

Follow-Up measure; however, 

performance on the measure requires 

only documentation that an attempt at 

screening and follow up was made.265

Additionally, this measure is already 

being used in the KCC Model. 

We stated in the proposed rule that 

while we understand the importance of 

including measures focused on 

depression, we believe that IOTA 

participants may have limited 

experience diagnosing and treating 

depression and may struggle to make 

referrals due to limited behavioral 

health providers (89 FR 43518). We also 

believe that this measure may be 

duplicative with other policies in this 

model that strive to improve the health 

and post-transplant outcomes of 

attributed patients. Additionally, based 

on the KCC Model experience, the 

Depression Remission measure is 

operationally complex due to the 10- 

month reporting period and novel 

collection and reporting processes. We 

believe that IOTA participants would 

experience similar challenges due to the 

mandatory nature of the model and 

unfamiliarity with reporting quality 

measure data to the Innovation Center. 

In section III.C.5.e(2) of the proposed 

rule, we considered the Depression 

Remission at 12 Months measure (CBE 

ID: 0710e) because major depression is 

prevalent in the dialysis population and 

most kidney transplant recipients spend 

some time on a dialysis modality.266

Depression measures are included in the 

Universal Foundation because 

successfully treating depression can 

improve physical health outcomes, in 

addition to behavioral health 

outcomes.267 A depression measure 

would align with the behavioral health 

domain of Meaningful Measures 2.0. We 

considered a depression remission 

measure over a depression screening 

measure because we believed a 

depression remission measure would 

incentivize IOTA participants to work 

with the other clinicians and providers 

involved in the care of attributed 

patients to resolve or improve the 

depressive symptoms rather than only 

identifying them. Our review of the 

literature found that presence of 

behavioral health symptoms affected the 

ability of patients to get on the kidney 

transplant waiting list, but did not affect 

likelihood of receiving a kidney 

transplant.268 We did not propose the 

Depression Remission at 12 Months 

Measure because we were unable to 

locate any publications that found 

depression remission affected access to 

a kidney transplant. We also chose not 

to propose this type of measure because 

the IOTA Model does not target prewaitlist patients for attribution to model 

participants. We also believe that IOTA 

participants may have limited 

experience in diagnosis and treating 

depression and may struggle to make 

referrals due to limited behavioral 

health providers. Additionally, 

behavioral health management is not 

under the purview of a kidney 

transplant hospital that might see a 

kidney transplant waitlist patient 

perhaps only a handful of times, but 

may be more appropriate for the 

patient’s nephrologist or dialysis center. 

We sought comment on our proposed 

quality measure set that includes two 

PRO–PMs (CollaboRATE Shared 

Decision-Making Score and 3-Item Care 

Transition Measure) and one process 

measure (Colorectal Cancer Screening) 

for purposes of measuring performance 

in the quality domain. We also sought 

comment on alternative quality 

measures considered. 

The following is a summary of the 

comments received on our proposed 

quality measure set that includes two 

PRO–PMs (CollaboRATE Shared 

Decision-Making Score and 3-Item Care 

Transition Measure) and one process 

measure (Colorectal Cancer Screening) 

for purposes of measuring performance 

in the quality domain and alternative 

quality measures considered and our 

responses: 

Comment: We received many 

responses from commenters who did 

not agree with the proposed quality 

measure set that includes two PRO–PMs 

(CollaboRATE Shared Decision-Making 

Score and 3-Item Care Transition 

Measure) and one process measure 

(Colorectal Cancer Screening), as 

described in the preamble of this final 

rule, in the IOTA Model and highlight 

several reasons. Commenters stated that 

the proposed measures have not been 


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developed, validated, or evaluated for 

use in this patient population and 

expressed uncertainty to how effective 

they would be in the model. A few 

commenters noted that the 

CollaboRATE Shared Decision-Making 

measure and CTM–3 are not currently 

being utilized by transplant hospitals 

and lack any evidence base for use in 

kidney transplantation or in patients 

with CKD and ESRD. Thus, including 

PRO–PMs without any convincing 

evidence base for efficacy could be 

counterproductive and discourage 

support for PRO measurements 

generally. Additionally, because the 

proposed quality measures are not 

currently used in any CMS program, a 

commenter anticipated that IOTA 

participants would face additional costs 

to implement these new requirements. 

Response: We thank commenters for 

expressing their concerns with the 

proposed quality measures. While we 

recognize that the CollaboRATE 

measure, COL and CTM–3 are not 

specific to transplantation, we believe 

they are helpful measures for assessing 

hospital quality and performance for the 

reasons set forth in sections 

III.C.5.e(2)(b), (c), and (d) of this final 

rule. However, in response to public 

comments, we will not be finalizing our 

proposed quality measure set that 

includes two PRO–PMs (CollaboRATE 

Shared Decision-Making Score and 3- 

Item Care Transition Measure) and one 

process measure (Colorectal Cancer 

Screening) at this time. 

Comment: A commenter agreed with 

the importance of assessing both 

patient’s level of SDM and readiness for 

self-care at the time of discharge but did 

not support the use of patient report 

survey-based measures. The commenter 

suspected that adding another survey 

would likely result in low response 

rates and survey fatigue. Patients are 

already overwhelmed by the numerous 

surveys from hospitals, doctors, dialysis 

centers, and post-acute care providers. 

Additionally, the commenter argued 

that transplant patients, who already 

face significant demands on their time 

and energy, would likely not prioritize 

completing survey measures. 

Response: We appreciate the 

commenters’ concerns regarding the use 

of patient-report survey measures, but 

we disagree. Chronic kidney disease is 

complex and demands thorough 

medical management, even after 

transplantation. Thus, when taking into 

consideration the lasting impact of CKD, 

symptom burden and its correlation to 

mental health and psychosocial 

difficulties, we believe it is essential 

that we understand the entirety of the 

patient experience and take steps to 

improve it using the policy levers 

available in the IOTA Model. We 

maintain that failure to address what is 

important to patients could result in 

continued, or the development of, 

decreased quality of life in addition to 

psychosocial distress, increased 

symptom burden and new physical 

problems or both to arise and be left 

untreated. We also acknowledge that it 

is equally important that any PROM 

included be relevant to the population 

being measured. To date, there are not 

only no kidney transplant specific PROs 

that are endorsed by NQF but there also 

remains a shortage of kidney transplant 

specific validated measures. However, 

given commenters concerns, we are 

persuaded not to finalize our proposed 

quality measure set that includes two 

PRO–PMs (CollaboRATE Shared 

Decision-Making Score and 3-Item Care 

Transition Measure) and one process 

measure (Colorectal Cancer Screening) 

at this time. We still believe in the 

importance of using validated, personcentered, measures of quality of care to 

support a holistic and patient-centered 

kidney transplant process, but 

acknowledge the challenges presented 

by commenters in the proposed quality 

measures set. We intend to propose 

additional quality measures which may 

include a focus on health-related quality 

of life (HRQoL) for kidney transplant 

recipients or address pre-transplant 

processes of care through future notice 

and comment rule making. We believe 

these measures will support the goals of 

the IOTA Model to improve quality and 

equity of care. In the interim, we have 

been convinced the other requirements 

that enforce SDM in the pre-transplant 

process (for example, Transplant 

Hospitals’ CoP) are adequate and 

mitigate the challenges posed by the 

proposed measures. Although we are 

not finalizing any of the proposed 

measures in our quality measure set, we 

think that the IOTA Model promotes 

SDM through some of our other policies, 

such as the proposed transparency 

requirements as described and finalized 

in section III.C.8(a) of the preamble in 

this final rule. 

Comment: Some commenters 

encouraged CMS to include the PAM®

in the IOTA Model. A couple 

commenters noted that while the PAM®

is not validated for use in 

transplantation it would serve as 

continuity with other models. A few 

commenters acknowledged that we 

considered whether the PAM® Measure 

could encourage IOTA participants and 

IOTA Collaborators, as defined at 

§ 512.402 of the proposed rule, to 

activate IOTA waitlist patients to work 

in collaboration with IOTA participants 

to complete requirements to maintain 

active waitlist status; however, we were 

unable to locate any peer-reviewed 

literature to support this hypothesis. 

One of these commenters recommended 

that CMS reevaluate possible inclusion 

of the PAM in the IOTA Model quality 

measure set after the public release of 

data on the PAM® use in the voluntary 

KCC Model. While a couple commenters 

disagreed with CMS, suggesting that 

there was ample evidence to support the 

inclusion of PAM® in the IOTA Model. 

Specifically, they asserted that the 

PAM® is well established, in use, valid 

and reliable across the kidney care 

journey, including specific peer 

reviewed studies on the proposed IOTA 

population. Moreover, they asserted that 

the evidence demonstrates the crucial 

importance of patient activation for 

patients diagnosed with CKD, 

particularly within the transplant 

population. Furthermore, the findings 

suggest that clinical teams could have a 

profound impact on supporting the 

main objectives of the IOTA Model. 

Response: We appreciate the 

suggestion from commenters to include 

the PAM® in the IOTA Model and will 

consider the suggestion for future 

rulemaking, where appropriate. Given 

the concerns raised by commenters 

about participant burden associated 

with PRO–PMs, including PAM®, we 

are not proposing to add it at this time. 

Rather, as mentioned in comment 

responses noted previously, we will 

consider future PRO–PMs use in the 

model. 

Comment: Many commenters 

suggested alternative measures that the 

IOTA Model should include in place of 

those proposed quality measure set. For 

example, a commenter recommended 

that CMS consider implementing 

stronger quality protections during the 

first two years of the model; suggesting 

that this could include assessing 

performance on additional process 

measures that reflect appropriate care 

delivery, rather than relying solely on 

pay-for-reporting. To align with the 

updates to the Hospital Consumer 

Assessment of Healthcare Providers and 

Systems (HCAHPS) survey, a 

commenter suggested that CMS should 

replace the retired CTM–3 measure with 

the proposed ‘‘Care Coordination’’ SubMeasure. 

Several commenters suggested that 

CMS include more specific health 

screening measures in place of the COL. 

For example, a commenter stated that 

colon cancer rates are similar between 

kidney transplant and non-transplant 

patients. Whereas skin cancer has a 

much higher prevalence in transplant 


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patients compared to non-transplant 

patients. Thus, they suggested that there 

would be more value in creating a skin 

cancer measure. The commenter also 

mentioned that they contemplated 

suggesting that CMS consider using a 

vaccination rate measure in place of the 

COL, since being current on 

vaccinations is more directly relevant to 

transplant candidate readiness and 

transplant recipient well-being 

regardless of age than colorectal cancer 

screening. However, they suggested that 

vaccination rates could present an 

evolving challenge for IOTA 

participants to achieve given the 

growing skepticism of vaccinations in 

the post-COVID–19 pandemic era. The 

same commenter also believed that 

many programs exclude individuals 

who refuse vaccinations who would 

otherwise be good transplant 

candidates, and such a metric could 

further encourage the exclusion of these 

patients. A couple of commenters 

suggested that addressing posttransplant cardiovascular risk factors 

could lead to better long-term outcomes. 

This is because multiple adverse cardiac 

events are more common causes of 

death than cancer or infection after 

transplant, noting that nearly 25 percent 

of deaths in the first-year posttransplant are related to cardiovascular 

reasons. Therefore, the commenters 

recommended that CMS include 

measures to screen for post-transplant 

diabetes mellitus and manage 

hyperlipidemia. 

A few commenters mentioned that 

CMS should include the Hemoglobin 

A1c poor control (≤9%) (CBE #0559) 

and Advance Care Plan (CBE #0326) 

measures to the quality domain to align 

with the Universal Measures. A 

commenter suggested that the Advance 

Care Plan and CollaboRATE score align 

with the program’s other measures, 

collectively upholding a high standard 

of care for transplant patients. 

Specifically, the commenter proposed 

that the Advance Care Plan and 

CollaboRATE score could work together 

to facilitate a comprehensive, patientinformed decision-making process. 

Another commenter encouraged CMS to 

consider the 15-item Care Transition 

Measure (CTM–15), proposing that it 

could facilitate a better understanding of 

post-transplant expectations for patients 

due to its incorporation of components 

like a written care plan and a list of 

scheduled appointments. 

Response: We would like to thank all 

commenters that closely reviewed and 

shared their suggestions for with the 

IOTA Model proposed quality measures, 

and recognize the efforts made by 

commenters to align measures relevant 

to the target population and to align to 

the Universal Foundation, a key CMS 

priority. We are committed to including 

quality measures in the IOTA quality 

domain to further the model goals for 

improving quality of care and 

supporting a holistic, patient-centered 

kidney transplant process. Responsive 

to comments, we will not be finalizing 

our proposed quality measure set that 

includes two PRO–PMs (CollaboRATE 

Shared Decision-Making Score and 3- 

Item Care Transition Measure) and one 

process measure (Colorectal Cancer 

Screening). We will consider future 

measures aligned to the priority areas of 

the kidney transplant process and will 

align, where possible, with CMS 

priorities and other CMS programs. 

Comment: Numerous commenters 

expressed concerns about the proposed 

quality measure reporting requirements. 

They cited challenges with data 

collection, administrative burden, and 

unfamiliarity with the measures; 

ultimately suggesting that the data 

collected would not justify the added 

administrative burden. For example, a 

commenter stated that if patients are 

attributed to multiple transplant 

hospitals, collecting quality measures 

data on the entire attributed population 

could be duplicative and burdensome. 

The same commenter also believed that 

allowing for quality measures to change 

each PY that it would cause confusion 

and lost revenue, and that more 

consideration should be put into the 

process for data collections so that it 

does not unduly burden programs in a 

way that compromises clinical 

outcomes and organ transplant access. A 

commenter stated that SDM and patient 

involvement in transplant care, as well 

as patient autonomy, are respected and 

assessed in the evaluation process but 

do not directly support the goal of 

improving patient outcomes. Thus, they 

felt that the that administering the 

CollaboRATE Shared Decision-Making 

Score and CTM–3 would cause 

unnecessary administrative burden. 

Another commenter expressed their 

belief that administering and 

documenting the CollaboRATE Shared 

Decision-Making Score and CTM–3 

would be laborious due to the volume 

of patients on the waitlist and 

questioned how this would be 

accomplished in a consistent manner. 

Response: We appreciate and 

acknowledge the commenters’ concern 

and challenges with the proposed 

quality measures. We recognize the 

difficulties associated with patient 

reported outcome measures and the 

underlying data collection tools used in 

a clinical domain. At this point, as 

mentioned in comment responses noted 

previously, we are not finalizing any of 

the three quality measures that we 

proposed. In the future we plan to 

propose additional quality measures 

which may include a focus on HRQoL 

for kidney transplant recipients or 

address pre-transplant processes of care. 

We suggest these measures would 

support the goals of the IOTA Model to 

improve quality and equity of care and 

acknowledge the burden of data 

collection in measures using EHR or 

survey data. However, it is a CMS 

priority to incorporate person-centered 

measures, including patient-reported 

measures, where possible. We will 

continue to consider EHR reporting 

challenges when selecting quality 

measures to account for future 

performance and intends to propose 

new quality measures for inclusion in 

the IOTA Model through future notice 

and comment rulemaking. 

Comment: A few commenters 

supported the inclusion of patientreported outcome (PRO) measures in the 

IOTA Model. For example, a commenter 

believed that including PROs is 

essential for evaluating the quality of 

care and patient satisfaction but 

believed that the quality measure set 

scoring methodology, as described at 

§ 512.428(e) of the proposed rule could 

inaccurately reflect the quality of care or 

patient satisfaction and lacked 

transparency and consistency; 

suggesting that it could cause 

discrepancies in evaluating IOTA 

participant performance. A commenter 

strongly supported the use of quality 

measures to evaluate transparency and 

SDM. This commenter also voiced their 

belief that the proposed quality measure 

was good because it did not 

significantly increase administrative 

burden but thought the measures’ 

simplicity might limit their ability to 

provide meaningful insights into the 

quality of care these patients receive. 

Another commenter voiced their 

appreciation for CMS’s inclusion of 

PROMs in the IOTA Model. The same 

commenter agreed that increasing 

patient involvement in the kidney 

transplant process is a critical objective 

but expressed concern over the 

inclusion of CollaboRATE and CTM–3. 

Specifically, the commenter felt that 

administering and documenting these 

measures, which have not been 

validated for this specific patient 

population, would increase burden on 

both IOTA participants and its 

attributed patients, without improving 

quality of care. 

Response: We thank the commenters 

for expressing their support. We agree 

that when taking into consideration the 

lasting impact of CKD, symptom 


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269Schick-Makaroff, K., Thummapol, O., 

Thompson, S., Flynn, R., Karimi-Dehkordi, M., 

Klarenbach, S., Sawatzky, R., & Greenhalgh, J. 

(2019). Strategies for incorporating patient-reported 

outcomes in the care of people with chronic kidney 

disease (PRO kidney): a protocol for a realist 

synthesis. Systematic Reviews, 8(1). https://doi.org/ 

10.1186/s13643-018-0911-6; Brett, K.E., Ritchie, 

L.J., Ertel, E., Bennett, A., & Knoll, G.A. (2018). 

Quality Metrics in Solid Organ Transplantation. 

Transplantation, 102(7), e308–e330. https://doi.org/ 

10.1097/tp.0000000000002149; Mendu, M.L., 

Tummalapalli, S.L., Lentine, K.L., Erickson, K.F., 

Lew, S.Q., Liu, F., Gould, E., Somers, M., Garimella, 

P.S., O’Neil, T., White, D.L., Meyer, R., Bieber, S.D., 

& Weiner, D.E. (2020). Measuring Quality in Kidney 

Care: An Evaluation of Existing Quality Metrics and 

Approach to Facilitating Improvements in Care 

Delivery. Journal of the American Society of 

Nephrology, 31(3), 602–614. https://doi.org/ 

10.1681/ASN.2019090869; Tang, E., Bansal, A., 

Novak, M., & Mucsi, I. (2018). Patient-Reported 

Outcomes in Patients with Chronic Kidney Disease 

and Kidney Transplant—Part 1. Frontiers in 

Medicine, 4. https://doi.org/10.3389/ 

fmed.2017.00254; Anderson, N.E., Calvert, M., 

Cockwell, P., Dutton, M., Aiyegbusi, O.L., & Kyte, 

D. (2018). Using patient-reported outcome measures 

(PROMs) to promote quality of care in the 

management of patients with established kidney 

disease requiring treatment with haemodialysis in 

the UK (PROM–HD): a qualitative study protocol. 

BMJ Open, 8(10), e021532. https://doi.org/10.1136/ 

bmjopen-2018-021532. 

270 Ibid. 

burden, and its correlation to mental 

health and psychosocial difficulties, it is 

important that the patient perspective 

and voice be included through the use 

of patient-reported outcome measures 

(PROMs) to truly grasp how CKD 

impacts their lives.269 As described at 

89 FR 43603 in the proposed rule, we 

also recognize that in spite of the 

growing recognition over the past two 

decades that this is paramount to 

advancing the quality of care at both the 

patient and policy levels, there remains 

significant information gaps in 

understanding how PROMs are, and can 

be utilized across different domains, 

especially within nephrology to enrich 

patient-centered care, and measure 

other important quality components, 

such as access to transplantation, 

shared-decision making and quality of 

life post-transplantation, to provide a 

comprehensive understanding.270

However, given commenters concerns, 

we are persuaded not to finalize the 

three quality measures proposed for 

inclusion in the IOTA Model at this 

time. It is a CMS priority to incorporate 

person-centered measures, including 

patient-reported measures, where 

possible and CMS believes in the 

importance of elevating patient’s voice 

in their care. We plan, in future notice 

and comment rulemaking, to propose 

additional quality measures which may 

include a focus on HRQoL for kidney 

transplant recipients or address pretransplant processes of care. We suggest 

these measures will support the goals of 

the IOTA Model to improve quality and 

equity of care. 

Comment: Lastly, many commenters 

urged CMS to focus on new measure 

development and collaborate with 

stakeholders, clinicians, and patients to 

develop meaningful quality measures in 

this space that can be validated in this 

setting. For example, many commenters 

encouraged CMS to eliminate the 

proposed quality measure and pursue 

new measure development. These 

commenters also stated that it is critical 

that CMS include all relevant 

stakeholders when developing new 

measures to ensure that any new 

measure is appropriate, reliable, and 

representative of the diverse patient 

population. A commenter appreciated 

CMS’s interest in developing a PROM 

pertaining to HRQoL in the context of 

kidney transplant especially given the 

relative paucity of measures of quality 

of care for kidney transplant; nothing 

that no validated PROMs of quality of 

life currently exist, much less any 

PROMs that are appropriate for use in 

the IOTA Model. A commenter strongly 

supported the development of a HRQoL 

PROM and suggested CMS invest in 

developing a measure(s) along these 

lines for inclusion in the IOTA Model 

as soon as possible. Some commenters 

voiced their belief that CMS should 

work with relevant stakeholders and 

focus on, and invest, in new measure 

development, provided it is rigorously 

tested and developed using the highest 

standards. One of these commenters 

suggested that it be used as a reporting 

measure initially before rewarding 

performance against quality 

performance benchmarks and should 

assess SDM about patient-focused risk 

tolerance regarding organ offer quality. 

Response: We acknowledge 

commenters suggestions for CMS to 

focus on new measure development for 

use in the IOTA Model, including 

support for a future PROM related to 

HRQoL for kidney transplant recipients. 

Appropriately evaluating the change in 

quality of care is an essential goal of the 

IOTA Model and we will consider 

future measure development, 

potentially in the areas of HRQoL and 

pre-transplant processes of care. 

After considering public comments, 

for the reasons set forth in this rule, we 

are not finalizing our proposed quality 

measure set that includes two PRO–PMs 

(CollaboRATE Shared Decision-Making 

Score and 3-Item Care Transition 

Measure) and one process measure 

(Colorectal Cancer Screening) for 

purposes of measuring performance in 

the quality domain at this time. We 

continue to note that quality of care is 

an important element of the IOTA 

Model, and we will be monitoring 

quality through other care delivery 

requirements and through the required 

independent evaluation of the model. 

We also will continue to evaluate the 

changing inventory of quality measures, 

considering public input, and have 

already begun developing new measures 

more clinically and setting appropriate. 

Because of the uncertain nature of 

timing of developing new quality 

measures we will not specify a timeline 

for incorporation but may in future 

rulemaking. 

(a) Quality Measure Set Selection, 

Reporting and Changes 

In section III.C.5.e(2) of the proposed 

rule, we proposed that CMS select and 

use quality measures to assess IOTA 

participant performance in the quality 

domain. We proposed that each PY, 

IOTA participants would be required to 

report quality measure data during 

survey and reporting windows to CMS 

in a form and manner, and at times, 

established by CMS. We also proposed 

that, where applicable, IOTA 

participants would be required to 

administer any surveys or screenings 

relevant to the quality measures selected 

for inclusion in the IOTA Model to 

attributed patients. We proposed to 

define ‘‘survey and reporting windows’’ 

as two distinct periods where IOTA 

participants would be required to 

administer a quality measure-related 

survey or screening to attributed 

patients or submit attributed patient 

responses to CMS pursuant to 

§ 512.48(b)(2)(ii). We proposed that 

CMS would notify, in a form and 

manner as determined by CMS, IOTA 

participants of the survey and reporting 

window for applicable quality measures 

by the first day of each PY. 

In section III.C.5.e(2)(a) of the 

proposed rule, we proposed that CMS 

would use future rulemaking to make 

substantiative updates to the 

specifications of any of the quality 

measures in the IOTA Model. 

Additionally, we proposed that the 

quality measures finalized for inclusion 

in the IOTA Model would remain in the 

quality measure set unless CMS, 

through future rulemaking, removed or 

replaced them. 

In section III.C.5.e(2)(a) of the 

proposed rule, we proposed that CMS 

could remove or replace a quality 

measure based on one of the following 

factors: 

• A quality measure does not align 

with current clinical guidelines or 

practice. 

• Performance on a quality measure 

among IOTA participants is so high and 

unvarying that meaningful distinctions 


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Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96371 

and improvement in performance can 

no longer be made (‘‘topped out’’ 

measure), as defined in 42 CFR 

412.140(g)(3)(i)(A). 

• Performance or improvement on a 

quality measure does not result in better 

patient outcomes. 

• The availability of a more broadly 

applicable quality measure (across 

settings or populations) or the 

availability of a quality measure that is 

more proximal in time to desired patient 

outcomes for the particular topic. 

• The availability of a quality 

measure that is more strongly associated 

with desired patient outcomes for the 

particular topic. 

• Collection or public reporting of a 

quality measure leads to negative 

unintended consequences other than 

patient harm. 

• It is not feasible to implement the 

quality measure specifications. 

• The costs associated with a quality 

measure outweigh the benefit of its 

continued use in the IOTA Model. 

In section III.C.5.e(2)(a) of the 

proposed rule, we proposed that CMS 

would assess the benefits of removing or 

replacing a quality measure from the 

IOTA Model on a case-by-case basis. We 

proposed that CMS would use the future 

rulemaking process to add, remove, 

suspend, or replace quality measures in 

the IOTA Model to allow for public 

comment, unless a quality measure 

raises specific safety concerns. We 

proposed that if CMS determines that 

the continued requirement for IOTA 

participants to submit data on a quality 

measure raises specific patient safety 

concerns, CMS could elect to 

immediately remove the quality 

measure from the IOTA Model quality 

measure set. Finally, we proposed that 

CMS would, upon removal of a quality 

measure, and in a form and manner 

determined by CMS, do the following: 

• Provide notice to IOTA participants 

and the public at the time CMS removes 

the quality measure, along with a 

statement of the specific patient safety 

concerns that would be raised if IOTA 

participants continued to submit data 

on the quality measure. 

• Provide notice of the removal in the 

Federal Register. 

We sought comment on the 

requirement that IOTA participants 

report quality measure data to CMS. We 

additionally sought comment on our 

proposed process for adding, removing, 

or replacing quality measures in the 

IOTA Model. 

The following is a summary of the 

comments received on our proposal to 

require that IOTA participants report 

quality measure data to CMS and our 

proposed process for adding, removing, 

or replacing quality measure in the 

IOTA Model and our responses: 

Comment: Several commenters felt 

that more consideration should be put 

into the process for data collection and 

reporting requirements so that it does 

not unduly burden IOTA participants in 

a way that could compromise clinical 

outcomes and transplant access. A 

commenter felt that CMS’s proposed 

rule lacked key logistical details 

necessary to understand how IOTA 

participants would collect the required 

quality measures and how CMS would 

evaluate them. Specifically, the 

proposed rule did not specify what 

patient information IOTA participants 

must collect and report alongside the 

measure results, nor whether hospitals 

should provide patient-level or 

aggregate data. 

Response: We understand the need for 

IOTA participants understand any 

quality measure set survey and 

reporting requirements finalized for 

inclusion in the IOTA Model. 

Additionally, we acknowledge the 

importance of, are committed to, 

providing key logistical details, where 

warranted, to mitigate administrative 

burdens for IOTA participants. As 

discussed in section III.C.5.e(2) of this 

final rule, we are not finalizing our 

proposed quality measure set. We 

intend to propose new quality measures 

for inclusion in the IOTA Model in 

future notice and comment rule making. 

As such, we will not be finalizing our 

proposed quality measure set survey 

and reporting requirements at 

§ 512.428(b)(2)(ii), our proposed process 

for adding, removing or replacing a 

quality measure at § 512.428(b)(3) or the 

definition of survey and reporting 

windows at § 512.402 as described in 

the proposed rule. While we are not 

finalizing any of the aforementioned 

provisions, we will continue to assess 

our quality measure data reporting 

requirement and policy for adding, 

removing, or replacing quality measures 

in the IOTA Model and intend to 

address a new or updated policy 

pursuant to future notice and comment 

rule making. 

Comment: A commenter urged CMS 

to allow greater flexibility in the 

proposed survey and reporting 

timelines, as discussed in section 

III.C.5.e(2)(a) of this final rule, for IOTA 

participants and recommended that 

CMS allow IOTA participants to adjust 

data collection processes to align with 

clinical schedules and patient 

preference. They noted that by allowing 

for greater flexibility that this would 

enable them to collect patient data in 

alignment with clinical practice for preand post-transplant appointments and 

prevent potential operational challenges 

if or when a survey and reporting 

window misaligns. 

Response: We appreciate the 

commenters’ suggestion. As discussed 

in section III.C.5.e(2) of this final rule, 

we are not finalizing our proposed 

quality measure set. We intend to 

propose new quality measures for 

inclusion in the IOTA Model in future 

notice and comment rule making. As 

such, we will not be finalizing our 

proposed quality measure set survey 

and reporting requirements at 

§ 512.428(b)(2)(ii), our proposed process 

for adding, removing or replacing a 

quality measure at § 512.428(b)(3) or the 

definition of survey and reporting 

windows at § 512.402 as described in 

the proposed rule. While we are not 

finalizing any of the provisions 

proposed in section III.C.5.e(2) of the 

proposed rule, we will take into 

consideration the commenter’s 

recommendation to allow for greater 

flexibility during survey and reporting 

windows and continue to assess our 

quality measure data reporting 

requirement and policy for adding, 

removing, or replacing quality measures 

in the IOTA Model. We note that we 

will continue to assess our quality 

measure data reporting requirement and 

policy for adding, removing, or 

replacing quality measures in the IOTA 

Model and intend to address a new or 

updated policy pursuant to future notice 

and comment rule making. 

Comment: A commenter noted that in 

the proposed rule we proposed that if 

performance on a quality measure 

among IOTA participants is so high and 

unvarying that meaningful distinctions 

and improvement in performance can 

no longer be made (‘‘topped out’’ 

measure), as defined in 42 CFR 

412.140(g)(3)(i)(A) that CMS could 

remove or replace that quality measure 

(89 FR 43518). They requested that CMS 

provide further detail on the proposed 

CMS review process and timeline for 

evaluating if ‘‘topping out’’ or other 

criteria has occurred. They also felt that 

while case-by-case adjustments may be 

appropriate when specific concerns 

arise, an ad hoc evaluation process risks 

overlooking instances where quality 

measures fall short of the established 

criteria. 

Response: We appreciate the 

commenters’ suggestion. As discussed 

in section III.C.5.e(2) of this final rule, 

we are not finalizing our proposed 

quality measure set. We intend to 

propose new quality measures for 

inclusion in the IOTA Model in future 

notice and comment rule making. As 

such, we will not be finalizing any of 

the provisions proposed in section 


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96372 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

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Noyes, J. (2023). Understanding people’s decisions 

when choosing or declining a kidney transplant: a 

qualitative evidence synthesis. BMJ Open, 13(8), 

e071348. https://doi.org/10.1136/bmjopen-2022- 

071348; Stephenson, M.D., & Bradshaw, W. (2018). 

Shared decision making in chronic kidney disease. 

Renal Society of Australasia Journal, 14(1), 26. 

https://www.proquest.com/scholarly-journals/ 

shared-decision-making-chronic-kidney-disease/ 

docview/2283078287/se-2; Gordon, E.J., Butt, Z., 

Jensen, S.E., Lok-Ming Lehr, A., Franklin, J., Becker, 

Y., Sherman, L., Chon, W.J., Beauvais, N., 

Hanneman, J., Penrod, D., Ison, M.G., & Abecassis, 

M.M. (2013). Opportunities for Shared Decision 

Making in Kidney Transplantation. American 

Journal of Transplantation, 13(5), 1149–1158. 

https://doi.org/10.1111/ajt.12195; Salter, M.L., 

Babak Orandi, McAdams-DeMarco, M.A., Law, A., 

Meoni, L.A., Jaar, B.G., Sozio, S.M., Hong, W., 

Parekh, R.S., & Segev, D.L. (2014). Patient- and 

Provider-Reported Information about 

Transplantation and Subsequent Waitlisting. 

Journal of the American Society of Nephrology, 

25(12), 2871–2877. https://doi.org/10.1681/ 

asn.2013121298; Schold, J.D., Huml, A.M., Poggio, 

E.D., Reese, P.P., & Mohan, S. (2022). A tool for 

decision-making in kidney transplant candidates 

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transplantation in the United States. Kidney 

International. https://doi.org/10.1016/ 

j.kint.2022.05.025; Schaffhausen, C.R., Bruin, M.J., 

McKinney, W.T., Snyder, J.J., Matas, A.J., Kasiske, 

B.L., & Israni, A.K. (2019). How patients choose 

kidney transplant centers: A qualitative study of 

patient experiences. 33(5), e13523–e13523. https:// 

doi.org/10.1111/ctr.13523; Hart, A., Bruin, M., Chu, 

S., Matas, A., Partin, M.R., & Israni, A.K. (2019). 

Decision support needs of kidney transplant 

candidates regarding the deceased donor waiting 

list: A qualitative study and conceptual framework. 

Clinical Transplantation, 33(5), e13530. https://

doi.org/10.1111/ctr.13530; S. Ali Husain, Brennan, 

C., Michelson, A., Tsapepas, D., Patzer, R.E., 

Schold, J.D., & Mohan, S. (2018). Patients prioritize 

waitlist over posttransplant outcomes when 

evaluating kidney transplant centers. 18(11), 2781– 

2790. https://doi.org/10.1111/ajt.14985; Patzer, 

R.E., McPherson, L., Basu, M., Mohan, S., Wolf, M., 

Chiles, M., Russell, A., Gander, J.C., Friedewald, J.J., 

Ladner, D., Larsen, C.P., Pearson, T., & Pastan, S. 

(2018). Effect of the iChoose Kidney decision aid in 

improving knowledge about treatment options 

among transplant candidates: A randomized 

controlled trial. American Journal of 

Transplantation: Official Journal of the American 

Society of Transplantation and the American 

Society of Transplant Surgeons, 18(8), 1954–1965. 

https://doi.org/10.1111/ajt.14693. 

272Stephenson, M. Stephenson, M. Stephenson, 

M. Stephenson, M.D., & Bradshaw, W. (2018). 

Shared decision making in chronic kidney disease. 

Renal Society of Australasia Journal, 14(1), 26. 

https://www.proquest.com/scholarly-journals/ 

shared-decision-making-chronic-kidney-disease/ 

docview/2283078287/se-2; Gordon, E. J., Butt, Z., 

Jensen, S.E., Lok-Ming Lehr, A., Franklin, J., Becker, 

Y., Sherman, L., Chon, W.J., Beauvais, N., 

Hanneman, J., Penrod, D., Ison, M.G., & Abecassis, 

M.M. (2013). Opportunities for Shared Decision 

Making in Kidney Transplantation. American 

Journal of Transplantation, 13(5), 1149–1158. 

https://doi.org/10.1111/ajt.12195; Schold, J.D., 

Huml, A.M., Poggio, E.D., Reese, P.P., & Mohan, S. 

(2022). A tool for decision-making in kidney 

transplant candidates with poor prognosis to 

receive deceased donor transplantation in the 

United States. Kidney International. https://doi.org/ 

10.1016/j.kint.2022.05.025; Schaffhausen, C.R., 

Bruin, M.J., McKinney, W.T., Snyder, J.J., Matas, 

A.J., Kasiske, B.L., & Israni, A.K. (2019). How 

patients choose kidney transplant centers: A 

qualitative study of patient experiences. 33(5), 

e13523–e13523. https://doi.org/10.1111/ctr.13523; 

Hart, A., Bruin, M., Chu, S., Matas, A., Partin, M.R., 

& Israni, A.K. (2019). Decision support needs of 

kidney transplant candidates regarding the 

deceased donor waiting list: A qualitative study and 

conceptual framework. Clinical Transplantation, 

33(5), e13530. https://doi.org/10.1111/ctr.13530; 

Patzer, R.E., McPherson, L., Basu, M., Mohan, S., 

Wolf, M., Chiles, M., Russell, A., Gander, J.C., 

Friedewald, J.J., Ladner, D., Larsen, C.P., Pearson, 

T., & Pastan, S. (2018). Effect of the iChoose Kidney 

decision aid in improving knowledge about 

treatment options among transplant candidates: A 

randomized controlled trial. American Journal of 

Transplantation: Official Journal of the American 

Society of Transplantation and the American 

Society of Transplant Surgeons, 18(8), 1954–1965. 

https://doi.org/10.1111/ajt.14693. 

273 Kucirka, L.M., Grams, M.E., Balhara, K.S., Jaar, 

B.G., & Segev, D.L. (2011). Disparities in Provision 

of Transplant Information Affect Access to Kidney 

Transplantation. American Journal of 

Transplantation, 12(2), 351–357. https://doi.org/ 

10.1111/j.1600-6143.2011.03865.x; Patzer, R.E., 

Retzloff, S., Buford, J., Gander, J., Browne, T., Jones, 

H., Ellis, M., Canavan, K., Berlin, A., Mulloy, L., 

Gibney, E., Sauls, L., Muench, D., Reeves-Daniel, 

A., Zayas, C., DuBay, D., Mutell, R., & Pastan, S.O. 

(2021). Community Engagement to Improve Equity 

in Kidney Transplantation from the Ground Up: the 

Southeastern Kidney Transplant Coalition. Current 

Transplantation Reports, 8(4), 324–332. https://

doi.org/10.1007/s40472-021-00346-x; Schold, J.D., 

Huml, A.M., Poggio, E.D., Reese, P.P., & Mohan, S. 

(2022). A tool for decision-making in kidney 

transplant candidates with poor prognosis to 

III.C.5.e(2)(a) of the proposed rule. 

While we are not finalizing any of these 

proposed provisions, we will take into 

consideration the commenter’s request 

to provide further specificity to our 

application of measure removal factors 

and continue to assess our quality 

measure data reporting requirement and 

policy for adding, removing, or 

replacing quality measures in the IOTA 

Model. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are not 

finalizing our policy for adding, 

removing, or replacing quality measures 

in the IOTA Model, as proposed at 

§ 512.428(b)(2) of the proposed rule. 

Additionally, because we are not 

finalizing any of the quality measures 

we proposed, as described and finalized 

in section III.C.5.e(2) of this final rule, 

we are not finalizing our proposed 

provision requiring IOTA participants to 

report quality measure data to CMS at 

§ 512.428(b)(2)(ii) or the definition of 

survey and reporting windows at 

§ 512.402 as described in the proposed 

rule. While we are not finalizing any of 

these proposed provisions, we will 

continue to assess our quality measure 

data reporting requirement and policy 

for adding, removing, or replacing 

quality measures in the IOTA Model 

and address a new or updated policy 

pursuant to future notice and comment 

rule making. 

(b) CollaboRATE Shared DecisionMaking Score 

In section III.C.5.e(2)(b) of the 

proposed rule, we stated that the 

CollaboRATE Shared Decision-Making 

Score is a patient-reported measure of 

shared decision-making. The measure 

provides a performance score 

representing the percentage of adults 18 

years of age and older who experience 

a high degree of shared decision 

making. The CollaboRATE Shared 

Decision-Making Score is based on three 

questions that assess the degree to 

which effort was made to inform the 

patient of his or her health issues, to 

listen to the patient’s priorities, and the 

extent to which the patient’s priorities 

were included in determining next 

steps. The measure is generic and 

applies to all clinical encounters, 

irrespective of the condition or the 

patient group. We proposed that IOTA 

participants would be required to 

administer the CollaboRATE Shared 

Decision-Making Score to attributed 

patients once per PY, at minimum, and 

report quality measure data to CMS 

during survey and reporting windows, 

as defined in section III.C.5.e(2)(a) of the 

proposed rule, that would be 

established by CMS. 

In section III.C.5.e(2)(b) of the 

proposed, we stated that we believed 

incentivizing shared decision-making is 

critical to ensuring the model centers 

the patient experience and treatment 

choice to meet the IOTA desired goals 

of improving equity, increasing the 

number of kidney transplants, and 

reducing kidney non-utilization. 

Patients needing a kidney transplant 

often face many challenges when 

making healthcare decisions, as they 

must first decide between treatment 

options (such as dialysis versus 

transplantation, living donor versus 

deceased-donor transplantation) and 

where they wish to be evaluated for 

transplantation. Research findings 

demonstrate the importance and impact 

of shared decision-making throughout 

the entire transplant process for patients 

because of the types of complex 

decisions they must make, and the 

dynamic factors involved in each 

patient’s decision.271 Research studies 

have found that shared decision-making 

shifts the patient-physician relationship 

past traditional practices and 

contributes to better health outcomes, 

increased quality of life, increased 

patient knowledge and medication 

adherence, and lower healthcare 

expenditures.272 Furthermore, research 

findings support that shared decisionmaking with the patient could reduce 

kidney non-utilization, improve equity, 

and increase the number of kidney 

transplants.273


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receive deceased donor transplantation in the 

United States. Kidney International. https://doi.org/ 

10.1016/j.kint.2022.05.025; Patzer, R.E., McPherson, 

L., Basu, M., Mohan, S., Wolf, M., Chiles, M., 

Russell, A., Gander, J.C., Friedewald, J.J., Ladner, 

D., Larsen, C.P., Pearson, T., & Pastan, S. (2018). 

Effect of the iChoose Kidney decision aid in 

improving knowledge about treatment options 

among transplant candidates: A randomized 

controlled trial. American Journal of 

Transplantation: Official Journal of the American 

Society of Transplantation and the American 

Society of Transplant Surgeons, 18(8), 1954–1965. 

https://doi.org/10.1111/ajt.14693. 

274Massie, A.B., Luo, X., Chow, E.K.H., Alejo, 

J.L., Desai, N.M., & Segev, D.L. (2014). Survival 

benefit of primary deceased donor transplantation 

with high-KDPI kidneys. American Journal of 

Transplantation, 14(10), 2310–2316. https://doi.org/ 

10.1111/ajt.12830. 

By pairing the CollaboRATE Shared 

Decision-Making Score measure with 

the proposed achievement domain 

number of kidney transplants metric, as 

described in section III.C.5.c. of the 

proposed rule, and the proposed quality 

domain post-transplant outcomes 

metrics, as described in section 

III.C.5.e.(1). of the proposed rule, we 

aimed to incentivize care delivery 

transformation and improvement 

activity across IOTA participants that 

would center attributed patients and 

their family and caregiver as a critical 

decision-maker in treatment choices 

that align with their preferences and 

values. This may include greater 

transparency on donor organ offers and 

reasons for non-acceptance, and 

increased education and support on the 

living donor process. We also believed 

that this would support attributed 

patients in receiving a kidney that may 

be at higher risk of non-use, but that 

may offer a survival and quality of life 

advantage over remaining on dialysis, 

dying while waitlisted, or being delisted.274

In section III.C.5.e(2)(b) of the 

proposed rule, we acknowledged that 

the instrument used for the 

CollaboRATE Shared Decision-Making 

Score is generic; however, we were 

unable to identify alternative measures 

of shared decision-making that are 

specific to kidney transplant that have 

been endorsed by the CBE. Similarly, 

while there may be value in an 

instrument that measures shared 

decision-making regarding the types of 

kidney organ offers attributed patients 

are willing to accept, no such measure 

exists. We believed the CollaboRATE 

Shared Decision-Making Score would 

capture variation in the presence and 

quality of shared decision-making 

among IOTA participants and that the 

instrument need not be specific to 

kidney transplant to incentivize 

meaningful improvements in patientcentricity and the patient experience, 

equity, and reducing kidney non-use. 

We sought comment on our proposal 

to include the CollaboRATE Shared 

Decision-Making Score as a quality 

measure for purposes of quality domain 

performance assessment. 

The following is a summary of the 

comments received on our proposal to 

include the CollaboRATE Shared 

Decision-Making Score as a quality 

measure for purposes of quality domain 

performance assessment and our 

responses: 

Comment: Commenters expressed 

concern over the proposed inclusion of 

CollaboRATE Shared Decision-Making 

Score as a quality measure within the 

quality measure set to assess IOTA 

participant performance in the quality 

domain. Many commenters noted its 

lack of validation for use with hospitals 

and data to support the use of this 

measure in this population. Many 

commenters expressed concerns that the 

CollaboRATE measure is for use in the 

outpatient setting and has not been 

designed for hospitals or transplant 

patients. Many commenters questioned 

the inclusion of CollaboRATE Shared 

Decision-Making Score because it does 

not require transplant-related 

discussions and its applicability for 

inclusion in the model is unclear. Some 

commenters were concerned that the 

CollaboRATE Shared Decision-Making 

Score might not impact the specific 

issues of organ offers when used to 

capture all kidney transplant care, but 

pilot work and a trail funded by the NIH 

are specifically studying shared 

decision making for kidney transplant 

organ offers with a focus on materials 

and interventions to support SDM in a 

specific decision or encounter. Several 

commenters expressed concern over 

whether survey responses would 

provide relevant data for care under the 

IOTA Model and suggested that 

responses might need to be adjusted to 

factor in patient demographic 

characteristics. A couple commenters 

noted that it was unclear when the 

survey would be completed, and 

questioned whether administering the 

survey once per year, as proposed, 

would result in each survey covering 

multiple visits, making it difficult to 

observe quality differences or determine 

how to intervene. Several commenters 

had concerns about the amount of 

burden placed on transplant hospitals to 

implement the CollaboRATE Shared 

Decision-Making Score. A couple 

commenters indicated that this would 

be especially burdensome for small 

transplant hospitals without access to 

electronic sampling methods and that a 

focus on high response rates may limit 

resources for SDM. 

Response: In response to these 

comments, we will not be finalizing our 

proposal to include the CollaboRATE 

Shared Decision-Making Score as a 

quality measure for purposes of 

assessing performance within the 

quality domain, as described in section 

III.C.5.e(2) of this final rule. We believe 

incentivizing SDM is critical to 

centering the patient experience and 

treatment choices in the IOTA Model. 

This aligns with the model’s goals of 

improving equity, increasing kidney 

transplants, and reducing nonutilization, as discussed in section 

III.C.5.e(2)(b) of the preamble in this 

final rule. While we are not finalizing 

this SDM measure, the IOTA Model 

promotes it through other policies, such 

as the transparency requirements as 

described and finalized in section 

III.C.8(a) of the preamble in this final 

rule. 

Comment: A few commenters 

expressed support for CMS’s proposal to 

include CollaboRATE Shared DecisionMaking Score as a quality measure 

within the quality measure set to assess 

IOTA participant performance in the 

quality domain. A commenter indicated 

that the CollaboRATE Shared DecisionMaking Score would capture how well 

providers engage with patients before 

and after surgery and help promote 

patient-centered care. A commenter also 

expressed belief that incorporating a 

SDM patient-reported measure 

requirement is critical for transplant 

patients. They also suggested that 

incentivizing SDM between patients and 

healthcare providers would foster 

patient-centered care and promote 

informed choices. 

Response: We thank commenters for 

their support and for their comments in 

support of our proposal to include 

CollaboRATE Shared Decision-Making 

Score as a quality measure for purposes 

of assessing performance within the 

quality domain, as described in section 

III.C.5.e(2) of this final rule. However, in 

response to public comment, we will 

not be finalizing the CollaboRATE 

Shared Decision-Making Score as a 

quality measure, as described in section 

III.C.5.e(2) of this final rule. We still 

believe that incentivizing shared 

decision-making is critical to ensuring 

the model centers the patient experience 

and treatment choice to meet the IOTA 

desired goals of improving equity, 

increasing the number of kidney 

transplants, and reducing kidney nonutilization, as discussed in section 

III.C.5.e(2)(b) of this final rule. Although 

we are not finalizing this measure at 

this, we think that the IOTA Model 

promotes SDM through some of our 

other policies, such as the proposed 


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275Rama, I., & Grinyo ́, J.M. (2010). Malignancy 

after renal transplantation: The role of 

immunosuppression. Nature Reviews Nephrology, 

6(9), 511–519. https://doi.org/10.1038/ 

nrneph.2010.102. 

276 Komaki, Y., Komaki, F., Micic, D., Ido, A., & 

Sakuraba, A. (2018). Risk of colorectal cancer in 

chronic kidney disease. Journal of Clinical 

Gastroenterology, 52(9), 796–804. https://doi.org/ 

10.1097/mcg.0000000000000880. 

277Privitera, F., Gioco, R., Civit, A.I., Corona, D., 

Cremona, S., Puzzo, L., Costa, S., Trama, G., 

Mauceri, F., Cardella, A., Sangiorgio, G., Nania, R., 

Veroux, P., & Veroux, M. (2021). Colorectal cancer 

after Kidney Transplantation: A screening 

colonoscopy case-control study. Biomedicines, 9(8), 

937. https://doi.org/10.3390/biomedicines9080937. 

278Farrugia, D., Mahboob, S., Cheshire, J., Begaj, 

I., Khosla, S., Ray, D., & Sharif, A. (2014). 

Malignancy-related mortality following kidney 

transplantation is common. Kidney International, 

85(6), 1395–1403. https://doi.org/10.1038/ 

ki.2013.458. 

279 Jacobs, D.B., Schreiber, M., Seshamani, M., 

Tsai, D., Fowler, E., & Fleisher, L.A. (2023). 

Aligning quality measures across CMS—the 

Universal Foundation. New England Journal of 

Medicine, 388(9), 776–779. https://doi.org/10.1056/ 

nejmp2215539. 

280Cancer Moonshot. (n.d.). The White House. 

https://www.whitehouse.gov/cancermoonshot/. 

transparency requirements as described 

and finalized in section III.C.8(a) of the 

preamble in this final rule. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are not 

finalizing our proposal to include the 

CollaboRATE Shared Decision-Making 

Score as a measure within the quality 

measure set to assess IOTA participant 

performance in the quality domain. 

(c) Colorectal Cancer Screening 

In section III.C.5.e(2)(C) of the 

proposed rule, we stated that the 

Colorectal Cancer Screening (COL) 

measure identifies the percentage of 

patients 50–75 years of age who had 

guideline concordant screening for 

colorectal cancer. Kidney transplant 

recipients are at higher risk for cancer 

than the general population, due in part 

to long-term immunosuppression.275

Kidney transplant recipients have a 

higher incidence of colorectal cancer 

and advanced adenomas and may have 

worse prognoses than the general 

population, both of which support 

improved screening and prophylactic 

care for kidney transplant 

recipients.276 277 278

The COL measure is a Universal 

Foundation measure in the CMS 

Meaningful Measures 2.0 Wellness and 

Prevention Domain. By nature of its 

inclusion in the Universal Foundation 

measure set, the COL measure addresses 

a condition associated with significant 

morbidity and mortality and 

incentivizes action on high-value 

preventive care.279 The COL measure is 

also aligned with the goals of the 

President’s Cancer Moonshot to reduce 

the death rate from cancer by 50 percent 

over the next 25 years and improve the 

experience of people living with cancer 

and those who have survived it.280

As described in section III.C.5.e(2)(c) 

of the proposed rule, we proposed the 

COL measure for inclusion in our 

assessment of quality domain 

performance in the model because we 

believed it would provide a signal of the 

importance of ongoing post-transplant 

care and reduce variation in the 

screening and prophylactic care of 

kidney transplant recipients by 

transplant hospital. We proposed that 

IOTA participants would be required to 

administer the COL measure yearly to 

all attributed IOTA transplant patients 

who are Medicare beneficiaries. The 

COL measure would work in concert 

with the proposed composite graft 

survival metric to increase the 

likelihood that attributed patients in the 

IOTA Model would receive 

comprehensive post-transplant care that 

would account not only for the 

attributed patient and graft survival, but 

also complications and comorbidities 

associated with receiving a kidney 

transplant. 

We sought comment on our proposal 

to include the COL measure as a quality 

measure for purposes of quality domain 

performance assessment. 

The following is a summary of the 

comments received on our proposal to 

include the COL measure as a quality 

measure for purposes of quality domain 

performance assessment and our 

responses: 

Comment: Many commenters 

expressed concerns about our proposal 

to include the COL measure as a quality 

measure for purposes of quality domain 

performance assessment. Specifically, 

some commenters noted that many 

transplant recipients return to 

community providers after their 

transplant, making it challenging for 

transplant hospitals to ensure 

appropriate post-transplant screenings 

after they are no longer responsible for 

overseeing their care. As described in 

section III.C.5.e.(2).(c). of this final rule, 

we proposed that IOTA participants 

would be required to administer the 

COL measure yearly to all attributed 

IOTA transplant patients who are 

Medicare beneficiaries. A couple 

commenters suggested that the COL 

measure, as proposed, would more 

accurately reflect the care provided by 

patients’ primary care physicians, since 

many transplant hospitals transfer the 

patients’ care back to their local primary 

care physicians. A few commenters 

noted that transplant hospitals are 

already required to administer the COL 

to patients prior to waitlisting; 

suggesting that its inclusion in the IOTA 

Model would be redundant and 

unnecessarily increase costs without 

improving patient care. Many 

commenters urged CMS to remove COL 

from inclusion in the IOTA Model; 

citing that this measure is unrelated to 

transplant outcomes, cancers other than 

colorectal cancer are much more 

common in transplant recipients, the 

measure was not designed to identify 

the quality of care, is not a transplantspecific quality measure and shifts 

primary care responsibilities to 

transplant hospitals as reasons for its 

removal. Some commenters felt that the 

inclusion of COL in the IOTA Model is 

redundant and not directly relevant to 

kidney transplant care and suggested 

removing COL or replacing it with 

quality measures more closely aligned 

to kidney transplant outcomes, such as 

a more comprehensive cancer screening 

protocol. 

Response: We thank commenters for 

sharing their concerns. In response to 

these comments, we will not be 

finalizing our proposal to include the 

COL measure as a quality measure for 

purposes of assessing performance 

within the quality domain as described 

in section III.C.5.e.(2). of this final rule. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are not 

finalizing our proposal to include the 

COL as a measure within the quality 

measure set to assess IOTA participant 

performance in the quality domain, as 

discussed in section III.C.5.e.(2). of this 

final rule. 

(d) 3-Item Care Transition Measure 

(CTM–3) 

As described in section 

III.C.5.e.(2).(d). of the proposed rule, the 

3-Item Care Transition Measure (CTM– 

3) is a hospital-level, patient-reported 

measure of readiness for self-care at 

time of discharge from an acute care 

hospital. The CTM–3 is based on data 

from a three-question instrument that 

assesses whether the patient and 

family’s preferences were accounted for 

in the care plan; whether patients 

understood their role in selfmanagement; and, whether appropriate 

medication education was provided. A 

higher score on the CTM–3 reflects a 

higher quality transition of care. We 

proposed that IOTA participants would 

be required to administer the CTM–3 to 

attributed patients once per PY, at 

minimum, and report quality measure 

data to CMS during survey and 

reporting windows, as defined and 

finalized in section III.C.5.e(2)(a) of this 


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281Covert, K.L., Fleming, J.N., Staino, C., Casale, 

J.P., Boyle, K.M., Pilch, N.A., Meadows, H.B., 

Mardis, C.R., McGillicuddy, J.W., Nadig, S., Bratton, 

C.F., Chavin, K.D., Baliga, P.K., & Taber, D.J. (2016). 

Predicting and preventing readmissions in Kidney 

Transplant Recipients. Clinical Transplantation, 

30(7), 779–786. https://doi.org/10.1111/ctr.12748. 282Covert, K.L., Fleming, J.N., Staino, C., Casale, 

J.P., Boyle, K.M., Pilch, N.A., Meadows, H.B., 

Mardis, C.R., McGillicuddy, J.W., Nadig, S., Bratton, 

C.F., Chavin, K.D., Baliga, P.K., & Taber, D.J. (2016). 

Predicting and preventing readmissions in Kidney 

Transplant Recipients. Clinical Transplantation, 

30(7), 779–786. https://doi.org/10.1111/ctr.12748. 

283 Jadlowiec, C.C., Frasco, P., Macdonough, E., 

Wagler, J., Das, D., Budhiraja, P., Mathur, A.K., 

Katariya, N., Reddy, K., Khamash, H., & Heilman, 

R. (2022). Association of DGF and early 

readmissions on outcomes following Kidney 

Transplantation. Transplant International, 35. 

https://doi.org/10.3389/ti.2022.10849. 

final rule, that would be established by 

CMS. 

Transitions of care after kidney 

transplant are common and indicate 

elements of modifiable transplant 

hospital quality. One study found that 

30-day hospital readmissions after an 

organ transplant were significantly 

associated with graft loss and death.281

Poor understanding of and adherence to 

immunosuppressive drugs were 

identified as key elements associated 

with an increased risk for early hospital 

readmission.282 Mitigating readmission 

risk may be of special importance given 

that IOTA participants may choose to 

increase their number of transplants by 

transplanting more kidneys that may 

have clinical value to patients. 

Simultaneously, there may also be 

increased healthcare utilization needs 

due to delayed graft function (DGF), 

which could require longer hospital 

stays, readmissions, and more complex 

care coordination.283 We have also 

heard from interested parties about the 

need for patient-reported measures to 

contribute to the assessment of posttransplant outcomes. 

The CTM–3 is a patient-reported 

measure and would measure transplant 

hospital performance on an aspect of 

care that we understand to be important 

to the patient experience, modifiable by 

transplant hospitals, and that may not 

otherwise improve based on the 

financial incentives in the model 

targeted towards one- and three-year 

outcomes, but not directly at 

perioperative transitions of care and 

readmission risk. The CTM–3 is a 

domain of the HCAHPS (CBE ID: 0166). 

We believe that IOTA participants 

would have some familiarity with the 

HCAHPS survey and that the hospital 

systems of which IOTA participants 

would be a part would have an 

infrastructure in place for the 

administration of HCAHPS that could 

be leveraged to support administration 

of the CTM–3. 

We sought comment on our proposal 

to include the CTM–3 measure as a 

quality measure as a quality measure for 

purposes of quality domain performance 

assessment. 

The following is a summary of the 

comments received on our proposal to 

include the CTM–3 measure as a quality 

measure for purposes of quality domain 

performance assessment and our 

responses: 

Comment: Many commenters urged 

CMS not to finalize CTM–3 as a quality 

measure within the quality measure set 

to assess IOTA participant performance 

in the quality domain, noting that it 

would add additional burden to patients 

and IOTA participants and unnecessary 

complexity, and cost to IOTA 

participants. A couple commenters 

urged CMS not to include the CTM–3 

measure, indicating that the association 

between CTM–3 and readmissions is 

inconsistent in that it does not predict 

30-day outcomes and only weakly 

predicts 3- and 12-month outcomes. 

Several commenters also noted that 

participants would be required to report 

the CTM–3 separately from their 

HCAHPS surveys, as this measure will 

soon be removed from the revised 

Inpatient Quality Reporting Program 

(IQR). A commenter also noted that 

collecting CTM–3 data could be 

redundant, as it will soon be removed 

from the hospital IQR in favor of an 

updated set of HCAHPS care 

coordination items. Finally, a 

commenter stated that they opposed the 

inclusion of CTM–3 as a quality 

measure within the quality measure set 

to assess IOTA participant performance 

in the quality domain. 

Response: We thank the commenters 

for their comment and appreciate these 

commenters concerns to our proposal to 

include the CTM–3 measure as a quality 

measure for purposes of assessing 

performance in the quality domain. In 

response to these comments, we will not 

be finalizing our proposal to include the 

CTM–3 measure as a quality measure for 

purposes of assessing performance 

within the quality domain, as described 

in section III.C.5.e(2) of this final rule. 

Comment: Some commenters 

recommended alternative measures that 

CMS should consider replacing the 

CTM–3 with. For example, several 

commenters suggested that CMS should 

replace the retired CTM–3 measure with 

the proposed ‘‘Care Coordination’’ SubMeasure to align with the updates to the 

HCAHPS survey. A commenter 

suggested that CMS should consider 

only looking at readmission rates as a 

proxy for sound care transition planning 

or using HCAPS data instead of the 

CTM–3 measure. 

Response: We thank the commenters 

for their comment and appreciate these 

commenters suggested alternatives to 

our proposal to include the CTM–3 

measure as a quality measure for 

purposes of assessing performance in 

the quality domain. In response to the 

public comments we received, we will 

not be finalizing our proposal to include 

the CTM–3 measure as a quality 

measure for purposes of assessing 

performance within the quality domain 

as described in section III.C.5.e(2) of this 

final rule. 

Comment: A couple commenters 

expressed support for the inclusion of 

CTM–3 as a quality measure within the 

quality measure set to assess IOTA 

participant performance in the quality 

domain. A commenter urged CMS to 

finalize this measure suggesting that it 

would encourage providers to actively 

engage patients before and after surgery 

to ensure they can make an informed 

decision about their treatment options 

and are prepared to manage their care 

afterwards. 

Response: We thank commenters for 

their support and for their comments in 

support of our proposal to include the 

CTM–3 measure as a quality measure for 

purposes of quality domain performance 

assessment. We believe that transitions 

of care after kidney transplant are 

common and indicate elements of 

modifiable transplant hospital quality, 

as discussed in section III.C.5.e(2)(d) of 

this final rule. However, as described in 

comment responses noted previously, 

due to concerns raised by commenters 

we will not be finalizing CTM–3 as a 

quality measure, as described in section 

III.C.5.e(2) of this final rule. We will 

continue to evaluate the changing 

inventory of quality measures, 

considering public input, and intend to 

propose alternative quality measures 

through future notice and comment 

rulemaking 

After considering public comments, 

for the reasons set forth in this rule, we 

are not finalizing our proposal to 

include the CTM–3 as a measure within 

the quality measure set to assess IOTA 

participant performance in the quality 

domain, as described and finalized in 

section III.C.5.e(2) of this final rule. 

(e) Calculation of Points 

In section III.C.5.e(2)(e) of the 

proposed rule, we proposed that the 

IOTA participant would receive up to 

10 points for performance on our three 

proposed measures within the quality 

domain—the CollaboRATE Shared 

Decision-Making Score, COL, and CTM– 

3 measures. For purposes of quality 

measure set performance scoring, we 

proposed that IOTA participants may 


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receive up to 4 points for performance 

on the CollaboRATE Shared DecisionMaking Score measure, up to 2 points 

on the COL measure, and up to 4 points 

on the CTM–3 measure. Lower weight 

in terms of scoring points were given to 

the COL measure because it is a claimsbased measure that does not require 

reporting from IOTA participants. 

Because the CTM–3 and CollaboRATE 

are PRO–PMs we believed it was 

important to allot more points to them, 

to recognize the additional operational 

activities necessary for IOTA 

participants. 

In section III.C.5.e(2)(e) of the 

proposed rule, we proposed to phase-in 

quality performance benchmarks for the 

three quality measures selected for the 

IOTA quality measure set, such that we 

would reward reporting for the first two 

years of the model performance period 

(‘‘pay-for-reporting’’), at minimum, 

before we reward performance against 

quality performance benchmarks for 

each measure (‘‘pay-for-performance’’). 

Thus, performance for each of these 

three quality measures would be 

measured against a ‘‘response rate 

threshold’’ applicable to our proposed 

‘‘pay-for-reporting’’ method for PY 1— 

PY 2, while performance would be 

measured against quality performance 

benchmarks calculated by CMS 

applicable to our proposed ‘‘pay-forperformance’’ method for PY 3—PY 6. 

Table 10 illustrates our proposed payfor-reporting and pay-for-performance 

timeline. We noted that we anticipated 

establishing a quality performance 

benchmarks and minimum attainment 

levels for quality measures in future rule 

making. 

In section III.C.5.e(2)(e) of the 

proposed rule, we proposed that CMS 

would determine and share with IOTA 

participants the response rate threshold 

by the first day of each PY in a form and 

manner chosen by CMS. We stated that 

this approach to assessing IOTA 

participant quality performance would 

serve four key purposes. First, it would 

promote measure implementation, 

uptake, and data collection by IOTA 

participants through a rewards-only 

scoring system. Second, it would build 

experience over the first two model PYs, 

giving IOTA participants more time to 

prepare and build capacity to meet 

performance benchmarks. Third, it 

would allow CMS to collect data needed 

to develop measure benchmarks. 

Finally, it would focus model incentives 

on care delivery transformation and 

improvement activity directly aimed at 

meeting quality performance goals, as to 

ensure the patient is centered in this 

approach. Ultimately, we considered the 

pay-for-reporting approach to be a 

reasonable approach. We also believed 

that some IOTA participants may be 

familiar with this as it is similar to the 

format within the KCC Model. We 

recognized that these measures already 

exist, but, because they are used in a 

much broader population, there are no 

benchmarks that are applicable for the 

model. 

In section III.C.5.e(2)(e) of the 

proposed rule, we proposed to define 

the ‘‘response rate threshold’’ as the 

level of complete and accurate reporting 

for each quality measure, within the 

quality measure set of the quality 

domain, that the IOTA participant must 

meet to earn points on the quality 

domain during a performance year as 

described in § 512.428(c) and (e) of the 

proposed rule. For the CTM–3 and 

CollaboRATE measures, we proposed 

that points be awarded based on 

response rate thresholds, as illustrated 

in Table 11, such that IOTA participants 

with a response rate threshold of— 

• 90–100 percent of attributed 

patients would receive 4 points; 

• 50–89 percent of attributed patients 

would receive 2 points; or 

• Under 50 percent of attributed 

patients would receive 0 points. 

In section III.C.5.e(2)(e) of the 

proposed rule, we proposed for the COL 

measure that a completion rate of 50 

percent or greater would result in the 

IOTA participant receiving two points, 

and a completion rate of less than 50 

percent would result in the IOTA 

participant receiving zero points, as 

illustrated in Table 11. 

As described in section III.C.5.e(2)(e) 

of the proposed rule, we recognized that 

the proposed response rate thresholds 

are high, but we want to make sure that 

we have enough data to set appropriate 

and meaningful benchmarks in PY 3 

through PY 6. We considered setting a 

higher maximum measure completion 

rate; however, given that each IOTA 

participant may have different levels of 

engagement with kidney transplant 

waitlist patients, we felt a higher 

threshold may be difficult for IOTA 

participants to achieve. We also 

believed that a higher response rate 


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TABLE 10: MEASURE PAYMENT TYPE BY PERFORMANCE YEAR 

Measure PYl PY2 PY3 PY4 PYS PY6 

CollaboRATE Shared Decision- Pay for Reporting (P4R) P4R Pay for P4P P4P P4P 

Making Score Performance (P4P) 

Colorectal Cancer Screening (COL) P4R P4R P4P P4P P4P P4P 

CTM-3 P4R P4R P4P P4P P4P P4P 

TABLE 11-IOTA MODEL QUALITY MEASURE SET SCORING 

Measure Performance Lower Bound Upper Bound Points 

Relative to Tar2et Condition Condition Earned 

CollaboRA TEICTM-3 90% Response Rate Equals 90% Greater than 90% 4 

CollaboRATE I CTM-3 50% Response Rate Equals 50% Less than 90% 2 

CollaboRATE I CTM-3 50% Response Rate NIA Less than 50% 0 

COL 50% Response Rate Equals 50% Greater than 50% 2 

COL 50% Response Rate NIA Less than 50% 0 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96377 

would incentivize IOTA participants to 

collect the data. We considered the 

following variations to the response rate 

threshold for each of the proposed 

quality measure: 

• Response rate threshold of 100 

percent would receive 10 points, if not 

100 percent 0 points would be awarded. 

• Response rate threshold of 80–100 

percent would receive 10 points, 50–79 

percent would receive 5 points, and 49– 

0 percent would receive 0 points. 

• 50–100 percent would receive 10 

points; under 50 percent would receive 

0 points. 

As described in section III.C.5.e(2)(e) 

of the proposed rule, we considered 

mirroring the point structure under 

which an IOTA participant would 

receive either all possible points, or, if 

data was not collected from all their 

attributed patients, none of the possible 

points. We thought that this could 

incentivize IOTA participants to 

administer the surveys associated with 

the proposed quality measures, which 

would allow us to create meaningful 

benchmarks for future model years. 

However, because there would be some 

additional burden placed onto IOTA 

participants to administer the surveys 

associated with the proposed quality 

measures, we believed this point 

structure would be difficult for some 

and wanted to provide more attainable 

response rate thresholds. We also 

considered lowering the response rate 

thresholds for the same reasons 

mentioned earlier, but, because there are 

currently no benchmarks for these 

measures in this specific population, we 

felt that the response rate threshold 

needed to be higher but still attainable. 

We also considered achievement and 

improvement scoring for the proposed 

quality measures. However, because 

none of the measures included in the 

proposed quality measure set, as 

described in section III.C.5.e(2) of this 

final rule, currently have benchmarks, 

we did not believe it was appropriate to 

propose achievement and improvement 

scoring for the proposed quality 

measures at this time. 

We sought comment on our proposed 

calculation of points for the quality 

measure set, as well as the proposal to 

reward IOTA participant reporting for 

the first two PYs (‘‘pay-for-reporting’’), 

before rewarding IOTA participant 

performance against quality 

performance benchmarks. We sought 

comment on the proposed response rate 

thresholds and point allocations for 

measures included in the proposed 

quality measure set within the quality 

domain. 

The following is a summary of the 

comments received on our proposed 

calculation of points for the quality 

measure set, as well as the proposal to 

reward IOTA participant reporting for 

the first two PYs (‘‘pay-for-reporting’’), 

before rewarding IOTA participant 

performance against quality 

performance benchmarks and the 

proposed response rate thresholds, 

point allocations for measures included 

in the proposed quality measure set 

within the quality domain and our 

responses: 

Comment: Some commenters 

expressed concern about the proposed 

response rate thresholds and point 

allocations and requested that CMS 

lower the proposed response rate 

threshold for the proposed quality 

measures. For example, a commenter 

expressed their belief that how well 

IOTA participants do getting their 

patients to respond to specific surveys 

is not an accurate reflection of quality. 

A few of commenters indicated that 

transplant hospitals currently struggle to 

achieve patient experience survey 

response rates above 30 percent. Given 

this challenge, they felt that the 

proposed 90 percent response rate 

threshold for quality measures is 

unrealistic. To achieve a 90 percent 

response rate for two new quality 

measures, a commenter suggested this 

would require that the surveys be 

administered in person; noting that this 

approach could create an administrative 

burden by requiring staff to distribute 

and collect the surveys, as well as 

necessitate patients making extra clinic 

visits solely for the purpose of 

completing the surveys. Several 

commenters urged CMS to adjust the 

response rate thresholds to mitigate this 

challenge. Specifically, a commenter 

recommended that CMS adopt a similar 

minimum response rate threshold like 

what is proposed for awarding domain 

points; suggesting 4 points awarded for 

response rate thresholds above 50 

percent, 2 points awarded for response 

rate thresholds of 25 percent to 50 

percent, and 0 points awarded for 

response rates below 25 percent. 

Response: We thank these 

commenters for sharing their concerns. 

We acknowledge the concerns related to 

the high response rate thresholds 

proposed for the CollaboRATE Shared 

Decision-Making Score and CTM–3. As 

we stated in the proposed rule, we 

acknowledge that the proposed response 

rate thresholds are quite high and that 

these measures are already in use, 

though applied to a much wider 

population. As a result, there are no 

benchmarks that can be utilized for the 

IOTA Model, and we sought to ensure 

that we had enough data to set 

appropriate and meaningful quality 

performance benchmarks in PY 3 

through PY 6. 

We also thank the commenters for 

their recommendations to lower the 

response rate thresholds given the 

number of surveys requests and 

obligations transplant patients are 

already asked to complete and the 

additional burden that could be placed 

onto IOTA participants to administer 

the surveys associated with the 

proposed quality measures and lower 

the response rate thresholds. We also 

appreciate the commenters suggestion 

for an alternative scoring methodology. 

As we stated in the proposed rule, we 

did consider lowering the response rate 

thresholds for the same reasons 

mentioned earlier, but, because there are 

currently no benchmarks for these 

measures in this specific population, we 

felt that the response rate threshold 

needed to be higher but still attainable. 

We direct readers to section 

III.C.5.e.(2)(e) for further discussion on 

the alternative scoring methodologies 

that were considered for inclusion in 

the IOTA Model. We also note that we 

considered the added reporting burden 

on IOTA participants when evaluating 

potential quality measures for inclusion 

in the IOTA Model, and direct 

commenters to section III.C.5.e(2) of this 

final rule for further discussion. 

Lastly, because we are not finalizing 

our proposed quality measure set, as 

described in section III.C.5.e(2) of this 

final rule, and in consideration on 

public comment received, we will not 

be finalizing our proposed quality 

measure set scoring methodology. In 

section III.C.5.e(e) of the proposed rule, 

we proposed that the IOTA participant 

would receive up to 10 points for 

performance on our three proposed 

measures within the quality domain 

while also noting in the proposed rule 

at 89 FR 43564, that if we finalize fewer 

measures, then we proposed to allocate 

the points accordingly within the 

remaining measures. Given that we are 

not finalizing any of the proposed 

measures within the quality measure set 

or quality measure set scoring 

methodology, the 10 points we 

proposed to award IOTA participants 

for performance on our three proposed 

measures within the quality domain 

will be allocated to the composite graft 

survival rate within the quality domain, 

as described and finalized in section 

III.C.5.e(1)(b) of this final rule. 

Although we are not finalizing our 

quality measure set scoring 

methodology at this time, CMS will take 

into consideration the commenters 

concerns and suggestions and intends to 

propose an alternative or updated policy 


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284National Committee for Quality Assurance. 

‘‘Colorectal Cancer Screening—NCQA.’’ NCQA, 

2024, www.ncqa.org/hedis/measures/colorectalcancer-screening/. 

proposal in future notice and comment 

rulemaking. 

Comment: A couple commenters 

expressed support for the proposed 

response rate thresholds, but they felt 

that a 90% response rate would be 

extremely unlikely to be achieved. 

Response: We thank commenters for 

their support and for their comments in 

support of our proposed response rate 

thresholds and concern over the 

achievability of a 90% response rate. As 

mentioned in comment responses noted 

previously, we acknowledge that the 

response rate thresholds we proposed 

were high. As discussed in the preamble 

of this final rule, we proposed the 

response rates for the proposed quality 

measures, as illustrated in Table 11 

noted previously, to allow CMS to 

collect enough data to develop 

meaningful and appropriate measure 

benchmarks in PYs 3–6. 

However, because we are not 

finalizing our proposed quality measure 

set, as described in section III.C.5.e(2) of 

this final rule, and based on public 

comment, we will not be finalizing our 

proposed quality measure set scoring 

methodology, as described in section 

III.C.5.e(2)(e) of this final rule, at this 

time, and intend to propose a new or 

updated policy in future notice and 

comment rulemaking that will address 

concerns with respect to response rate 

thresholds IOTA participants may have. 

Comment: A couple commenters 

requested that CMS provide additional 

clarity about the proposed response rate 

thresholds and point allocations. For 

example, a commenter urged CMS to 

not only propose response rate 

thresholds, but also define what 

constitutes ‘‘complete and accurate 

reporting’’ and provide specifics on how 

the response rate threshold would be 

calculated for CollaboRATE; stating that 

until CMS did so, they could not 

support the inclusion of this measure in 

the IOTA Model. Another commenter 

cited that the Healthcare Effectiveness 

Data and Information Set (HEDIS) 

specifications for the COL measure 

indicate that COL is an administrative 

measure,284 noting that CMS proposed 

response rate thresholds for it during 

the pay-for-reporting years of the model. 

This commenter asked CMS to clarify 

two key points: (1) How the response 

rate would be calculated for an 

administrative measure, and (2) How 

this calculation differs from the quality 

performance benchmarks that would 

need to be met once the measure 

transitions to pay-for-performance in 

future program years. 

Response: We appreciate the 

commenters comments and clarifying 

questions. In the proposed rule at 89 FR 

43658, we proposed to define response 

rate threshold as the level of complete 

and accurate reporting for each quality 

measure, within the quality measure set 

of the quality domain, that the IOTA 

participant must meet to earn points on 

the quality domain during a 

performance year as described in 

§§ 512.428(c) and 512.428(e). In 

response to the commenters request that 

CMS further explain how the response 

rate threshold would be calculated for 

CollaboRATE and COL, we clarify here 

that, based on our proposed definition 

and industry standards, the response 

rate for each of the proposed quality 

measures would be calculated as 

follows: 

Equation 5: Response Rate Threshold 

For example, if in PY 1 of the model, 

an IOTA participant was required to 

administer the CollaboRATE to 30 of 

their attributed patients and submitted 

28 complete and accurate responses, the 

response rate for that IOTA participant 

on the CollaboRATE would be 93% (28 

complete and accurate responses 

submitted divided by 30 and then 

multiplied by 100). Based on our 

proposed quality measure set scoring 

methodology, as described in the 

preamble of this final rule, that IOTA 

participant would be awarded four 

points for their response rate threshold 

on the CollaboRATE. 

In accordance with the Share Savings 

Program Final Rule as outlined in 76 FR 

67873, we are clarifying that ‘‘complete 

and accurate reporting’’ signifies that 

that the quality data submitted to CMS 

is accurate, complete, and truthful. 

However, we disagree with the 

commenters’ belief that CMS needs to 

define what is meant by ‘‘complete and 

accurate reporting,’’ as this is language 

that has been used in other models, 

such as the Shared Savings Program at 

42 CFR 425.502. Regarding the 

commenters request that CMS clarify 

how our proposals for calculating 

response rate thresholds differs from 

calculating performance benchmarks in 

later PYs, we note that, as discussed in 

the proposed rule at 89 FR 43658, we 

anticipated establishing quality 

performance benchmarks and minimum 

attainment levels for quality measures 

in future rule making. 

Finally, as mentioned in comment 

responses noted previously in this 

section, since we are not finalizing our 

proposed quality measure set, as 

described in section III.C.5.e(2) of this 

final rule, and based on public 

comment, we will not be finalizing our 

proposed quality measure set scoring 

methodology at this time and the 10 

points we proposed to award IOTA 

participants for performance on our 

three proposed measures within the 

quality domain will be allocated to the 

composite graft survival rate within the 

quality domain, as described and 

finalized in section III.C.5.e(1)(b) of this 

final rule. We also note that we intend 

to propose a new or updated policy in 

future notice and comment rulemaking. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are not 

finalizing our proposed quality measure 

set scoring methodology, as described at 

§ 512.428(e) of the proposed rule, or our 

proposed definition of response rate 

threshold, as described at § 512.402 of 

the proposed rule. Although we are not 

finalizing any of the measures that we 

proposed for inclusion in our proposed 

quality measure set, as described in 

section III.C.5.e(2) of this final rule, we 

intend to propose alternatives in future 

notice and comment rulemaking. 

Additionally, in section III.C.5.e(e) of 

the proposed rule, we proposed that the 

IOTA participant would receive up to 

10 points for performance on our three 

proposed measures within the quality 

domain while also noting in the 

proposed rule at 89 FR 43564, that if we 

finalize fewer measures, then we 

proposed to allocate the points 

accordingly within the remaining 

measures. Given that we are not 

finalizing the proposed quality measure 

set within the quality domain or quality 

measure set scoring methodology, the 10 


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Response Rate 

# of complete and accurate responses submitted 

# of eligible attributed patients surveyed XlOO 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96379 

285https://www.cms.gov/priorities/innovation/ 

key-concepts/risk-arrangements-health-care. 

points we proposed to award IOTA 

participants for performance on our 

three proposed measures within the 

quality domain will be allocated to the 

composite graft survival rate within the 

quality domain, as described and 

finalized in section III.C.5.e(1)(b) of this 

final rule. We will continue to assess 

our quality domain methodology and 

how to best balance incentives in the 

efficiency domain and quality domain 

and will address a new or updated 

policy pursuant to future notice and 

comment rulemaking. 

■ 6. Payment 

a. Purpose and Goals 

We believe that risk-based payment 

arrangements in Innovation Center 

models drive healthcare innovation and 

transform the healthcare payment 

system by rewarding value over volume. 

Risk-based payment models hold 

participants financially accountable, as 

these payments are structured to 

incentivize value-based care that 

improves quality and reduces total cost 

of care for beneficiaries. Risk-based 

payment models may be upside-risk 

only, or have two-sided, upside and 

downside, risk. Under these risk-based 

arrangements, IOTA participants may 

receive a payment from CMS if 

performance goals are met or exceeded, 

and, if the model features downside 

risk, may owe a payment to CMS for 

failing to meet performance goals.285

For the IOTA Model, we proposed an 

alternative payment model (APM) 

structure that incorporates both upside 

and downside risk to existing Medicare 

fee-for-service (FFS) payments for 

kidney transplantations as described in 

section III.C.6.b. of the proposed rule. 

The IOTA Model will test whether 

performance-based payments, including 

an upside risk payment and downside 

risk payment, to IOTA participants 

increases access to kidney transplants 

for attributed patients while preserving 

or enhancing quality of care and 

reducing kidney transplant hospital 

expenditures. As described in section 

III.C.5. of this final rule, IOTA 

participants will be assessed against 

proposed metrics to assess performance 

for each PY relative to specified targets, 

thresholds, or benchmarks proposed 

and determined by CMS. The final 

performance score, not to exceed a 

maximum of 100 points, will determine 

if and how upside and downside risk 

payments are applied, as described in 

section III.C.6.c. of this final rule. We 

believe this upside and downside risk 

approach will be a strong incentive to 

promote performance improvement. 

We sought comment on our proposed 

two-sided risk payment design to 

incentivize model performance goals. 

The following is a summary of the 

comments received on our proposed 

two-sided risk payment design and our 

responses: 

Comment: We received multiple 

comments pointing out that kidney 

transplant hospitals do not make their 

decisions for transplants based on 

financial incentives and that it is 

inappropriate to incentivize IOTA 

participants to do more transplants 

through a pay-for-performance model. 

Response: We understand that the 

decision to transplant a specific 

beneficiary is not made for financial 

reasons. However, we recognize that 

resource allocation decisions for a 

kidney transplant hospital are made at 

an administrative level that will allocate 

resources in part based on CMS 

reimbursement policies, which is why 

we are testing the IOTA Model using 

this framework. 

Comment: We received a comment 

saying that CMS should consider the 

impact on private payer COE programs 

for transplant based on the incentives in 

the model. 

Response: We recognize the 

importance of COE programs to kidney 

transplant hospitals and recognizes that 

being in a COE for a payer is a key 

source of revenue for many kidney 

transplant hospitals. The model was 

designed to align with many of the 

metrics used for a COE, which generally 

include a minimum volume 

requirement and some minimum level 

of performance on post-transplant 

outcomes. Though their metrics do not 

generally include a major requirement 

to increase volume like those of the 

IOTA Model, transplants represent a 

major source of potential savings on the 

plan side, just as it does for CMS. CMS 

is hopeful that with the finalization of 

the IOTA Model that other payers will 

more closely harmonize their measures 

to create a unified regulatory framework 

that reduces burden for kidney 

transplant hospitals and improves 

overall quality. 

Comment: We received a comment 

saying that the model should not focus 

on accountability at the kidney 

transplant hospital level, but instead 

direct resources directly to the most 

vulnerable patients to assist them 

through the transplant process. 

Response: We understand the 

comment, but ultimately disagree with 

the commenter. The IOTA Model is 

based on the idea that the kidney 

transplant hospital is the key locus for 

the transplant process, given the role of 

the kidney transplant hospital in getting 

candidates onto the waitlist, deciding 

which organs to accept, performing 

transplant surgeries, managing the 

living donor process, and overseeing 

post-transplant care. Given that role, we 

believe that the kidney transplant 

hospitals are closer to their patients and 

will be better able to determine their 

exact needs to help get them through the 

transplant process. 

Comment: We received a comment 

saying that downside risk in the IOTA 

Model was inappropriate because organ 

supply is out of the control of kidney 

transplant hospitals. 

Response: We recognize that kidney 

transplant hospitals are not the entities 

responsible for recovering organs. 

However, research has shown 

significant variance in organ-offer 

acceptance practices, even among 

kidney transplant hospitals that are 

geographically proximate, as discussed 

in the background section. Additionally, 

kidney transplant hospitals are in 

complete control of the living donor 

kidney process, which is not dependent 

upon the procurement process. 

Comment: We received multiple 

comments saying that downside risk in 

the model was inappropriate because 

kidney transplant hospitals are new to 

value-based care. 

Response: We understand the need for 

IOTA participants to ramp up their 

value-based care operations, which is 

why there is no downside risk for IOTA 

participants in PY 1. Additionally, in 

this final rule, we removed many 

requirements that may have been 

perceived as burdensome by kidney 

transplant hospitals, such as reporting 

on multiple quality measures and on 

declined organ offers and we believe 

that this will make it more achievable 

for IOTA participants to devote the 

necessary resources required to succeed 

in the IOTA Model. The IOTA Model 

also focuses on major functions and 

activities that kidney transplant 

hospitals are already doing, rather than 

changing the focus to a more population 

health perspective as is done in many 

other Innovation Center models. Given 

these circumstances, we then believe 

that downside risk can be fairly applied 

in PY 2 to help further incentivize 

performance in the model. 

Comment: We received a comment 

saying that many kidney transplant 

hospitals face structural barriers that 

prevent them from increasing their 

numbers of transplants, making 

downside risk inappropriate for the 

model. 

Response: We recognize that different 

kidney transplant hospitals face 


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286https://hcp-lan.org/workproducts/apmrefresh-whitepaper-final.pdf. 287https://hcp-lan.org/workproducts/apmrefresh-whitepaper-final.pdf. 

different limitations in how they 

manage the transplant process. This is 

why the IOTA Model includes a flexible 

scoring system that gives IOTA 

participants different areas to focus on 

to achieve an upside risk payment 

under the model. Every IOTA 

participant can adjust their organ offer 

filters to be more efficient and remove 

offers that they are unlikely to use. 

Additionally, the model is not 

prescriptive on how IOTA participants 

can transplant more organs, meaning 

that IOTA participants could invest in 

their living donor program or could 

focus on using deceased donor organs 

that they may not have utilized in the 

baseline years. Finally, each IOTA 

participant is judged against scored 

based on their own historic number of 

transplants, or historic organ offer 

acceptance rate, for the achievement 

and efficiency domains. This approach 

demonstrates CMS’s effort to recognize 

that kidney transplant hospitals are 

starting at different places before the 

IOTA Model and to provide an 

opportunity to fostering innovation by 

competing against their own historic 

performance. 

Comment: We received a comment 

saying that many smaller or essential 

kidney transplant hospitals lack the 

resources to effectively participate in 

the IOTA Model and should have no 

downside risk. 

Response: We understand that smaller 

kidney transplant hospitals may have 

fewer overall resources and we do not 

want any kidney transplant hospitals to 

stop offering kidney transplant services 

because of the IOTA Model. To address 

this issue, we proposed a low-volume 

threshold of 11 or more kidney 

transplants performed annually to 

exclude the kidney transplant hospitals 

with the lowest volumes, as described 

and finalized in section III.C.3.c of this 

final rule. Additionally, benchmarks for 

the achievement domain and efficiency 

domain in the IOTA Model are based on 

improvement relative to the IOTA 

participant’s own historic number of 

transplants, or historic organ offer 

acceptance rate, meaning that for 80 of 

100 possible points that an IOTA 

participant can earn for the model, they 

are evaluated against their own historic 

performance. Finally, the payment 

methodology for the IOTA Model is 

based on the number of transplants 

performed and includes asymmetrically 

less downside risk, minimizing the 

potential downside for smaller kidney 

transplant hospitals. We will monitor 

the effects of these different 

mechanisms within the IOTA Model to 

see if they are successful in helping 

smaller kidney transplant hospitals and 

will consider further efforts in future 

rulemaking based on the results of those 

monitoring efforts. 

Comment: We received a comment 

supporting the two-sided risk structure 

for the IOTA Model, supporting the 

inclusion of downside risk in order to 

help change behavior of IOTA 

participants. 

Response: We appreciate the feedback 

and believe that downside risk is 

ultimately necessary to help incentivize 

IOTA participants to achieve the goals 

of the IOTA Model. 

Comment: A commenter questioned 

whether payment adjustments 

effectively drive physician behavior, 

and instead urged CMS to prioritize 

upstream investments as a means of 

promoting increased organ 

transplantation. 

Response: We appreciate the feedback 

but disagree with the commenter. We 

recognize some of the limitations of 

payment adjustments to move physician 

behavior. However, we recognize that 

they have never been tried in this area. 

There is significant variation kidney 

transplant hospitals among their use of 

organ offer filters, organ offer 

acceptance rate, and investment in the 

living donation process, and the IOTA 

Model will test whether IOTA 

participants can learn from other IOTA 

participants that may be higher 

performing in these areas. We also 

recognize that organ transplant, as 

opposed to many other areas covered in 

other Innovation Center models, 

contains a cost-based reimbursement 

model for organ acquisition costs that 

provides a significant source of funding 

to support IOTA participants’ 

investments in performance. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

this two-sided payment framework as 

originally designed. We believe that the 

two-sided framework best creates a clear 

incentive for improved performance by 

IOTA participants, with sufficient 

upside to reward IOTA participants for 

excellent performance. Furthermore, as 

described and finalized in section 

III.C.6.c(1) of this final rule, we are 

finalizing at § 512.430(b)(3)(i) that for 

PY 1, the IOTA participant does not owe 

a downside risk payment to CMS. We 

direct readers to sections III.C.6.C(2)(ac) for a full discussion on our proposed 

upside risk payment, downside risk 

payment, and neutral zone provisions. 

b. Alternative Payment Design Overview 

There are two payment components 

in the current Medicare FFS program for 

organ transplantation. Under the 

Medicare Inpatient Prospective Payment 

System (IPPS), kidney transplant 

hospitals are paid a prospective 

payment system rate based on the MS– 

DRG for the organ transplant. Payment 

for organ acquisition costs as described 

at 42 CFR 413.402, which include costs 

associated with beneficiary and donor 

evaluation, is made on a reasonable cost 

basis. To remain active on the transplant 

waitlist, candidates must meet a variety 

of criteria, including annual screenings 

for cardiovascular diseases and cancers. 

In the IOTA Model, CMS proposed 

two-sided performance-based payments 

for ‘‘Medicare kidney transplants,’’ 

defined as kidney transplants furnished 

to attributed patients whose primary or 

secondary insurance is Medicare FFS, as 

identified in Medicare FFS claims with 

MS–DRGs 008, 019, 650, 651 and 652, 

and as illustrated in Table 12. We stated 

that this APM design aligns with the 

Health Care Payment Learning & Action 

Network (LAN) Category 3 APM 

framework in which IOTA participants 

continue to be paid on the basis of 

Medicare FFS, but a retrospective 

annual attribution reconciliation and 

performance assessment after the end of 

each model PY is conducted to 

determine performance-based 

payments.286 287

The IOTA Model’s performance-based 

payments are linked to existing 

Medicare Part A and Part B services for 

kidney transplants, and align with other 

Innovation Center models’ payment 

structure, including the ETC Model 

where upward and downward 

adjustments are made to certain 

Medicare payments under the ESRD 

Prospective Payment System and 

Physician Fee Schedule depending on 

an ETC Participant’s performance at the 

aggregation group level under the 

model. The difference between ETC and 

the IOTA Model, for example, is how 

these retrospective adjustments would 

be paid or recouped by CMS. CMS did 

not propose to adjust existing Medicare 

IPPS payments for kidney transplants 

furnished to Medicare beneficiaries. 

Instead, CMS proposed to make 

performance-based payments to IOTA 

participants separate from claims-based 

payments. 


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We proposed to base performancebased payments on increasing the 

number of transplants and other metrics 

of efficiency and quality because we 

believe this approach: (1) would be a 

strong proxy for total cost; (2) directly 

aligns with the model’s goal of 

increasing access to and the volume of 

kidney transplantations; (3) 

acknowledges kidney waitlist and 

transplant patients are high-cost and 

high-need, making performance based 

on total cost of care unfair for IOTA 

participants with lower volume and 

fewer capabilities and resources given 

the increased opportunity for outliers; 

and (4) may safeguard against 

unintended consequences introduced by 

defining value based on cost for an 

attributed patient population already at 

high-risk, such as inappropriate cost 

shifting and widening access to care 

disparities. We theorize that increasing 

the number of, and access to, kidney 

transplants alone would result in better 

quality. As indicated in our estimates 

presented in section IV of this final rule, 

it would also result in savings to 

Medicare. 

While we proposed to assess model 

performance for each IOTA participant 

for all attributed patients regardless of 

payer type, as described in section 

III.C.6.c of this final rule, we proposed 

model performance-based payments that 

would only be based on kidney 

transplants furnished to attributed 

patients with Medicare FFS as their 

primary or secondary insurance. 

As described in section III.C.6.b of the 

proposed rule, we considered also 

basing the model performance-based 

payments on kidney transplants 

furnished to attributed patients enrolled 

in Medicare Advantage (MA), as kidney 

transplants are a Medicare-covered 

service that MA plans must also cover. 

As these payments would be made to 

kidney transplant hospitals, a potential 

waiver of section 1851(i)(2) of the Act, 

which provides that only the MA plan 

shall be entitled to payments for 

services furnished to the beneficiary, 

may have been necessary to apply the 

payments to attributed patients enrolled 

in MA. Because further consideration 

was needed for the implications of such 

a potential waiver, we did not propose 

to apply model performance-based 

payments performed on attributed 

patients enrolled in MA. 

We believed that the benefits of 

applying model performance-based 

payments to transplants furnished to 

attributed patients enrolled in MA 

would be recognizing the growth in MA 

enrollment relative to Medicare FFS 

enrollment, strengthening the model test 

through aligned payment incentives 

across payers, and protecting against 

unintended consequences of 

incentivizing inappropriate organ offer 

acceptance based on payer type. 

However, we did not propose to base 

payments on attributed patients 

enrolled in MA because of concerns 

about potentially waiving section 

1851(i)(2) of the Act. This provision 

states that only the MA plan is entitled 

to payments for services provided to the 

beneficiary. We noted that waiving this 

requirement would be unprecedented 

and the effects are unknown. We 

recognized that the proposed incentives 

in the IOTA Model would have a larger 

effect if kidney transplant hospitals 

were receiving performance-based 

payments based on their entire panel of 

attributed beneficiaries who receive 

transplants, and not just based on 

transplants for attributed beneficiaries 

with Medicare FFS as their primary or 

secondary insurance. To that end, we 

proposed that the IOTA Model would 

encourage multi-payer alignment with 

the goal of aligning on goals, incentives, 

and quality. We noted in the proposed 

rule that CMS intended to engage with 

the payer community, including MA, 

Medicaid, and commercial payers, in 

future years to discuss opportunities 

and approaches for alignment. 

We requested comment and feedback, 

especially from MA plans, on our 

decision not to calculate model 

performance-based payments to 

transplants furnished to attributed 

patients enrolled in MA. We were 

especially interested in comments that 

address how the Innovation Center 

should generally approach the growing 

MA population with the design of its 

models, which have traditionally been 

focused on the fee-for-service Medicare 

population. 

While kidney transplant hospitals are 

subject to value-based payment 

programs, some IOTA participants may 

have limited APM experience, 

resources, and capacity to meet model 

goals. We considered an upside-risk 

payment only framework that would 

still base model payments on kidney 

transplant utilization and other metrics 

of efficiency and quality. However, we 

believed that two-sided risk payments 

would be stronger incentives to achieve 

the desired goals. We also recognized 

this in the model design by proposing 

a phased-in approach to two-sided risk, 

with only upside-risk applied to the first 

model PY. We also considered other 

APM frameworks that would link 

performance to quality, such as pay-forreporting on the measures. We did not 

propose these frameworks, as they did 

not align with our goals of establishing 

two-sided risk accountability for IOTA 

participants. We recognized the benefits 

of a rewards-focused approach, 

particularly as it relates to quality 

performance, and we therefore did 

incorporate a rewards-focused 

performance scoring structure designed 

as pay-for-reporting and pay-forperformance within the quality domain 

performance assessment. (89 FR 43571). 

Another alternative we considered 

was a flat positive adjustment to the 

Medicare FFS payment for a kidney 

transplant based on the number of 

completed kidney transplants that an 

IOTA participant performs. Increasing 

the amount paid for completed kidney 

transplants through a FFS adjustment is 

the simplest policy and aligns with the 

IOTA Model’s focus on increasing the 

number of kidney transplants. 

Additionally, adjusting the FFS 

payment would directly incentivize an 

increase in the number of kidney 

transplants performed by IOTA 

participants. Under this approach, 

eligible claims would be identified 

utilizing Medicare claims data with 

Medicare Severity Diagnosis Related 

Groups (MS–DRGs) 008 (simultaneous 

pancreas-kidney transplant) and 652 


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008 

019 

650 

651 

652 

TABLE 12: MS-DRGs PROPOSED FOR INCLUSION IN DEFINITION OF 

MEDICARE KIDNEY TRANSPLANTS 

MS-DRG Description 

SIMULTANEOUS PANCREAS AND KIDNEY TRANSPLANT 

SIMULTANEOUS PANCREAS AND KIDNEY TRANSPLANT WITH HEMODIALYSIS 

KIDNEY TRANSPLANT WITH HEMODIAL YSIS WITH MCC 

KIDNEY TRANSPLANT WITH HEMODIAL YSIS WITHOUT MCC 

KIDNEY TRANSPLANT 
96382 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

288For instance, Aetna’s criteria is here: https:// 

www.aetna.com/content/dam/aetna/pdfs/ 

aetnacom/healthcare-professionals/documentsforms/Aetna-Institutes-of-Excellence.pdf. 

(kidney transplant); and claims with 

ICD–10 procedure codes 0TY00Z0 

(transplantation of right kidney, 

allogeneic, open approach), 0TY00Z1 

(transplantation of right kidney, 

syngeneic, open approach), 0TY00Z2 

(transplantation of right kidney, 

zooplastic, open approach) 0TY10Z0 

(transplantation of left kidney, 

allogeneic, open approach), 0TY10Z1 

(transplantation of left kidney, 

syngeneic, open approach), and 

0TY10Z2 (transplantation of left kidney, 

zooplastic, open approach). 

We did not propose a performance 

methodology based solely on adjusting 

the DRG payment for a kidney 

transplant, because this option would 

not encourage IOTA participants to 

focus on issues other than transplant 

volume, including equity, increased 

utilization of donor kidneys, quality of 

care, and patient outcomes, all of which 

are important parts of the transplant 

process where we believe performance 

is variable and can be improved. We 

further believe that the claims-only 

approach would not be as effective in 

incentivizing a continuous increase in 

transplants because IOTA participants 

that already have high kidney transplant 

volumes would be rewarded through 

increased reimbursements whether they 

improved year-over-year or not. Finally, 

we do not believe that this approach 

would provide any additional 

encouragement for IOTA participants to 

manage post-transplant care. 

We also considered establishing a 

payment for transplant waitlist 

management to encourage additional 

investment in the transplant process, 

but decided to focus more on the 

outcomes described in section III.C.5 of 

the proposed rule. Additionally, given 

that IOTA participants are already 

reimbursed at cost for efforts to manage 

beneficiaries on the waitlist, we did not 

believe an explicit additional payment 

would be necessary in this area. 

We sought feedback on our proposed 

alternative payment model design, data 

source to identify kidney transplants, 

and proposal to only apply model 

performance-based payments, both 

upside and downside, to Medicare FFS 

kidney transplants. We also sought 

feedback on alternative approaches 

considered, such as the alternative 

approach of including MA transplants. 

We welcomed input on how CMS may 

be able to work with multiple payers to 

ensure alignment with the IOTA Model. 

The following is a summary of the 

comments we received regarding our 

proposed alternative payment model 

design, data source to identify kidney 

transplants, our proposal to apply 

model performance-based payments and 

our alternative approach of including 

MA transplants, and our responses: 

Comment: We received over twenty 

comments urging CMS to apply the 

payment adjustments in the IOTA 

Model to transplants performed for 

beneficiaries with Medicare Advantage 

as a primary or secondary payer, and 

not just beneficiaries with Medicare FFS 

as a primary or secondary payer. 

Commenters pointed out the limited 

reach of the proposed incentives by 

focusing the incentives solely on a small 

portion of a kidney transplant hospital’s 

overall patient panel. They were 

worried that the model may be 

ineffective without the incentive effects 

provided by applying the payment 

adjustments in the IOTA Model to more 

than just Medicare FFS transplants. 

Many commenters also pointed out that 

there is a rising number of beneficiaries 

enrolling in Medicare Advantage 

relative to Medicare FFS, which would 

decrease the effects of the model’s 

proposed incentives over time. 

Commenters also pointed out that 

kidney transplant hospitals are paid 

directly through FFS Medicare for 

Organ Acquisition Costs for kidney 

transplants as defined in 42 CFR 

413.402, even for beneficiaries with 

Medicare Advantage, due to their 

statutory exclusion in § 1853(k)(5) of the 

Act. Another commenter pointed out 

that in other Medicare APMs operated 

by the Innovation Center, when a 

beneficiary has transitioned from FFS 

Medicare to Medicare Advantage, it has 

made them become ineligible for 

payments from the APM and 

discouraged potential investment in 

those beneficiaries. 

Response: We appreciate the feedback 

from commenters. However, we plan to 

finalize the policy as proposed as we do 

not believe that the additional incentive 

effects from including Medicare 

Advantage in the calculation for upside 

and downside payments are necessary 

at this point to provide sufficient 

incentive to test the model. We plan to 

further engage with Medicare Advantage 

plans to think about the incentives in 

the IOTA Model and those set up by 

Medicare Advantage plans. We also 

plan to monitor relative enrollment of 

beneficiaries who receive kidney 

transplants in Medicare FFS as opposed 

to Medicare Advantage to see if further 

policy changes will be necessary for 

future years of the IOTA Model. 

Comment: Multiple commenters 

expressed concern that the proposed 

payment structure for the IOTA Model, 

which would make payments based 

only on Medicare FFS kidney 

transplants, could lead to IOTA 

participants preferring to transplant 

Medicare FFS patients at the expense of 

patients with Medicare Advantage. 

Response: We appreciate the feedback 

from commenters as this is an outcome 

that we do not want. We recognize that 

the achievement domain is based on 

transplants performed across all payers 

and is worth the greatest number of 

points, which we believe will help to 

prevent this behavior. Additionally, we 

plan to monitor for potential shifts by 

payer as an unintended side effect of the 

model to ensure that this outcome does 

not occur, and we may consider taking 

additional action in future rulemaking if 

we see significant evidence that this is 

occurring. 

Comment: A commenter supported 

our proposed policy to exclude 

payments for beneficiaries with 

Medicare Advantage from the positive 

and negative payment adjustments in 

the Model. 

Response: We plan to monitor relative 

enrollment of beneficiaries who receive 

kidney transplants in Medicare FFS as 

opposed to Medicare Advantage to see 

if further policy changes will be 

necessary for future years of the IOTA 

Model. 

Comment: We received a comment 

urging CMS to align the payments in the 

IOTA Model with those from Medicare 

Advantage plans. 

Response: We recognize the 

importance of multi-payer alignment 

and has engaged in numerous 

conversations with Medicare Advantage 

plans about their transplant strategies. It 

is our understanding from discussions 

with MAOs that most MAOs use their 

COE programs to evaluate kidney 

transplant hospitals for network 

inclusion often provide them special 

contracting rates. Many plans use a 

variety of criteria to determine COE, 

including a minimum transplant 

volume, and minimum performance on 

certain outcomes metrics.288 We believe 

that IOTA participants’ quality 

improvement activities as a result of the 

model’s performance metrics and 

payment methodology may help them 

reach and maintain COE status. 

Comment: We received multiple 

comments urging CMS to include 

kidney transplants covered by other 

payers in the model’s payment 

methodology, particularly the Medicaid 

program. 

Response: Medicare is the dominant 

payer in the marketplace for transplants, 

accounting for 57 percent of adult 

transplants, relative to only 7 percent 


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for patients with Medicaid. As such, we 

believe that testing the model payment 

incentives based on just those 

transplants for beneficiaries with 

Medicare will provide sufficient 

incentive to drive the increases in 

transplants that CMS is hoping will 

occur from the Model. Additionally, 

transplants provide additional savings 

for the Medicare program given that 

patients may become entitled to 

Medicare based on ESRD, and given that 

Medicare is the primary payer for 

services for the majority of patients with 

ESRD across the country. 

However, we urge other payers, 

including private plans, to follow the 

lead of CMS and learn from the lessons 

we glean from this Model to evaluate 

how they pay kidney transplant 

hospitals to incentivize quality care and 

better outcomes. 

As a result, we believe that applying 

these payments in the IOTA Model to 

all Medicare FFS transplants will apply 

a strong incentive for IOTA participants 

to increase access to kidney 

transplantation given Medicare’s 

dominant role in the marketplace. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

our proposed definition of Medicare 

kidney transplants at § 512.402 without 

modification. 

c. Performance-Based Payment Method 

We proposed that the final 

performance score as described in 

section III.C.5. of this final rule would 

determine if and how an IOTA 

participant qualifies for an upside risk 

payment, falls in the neutral zone, or 

qualifies for a downside risk payment, 

proposed using a two-step process. 

First, we would determine if an IOTA 

participant’s final performance score 

qualifies the IOTA participant for 

upside risk payments, downside risk 

payments, or the neutral zone, as 

described in section III.C.6.c.(1). of this 

final rule. Second, we would apply the 

proposed calculation formula for each of 

type of payment, as described in section 

III.C.6.c.(2). of this final rule. 

Ultimately, we proposed a performancebased payment method that prioritizes 

the following principles: 

• Significant weight should be given 

to performance in the achievement 

domain, representing up to 60 points 

relative to a 100 maximum performance 

score, in alignment with the primary 

goals of the model to increase number 

of kidney transplants. 

• The magnitude of performancebased payments should be tied to 

relative number of kidney transplants, 

given significant differentials across 

kidney transplant hospitals nationally. 

• The largest performance-based 

payments amount in total dollars should 

go to IOTA participants that perform the 

most transplants because they are 

removing the most people from dialysis 

and creating the largest quality 

improvement and cost savings for the 

Medicare Trust Fund. 

• The payments need to be calibrated 

to provide an incentive to IOTA 

participants, but still ensure net savings 

to Medicare based on the analysis 

performed by OACT in section IV of this 

final rule. 

• The mechanisms should recognize 

that CMS has not previously offered 

kidney transplant hospitals a valuebased care payment model around 

transplantation and should provide a 

transition to any form of downside risk 

to allow for an opportunity to become 

familiar with the value-based care 

process. 

• Limit operational complexity for 

both IOTA participants and CMS to 

avoid any potential for errors. 

(1) Determine Final Performance Score 

Range Category 

We proposed to establish three final 

performance score range categories, as 

illustrated in Table 13, that dictate 

which type of performance-based 

payment would apply to an IOTA 

participant for a given PY. 

We proposed at § 512.402 to define 

‘‘upside risk payment’’ as a lump sum 

payment that CMS would make to an 

IOTA participant if the IOTA 

participant’s final performance score for 

a PY falls within the payment range 

specified in section III.C.6.c(2)(a) of this 

final rule. As proposed and indicated in 

Table 13, if in PY 1–6, an IOTA 

participant’s final performance score is 

greater than or equal to 60 points, the 

IOTA participant would qualify for an 

upside risk payment. 

We proposed at § 512.402 to define 

‘‘neutral zone’’ as the final performance 

score range in which the IOTA 

participant would not owe a downside 

risk payment to CMS or receive an 

upside-risk payment from CMS if the 

IOTA participant’s final performance 

score falls within the ranges specified in 

section III.C.6.c.(2).(c). of this final rule. 

In the first year of the model, we 

proposed that the neutral zone would 

apply for final performance scores 

below 60. As such, only upside 

payments and the neutral zone would 

exist in PY 1. We also proposed that the 

neutral zone in PYs 2–6 would apply for 

final performance scores of 41–59 

(inclusive). We believe that average 

performance should yield no upside or 

downside risk payment. 

We proposed at § 512.402 to define 

‘‘downside risk payment’’ as a lump 

sum payment the IOTA participant 

would be required to pay to CMS after 

a PY if the IOTA participant’s final 

performance score falls within the 

ranges specified in section 

III.C.6.c.(2).(b). of this final rule. We 

proposed that there will be no downside 

risk payment in the PY 1. We proposed 

no downside risk payment in the first 

PY to allow IOTA participants time to 

implement changes to improve 

performance prior to facing downside 

risk. In PYs 2–6, we proposed to 

introduce downside risk payments. We 

proposed that an IOTA participant’s 

final performance score of 40 or below 

in PYs 2–6, would result in a downside 

risk payment. We believe that below 

average performance should yield a 

downside risk payment. 

The performance assessment scoring 

method, as described in section III.C.5. 

of this final rule, was designed such that 

IOTA participants with limited 

experience in APMs would still be 

likely to achieve a sufficient final 

performance score that would result in 

no downside risk payment. For 

example, it is expected that most IOTA 

participants would earn around 30 of 60 

possible points in the achievement 

domain. We believe that average 

performance should be neither 

rewarded nor penalized. We also 

considered eliminating the neutral zone 

and only applying upside and downside 

performance payments, narrowing the 

neutral zone score range (that is, 44–55), 

or applying a wider-to-narrower phasedin approach over the model 

performance period. We believed these 

alternative options would be less 

flexible and more penalty-focused, with 

some IOTA participants more likely to 

be penalized due to varying degrees of 

capabilities and capacity that would 

limit their ability to achieve 

performance targets as they progress and 

evolve over the model performance 

period. Thus, we proposed a neutral 

zone that would allow for more 

opportunities and incentives to achieve 

improvements over time without a large 

probability of downside risk. 


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96384 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

We sought feedback on the use of the 

final performance scores to determine 

the upside risk payment, the downside 

risk payment, and the neutral zone. 

The following is a summary of the 

comments received on our proposal to 

use the final performance scores to 

determine the upside risk payment, the 

downside risk payment, the neutral 

zone and our responses: 

Comment: We received multiple 

comments urging a delay of downside 

payments until PY 3 or PY 4 of the 

model. 

Response: We believe that downside 

risk is an important part of testing 

models. We recognize the importance of 

transition into the model, but our 

thought is that the six-month starting 

delay, along with no downside risk in 

PY 1 allows for times for IOTA 

Participants to invest and transition into 

the accountability of the model, while 

still allowing for increased 

accountability in future years of the 

model. 

Comment: A commenter noted that 

IOTA participants would not receive 

their PY 1 results until PY 2, 

diminishing the impact of the initial 

year’s lack of downside risk. 

Response: We understand that IOTA 

participants will not receive final results 

until into PY 2, but we know that IOTA 

participants are able to track their 

number of transplants done and their 

post-transplant outcomes. To help IOTA 

participants to better project their 

potential results, CMS will also share 

interim data reports with IOTA 

participants. 

Comment: We received comments 

urging that we lower the top of the 

neutral zone from 60 to 50 points. 

Response: In designing the scoring 

system, CMS wanted to make sure that 

performance was evaluated 

symmetrically, such that it would take 

excellent performance or performance 

far below what was expected to be able 

to get a positive or negative payment 

adjustment. Additionally, given the 

breakdown of quality points for PY 1, 

we believe that reaching a positive 

payment adjustment will be more 

achievable for IOTA participants to be 

able to earn a positive payment 

adjustment. 

Comment: We received multiple 

comments recommending that we lower 

the points required for a downside risk 

adjustment, including one 

recommending lowering the threshold 

to 20 points. 

Response: We considered this 

recommendation but decided to keep it 

at 40 points to balance all the different 

goals on the model. Given that an IOTA 

participant performing as expected on 

the achievement and efficiency domains 

would receive 40 points, the proposed 

scoring methodology is our attempt to 

balance the goals of being fair to IOTA 

participants, while also attempting to 

incentivize improvement on the IOTA 

performance metrics. 

After consideration of the public 

comments we received, we are 

finalizing our proposal to use the final 

performance scores to determine the 

upside risk payment, the downside risk 

payment, and the neutral zone as 

proposed without modification at 

§ 512.430(a). Additionally, we are 

finalizing as proposed the definitions of 

upside risk payment, and neutral zone 

at § 512.402 without modification. 

Finally, we are finalizing as proposed 

the definition of downside risk payment 

§ 512.402, with a minor technical 

correction to include the complete cross 

reference to § 512.430. 

(2) Apply Payment Calculation Formula 

to Final Performance Score 

In the proposed rule at § 512.430(a), 

we proposed that after determining if an 

IOTA participant’s final performance 

score qualifies the IOTA participant for 

an upside risk payment, downside risk 

payment, or the neutral zone, as 

described in section III.C.6.c(1) of this 

final rule, we would apply a calculation 

formula unique to each PY to the final 

performance score, as specified in 

sections III.C.6.c(2)(a) through (c) of this 

final rule. 

We are finalizing this provision 

without modification at § 512.430(a) and 

direct commenters to section III.C.6.c(1) 

of this final rule for discussion of the 

methodology for determining the final 

performance score and the use of the 

final performance scores to determine 

the upside risk payment, the downside 

risk payment, and the neutral zone. 

(a) Upside Risk Payment 

If, in PYs 1–6, an IOTA participant’s 

final performance score is greater than 

or equal to 60 points, we proposed that 

the IOTA participant would qualify for 

an upside risk payment. If an IOTA 

participant’s final performance score 

would qualify them for the upside risk 

payment, we proposed a methodology to 

calculate their upside risk payment 

using the formula in Equation 6 below, 

where: 

• $8,000 is a fixed, risk-based 

payment amount within the calculation 

formula, estimated to be about 33 

percent of the average Medicare FFS 

kidney transplant MS–DRG cost. We 

aimed to create a strong financial 

incentive with significant earning 

opportunity for IOTA participants that 

meet or exceed model performance 

expectations. We believe this amount or 

proportion of the MS–DRG to be a large 

financial incentive to promote behavior 

changes while maintaining expectations 

of net savings to Medicare. We 

calibrated this based on projection of 

the incentive effects that would 

encourage the necessary support and 

infrastructure investment needed to 

achieve high performance and produce 

overall model savings and have the 

effects that we are looking for. 

• The final performance score is the 

sum of points earned from the 

achievement domain, efficiency 

domain, and quality domain in a PY, as 

described in section III.C.5 of this final 

rule. 

• Medicare kidney transplants is the 

number of Medicare kidney transplants 

furnished by the IOTA participant in a 

PY. 

Equation 6: Proposed Upside Risk 

Payment Calculation Formula 

Upside Risk Payment = $8,000 * (( Final 

Performance Score¥60)/40) * 

Medicare Kidney Transplants 

We also considered calculating the 

maximum positive multiplier per 

Medicare kidney transplant claim based 

on the Kidney Transplant Bonus in the 

KCC Model. In 2019, the Kidney 

Transplant Bonus for entities 

participating in the KCC Model was set 

to $15,000. Adjusted for inflation, this is 

roughly $18,000, which would be the 


ddrumheller on DSK120RN23PROD with RULES2ER04DE24.017</GPH>

TABLE 13. PROPOSED PERFORMANCE-BASED PAYMENTS BY FINAL 

PERFORMANCE SCORE 

Final Performance Score PYl PY2-6 

60-100 Upside Risk Payment Upside Risk Payment 

41-59 Neutral Zone Neutral Zone 

0 - 40 Neutral Zone Downside Risk Payment 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96385 

maximum allowable positive bonus 

payment per transplant. The Kidney 

Transplant Bonus was originally 

calculated based on the difference in 

spending between a beneficiary who 

went on to get a transplant and the 

average ESRD beneficiary cost. 

However, we believed that the 

maximum positive adjustment may be 

too large in relation to current Medicare 

payments for kidney transplants for the 

model to yield net savings. 

We also considered using a system 

similar to the Hospital VBP Program 

under which CMS withholds 2 percent 

of participating’s hospitals Medicare 

payments and uses the sum of these 

reductions to fund value-based 

incentive payments to hospitals based 

on their performance under the 

program. However, we wished to have 

the opportunity for both upside and 

downside across IOTA participants to 

most effectively incentivize 

performance in the model. 

We also considered adjusting the 

maximum upside multiplier in PYs 2– 

6; however, we felt making that decision 

prior to the start of the model would be 

premature and wish to understand 

IOTA participant performance before 

making such a decision. 

We sought comment on our proposed 

methodology to calculate the upside risk 

payment and alternatives considered. 

The following is a summary of the 

comments received on our proposed 

methodology to calculate the upside risk 

payment, alternatives considered and 

our responses: 

Comment: We received many 

comments saying that the proposed 

payment amount was not high enough 

to incentivize performance in the 

model. Commenters pointed out a 

concern that they lose money on kidney 

transplants, based on the difference 

between their cost and the Medicare 

FFS DRG payments and that an 

increased number of transplants would 

be more likely to come from using more 

complex organs, which would be more 

expensive for the IOTA participants. 

Many commenters also believed that the 

proposed maximum upside amount of 

$8,000 would not be sufficient to 

incentivize investment by hospital 

leadership, particularly given that the 

payment amount was only proposed to 

be applied to Medicare FFS kidney 

transplants. 

Response: We appreciate the feedback 

from commenters and recognize the 

validity of the concerns expressed. The 

IOTA Model is designed to save money 

for CMS, improve care for beneficiaries, 

to save money for Medicare, and to 

increase payments to IOTA participants 

who do more transplants. To effectively 

accomplish those goals, the incentives 

must be effectively calibrated high 

enough to incentivize improved 

performance, while still ensuring 

sufficient savings for CMS. We believe 

that applying the payment adjustments 

to all Medicare kidney transplants, as 

discussed previously will help to 

increase the incentives in the model and 

account for the changing nature of the 

Medicare program. Additionally, the 

CMS Office of the Actuary conducted 

additional analyses and determined that 

CMS would still be able to see projected 

savings of $22 million if the maximum 

upward adjustment were raised to 

$15,000. We considered this alternative 

based on the Kidney Transplant Bonus 

in the KCC Model, which was designed 

to reflect the net savings to the Medicare 

Trust Fund from a patient who is 

transplanted. Our analyses also show an 

average cost in 2023 of approximately 

$40,000 for performing MS–DRG 650, 

which is billed for Kidney transplants 

that then require hemodialysis 

afterwards. We recognize that many of 

the kidney transplants that will be 

performed under the IOTA Model may 

be for more complex organs that require 

hemodialysis after being transplanted 

and wants to recognize the increased 

costs to the IOTA participants for the 

transplant surgery and recovery when 

that occurs. Given that costs will grow 

over the course of the model period 

until 2030, we believe that it is 

appropriate to take approximately 1⁄3 of 

those costs to calculate the maximum 

upward adjustment, as we did for the 

average payment in the proposed rule, 

to also come up with the $15,000 figure. 

We proposed to keep this figure flat over 

the course of the model, given that it 

already accounts for some level of cost 

growth over the six-year period of the 

model. We will also evaluate the effects 

of this maximum upward adjustment 

and consider updating the amount 

based on the incentive effects and CMS 

savings. 

Comment: We received multiple 

comments arguing that higher risk 

candidates are more expensive and are 

the ones who are likely to receive 

transplants based on the incentives in 

the model. Commenters urged CMS to 

base payment amounts on DRGs for 

more complex transplant surgeries given 

this concern. 

Response: We recognize this concern 

from commenters and, as described in 

comment responses in this section, are 

finalizing an increased maximum 

upside risk payment amount of $15,000, 

based on the increased costs of DRG– 

650, which CMS projects may be 

necessary to be billed for the use of 

more complex organs. 

Comment: Multiple commenters 

suggested that CMS should base the 

upward risk payment amount on the 

Kidney Transplant Bonus from the 

Kidney Care Choices Model. 

Response: We recognize the validity 

of these comments and adjusted the 

amount upwards to be similar to the 

amount that the Innovation Center paid 

out in the KCC Model. 

Comment: We received a comment 

expressing concern that the maximum 

upward payment amounts would not be 

sufficient to support IOTA collaborators, 

given that they would only be used by 

IOTA participants. 

Response: We recognize the 

commenter’s concern and believe that 

the increased payment amounts and 

increased overall payments by 

accounting for all Medicare kidney 

transplants gives the opportunity for 

IOTA participants to earn enough 

upward payments through the model to 

be able to support collaboration with 

IOTA collaborators. 

Comment: We received a comment 

from commenters that the maximum 

upward adjustment should increase 

over the years of the model. 

Response: We recognize that costs 

have historically risen over time and 

CMS payments have gone up. As a 

result, the updated payment amount is 

based on a projected rise in costs from 

the 2023 costs of MS–DRG 650 of 

$40,151. We are taking slightly more 

than 1⁄3 of that amount and keeping it 

as a flat rate for all six years of the 

model to help account for a potential 

rise in costs in the future. We may also 

re-evaluate the effects of the maximum 

adjustment over time based on any 

potential future rise in payments and 

the effects on the Medicare Trust Fund. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

our proposed methodology to calculate 

the upside risk payment upside risk 

payment at § 512.430(b)(1), with slight 

modifications. Specifically, we are 

making a technical correction at 

§ 512.430(b)(1)(i) to remove the 

following verbiage: from 100. In the 

proposed rule at 89 FR 43572, we 

proposed that the upside risk payment 

would be calculated by subtracting 60 

from the IOTA participant’s final 

performance score, as outlined in 

Equation 2 of section III.C.6.c(2)(a) of 

the proposed rule. As such, we are 

finalizing at § 512.430(b)(1)(i) that CMS 

subtracts 60 from the IOTA participant’s 

final performance score. We are also 

modifying our regulation at 

§ 512.430(b)(1)(iii) to reflect a maximum 

upside risk payment multiplier amount 

of $15,000 (see Equation 7). 


ddrumheller on DSK120RN23PROD with RULES2
96386 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

Lastly, we are finalizing our proposed 

definition of Medicare kidney 

transplants at § 512.402 without 

modification, as described and finalized 

in section III.C.6(b) of this final rule. 

Equation 7: Upside Risk Payment 

Calculation Formula 

(b) Downside Risk Payment 

If an IOTA participant’s final 

performance score is at or below 40 

points in PYs 2–6, the IOTA participant 

would qualify for a downside risk 

payment. If an IOTA participant 

qualifies for a downside risk payment, 

we describe the methodology to 

calculate their downside risk payment 

risk using the formula in Equation 8: 

Equation 8: Proposed Downside Risk 

Payment Calculation Formula 

Downside Risk Payment= $2,000 * 

((40¥Final Performance Score)/40) 

* Medicare Kidney Transplants 

• $2,000 is a fixed, risk-based 

payment amount within the calculation 

formula, estimated to be about onetwelfth, or 8 percent, of the average 

Medicare FFS kidney transplant MS– 

DRG cost. We proposed a lower 

downside-risk value relative to the 

upside-risk value proposed for the 

upside risk payments (about one-fourth 

lower) because we wanted to maintain 

a greater rewards approach, while still 

holding IOTA participants accountable 

for poor performance. We also believe 

that this approach is more flexible and 

accommodating to IOTA participants 

with no, or limited, APM experience, or 

that are more limited in terms of 

resources and capabilities. 

• The final performance score is the 

sum of points earned from the 

achievement domain, efficiency 

domain, and quality domain, as 

described in section III.C.5. of this final 

rule. 

• Medicare kidney transplants is the 

count of furnished Medicare kidney 

transplants during the PY. 

We also considered applying the same 

fixed amount to both the upside and 

downside risk payment ($8,000 or 

$2,000 in both) or having the downside 

risk payment be 50 percent of the fixed 

amount of the upside risk payment 

($4,000) but opted against it to maintain 

lower levels of risk given the fact that 

this model would be mandatory for 

eligible kidney hospitals. As discussed 

in section III.C.6.b of this final rule, we 

considered an upside-risk only payment 

framework, thus eliminating the 

application of downside-risk payments. 

Recognizing the potential for volatility 

in performance year-over-year, we also 

considered requiring IOTA participants 

to owe downside-risk payments to CMS 

if their final performance score was at 

or below 40 for more than one PY, 

starting from PY 1, potentially giving 

IOTA participants a similar phased-in, 

or, rather, ramp-up, opportunity to 

adjust and improve before downsiderisk payments kick in. We considered 

this option to be unnecessary and 

operationally complex, particularly as it 

would function in a similar way as our 

proposed approach from a phasing-in 

standpoint. We also considered 

adjusting the $2,000 fixed, risk-based 

payment amount for PYs 2–6; however, 

we believe a fixed amount would 

provide greater transparency to IOTA 

participants on financial risk and model 

implementation experience would 

better inform if this approach would be 

necessary. 

We sought comment on our proposed 

downside risk payment calculation 

formula, and alternatives considered. 

The following is a summary of the 

comments received on our proposed 

downside risk payment calculation 

formula, alternatives considered, and 

our responses: 

Comment: A couple commenters 

suggested that we should increase the 

maximum downside risk payment. To 

encourage greater engagement from 

IOTA participants who are likely to 

struggle, a commenter recommended 

two changes: (1) Lowering the proposed 

final performance score threshold for 

the downside risk payment zone in PY 

2 from less than 40 points to less than 

20 points, and (2) Increasing the 

maximum downside risk payment 

amount to ¥$4000 per Medicare kidney 

transplant. The commenter believed that 

by decreasing the likelihood of failure 

but increasing its consequences, CMS 

would ensure that only IOTA 

participants who actively choose not to 

engage would face negative 

repercussions. Another commenter 

proposed increasing the maximum 

downside risk payment for each 

Medicare kidney transplant from the 

proposed $2,000 to $3,750. They 

believed the IOTA Model incentives 

must be substantial enough to capture 

the attention of transplant hospital and 

health system administrators, while the 

downside risk payment should be high 

enough to motivate IOTA participants to 

avoid incurring it entirely. 

Another commenter pointed out that 

IOTA participants who abstain from 

participating risk termination from the 

model and may face penalties. 

Specifically, under the proposed rule, 

terminated IOTA participants could be 

liable for a penalty in the PY of their 

termination and may have to refund any 

upside risk payments from previous 

PYs. The commenter further noted that 

IOTA participants could view the 

penalty as a low-cost way to avoid 

accountability in the model through 

2031. The commenter also pointed out 

that the shrinking pool of Medicare FFS 

patients, has the same effect of reducing 

both upside risk payments and 

downside risk payments. Based on these 

concerns, the commenter urged CMS to 

reconsider how it calculates downside 

risk payments, and at minimum, to 

apply the same $8,000 fixed amount 

used in the upside risk payment 

calculation to the downside risk 

payment calculation. 

Response: We thank the commenters 

for their suggestions. In putting 

downside risk in the model, we are 

attempting to incentivize improved 

performance on the IOTA metrics, while 

also attempting to not make the model 

too punitive for IOTA participants. As 

such, we will be finalizing the 

maximum downside risk payment as 

proposed. We will evaluate the effects of 

our payment methodology and may 

propose raising the maximum downside 

risk payment if we are not seeing the 

level of change that we are hoping for 

in future notice and comment rule 

making 


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Upside Risk Payment 

_ * (Final Performance Score - 60) - $15,000 40 

* Medicare Kidney Transplants 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96387 

Comment: A commenter urged that 

CMS make the proposed maximum 

downside risk payment proportional to 

the proposed maximum upside risk 

payment. 

Response: The model was designed 

with asymmetric upside and downside 

risk in recognition of the benefits 

provided by transplant to the Medicare 

Trust Fund and the desire of CMS to not 

be overly punitive in a mandatory 

model. We plan to test out the effects of 

a $2,000 maximum downside risk 

payment to assess its effects on the 

metrics in the IOTA Model. Based on 

the results, we may consider increasing 

the maximum downward amount in 

future notice and comment rule making. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

the proposed provision for calculating 

the downside risk payment at 

§ 512.430(b)(3), without modification.. 

We also note that we are finalizing, as 

proposed, the definition of Medicare 

kidney transplants at § 512.402 without 

modification, as described and finalized 

in section III.C.6(b) of this final rule. 

(c) Neutral Zone 

If, in PY 1, an IOTA participant’s final 

performance score was below 60 points, 

or if, in PYs 2–6, an IOTA participant’s 

final performance score was between 41 

and 59 (inclusive), we proposed that the 

final performance score, as described in 

section III.C.6.c.(1). of this final rule, 

would qualify the IOTA participant for 

the neutral zone, where no upside risk 

payment or downside risk payment 

would apply. As such, in a PY where an 

IOTA participant’s final performance 

score falls in the neutral zone, no money 

would be paid to the IOTA participant 

by CMS, nor would money be owed by 

the IOTA participant to CMS. 

We sought comment on our proposed 

neutral zone. 

Comment: Multiple comments urge 

constricting the neutral zone to make it 

more likely that an IOTA participant 

would receive a positive or negative 

payment adjustment. 

Response: To begin the model, we 

plan to keep the neutral zone as 

designed. Our goal is to recognize both 

excellent performers and those that fall 

far below expectations and ensure that 

only those IOTA participants receive a 

positive or negative payment 

adjustment. We will evaluate how many 

IOTA participants fall into the neutral 

zone and consider constriction in the 

future. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

the neutral zone provisions at 

§ 512.430(b)(2) as proposed without 

modification. 

(3) Payments Operations and Timelines 

After the end of each PY, CMS would 

assess each IOTA participant’s 

performance in accordance with section 

III.C.5. of this final rule and calculate 

performance-based payments in 

accordance with the methodology 

specified in section III.C.6.c. of this final 

rule. We proposed to define this process 

as ‘‘preliminary performance assessment 

and payment calculations.’’ 

We proposed that CMS would 

conduct and calculate preliminary 

performance assessment and payment 

calculations at least 3 to 6 months after 

the end of each PY to allow for 

sufficient Medicare kidney transplant 

claims runout. We proposed that CMS 

would notify IOTA participants of their 

preliminary model performance 

assessment, including the IOTA 

participant’s score for each metric 

within the achievement domain, 

efficiency domain, and quality domain 

and the final performance score, and 

payment calculations with respect to 

any applicable upside risk payment or 

downside risk payment, at least 5 to 9 

months after the end of each PY, 

allowing for a two-to-three month 

period for CMS to conduct calculations 

after the claims runout period. We 

proposed that a 30-day notification 

period between preliminary and final 

calculations would apply, giving IOTA 

participants 30 days to review 

preliminary data and calculations and 

request targeted reviews, as described in 

section III.C.6.c.(4). of this final rule. 

This 30-day notification period would 

also be intended to provide IOTA 

participants with advance notice of 

forthcoming performance-based 

payments before upside risk payments 

or demand letters for downside risk 

payments would be issued by CMS. We 

also proposed that CMS would notify 

IOTA participants of their model 

performance assessment and payment 

calculations in a form and manner 

determined by CMS, such as letters, 

email, or model dashboard. We 

proposed that CMS would notify the 

IOTA participant of their final 

performance score and any associated 

upside risk payment or downside risk 

payment at least 30 days after notifying 

the IOTA participant of their 

preliminary model performance 

assessment and payment calculations. 

We proposed that after CMS notifies 

the IOTA participant of their final 

performance score and any associated 

upside risk payment and by a date 

determined by CMS, CMS would issue 

the upside risk payment to the tax 

identification number (TIN) on file for 

the IOTA participant in the Medicare 

Provider Enrollment, Chain, and 

Ownership System (PECOS). 

We proposed that after CMS notifies 

the IOTA participant of their final 

performance score and any associated 

downside risk payment and by a date 

determined by CMS, CMS would issue 

a demand letter to the TIN on file in 

PECOS for the IOTA participant for 

downside risk payments owed to CMS, 

with a payment due date of at least 60 

days after the date on which the 

demand letter is issued. We proposed 

that the demand letter would include 

details on model performance, the 

downside risk payment, and how 

payments would be made to CMS. 

Rather than the proposed lump-sum 

payment and demand letter approach, 

we also considered making the upside 

risk payments and downside risk 

payments to IOTA participants in the 

form of Medicare FFS claim 

adjustments. The benefit of this 

approach would be that upside risk 

payments and downside risk payments, 

which are retrospective, would be 

applied prospectively and spread out 

over a 12-month period, so that a 

transplant hospital would not need to 

pay back to CMS a large sum of monies 

owed all at once. However, we believe 

that this approach would delay model 

payments and collection of monies 

owed to CMS. We also consider this 

approach to be disruptive to standard 

claims processing systems and 

operationally complex, with more 

opportunities for error and less 

flexibility to correct errors in a timely 

manner. 

We sought comment on our proposed 

payment operations and timeline and 

alternative considered. 

The following is a summary of the 

comments received on our proposed 

payment operations and timeline, 

alternative considered and our 

responses: 

Comment: We received a comment 

approving of the payment operations 

timeline process. 

Response: We appreciate that 

comment and plan to finalize as 

proposed. 

Comment: We received a comment 

urging an alternative methodology for 

potential repayments that would allow 

an IOTA participant to mitigate the 

downside risk payments owed to CMS 

through an agreed upon strategy of 

process and performance improvement 

across various metrics. 

Response: We see this as an 

interesting idea, but ultimately decided 

to go with the proposed strategy of 

repayment to recognize the large 


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behavioral incentives of wanting to 

avoid writing a check to repay CMS. We 

also see that this process is inherently 

present in the model, given that 

performance on model measures resets 

each year. We also recognize that there 

is no downside risk in PY 1, and we 

hope that any IOTA participants with a 

final performance score below 40 who 

would otherwise have had to pay 

downside risk payments to CMS can use 

that as an opportunity for process 

improvement to avoid having to make 

downside risk payments for PY 2. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

these provisions without modification at 

§ 512.430(d). We are also finalizing the 

definition of preliminary performance 

assessment and payment calculations at 

§ 512.402, without modification. 

(4) Targeted Review 

We believe that CMS calculation 

errors are possible, and therefore IOTA 

participants should be able to dispute 

the results of calculations. 

Thus, upon receipt of CMS issued 

notifications of preliminary 

performance assessment and payment 

calculations, as described in section 

III.C.6.c(3) of this final rule, we 

proposed at § 512.434 that IOTA 

participants may appeal via a ‘‘targeted 

review process,’’ defined as the process 

in which an IOTA participant could 

dispute performance assessment and 

payment calculations made, and issued, 

by CMS. 

We proposed at § 512.434(a) that an 

IOTA participant would be able to 

request a targeted review for one or 

more calculations made and issued by 

CMS within the preliminary 

performance assessment and payment 

calculations. We proposed at 

§§ 512.434(a)(1) and (2) that an IOTA 

participant would be able to request a 

targeted review for CMS consideration 

if— 

• The IOTA participant believes an 

error occurred in calculations due to 

data quality or other issues; or 

• The IOTA participant believes an 

error occurred in calculations due to 

misapplication of methodology. 

We proposed at § 512.434(b)(1) that an 

IOTA participant would be required to 

submit a targeted review request within 

30 days, or another time period as 

specified by CMS, of receiving its 

preliminary performance assessment 

and payment calculations from CMS. 

We also proposed at § 512.434(b)(2) that 

the request would require supporting 

information from the IOTA participant, 

in a form and manner specified by CMS. 

The 30-day window to appeal generally 

aligns with the length of time we have 

finalized for submitting appeals in other 

CMS models, such as the ETC Model, as 

well as under the Hospital VBP 

Program, and we believed would allow 

ample time for IOTA participants to 

separately review CMS calculations. 

We proposed at § 512.434(c) that the 

targeted review process would not 

provide IOTA participants the ability to 

dispute policy and methodology, as it 

would be limited to the dispute of 

calculations. Specifically, we proposed 

at § 512.434(c)(1) that CMS would not 

consider targeted review requests 

regarding, without limitation, the 

following: 

• The selection of the kidney 

transplant hospital to be an IOTA 

participant. 

• The attribution of IOTA waitlist 

patients and the attribution of IOTA 

transplant patients to the IOTA 

participant, or to any other kidney 

transplant hospital selected for 

participation in the IOTA Model, or to 

any kidney transplant hospital not 

selected for participation in the IOTA 

Model. 

• The methodology used for 

determining the achievement domain, 

efficiency domain, and quality domain. 

• The methodology used for 

calculating and assigning points for 

each metric within the achievement 

domain, efficiency domain, and quality 

domain. 

• The methodology used for 

calculating the payment amount per 

Medicare kidney transplant paid to an 

IOTA participant. 

We proposed § 512.434(c)(2) that a 

targeted review request that includes 

one or more of the exclusions under 

§ 512.434(c)(1) could still be reviewed 

by CMS, given that all remaining 

considerations of the request meet all 

other criteria for consideration by CMS. 

Upon receipt of a targeted review 

request from an IOTA participant, we 

proposed at § 512.434(d)(1) that CMS 

would conduct an initial assessment 

and final assessment of the targeted 

review. We believed that this proposal 

would be in line with other CMS 

models. 

The CMS targeted review initial 

assessment would determine if the 

targeted review request met the targeted 

review requirements and contained 

sufficient information to substantiate 

the request. If the request was not 

compliant with the requirements or 

required additional information, CMS 

would follow up with IOTA participants 

to request additional information in a 

form and manner determined by CMS. 

Any additional information that CMS 

requests from an IOTA participant 

would be due to CMS within 30 days of 

CMS’s request, also in a form and 

manner determined by CMS. An IOTA 

participant’s non-responsiveness to the 

request for additional information from 

CMS could result in the closure of the 

targeted review request. 

In a final assessment, CMS would 

determine whether it erred in a 

calculation, as disputed by the IOTA 

participant. 

CMS’s correction of an error may 

delay the date of payment of an IOTA 

participant’s upside risk payments or 

downside risk payments. 

We stated in the proposed rule that 

were a calculation error to be found as 

a result of an IOTA participant’s 

targeted review request, we would 

notify the IOTA participant within 30 

days of any findings in a form and 

manner determined by CMS and resolve 

and correct the error and discrepancy in 

the amount of the upside risk payment 

or downside risk payment in a time and 

manner as determined by CMS. 

We proposed at § 512.434(d)(2) that 

targeted review decisions made by CMS 

would be final, unless submitted by the 

IOTA participant or CMS for a CMS 

Administrator review. We also proposed 

to include the reconsideration 

determination process as outlined in 

proposed § 512.190 in the IOTA Model. 

We noted that if an IOTA participant 

has regular Medicare FFS claims issues 

or decisions that it wishes to appeal 

(that is, issues during the model 

performance period with Medicare FFS 

that are unrelated to the model 

performance and payment calculations 

and payments), then the IOTA 

participant should continue to use the 

standard CMS procedures. Section 1869 

of the Act provides for a process for 

Medicare beneficiaries, providers, and 

suppliers to appeal certain claims and 

decisions made by CMS. 

We sought comment on our proposals 

regarding the process by which an IOTA 

participant could request a targeted 

review of CMS calculations. 

The following is a summary of the 

comments received on our proposals 

regarding the process by which an IOTA 

participant could request a targeted 

review of CMS calculations and our 

responses: 

Comment: We received a comment 

approving of the proposed targeted 

review process. 

Response: We that the commenter for 

their support and plan to finalize these 

provisions as proposed. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

the provisions for the proposed targeted 

review process at 512.434(d) without 


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modification. We are also finalizing the 

definition of targeted review process at 

§ 512.402, with a minor technical 

correction to update the cross reference. 

(5) Extreme and Uncontrollable 

Circumstances 

As we stated in the proposed rule, 

events may occur outside the purview 

and control of the IOTA participant that 

may affect their performance in the 

model (89 FR 43518). In the event of 

extreme and uncontrollable 

circumstances, such as a public health 

emergency, we proposed that CMS may 

reduce the downside risk payment, if 

any, prior to recoupment by an amount 

determined by multiplying the 

downside risk payment by the 

percentage of total months during the 

PY affected by an extreme and 

uncontrollable circumstance, by the 

percentage of attributed patients who 

reside in an area affected by the extreme 

and uncontrollable circumstance. We 

proposed to address only the downside 

risk payment under this policy, as we 

wish to mitigate the harm to entities due 

to extreme and uncontrollable 

circumstances. We considered applying 

this policy to upside risk payments and 

final performance scores in the neutral 

zone, but we believe that IOTA 

participants that have been able to 

achieve model success do not need to be 

made whole by this policy. 

We proposed at § 512.436(a)(1) to 

apply determinations made under the 

Quality Payment Program with respect 

to whether an extreme and 

uncontrollable circumstance has 

occurred, and the affected areas, during 

the PY. We chose the Quality Payment 

Program to align across Innovation 

Center models and CMS policy. We 

proposed at § 512.436(a)(2) that CMS 

has the sole discretion to determine the 

time period during which an extreme 

and uncontrollable circumstance 

occurred and the percentage of 

attributed patients residing in affected 

areas for the IOTA participant. 

We requested comment on our 

extreme and uncontrollable 

circumstances policy and whether the 

determinations by the Quality Payment 

Program that an extreme and 

uncontrollable circumstance have 

occurred should apply to IOTA 

participants. 

We did not receive any comments on 

this policy and therefore are finalizing 

these provisions without modification at 

§ 512.436. 

7. Data Sharing 

a. General 

As discussed in the proposed rule, we 

expect that IOTA participants would 

work toward independently identifying 

and producing their own data, through 

electronic health records, health 

information exchanges, or other means 

that they believe are necessary to best 

evaluate the health needs of their 

patients, improve health outcomes, and 

produce efficiencies in the provision 

and use of services. 

To assist IOTA participants in this 

process, we proposed to provide IOTA 

participants with certain beneficiaryidentifiable data for their Medicare 

beneficiaries who are attributed 

patients, upon request. We anticipated 

that IOTA participants would use this 

data to better assess transplant readiness 

and post-transplant outcomes. We also 

proposed to provide certain aggregate 

data that has been de-identified in 

accordance with the HIPAA Privacy 

Rule, 45 CFR 164.514(b), as discussed 

later in this section, for the purposes of 

helping IOTA participants understand 

their progress towards the model’s 

performance metrics. 

Specifically, subject to the limitations 

discussed in this final rule, and in 

accordance with applicable law, 

including the HIPAA Privacy Rule, we 

proposed that CMS may offer an IOTA 

participant an opportunity to request 

certain Medicare beneficiaryidentifiable data and reports as 

discussed in section III.C.7.b of this 

final rule. We proposed that CMS would 

share this beneficiary-identifiable data 

with IOTA participants on the condition 

that the IOTA participants, their IOTA 

collaborators, and other individuals or 

entities performing functions or services 

related to the IOTA participant’s 

activities observe all relevant statutory 

and regulatory provisions regarding the 

appropriate use of data and the 

confidentiality and privacy of 

individually identifiable health 

information, and comply with the terms 

of the data sharing agreement described 

in this section of the final rule. 

We proposed that the beneficiaryidentifiable claims data described in 

section III.C.7.b of this final rule would 

omit individually identifiable data for 

Medicare beneficiaries who have opted 

out of data sharing with the IOTA 

participant, as described in section 

III.C.7.c of this final rule. We also noted 

that, for the beneficiary-identifiable 

claims data, we would exclude 

information that is subject to the 

regulations governing the 

confidentiality of substance use disorder 

patient records (42 CFR part 2) from the 

data shared with an IOTA participant. 

b. Beneficiary-Identifiable Data 

(1) Legal Authority To Share 

Beneficiary-Identifiable Data 

As discussed in the proposed rule, we 

believe that an IOTA participant may 

need access to certain Medicare 

beneficiary-identifiable data for the 

purposes of evaluating its performance, 

conducting quality assessment and 

improvement activities, conducting 

population-based activities relating to 

improving health or reducing health 

care costs, or conducting other health 

care operations listed in the first or 

second paragraph of the definition of 

‘‘health care operations’’ under the 

HIPAA Privacy Rule, 45 CFR 164.501. 

We proposed that, subject to 

providing the beneficiary with the 

opportunity to decline data sharing as 

described in section III.C.10.a of this 

final rule, and subject to having a valid 

data sharing agreement in place, an 

IOTA participant may request from CMS 

certain beneficiary identifiable claims 

for attributed patients who are Medicare 

beneficiaries. 

As stated in section III.C.7(b)(1) of the 

proposed rule, we recognized there are 

sensitivities surrounding the disclosure 

of individually identifiable (beneficiaryspecific) health information, and several 

laws place constraints on the sharing of 

individually identifiable health 

information. For example, section 1106 

of the Act generally bars the disclosure 

of information collected under the Act 

unless a law (statute or regulation) 

permits the disclosure. Here, we noted 

that, in this circumstance, the HIPAA 

Privacy Rule would allow for the 

proposed disclosure of individually 

identifiable health information by CMS. 

We noted in the proposed rule that 

under the HIPAA Privacy Rule, covered 

entities (defined in 45 CFR 160.103 as 

health care plans, health care providers 

that submit certain transactions 

electronically, and health care 

clearinghouses) are barred from using or 

disclosing individually identifiable 

health information (called ‘‘protected 

health information’’ or PHI) in a manner 

that is not explicitly permitted or 

required under the HIPAA Privacy Rule, 

without the individual’s authorization 

(89 FR 43518). The Medicare FFS 

program, a ‘‘health plan’’ function of the 

Department, is subject to the HIPAA 

Privacy Rule limitations on the 

disclosure of PHI without an 

individual’s authorization. IOTA 

participants are also covered entities, 

provided they are health care providers 

as defined by 45 CFR 160.103 and they 

or their agents electronically engage in 

one or more HIPAA standard 

transactions, such as for claims, 


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eligibility or enrollment transactions. In 

light of these relationships, as discussed 

in the proposed rule, we believe that the 

proposed disclosure of the beneficiaryidentifiable data under the IOTA Model 

would be permitted by the HIPAA 

Privacy Rule under the provisions that 

permit disclosures of PHI for ‘‘health 

care operations’’ purposes. Under those 

provisions, a covered entity is permitted 

to disclose PHI to another covered entity 

for the recipient’s health care operations 

purposes if both covered entities have or 

had a relationship with the subject of 

the PHI to be disclosed, the PHI pertains 

to that relationship, and the recipient 

will use the PHI for a ‘‘health care 

operations’’ function that falls within 

the first two paragraphs of the definition 

of ‘‘health care operations’’ in the 

HIPAA Privacy Rule (45 CFR 

164.506(c)(4)). 

The first paragraph of the definition of 

health care operations includes 

‘‘conducting quality assessment and 

improvement activities, including 

outcomes evaluation and development 

of clinical guidelines,’’ and 

‘‘population-based activities relating to 

improving health or reducing health 

costs, protocol development, case 

management and care coordination.’’ 

The second paragraph of the definition 

of health care operations includes 

‘‘evaluating practitioner and provider 

performance’’ (45 CFR 164.501). 

Under our proposal, IOTA 

participants would be using the data on 

their patients to evaluate the 

performance of the IOTA participant 

and other providers and suppliers that 

furnished services to the patient, 

conduct quality assessment and 

improvement activities, and conduct 

population-based activities relating to 

improved health for their patients. 

When done by or on behalf of a covered 

entity, these are covered functions and 

activities that would qualify as ‘‘health 

care operations’’ under the first and 

second paragraphs of the definition of 

health care operations at 45 CFR 

164.501. Hence, as discussed in the 

proposed rule, we believe that this 

provision is extensive enough to cover 

the uses we would expect an IOTA 

participant to make of the beneficiaryidentifiable data and would be 

permissible under the HIPAA Privacy 

Rule. Moreover, our proposed 

disclosures would be made only to 

HIPAA covered entities that have (or 

had) a relationship with the subject of 

the information, the information we 

would disclose would pertain to such 

relationship, and those disclosures 

would be for purposes listed in the first 

two paragraphs of the definition of 

‘‘health care operations.’’ Finally, the 

proposed disclosures would be limited 

to beneficiary-identifiable data that we 

believe would meet HIPAA 

requirements in 45 CFR 164.502(b) to 

limit PHI to the minimum necessary to 

accomplish the intended purpose of the 

use, disclosure, or request. 

The Privacy Act of 1974 also places 

limits on agency data disclosures. The 

Privacy Act applies when Federal 

agencies maintain systems of records by 

which information about an individual 

is retrieved by use of one of the 

individual’s personal identifiers (names, 

Social Security numbers, or any other 

codes or identifiers that are assigned to 

the individual). The Privacy Act 

generally prohibits disclosure of 

information from a system of records to 

any third party without the prior written 

consent of the individual to whom the 

records apply (5 U.S.C. 552a(b)). 

As described in the proposed rule, 

‘‘routine uses’’ are an exception to this 

general principle (89 FR 43576). A 

routine use is a disclosure outside of the 

agency that is compatible with the 

purpose for which the data was 

collected. Routine uses are established 

by means of a publication in the Federal 

Register about the applicable system of 

records describing to whom the 

disclosure will be made and the purpose 

for the disclosure. As we stated in the 

proposed rule, we believe that the 

proposed data disclosures are consistent 

with the purposes for which the data 

discussed in this rule was collected, 

and, thus, would not run afoul of the 

Privacy Act, provided we ensure that an 

appropriate Privacy Act system of 

records ‘‘routine use’’ is in place prior 

to making any disclosures. The systems 

of records from which CMS would share 

data are the Medicare Integrated Data 

Repository (IDR) and the Health 

Resources and Services Administration 

(HRSA) Organ Procurement and 

Transplantation Network (OPTN)/ 

Scientific Registry of Transplant 

Recipients (SRTR) Data System. We 

stated in the proposed rule that we 

believe that the proposed data 

disclosures are consistent with the 

purposes for which the data were 

collected and may be disclosed in 

accordance with the routine uses 

applicable to those records. 

We proposed that CMS would share 

the following beneficiary-identifiable 

lists and data with IOTA participants 

that have submitted a formal request for 

the data. Under our proposal, the 

request must be submitted on an annual 

basis in a manner and form and by a 

date specified by CMS. The request also 

would need to identify the data being 

requested and include an attestation 

that (A) the IOTA participant is 

requesting this beneficiary-identifiable 

data as a HIPAA covered entity or as a 

business associate, as those terms are 

defined at 45 CFR 160.103, to the IOTA 

participant’s providers and suppliers 

who are HIPAA covered entities; and (B) 

the IOTA participant’s request reflects 

the minimum data necessary for the 

IOTA participant to conduct health care 

operations work that falls within the 

first or second paragraph of the 

definition of health care operations at 45 

CFR 164.501. In addition, we proposed 

that IOTA participants who request this 

data must have a valid and signed data 

sharing agreement in place, as described 

in more detail later in this section. We 

proposed that we would make available 

beneficiary-identifiable data as 

described in section III.C.8.b. of this 

final rule for IOTA participants to 

request for purposes of conducting 

health care operations that fall within 

the first or second paragraph of the 

definition of health care operations at 45 

CFR 164.501 on behalf of their 

attributed patients who are Medicare 

beneficiaries. We explained that we 

believe that access to beneficiaryidentifiable claims data would improve 

care coordination between IOTA 

participants and other health care 

providers. Patients can spend months in 

between their visits to the kidney 

transplant hospital at which they are 

listed, and the post-transplant period is 

critical to transplant success. We stated 

that we believe that improved care 

coordination would improve outcomes 

and keep patients engaged in their care. 

We also proposed that IOTA 

participants limit the request for 

beneficiary-identifiable claims data to 

Medicare beneficiaries whose name 

appears on the quarterly attribution list 

who have been notified in compliance 

with section III.C.10.a. of the proposed 

rule, and who did not decline having 

their claims data shared with the IOTA 

participant, as proposed in section 

III.C.7.d. of the proposed rule. Finally, 

we proposed that CMS would share 

beneficiary identifiable data with an 

IOTA participant on the condition that 

the IOTA participant, its IOTA 

collaborators, and other individuals or 

entities performing functions or services 

related to the IOTA participant’s 

activities, observe all relevant statutory 

and regulatory provisions regarding the 

appropriate use of data and the 

confidentiality and privacy of 

individually identifiable health 

information and comply with the terms 

of the data sharing agreement described 

in section III.C.7.f. of the proposed rule. 

The following is a summary of the 

public comments we received on the 

proposal to share certain beneficiaryVerDate Sep<11>2014 18:30 Dec 03, 2024 Jkt 265001 PO 00000 Frm 00112 Fmt 4701 Sfmt 4700 E:\FR\FM\04DER2.SGM 04DER2

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identifiable data with IOTA participants 

and our responses: 

Comment: A couple of commenters 

expressed support for the proposal to 

share certain beneficiary-identifiable 

data with IOTA participants. The 

commenters indicated that these data 

would enable IOTA participants to 

identify their patient populations, plan 

and improve care, and gauge the quality 

of post-acute care providers. 

Response: We thank the commenters 

for their support for the proposal to 

share certain beneficiary-identifiable 

data under this model and concur with 

the stated benefits for IOTA participants 

in receiving such data. 

After consideration of the comments 

received, we are finalizing at § 512.440 

our proposals to share certain 

beneficiary-identifiable claims data with 

IOTA participants as proposed with 

minor technical corrections. 

Specifically, we made a minor technical 

correction at § 512.440(a) to clarify that, 

as stated in this section and in the 

proposed rule, CMS shares certain 

beneficiary-identifiable data as 

described in § 512.440(b) and certain 

aggregate data as described in 

§ 512.440(c) with IOTA participants 

regarding attributed patients who are 

Medicare beneficiaries and performance 

under the model. We also made a minor 

technical correction at § 512.440(b)(3) to 

correct a grammatical error. 

(2) Quarterly Attribution Lists 

We proposed that this beneficiaryidentifiable data would include, for the 

relevant PY, a beneficiary attribution 

report, shared quarterly, that would 

include a list of attributed patients and 

patients who have been de-attributed 

from the IOTA participant. We proposed 

that the report would include at least 

the following information for each 

attributed patient: the attribution year 

the attributed patient became attributed 

to the IOTA participant; the effective 

date of the attributed patient’s 

attribution to the IOTA participant; the 

effective date of the patient’s deattribution from the IOTA participant 

and the reason for such removal (if 

applicable); and the attributed patient’s 

data sharing preferences made pursuant 

to section III.C.7.d. of this final rule. We 

proposed that CMS may include 

additional information at its discretion 

in any of the quarterly attribution 

reports as data becomes available. Such 

data may include information from the 

SRTR or OPTN on waitlist status or 

transplant status. 

We requested comment on whether 

such additional information would be 

beneficial to IOTA participants or 

whether this information is best 

accessed by the IOTA participant 

through other means. 

We received no public comments on 

these proposals and therefore are 

finalizing this provision as proposed to 

provide quarterly attribution lists to 

IOTA participants at § 512.440(b)(5)(i), 

without modification. 

(3) Beneficiary-Identifiable Claims Data 

In section III.C.7(b)(3) of the proposed 

rule, we proposed to offer certain 

beneficiary-identifiable claims data to 

IOTA participants no later than one 

month after the start of each PY, in a 

form and manner specified by CMS. We 

proposed that IOTA participants may 

retrieve this data at any point during the 

relevant PY and that it would include, 

at a minimum— 

• Three years of historical Parts A, B, 

and D claims data files for attributed 

patients who are Medicare beneficiaries 

for 36 months immediately preceding 

the effective date of the Medicare 

beneficiary’s attribution to the IOTA 

participant; 

• Monthly Parts A, B, and D claims 

data files specified for attributed 

patients who are Medicare beneficiaries; 

and 

• Monthly Parts A, B, and D claims 

data files for Medicare beneficiaries who 

have been de-attributed from the IOTA 

participant for claims with a date of 

service prior to the date the Medicare 

beneficiary was removed from 

attribution to the IOTA participant. 

We proposed that CMS would omit 

from the beneficiary-identifiable claims 

data any substance use disorder patient 

records subject to 42 U.S.C. 290dd–2 

and the implementing regulations at 42 

CFR part 2. 

We stated that we believe these data 

elements would consist of the minimum 

data element necessary for IOTA 

participants to effectively manage the 

care of Medicare beneficiaries who are 

attributed patients. Specifically, this 

data would allow IOTA participants to 

coordinate care across the continuum as 

Medicare beneficiaries who are 

attributed patients transition from IOTA 

waitlist patients to IOTA transplant 

patients. 

We requested comments on this 

proposal to share beneficiaryidentifiable claims data with IOTA 

participants at § 512.440(b)(5)(ii). 

The following is a summary of the 

public comments we received on the 

proposal to share beneficiaryidentifiable claims data with IOTA 

participants and our responses: 

Comment: A few commenters 

expressed support for the proposal to 

share certain beneficiary-identifiable 

claims data with IOTA participants. A 

commenter indicated that more data 

delivered more frequently to ensure 

timely opportunity to influence 

performance would be more beneficial. 

Response: We thank the commenters 

for their support for the proposal to 

share certain beneficiary-level data 

under this model and will strive to 

deliver data to IOTA participants in a 

timely manner to assist in their 

performance under the model. We have 

committed to a minimum data set and 

this specific frequency to allow for 

potential operational challenges or 

delays. 

After consideration of the comments 

received, we are finalizing our 

regulation at § 512.440 (b)(5)(ii) to share 

certain beneficiary-identifiable claims 

data with IOTA participants, without 

modification. 

c. Minimum Necessary Data 

We proposed IOTA participants must 

limit their beneficiary-identifiable data 

requests to the minimum necessary to 

accomplish a permitted use of the data. 

We proposed the minimum necessary 

Parts A and B data elements may 

include, but are not limited to, the 

following data elements: 

• Medicare beneficiary identifier (ID). 

• Procedure code. 

• Gender. 

• Diagnosis code. 

• Claim ID. 

• The from and through dates of 

service. 

• The provider or supplier ID. 

• The claim payment type. 

• Date of birth and death, if 

applicable. 

• Tax Identification Number (TIN). 

• National Provider Identification 

(NPI). 

We proposed the minimum necessary 

Part D data elements may include, but 

are not limited to, the following data 

elements: 

• Beneficiary ID. 

• Prescriber ID. 

• Drug service date. 

• Drug product service ID. 

• Quantity dispensed. 

• Days supplied. 

• Brand name. 

• Generic name. 

• Drug strength. 

• TIN. 

• NPI. 

• Indication if on formulary. 

• Gross drug cost. 

We requested comment and feedback 

on the minimum beneficiaryidentifiable claims data necessary for 

IOTA participants to request for 

purposes of conducting permissible 

health care operations purposes under 

this model. 


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We received no public comments on 

our proposed provisions regarding the 

minimum beneficiary-identifiable 

claims data necessary for IOTA 

participants to request for purposes of 

conducting permissible health care 

operations under this model. Thus, we 

are finalizing the proposed provisions at 

§ 512.440(b)(ii)(6), without 

modification. 

d. Medicare Beneficiary Opportunity To 

Decline Data Sharing 

As described in section III.C.10.a. of 

this final rule, we proposed that 

Medicare beneficiaries must receive 

notification about the IOTA Model. We 

also proposed that Medicare 

beneficiaries must be given the 

opportunity to decline claims data 

sharing, and instructions on how to 

inform CMS directly of their preference. 

We proposed that Medicare 

beneficiaries would be notified about 

the opportunity to decline claims data 

sharing through the proposed 

notifications discussed in section 

III.C.10.a. of this final rule. We proposed 

that these notifications must state that 

the IOTA participant may have 

requested beneficiary identifiable claims 

data about the Medicare beneficiary for 

purposes of its care coordination and 

quality improvement work and/or 

population-based activities relating to 

improving health or reducing health 

care costs, and inform the Medicare 

beneficiary how to decline having his or 

her claims information shared with the 

IOTA participant in the form and 

manner specified by CMS. We proposed 

that Medicare beneficiary requests to 

decline claims data sharing would 

remain in effect unless and until a 

beneficiary subsequently contacts CMS 

to amend that request to permit claims 

data sharing with IOTA participants. 

As discussed in the proposed rule (89 

FR 43577), we proposed that Medicare 

beneficiaries may not decline to have 

the aggregate, de-identified data 

proposed in section III.C.7.f. of the 

proposed rule shared with IOTA 

participants. We also proposed that 

Medicare beneficiaries may not decline 

to have the initial attribution lists, 

quarterly attribution lists, or annual 

attribution reconciliation list as 

proposed in section III.C.4.b.(2)., b.(3). 

and b.(4). of this final rule shared with 

IOTA participants. We noted that, in 

accordance with 42 U.S.C. 290dd–2 and 

its implementing regulations at 42 CFR 

part 2, CMS would not share beneficiary 

identifiable claims data relating to the 

diagnosis and treatment of substance 

use disorders under this model. 

In section III.C.7(d) of the proposed 

rule, we noted that the proposed opt out 

provisions discussed in this section 

would relate only to the proposed 

sharing of beneficiary-identifiable data 

between the Medicare program and the 

IOTA participant under the IOTA 

Model, and were in no way intended to 

impede existing or future data sharing 

under other authorities or models. 

We requested comment and feedback 

on our proposed policies to enable 

Medicare beneficiaries to decline data 

sharing under the model. 

We received no comments on this 

proposal and therefore are finalizing the 

proposed provisions to allow Medicare 

beneficiaries to decline data sharing at 

§ 512.440(b)(ii)(7), without 

modification. 

e. Data Sharing Agreement 

(1) General 

As noted in section III.C.7.a. of this 

final rule, we proposed that, prior to 

receiving any beneficiary-identifiable 

data, IOTA participants would be 

required to first complete, sign, and 

submit—and thereby agree to the terms 

of—a data sharing agreement with CMS. 

We proposed that under the data 

sharing agreement, the IOTA participant 

would be required to comply with the 

limitations on use and disclosure that 

are imposed by HIPAA, the applicable 

data sharing agreement, and the 

statutory and regulatory requirements of 

the IOTA Model. We also proposed that 

the data sharing agreement would 

include certain protections and 

limitations on the IOTA participant’s 

use and further disclosure of the 

beneficiary-identifiable data and would 

be provided in a form and manner 

specified by CMS. Additionally, we 

proposed that an IOTA participant that 

wishes to retrieve the beneficiary 

identifiable-data would be required to 

complete, sign, and submit to CMS a 

signed data sharing agreement at least 

annually. We stated that we believe that 

it is important for the IOTA participant 

to complete and submit a signed data 

sharing agreement at least annually so 

that CMS has up-to-date information 

that the IOTA participant wishes to 

retrieve the beneficiary-identifiable data 

and information on the designated data 

custodian(s). As described in greater 

detail later in this section, we proposed 

that a designated data custodian would 

be the individual(s) that an IOTA 

participant would identify as 

responsible for ensuring compliance 

with all privacy and security 

requirements and for notifying CMS of 

any incidents relating to unauthorized 

disclosures of beneficiary-identifiable 

data. 

As described in section III.C.7.e(1) of 

the proposed rule, CMS believes it is 

important for the IOTA participant to 

first complete and submit a signed data 

sharing agreement before it retrieves any 

beneficiary-identifiable data to help 

protect the privacy and security of any 

beneficiary-identifiable data shared by 

CMS with the IOTA participant. We 

noted that there are important 

sensitivities surrounding the sharing of 

this type of individually identifiable 

health information, and CMS must 

ensure to the best of its ability that any 

beneficiary-identifiable data that it 

shares with IOTA participants would be 

further protected in an appropriate 

fashion. 

We solicited public comment on our 

proposal to require that the IOTA 

participant agree to comply with all 

applicable laws and terms of the data 

sharing agreement as a condition of 

retrieving beneficiary-identifiable data, 

and on our proposal that the IOTA 

participant would need to submit the 

signed data sharing agreement at least 

annually if the IOTA participant wishes 

to retrieve the beneficiary-identifiable 

data. 

The following is a summary of the 

public comments we received on the 

proposals to define the IOTA data 

sharing agreement, to require 

compliance with the terms of the IOTA 

data sharing agreement as a condition of 

retrieving the beneficiary-identifiable 

data, and to require submission of the 

IOTA data sharing agreement at least 

annually, and our responses to these 

comments: 

Comment: A couple commenters 

expressed support and appreciation for 

the proposed protections surrounding 

the sharing of beneficiary-identifiable 

data with IOTA participants. A 

commenter reiterated that any data 

sharing should be conducted in a 

manner that protects patient privacy 

and allows all points of care to 

maximize lessons learned and 

implement quality improvement 

activities. A commenter expressed 

concern with prohibiting disclosures to 

an individual practitioner in a treatment 

relationship with the attributed patient 

who is a Medicare beneficiary, or that 

practitioner’s business associates. 

Response: We thank the commenters 

for their support and agree that 

appropriate protections must be ensured 

in the sharing of beneficiary-identifiable 

data. We are finalizing that the data 

sharing agreement will include a 

provision prohibiting any further 

disclosure, not otherwise required by 

law, of the beneficiary-identifiable data 

to anyone who is not a HIPAA covered 

entity or business associate, as defined 


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in 45 CFR 160.103, or who is not an 

individual practitioner in a treatment 

relationship with the attributed patient 

who is a Medicare beneficiary, or that 

practitioner’s business associates. 

Therefore, this provision would not 

prohibit data sharing with a covered 

entity or its business associate for 

treatment purposes. Such a prohibition 

would be similar to that imposed by 

CMS in other models tested under 

section 1115A of the Act, such as the 

KCC Model, in which CMS shares 

certain beneficiary-identifiable data 

with model participants for their health 

care operations. 

CMS will include this prohibition in 

the data sharing agreement because 

there exist important legal and policy 

limitations on the sharing of the 

beneficiary-identifiable data and must 

carefully consider the ways in which 

and reasons for which CMS would 

provide access to this data for purposes 

of the IOTA Model. 

After consideration of the comments 

received, for the reasons set forth in this 

rule, we are finalizing at § 512.440(b)(8) 

the provisions of the data sharing 

agreement as an agreement entered into 

between the IOTA participant and CMS 

that includes the terms and conditions 

for any beneficiary-identifiable data 

shared with the IOTA participant under 

§ 512.440, without modification. In 

addition, we are finalizing at 

§ 512.440(b)(8)(i) the proposal that the 

IOTA participant would need to submit 

the signed IOTA data sharing agreement 

at least annually if the IOTA participant 

wishes to retrieve the beneficiaryidentifiable data from CMS. 

We are also finalizing at 

§ 512.440(b)(8)(ii) the proposed 

requirement that the IOTA participant 

agree to comply with all applicable laws 

and the terms of the IOTA data sharing 

agreement as a condition of retrieving 

the beneficiary-identifiable data. 

(2) Content of the Data Sharing 

Agreement 

We proposed that CMS would share 

the following beneficiary-identifiable 

data with IOTA participants that have 

requested the data and have a valid data 

sharing agreement in place, as described 

in more detail later in this section. We 

proposed that an IOTA participant that 

wishes to receive beneficiaryidentifiable data for its attributed 

patients who are Medicare beneficiaries 

must also agree to certain terms, 

namely: (1) to comply with the 

requirements for use and disclosure of 

this beneficiary-identifiable data that are 

imposed on covered entities by the 

HIPAA regulations at 45 CFR part 160 

and part 164, subparts A and E, and the 

requirements of the proposed IOTA 

Model; (2) to comply with additional 

privacy, security, breach notification, 

and data retention requirements 

specified by CMS in the data sharing 

agreement; (3) to contractually bind 

each downstream recipient of the 

beneficiary-identifiable data that is a 

business associate of the IOTA 

participant, including all IOTA 

collaborators, to the same terms and 

conditions with the IOTA participant is 

itself bound in its data sharing 

agreement with CMS as a condition of 

the business associate’s receipt of the 

beneficiary-identifiable data retrieved 

by the IOTA participant under the IOTA 

Model; and (4) that if the IOTA 

participant misuses or discloses the 

beneficiary-identifiable data in a 

manner that violates any applicable 

statutory or regulatory requirements or 

that is otherwise non-compliant with 

the provisions of the data sharing 

agreement, CMS may: (A) deem the 

IOTA participant ineligible to retrieve 

the beneficiary-identifiable data under 

paragraph (b) of this section for any 

amount of time; (B) terminate the IOTA 

participant’s participation in the IOTA 

Model under § 512.466; and (C) subject 

the IOTA participant to additional 

sanctions and penalties available under 

the law. 

We stated in the proposed rule that 

CMS believes these proposed terms for 

sharing beneficiary-identifiable data 

with IOTA participants are appropriate 

and important, as CMS must ensure to 

the best of its ability that any 

beneficiary-identifiable data that it 

shares with IOTA participants would be 

further protected by the IOTA 

participant, and any business associates 

of the IOTA participant, in an 

appropriate fashion. 

CMS sought public comment on the 

additional privacy, security, breach 

notification, and other requirements that 

we would include in the data sharing 

agreement. CMS has these types of 

agreements in place as part of the 

governing documents of other models 

tested under section 1115A of the Act 

and in the Medicare Shared Savings 

Program. In these agreements, CMS 

typically requires the identification of 

data custodian(s) and imposes certain 

requirements related to administrative, 

physical, and technical safeguards 

relating to data storage and 

transmission; limitations on further use 

and disclosure of the data; procedures 

for responding to data incidents and 

breaches; and data destruction and 

retention. These provisions would be 

imposed in addition to any restrictions 

required by law, such as those provided 

in the HIPAA privacy, security, and 

breach notification regulations. We 

noted that these data sharing agreement 

provisions would not prohibit the IOTA 

participant from making any disclosures 

of the data otherwise required by law. 

CMS also sought public comment on 

what specific disclosures of the 

beneficiary identifiable data might be 

appropriate to permit or prohibit under 

the data sharing agreement. For 

example, we stated that CMS was 

considering prohibiting, in the data 

sharing agreement, any further 

disclosure, not otherwise required by 

law, of the beneficiary-identifiable data 

to anyone who is not a HIPAA covered 

entity or business associate, as defined 

in 45 CFR 160.103, or to an individual 

practitioner in a treatment relationship 

with the attributed patient who is a 

Medicare beneficiary, or that 

practitioner’s business associates. Such 

a prohibition would be similar to that 

imposed by CMS in other models tested 

under section 1115A of the Act in 

which CMS shares certain beneficiaryidentifiable data with model 

participants for their health care 

operations. 

We noted in the proposed rule that 

CMS is considering these possibilities 

because there exist important legal and 

policy limitations on the sharing of the 

beneficiary-identifiable data and CMS 

must carefully consider the ways in 

which and reasons for which we would 

provide access to this data for purposes 

of the IOTA Model. We stated that CMS 

believes that some IOTA participants 

may require the assistance of business 

associates, such as contractors, to 

perform data analytics or other 

functions using this beneficiaryidentifiable data to support the IOTA 

participant’s review of their care 

management and coordination, quality 

improvement activities, or clinical 

treatment of IOTA beneficiaries. CMS 

also believes that this beneficiaryidentifiable data may be helpful for any 

HIPAA covered entities who are in a 

treatment relationship with the IOTA 

beneficiary. 

We sought public comment on how 

an IOTA participant might need to, and 

want to, disclose the beneficiaryidentifiable data to other individuals 

and entities to accomplish the goals of 

the IOTA Model, in accordance with 

applicable law. 

Under our proposal, the data sharing 

agreement would include other 

provisions, including requirements 

regarding data security, retention, 

destruction, and breach notification. For 

example, as stated in section III.C.7 of 

the proposed rule, we were considering 

including, in the data sharing 

agreement, a requirement that the IOTA 


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96394 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

289https://www.ecfr.gov/current/title-42/section482.90. 

290 Ibid. 

291 Ibid. 

292 Ibid. 

293 Ibid. 

294OPTN. (n.d.). OPTN Policies—Living 

Donation, Chapter 14. https://

optn.transplant.hrsa.gov/media/eavh5bf3/optn_

policies.pdf. 

295AMA Council on Ethical and Judicial Affairs. 

(2019). AMA Code of Medical Ethics’ Opinions on 

Organ Transplantation. AMA Journal of Ethics, 

14(3), 204–214. https://doi.org/10.1001/ 

virtualmentor.2012.14.3.coet1-1203. 

296https://www.ecfr.gov/current/title-42/section482.90. 

297Park, C., Jones, M.-M., Kaplan, S., Koller, F.L., 

Wilder, J.M., Boulware, L.E., & McElroy, L.M. 

(2022). A scoping review of inequities in access to 

organ transplant in the United States. International 

Journal for Equity in Health, 21(1). https://doi.org/ 

10.1186/s12939-021-01616-x. 

298Epstein, A.M., Ayanian, J.Z., Keogh, J.H., 

Noonan, S.J., Armistead, N., Cleary, P.D., 

Weissman, J.S., David-Kasdan, J.A., Carlson, D., 

Fuller, J., Marsh, D., & Conti, R.M. (2000). Racial 

Disparities in Access to Renal Transplantation— 

Clinically Appropriate or Due to Underuse or 

Overuse? New England Journal of Medicine, 

343(21), 1537–1544. https://doi.org/10.1056/ 

nejm200011233432106. 

299Ng, Y.-H., Pankratz, V.S., Leyva, Y., Ford, C.G., 

Pleis, J.R., Kendall, K., Croswell, E., Dew, M.A., 

Shapiro, R., Switzer, G.E., Unruh, M.L., & 

Myaskovsky, L. (2019). Does Racial Disparity in 

Kidney Transplant Wait-listing Persist After 

Accounting for Social Determinants of Health? 

Transplantation, 1. https://doi.org/10.1097/ 

tp.0000000000003002. 

300Ahern, Patrick et al. Sex Disparity in 

Deceased-Donor Kidney Transplant Access by 

Cause of Kidney Disease. 2021. Clinical Journal of 

the American Society of Nephrology. 16 (2) 241– 

250, https://cjasn.asnjournals.org/content/16/2/241. 

301Wadhwani, S.I., Lai, J.C., & Gottlieb, L.M. 

(2022). Medical Need, Financial Resources, and 

Transplant Accessibility. JAMA, 327(15), 1445. 

https://doi.org/10.1001/jama.2022.5283. 

participant designate one or more data 

custodians who would be responsible 

for ensuring compliance with the 

privacy, security and breach notification 

requirements for the data set forth in the 

data sharing agreement; various security 

requirements like those found in 

participation agreements for other 

models tested under section 1115A of 

the Act, but no less restrictive than 

those provided in the relevant Privacy 

Act system of records notices; how and 

when beneficiary-identifiable data could 

be retained by the IOTA participant or 

its downstream recipients of the 

beneficiary-identifiable data; procedures 

for notifying CMS of any breach or other 

incident relating to the unauthorized 

disclosure of beneficiary-identifiable 

data; and provisions relating to 

destruction of the data. We stated that 

these are only examples and are not the 

only terms CMS would potentially 

include in the data sharing agreement. 

We solicited public comment on this 

proposal to impose certain additional 

requirements in the IOTA data sharing 

agreement related to privacy, security, 

data retention, breach notification, and 

data destruction. 

We received no comments on this 

proposal and therefore are finalizing 

these proposed provisions at 

§ 512.440(b)(8), without modification. 

f. Aggregate Data 

We proposed that CMS would share 

certain aggregate performance data with 

IOTA participants in a form and manner 

to be specified by CMS. This aggregate 

data would be de-identified in 

accordance with HIPAA requirements at 

45 CFR 164.514(b) and would include, 

when available, transplant target data. 

We proposed that, for the relevant PY, 

CMS would provide aggregate data to 

the IOTA participant detailing the IOTA 

participant’s performance against the 

transplant target, as described in section 

III.C.5.c.(2). of this final rule. 

We sought comment and feedback on 

our proposal to share aggregate data 

with IOTA participants. 

We received no comments on this 

proposal and therefore are finalizing the 

proposed provisions at § 512.440(c) 

without modification. 

8. Other Requirements 

a. Transparency Requirements 

(1) Publication of Patient Selection 

Criteria for Kidney Transplant 

Evaluations 

Transplant hospitals are currently 

required to use written patient selection 

criteria in determining a patient’s 

suitability for placement on the waitlist 

or a patient’s suitability for 

transplantation per the CoP (see 42 CFR 

482.90). If the transplant hospital 

performs living donor transplants, the 

transplant hospital must use written 

donor selection criteria to determine the 

suitability of candidates for donation.289

The patient selection criteria must 

ensure fair and non-discriminatory 

distribution of organs, and the program 

must document in the patient’s medical 

record the patient selection criteria 

used.290 Prior to placement on the 

transplant hospital’s waitlist, a 

prospective transplant candidate must 

receive a psychosocial evaluation, if 

possible.291 Before a transplant hospital 

places a transplant candidate on its 

waitlist, the candidate’s medical record 

must contain documentation that the 

candidate’s blood type has been 

determined.292 In addition, when a 

patient is placed on a hospital’s waitlist 

or is selected to receive a transplant, the 

transplant hospital must document in 

the patient’s medical record the patient 

selection criteria used.293 Currently, the 

transplant hospital must also provide a 

copy of its patient selection criteria to 

a transplant patient, or a dialysis 

facility, as requested by the patient or a 

dialysis facility. For living donor 

selection, the transplant hospital’s 

living donor selection criteria must be 

consistent with the general principles of 

medical ethics.294 295 Transplant 

hospitals must also ensure that a 

prospective living donor receives a 

medical and psychosocial evaluation, 

document in the living donor’s medical 

records the living donor’s suitability for 

donation, and document that the living 

donor has given informed consent.296

Available data and studies 

demonstrate that disparities exist for 

patients in underserved communities 

who seek or are referred for, or are 

evaluated for a transplant and who 

eventually are placed on a transplant 

waitlist and receive an organ transplant 

(89 FR 43579).297 For instance, the data 

has shown that White patients are more 

likely than Black patients to be referred 

for organ transplant, while Black 

patients are less likely than White 

patients to be referred for transplant 

evaluation.298 Racial disparities also 

exist in transplant wait listing, even 

after correcting for SDOH.299 In 

addition, there are sex and gender 

disparities in access to the kidney 

transplant waitlist, with men more 

likely to have access compared to 

women.300 Finally, a recent article in 

the Journal of the American Medical 

Association considers how transplant 

programs factor patient financial 

resources into waitlist decisions.301 The 

authors’ review of several studies 

suggested that socioeconomically 

deprived patients were proportionally 

less likely to be selected for placement 

on a waitlist for an organ transplant. 

They suggested, based on the strong and 

consistent associations between race 

and poverty, that ‘‘withholding 

transplants from those with inadequate 

financial resources equates to an 

example of structural racism in the 

health care system.’’ We refer readers to 

the numerous additional studies 

regarding disparities in organ 

transplantation and organ donation that 

are cited throughout the final rule. 

In section III.C.8.a(1) of the proposed 

rule, to improve transparency for those 

looking to gain access to a transplant 

waitlist in the transplant program 

evaluation processes, we proposed to 

require IOTA participants to publicly 

post, on a website, their patient 

selection criteria for evaluating patients 

for addition to their kidney transplant 

waitlist by the end of PY 1. We 

proposed to finalize this requirement 

only if it is not redundant with other 


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HHS guidance. We also considered 

requiring that IOTA participants update 

their selection criteria at a certain 

frequency to ensure that attributed 

patients have the most up to date 

information. However, we are unsure 

what cadence of update would be most 

appropriate. 

We solicited public comments on this 

proposal and on how often the selection 

criteria should be updated by the IOTA 

participant. 

The following is a summary of the 

comments received on our proposal to 

require IOTA participants to publicly 

post their patient selection criteria for 

kidney transplant waitlist candidates on 

a website and the frequency at which 

updating this information should occur 

and our responses: 

Comment: Many commenters stated 

they support the publication of patient 

selection criteria for kidney transplant 

evaluations. A commenter specified that 

it could help reduce distrust around 

organ transplant decisions. 

Response: We thank the commenters 

for their support. We agree that posting 

patient selection criteria for evaluating 

patients for addition to a waitlist will 

help reduce distrust about organ 

transplant decisions. 

Comment: A commenter suggested 

that patient selection criteria should be 

posted in common languages of the 

local community and that any written 

materials be delivered in patients’ 

preferred language. 

Response: We thank the commenter 

for their suggestion. We agree that 

public facing patient selection criteria 

for evaluating patients for addition to a 

waitlist should be made available in 

local languages and should be 

compliant with regulations requiring 

patients to have written information in 

their preferred language. 

Comment: Numerous commenters 

were concerned about the impact of 

publicly posted patient selection criteria 

on their patients. A commenter was 

concerned that overwhelming patients 

with selection criteria published on a 

public-facing website is not patientcentered, does not promote autonomy 

and impacts the patient-provider 

relationship. Similarly, a commenter 

conveyed their concern that there is a 

significant risk of misinterpretation of 

the selection criteria by referring 

providers in the community and 

patients, which may decrease referrals. 

Additionally, a commenter was 

concerned that public disclosure of 

waitlist selection criteria that only 

applies to IOTA participants, does not 

help patients who may live in a region 

with access to more than one kidney 

transplant hospital. 

Response: We thank the commenters 

for their responses and concerns. We 

believe that providing patient selection 

criteria for evaluating patients for 

addition to a waitlist publicly creates 

transparency for both patients and for 

their referring nephrologists. Referring 

nephrologists have more patient contact 

than a transplant nephrologist at time of 

referral, and therefore are key in 

referring patients for kidney transplant 

evaluation and in having the ability to 

guide the patient to the kidney 

transplant hospital that may be most 

ideal for the patient. With the 

overwhelming amount of information 

that a kidney transplant patient learns 

during their multi-hour initial 

transplant evaluation, we believe that 

resources to encourage early transplant 

discussions between a referring 

nephrologist and patient can create 

opportunities for a more fruitful 

evaluation experience for the patient. 

This may also open communication 

between transplant nephrologists and 

referring nephrologists. We agree that 

potential transplant candidates and 

selection criteria can be extremely 

complex and vary on a case-by-case 

basis; however, we believe that 

providing general expectations for 

kidney transplant candidacy is by no 

means unreasonable and can make the 

evaluation process more efficient. For 

example, if a kidney transplant hospital 

will definitively not transplant a patient 

with a certain co-morbidity, whereas 

another kidney transplant hospital may, 

this can be extremely helpful for a 

patient to know before taking off from 

work or a dialysis session and 

organizing transportation or both for a 

kidney transplant hospital that is 

hundreds of miles away. Sometimes it 

may take months to schedule specialist 

visits or preventative health screenings, 

needed for transplant waitlisting. 

Listing selection waitlist criteria can 

help patients anticipate what 

appointments they may need to 

schedule. We understand there are 

‘‘gray’’ areas of candidacy and 

subsequently have not created 

prescriptive requirements for patient 

selection lists. 

Public-facing patient selection criteria 

for evaluating patients for addition to a 

waitlist allows patients to understand 

general expectations earlier in their 

transplant evaluation journey, ensures 

keeping criteria up to date, and provides 

greater access and autonomy to patients. 

While non-participants of the IOTA 

Model are not mandated by this 

requirement, we suggest that other 

kidney transplant hospitals follow suit. 

Comment: A commenter was 

concerned that public posting of kidney 

transplant waitlist selection criteria 

policy is redundant since it is already 

available publicly through groups such 

as CMS, HRSA, UNOS and OPTN. 

Response: We thank the commenter 

for their concern. While 42 CFR 482.90 

already requires documentation of 

selection criteria within the patient’s 

medical record upon placement on the 

waiting list, it does not specify the need 

for publicly posting patient selection 

criteria decisions.302 Currently, there is 

not a centralized site listing all 

transplant programs’ selection criteria. 

Patients have access to their medical 

records through patient portals or can 

alternatively access a hard copy of their 

records by request. We believe it is also 

important that the patient has access to 

this information before the visit. We 

also believe that public facing listing 

criteria provides greater access to 

patients who may not be able to easily 

access their patient portal, reducing 

disparities. 

Comment: A commenter suggested 

that CMS would need to closely monitor 

this transparency requirement and 

penalize IOTA participants that do not 

comply. 

Response: Thank you for your 

responses regarding monitoring for 

compliance. We agree that long term 

there will need to be monitoring and 

auditing to ensure that IOTA 

participants are compliant with listing 

their selection criteria. We are hopeful 

to receive further feedback throughout 

and after PY 1 to modify this 

requirement to be as specific as is 

reasonable to ensure compliance. 

Additionally, we are hopeful that there 

is opportunity to have a collective site, 

which would feature all IOTA 

participants’ selection criteria on one 

website. 

Comment: A couple of commenters 

were concerned by the differences in 

self-reported listing criteria versus 

characteristics of patients that are 

ultimately listed. One of these 

commenters recommended that CMS 

focus on the data of waitlist patients. A 

commenter stated that CMS should also 

consider the differences in the criteria 

for accepting a referral, evaluating the 

patient, and listing the patient. 

Response: We thank the commenters 

for their feedback. We recognize there 

are limitations in mandating public 

posting of selection criteria and that 

there is discordance between selfreported kidney transplant hospital 

listing criteria and the actual 

characteristics of their listed patients for 

transplant. While we acknowledge that 


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303https://www.ecfr.gov/current/title-42/section482.90. 

304https://www.ecfr.gov/current/title-42/section482.90. 305https://www.ecfr.gov/current/title-42/section482.90. 

it may be challenging to package 

numerous patient co-morbidities into an 

easily digestible and reasonable list of 

selection criteria, we believe that 

exercising a requirement to bring 

transparency to selection criteria will 

also assist kidney transplant hospitals in 

tailoring those criteria and be as specific 

as possible. To avoid deterring referrals 

of possible transplants, we have not 

considered posting referral requirements 

at this time and will not do so without 

further consideration and input from the 

transplant community. We do, however, 

believe it would be greatly beneficial for 

kidney transplant hospitals to outline 

the difference between referral, 

evaluation and listing on their website 

and additionally review this 

information during every patient’s 

transplant evaluation visit. 

Comment: A couple of commenters 

included their support for the 

development of a centralized, 

standardized way to present information 

about transparency requirements such 

as selection criteria and bypass filters. A 

commenter further recommended that 

patient education surrounding this 

transparency information should be 

created by a centralized group (such as 

OPTN or SRTR) to reduce kidney 

transplant hospital burdens. 

Response: We agree that a centralized 

location for waitlist selection criteria 

and organ offer acceptance criteria 

would be ideal and are hopeful that the 

transplant community can move toward 

a database that is accessible to patients 

and providers or both that will provide 

this information; however, we do not 

believe that this is necessary for PY 1 for 

IOTA participants. We believe it is 

reasonable and not overly burdensome 

to request IOTA participants to post 

their selection criteria on their website. 

We intend to continue discussions 

about a centralized database for patient 

waitlist selection criteria and will 

consider this for future rulemaking, 

Comment: A commenter suggested 

that IOTA participants should be 

required to conduct targeted outreach to 

non-citizens and other underserved 

communities to provide clarifications 

and education on transplant. 

Response: We appreciate the 

commenter’s feedback. We believe it is 

in the purview of individual IOTA 

participants to have outreach events to 

serve their community. Currently the 

IOTA Model does not outline the topic 

of educational outreach; however, we 

will take this comment into 

consideration for future rulemaking 

since patient education is extremely 

important throughout the continuum of 

kidney care and is needed to expand 

equal access to transplant. Additionally, 

please note that community outreach 

would be a potential opportunity for 

IOTA participant to consider as part of 

the voluntary health equity plans in the 

IOTA Model, as reviewed in section 

III.C.8.c of this final rule. 

Comment: A commenter requested 

that CMS provide flexibility regarding 

the frequency of updating waitlist 

selection criteria. A couple of 

commenters were concerned with 

balancing accurate information with 

resource burden. 

Response: We appreciate the 

commenter’s response regarding 

frequency of waitlist criteria updates 

and type of information included. 

Beyond requirements previously 

outlined in 42 CFR 482.90, we have not 

provided specific requirements that 

IOTA participants must include 

regarding listing practices.303 We do, 

however, expect and trust that IOTA 

participants are acting in good faith to 

provide accurate waitlisting criteria and 

specific details, when possible. While 

we did not propose a specific cadence 

as to how frequently IOTA participants 

should be required to update their 

selection criteria after PY 1, we will take 

these comments into consideration 

during future rulemaking. We do not 

believe that requesting a public online 

posting about patient waitlist selection 

criteria by the end of PY 1, is overly 

burdensome to IOTA participants, as 

IOTA participants are already expected 

to provide these criteria in patient 

waitlist documentation. We are 

finalizing this requirement as originally 

proposed in section III.C.8.a(1) of the 

proposed rule, for PY 1, without 

modification. 

Comment: A commenter suggested 

that waitlist selection criteria should 

include specific details such as absolute 

contraindications of IOTA participants 

(for example, BMI limits), whether there 

are financial reserve requirements, and 

if other factors such as psychiatric or 

psychosocial factors impact listing. 

Response: We thank the commenters 

for their recommendations. Beyond 

requirements previously outlined in 42 

CFR 482.90, CMS has not provided 

specific requirements that IOTA 

participants must include regarding 

listing practices.304 We do believe, 

though, that if IOTA participants have a 

list of absolute versus relative 

contraindications for their patients, it 

would be beneficial to make patients 

and referring nephrologists aware of 

these concerns. 

While we agree that it could be 

helpful for patients to understand 

specific psychosocial and psychiatric 

requirements, we believe that this could 

be challenging given the 

multidimensional evaluation that is 

completed during transplant evaluation 

and the complexity of understanding 

each individual’s situation. 

Additionally, psychiatric and 

psychosocial diagnoses can be fluid, 

and we would not want to discourage 

patients from transplant evaluation, 

particularly since they may learn about 

helpful resources during the evaluation. 

A goal of the IOTA Model is to reduce 

disparities in kidney transplant, and we 

believe that listing granular 

psychosocial or psychiatric 

requirements could be contradictory to 

these goals. 

Listing specific financial requirements 

could be helpful if transplant programs 

have absolute cutoffs for transplant 

recipients; however, if patients do not 

initially meet financial requirements, 

transplant program resources (financial 

counselor, social workers) may be able 

to help that patient create a financial 

plan to meet that requirement. We will 

take this comment into consideration for 

future iterations of the IOTA Model and 

encourage additional feedback from 

kidney transplant hospitals during PY 1. 

Comment: A commenter suggested it 

may be easier if CMS created a list of 

criteria that each IOTA participant 

needs to address in the selection 

criteria. 

Response: We thank you for your 

comment. As previously mentioned in 

section III.C.8.a.(1) of this final rule, 42 

CFR part 428.90 does outlines basic 

requirements for kidney transplant 

evaluation.305 Currently, we believe that 

being prescriptive beyond these 

requirements prevents kidney transplant 

providers and kidney transplant 

hospitals from creating selection criteria 

applicable to risk level they believe is 

appropriate based on their resources 

and their community. We believe that 

including referring nephrologists in 

conversations regarding specific listing 

criteria could be helpful, however, we 

are not mandating this. 

After consideration of public 

comments, for the reasons set forth in 

this rule, we are finalizing the 

requirement that IOTA participants 

must publicly post their patient 

selection waitlist criteria on a website 

by the end of PY 1 at § 512.442(a), 

without modification. We intend to use 


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306Optimizing Usage of Kidney Offer Filters— 

OPTN. (n.d.). Optn.transplant.hrsa.gov. Retrieved 

March 11, 2023, from https://

optn.transplant.hrsa.gov/policies-bylaws/publiccomment/optimizing-usage-of-kidney-offer-filters/. 

future rulemaking to determine the 

cadence of updating this website and 

patient selection criteria. For IOTA 

participants who choose to post their 

patient selection criteria for evaluating 

patients for addition to their kidney 

transplant waitlist early in the PY 1, we 

also encourage them to update their 

criteria again, should it change 

throughout the year. 

(2) Transparency Into Kidney 

Transplant Organ Offers 

As discussed in section III.C.8.a(2) of 

the proposed rule, those active on a 

kidney transplant waitlist may receive 

organ offers at any time. However, there 

is currently no requirement for 

providers to discuss organ offers with 

their patients. A provider may decline 

an organ offer for any number of 

reasons; however, declining without 

disclosing the rationale with the patient 

may miss an important opportunity for 

shared decision-making. 

In section III.C.8.a(2) of the proposed 

rule, we proposed to add requirements 

to increase transparency for IOTA 

waitlist patients who are Medicare 

beneficiaries regarding the volume of 

organ offers received on their behalf 

while on the waitlist. Specifically, we 

proposed that for each month an organ 

is offered for an IOTA waitlist patient 

who is a Medicare beneficiary, an IOTA 

participant must inform the Medicare 

beneficiary, on a monthly basis, of the 

number of times an organ is declined on 

the Medicare beneficiary’s behalf and 

the reason(s) for the decline. We are not 

proposing to prescribe the method of 

this notification but would require that 

the medical record reflect that the 

patient received this information and 

the method by which it was delivered 

(for example, mail, email, medical 

appointment, internet portal/dashboard, 

etc.). We proposed that this information 

must be shared with the IOTA waitlist 

patient who is a Medicare beneficiary, 

and should be shared, where deemed 

appropriate, with their nephrologist or 

nephrology professional, to provide the 

opportunity for questions and 

clarification of information. 

Organ offer filters are a tool that 

transplant programs can use to bypass 

organ offers they would not accept. 

Offer filters were tested during two pilot 

programs and released nationally in 

January 2022.306 In section III.C.8.a(2) of 

the proposed rule, we proposed that 

IOTA participants would be required to 

review transplant acceptance criteria 

and organ offer filters with their IOTA 

waitlist patients who are Medicare 

beneficiaries at least once every 6 

months that the Medicare beneficiary is 

on their waitlist. We proposed that this 

review may be done on an individual 

basis in a patient visit, via phone, email, 

or mail. We believed that sharing this 

information with the patient would offer 

an opportunity for shared decisionmaking between the patient and IOTA 

participants and may increase the 

patient’s quality of care. We proposed 

that Medicare beneficiaries would be 

able to decline this review with the 

IOTA participant, as some may not wish 

to have this information. We anticipated 

that the Medicare beneficiary may 

decline this review during their next 

provider visit or over the phone. 

We solicited public comment on 

whether an alternative frequency of 

sharing of organ offers with the 

Medicare beneficiary is more 

appropriate. We also solicited comment 

on whether there is a more suitable 

timeframe and frequency for addressing 

acceptance criteria with attributed 

patients. Per 42 CFR 482.94(c), and 

482.102(a) and (c), kidney transplant 

hospitals currently review these criteria 

with patients upon patient request. Our 

goal was to provide a balance of 

transparency and patient engagement in 

this process without being overly 

prescriptive or burdensome. We also 

recognized that there are beneficiaries 

on the waitlist who may not be eligible 

to receive an organ offer for multiple 

years, so we sought feedback on 

whether this requirement should be 

limited to beneficiaries who have 

received or are likely to receive an organ 

offer in the next year. 

The following is a summary of 

comments we received on our proposal 

to (1) require monthly notifications to 

Medicare beneficiaries receiving organ 

offers who are IOTA waitlist patients 

about number of organs declined and 

the rationale for the decline and to (2) 

require review of transplant acceptance 

criteria and organ offer filters with their 

IOTA waitlist patients who are 

Medicare beneficiaries at least once 

every 6 months that the Medicare 

beneficiary is on their waitlist and our 

responses: 

Comment: Commenters expressed 

concern about the proposed 

transparency into kidney transplant 

organ offers provision, which would 

require IOTA participants to inform, on 

a monthly basis, IOTA waitlist patients 

who are Medicare beneficiaries of the 

number of times an organ is declined on 

the patient’s behalf and the reason(s) for 

the decline. Specifically, commenters 

felt this would impose a significant 

administrative burden on IOTA 

participants. Some of these commenters 

were concerned that notifying waitlisted 

Medicare patients of organ offer 

declines and the reasons for those 

declines would be burdensome, costly, 

and of questionable value. This was 

seen as at odds with the IOTA Model’s 

quality and efficiency domain goals and 

was seen as disproportionately 

burdensome to smaller transplant 

hospitals. Commenters also noted that 

the provision does not account for the 

clinical and administrative resources 

needed to review the high volume of 

organ declines across all waitlisted 

individuals. This could divert resources 

away from patient care. Furthermore, a 

commenter stated that patient care 

groups are more interested in data on 

time-to-transplant and likelihood of 

receiving a transplant, which are 

already publicly available. 

Response: We thank the commenters 

for their concerns. Due to the many 

concerns received, we recognize that 

monthly notification to Medicare 

beneficiaries regarding volume and 

reason for organ decline could be very 

burdensome to IOTA participants and 

their staff in PY 1 since this is a new 

initiative and there is not current 

infrastructure or database resources to 

aid in minimizing burden on IOTA 

participants. We believe we need more 

time to better identify how we can 

increase transparency of the organ offer 

process for transplant recipients with 

the help of the transplant community. 

Minimizing administrative burden for 

kidney transplant hospitals while 

maximizing meaningful communication 

with beneficiaries will be key in these 

discussions as the transplant 

community participates in this dialogue. 

Subsequently, we will not be finalizing 

our regulation at proposed § 512.442(b), 

which required that Medicare 

beneficiaries on the IOTA participant’s 

waitlist be notified monthly about organ 

offers. We look forward to engaging in 

conversation with transplant 

stakeholders to understand additional 

transparency opportunities to mutually 

meet patient and provider goals, prior to 

potentially revisiting this in future 

rulemaking. 

Comment: A commenter expressed 

concern that discussions about organ 

offer filters, while allowing patients to 

influence decisions, may not provide 

providers with enough data to fully 

inform and engage patients. For 

example, providers may lack 

information on how these filters impact 

wait times. The commenter suggested 

this could prevent patients from 

believeing they can meaningfully 

contribute to shared decision-making. 


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Response: We appreciate the 

commenter’s feedback and subsequently 

recognize that our proposal to require 

IOTA participants to review transplant 

acceptance criteria and organ offer 

filters with their IOTA waitlist patients 

who are Medicare beneficiaries requires 

clarification. We also acknowledge that 

explaining the organ offer filter itself 

may not promote the same outcome as 

sharing the impact of organ offer 

acceptance criteria. In light of this, we 

are finalizing our review of selection 

criteria and organ offer filters provisions 

with slight modifications. Specifically, 

we are finalizing at § 512.442(c) that 

IOTA participants must review 

transplant organ offer acceptance 

criteria (rather than acceptance criteria 

and organ offer filters) with their IOTA 

waitlist patients who are Medicare 

beneficiaries at least once every 6 

months that the Medicare beneficiary is 

on their waitlist. Additionally, we are 

removing all references to organ offer 

filters. 

Regarding the commenter’s concern 

that they may not have enough 

information to share with patients 

regarding organ offer filters, we believe 

that generally discussing organ offer 

acceptance criteria is a first step in 

increasing patient’s awareness about 

why certain organs may or may not be 

accepted at a particular transplant 

program. As IOTA participants may 

choose to analyze data to better 

understand ideal organ offer filters, 

these findings can be used as supporting 

evidence when explaining to 

beneficiaries why their transplant 

program for example, may not accept 

kidney transplant with a particular cold 

ischemic time. 

Comment: A commenter agreed that 

organ offer filters should be reviewed 

with patients at least every 6 months to 

strengthen their original education. 

Response: We thank the commenter 

for their support. We recognize that 

explaining the organ offer filter itself 

may not promote the same outcome as 

sharing the organ offer acceptance 

criteria. Subsequently, we are finalizing 

and clarifying that reviewing organ offer 

acceptance criteria (rather than the filter 

itself), with IOTA waitlist patients who 

are Medicare beneficiaries at least every 

6 months, will meet this requirement. 

We suspect that IOTA participants will 

have more frequent changes in their 

organ offer filters during the first few 

years of the IOTA Model as kidney 

transplant hospitals optimize their 

practices. 

Comment: A commenter expressed 

support for reviewing transplant organ 

offer acceptance criteria with IOTA 

waitlist patients who are Medicare 

beneficiaries every six months. 

Response: We thank the commenter 

for their support. 

Comment: A commenter argued that 

operationalizing the proposed 

transparency into kidney transplant 

organ offers would be more efficiently 

achieved by directing the OPTN to 

develop a patient portal. This portal 

would allow patients to view their own 

organ offer filters and organ decline 

statistics online, rather than requiring 

each IOTA participant to develop their 

own reporting system. The commenter 

emphasized that this approach would 

promote patient engagement, education, 

and accountability at kidney transplant 

hospitals, as patients would be able to 

access the information themselves. 

Overall, the commenter felt this would 

be both more efficient and more 

effective in achieving the desired result 

of increased transparency. 

Response: We thank the commenter 

for their valuable suggestions. We 

recognize the importance of delivering 

consistent messages about patient 

education and matters such as organ 

offer filters, organ offer acceptance 

criteria, and declined organ offers. As 

we continue our collaborative work 

with OTAG, we will carefully consider 

these recommendations. Additionally, 

we encourage IOTA participants to 

discuss this proposal within the IOTA 

Model learning system. We direct 

readers to section III.C.15 of this final 

rule for a full discussion on the IOTA 

Model learning system. 

Comment: A few commenters 

suggested reviewing acceptance criteria 

and declined organ offers during key 

timeframes, such as transplant 

evaluation, annual waitlist visits, or 

when first listed on the waiting list. For 

example, a commenter, while 

supporting transparency, encouraged 

upfront communication with patients 

about organ offer practices during 

evaluation and annual visits. As an 

alternative, this commenter 

recommended that IOTA participants be 

required to educate patients on the 

organ offer process, declines, and 

patients’ right to information—with 

IOTA participants providing specific 

details upon patient request. 

Another commenter expressed 

support for sharing organ offer filters 

and transplant acceptance criteria with 

patients. However, the commenter 

recommended IOTA participants review 

these details with patients when they 

are first listed on the waiting list, and 

update patients if any changes are made. 

For patients who want information 

about declined offers, the commenter 

suggested discussing their transplant 

acceptance criteria periodically as they 

receive that information. For patients 

who opt out of declined offer details or 

do not discuss them with the IOTA 

participant, the commenter 

recommended an annual review of their 

organ offer filters and transplant 

acceptance criteria (or at the time of reevaluation, whichever comes first). 

Additionally, the commenter supported 

CMS’s proposal to allow patients to 

decline this review altogether. Lastly, a 

commenter suggested that IOTA 

participants review organ offers 

received with their waitlisted patients 

during annual or biannual waitlist 

visits. The commenter asserted that this 

would give patients the chance to 

discuss any changes to their organ offer 

acceptance criteria and ask their 

provider questions directly. 

Response: We appreciate the valuable 

feedback from commenters. Although 

many kidney transplant hospitals see 

their waitlisted patients at least 

annually, this practice is inconsistent. 

Waitlist patient visit frequency can also 

vary depending on the patient’s active 

or inactive waitlist status. To better 

inform patients about organ offers and 

the reasons for declining them, beyond 

the initial evaluation and waitlist clinic 

visits, we proposed more frequent 

patient notifications, as described in 

section III.C.8.a(2) of this final rule. In 

light of the comments received, we 

recognize that successfully 

implementing an organ offer notification 

process will require more extensive 

planning. Therefore, we will not be 

finalizing the transparency into kidney 

transplant organ offer provisions at 

proposed § 512.442(b). However, we 

remain committed to increasing 

communication and engagement with 

patients on the kidney transplant 

waitlist. 

Regarding the proposed review of 

acceptance criteria and organ offer 

filters transparency requirement, as 

described in section III.C.8.a(2) of this 

final rule, we believe it is important to 

finalize this provision for several key 

reasons: (1) it should not create a 

significant administrative burden; (2) it 

provides the building blocks of 

education for IOTA waitlist patients; 

and (3) due to other themes of the IOTA 

Model that may impact organ offer filter 

use, we believe reviewing organ offer 

acceptance criteria with patients every 6 

months is appropriate. As mentioned in 

comment responses in this section, we 

also recognize that explaining organ 

offer filters with waitlisted patients may 

not promote the same outcome as 

reviewing organ offer acceptance 

criteria. As such, we will be finalizing 

our proposed review of acceptance 


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criteria provision at § 512.442(c) with 

minor technical corrections. 

Specifically, we added ‘‘organ offer’’ to 

transplant acceptance criteria that must 

be disclosed and removed all references 

to ‘‘organ offer filters’’. Additionally, we 

will provide further sub-regulatory 

guidance on how IOTA waitlist patients 

who are Medicare beneficiaries can 

choose to decline the review of their 

transplant organ offer acceptance 

criteria. 

Comment: Several commenters 

recommended organ offer inclusion or 

exclusion criteria for the proposed 

transparency into kidney transplant 

organ offer provision. The commenters 

believed the proposed notification 

requirement should be limited to 

minimize administrative burden. Their 

suggested inclusion criteria were: (1) if 

the patient is the primary recipient, or 

(2) if the kidney offer is declined by one 

hospital but used by another. Their 

suggested exclusion criteria included: 

(1) kidneys outside a 250-mile radius, 

(2) discarded kidneys, (3) kidney organ 

offers that were declined by all kidney 

transplant hospitals on the match run, 

or (4) patients removed from a waitlist 

before a monthly reporting period 

concluded. Several commenters replied 

about the inclusions and exclusions 

from notification requirements. 

Response: We appreciate the 

commenters’ feedback. We reiterate that, 

as mentioned in comment responses in 

this section, we are not finalizing the 

proposed transparency organ offer 

notification provision at proposed 

§ 512.442(b). We aim to engage with the 

transplant community to identify 

conditions that should be captured in 

exclusion criteria, to inform future 

rulemaking pertaining to transparency 

into kidney transplant organ offers. 

Comment: Some commenters 

expressed concerns about the proposed 

transparency into kidney organ offers 

provision. In particular, they worried it 

may require IOTA participants to 

carefully manage how information is 

shared. The commenters also mentioned 

that additional security controls may be 

needed to prevent donor information 

from being shared with recipients. 

Another commenter stated the 

transparency into kidney transplant 

organ offers provision should include 

specific details on donor kidney offers, 

to protect patient privacy and prevent 

increased use of suboptimal kidneys. 

Additionally, a commenter cited 

safeguarding patients’ legal and ethical 

rights to informed consent and 

autonomy as paramount. Lastly, a 

couple commenters suggested 

alternatives, such as only discussing 

declined organ offer review at the 

programmatic level among transplant 

program providers, or using a 

collaborative model with some privacy 

walls while sharing select information 

with patients or the public. 

Response: We thank the commenters 

for sharing their concerns and 

suggestions about patient privacy. We 

agree that patient privacy of donors and 

potential recipients is paramount and 

believe that safeguarding patients’ rights 

to informed consent and autonomy is 

imperative. However, in response to the 

comments we received, as mentioned in 

comment responses in this section, we 

are not finalizing the proposed 

transparency into kidney transplant 

organ offers provision, requiring IOTA 

participants to inform IOTA waitlist 

patients who are Medicare beneficiaries 

of the number of times an organ is 

declined on the patient’s behalf, at 

proposed § 512.442(b). 

Comment: A few commenters 

expressed concerns that the 

transparency into kidney transplant 

organ offers provisions are overly 

complex and unnecessary. Moreover, a 

commenter felt these requirements are 

redundant, as transplant programs must 

already provide patients access to SRTR 

data resources that publicly disclose 

information about their organ offer 

acceptance rates. 

Response: We thank the commenters 

for expressing their concerns. While we 

acknowledge that the new processes 

needed to meet the proposed 

transparency into kidney transplant 

organ offer provisions (89 FR 43580) 

would initially be labor-intensive or 

technologically challenging, we 

maintain that these requirements are 

important and increase patient 

awareness. 

Additionally, we disagree that the 

proposed transparency into kidney 

transplant organ offers requirements are 

redundant programmatic requirements 

of providing SRTR data; providing 

generalized organ offer acceptance rate 

ratio data is very different from 

providing direct notification to a patient 

about an organ offer that was declined 

on their behalf. However, based on 

commenter feedback, we recognize the 

complexities of notifying patients about 

declined organ offers. While we are not 

finalizing the proposed transparency 

into kidney transplant organ offers 

provisions at proposed § 512.442(b), we 

remain interested in exploring 

alternative ways to promote 

transparency for kidney transplant 

waitlist patients. 

Comment: A couple commenters 

urged CMS to consider how the 

proposed transparency into kidney 

transplant organ offers provision could 

inadvertently impact the behavior of 

kidney transplant hospitals. For 

example, a commenter noted that the 

proposed organ offers notification 

requirement emphasizes the importance 

of discussing organ offer declines with 

patients, which is crucial for informed 

decision-making. However, the 

commenter expressed concern that the 

focus on organ offer declines could 

deter the use of higher-risk organs, 

ultimately reducing the number of 

viable transplants, or kidney transplant 

hospitals might potentially offer the 

organ despite it not being the best fit for 

the recipient. 

Response: We appreciate the 

commenters concerns regarding the 

proposed transparency into kidney 

transplant organ offers provision, as 

outlined at § 512.442(b) in the proposed 

rule. We agree that this provision may 

impact provider and staff awareness of 

consistent kidney transplant offers that 

are being declined, which could affect 

filtering practices. Increasing patientstaff conversations not only creates 

opportunities for patients to stay better 

informed about their care, but also 

allows transplant staff to stay up to date 

on a patient’s waitlist status and recent 

medical changes. We view more 

frequent patient interactions as a 

positive behavioral change. As 

previously discussed in comment 

responses in this section, we are not 

finalizing the transparency into kidney 

transplant organ offers provision at 

proposed § 512.442(b), however, we 

continue to be committed to working 

with the transplant community to 

identify alternative transparency 

opportunities for kidney transplant 

waitlist patients. 

Comment: A couple of commenters 

stated that CMS should consider 

alternate ways to promote transparency, 

including incorporating the voices of 

consumers, including patients in 

community councils, inviting 

community members to serve on boards 

and equipping patients with data about 

kidney transplant hospitals so they can 

make informed decisions. 

Response: We appreciate the 

commenters’ feedback. We believe 

direct dialogue and advocacy between 

patients and kidney transplant hospitals 

can enhance communication, helping 

these hospitals better understand areas 

needing improvement, such as 

information gaps and lack of 

transparency. HHS intends to make 

organ offer information more easily 

accessible for patients who are on the 

waiting list, to minimize administrative 

burden. While these concepts are not 

incorporated into the IOTA Model, we 

believe they are concepts that kidney 


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transplant hospitals should further 

consider. 

Comment: A commenter expressed 

concern that the proposed organ offer 

notification requirement would create 

disparities, as it would only apply to 

Medicare patients and IOTA 

participants. 

Response: We thank the commenter 

for sharing their concern that the 

transparency into kidney transplant 

organ offers provision, as proposed, 

would create disparities because only 

Medicare patients and IOTA patients 

would be subject to the requirement. 

The Innovation Center’s authority in 

this proposed rule only extends to 

Medicare beneficiaries, which is why 

we only proposed that it apply to IOTA 

waitlist patients who are Medicare 

beneficiaries. However, as mentioned in 

comment responses in this section, we 

are not finalizing the proposed 

transparency into kidney transplant 

organ offers provision, requiring IOTA 

participants to inform IOTA waitlist 

patients who are Medicare beneficiaries 

of the number of times an organ is 

declined on the patient’s behalf, at 

proposed § 512.442(b). 

Comment: A few commenters urged 

CMS to reduce the administrative 

burden on IOTA participants imposed 

by the proposed transparency 

requirements. Suggestions included 

leveraging existing technology and data, 

evaluating the administrative and 

financial impacts, and providing IOTA 

participants with the necessary 

resources to successfully implement the 

proposed transparency requirements. 

Several commenters supported a 

centralized process to achieve 

transparency, facilitated by CMS or 

UNOS/OPTN, which could include 

standardized patient-specific reports 

using existing OPTN information, an 

application programming interface, or a 

patient portal. 

Response: We agree that a future 

centralized online resource could 

improve patient access and reduce 

administrative burdens for kidney 

transplant hospitals by providing 

patient organ offer notifications. HHS 

intends to make organ offer information 

more easily accessible in the future, to 

minimize administrative burden for 

transplant programs. As previously 

mentioned in this section, we will not 

be finalizing the proposed transparency 

into kidney transplant organ offers 

provision at proposed § 512.442(b). We 

aim to examine the administrative and 

financial challenges involved in 

notifying patients of organ offers, and 

explore how technology can be used to 

reduce this administrative burden. 

Comment: A commenter expressed 

support for informing patients on the 

transplant waitlist, if a patient is active 

on the transplant waiting list and 

eligible to receive organ offers, when 

those organ offers have been declined 

on their behalf. The commenter argued 

that transparency should not be 

compromised for these patients. 

Additionally, the commenter urged 

CMS to hold IOTA participants 

accountable for communicating a 

patient’s waitlisting status when: (1) a 

patient becomes inactive, including 

explaining the reasons why and possible 

solutions to regaining active status, if 

feasible; and, (2) a patient regains active 

waitlisting status after being inactivated. 

Response: We thank the commenter 

for their support of the proposed 

transparency into kidney transplant 

organ offers provision. However, as 

mentioned in comment responses in 

this section, we will not be finalizing 

this provision at this time. We still 

believe that it is important to increase 

transparency for kidney transplant 

waitlist patients regarding the volume of 

organ offers received and declined on 

their behalf while on the waiting list. 

We also value the commenter’s 

recommendation to hold IOTA 

participants accountable for 

communicating a patient’s waitlisting 

status. We acknowledge the importance 

of patient awareness regarding their 

waitlist status, an aspect that is often 

overlooked. Additionally, we recognize 

the significant number of inactive 

patients on the waiting list, many of 

whom may be unaware of their inactive 

status or the reasons behind it. This 

aligns with our goal of promoting 

transparency and SDM between the 

patient and IOTA participants. We will 

consider the commenter’s suggestion 

along with the public comments on the 

proposed transparency requirements 

and may make future proposals during 

the course of the model test. 

Comment: A commenter asserted that 

CMS could achieve the goals of the 

proposed transparency into kidney 

transplant organ offers requirements 

without significantly increasing the 

administrative burden on participating 

kidney transplant hospitals. Instead of 

the proposed requirements, the 

commenter recommended that CMS 

mandate a discussion about offer 

screening during the patient consent 

process. Additionally, the commenter 

suggested that participating kidney 

transplant hospitals be required to 

document these discussions, include 

them in their records, or address them 

with patients during evaluations or once 

they are placed on the waitlist. 

Response: We thank the commenters 

for their suggestions. However, we are 

concerned that organ offer discussions 

at the time of initial evaluation for 

transplant candidacy, while a good start, 

is insufficient for patient education. 

Patients often feel overwhelmed by the 

extensive transplant education they 

receive when first considering a kidney 

transplant. This can be especially 

challenging for those who have recently 

been diagnosed with kidney disease, 

making the prospect of transplant seem 

particularly daunting. While 

comprehensive education at the time of 

evaluation and waitlist is important, we 

believe patients would benefit from 

more frequent, ongoing guidance about 

organ offers, acceptance criteria, and 

deferral tendencies throughout the 

listing process. As previously 

mentioned in comment responses in 

this section, we will not be finalizing 

the transparency into kidney transplant 

organ offers provisions at proposed 

§ 512.442(b) at this time due to the 

aforementioned concerns. We are 

committed to exploring new ways to 

increase transparency in collaboration 

with the transplant community. 

Comment: A commenter highlighted 

that they previously urged CMS to 

mandate greater transparency about the 

risk aversion of transplant hospitals and 

surgeons. This transparency, the 

commenter argued, would allow 

patients to find a transplant hospital 

that aligns with their personal risk 

tolerance. While the commenter 

welcomed the IOTA Model’s proposal to 

include two such transparency policies, 

they strongly disagreed with the policies 

being part of a demonstration rather 

than a nationwide requirement. 

Response: We thank the commenter 

for their support. The Innovation Center 

is limited in exercising authority 

specific to Medicare beneficiaries and is 

unable to create nationwide mandates 

for patients with all types of insurance 

coverage. However, successful 

Innovation Center models are often 

reviewed and discussed as 

opportunities to expand to the nation 

through other policies. While we are not 

finalizing the proposed transparency 

into kidney transplant organ offers 

requirements at § 512.442(b) of the 

proposed rule, we hope that transplant 

hospitals who are not selected to 

participate in the IOTA Model will 

consider integrating IOTA Model 

concepts into their kidney transplant 

hospital. 

Comment: A few commenters 

mentioned that modifications to the 

transparency requirements were needed 

or that the transparency into kidney 

transplant offers provision should be 


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eliminated entirely but did not provide 

further suggestions or justification. 

Response: We thank the commenters 

for the feedback. We are interested in 

understanding the commenters’ specific 

modification suggestions and invite 

them to provide further details in the 

future. 

Comment: Several commenters 

supported the provision requiring 

transparency into kidney transplant 

organ offers, with some of them 

specifying that providing Medicare 

beneficiaries the option to be informed 

about organs that were declined on their 

behalf supports increased 

communication and shared decision 

making between patients and providers. 

One of these commenters also believed 

that increasing transparency would hold 

kidney transplant hospitals accountable, 

drive ongoing improvements across the 

transplant system and help eliminate 

health disparities. 

Response: We greatly appreciate the 

commenters’ words of support; 

however, we are not finalizing this 

provision. We look forward to future 

feedback as we work to create 

transparency requirements that are not 

unduly burdensome. We remain 

invested in evaluating alternative 

transparency opportunities with the 

transplant community. 

Comment: A couple of commenters 

conveyed concerns with barriers to 

patient receipt of transparency 

notifications, stating that IOTA 

participants may use automated 

notifications in place of the meaningful 

communication that would be required 

to provide quality care. A commenter 

was specifically concerned by technical 

barriers reaching patients, such as 

outdated contact information. 

Response: We agree these are valid 

challenges with all types of patient 

communications. While automated 

notifications may be preferred by some 

patients, it may further worsen 

disparities in already vulnerable 

populations. We recognize that 

disparities in access to technology can 

limit certain patients, making phone 

calls or other methods of contact 

necessary. Patient portals may provide a 

source of quick, easy access to 

information; however, this can prevent 

real-time discussions. This concern is 

one of the reasons that we will not be 

finalizing the proposed transparency 

into kidney transplant organ offers 

provision as proposed at § 512.442(b). 

We look forward to engaging with 

kidney transplant hospitals to identify 

and share efficient yet appropriate 

methods for equitably notifying and 

making patients aware of declined 

kidney transplant organ offers, without 

creating disparities for those who may 

not have access to technology. 

Comment: Several commenters 

suggested CMS modify the transparency 

into kidney transplant organ offers 

provision, which would require IOTA 

participants to inform, on a monthly 

basis, IOTA waitlist patients who are 

Medicare beneficiaries of the number of 

times an organ is declined on the 

patient’s behalf and the reason(s) for the 

decline. Specifically, they suggested 

that organ offer declines should be 

shared only to a certain sequence 

number in the match run, keeping the 

information to a manageable amount 

and focusing on organs that the patient 

had a reasonable likelihood of receiving. 

Suggested notification thresholds 

included the top 5, 100, 150, or 200 

matches of the match run, or only when 

the organ was used for a transplant 

candidate positioned further down on 

the waiting list. For example, a 

commenter suggested that since a 

quarter of organ offers are accepted at or 

after having been offered to 73 

transplant candidates, organ offer 

declines should be shared with 

transplant candidates up to match run 

sequence 150, which is about 73 

doubled. Alternatively, the commenter 

suggested that CMS could mirror the 

SRTR definition of a hard-to-place 

kidney (100) and cap sharing the organ 

offer decline information at transplant 

candidates who were lower than 100 in 

the match run sequence. 

Response: We thank the commenters 

for their suggestion to only share organ 

offer declines to a certain sequence 

number in the match run and modify 

the provision requiring transparency 

into kidney transplant organ offers. 

Since we are not currently finalizing 

this provision, as mentioned in 

comment responses in this section, we 

will keep this feedback in mind as we 

consider alternatives in future 

rulemaking. 

Comment: Many commenters 

requested clarification on the proposed 

transparency into kidney transplant 

organ offer provision requiring IOTA 

participants, for months in which an 

organ offer is made, to inform IOTA 

waitlist patients who are Medicare 

beneficiaries of the number of times an 

organ is declined on the patient’s behalf. 

For example, a commenter wanted to 

know what deliverable(s) CMS expects 

in order to validate compliance with 

this requirement. Another commenter 

asked CMS to clarify what constitutes 

an organ offer decline. The commenter 

stated that due to the complexity of the 

organ offer system and variability in 

OPO behavior, a transplant hospital may 

receive an organ offer before many 

transplant hospitals ahead of them have 

reviewed and declined it. As a result, 

the commenter was concerned that a 

transplant hospital may review an offer 

when they do not actually have the 

opportunity to transplant the organ, as 

they are not the ‘‘primary’’ recipient. 

The commenter also noted a recent 

significant increase in expedited organ 

placement, where an OPO can send an 

organ to a hospital that is not next in 

line. Additionally, the commenter 

pointed out that an IOTA waitlist 

patient may have a declined offer but 

then be removed from the waitlist due 

to transplant or other reasons before the 

monthly report period ends; potentially 

creating uncertainty for IOTA 

participants on whether to notify the 

IOTA waitlist patient in such scenarios. 

Furthermore, the commenter suggested 

that different IOTA participants may 

define the required reporting differently, 

and that some declined offers may be 

more relevant to IOTA waitlist patients 

than others. 

A few commenters sought clarity on 

which organ offers and declines would 

be included in this requirement. For 

instance, a commenter asked if the 

requirement would cover only primary 

offers, which occur sporadically, or all 

offers regardless of match quality— 

potentially numbering in the hundreds 

per month. This same commenter also 

raised questions about whether hospital 

representatives or physicians (who may 

be unaffiliated private practitioners) 

should have discussions about organ 

offers with IOTA waitlist patients, and 

how IOTA participants could effectively 

communicate complex clinical 

information to non-clinical patients 

without causing strife or animosity, as 

patients and families often 

misunderstand or underestimate the 

risks of poorly matched organs and 

recipients. 

Response: We thank the commenters 

for their questions and feedback. As 

mentioned in comment responses in 

this section, we are not finalizing the 

proposed transparency into kidney 

transplant organ offers provision, 

requiring IOTA participants to inform 

IOTA waitlist patients who are 

Medicare beneficiaries of the number of 

times an organ is declined on the 

patient’s behalf. However, as we 

continue to consider ways to increase 

transparency, we will consider this 

feedback in future rulemaking. 

Comment: A few commenters 

expressed concerns that the new 

transparency requirements into kidney 

transplant organ offers may have 

unintended consequences. They 

worried the requirements could 

encourage IOTA participants to accept 


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lower-quality kidneys, offer kidneys that 

are not the best fit for recipients, or 

deter the use of higher-risk organs. 

Additionally, a commenter noted that 

monthly reporting on declined kidney 

offers does not account for the 

increasing reliance on out-of-sequence 

allocation for high-risk kidneys that may 

otherwise be discarded. 

Many commenters emphasized the 

importance of allowing transplant 

surgeons, who are knowledgeable about 

each patient’s unique circumstances, to 

exercise discretion in making clinical 

decisions without facing pressure to 

accept suboptimal organs or penalties 

for denying them. They warned that 

restricting this discretion could 

undermine trust between the transplant 

program and patients. One of these 

commenters also expressed concern that 

transplant programs are worried about 

patient dissatisfaction and potential 

legal actions due to declinations. This is 

because patients might falsely be given 

the sense that they would have had the 

option of accepting a kidney that is not 

clinically acceptable. 

Response: We thank the commenters 

for their feedback. The proposed 

provisions for transparency into 

declined kidney transplant offers is not 

intended to question a provider’s 

medical judgment or expertise. Rather, 

it aims to better inform patients about 

whether they are receiving offers and 

the reasons behind any declines. For 

instance, if a size mismatch between the 

recipient and donor kidney prompts 

deferring the transplant to an alternative 

recipient, the transparency requirement 

should not impact that clinical decision. 

However, we proposed that IOTA 

waitlist patients who are Medicare 

beneficiaries be made aware of any 

declined offers and the rationale, 

allowing them the opportunity to ask 

questions and understand the process. 

The goal of this proposed transparency 

requirement is to facilitate more open 

patient-provider discussions about the 

kidney transplant process before 

undergoing the major, life-altering 

procedure—not to erode trust or 

encourage litigation. Although we are 

not finalizing the proposed transparency 

into kidney transplant organ offers 

provisions at proposed § 512.442(b), we 

continue to support increasing 

transparency for patients on the waiting 

list and will consider alternative 

pathways with the transplant 

community to fulfill this important 

need. 

Comment: Numerous commenters 

voiced concerns about the transparency 

into kidney transplant organ offers 

requirements. Specifically, they worried 

that notifying patients about declined 

organ offers could undermine patient 

trust, evoke strong emotions, and 

negatively impact mental health. 

Commenters also expressed concern 

that patients and families may not fully 

grasp complex medical factors like 

organ quality and suitability, potentially 

leading to confusion over the clinical 

decisions made. 

Response: We appreciate the 

commenters’ feedback and agree that 

monthly notifications of declined organ 

offers may not be the right option for 

every patient. We believe this is an 

important topic to consider as we 

evaluate future opportunities for 

transparency requirements. At this time, 

we will not be finalizing the proposed 

transparency into kidney transplant 

organ offers provisions; however, we 

will take this feedback into 

consideration for future notice and 

comment rulemaking. 

Comment: Several commenters 

mentioned that patient-centered and 

secure reporting is important stating 

that CMS should consider beneficiaries’ 

preferences to ensure that the 

transparency requirements are practical 

for IOTA participants to implement and 

meaningful to kidney transplant 

patients and should ensure that data 

reported is meaningful. A commenter 

specified the information should be 

culturally and linguistically 

appropriate. Several commenters stated 

that information should be processed in 

a way that safeguards patients and their 

families, and authentication measures 

should be implemented to verify that 

patients’ contact information. 

Commenters added that mechanisms for 

sharing information should be 

developed carefully and with input 

from the donation and transplant 

community. Some of these commenters 

also felt patients should be able to opt 

in and out of receiving notifications. 

Response: We appreciate the 

commenters’ feedback. We agree that 

organ offer notifications in addition to 

organ offer acceptance criteria need to 

be practical and consider linguistic and 

cultural modifications. Although we are 

not finalizing the proposed transparency 

into kidney transplant organ offers 

provisions, as mentioned in comment 

responses in this section, we will 

consider these important patientcentered provision details in future 

notice and comment rulemaking. 

Comment: A commenter 

recommended that rather than report 

monthly on kidney transplant offers, 

CMS should require IOTA participants 

to report their quartile rank for their 

organ offer acceptance rate ratio to all 

wait-listed patients on a semiannual or 

annual basis. 

Response: Thank you for your 

recommendation. As described in 

section III.C.5.d of this final rule, we are 

finalizing the inclusion of the organ 

offer acceptance rate ratio performance 

measure in the efficiency domain. 

Section 1115A(b)(4)(B) of the Act 

requires CMS to the public, and we plan 

to do so annually. This report would 

include the organ offer acceptance rate 

ratio results. Despite making organ offer 

acceptance rate ratio results available to 

patients, we believe that this does not 

negate the need for other transparency 

requirements as one data point focuses 

on kidney transplant hospital level data 

while the other focuses on patient level 

data. Although we are not finalizing the 

proposed transparency into kidney 

transplant organ offers provisions, as 

mentioned in comment responses in 

this section, this remains an important 

topic requiring ongoing discussion. 

Comment: A couple of commenters 

recommended that organ offer declines 

be shared with both the patient and 

their referring nephrologist. 

Response: We appreciate the 

commenters’ feedback and agree that 

referring nephrologists are an important 

individual in the care continuum for 

patients with kidney disease. As 

described in comment responses in this 

section, we are not finalizing our 

proposed transparency into kidney 

transplant organ offers provisions at this 

time. However, we believe this is an 

important consideration and will take 

this comment into consideration in 

future notice and rulemaking. After 

consideration of public comment, for 

the reasons set forth in this rule, we are 

not finalizing our proposed provision 

for transparency into kidney transplant 

organ offers at § 512.442(b). 

We are, however, finalizing the 

provisions as proposed at § 512.442(c), 

with minor technical corrections. 

Specifically, we added ‘‘organ offer’’ to 

transplant acceptance criteria that must 

be disclosed and removed all references 

to ‘‘organ offer filter’’ from the provision 

at § 512.442(c). Additionally, at 

§ 512.442(c) we replaced ‘‘selection 

criteria’’ to now say ‘‘acceptance 

criteria’’. These changes were made in 

order to clarify the specific provisions 

regarding the review of transplant organ 

offer acceptance criteria, as described in 

section III.C.8(a)(2) of the preamble in 

this final rule. We will provide further 

sub-regulatory guidance on the specifics 

of how IOTA waitlist patients who are 

Medicare beneficiaries can decline 

reviewing their transplant organ offer 

acceptance criteria. 


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(3) Publication of IOTA Participant 

Results 

In the Specialty Care Models final 

rule (85 FR 61114), CMS established 

certain general provisions in 42 CFR 

part 512 subpart A that apply to all 

Innovation Center models. One such 

general provision pertains to rights in 

data. Specifically, in the Specialty Care 

Models final rule, we stated that to 

enable CMS to evaluate the Innovation 

Center models as required by section 

1115A(b)(4) of the Act and to monitor 

the Innovation Center models pursuant 

to § 512.150, in § 512.140(a) we would 

use any data obtained in accordance 

with § 512.130 and 512.135 to evaluate 

and monitor the Innovation Center 

models (85 FR 61124). We also stated 

that, consistent with section 

1115A(b)(4)(B) of the Act, CMS would 

disseminate quantitative and qualitative 

results and successful care management 

techniques, including factors associated 

with performance, to other providers 

and suppliers and to the public. We 

stated that the data to be disseminated 

would include, but would not be 

limited to, patient de-identified results 

of patient experience of care and quality 

of life surveys, as well as patient deidentified measure results calculated 

based upon claims, medical records, 

and other data sources. We finalized 

these policies in 42 CFR part 512.140(a). 

Consistent with these provisions, we 

proposed in section III. C.8.a(3) of the 

proposed rule, to publish results from 

all PYs of the IOTA Model. Specifically, 

for each PY, we intend to post 

performance across the achievement 

domain, efficiency domain, and quality 

domain for each IOTA participant. We 

would also identify each IOTA 

participant for the PY. The results 

would be published on the IOTA Model 

website. Given that we have proposed 

that the IOTA Model would include a 

process for IOTA participants to request 

a targeted review of the calculation of 

performance score which is calculated 

based on the various rates we intend to 

publish, CMS anticipates that it would 

publish these rates only after they have 

been finalized and CMS has resolved 

any targeted review requests timely 

received from IOTA participants under 

section II.E. of this final rule. We 

believed that the release of this 

information would inform the public 

about the cost and quality of care and 

about IOTA participants’ performance 

in the IOTA Model. This would 

supplement, not replace, the annual 

evaluation reports that CMS is required 

to conduct and release to the public 

under section 1115A(b)(4) of the Act. 

In section III.C.8.a(3) of the proposed 

rule, we considered requiring IOTA 

participants to publish their 

performance results on their own 

websites as well to increase 

transparency; however, we did not want 

to place additional reporting burden on 

IOTA participants, particularly because 

we proposed that CMS would publish 

the performance results, which should 

be adequate. 

We sought comment on our intent to 

post this information to our website, as 

well as the information we intend to 

post and the manner and timing of the 

posting. 

The following is a summary of 

comments received on our intent to 

publish this information to our website, 

as well as the information we intend to 

post and the manner and timing of the 

posting and our responses: 

Comment: A commenter urged CMS 

to ensure that any data shared on the 

CMS website is easily understandable 

for the public. 

Response: We thank the commenter 

for their feedback. We agree that it is 

important for patients to have 

information that is presented in a format 

that is easily reviewed and understood. 

We will review the results to be 

published and further consider how to 

best present information to both the 

public and kidney transplant hospitals 

in a meaningful manner, while abiding 

by the requirements of section 

1115A(b)(4) of the Act. 

Comment: A commenter stated that 

sharing results during the test phase 

should be limited to enrolled IOTA 

participants to avoid confusion and 

inequities. 

Response: We thank the commenter 

for their recommendation and sharing 

their concerns, however, section 

1115A(b)(4)(B) of the Act requires that 

model evaluation results be made 

available to the public. We believe it is 

important for patients to have model 

information available to them as they 

review IOTA participants. Additionally, 

access to these reports by all patients 

invites further research and evaluation 

by the transplant community to identify 

model requirements that should be 

applied to all kidney transplant 

hospitals and to identify areas of 

necessary changes in future iterations of 

the IOTA Model and transplant policy. 

Comment: A commenter suggested 

that CMS should develop charts or other 

tools that track and communicate 

performance to IOTA participants in 

real-time. The commenter also 

suggested that performance-related 

information should be made available to 

providers in addition to IOTA 

participants so they can better identify 

areas for improvement and change 

behaviors as necessary before each 

performance year ends. 

Response: We appreciate the 

commenter’s feedback. We suggest 

referring to section III.C.7 of this final 

rule, on data sharing, for more detailed 

comment and will consider this request 

for timely performance reports as we 

develop implementation methodology 

for data collection and data reporting to 

IOTA participants. 

Comment: A few commenters relayed 

their support for the publication of 

IOTA participant results. A commenter 

stated that they are eager to evaluate the 

model after its conclusion to determine 

whether the three domains were 

effective and whether the IOTA Model 

goals have been achieved, but also want 

to reevaluate further future 

improvements, encouraging CMS to 

publish annual interim reporting to 

assess the model’s progress. 

Response: We thank the commenters 

for their support and we reiterate the 

importance of transparency of 

performance results of IOTA 

participants to understand the pros and 

cons of the IOTA Model, what to modify 

in future iterations of the IOTA Model, 

and what components should be part of 

routine care for all kidney transplant 

hospitals in the future. Additionally, 

these performance results give patients, 

the transplant community and IOTA 

participants the opportunity to compare 

kidney transplant hospitals and identify 

where there is room for improvement 

year over year. 

After consideration of public 

comments, for the reasons set forth in 

this rule, we are finalizing our proposals 

to publish results from all PYs of the 

IOTA Model, without modification, as 

outlined in section III.C.8.a(3) of this 

final rule. Specifically, for each PY, we 

intend to identify each IOTA participant 

for the PY and to post performance 

across the achievement domain, 

efficiency domain, and quality domain 

for each IOTA participant on the IOTA 

Model website annually, as they become 

available. Not only does this meet CMS 

requirements, as previously discussed, 

but also demonstrates transparency for 

the transplant community. We will 

further consider the frequency and 

availability of interim performance 

results in future rulemaking. We direct 

readers to section III.C.7 of this final 

rule, for further details on data sharing. 

b. Health Equity Data Reporting 

(1) Demographic Data Reporting 

As previously discussed in section 

III.B. of this final rule, and throughout 

this final rule, disparities exist 


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National Academies Press https://www.ahrq.gov/ 

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iomracereport.pdf. 

308Sivashanker, K., & Gandhi, T.K. (2020). 

Advancing Safety and Equity Together. New 

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https://doi.org/10.1056/nejmp1911700. 

309Weinick, R.M., & Hasnain-Wynia, R. (2011). 

Quality Improvement Efforts Under Health Reform: 

How To Ensure That They Help Reduce 

Disparities—Not Increase Them. Health Affairs, 

30(10), 1837–1843. https://doi.org/10.1377/ 

hlthaff.2011.0617. 

310American Society for Quality. (2019). What is 

root cause analysis (RCA)? Asq.org. https://asq.org/ 

quality-resources/root-cause-analysis. 

311Agency for Healthcare Research and Quality. 

(2020). Plan-Do-Study-Act (PDSA) directions and 

examples. www.ahrq.gov. https://www.ahrq.gov/ 

health-literacy/improve/precautions/tool2b.html. 

312 Failure Modes and Effects Analysis (FMEA) 

Tool | IHI—Institute for Healthcare Improvement. 

(2017). www.ihi.org. https://www.ihi.org/resources/ 

Pages/Tools/ 

FailureModesandEffectsAnalysisTool.aspx. 

313 Kane, R. (2014). How to Use the Fishbone Tool 

for Root Cause Analysis. https://www.cms.gov/ 

medicare/provider-enrollment-and-certification/ 

qapi/downloads/fishbonerevised.pdf. 

314Sivashanker, K., & Gandhi, T.K. (2020). 

Advancing Safety and Equity Together. New 

England Journal of Medicine, 382(4), 301–303. 

https://doi.org/10.1056/nejmp1911700. 

315Booske, B.C., Athens, J.K., Kindig, D.A., Park, 

H., & Remington, P.L. (2010). County Health 

Rankings (Working Paper). https://

www.countyhealthrankings.org/sites/default/files/ 

differentPerspectivesForAssigning

WeightsToDeterminantsOfHealth.pdf. 

316ROI Calculator for Partnerships to Address the 

Social Determinants of Health Review of Evidence 

for Health-Related Social Needs Interventions. 

(2019). https://www.commonwealthfund.org/sites/ 

default/files/2019-07/COMBINED-ROI-EVIDENCEREVIEW-7-1-19.pdf. 

317Medicare Program; End-Stage Renal Disease 

Prospective Payment System, Payment for Renal 

Dialysis Services Furnished to Individuals with 

Acute Kidney Injury, End-Stage Renal Disease 

Quality Incentive Program, and End- Stage Renal 

Disease Treatment Choices model NPRM (citing A 

Guide to Using the Accountable Health 

Communities Health-Related Social Needs 

Screening Tool) 87 FR 38554 (Jun. 28, 2022). 

318 De Marchis, E., Brown, E., Aceves, B., Loomba, 

V., Molina, M., Cartier, Y., Wing, H., Ma, L., & 

Gottlieb. (n.d.). State of the Science of Screening in 

Healthcare Settings siren State of the Science on 

Social Screening in Healthcare Settings Summer 

2022. https://sirenetwork.ucsf.edu/sites/default/ 

files/2022-06/final%20SCREEN%20State-ofScience-Report%5B55%5D.pdf. 

319 Ibid. 

throughout the transplant process. 

These circumstances highlight the 

importance of data collection and 

analysis that includes race, ethnicity, 

language, disability, sexual orientation, 

gender identity, and sex characteristics 

or other demographics by health care 

facilities. Such data are necessary for 

integration of health equity in quality 

programs, because the data permits 

stratification by patient 

subpopulation.307 308 Stratified data can 

produce meaningful measures that can 

be used to expose health disparities, 

develop focused interventions to reduce 

them, and monitor performance to 

ensure interventions to improve care do 

not have unintended consequences for 

certain patients.309 Furthermore, quality 

programs are carried out with wellknown and widely used standardized 

procedures, including but not limited 

to, root cause analysis, plan-do-studyact (PDSA) cycles, health care failure 

mode effects analysis, and fish bone 

diagrams. These are common 

approaches in the health care industry 

to uncover the causes of problems, show 

the potential causes of a specific event, 

test a change that is being implemented, 

prevent failure by correcting a process 

proactively, and identify possible causes 

of a problem and sort ideas into useful 

categories, respectively.310 311 312 313

Adding a health equity prompt to these 

standardized procedures integrates a 

health equity lens within the quality 

structure and cues considerations of the 

patient subpopulations who receive care 

and services from a transplant 

hospital.314

To align with other Innovation Center 

efforts, we considered proposing that, 

beginning with the first PY and each PY 

thereafter, each IOTA participant would 

be required to collect and report to CMS 

demographic and SDOH data pursuant 

to 42 CFR part 403.1110(b) for the 

purposes of monitoring and evaluating 

the model. We considered proposing 

that, in conducting the collection 

required under this section, the IOTA 

participant would make a reasonable 

effort to collect demographic and social 

determinants of health data from all 

attributed patients but, in the case the 

IOTA participant attributed patient 

elects not to provide such data to the 

IOTA participant, the IOTA participant 

would indicate such election by the 

attributed patient in its report to CMS. 

We decided not to propose the 

collection of demographic data as this 

data is already collected by OPOs and 

the SRTR, thereby making such a 

requirement for purposes of this model 

potentially duplicative and 

unnecessarily burdensome. We wish to 

minimize reporting burden on IOTA 

participants where possible to ensure 

sufficient time and effort is spent 

adjusting to the requirements of a 

mandatory model. 

We solicited public comment on the 

decision not to propose the collection of 

this data and potential applications. 

The following is a summary of the 

comments received and our responses: 

Comment: A few commenters agreed 

with CMS’ decision not to propose the 

collection of demographic data as this 

data is already collected, thereby 

making such a requirement for purposes 

of this model potentially duplicative 

and unnecessarily burdensome. 

Response: We thank commenters for 

their support in our decision to not 

include demographic data reporting in 

the IOTA Model. 

After consideration of the public 

comments we received, we are not 

finalizing any requirements to include 

demographic data reporting in the IOTA 

Model. 

(2) Health Related Social Needs (HRSN) 

Data Reporting 

The Innovation Center is charged with 

testing innovations that improve quality 

and reduce the cost of health care. There 

is strong evidence that non-clinical 

drivers of health are the largest 

contributor to health outcomes and are 

associated with increased health care 

utilization and costs.315 316 These 

individual-level, adverse social 

conditions that negatively impact a 

person’s health or healthcare are 

referred to as ‘‘health-related social 

needs’’ or HRSNs.317 CMS aims to 

expand the collection, reporting, and 

analysis of standardized HRSNs data in 

its efforts to drive quality improvement, 

reduce health disparities, and better 

understand and address the unmet 

social needs of patients. Standardizing 

HRSN Screening and Referral as a 

practice can inform larger, communitywide efforts to ensure the availability of 

and access to community services that 

are responsive to the needs of Medicare 

beneficiaries. 

HRSN screening is becoming 

increasingly common nationally, but 

implementation is not uniform across 

geography or health care setting. A 

literature review of national surveys 

measuring prevalence of social 

screening found that almost half of State 

Medicaid agencies have established 

managed care contracting requirements 

for HRSN screening in Medicaid.318 It 

also found that health care payers and 

delivery organizations or both reported 

a screening prevalence of 55–77 percent, 

with ‘‘the highest estimate reported 

among American Hospital Association 

member hospitals.’’ 319 Despite 

screening proliferation and generally 

positive views toward screening among 

both patients and health care providers, 

implementation of screening and 

referral policies for beneficiaries of CMS 

programs with similar health—and even 

demographic—profiles may be 

inconsistent, potentially exacerbating 


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disparities in the comprehensiveness 

and quality of care. 

One of the goals stated in the 

Innovation Center Strategy Refresh for 

advancing system transformation is to 

require all new models to collect and 

report demographic and SDOH data. 

Thus, in addition to the proposed health 

equity requirements in section III.C.8.b. 

of this final rule, we considered 

proposing a requirement that IOTA 

participants conduct HRSN screening 

for at least four core areas—food 

security, housing, transportation, and 

utilities. We recognize these areas as 

some of the most common barriers to 

kidney transplantation and the most 

pertinent for the IOTA participant 

patient population. However, given the 

need for a psychosocial evaluation prior 

to addition to the waitlist, we 

understand that such a requirement may 

be redundant given current clinical 

practices, we have refrained from 

making such a proposal. 

We sought comment on whether we 

should include a requirement for IOTA 

participants to conduct HRSN screening 

and report HRSN data in a form and 

manner specified by CMS each PY for 

their attributed patients. We sought 

input on following the questions in this 

section, and comment on any aspect of 

the psychosocial evaluation of 

waitlisted patients and how this 

compares to HRSN screenings for the 

four domains—food security, housing, 

transportation, and utilities. Even if 

CMS were to adopt an HRSN screening 

and reporting requirement in the final 

rule, CMS might consider delaying the 

implementation of such a requirement. 

• When evaluating a patient for 

potential addition to the kidney 

transplant waitlist, what questions are 

asked as part of the psychosocial 

evaluation? 

• How might a psychosocial 

evaluation compare to an HRSN 

screening? What HRSNs are identified 

as part of a psychosocial evaluation? 

• What data is collected from the 

psychosocial evaluation on HRSNs? 

• If HRSNs are identified as part of 

the evaluation process, what, if any, 

steps are taken to assist the patient in 

addressing these needs and improving 

their transplant readiness? 

• If HRSNs are identified of a patient 

already on the transplant waitlist, how 

might this affect their status on the 

transplant waitlist? Could a patient be 

removed from the transplant waitlist if 

HRSNs are identified that may impact 

transplant readiness? 

• What, if any, follow-up is 

conducted with waitlist patients that 

have identified HRSNs? 

• Are there any concerns with HRSN 

screening and data collection 

requirements? 

We received 33 submissions on this 

RFI. We thank commenters for their 

comments. While we will not be 

responding to specific comments 

submitted in response to this RFI, we 

have shared all the comments received 

with the appropriate agencies and 

offices for consideration in subsequent 

rulemaking for the inclusion of 

demographic data reporting. 

c. Health Equity Plans 

To further align with other Innovation 

Center models and promote health 

equity across the transplant process, we 

proposed that, for PY 2 through PY 6, 

each IOTA participant must submit to 

CMS, in a form and manner and by the 

date(s) specified by CMS, a health 

equity plan. Given that this would be a 

mandatory model, we proposed that the 

health equity plan be voluntary in the 

first PY of the model to allow IOTA 

participants time to adjust to model 

requirements. We proposed that the 

health equity plan must: 

• Identify target health disparities. 

We proposed to define ‘‘target health 

disparities’’ as health disparities 

experienced by one or more 

communities within the IOTA 

participant’s population of attributed 

patients that the IOTA participant 

would aim to reduce. 

• Identify the data sources used to 

inform the identification of target health 

disparities. 

• Describe the health equity plan 

intervention. We proposed to define 

‘‘health equity plan intervention’’ as the 

initiative(s) the IOTA participant would 

create and implement to reduce target 

health disparities. 

• Include a resource gap analysis. We 

proposed to define ‘‘resource gap 

analysis’’ as the resources needed to 

implement the health equity plan 

interventions and identifies any gaps in 

the IOTA participant’s current resources 

and the additional resources that would 

be needed. 

• Include a health equity project plan. 

We proposed to define ‘‘health equity 

project plan’’ as the timeline for the 

IOTA participant to implement the 

IOTA participant’s the health equity 

plan. 

• Identify health equity plan 

performance measure(s). We proposed 

to define ‘‘health equity performance 

plan measure(s)’’ as one or more 

quantitative metrics that the IOTA 

participant would use to measure the 

reductions in target health disparities 

arising from the health equity plan 

interventions. 

• Identify health equity goals and 

describes how the IOTA participant 

would use the health equity goals to 

monitor and evaluate progress in 

reducing targeted health disparities. We 

proposed to define ‘‘health equity goals’’ 

as targeted outcomes relative to the 

health equity plan performance 

measures for the first PY and all 

subsequent PYs. 

In the proposed rule, we proposed 

that once an IOTA participant submits 

their health equity plan to CMS, CMS 

would use reasonable efforts to approve 

or reject the health equity plan within 

60 business days (89 FR 43582). We 

proposed that if CMS approves the 

IOTA participant’s health equity plan, 

the IOTA participant must engage in 

activities related to the execution of the 

IOTA participant’s health equity plan, 

including implementing health equity 

plan interventions and monitoring and 

evaluating progress in reducing target 

health disparities. Discrimination on the 

basis of race, ethnicity, national origin, 

religion, or gender in activities related 

to the execution of the IOTA 

participant’s health equity plan would 

be prohibited. 

Should CMS determine that the IOTA 

participant’s health equity plan does not 

satisfy the proposed requirements and is 

inconsistent with the applicable CMS 

Health Equity Plan guidance, does not 

provide sufficient evidence or 

documentation to demonstrate that the 

health equity plan is likely to 

accomplish the IOTA participant’s 

intended health equity goals, or is likely 

to result in program integrity concerns 

or negatively impact beneficiaries’ 

access to quality care, we proposed that 

CMS may reject the health equity plan 

or require amendment of the health 

equity plan at any time, including after 

its initial submission and approval (89 

FR 43582). 

We proposed that if CMS rejects the 

IOTA participant’s health equity plan, 

in whole or in part, the IOTA 

participant must not, and must require 

its IOTA collaborators to not, conduct 

health equity activities identified in the 

health equity plan that have been 

rejected by CMS (89 FR 43582). 

We proposed that in PY 3, and each 

subsequent PY, in a form and manner 

and by the date(s) specified by CMS, 

each IOTA participant would be 

required to submit to CMS an update on 

its progress in implementing its health 

equity plan (89 FR 43582). We stated 

that this update would be required to 

include all of the following: 

• Updated outcomes data for the 

health equity plan performance 

measure(s). 


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• Updates to the resource gap 

analysis. 

• Updates to the health equity project 

plan. 

We proposed that if an IOTA 

participant fails to meet the 

requirements of the heath equity plan 

described in this section of the proposed 

rule, the IOTA participant would be 

subject to remedial action as specified 

in section III.C.16. of this final rule. 

Such remedial actions could include 

requesting a corrective action plan, 

recoupment of any upside risk 

payments; or termination from the 

model (89 FR 43582). 

We solicited feedback on these 

proposals. We also solicited comment 

on the potential impact of creation of a 

health equity plan, whether such plans 

should be voluntary, and whether 

health equity plans should only be a 

requirement in later PYs of the IOTA 

Model. 

The following is a summary of the 

comments received on our proposed 

health equity plan provisions, whether 

such plans should be voluntary, and 

whether health equity plans should be 

a requirement in later PYs of the IOTA 

Model and our responses: 

Comment: Several commenters 

applauded CMS’ proposed requirement 

to integrate health equity plans into the 

model framework. Commenters 

expressed support stating the health 

equity plans provide a context-specific 

system-level approach to addressing the 

social determinants of health and the 

health equity plan provision will 

encourage IOTA participants to identify 

health equity gaps and to develop and 

implement targeted strategies to address 

those gaps. 

Response: We appreciate the 

commenters’ support of the IOTA health 

equity plan. We acknowledge 

commenters’ support for CMS’ and the 

IOTA model’s goal to promote health 

equity across the transplant process. 

Comment: A few commenters 

suggested that CMS should not pursue 

the health equity plan provision. 

Several commenters supported the 

proposed requirements to delay the 

submission of the heath equity plans 

until performance year two, however, 

other commenters recommended CMS 

reconsider requiring each IOTA 

participant to submit to CMS an update 

on its progress in implementing its 

health equity plan (in PY 3, and each 

subsequent PY). Some commenters 

expressed the health equity plan 

requirement would be burdensome and 

inhibit IOTA participants resources and 

their ability to successfully implement 

and operationalize the model 

requirements. For example, commenters 

stated the health equity plans would be 

an unfair requirement and burdensome 

for transplant hospitals that have a 

larger low-income patient population 

and would penalize model participants’ 

efforts to address health equity issues. 

Other commenters suggested that to 

reduce burden, CMS should provide 

clarity on the health equity plan criteria. 

For example, commenters stated CMS 

should consider providing IOTA 

participants examples of a 

comprehensive health equity plan that 

describes the health equity plan 

inclusion criteria, and clear and 

measurable endpoints on which CMS 

would deem suitable for approval. 

Response: We thank the commenters 

for their feedback. However, we disagree 

with the suggestion to remove the health 

equity plan provision from the model. 

We believe health equity plans are vital 

to incentivize meaningful changes and 

promote health equity across the 

transplant process. However, we 

recognize that the IOTA health equity 

plan requirement may be burdensome 

for some model participants, and CMS 

solicited comment on whether such 

plans should be voluntary. With respect 

to comments received, we are modifying 

our proposal to allow health equity 

plans to be a voluntary provision for all 

performance years. 

Comment: Several commenters 

recommended that CMS provide upfront 

investment funding to support the 

development and implementation of the 

IOTA participants’ health equity plans. 

Several commenters stated the health 

equity plan requirements would be 

burdensome to model participants and 

would require significant resources and 

investments involving administrative, 

human and operational capital from 

model participants to be successful. In 

addition, some commenters stated that 

the health equity plan requirement fails 

to consider or address patients’ barriers 

such as high out-of-pocket costs, or 

patients living in rural areas. 

Other commenters expressed their 

support of the health equity plan policy 

but expressed concerns that the lack of 

upfront investments of resources and 

the design rigor would make the health 

equity plan requirements unlikely to 

yield meaningful results for patients. 

For example, these commenters 

suggested CMS should include upfront 

financial support to help empower 

participating hospitals to fully engage in 

the IOTA Model without compromising 

their financial stability or the quality of 

care they provide to their communities 

and patients. A commenter stated that 

tasking transplant hospitals to address 

patient’s social risk factors and the 

social determinants of health via the 

health equity plan is beyond the 

purview or expertise of transplant 

hospitals. The commenter stated that 

the social determinants of health issues 

among transplant hospital patients are 

generally managed by social workers 

(and/or non-clinical staff) within the 

patients’ communities, and therefore, 

supplemental funding would be needed 

to hire appropriate staff and support the 

resources needed to design and 

implement the IOTA health equity plan. 

Other commenters suggested CMS 

should consider issuing waivers to 

allow for broader financial assistance 

programs for underserved communities 

who may be facing additional barriers 

and social risk factors such as food 

insecurity, housing insecurity, 

inaccessible transportation and high 

childcare costs. A commenter suggested 

CMS should include additional 

incentives or supplemental funding for 

local healthcare providers and dialysis 

units to screen patients for social 

determinants of health metrics and link 

patients to community-based services. 

Response: We appreciate the 

commenters’ suggestions for CMS to 

include supplemental funding for the 

health equity plan provision. We believe 

it is important that IOTA participants 

receive the necessary support to 

successfully implement their health 

equity plan. We sought comment on the 

potential impact of creation of a health 

equity plan, and we will consider 

including health equity plan 

supplemental funding opportunities in 

future rulemaking. 

Comment: Some commenters 

expressed concern that the health equity 

plan provision may promote 

discriminatory practices on the basis of 

race. Specifically, commenters stated 

the health equity plan requirement 

incentivizes model participants to 

prioritize certain group(s) over others in 

a discriminatory manner. A commenter 

suggested that the IOTA health equity 

plan ‘‘target health disparities’’ 

requirement should be defined in raceneutral terms, and CMS should prohibit 

IOTA participants’ health equity plans 

from being implemented in a 

discriminatory manner. 

Response: We acknowledge the 

commenters concerns. Our proposal 

states that ‘‘discrimination on the basis 

of race, ethnicity, national origin, 

religion, or gender in activities related 

to the execution of the IOTA 

participant’s health equity plan would 

be prohibited.’’ We believe there are 

significant safeguards in place to assure 

health equity plans will not be designed 

or implemented in a discriminatory 

manner. 


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Comment: Some commenters 

recommended CMS implement the 

IOTA health equity plans through the 

CMS Hospital Inpatient Quality 

Reporting (IQR) Program. For example, 

commenters stated they do not agree 

that the IOTA model is an appropriate 

venue to promote health equity and the 

health equity plan provision would be 

better served within the IQR program 

given transplant hospitals already 

participant in IQR. Commenters 

suggested the IOTA health equity plan 

requirements would be duplicative, 

create additional administrative burden, 

and be confusing for hospitals given 

CMS has already introduced the 

Hospital Commitment to Health Equity 

via the IQR program. Other commenters 

suggested CMS should implement the 

model’s health equity plans through The 

Joint Commission instead of an IOTAspecific plan. Another commenter 

recommended dialysis centers would be 

a more suited environment to 

implement health equity plans rather 

than via transplant hospitals. 

Response: We disagree with 

implanting IOTA health equity plans 

within other CMS or hospital programs. 

The IOTA Model structure is designed 

to promote improvement activities 

across selected transplant hospitals, 

including the social determinants of 

health, and health equity. The IOTA 

health equity plans are designed 

specifically for the selected transplant 

hospital participants. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

our proposed provisions on health 

equity plans at § 512.444(a)(1–7) with 

slight modifications. Specifically, we 

are redesignating what was proposed at 

§ 512.444 to be § 512.446. Additionally, 

we proposed at § 512.444(a) that the 

health equity plan be voluntary for 

IOTA participants for PY 1 and 

mandatory for PY 2 through PY 6. We 

are instead finalizing at § 512.446(a) that 

a health equity plan shall be voluntarily 

submitted by an IOTA participant for all 

performance years (PY 1 through PY 6) 

in a form and manner and by the date(s) 

specified by CMS. We are also finalizing 

that a health equity plan voluntarily 

submitted by an IOTA participant must 

include all elements as proposed at 

§ 512.446(a)(1–7), without modification. 

Additionally, we are finalizing as 

proposed without modification the 

definitions of target health disparities, 

health equity plan intervention, 

resource gap analysis, health equity 

project plan, health equity performance 

plan measure(s) and health equity goals 

at § 512.402. We also note that we are 

finalizing the proposed definition of 

health equity performance plan 

measure(s) with a slight modification to 

correct the defined term to read as 

follows: health equity plan performance 

measure(s). In the proposed rule at 89 

FR 43582, we proposed to define health 

equity performance plan measure(s) as 

one or more quantitative metrics that 

the IOTA participant would use to 

measure the reductions in target health 

disparities arising from the health 

equity plan interventions. However, in 

the proposed rule at 89 FR 43582, we 

proposed that health equity plans must 

identify health equity plan performance 

measure(s). Additionally, in the 

proposed rule at 89 FR 43582, we 

proposed to define health equity goals 

as targeted outcomes relative to the 

health equity plan performance 

measures for the first PY and all 

subsequent PYs. As such, we are 

finalizing the definition of health equity 

plan performance measure(s) at 

§ 512.402 as one or more quantitative 

metrics that the IOTA participant would 

uses to measure the reductions in target 

health disparities arising from the 

health equity plan interventions. 

9. Overlap With Other Innovation 

Center Models, CMS Programs, and 

Federal Initiatives 

a. Other Innovation Center Models and 

CMS Programs 

We proposed that IOTA participants 

would be allowed to simultaneously 

participate in IOTA and other CMS 

programs and models. The IOTA Model 

would overlap with several other CMS 

programs and models and Departmental 

regulatory efforts, and we sought 

comment on our proposals to account 

for overlap. 

KCC Model—The KCC Model is a 

voluntary Innovation Center model for 

nephrologists, dialysis facilities, 

transplant providers, and other 

providers and suppliers that are focused 

on beneficiaries with CKD and 

beneficiaries with ESRD. The KCC 

Model performance period began on 

January 1, 2022, and is scheduled to end 

December 31, 2026. As such, the KCC 

Model would run concurrently for 2 

years with the IOTA Model, which 

would have a proposed start date of 

January 1, 2025. The KCC Model 

includes a payment incentive called the 

Kidney Transplant Bonus (KTB). KCC 

participants are eligible for up to 

$15,000 for every aligned beneficiary 

with CKD or ESRD who receives a 

kidney transplant, whether from a living 

or deceased donor, provided the 

transplant remains successful. Kidney 

Contracting Entities (KCEs) participating 

in the KCC Model are also required to 

include a transplant provider, defined 

as a transplant program that provides 

kidney transplants, a transplant hospital 

that provides kidney transplants, a 

transplant surgeon who provides kidney 

transplants, a transplant nephrologist, a 

transplant nephrology practice, an OPO, 

or another Medicare-enrolled provider 

or supplier that provides kidney 

transplant related covered services to 

Medicare beneficiaries. 

Though transplant hospitals are one 

of the types of health care provider 

eligible to serve as a transplant provider, 

CMS has found relatively low 

participation by transplant hospitals in 

the KCC Model. Across the 100 KCEs 

participating in the model in 2023, there 

were only 10 kidney transplant 

hospitals participating in the model and 

serving as the transplant provider for 

the relevant KCE. In discussions with 

participants and with kidney transplant 

hospitals, CMS heard a few reasons for 

this relatively low rate of participation. 

CMS heard that it was difficult 

administratively for kidney transplant 

hospitals to participate as they are part 

of corporate entities that may have a 

larger organizational focus on broader 

shared savings efforts, rather than just 

for the kidney population. 

We proposed that any providers or 

suppliers participating in the KCC 

Model that meet the proposed IOTA 

participant eligibility requirements 

would still be required to participate in 

the IOTA Model. We believed that 

granting an exemption to the IOTA 

Model for these providers or suppliers 

could disrupt the patterns of care being 

tested in the KCC Model. We also 

believed that a prohibition on dual 

participation could prevent enough 

KCEs from having a transplant provider 

and meeting model requirements, which 

could undermine participation in the 

KCC model. 

We considered proposing that any 

transplant hospitals participating in the 

IOTA Model would not be able to 

participate in the KCC Model and be 

able to receive any portion of a Kidney 

Transplant Bonus payment. However, 

we did not believe that this was 

necessary given that there are currently 

only 10 transplant hospitals 

participating in the KCC Model, 

meaning that dual participation should 

not substantially affect the evaluation of 

either model. We also considered 

proposing that any kidney transplant for 

an aligned beneficiary that results in a 

Kidney Transplant Bonus being paid out 

in the KCC Model would not be counted 

for calculating an upside risk payment 

or downside risk payment in the IOTA 

Model. We decided not to propose this 

policy because of potential disruption to 


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the KCC Model, which would be in its 

fourth performance year when the 

proposed IOTA Model would likely 

begin in 2025. Additionally, the Kidney 

Transplant Bonus payment in the KCC 

Model serves multiple functions within 

that model, as it also incentivizes posttransplant care for up to three years 

post-transplant. 

We believed that it is important to test 

both the IOTA Model and the KCC 

Model, to test the effectiveness of 

payment incentives for kidney 

transplants at different points of the care 

coordination process. The IOTA Model 

would test the effect of upside and 

downside risk payments for kidney 

transplant hospitals, while the KCC 

Model tests how nephrologists and 

other providers and suppliers can 

support transplantation in the overall 

care coordination process. Upside risk 

payment and downside risk payment 

from the IOTA Model would not be 

counted as expenditures for purposes of 

the KCC Model, as they would not be 

adjustments to claims for individual 

beneficiaries, but would be paid out in 

a lump sum based on aggregate 

performance directly tied to individual 

beneficiary level claims. Additionally, 

we do not want to potentially hurt KCC 

participants that have beneficiaries who 

could benefit from the KCC participant’s 

potential high performance in the IOTA 

Model. 

Both the KCC Model and the IOTA 

Model would include explicit 

incentives for participants when aligned 

beneficiaries receive kidney transplants; 

and a transplant hospital participating 

in both models would be eligible to 

receive a portion of a Kidney Transplant 

Bonus from a KCE under the KCC Model 

and an upside risk payment or 

downside risk payment under the IOTA 

Model. Kidney transplants represent the 

most desired and cost-effective 

treatment for most beneficiaries with 

ESRD, but providers and suppliers may 

currently have insufficient financial 

incentives to assist beneficiaries through 

the transplant process because dialysis 

generally results in higher 

reimbursement over a more extended 

period of time than a transplant. As a 

result, CMS believed it would be 

appropriate to allow a transplant 

hospital to receive both an upside risk 

payment or downside risk payment 

from the IOTA Model and portion of a 

Kidney Transplant Bonus from the KCC 

Model and the IOTA Model 

simultaneously to assess their effects on 

the transplant rate. 

ETC Model—The ETC Model is a 

mandatory Innovation Center model 

that includes as participants certain 

clinicians who manage dialysis patients 

(referred to as Managing Clinicians) and 

ESRD facilities and provides incentives 

for increasing rates of home dialysis, 

transplant waitlisting, and living donor 

transplantation. The ETC Model began 

on January 1, 2021, and the model 

performance period is scheduled to end 

December 31, 2025, and it would have 

one year of overlap with the proposed 

model performance period of the IOTA 

Model beginning January 1, 2025. The 

ETC Model includes an upward or 

downward payment adjustment called 

the Performance Payment Adjustment 

(PPA) that is calculated in part based on 

the rates of transplant waitlisting and 

living donor transplants for the 

population of beneficiaries aligned to a 

participating Managing Clinician or 

ESRD facility. 

We believed that the goals of the ETC 

Model and the goals of the proposed 

IOTA Model are aligned. As CMS 

described in the 2020 rule finalizing the 

ETC Model (85 FR 61114), ‘‘[t]he ETC 

Model [is] a mandatory payment model 

focused on encouraging greater use of 

home dialysis and kidney transplants.’’ 

We believe that the IOTA Model would 

then test a corresponding incentive on 

the transplant hospital side to further 

assist beneficiaries in moving through 

the transplant process to get a 

transplant. CMS believed it is 

appropriate to test both models as the 

ETC Model does not include direct 

incentives for transplant hospitals and 

we believe that transplant hospitals play 

a very important role in the transplant 

process. 

We note for the ETC Model, 

participants are selected based on their 

location in a Selected Geographic Area, 

which are randomly selected Hospital 

Referral Regions (HRR), stratified by 

census region, representing 

approximately one third of the country, 

as well as HRRs predominately 

comprised of ZIP codes in Maryland. 

This is a different randomization 

strategy than is being proposed for the 

IOTA Model. It is our intent to look at 

the effects of each model and its 

randomization strategy on the transplant 

rate as part of our model evaluation, 

which is discussed in section III.C.12 of 

this final rule. 

Additionally, we note that the ETC 

Model includes the ETC Learning 

Collaborative as part of its model test. 

This is further discussed in section 

III.C.13. of this final rule, where we 

sought feedback about the experience of 

kidney transplant hospitals, OPOs, ETC 

Participants, and other interested parties 

engaged in the ETC Learning 

Collaborative, as we consider how to 

best promote shared learning in the 

IOTA Model. 

Other Medicare Alternative Payment 

Models (APMs)—For the Medicare 

Shared Savings Program (the Shared 

Savings Program) and the ACO 

Realizing Equity, Access, and 

Community Health (ACO REACH) 

Model, which focus on total cost of care, 

payment adjustments made under the 

IOTA Model would not be counted as 

program expenditures. The Medicare 

Shared Savings Program regulations 

address payments under a model, 

demonstration, or other time-limited 

program when defining program 

expenditures. Specifically, when 

calculating Shared Savings and Shared 

Losses for an ACO in the Shared 

Savings Program, CMS considers only 

‘‘individually beneficiary identifiable 

final payments made under a 

demonstration, pilot, or time limited 

program’’ to be a part of the ACO’s 

Medicare Parts A and B fee-for-service 

expenditures (see, for example, 42 CFR 

425.605(a)(5)(ii)). Similarly, in the ACO 

REACH Model, an ACO’s performance 

year expenditure is defined to include 

the total payment that has been made by 

Medicare fee-for-service for services 

furnished to REACH Beneficiaries (see 

ACO REACH Model First Amended and 

Restated Participation Agreement (Dec. 

1, 2023)). Payments under the IOTA 

Model are not directly tied to any 

specific beneficiary. Instead, they are 

made on a lump sum basis based on 

aggregate performance across transplant 

patients seen by the center during the 

performance year. IOTA Model 

payments, therefore, would not be 

considered by the Shared Savings 

Program as an amount included in Part 

A or B fee-for-service expenditures or by 

the ACO REACH Model as an amount 

included in payment for REACH 

Beneficiaries’ Medicare fee-for-service 

services. 

Hospital VBP Program—CMS adjusts 

payments to hospitals under the 

Inpatient Prospective Payment System 

(IPPS) based on their performance under 

the Hospital VBP Program. However, the 

Hospital VBP Program does not 

currently include any measures related 

to transplant services. In addition, 

transplant services are only offered by a 

subset of hospitals. Given the different 

focuses between the Hospital VBP 

Program and the IOTA Model, we are 

not proposing any changes to the 

Hospital VBP Program and believe it is 

appropriate to test the IOTA Model 

alongside the existing Hospital VBP 

Program. 

b. Overlap With Departmental 

Regulatory Efforts 

December 2020 OPO Conditions for 

Coverage—In December 2020, CMS 


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320Sumit Mohan, Miko Yu, Kristen L. King, S. Ali 

Husain, Increasing Discards as an Unintended 

Consequence of Recent Changes in United States 

Kidney Allocation Policy, Kidney International 

Reports, Volume 8, Issue 5, 2023, Pages 1109–1111, 

ISSN 2468–0249, https://doi.org/10.1016/ 

j.ekir.2023.02.1081. 

321https://www.federalregister.gov/d/2019-20736/ 

p-87. 

322Request for Information; Health and Safety 

Requirements for Transplant Programs, Organ 

Procurement Organizations, and End-Stage Renal 

Disease Facilities. https://www.federalregister.gov/ 

documents/2021/12/03/2021-26146/request-forinformation-health-and-safety-requirements-fortransplant-programs-organ-procurement. 

323OPTN Board adopts new transplant program 

performance metrics—OPTN. (2021, December 16). 

Optn.transplant.hrsa.gov. Retrieved May 30, 2023, 

from https://optn.transplant.hrsa.gov/news/optnboard-adopts-new-transplant-programperformance-metrics/. 

issued a final rule titled ‘‘Organ 

Procurement Organizations Conditions 

for Coverage: Revisions to the Outcome 

Measure Requirements for Organ 

Procurement Organizations; Final Rule’’ 

(85 FR 77898). The final rule revised the 

OPO CfCs and was intended to increase 

donation rates and organ transplantation 

rates by replacing the previous outcome 

measures. In general, the new outcome 

measures improve on the prior measures 

by using objective, transparent, and 

reliable data, rather than OPO selfreported data, to establish the donor 

potential in the OPO’s DSA. The rule 

also permits CMS to begin decertifying 

underperforming OPOs beginning in 

2026. 

We believed that the proposed IOTA 

Model supports the policies set out in 

that final rule. We noted that we have 

received feedback from OPOs and other 

interested parties that OPOs are 

required to procure more organs, while 

there is not a corresponding incentive 

on the transplant hospital side to 

transplant more organs into 

beneficiaries. We also noted that the 

number of discarded organs has risen 

from 21 percent to 25 percent from 2018 

to 2022.320 Though there have been 

other changes during that time, 

including the updated organ allocation 

system and the effects of the COVID–19 

pandemic, this rise in discarded organs 

is highly concerning, and we believed 

that the IOTA Model can help to 

mitigate this troubling rise by giving 

transplant hospitals an incentive to 

accept more offers that they may not 

have accepted without that incentive. 

In September 2019, CMS finalized a 

rule titled ‘‘Medicare and Medicaid 

Programs; Regulatory Provisions to 

Promote Program Efficiency, 

Transparency, and Burden Reduction; 

Fire Safety Requirements for Certain 

Dialysis Facilities; Hospital and Critical 

Access Hospital (CAH) Changes To 

Promote Innovation, Flexibility, and 

Improvement in Patient Care’’ (84 FR 

51732). This rule was in part motivated 

by a commitment across CMS and HHS 

to ‘‘the vision of creating an 

environment where agencies 

incorporate and integrate the ongoing 

retrospective review of regulations into 

Department operations to achieve a 

more streamlined and effective 

regulatory framework.’’ 

One of the major provisions finalized 

in this rule was the removal of data 

submission, clinical experience, and 

outcomes requirements for Medicare reapproval that were previously required 

of transplant hospitals participating in 

the Medicare program. As described in 

the rule, CMS had put in place 

additional CoPs in the March 2007 final 

rule (72 FR 15198) in an effort to 

increase the quality of care by 

specifying minimal health and safety 

standards for transplant hospitals. In 

addition, outcome metrics (1 year graft 

and patient survival) were included in 

the regulation and mirrored the OPTN 

outcomes metrics as calculated by the 

SRTR. 

CMS removed the outcomes 

requirements for a few key reasons. 

First, the concern was that transplant 

centers were also subject to OPTN 

policies, so parallel regulation on the 

CMS side was duplicative. Additionally, 

the concern was that ‘‘increased 

emphasis on organ and patient survival 

rates, as key metrics of transplant 

performance, created incentives for 

transplant programs to select organs 

most likely to survive after transplant 

without rejection, and to select 

recipients most likely to survive after 

the transplant.’’ This focus had the 

effect of creating ‘‘performance 

standards that focused only on organ 

and patient survival rates for those who 

received a transplant, not on survival 

rates of patients awaiting 

transplant.’’ 321

In December 2021, CMS published an 

RFI titled ‘‘Health and Safety 

Requirements for Transplant Programs, 

Organ Procurement Organizations, and 

End-Stage Renal Disease Facilities’’ (86 

FR 68594).322 In this RFI, CMS asked 

questions about the overall transplant 

ecosystem, with goal of helping ‘‘to 

inform potential changes that would 

create system-wide improvements, 

which would further lead to improved 

organ donation, organ transplantation, 

quality of care in dialysis facilities, and 

improved access to dialysis services.’’ 

We noted that we were seeking ways 

to harmonize policies across the 

primary HHS agencies (CMS, HRSA, 

and the Food and Drug Administration 

(FDA)) that are involved in regulating 

stakeholders in the transplant ecosystem 

so that our requirements are not 

duplicative, conflicting, or overly 

burdensome. We asked if there any 

current requirements for transplant 

programs, ESRD facilities, or OPOs that 

are unnecessarily duplicative of, or in 

conflict with, OPTN policies or policies 

that are covered by other government 

agencies. We also asked about the 

impacts of these duplicative 

requirements on organ utilization and 

transplant program/ESRD facility/OPO 

quality and efficiency (86 FR 68596). 

Given the concerns described in these 

past efforts, the OPTN has been in part 

responsive to concerns from interested 

parties about their metrics and effects 

and has expanded which metrics they 

are evaluating transplant centers for 

their performance. In December 2021, 

the OPTN approved four new riskadjusted metrics to be used to monitor 

transplant program performance, 

including 90-day graft survival hazard 

ratio, 1-year conditional graft survival 

hazard ratio, pre-transplant mortality 

rate ratio, and offer acceptance ratio.323

This added two new metrics for areas 

beyond simply looking at transplant 

survival, and looked at a more holistic 

view of patient care for beneficiaries on 

the transplant list. There is a critical 

role for both the Department and the 

OPTN with regard to the transplant 

ecosystem. The final rule governing the 

operation of the OPTN from 1996 (63 FR 

16296) stated the following: 

The Department believes that the 

transplantation network must be 

operated by professionals in the 

transplant community, and that both 

allocation and other policies of the 

OPTN should be developed by 

transplant professionals, in an open 

environment that includes the public, 

particularly transplant patients and 

donor families. It is not the desire or 

intention of the Department to interfere 

in the practice of medicine. This rule 

does not alter the role of the OPTN to 

use its judgment regarding appropriate 

medical criteria for organ allocation nor 

is it intended to circumscribe the 

discretion afforded to doctors who must 

make the difficult judgments that affect 

individual patients. At the same time, 

the Department has an important and 

constructive role to play, particularly on 

behalf of patients. Human organs that 

are given to save lives are a public 

resource and a public trust. 

We believed that the proposed IOTA 

Model recognizes the goals of the 

Department on behalf of the public and 

the medical judgment exhibited by the 

OPTN. We believed that constructing 


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324https://optn.transplant.hrsa.gov/media/ 

5j5dov5s/what_to_expect_performance_reviews.pdf. 

325Mohan, S., Chiles, M.C., Patzer, R.E., Pastan, 

S.O., Husain, S.A., Carpenter, D.J., Dube, G.K., 

Crew, R.J., Ratner, L.E., & Cohen, D.J. (2018). 

Factors leading to the discard of deceased donor 

kidneys in the United States. Kidney International, 

94(1), 187–198. https://doi.org/10.1016/ 

j.kint.2018.02.016. 

this as a model test would enable the 

Department to test out a different 

approach to incentivize certain behavior 

for transplant centers, while also 

acknowledging the role of the OPTN 

and transplant professionals in this area. 

We noted the concern put forward by 

kidney transplant hospitals that they 

would not be able to increase their 

number of transplants without 

potentially affecting their performance 

90 day and 1-year graft survival rate 

metrics used by the MPSC. However, we 

believed that there are several different 

ways that IOTA participants would 

ultimately be able to succeed under the 

IOTA Model and OPTN policies: 

• The MPSC standard represents a 

standard far below the national average 

of performance that should be able to be 

met by member transplant centers. The 

MPSC describes this as meaning that to 

be identified for outcomes review in a 

document describing their Performance 

Reviews,324 ‘‘[t]he adult criteria is based 

on the likelihood that the program’s 

performance was at least 75 percent 

worse than an average program, 

accounting for differences in the types 

of recipients and donor organs 

transplanted. The pediatric criterion is 

based on the likelihood that the 

program’s performance was at least 60 

percent worse than an average program, 

accounting for differences in the types 

of recipients and donor organs 

transplanted. Even if a program meets 

one or both of the criteria for graft 

survival, the MPSC may not send the 

program an inquiry based on various 

situations, such as recent release from 

review for outcomes or program 

membership status.’’ This represents a 

minimum standard of care and only a 

small percentage were flagged for not 

meeting those standards. 

• The IOTA Model incentivizes 

investment in both living and deceased 

donor transplants. Living donor 

transplantation has rates that have been 

relatively flat for 20 years and has 

recipients of those organs with better 

post-transplant outcomes. 

• MPSC outcomes metrics are risk 

adjusted based on organ quality and can 

account for the use of organs that are 

currently being discarded. 

• Many organs currently being 

discarded are quality organs. Though 

the median KDRI of discarded kidneys 

was higher for discarded kidneys than 

transplanted kidneys, there is a large 

overlap in the quality of discarded and 

transplanted kidneys.325

• Per 42 CFR 121.10(c)(1), the reviews 

conducted by the OPTN result in an 

advisory opinion to the Secretary of a 

recommended course of action. The 

Secretary then has the option under 42 

CFR 121.10(c)(2) of requesting 

additional information, declining to 

accept the recommendation, accepting 

the recommendation, or taking such 

other action as the Secretary deems 

necessary. Given the enforcement 

discretion given to the Secretary, the 

Secretary may take into account 

performance on the metrics evaluated in 

the IOTA Model as part of a holistic 

evaluation of transplant hospital 

performance. 

Additionally, CMS also considered, 

but did not propose, a limited waiver of 

section 1138(a)(1)(B) of the Act as part 

of the IOTA Model, which requires that 

a hospital be a member and abide by the 

rules and requirements of the OPTN. We 

considered retaining transplant 

hospitals’ membership obligations to the 

OPTN with the exception of their 

required responsiveness to MPSC 

transplant hospital performance reviews 

and the potential for adverse actions 

that may risk a transplant hospital’s 

operations and reimbursement by 

Federal health insurance programs. 

However, we do not believe that this 

waiver is necessary for testing the 

model, and that a transplant hospital 

can perform on both the metrics put 

forward by the MPSC and demonstrate 

successful performance in the IOTA 

Model. 

We invited public comments on our 

proposals to account for overlaps with 

other CMS programs and models. 

The following is a summary of the 

comments received on our proposals to 

account for overlaps with other CMS 

programs and models and our 

responses: 

Comment: We received multiple 

comments about the OPTN 

Modernization and concerns that the 

OPTN Modernization process is 

happening right now, as the IOTA 

Model is being implemented, which 

would potentially be too disruptive to 

the transplant system. We also received 

comments concerned about the 

solicitation for a new OPTN contractor 

and concerns that any potential 

transition that could happen from a new 

contract could lead to disruption that 

could impact ability to perform in the 

IOTA Model. 

Response: We disagree with the 

commenters as we believe that the 

OPTN Modernization process will 

improve the system overall and includes 

a series of improvements in technology, 

governance, and organ tracking that will 

benefit IOTA participants as they 

participate in this model. At a high 

level, the IOTA Model was proposed 

and developed in coordination with 

CMS and HRSA in an effort to create a 

series of coordinated initiatives across 

the transplant ecosystem, using a variety 

of different levers to improve 

performance and equity in the United 

States transplant system. Through the 

OTAG, CMS and HRSA have 

collaborated and produced the IOTA 

Model, the OPTN Modernization 

Process, and further efforts to come 

including around the HIV Organ Policy 

Equity Act in an effort to increase 

accountability in the transplant system 

and improve it for patients. 

Additionally, HRSA and the OPTN 

are committed that the Modernization 

Process will not disrupt existing 

procurement and allocation practices. 

HHS also believes that this 

modernization process will improve 

accountability and performance for the 

OPTN and accelerate progress in 

technology, data transparency and 

analytics, governance, operations, and 

quality improvement and innovation. 

Some key steps that have already been 

taken include in August 2024 separating 

the OPTN Board of Directors from the 

OPTN contractor so it may better serve 

the interests of patients and their 

families, which HHS believes will 

strengthen governance and prevent 

conflicts of interest within the Network. 

Other major steps include issuing a 

Request for Proposals for a multi-vendor 

contract solicitation for critical OPTN 

functions and a transition to an 

upgraded IT system that leverages 

industry-leading standards. The net 

result of these efforts will be a more 

functional and accountable system that 

will better be able to get and share data 

than in the status quo. We also believe 

that the delayed start date for model 

accountability to July 1, 2025, will 

enable the OPTN Modernization to 

progress further and allow for the 

awarding of these contracts and 

onboarding of new contractors before 

accountability begins. We also note that 

the randomized design of the model 

means that major national changes, like 

this OPTN Modernization effort, will 

apply equally to both the selected IOTA 

DSAs and the DSAs that are not selected 

and are in the comparison group, 

meaning that CMS will still be able to 

fully evaluate the impacts of the 

interventions in the IOTA Model. 

Comment: We received multiple 

comments about the OPTN’s 


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326U.S. Department of Health and Human 

Services. (2024, November 4). Agency information 

collection activities; proposed collection; public 

comment request [Docket No. HHS–2024–25522]. 

Federal Register. https://www.federalregister.gov/ 

documents/2024/11/04/2024-25522/agencyinformation-collection-activities-proposedcollection-public-comment-request-information. 

Expeditious Task Force, with some 

concerns about the implications of 

overlapping initiatives both designed to 

increase number of transplants. A 

commenter specifically pointed out that 

a part of the Expeditious effort includes 

a proposed allocation variance to allow 

for the study of out-of-sequence 

allocation. 

Response: We appreciate the 

comments and believe that overall, there 

is a great deal of synergy between the 

efforts being promoted as part of the 

Expeditious Task Force and the IOTA 

Model, starting with their initial aim of 

greatly increasing the number of 

transplants completed across the 

country. The Expeditious efforts include 

many different components, many of 

which will help selected IOTA 

participants perform better in the 

model. This includes efforts like 

analyzing patterns of non-use of 

kidneys, conducting data analysis to 

improve organ offer filters, and working 

on how to best secure commitments 

from hospital leadership to secure 

investment for the IOTA participant to 

be able to build up infrastructure to 

support a growth in kidney transplants. 

We believe that these efforts are 

incredibly helpful and will support 

improved performance in the 

achievement and efficiency domains in 

the IOTA Model. 

We saw multiple comments about 

out-of-sequence allocation and the 

proposed limited trials being proposed 

by the Expeditious Task Force that are 

designed to test a proposed variance to 

the allocation methodology for certain 

OPOs. We note that these proposed 

trials are meant to last for only a few 

months and are meant to be limited in 

scope and do not believe that they 

would impact the ability to evaluate the 

IOTA Model. We also note that we 

described in the monitoring section of 

this rule that we plan to monitor out-ofsequence allocation in the context of the 

IOTA Model to see if that is a strategy 

used by IOTA participants to utilize 

more kidneys. 

Comment: We received a comment 

saying that this model is being proposed 

to be implemented amidst too many 

other initiatives, including the proposed 

new OPTN data collection initiative. 

Response: HHS believes that 

collecting the proposed data from OPOs 

and kidney transplant hospitals will be 

beneficial for patients, improve the 

overall transplant process, and help 

IOTA participants succeed in the IOTA 

Model. The transplant hospital forms 

will help to track sources of waitlist 

referral, the results of referrals, and the 

results of transplant evaluations to see 

who makes it onto the transplant 

waiting list. We believe that this data 

driven approach will help transplant 

hospitals better understand their 

sources of referral and potential areas of 

improvement in the waitlisting process 

that may allow for better waitlist 

management. The organ procurement 

forms will require OPOs to track how 

effective they are at responding to 

referrals from donor hospitals and how 

effective they are at procuring organs 

from potential donor candidates. We 

believe that this data driven approach 

will help OPOs with quality 

improvement to understand their 

success at different stages in the 

procurement process and will therefore 

help to increase the supply of organs for 

IOTA participants. 

At the same time, HHS understands 

this potential criticism and will work to 

coordinate once the waitlist referral and 

evaluation forms are established, 

recognizing that it would be the same 

staff at transplant hospitals who would 

be likely to fill these out as those who 

would be working to increase the 

number of transplants under the IOTA 

Model. We also note that the proposed 

forms for transplant hospitals and OPOs 

will undergo a thorough public review 

process that began via Federal Register 

Notice on November 4, 2024.326

Comment: We received multiple 

comments about the metrics used by the 

MPSC, some pointing out the 

duplicative nature with the metrics that 

are a part of the IOTA Model and some 

worried that their performance on 

MPSC metrics may be hurt by their 

performance under the IOTA Model. 

Response: As discussed previously in 

this section, we anticipated this concern 

and believe that there are several 

different ways that IOTA participants 

would ultimately be able to succeed 

under the IOTA Model and OPTN 

policies. Given the relatively low bar for 

the different metrics for the MPSC, the 

risk adjusted nature of their metrics, and 

the potential for increasing transplants 

with the quality organs that are 

currently going unused and the 

opportunity to increase living donation 

rates, we see many ways that 

participants will be able to be successful 

under both sets of metrics. Additionally, 

we constructed the IOTA Model in the 

context of the regulatory efforts through 

the OPTN and the CMS Transplant 

Center CfCs, recognizing that CMS is 

incentivizing more transplants for 

patients, but that we want to make sure 

they are done in a way that still ensures 

an appropriate level of patient safety. 

Comment: We received a comment 

about the potential that OPTN will 

move to continuous allocation for 

kidneys, which could disrupt their 

operations. 

Response: HHS recognizes that the 

OPTN is considering further 

adjustments to the organ allocation 

system. We believe that the randomly 

selection methodology in the IOTA 

Model will help to account for any 

changes to the allocation system, given 

the national focus of any of these 

changes. We also believe that the focus 

on organ offer acceptance rate in the 

model will encourage participating 

kidney transplant hospitals to carefully 

consider their organ offer filters, which 

will help to limit potential disruption to 

transplant operations. 

We also received comments about the 

potential overlap between initiatives 

and regulations elsewhere within CMS 

and the IOTA Model. 

Comment: We received multiple 

comments worried about 

implementation of the 2020 update to 

the OPO CfCs and their potential impact 

on OPO decertification, with worries 

about the potential effects of new OPOs 

coming in on organ allocation. We also 

received comments about the OPO CfC 

methodology that were out of scope. 

Response: We recognize that 

implementation of accountability in the 

IOTA Model will intersect with the 

recertification period for OPOs in 2026. 

However, we believe that though there 

is a hypothetical potential for some 

disruption as a new OPO takes over a 

DSA, we believe that the interaction 

between the IOTA Model and the 

updated CfCs will ultimately be positive 

for both OPOs and transplant hospitals 

and will better allow both to perform 

better on their respective metrics. Since 

the updated CfCs were finalized in 

2020, OPOs have been procuring more 

organs and have complained that there 

was not a corresponding incentive on 

the transplant hospital side to use more 

of the organs that are procured. 

Additionally, the number of organ offers 

and turndowns has grown since the 

updated CfCs and allocation system 

were finalized. We believe that the 

incentives in the IOTA Model will help 

to better ensure more judicious use of 

organ offer filters to better reflect 

potential for utilization, which will 

make it easier for OPOs to place the 

organs that they procure. CMS also 

commits to recognizing the potential for 

disruption with the decertification of 


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any OPO and will work to make this 

process as smooth as possible. 

Comment: We received a comment 

asking CMS to prioritize waiver requests 

from hospitals seeking to work with a 

different OPO before taking action on 

creating a new transplant model. 

Response: We appreciate this 

commenters suggestion and the 

importance of this issue; however, this 

comment is beyond the scope of this 

rule. 

Comment: We received a comment 

from a hospital pointing out that they 

are already subject to the CMS Survey 

and Certification process, making the 

IOTA Model unnecessary. 

Response: As discussed previously, in 

2019, CMS removed any outcomes 

requirements from its Survey and 

Certification requirements. The IOTA 

Model focuses on increasing numbers of 

transplants and improving organ offer 

acceptance rate, neither of which were 

addressed in the previous version of the 

Survey and Certification requirements 

and includes financial incentives for 

performance that are not included in the 

CMS Survey and Certification process. 

We believe that this model test can 

complement existing Survey and 

Certification requirements as those will 

help to ensure a baseline level of patient 

care in the transplant process, while 

still enabling CMS to test out a new 

method to pay for care, without 

compromising care for patients. 

Comment: We received some concern 

about the potential implications on the 

IOTA Model if CMS implements some 

previously proposed changes to the way 

that organ acquisition costs are 

calculated. 

Response: In the FY 2022 IPPS Final 

Rule (CMS 1752–FC3), We decided not 

to finalize a proposed change to the way 

that Medicare’s share of organ 

acquisition costs are calculated for 

centers. Based on the consideration of 

concerns received from commenters, 

CMS decided not to finalize the 

proposed policy with respect to 

counting organs at this time, but stated 

that we may consider it in future 

rulemaking. 

We also received comments from the 

public about interaction with multiple 

efforts at the Innovation Center. 

Comment: We received a comment 

from a dialysis company pointing out 

the potential for cooperation between 

selected IOTA transplant hospitals and 

participants in the existing ETC and 

KCC Models. 

Response: We appreciate the 

comment, as these models were 

designed to fit together. Participating 

entities in the KCC Model have the 

opportunity to partner with selected 

IOTA participants and to even add them 

to their participant lists for an upcoming 

performance year. CMS encourages 

greater collaboration throughout the 

entire spectrum of transplant care and 

believes that alignment for patients from 

the first detection of CKD, through the 

need for dialysis, and all the way 

through the delivery of a transplant 

results in the best outcomes for most 

beneficiaries. 

Comment: We received a comment 

from a hospital association urging that 

transplant hospitals participating in any 

Innovation Center Advanced APM 

model be able to opt out of the proposed 

IOTA Model. 

Response: We disagree with the 

comment as CMS decided to make the 

model mandatory for reasons discussed 

previously in the relevant section. We 

recognize that many kidney transplant 

hospitals have made decisions to be 

involved in many other different valuebased purchasing programs like the 

Shared Savings Program or another 

Innovation Center Model and allowing 

those involved in those other models to 

opt out could hurt the ability to evaluate 

the IOTA Model. We also recognize that 

none of these models, outside of the 

KCC Model which has seen a relatively 

low level of participation from kidney 

transplant hospitals, are particularly 

focused on transplantation, which we 

believe helps to show the need for a 

transplant-focused value-based care 

model. 

Comment: We received a comment 

from one hospital expressing concern 

about being opted into both the IOTA 

Model and the TEAM Model, recently 

finalized by the Innovation Center, and 

were concerned about their ability to 

conduct change management at their 

hospital if they are selected into both 

models. 

Response: The TEAM Model was 

finalized in the 2025 IPPS Rule in July 

2024 (CMS–1808–F). We recognize the 

potential complications as CMS and 

particularly the Innovation Center tests 

multiple models at the same time. 

However, we believe that this model has 

very different goals than the TEAM 

Model, which is focused on surgical 

bundles for five procedures and postacute care spending, rather than the 

transplant process. We also note that 

both models include a period of time 

before implementation, creating an 

opportunity for hospitals that are 

required to participate in both models’ 

time to enact necessary changes in 

practice. 

After consideration of the public 

comments we received, we are 

finalizing the overlaps policy in the 

model as proposed. The Innovation 

Center will continue to monitor 

developments in the transplant 

ecosystem to see if changes are needed 

to the model for unintended 

consequences. The Innovation Center is 

committed to continuing to work and 

coordinate with other components of 

CMS and HRSA as they continue to 

implement the updated OPO CfCs and 

the OPTN Modernization process in 

order to see if any actions do end up 

affecting the ability of selected IOTA 

transplant hospitals to perform in the 

model. These coordination efforts 

through the Organ Transplant Affinity 

Group are part of a larger HHS effort to 

ensure policy coordination and ensure 

input across HHS as we consider and 

implement reforms to the transplant 

system. 

10. Beneficiary Protections 

a. Beneficiary Notifications 

At § 512.450 of the proposed rule, we 

proposed to require IOTA participants 

to provide notice to attributed patients 

that the IOTA participant is 

participating in the IOTA Model. We 

believed it would be important for IOTA 

participants to provide attributed 

patients with a standardized, CMSdeveloped, beneficiary notice to limit 

the potential for fraud and abuse, 

including patient steering. We intended 

to provide a notification template that 

IOTA participants would be required to 

use. This template would, at minimum, 

indicate content that the IOTA 

participant would not be permitted to 

change and would indicate where the 

IOTA participant could insert its own 

content. It would also include 

information regarding the attributed 

patient’s ability to opt-out of data 

sharing with IOTA participants and how 

they may opt out if they choose to do 

so (89 FR 43518). 

At § 512.450 of the proposed rule, we 

proposed requiring IOTA participants to 

display a notice containing these rights 

and protections prominently at each 

office or facility location where an 

attributed patient may receive 

treatment, in a clear manner on its 

public facing website, and to each 

attributed patient in a paper format. 

This would increase the probability that 

the attributed patients would receive 

and take note of this information. 

We sought comment on the proposed 

requirements for beneficiary 

notifications. 

The following is a summary of the 

public comments received on these 

proposals and our response: 

Comment: Several commenters 

expressed support for requiring 

hospitals and providers to notify 


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patients about their participation in the 

IOTA Model. 

Response: We thank the commenters 

for their support. 

Comment: A commenter expressed 

concern that CMS should provide more 

information about the required notice of 

attribution, including expectations for 

hospitals and patients. 

Response: We thank the commenter 

for its feedback. We will provide a 

template for the beneficiary notification 

that will have additional information 

concerning the notice of attribution. We 

will take the commenter’s feedback into 

consideration as we draft the template. 

Comment: Several commenters 

suggested that the beneficiary 

notifications should require an IOTA 

participant to notify patients of 

participation in IOTA in multiple 

languages and that CMS limit the 

requirement for beneficiary notifications 

to be provided only upon patient 

request and only at the main transplant 

hospital. 

Response: We thank the commenters 

for their feedback. Although the IOTA 

Model does not require IOTA 

participants to provide beneficiary 

notifications in multiple languages, 

other federal laws and regulations that 

apply to language services will still 

apply to IOTA participants. 

Accordingly, we decline to include such 

requirements in the IOTA Model 

regulations at this time. 

We also disagree with the suggestion 

that the notice only be required upon 

patient request. Many patients may not 

be aware of their rights and not know 

that such a request should be made. 

Additionally, we disagree with the 

suggestion that the notice only be 

required at the main location of the 

IOTA participant. It is possible that a 

beneficiary would not be seen at the 

main location of the IOTA participant 

and therefore not be properly informed. 

After consideration of the public 

comments received, for the reasons set 

forth in this rule, we are finalizing our 

proposed provision to require IOTA 

participants to provide notice to 

attributed patients that the IOTA 

participant is participating in the IOTA 

Model, including the requirement to 

display a notice containing these rights 

and protections prominently at each 

office or facility location, at § 512.450, 

with minor technical corrections to 

update the spacing in the regulation and 

provide clarification, including the 

removal of duplicative text, at 

§ 512.450(a)(3)(ii). 

b. Availability of Services and 

Beneficiary Freedom of Choice 

In section II.B of the proposed rule, 

we proposed the Standard Provisions 

for Innovation Center Models relating to 

availability of services and beneficiary 

freedom of choice would apply to the 

IOTA Model. These provisions were 

originally finalized as general 

provisions in the Code of Federal 

Regulations (42 CFR part 512 subpart A) 

that applied to specific Innovation 

Center models, but are finalized 

separately in section II.B of this final 

rule for expansion to all mandatory 

Innovation Center Models with 

performance periods that begin on or 

after January 1, 2025. Consistent with 

this final rule, IOTA participants will 

need to preserve beneficiary freedom of 

choice and continue to make medically 

necessary covered services available to 

beneficiaries to the extent required by 

applicable law. 

We received no comments on these 

proposals and therefore are finalizing 

these proposals without modification. 

11. Financial Arrangements and 

Attributed Patient Engagement 

Incentives 

a. Background 

We believe it is necessary to provide 

IOTA participants with flexibilities that 

could support their performance in the 

IOTA Model and allow for greater 

support for the needs of attributed 

patients. These flexibilities are outlined 

in this section and include the ability to 

engage in financial arrangements to 

share IOTA upside risk payments and 

responsibility for paying Medicare for 

IOTA downside risk payments with 

providers and suppliers making 

contributions to the IOTA participants’ 

performance against model metrics, and 

the availability of the provision of 

attributed patient engagement 

incentives. Such flexibilities would 

allow IOTA participants to share all or 

some of the payments they may be 

eligible to receive from CMS and to 

share the responsibility for the funds 

needed to pay CMS providers and 

suppliers engaged in caring for 

attributed patients, if those providers 

and suppliers have a role in the IOTA 

participant’s spending or quality 

performance. Additionally, we believe 

that IOTA participants caring for 

attributed patients may want to offer 

attributed patient engagement 

incentives to encourage adherence to 

recommended treatment and active 

patient engagement in recovery. These 

incentives may help an IOTA 

participant reach their quality and 

efficiency goals for the model, while 

also benefitting beneficiaries’ health and 

the Medicare Trust Fund if the IOTA 

participant improves the quality and 

efficiency of care that results in the 

Medicare beneficiary’s reductions in 

hospital readmissions, complications, 

days in acute care, and mortality, while 

recovery continues uninterrupted or 

accelerates. 

b. Overview of IOTA Model Financial 

Arrangements 

We believe that IOTA participants 

may wish to enter into financial 

arrangements with providers and 

suppliers caring for attributed patients 

to share model upside risk payments or 

downside risk payments, to align the 

financial incentives of those providers 

and suppliers with the IOTA Model 

goals of increasing the number of kidney 

transplants furnished to attributed 

patients to lower costs and to improve 

their quality of life. To do so, we expect 

that IOTA participants would identify 

key providers and suppliers caring for 

attributed patients in their communities 

and DSAs. The IOTA participants could 

establish partnerships with these 

providers and suppliers to promote 

accountability for the quality, cost, and 

overall care for attributed patients, 

including managing and coordinating 

care; encouraging investment in 

infrastructure, enabling technologies, 

and redesigning care processes for high 

quality and efficient service delivery; 

and carrying out other obligations or 

duties under the IOTA Model. These 

providers and suppliers may invest 

substantial time and other resources in 

these activities, yet they would neither 

be the direct recipients of any model 

upside risk payments from Medicare, 

nor directly responsible for paying to 

CMS any downside risk payments 

incurred. Therefore, we believe it is 

possible that an IOTA participant that 

may receive an upside risk payment 

from Medicare or may need to pay a 

downside risk payment to Medicare 

may want to enter into financial 

arrangements with other providers or 

suppliers to share these performance 

adjustments with the IOTA participant. 

We require that all financial 

relationships established between IOTA 

participants and providers or suppliers 

for purposes of the IOTA Model would 

only be those permitted under 

applicable law and regulations, 

including the applicable fraud and 

abuse laws and all applicable payment 

and coverage requirements. As 

discussed in section III.C.3 of this final 

rule, CMS determined that the Federal 

anti-kickback statute safe harbor for 

CMS-sponsored model arrangements (42 

CFR 1001.952(ii)(1)) is available to 


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327Subsequent to the publication of the proposed 

rule, we found that the proposed definition of 

‘‘hospital’’ included an incorrect citation to the 

Social Security Act. Section 1861(u) of the Act 

defines ‘‘provider of services,’’ which includes 

more than just hospitals. We clarify that, for the 

purposes of the IOTA Model, the term ‘‘hospital’’ 

has the meaning set forth in § 1861(e) of the Act. 

protect the financial arrangements 

proposed in this section when 

arrangements with eligible providers 

and suppliers are in compliance with 

this policy and the conditions for use of 

the Federal anti-kickback statute safe 

harbor set out at § 1001.952(ii)(1). 

We recognize that there are numerous 

arrangements that IOTA participants 

may wish to enter other than the 

financial arrangements described in the 

proposed regulations for which safe 

harbor protection may be extended that 

could be beneficial to the IOTA 

participants. For example, IOTA 

participants may choose to engage with 

organizations that are neither providers 

nor suppliers to assist with matters such 

as data analysis; local provider and 

supplier engagement; care redesign 

planning and implementation; 

beneficiary outreach; beneficiary care 

coordination and management; 

monitoring IOTA participants’ 

compliance with the model’s terms and 

conditions; or other model-related 

activities. Such organizations may play 

important roles in an IOTA participant’s 

plans to implement the model based on 

the experience these organizations may 

bring, such as prior experience with 

living donation initiatives, care 

coordination expertise, familiarity with 

a particular local community, or 

knowledge of SRTR data. We require 

that all relationships established 

between IOTA participants and these 

organizations for purposes of the model 

would be those permitted only under 

existing law and regulation, including 

any relationships that would include 

the IOTA participant’s sharing of model 

upside risk payments or downside risk 

payments with such organizations., and 

must comply with all applicable laws 

and regulations We require these 

relationships to be solely based on the 

level of engagement of the 

organization’s resources to directly 

support the participants’ model 

implementation. 

c. IOTA Collaborators 

Given the financial incentives of the 

IOTA performance-based payments, as 

described in section III.C.6.c of this final 

rule, an IOTA participant may want to 

engage in financial arrangements with 

providers and suppliers making 

contributions to the IOTA participant’s 

performance across the achievement 

domain, efficiency domain, and quality 

domain. Such arrangements would 

allow the IOTA participant to share 

monies earned from the upside risk 

payments. Likewise, such arrangements 

could allow the IOTA participant to 

share the responsibility for the funds 

needed to repay CMS the downside risk 

payments. We proposed to use the term 

‘‘IOTA collaborator’’ to refer to these 

providers and suppliers. 

Because attributed patients include 

both those on the kidney transplant 

waitlist and those who have received a 

kidney transplant, as described in 

section III.C.4.a of this final rule, many 

providers and suppliers other than the 

IOTA participant would furnish related 

services to attributed patients during the 

model performance period. As such, for 

purposes of the Federal anti-kickback 

statute safe harbor for CMS-sponsored 

model arrangements (42 CFR 

1001.952(ii)), we proposed that the 

following types of providers and 

suppliers that are Medicare-enrolled 

and eligible to participate in Medicare 

may be IOTA collaborators: 

• Nephrologist. 

• ESRD Facility. 

• Skilled Nursing Facility (SNF). 

• Home Health Agency (HHA). 

• Long-Term Care Hospital (LTCH). 

• Inpatient Rehabilitation Facility 

(IRF). 

• Physician. 

• Nonphysician practitioner. 

• Therapist in a private practice. 

• Comprehensive Outpatient 

Rehabilitation Facility (CORF). 

• Provider or supplier of outpatient 

therapy services. 

• Physician Group Practice (PGP). 

• Hospital. 

• Critical Access Hospital (CAH). 

• Non-physician provider group 

practice (NPPGP). 

• Therapy Group Practice (TGP). 

We sought comment on the proposed 

definition of IOTA collaborators and 

any additional Medicare-enrolled 

providers or suppliers that should be 

included in this definition. 

The following is a summary of the 

public comments received on this 

proposal and our responses: 

Comment: Several commenters 

supported the inclusion of IOTA 

collaborators in the model and 

encouraged expanding the types of 

entities allowed as IOTA collaborators 

to include other provider types. 

Commenters recommended including 

in the list of IOTA collaborators: 

audiologists, registered dietitian 

nutritionists (RDNs), and rural 

emergency hospitals. 

Response: We thank commenters for 

their recommendations and support of 

this initiative. We appreciate your 

insights on expanding the types of 

entities allowed as IOTA collaborators. 

We will take them into consideration in 

future rulemaking. 

After consideration of the public 

comments received, for the reasons set 

forth in this rule, we are finalizing the 

proposal for the model definition of 

IOTA collaborators as proposed at 

§ 512.402. We are also finalizing as 

proposed the definitions for the types of 

IOTA collaborator Medicare-enrolled 

providers or suppliers at § 512.402 with 

minor technical corrections to update 

cross references. Specifically, we are 

finalizing our proposed definition of 

nonphysician practitioner at § 512.402 

with a minor technical correction to 

include the full cross reference. 

Additionally, we are finalizing our 

proposed definition of therapist at 

§ 512.402 with a minor technical 

correction to include the correct cross 

reference to the regulatory definition for 

that term. Lastly, we are finalizing our 

proposed definition of hospital at 

§ 512.402 with a technical correction to 

specify that hospital has the meaning set 

forth in § 1861(e) of the Act.327

d. Sharing Arrangements 

(1) General 

Similar to the Comprehensive Care for 

Joint Replacement Payment Model (CJR) 

(42 CFR part 510), we proposed that 

certain financial arrangements between 

an IOTA participant and an IOTA 

collaborator be termed ‘‘sharing 

arrangements.’’ For purposes of the 

Federal anti-kickback statute safe harbor 

for CMS-sponsored model arrangements 

(§ 1001.952(ii)(1)), we proposed that a 

sharing arrangement would be a 

financial arrangement to share only—(1) 

the upside risk payment; and (2) the 

downside risk payment. 

Where a payment from an IOTA 

participant to an IOTA collaborator is 

made pursuant to a sharing 

arrangement, we proposed to define that 

payment as a ‘‘gainsharing payment,’’ 

which is discussed in section 

III.C.11.d.(3). of this final rule. Where a 

payment from an IOTA collaborator to 

an IOTA participant is made pursuant to 

a sharing arrangement, we proposed to 

define that payment as an ‘‘alignment 

payment,’’ which is discussed in section 

III.C.11.d.(3). of this final rule. 

We sought comment about all 

provisions described in the preceding 

discussion. 

We received no comments on these 

proposals and therefore are finalizing 

these proposals as proposed in our 

regulation at § 512.452. We are also 

finalizing without modification the 

proposed definitions of sharing 


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arrangements, gainsharing payment, and 

alignment payment at § 512.402. 

(2) Requirements 

We proposed several requirements for 

sharing arrangements to help ensure 

that their sole purpose is to create 

financial alignment between IOTA 

participants and IOTA collaborators 

toward the goals of the model while 

maintaining adequate program integrity 

safeguards. An IOTA participant must 

not make a gainsharing payment or 

receive an alignment payment except in 

accordance with a sharing arrangement. 

We proposed that a sharing arrangement 

must comply with the provisions of 

§ 512.452 and all other applicable laws 

and regulations, including the 

applicable fraud and abuse laws and all 

applicable payment and coverage 

requirements. 

We proposed that the IOTA 

participant must develop, maintain, and 

use a set of written policies for selecting 

providers and suppliers to be IOTA 

collaborators. To safeguard against 

potentially fraudulent or abusive 

practices, we proposed that the 

selection criteria must include the 

quality of care delivered by the potential 

IOTA collaborator. We also proposed 

that the selection criteria cannot be 

based directly or indirectly on the 

volume or value of referrals or business 

otherwise generated by, between, or 

among the IOTA participant, any IOTA 

collaborator, any collaboration agent, or 

any individual or entity affiliated with 

an IOTA participant, IOTA collaborator, 

or collaboration agent. Additionally, we 

proposed that IOTA participants must 

consider the selection of IOTA 

collaborators based on criteria related 

to, and inclusive of, the anticipated 

contribution to the performance of the 

IOTA participant across the 

achievement domain, efficiency 

domain, and quality domain by the 

potential IOTA collaborator to ensure 

that the selection of IOTA collaborators 

takes into consideration the likelihood 

of their future performance. 

It is necessary that IOTA participants 

have adequate oversight over sharing 

arrangements to ensure that all 

arrangements meet the requirements of 

the model. Therefore, we proposed that 

the board or other governing body of the 

IOTA participant have responsibility for 

overseeing the IOTA participant’s 

participation in the model, including, 

but not limited to, its arrangements with 

IOTA collaborators, its payment of 

gainsharing payments, its receipt of 

alignment payments, and its use of 

beneficiary incentives (as discussed in 

III.C.11.g of this final rule). 

Finally, we proposed that if an IOTA 

participant enters a sharing 

arrangement, its compliance program 

must include oversight of sharing 

arrangements and compliance with the 

applicable requirements of the model. 

Requiring oversight of sharing 

arrangements to be included in the 

compliance program provides a program 

integrity safeguard. 

We sought comment about all 

provisions described in the preceding 

discussion, including whether 

additional or different safeguards would 

be needed to ensure program integrity, 

protect against abuse, and ensure that 

the goals of the model are met. 

We proposed that the sharing 

arrangement must be in writing, signed 

by the parties, and entered into before 

care is furnished to attributed patients 

during the PY under the sharing 

arrangement. In addition, participation 

in the sharing arrangement must require 

the IOTA collaborator to comply with 

the requirements of this model, as those 

pertain to their actions and obligations. 

Participation in a sharing arrangement 

must be voluntary and without penalty 

for nonparticipation. It is important that 

providers and suppliers rendering items 

and services to attributed patients 

during the model performance period 

have the freedom to provide medically 

necessary items and services to 

attributed patients without any 

requirement that they participate in a 

sharing arrangement to safeguard 

beneficiary freedom of choice, access to 

care, and quality of care. The sharing 

arrangement must set out the mutually 

agreeable terms for the financial 

arrangement between the parties to 

guide and reward model care redesign 

for future performance across the 

achievement domain, efficiency 

domain, and quality domain, rather than 

reflect the results of model PYs that 

have already occurred and where the 

financial outcome of the sharing 

arrangement terms would be known 

before signing. 

We proposed that the sharing 

arrangement must require the IOTA 

collaborator and its employees, 

contractors (including collaboration 

agents), and subcontractors to comply 

with certain requirements that are 

important for program integrity under 

the arrangement. We note that the terms 

contractors and subcontractors, 

respectively, include collaboration 

agents as defined later in this section. 

The sharing arrangement must require 

all of the individuals and entities in this 

group to comply with the applicable 

provisions of §§ 512.450–512.466 of this 

final rule, including requirements 

regarding beneficiary notifications, 

access to records, record retention, and 

participation in any evaluation, 

monitoring, compliance, and 

enforcement activities performed by 

CMS or its designees, because these 

individuals and entities all would play 

a role in model care redesign and be 

part of financial arrangements under the 

model. The sharing arrangement must 

also require all individuals and entities 

in the group to comply with the 

applicable Medicare provider 

enrollment requirements at § 424.500 et 

seq., including having a valid and active 

TIN or NPI, during the term of the 

sharing arrangement. This is to ensure 

that these individuals and entities have 

the required enrollment relationship 

with CMS under the Medicare program, 

although we note that they are not 

responsible for complying with 

requirements that do not apply to them. 

Finally, the sharing arrangement must 

require these individuals and entities to 

comply with all other applicable laws 

and regulations. 

We proposed that the sharing 

arrangement must not pose a risk to 

beneficiary access, beneficiary freedom 

of choice, or quality of care so that 

financial relationships between IOTA 

participants and IOTA collaborators do 

not negatively impact beneficiary 

protections under the model. The 

sharing arrangement must require the 

IOTA collaborator to have, or be covered 

by, a compliance program that includes 

oversight of the sharing arrangement 

and compliance with the requirements 

of the IOTA Model that apply to its role 

as an IOTA collaborator, including any 

distribution arrangements, just as we 

require IOTA participants to have a 

compliance program that covers 

oversight of the sharing arrangement for 

this purpose as a program integrity 

safeguard. We sought comment on the 

anticipated effect of the proposed 

compliance program requirement for 

IOTA collaborators, particularly with 

regard to individual physicians and 

nonphysician practitioners, small PGPs, 

NPPGPs, and TGPs and whether 

alternative compliance program 

requirements for all or a subset of IOTA 

collaborators should be adopted to 

mitigate any effect of the proposal that 

could make participation as an IOTA 

collaborator infeasible for any provider, 

supplier, or other entity on the proposed 

list of types of IOTA collaborators. 

For purposes of sharing arrangements 

under the model, we proposed to define 

activities related to promoting 

accountability for the quality, cost, and 

overall care for attributed patients and 

performance across the achievement 

domain, efficiency domain, and quality 

domain, including managing and 


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coordinating care; encouraging 

investment in infrastructure and 

redesigned care processes for high 

quality and efficient service delivery; 

the provision of items and services preor post-transplant in a manner that 

reduces costs and improves quality; or 

carrying out any other obligation or duty 

under the model as ‘‘IOTA activities.’’ 

In addition to the quality of episodes of 

care, we believe the activities that 

would fall under this proposed 

definition could encompass the totality 

of activities upon which it would be 

appropriate for sharing arrangements to 

value the contributions of collaborators 

and collaboration agents toward meeting 

the performance goals of the model. We 

sought comment on the proposed 

definition of IOTA activities as an 

inclusive and comprehensive 

framework for capturing direct care and 

care redesign that contribute to 

performance across the achievement 

domain, efficiency domain, and quality 

domain. 

We proposed that the written sharing 

arrangement agreement must specify the 

following parameters of the 

arrangement: 

• The purpose and scope of the 

sharing arrangement. 

• The identities and obligations of the 

parties, including specified IOTA 

activities and other services to be 

performed by the parties under the 

sharing arrangement. 

• The date of the sharing 

arrangement. 

• Management and staffing 

information, including type of 

personnel or contractors that would be 

primarily responsible for carrying out 

IOTA activities. 

• The financial or economic terms for 

payment, including all of the following: 

++ Eligibility criteria for a gainsharing 

payment. 

++ Eligibility criteria for an alignment 

payment. 

++ Frequency of gainsharing or 

alignment payment. 

++ Methodology and accounting 

formula for determining the amount of 

a gainsharing payment that is 

substantially based on performance 

across the achievement domain, 

efficiency domain and quality domain, 

and the provision of IOTA Model 

activities. 

++ Methodology and accounting 

formula for determining the amount of 

an alignment payment. 

Finally, we proposed to require that 

the terms of the sharing arrangement 

must not induce the IOTA participant, 

IOTA collaborator, or any employees, 

contractors, or subcontractors of the 

IOTA participant or IOTA collaborator 

to reduce or limit medically necessary 

services to any attributed patient or 

restrict the ability of an IOTA 

collaborator to make decisions in the 

best interests of its patients, including 

the selection of devices, supplies, and 

treatments. These requirements are to 

ensure that the quality of care for 

attributed patients is not negatively 

affected by sharing arrangements under 

the model. 

The proposals for the requirements for 

sharing arrangements under the model 

are included in § 512.452. 

We sought comment about all of the 

requirements set out in the preceding 

discussion, including whether 

additional or different safeguards would 

be needed to ensure program integrity, 

protect against abuse, and ensure that 

the goals of the model are met. 

We received no comments on these 

proposals and therefore are finalizing 

these proposals as proposed in our 

regulation at § 512.452 with slight 

modifications. Specifically, we are 

redesignating what was proposed at 

§§ 512.452(b)(5), (6), (7), and (8) to be 

§§ 512.452(b)(6), (7), (8), and (9). We are 

also finalizing without modification the 

proposed definition of IOTA activities at 

§ 512.402. 

(3) Gainsharing Payments and 

Alignment Payments 

We proposed several conditions and 

limitations for gainsharing payments 

and alignment payments as program 

integrity protections for the payments to 

and from IOTA collaborators. We 

proposed to require that gainsharing 

payments be derived solely from upside 

risk payments; that they be distributed 

on an annual basis, not more than once 

per performance year; that they not be 

a loan, advance payment, or payment 

for referrals or other business; and that 

they be clearly identified as a 

gainsharing payment at the time they 

are paid. 

We believe that gainsharing payment 

eligibility for IOTA collaborators should 

be conditioned on two requirements— 

(1) contributing to performance across 

the achievement domain, efficiency 

domain or quality domain; and (2) 

rendering items and services to 

attributed patients during the model 

performance period—as safeguards to 

ensure that eligibility for gainsharing 

payments is solely based on aligning 

financial incentives for IOTA 

collaborators with the performance 

metrics of the model. With respect to 

the first requirement, we proposed that 

to be eligible to receive a gainsharing 

payment, an IOTA collaborator must 

contribute to the performance of the 

IOTA participant across the 

achievement domain, efficiency domain 

or quality domain during the PY for 

which the IOTA participant earned the 

upside risk payment that comprises the 

gainsharing payment. We also proposed 

that the contribution to performance 

across the achievement domain, 

efficiency domain, or quality domain 

criteria must be established by the IOTA 

participant and directly related to the 

care of attributed patients. With regard 

to the second requirement, to be eligible 

to receive a gainsharing payment, or to 

be required to make an alignment 

payment, an IOTA collaborator other 

than a PGP, NPPGP, or TGP must have 

directly furnished a billable item or 

service to an attributed patient that 

occurred during the same PY for which 

the IOTA participant earned the upside 

risk payment that comprises the 

gainsharing payment or incurred a 

downside risk payment. For purposes of 

this requirement, we consider a 

hospital, CAH or post-acute care 

provider to have ‘‘directly furnished’’ a 

billable service if one of these entities 

billed for an item or service for an 

attributed patient in the same PY for 

which the IOTA participant earned the 

upside risk payment that comprises the 

gainsharing payment or incurred a 

downside risk payment. The phrase ‘‘PY 

for which the IOTA participant earned 

the upside risk payment that comprises 

the gainsharing payment or incurred a 

downside risk payment’’ does not mean 

the year in which the gainsharing 

payment was made. These requirements 

ensure that there is a required 

relationship between eligibility for a 

gainsharing payment and the direct care 

for attributed patients during the PY for 

these IOTA collaborators. We believe 

the provision of direct care is essential 

to the implementation of effective care 

redesign, and the requirement provides 

a safeguard against payments to IOTA 

collaborators other than a PGP, NPPGP, 

or TGP that are unrelated to direct care 

for attributed patients during the model 

performance period. 

We proposed to establish similar 

requirements for IOTA collaborators 

that are PGPs, NPPGPs and TGPs that 

vary because these entities do not 

themselves directly furnish billable 

services. To be eligible to receive a 

gainsharing payment or required to 

make an alignment payment, a PGP, 

NPPGP or TGP must have billed for an 

item or service that was rendered by one 

or more members of the PGP, NPPGP or 

TGP to an attributed patient that 

occurred during the same PY for which 

the IOTA participant earned an upside 

risk payment that comprises the 

gainsharing payment or incurred a 


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downside risk payment. Like the 

proposal for IOTA collaborators that are 

not PGPs, NPPGPs or TGPs, these 

proposals also require a link between 

the IOTA collaborator that is the PGP, 

NPPGP or TGP and the provision of 

items and services to attributed patients 

during the PY by PGP, NPPGP or TGP 

members. 

Moreover, we further proposed that, 

because PGPs, NPPGPs and TGPs do not 

directly furnish items and services to 

patients, to be eligible to receive a 

gainsharing payment or be required to 

make an alignment payment, the PGP, 

NPPGP or TGP must have contributed to 

IOTA activities and been clinically 

involved in the care of attributed 

patients during the same PY for which 

the IOTA participant earned the upside 

risk payment that comprises the 

gainsharing payment or incurred a 

downside risk payment. For example, a 

PGP, NPPGP, or TGP could have 

contributed to IOTA activities and been 

clinically involved in the care of 

attributed patients if they— 

• Provided care coordination services 

to attributed patients during and after 

inpatient admission; 

• Engaged with an IOTA participant 

in care redesign strategies, and 

performed a role in the implementation 

of such strategies, that were designed to 

improve the quality of care for 

attributed patients; or 

• In coordination with other 

providers and suppliers (such as PGP 

members, NPPGP members, or TGP 

members; the IOTA participant; and 

post-acute care providers), implemented 

strategies designed to address and 

manage the comorbidities of attributed 

patients. 

We proposed to limit the total amount 

of gainsharing payments for a PY to 

IOTA collaborators that are physicians, 

nonphysician practitioners, PGPs, 

NPPGPs or TGPs. For IOTA 

collaborators that are physicians or 

nonphysician practitioners, that limit is 

50 percent of the Medicare-approved 

amounts under the PFS for items and 

services furnished by that physician or 

nonphysician practitioner to the IOTA 

participant’s attributed patients during 

the same PY for which the IOTA 

participant earned the upside risk 

payment that comprises the gainsharing 

payment being made. For IOTA 

collaborators that are PGPs, NPPGPs or 

TGPs that limit is 50 percent of the 

Medicare-approved amounts under the 

PFS for items and services billed by the 

PGP, NPPGP or TGP and furnished to 

the IOTA participant’s attributed 

patients by members of the PGP, NPPGP 

or TGP during the same PY for which 

the IOTA participant earned the upside 

risk payment that comprises the 

gainsharing payment being made. These 

limits are consistent with those in the 

CJR model. 

We proposed that the amount of any 

gainsharing payments must be 

determined in accordance with a 

methodology that is substantially based 

on contribution to performance across 

the achievement domain, efficiency 

domain, and quality domain and the 

provision of IOTA activities. The 

methodology may take into account the 

amount of such IOTA activities 

provided by an IOTA collaborator 

relative to other IOTA collaborators. 

While we emphasize that financial 

arrangements may not be conditioned 

directly or indirectly on the volume or 

value of referrals or business otherwise 

generated by, between or among the 

IOTA participant, any IOTA 

collaborator, any collaboration agent, or 

any individual or entity affiliated with 

an IOTA participant, IOTA collaborator, 

or collaboration agent so that their sole 

purpose is to align the financial 

incentives of the IOTA participant and 

IOTA collaborators toward the model, 

we believe that accounting for the 

relative amount of IOTA activities by 

IOTA collaborators in the determination 

of gainsharing payments does not 

undermine this objective. Rather, the 

proposed requirement allows flexibility 

in the determination of gainsharing 

payments where the amount of an IOTA 

collaborator’s provision of IOTA 

activities (including direct care) to 

attributed patients during the model 

performance period may contribute to 

the IOTA participant’s upside risk 

payment that may be available for 

making a gainsharing payment. Greater 

contributions of IOTA activities by one 

IOTA collaborator versus those that 

result in greater differences in the funds 

available for gainsharing payments may 

be appropriately valued in the 

methodology used to make gainsharing 

payments to those IOTA collaborators to 

reflect these differences in IOTA 

activities among them. For example, a 

physician who is an IOTA collaborator 

who treats 20 attributed patients during 

the PY that result in high quality, less 

costly care could receive a larger 

gainsharing payment than a physician 

who is an IOTA collaborator who treats 

10 attributed patients during episodes 

that similarly result in high quality, less 

costly care. 

However, we do not believe it would 

be appropriate to allow the selection of 

IOTA collaborators or the opportunity to 

make or receive a gainsharing payment 

or an alignment payment to take into 

account the amount of IOTA activities 

provided by a potential or actual IOTA 

collaborator relative to other potential or 

actual IOTA collaborators because these 

financial relationships are not to be 

based directly or indirectly on the 

volume or value of referrals or business 

otherwise generated by, between, or 

among the IOTA participant, any IOTA 

collaborator, any collaboration agent, or 

any individual or entity affiliated with 

an IOTA participant, IOTA collaborator, 

or collaboration agent. Specifically, with 

respect to the selection of IOTA 

collaborators or the opportunity to make 

or receive a gainsharing payment or an 

alignment payment, we do not believe 

that the amount of model activities 

provided by a potential or actual IOTA 

collaborator relative to other potential or 

actual IOTA collaborators could be 

taken into consideration by the IOTA 

participant without a significant risk 

that the financial arrangement in those 

instances could be based directly or 

indirectly on the volume or value of 

referrals or business generated by, 

between or among the parties. Similarly, 

if the methodology for determining 

alignment payments was allowed to take 

into account the amount of IOTA 

activities provided by an IOTA 

collaborator relative to other IOTA 

collaborators, there would be a 

significant risk that the financial 

arrangement could directly account for 

the volume or value of referrals or 

business generated by, between, or 

among the parties and, therefore, we 

proposed that the methodology for 

determining alignment payments may 

not directly take into account the 

volume or value of referrals or business 

generated by, between or among the 

parties. 

We sought comment on this proposal 

for gainsharing payments, where the 

methodology could take into account 

the amount of IOTA activities provided 

by an IOTA collaborator relative to other 

IOTA collaborators. We also sought 

comments about whether this standard 

would provide sufficient additional 

flexibility in the gainsharing payment 

methodology to allow the financial 

reward of IOTA collaborators 

commensurate with their level of effort 

that achieves model goals. In addition, 

we requested comment on whether 

additional safeguards or a different 

standard is needed to allow for greater 

flexibility to provide certain 

performance-based payments consistent 

with the goals of program integrity, 

protecting against abuse and ensuring 

the goals of the model are met. 

We proposed that for each PY, the 

aggregate amount of all gainsharing 

payments that are derived from an 

upside risk payment must not exceed 

the amount of the upside risk payment 


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paid by CMS. In accordance with the 

prior discussion, no entity or 

individual, whether a party to a sharing 

arrangement or not, may condition the 

opportunity to make or receive 

gainsharing payments or to make or 

receive alignment payments, directly or 

indirectly, on the volume or value of 

referrals or business otherwise 

generated by, between, or among the 

IOTA participant, any IOTA 

collaborator, any collaboration agent, or 

any individual or entity affiliated with 

an IOTA participant, IOTA collaborator, 

or collaboration agent. We proposed that 

an IOTA participant must not make a 

gainsharing payment to an IOTA 

collaborator that is subject to any action 

for noncompliance with this 42 CFR 

part 512 or the fraud and abuse laws, or 

for the provision of substandard care to 

attributed patients or other integrity 

problems. Finally, the sharing 

arrangement must require the IOTA 

participant to recoup any gainsharing 

payment that contained funds derived 

from a CMS overpayment on an upside 

risk payment or was based on the 

submission of false or fraudulent data. 

These requirements provide program 

integrity safeguards for gainsharing 

under sharing arrangements. 

With respect to alignment payments, 

we proposed that alignment payments 

from an IOTA collaborator to an IOTA 

participant may be made at any interval 

that is agreed upon by both parties. We 

proposed that alignment payments must 

not be issued, distributed, or paid prior 

to the calculation by CMS of a payment 

amount reflected in a notification of the 

downside risk payment; loans, advance 

payments, or payments for referrals or 

other business; or assessed by an IOTA 

participant if the IOTA participant does 

not owe a downside risk payment. The 

IOTA participant must not receive any 

amounts under a sharing arrangement 

from an IOTA collaborator that are not 

alignment payments. 

We also proposed certain limitations 

on alignment payments that are 

consistent with the CJR Model. For a 

PY, the aggregate amount of all 

alignment payments received by the 

IOTA participant must not exceed 50 

percent of the IOTA participant’s 

downside risk payment. Given that the 

IOTA participant would be responsible 

for developing and coordinating care 

redesign strategies in response to its 

IOTA participation, we believe it is 

important that the IOTA participant 

retain a significant portion of its 

responsibility for payment to CMS. For 

example, upon receipt of a notification 

indicating that the IOTA participant 

owes a downside risk payment of $100 

to CMS, the IOTA participant would be 

permitted to receive no more than $50 

in alignment payments, in the aggregate, 

from its IOTA collaborators. In addition, 

the aggregate amount of all alignment 

payments from a single IOTA 

collaborator to the IOTA participant 

may not be greater than 25 percent of 

the IOTA participant’s downside risk 

payment over the course of a single PY 

for an IOTA collaborator. We sought 

comment on our proposed aggregate and 

individual IOTA collaborator 

limitations on alignment payments. 

We proposed that all gainsharing 

payments and any alignment payments 

must be administered by the IOTA 

participant in accordance with generally 

accepted accounting principles (GAAP) 

and Government Auditing Standards 

(The Yellow Book). Additionally, we 

proposed that all gainsharing payments 

and alignment payments must be made 

by check, electronic funds transfer 

(EFT), or another traceable cash 

transaction. We sought comment on the 

effect of this proposal. 

The proposals for the conditions and 

restrictions on gainsharing payments 

and alignment payments under the 

model are included in § 512.452. 

We sought comment about all of the 

conditions and restrictions set out in the 

preceding discussion, including 

whether additional or different 

safeguards would be needed to ensure 

program integrity, protect against abuse, 

and ensure that the goals of the model 

are met. 

The following is a summary of the 

public comments received on these 

proposals and our responses: 

Comment: A few commenters 

supported CMS’ proposal to allow 

gainsharing in IOTA but expressed 

concern regarding the proposed 50 

percent cap on shared losses. The 

commenters recommended that CMS 

remove the 50 percent cap on shared 

losses in order to reduce administrative 

burden for providers, strengthen 

integration between kidney transplant 

hospitals and specialists, and maintain 

consistency with prior models like CJR 

and BPCI Advanced. 

Response: We thank the commenters 

for their suggestions regarding the 

proposed 50 percent cap on shared 

losses. We believe, however, that given 

that the IOTA participant would be 

responsible for achieving model goals, it 

is important that the IOTA participant 

retain a significant portion of its 

responsibility for repayment amounts. 

With that said, we also believe that the 

50 percent cap on shared losses 

supports CMS’ goal. However, we will 

consider this recommendation in future 

notice and comment rulemaking. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

our proposed provisions for gainsharing 

payment and alignment payment 

conditions and limitations in our 

regulation at § 512.452 with a slight 

modification. As described and 

finalized in section III.C.1.a of this final 

rule, we are finalizing an alternative 

model start date of July 1, 2025. As 

such, we are also finalizing a slight 

modification to the definition of 

performance year (PY) to mean a 12- 

month period beginning on July 1 and 

ending on June 30 of each year during 

the model performance period, as 

described and finalized in section 

III.C.1.a of this final rule. Accordingly, 

we are modifying the regulation at 

§ 512.452(c)(1)(ii) to remove reference to 

a calendar year and specify that 

gainsharing payments and alignment 

payments must be distributed on an 

annual basis (not more than once per 

performance year). 

(4) Documentation Requirements 

To ensure the integrity of the sharing 

arrangements, we proposed that IOTA 

participants must meet a variety of 

documentation requirements for these 

arrangements. Specifically, the IOTA 

participant must— 

• Document the sharing arrangement 

contemporaneously with the 

establishment of the arrangement; 

• Maintain accurate current and 

historical lists of all IOTA collaborators, 

including IOTA collaborator names and 

addresses. Specifically, the IOTA 

participant must— 

++ Update such lists on at least a 

quarterly basis; and 

++ Publicly report the current and 

historical lists of IOTA collaborators 

and any written policies for selecting 

individuals and entities to be IOTA 

collaborators required by the IOTA 

participant on a web page on the IOTA 

participant’s website; and 

• Maintain and require each IOTA 

collaborator to maintain 

contemporaneous documentation with 

respect to the payment or receipt of any 

gainsharing payment or alignment 

payment that includes at a minimum 

the— 

++ Nature of the payment 

(gainsharing payment or alignment 

payment); 

++ Identity of the parties making and 

receiving the payment; 

++ Date of the payment; 

++ Amount of the payment; 

++ Date and amount of any 

recoupment of all or a portion of an 

IOTA collaborator’s gainsharing 

payment; and 


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++ Explanation for each recoupment, 

such as whether the IOTA collaborator 

received a gainsharing payment that 

contained funds derived from a CMS 

overpayment of an upside risk payment, 

or was based on the submission of false 

or fraudulent data. 

In addition, we proposed that the 

IOTA participant must keep records for 

all of the following: 

• Its process for determining and 

verifying its potential and current IOTA 

collaborators’ eligibility to participate in 

Medicare; 

• A description of current health 

information technology, including 

systems to track upside risk payments 

and downside risk payments; and 

• Its plan to track gainsharing 

payments and alignment payments. 

Finally, we proposed that the IOTA 

participant must retain and provide 

access to, and must require each IOTA 

collaborator to retain and provide access 

to, the required documentation in 

accordance with § 512.460 and 

§ 1001.952(ii). 

The proposals for the requirements for 

documentation of sharing arrangements 

under the model are included in 

§ 512.452(d). 

We sought comment about all of the 

requirements set out in the preceding 

discussion, including whether 

additional or different safeguards would 

be needed to ensure program integrity, 

protect against abuse, and ensure that 

the goals of the model are met. 

We received no comments on these 

proposals and therefore are finalizing 

these proposals as proposed in our 

regulation at § 512.452. 

e. Distribution Arrangements 

(1) General 

Similar to the CJR Model, we 

proposed that certain financial 

arrangements between IOTA 

collaborators and other individuals or 

entities called ‘‘collaboration agents’’ be 

termed ‘‘distribution arrangements.’’ For 

purposes of the Federal anti-kickback 

statute safe harbor for CMS-sponsored 

model arrangements (§ 1001.952(ii)(1)), 

we proposed to define ‘‘distribution 

arrangement’’ as a financial arrangement 

between an IOTA collaborator that is a 

PGP, NPPGP or TGP and a collaboration 

agent for the sole purpose of sharing a 

gainsharing payment received by the 

PGP, NPPGP or TGP. We proposed to 

define ‘‘collaboration agent’’ as an 

individual or entity that is not an IOTA 

collaborator and that is a member of a 

PGP, NPPGP, or TGP that has entered 

into a distribution arrangement with the 

same PGP, NPPGP, or TGP in which he 

or she is an owner or employee, and 

where the PGP, NPPGP, or TGP is an 

IOTA collaborator. Where a payment 

from an IOTA collaborator that is an 

PGP, NPPGP, or TGP is made to a 

collaboration agent, under a distribution 

arrangement, composed only of 

gainsharing payments, we proposed to 

define that payment as a ‘‘distribution 

payment.’’ We proposed that a 

collaboration agent could only make a 

distribution payment in accordance 

with a distribution arrangement that 

complies with the provisions of 

§ 512.454 and all other applicable laws 

and regulations, including the fraud and 

abuse laws. 

The proposals for the general 

provisions for distribution arrangements 

under the model are included in 

§ 512.454. 

We sought comment about all of the 

provisions set out in the preceding 

discussion, including whether 

additional or different safeguards would 

be needed to ensure program integrity, 

protect against abuse, and ensure that 

the goals of the model are met. 

We received no comments on these 

proposals and therefore are finalizing 

these proposals as proposed in our 

regulation at § 512.454. We are also 

finalizing without modification the 

proposed definitions of distribution 

arrangement, collaboration agent, and 

distribution payment at § 512.402. 

(2) Requirements 

We proposed a number of specific 

requirements for distribution 

arrangements as a program integrity 

safeguard to help ensure that their sole 

purpose is to create financial alignment 

between IOTA collaborators and 

collaboration agents and performance 

across the achievement domain, 

efficiency domain, and quality domain. 

These requirements largely parallel 

those proposed in § 512.452 for sharing 

arrangements and gainsharing payments 

based on similar reasoning for these two 

types of arrangements and payments. 

We proposed that all distribution 

arrangements must be in writing and 

signed by the parties, contain the date 

of the agreement, and be entered into 

before care is furnished to attributed 

patients under the distribution 

arrangement. Furthermore, we proposed 

that participation must be voluntary and 

without penalty for nonparticipation, 

and the distribution arrangement must 

require the collaboration agent to 

comply with all applicable laws and 

regulations. 

Like our proposal for gainsharing 

payments, we proposed that the 

opportunity to make or receive a 

distribution payment must not be 

conditioned directly or indirectly on the 

volume or value of referrals or business 

otherwise generated by, between or 

among the IOTA participant, any IOTA 

collaborator, any collaboration agent, or 

any individual or entity affiliated with 

an IOTA participant, IOTA collaborator, 

or collaboration agent. We proposed 

more flexible standards for the 

determination of the amount of 

distribution payments from PGPs, 

NPPGPs and TGPs for the same reasons 

we proposed this standard for the 

determination of gainsharing payments. 

We note that for distribution 

payments made by a PGP to PGP 

members, by NPPGPs to NPPGP 

members, or by TGPs to TGP members, 

the requirement that the amount of any 

distribution payments must be 

determined in accordance with a 

methodology that is substantially based 

on performance across the achievement 

domain, efficiency domain, and quality 

domain and the provision of IOTA 

activities may be more limiting in how 

a PGP pays its members than is allowed 

under existing law. Therefore, to retain 

existing flexibility for distribution 

payments by a PGP to PGP members, we 

proposed that the amount of the 

distribution payment from a PGP to PGP 

members must be determined in a 

manner that complies with § 411.352(g) 

or in accordance with a methodology 

that is substantially based on 

contribution to performance across the 

achievement domain, efficiency 

domain, and quality domain and the 

provision of IOTA activities and that 

may take into account the amount of 

such IOTA activities provided by a 

collaboration agent relative to other 

collaboration agents. The former option 

may allow a PGP to provide its members 

a financial benefit through the model 

without consideration of the PGP 

member’s individual contribution to 

performance across the achievement 

domain, efficiency domain and quality 

domain, and PGP members that are not 

collaboration agents (including those 

who furnished no services to attributed 

patients) would be able to receive a 

share of the profits from their PGP that 

includes the monies contained in a 

gainsharing payment. We believe this is 

an appropriate exception to the general 

standard for determining the amount of 

a distribution payment under the model 

from a PGP to a PGP member, because 

CMS has determined under the 

physician self-referral law that 

payments from a group practice as 

defined under § 411.352 to its members 

that comply with § 411.352(g) are 

appropriate. 

We sought comment on this proposal 

and specifically on whether there are 

additional safeguards or a different 


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standard is needed to allow for greater 

flexibility in calculating the amount of 

distribution payments that would avoid 

program integrity risks and whether 

additional or different safeguards are 

reasonable, necessary, or appropriate for 

the amount of distribution payments 

from a PGP to its members, a NPPGP to 

its members or a TGP to its members. 

Similar to our proposed requirements 

for sharing arrangements for those IOTA 

collaborators that furnish or bill for 

items and services, except for a 

distribution payment from a PGP to a 

PGP member that complies with 

§ 411.352(g), we proposed that a 

collaboration agent is eligible to receive 

a distribution payment only if the 

collaboration agent furnished or billed 

for an item or service rendered to an 

attributed patient during the same PY 

for which the IOTA participant earned 

the upside risk payment. We note that 

all individuals and entities that fall 

within our proposed definition of 

collaboration agent may either directly 

furnish or bill for items and services 

rendered to attributed patients. This 

proposal ensures that, absent the 

alternative safeguards afforded by a 

PGP’s distribution payments in 

compliance with § 411.352(g), there is 

the same required relationship between 

direct care for attributed patients during 

the PY and distribution payment 

eligibility that we require for 

gainsharing payment eligibility. We 

believe this requirement provides a 

safeguard against payments to 

collaboration agents that are unrelated 

to direct care for attributed patients 

during the PY when the amount of the 

distribution payment is not determined 

in a manner that complies with 

§ 411.352(g). 

Except for a distribution payment 

from a PGP to a PGP member that 

complies with § 411.352(g), we 

proposed the same limitations on the 

total amount of distribution payments to 

physicians, nonphysician practitioners, 

PGPs, NPPGPs and TGPs as we 

proposed for gainsharing payments. In 

the case of a collaboration agent that is 

a physician or nonphysician 

practitioner, we proposed to limit the 

total amount of distribution payments 

paid for a PY to the collaboration agent 

to 50 percent of the total Medicareapproved amounts under the PFS for 

items and services furnished by the 

collaboration agent to the IOTA 

participant’s attributed patients during 

the same PY for which the IOTA 

participant earned the upside risk 

payment that comprises the gainsharing 

payment being distributed. In the case 

of a collaboration agent that is a group 

practice, we proposed that the limit 

would be 50 percent of the total 

Medicare-approved amounts under the 

PFS for items and services billed by the 

group practice for items and services 

furnished by members of the group 

practice to the IOTA participant’s 

attributed patients during the same PY 

for which the IOTA participant earned 

the upside risk payment that comprises 

the gainsharing payment being 

distributed. We believe that, absent the 

alternative safeguards afforded by a 

group practice’s distribution payments 

in compliance with § 411.352(g), these 

proposed limitations on distribution 

payments, which are the same as those 

for gainsharing payments to physicians, 

nonphysician practitioners, and group 

practices, are necessary to eliminate any 

financial incentives for these 

individuals or entities to engage in a 

financial arrangement as an IOTA 

collaborator versus as a collaboration 

agent. Furthermore, we believe that 

group practices should be able to choose 

whether to engage in financial 

arrangements directly with IOTA 

participants as IOTA collaborators 

without having a different limit on their 

maximum financial gain from one 

arrangement versus another. 

We further proposed that with respect 

to the distribution of any gainsharing 

payment received by a PGP, NPPGP or 

TGP, the total amount of all distribution 

payments must not exceed the amount 

of the gainsharing payment received by 

the IOTA collaborator from the IOTA 

participant. Like gainsharing and 

alignment payments, we proposed that 

all distribution payments must be made 

by check, electronic funds transfer, or 

another traceable cash transaction. The 

collaboration agent must retain the 

ability to make decisions in the best 

interests of the patient, including the 

selection of devices, supplies, and 

treatments. Finally, the distribution 

arrangement must not induce the 

collaboration agent to reduce or limit 

medically necessary items and services 

to any Medicare beneficiary or reward 

the provision of items and services that 

are medically unnecessary. 

We proposed that the IOTA 

collaborator must maintain 

contemporaneous documentation 

regarding distribution arrangements in 

accordance with § 512.454, including— 

• The relevant written agreements; 

• The date and amount of any 

distribution payment(s); 

• The identity of each collaboration 

agent that received a distribution 

payment; and 

• A description of the methodology 

and accounting formula for determining 

the amount of any distribution payment. 

We proposed that the IOTA 

collaborator may not enter into a 

distribution arrangement with any 

individual or entity that has a sharing 

arrangement with the same IOTA 

participant. This proposal ensures that 

the proposed separate limitations on the 

total amount of gainsharing payment 

and distribution payment to PGPs, 

NPPGPs, TGPs, physicians, and 

nonphysician practitioners that are 

substantially based on performance 

across the achievement domain, 

efficiency domain, and quality domain 

and the provision of IOTA activities are 

not exceeded in absolute dollars by a 

PGP, NPPGP, TGP, physician, or 

nonphysician practitioner’s 

participation in both a sharing 

arrangement and distribution 

arrangement for the care of the same 

IOTA beneficiaries during the PY. 

Allowing both types of arrangements for 

the same individual or entity for care of 

the same attributed patients during the 

PY could also allow for duplicate 

counting of the individual or entity’s 

same contribution to the achievement 

domain, efficiency domain, and quality 

domain and provision of IOTA Model 

activities in the methodologies for both 

gainsharing and distribution payments, 

leading to financial gain that is 

disproportionate to the contribution to 

the achievement domain, efficiency 

domain and quality domain and 

provision of IOTA Model activities by 

that individual or entity. Finally, we 

proposed that the IOTA collaborator 

must retain and provide access to, and 

must require collaboration agents to 

retain and provide access to, the 

required documentation in accordance 

with § 512.460. 

The proposals for requirements for 

distribution arrangements under the 

model are included in § 512.454. 

We sought comment about all of the 

requirements set out in the preceding 

discussion, including whether 

additional or different safeguards would 

be needed to ensure program integrity, 

protect against abuse, and ensure that 

the goals of the model are met. In 

addition, we sought comment on how 

the regulation of the financial 

arrangements under this proposal may 

interact with how these or similar 

financial arrangements are regulated 

under the Medicare Shared Savings 

Program. 

The following is a summary of the 

public comments received on these 

proposals and our responses: 

Comment: A commenter expressed 

support for the proposal that the Federal 

anti-kickback statute safe harbor be 

made available to IOTA participants and 

their IOTA collaborators. 


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Transplant Immunosuppressant Therapy: Is This 

Sustainable? Current Transplantation Reports, 2(2), 

113–121. https://doi.org/10.1007/s40472-015-0052- 

y. 

329The kidney transplant waitlist. (n.d.). 

Transplant Living. https://transplantliving.org/ 

kidney/the-kidney-transplant-waitlist/. 

330Park, C., Jones, M.-M., Kaplan, S., Koller, F.L., 

Wilder, J.M., Boulware, L.E., & McElroy, L.M. 

(2022). A scoping review of inequities in access to 

organ transplant in the United States. International 

Journal for Equity in Health, 21(1). https://doi.org/ 

10.1186/s12939-021-01616-x. 

331Evans, R.W., Applegate, W.H., Briscoe, D.M., 

Cohen, D.J., Rorick, C.C., Murphy, B.T., & Madsen, 

J.C. (2010). Cost-related immunosuppressive 

medication nonadherence among kidney transplant 

recipients. Clinical Journal of the American Society 

of Nephrology, 5(12), 2323–2328. https://doi.org/ 

10.2215/cjn.04220510. 

332Assessing the Costs and Benefits of Extending 

Coverage of Immunosuppressive Drugs under 

Medicare. (n.d.). ASPE. https://aspe.hhs.gov/ 

reports/assessing-costs-benefits-extending-coverageimmunosuppressive-drugs-under-medicare. 

333United States Renal Data System. (2022). 2022 

USRDS Annual Data Report: Epidemiology of 

kidney disease in the United States. National 

Institutes of Health, National Institute of Diabetes 

and Digestive and Kidney Diseases, Bethesda, MD. 

https://usrds-adr.niddk.nih.gov/2022. 

334 Ibid. 

Response: We thank the commenter 

for their support. 

After consideration of the public 

comment we received, we are finalizing 

our proposals regarding the 

requirements for distribution 

arrangements without modification in 

our regulation at § 512.454. 

f. Enforcement Authority 

OIG authority is not limited or 

restricted by the provisions of the 

model, including the authority to audit, 

evaluate, investigate, or inspect the 

IOTA participant, IOTA collaborators, 

collaboration agents, or any other 

person or entity or their records, data, 

or information, without limitations. 

Additionally, no model provisions limit 

or restrict the authority of any other 

Government Agency to do the same. The 

proposals for enforcement authority 

under the model are included in 

§ 512.455. 

We sought comment about all of the 

requirements set out in the preceding 

discussion, including whether 

additional or different safeguards would 

be needed to ensure program integrity, 

protect against abuse, and ensure that 

the goals of the model are met. 

We received no comments on these 

proposals. These proposals are finalized 

at § 512.455 with slight modification to 

remove a stray reference to the CJR 

Model at § 512.455(b). 

g. Attributed Patient Engagement 

Incentives 

We believed it was necessary and 

appropriate to provide additional 

flexibilities to IOTA participants for 

purposes of testing the IOTA Model to 

give IOTA participants additional access 

to the tools necessary to improve 

attributed patients’ access to kidney 

transplants and ensure attributed 

patients receive comprehensive and 

patient-centered post-transplant care. As 

discussed in section III.C.11.i. of this 

final rule, CMS made a determination 

that the Federal anti-kickback statute 

safe harbor for CMS-sponsored model 

patient incentives is available to protect 

Part B and Part D immunosuppressive 

drug cost sharing support and attributed 

patient engagement incentives finalized 

in this section when the incentives are 

offered in compliance with this policy, 

specifically the conditions for use of the 

Federal anti-kickback statute safe harbor 

set out at § 1001.952(ii)(2). 

(1) Part B and Part D 

Immunosuppressive Drug Cost Sharing 

Support 

The cost of immunosuppressive drugs 

is a financial burden for many 

transplant recipients, particularly those 

without sufficient health insurance 

coverage.328 A person’s ability to pay for 

immunosuppressive drugs, among other 

services needed in the perioperative and 

postoperative periods, is a factor used 

by transplant hospitals to assess 

suitability for the transplant waitlist.329

Studies have found that low income 

status decreases the likelihood of 

waitlisting.330 One survey of transplant 

programs found that 67.3 percent of 

programs surveyed reported frequent or 

occasional failure to list patients due to 

concerns regarding ability to pay for 

immunosuppressive medications.331 In 

assessing the financial implications of 

extending Medicare coverage of 

immunosuppressive drugs for the 

lifetime of the patient, the Assistant 

Secretary for Planning and Evaluation 

(ASPE) assumed a non-adherence graft 

failure rate of 10.7 percent and assessed 

that factors outside of affordability had 

minimal impact on non-adherence to 

immunosuppressive drugs.332

Between 2016 and 2019, 

immunosuppressive drugs represented 

the greatest proportion of drug 

expenditures in the year following 

kidney transplant in Medicare Parts B 

and D.333 Between 2016 and 2019, the 

Per-Patient-Per-Year expenditure in the 

year following transplant in Medicare 

Parts B and D was $6,947.334 Medicare 

beneficiaries whose immunosuppressive 

drugs are covered by Part B are 

responsible for 20 percent of these costs. 

The cost sharing obligation of Medicare 

beneficiaries whose immunosuppressive 

drugs are covered by Part D can vary 

depending on the benefit structure of 

the Part D plan. 

At § 512.456 of the proposed rule, we 

proposed to allow IOTA participants to 

subsidize, in whole or in part, the cost 

sharing associated with 

immunosuppressive drugs covered by 

Part B, the Part B Immunosuppressive 

Drug (Part B ID) benefit, and Part D 

(‘‘Part B and Part D immunosuppressive 

drug cost sharing support’’) incurred by 

attributed patients. As discussed in 

section III.C.11.i. of this final rule, CMS 

has made a determination that the 

Federal anti-kickback statute safe harbor 

for CMS-sponsored model patient 

incentives (§ 1001.952(ii)(2)) is available 

to protect the subsidy of cost sharing 

obligations that are made in compliance 

with this policy and the conditions for 

use of the Federal anti-kickback statute 

safe harbor set out at § 1001.952(ii)(2). 

As stated in the proposed rule, we 

expect that a large proportion of an 

IOTA participant’s attributed patient 

population would be Medicare ESRD 

beneficiaries, covered either by 

traditional Medicare or by MA (89 FR 

43518). Most ESRD beneficiaries 

covered by traditional Medicare receive 

immunosuppressive drug coverage 

through Part B. A proportion of ESRD 

beneficiaries who are not eligible for 

Part A at the time of the kidney 

transplant or who receive a kidney 

transplant in a non-Medicare approved 

facility receive immunosuppressive 

drugs through Medicare Part D. ESRD 

beneficiaries covered by MA receive 

Part B immunosuppressive drugs 

through the plan in which the 

beneficiary is enrolled. 

To be eligible for Part B and Part D 

immunosuppressive drug cost sharing 

support, at § 512.402 of the proposed 

rule, we proposed to define eligible 

attributed patient as an attributed 

patient that receives 

immunosuppressive drug coverage 

through Part B or Part D but that does 

not have secondary insurance that could 

provide cost sharing support. An IOTA 

participant’s attributed patient 

population could include several 

subsets of eligible attributed patients. 

One subset of eligible attributed patients 

could be ESRD beneficiaries who are not 

able to purchase secondary insurance 

due to State laws that do not require 

insurers to sell Medigap plans to 

Medicare Beneficiaries under the age of 

65. Another subset of eligible attributed 

patients could, under certain 

conditions, be ESRD beneficiaries 

whose eligibility for Medicare only due 

to ESRD ends 36 months following a 

kidney transplant. Attributed patients 

whose eligibility for Medicare due to 

ESRD ends 36 months following a 


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kidney transplant may be eligible for the 

Part B–ID benefit depending on the 

availability of other health coverage 

options such as Medicaid, plans 

purchased via a State health exchange, 

or the TRICARE for Life program. Other 

attributed patients whose Medicare 

eligibility due to ESRD concludes 36 

months following a transplant could 

choose to return to work and receive 

immunosuppressive drug coverage 

through an Employer Group Health Plan 

(EGHP), enroll in a Qualified health 

plan (QHP) under the Affordable Care 

Act as defined by 45 CFR 155.20, or 

receive coverage through Medicaid. 

These attributed patients would not be 

eligible for Part B and Part D 

immunosuppressive drug cost sharing 

support. We believed that Part B and 

Part D immunosuppressive drug cost 

sharing support would have special 

value for attributed patients whose 

Medicare eligibility due only to ESRD 

ends after 36 months and who are 

eligible for Medicare Savings Programs 

(MSPs) but who live in States that have 

not expanded Medicaid eligibility for 

adults to include certain individuals 

with incomes up to 138 percent of the 

Federal Poverty Level (FPL). These 

individuals may have incomes that are 

too high to qualify for Medicaid, but too 

low to qualify for advance premium tax 

credits (APTCs) or cost-sharing 

reductions (CSRs) that would allow 

them to purchase a QHP. We did not 

propose that Part B and Part D 

immunosuppressive drug cost sharing 

support would count towards an eligible 

attributed patients’ Part D True Out-ofPocket (TrOOP). Part B and Part D 

immunosuppressive drug cost sharing 

support would be reported on the 

Prescription Drug Event (PDE) record as 

Patient Liability Reduction due to Other 

Payer Amount (PLRO) (89 FR 43518). 

At § 512.456(a) of the proposed rule, 

we proposed to allow IOTA participants 

to subsidize, in whole or in part, the 

cost sharing associated with 

immunosuppressive drugs covered by 

Part B, the Part B–ID benefit, and Part 

D because we believed cost sharing 

associated with medically necessary 

immunosuppressive drugs would 

represent a significant out-of-pocket cost 

burden to attributed patients who 

receive immunosuppressive drug 

coverage through Part B, the Part B–ID 

benefit, or Part D, and because we 

believed an IOTA participant’s 

attributed patient population would 

include beneficiaries whose 

immunosuppressive drugs are covered 

through each of these avenues (that is, 

Part B, the Part B–ID benefit, and Part 

D). 

At § 512.456(a) of the proposed rule, 

we proposed several safeguards for the 

proposed Part B and Part D 

immunosuppressive drug cost sharing 

support policy. First, an attributed 

patient must be eligible to receive cost 

sharing support under the Part B and 

Part D cost sharing support policy. 

IOTA participants must provide a 

written policy for Part B and Part D 

immunosuppressive drug cost sharing 

support in a form and manner 

determined by CMS that is approved by 

CMS prior to the PY in which the cost 

sharing support would be available and 

prior to offering attributed patients the 

incentive. An IOTA participant would 

be required to revalidate the written 

policy with CMS in a form and manner 

determined by CMS prior to each PY in 

which Part B and Part D 

immunosuppressive drug cost sharing 

support would be offered subsequently. 

The initial written policy and the policy 

that would be revalidated by CMS must 

establish and justify the criteria that 

qualify an eligible attributed patient to 

receive Part B and Part D 

immunosuppressive drug cost sharing 

support. In providing the written policy 

and the revalidation of the written 

policy for Part B and Part D 

immunosuppressive drug cost sharing 

support, the IOTA participant must 

attest that the IOTA participant will not, 

in providing Part B and Part D 

immunosuppressive drug cost sharing 

support, take into consideration the 

type, cost, generic status, or 

manufacturer of the immunosuppressive 

drug(s) or limit an eligible attributed 

patient’s choice of pharmacy. We 

believed these policies were necessary 

to ensure that an IOTA participant 

would have a sound basis for 

determining eligibility requirements for 

Part B and Part D immunosuppressive 

drug cost sharing support. 

At § 512.456(b) of the proposed rule, 

we proposed safeguards to protect 

against an IOTA participant 

preferentially providing cost sharing 

support for certain immunosuppressive 

drugs. An IOTA participant must not 

take into consideration the type, cost, 

generic status, or manufacturer of the 

immunosuppressive drug(s) or limit an 

eligible attributed patients’ choice of 

pharmacy when providing Part B and 

Part D immunosuppressive drug cost 

sharing support. In addition, an IOTA 

participant must not accept financial or 

operational support for the Part B and 

Part D immunosuppressive drug cost 

sharing support from pharmacies and 

pharmaceutical manufacturers. 

Immunosuppressive drug regimens are 

adjusted to an individual’s unique 

clinical characteristics to achieve a 

balance between preserving the health 

of the transplanted organ and reducing 

morbidity associated with long-term 

immunosuppression. We did not believe 

that the Federal anti-kickback statute 

safe harbor for CMS-sponsored model 

patient incentives should be used to 

protect arrangements that could limit or 

influence attributed patients’ access to 

the most clinically appropriate 

immunosuppressive drugs. Finally, to 

facilitate compliance monitoring, we 

proposed that IOTA participants must 

maintain documentation regarding this 

beneficiary incentive. At minimum, the 

IOTA participant must maintain 

contemporaneous documentation that 

includes the identity of the eligible 

attributed patient to whom Part B and 

Part D immunosuppressive drug cost 

sharing support was provided, the date 

or dates on which Part B and Part D 

immunosuppressive drug cost sharing 

support was provided, and the amount 

or amounts of Part B and Part D 

immunosuppressive drug cost sharing 

support that was provided. IOTA 

participants must retain and provide 

access to the required documentation 

consistent with section III.C.12 and 

§ 1001.952(ii)(2). 

We considered alternative safeguards 

for the Part B and Part D 

immunosuppressive drug cost sharing 

support policy (89 FR 43518). We 

considered requiring that an IOTA 

participant that wishes to offer Part B 

and Part D immunosuppressive drug 

cost sharing support must offer it to 

every attributed patient whose 

immunosuppressive drugs are covered 

by Part B or Part D and who does not 

have secondary insurance (89 FR 

43518). Ultimately, we believed such a 

policy would run counter to our 

intention to offer IOTA participants 

flexibility to meet the needs of their 

attributed patient populations. 

We also considered alternatives to the 

entirety of the proposed Part B and Part 

D immunosuppressive drug cost sharing 

support policy (89 FR 43594). We 

considered waiving Medicare payment 

requirements such that CMS would pay 

the full amount of the Part B or Part B– 

ID coinsurance for immunosuppressive 

drugs that are medically necessary for 

preventing or treating the rejection of a 

transplanted organ or tissue. If we were 

to pay 100 percent of the cost of 

immunosuppressive drugs for attributed 

patients who are Medicare beneficiaries 

whose immunosuppressive drugs are 

covered by Part B and attributed 

patients whose immunosuppressive 

drugs are covered by the Part B–ID 

benefit, such attributed patients would 

have no cost sharing obligation. 


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However, we believed that this policy 

would represent too large an impact to 

the IOTA Model savings estimates, and 

thus would potentially jeopardize our 

ability to continue to test the IOTA 

Model, if such a policy were finalized. 

We also considered waiving the 

premium for the Part B–ID benefit (89 

FR 43595). Under section 402(d) of the 

CAA and the implementing regulations 

at 42 CFR 408.20(f), the Secretary 

determines and promulgates a monthly 

premium rate for individuals enrolled in 

the Part B–ID benefit that is 15 percent 

of the monthly actuarial rate for 

beneficiaries who are age 65 and older. 

The Part B premium for 2024 for 

individuals enrolled in the Part B–ID 

benefit who file individual or joint tax 

returns with a modified adjusted gross 

income of less than or equal to $103,000 

or $206,000 respectively, is $103.00. 

The Part B–ID premium is subject to 

income-related adjustments based on 

modified adjusted gross income. We 

believed the Part B–ID benefit monthly 

premium may represent a substantial 

out-of-pocket expenditure for 

individuals enrolled in the benefit given 

that it is prudent for the individual to 

acquire additional health insurance to 

cover other necessary health care 

services outside of immunosuppressive 

drugs. A premium waiver for the Part B– 

ID benefit is authorized by section 

1115A(d)(1) of the Act, under which the 

Secretary may waive provisions of Title 

XVIII of the Act, including provisions of 

section 1836(b) of the Act, as may be 

necessary solely for purposes of carrying 

out section 1115A of the Act. We 

believed, however, that waiving the 

premium for the Part B–ID benefit 

would have too significant an impact on 

the IOTA Model savings estimates; 

therefore, we are not proposing to waive 

it for purposes of the IOTA Model. 

We sought feedback on the proposal 

to allow an IOTA participant to 

subsidize the 20 percent coinsurance on 

immunosuppressive drugs covered by 

Part B or the Part B–ID benefit and the 

cost sharing associated with 

immunosuppressive drugs covered by 

Part D, when an attributed patient is 

eligible, meaning the attributed patient 

does not have secondary insurance and 

meets the eligibility criteria defined by 

the IOTA participant and approved by 

CMS prior to the PY in which the cost 

sharing support is provided. We also 

solicited input from interested parties 

on additional patient-centered 

safeguards that we may consider 

protecting cost sharing subsidies made 

under the proposed Part B and Part D 

immunosuppressive drug cost sharing 

support policy, if finalized. 

The following is a summary of the 

public comments received on these 

proposals and our responses: 

Comment: Several commenters 

expressed support to provide cost 

sharing for immunosuppressive drugs 

covered under Part B and Part D to 

ensure long term success of kidney 

transplants. 

Response: We thank the commenters 

for their support. 

Comment: Several commenters 

expressed concern with the Part B and 

Part D drug cost-sharing provision, as it 

could incentivize patient choice of 

kidney transplant hospital, disadvantage 

patients with other insurance, create 

logistical challenges, and create 

significant financial burden for IOTA 

participants. 

Response: We thank the commenters 

for their feedback. We understand the 

concerns about possible incentivization 

of patient choice of kidney transplant 

hospital but believe patient choice is 

adequately protected in the provision to 

be finalized. First, and most 

importantly, we note that providers and 

suppliers are still required to provide all 

medically necessary services to 

beneficiaries, and that this model does 

not change beneficiary access to 

services, providers, or suppliers. 

Second, we note that there are already 

policies in other models that include 

similar incentives. We also understand 

the possible disadvantage to patients 

with other insurance. We expect that a 

large portion of the IOTA participant’s 

attributed patient population would be 

Medicare ESRD beneficiaries, covered 

by traditional Medicare, so any possible 

impact would be mitigated as there 

would be only a small number of 

patients with other insurance. We also 

believe that the safeguards that we have 

put into place, such as the written 

policy requirements, will limit these 

concerns as we will be monitoring the 

provision of any incentives. 

We also understand the concerns 

about the potential burdens these 

incentives may place on IOTA 

participants. IOTA participants can 

choose whether to offer the Part B and 

Part D drug cost-sharing provision. As 

such, if the logistical challenges and 

financial burden for transplant hospitals 

exceeds the benefits for the IOTA 

participants, then the benefit does not 

need to be provided. Our goal is to 

ensure that beneficiary incentives 

effectively support patient care without 

imposing unnecessary burdens on IOTA 

participants. We are finalizing this 

policy as proposed. However, we 

appreciate these insights and will take 

them into account in future rulemaking 

cycles. 

Comment: Several commenters 

suggested the cost-sharing provision 

should include additional metrics such 

as allowing the Part B copay to count 

towards out-of-pocket maximum, 

allowing IOTA participants to have the 

cost sharing total be offset in part or 

whole, and track the effectiveness of 

cost sharing on patient care. 

Response: We thank the commenters 

for their suggestion. We did not propose 

that Part B and Part D 

immunosuppressive drug cost sharing 

support would count towards an eligible 

attributed patients’ Part D True Out-ofPocket (TrOOP). Part B and Part D 

immunosuppressive drug cost sharing 

support would be reported on the 

Prescription Drug Event (PDE) record as 

Patient Liability Reduction due to Other 

Payer Amount (PLRO). We believe that 

as these costs are not being expended by 

the attributed patients themselves but 

rather by the IOTA participant, that it 

would contravene the purposes behind 

the TrOOP. 

Neither allowing IOTA participants to 

have the cost sharing total to be offset 

nor tracking the effectiveness of cost 

sharing on patient care were included in 

the proposed rule, and we therefore are 

not finalizing this expansion suggested 

by the commenters in this final rule. We 

will take the commenters’ feedback into 

consideration as we consider potential 

future changes to the model design. 

Comment: A few commenters 

suggested CMS should provide full cost 

coverage for Part B and Part D 

immunosuppressive drugs for all 

patients included on the low-income 

list. 

Response: We thank the commenters 

for their suggestion. We considered 

waiving Medicare payment 

requirements such that we would pay 

the full amount of the Part B or Part D 

coinsurance for immunosuppressive 

drugs that are medically necessary for 

preventing or treating the rejection of a 

transplanted organ or tissue. We believe 

that covering the cost even for the 

subset of patients who qualify as lowincome would represent too large an 

impact to the IOTA Model savings 

estimates, and thus would potentially 

jeopardize our ability to continue to test 

the IOTA Model. As such, we 

determined that a cost support subsidy 

rather than a reduction would meet the 

objectives of this model. 

Comment: A few commenters 

suggested the provision should include 

other related services, such as anti-viral, 

blood pressure and diabetes 

medications, blood and urine testing, 

and office visits. 

Response: We thank the commenters 

for their suggestion. The suggested 


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96424 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

335Recovery after transplant surgery | American 

Kidney Fund. (2021, December 14). 

www.kidneyfund.org. https://www.kidneyfund.org/ 

kidney-donation-and-transplant/life-aftertransplant-rejection-prevention-and-healthy-tips/ 

recovery-after-transplant-surgery. 

336Browne, T., McPherson, L., Retzloff, S., 

Darius, A., Wilk, A.S., Cruz, A., Wright, S., Pastan, 

S.O., Gander, J.C., Berlin, A.A., & Patzer, R.E. 

(2021). Improving access to kidney transplantation: 

Perspectives from Dialysis and Transplant Staff in 

the Southeastern United States. Kidney Medicine, 

3(5). https://doi.org/10.1016/j.xkme.2021.04.017. 

337 Ibid. 

338 Gillespie, A. (2021). Communication 

breakdown: Improving communication between 

transplant centers and dialysis facilities to improve 

access to kidney transplantation. Kidney Medicine, 

3(5), 696–698. https://doi.org/10.1016/ 

j.xkme.2021.08.003. 

339Corruble, E., Durrbach, A., Charpentier, B., 

Lang, P., Amidi, S., Dezamis, A., Barry, C., & 

Falissard, B. (2010). Progressive increase of anxiety 

and depression in patients waiting for a kidney 

transplantation. Behavioral Medicine, 36(1), 32–36. 

https://doi.org/10.1080/08964280903521339. 

expansion of other related services, such 

as anti-viral, blood pressure and 

diabetes medications, blood and urine 

testing, and office visits, was not 

included in the proposed rule, and we 

therefore are not finalizing this 

expansion suggested by the commenters 

in this final rule. We will take the 

commenters’ feedback into 

consideration as we consider potential 

future changes to the model design. 

After consideration of the public 

comments we received, we are 

finalizing our proposed provision for 

the Part B and Part D 

immunosuppressive drug cost sharing 

support beneficiary incentive as 

proposed, with a minor technical 

correction to update the section 

numbering in our regulation at 

§ 512.456. We are finalizing the 

proposed definition of eligible 

attributed patient at § 512.402 with a 

minor technical correction to address a 

typographical error by inserting the 

word ‘‘drug’’ in ‘‘immunosuppressive 

drug coverage.’’ We are also finalizing 

the proposed definition of Part B and 

Part D immunosuppressive drug cost 

sharing support at § 512.402 with a 

minor technical correction to update the 

cross reference. Specifically, we are 

removing the cross reference to 

§ 512.458 and replacing it to reflect 

§ 512.456. 

(2) Attributed Patient Engagement 

Incentives 

We believed that providing additional 

flexibilities under the IOTA Model 

would allow IOTA participants to 

support attributed patients in 

overcoming challenges associated with 

remaining active on the kidney 

transplant waitlist and adhering to 

comprehensive post-transplant care. 

Thus, at § 512.458(a) of the proposed 

rule, we proposed that IOTA 

participants may offer the following 

attributed patient engagement 

incentives under certain circumstances: 

• Communication devices and related 

communication services directly 

pertaining to communication with an 

IOTA participant or IOTA collaborator 

to improve communication between an 

attributed patient and an IOTA 

participant or IOTA collaborator; 

• Transportation to and from a 

transplant hospital that is an IOTA 

participant and between other providers 

and suppliers involved in the provision 

of ESRD care; 

• Mental health services to address an 

attributed patient’s behavioral health 

symptoms pre- and post-transplant; and 

• In-home care to support the health 

of the attributed patient or the kidney 

transplant in the post-transplant period. 

For the purposes of the proposed 

attributed patient engagement 

incentives, at § 512.402 of the proposed 

rule, we defined post-transplant period 

to mean the 90-day period following an 

attributed patient’s receipt of a kidney 

transplant. We proposed a 90-day posttransplant period because it may take up 

to 3 months for many individuals to 

fully recover from a kidney 

transplant.335 At § 512.458(b) of the 

proposed rule, we proposed that 

attributed patient engagement 

incentives that are communication 

devices and related communication 

services, transportation to and from an 

IOTA participant and between other 

providers and suppliers involved in the 

provision of ESRD care, and mental 

health services to address an attributed 

patient’s behavioral health symptoms 

could, under certain circumstances 

described in this section, be offered 

while an attributed patient is on a 

waitlist, after an attributed patient 

receives a transplant, or both. In-home 

care to support the health of the 

attributed patient or the kidney 

transplant may only be offered in the 

post-transplant period. 

A mixed methods study of transplant 

providers’ assessment of barriers to 

accessing a kidney transplant found that 

transportation was the most reported 

impediment to transplant (89 FR 

43518).336 Interested parties have 

informed us that transportation to 

medical appointments pre- and posttransplant, as well as to and from the 

dialysis center for treatments pretransplant, is an important factor in 

maintaining active status on the list and 

the health of an individual and the graft 

after the transplant. Interested parties 

have also communicated with us about 

the importance of communication with 

waitlisted patients. We understood it 

can be common for an individual to not 

receive important information about the 

kidney transplant process when 

transplant hospitals and dialysis 

facilities do not communicate with one 

another about a patient’s status. We 

believed we may be able to overcome 

this challenge by providing IOTA 

participants with greater flexibility to 

communicate directly with attributed 

patients about their status in the kidney 

transplant process.337 338 We understood 

that attributed patients who face 

communication and transportation 

barriers while on the kidney transplant 

waitlist may be inactivated, meaning 

that the attributed patient cannot 

receive organ offers (89 FR 43518). An 

attributed patient that cannot receive 

organ offers is misaligned with the 

IOTA Model’s proposed performance 

assessment methodology, which would 

encourage an IOTA participant to 

increase its number of transplants. An 

attributed patient that cannot receive 

organ offers represents a missed 

opportunity for transplant, which is 

inconsistent with the goals of the 

proposed IOTA Model. Accordingly, we 

were interested in providing a 

framework under which an IOTA 

participant would be able to offer 

attributed patient engagement 

incentives in the form of 

communication devices and related 

communication services may increase 

the number of attributed patients who 

achieve and maintain active status on 

the kidney transplant waitlist. We 

believed the availability of 

transportation to and from an IOTA 

participant and between other providers 

and suppliers involved in the provision 

of ESRD care and mental health services 

to address an attributed patient’s 

behavioral health symptom may also act 

in service of assisting more attributed 

patients in overcoming barriers to 

achieving or maintaining active status 

on a waitlist, among other challenges in 

the kidney transplant process prior to 

and after receiving a kidney transplant. 

For example, we were also interested 

in providing greater flexibility to IOTA 

participants to support improved 

adherence to processes of care pre- and 

post-transplant that may support the 

ability of an attributed patient to accept 

an organ offer and the outcomes of the 

attributed patient and the graft after 

receiving a kidney transplant. Anxiety 

and depression may increase as 

attributed patients spend time on the 

kidney transplant waitlist.339 Prevalence 

of depression is reported to decrease 

after kidney transplant, but may still 


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340Szeifert, L., Molnar, M.Z., Ambrus, C., Koczy, 

A.B., Kovacs, A.Z., Vamos, E.P., Keszei, A., Mucsi, 

I., & Novak, M. (2010). Symptoms of depression in 

kidney transplant recipients: A cross-sectional 

study. American Journal of Kidney Diseases, 55(1), 

132–140. https://doi.org/10.1053/ 

j.ajkd.2009.09.022. 

exceed 20 percent.340 Interested parties 

have reported that behavioral health 

symptoms interfere with adherence to 

care recommendations, including 

activities that support remaining active 

on the transplant waitlist and behaviors 

that support positive clinical outcomes 

for the patient and the graft after the 

kidney transplant procedure. Interested 

parties have also informed us of the 

importance of a transplant recipient 

having the support of another person in 

the home for a short period in the posttransplant period to enhance recovery. 

We also believed providing the option 

for flexibility to offer attributed patient 

engagement incentives under the 

auspices of the IOTA Model would 

allow IOTA participants to provide 

attributed patients with tools to 

overcome barriers in the process of 

receiving a kidney transplant, thereby 

increasing adherence to the kidney 

transplant process, improving posttransplant outcomes, and supporting 

patient-centricity in the IOTA Model. 

As stated in section III.C.11.i. of this 

final rule, we made the determination 

that the Federal anti-kickback statute 

safe harbor for CMS-sponsored model 

patient incentives (§ 1001.952(ii)(2)) is 

available to protect the attributed 

patient engagement incentives proposed 

in this section when the incentives are 

offered or given to the attributed patient 

solely when the remuneration is 

exchanged between an IOTA participant 

and an attributed patient in compliance 

with the requirements of § 512.459 and 

the conditions of the safe harbor for 

CMS-sponsored model patient 

incentives. 

At § 512.458(b) of the proposed rule, 

we proposed programmatic 

requirements for the attributed patient 

engagement incentives. First, an IOTA 

participant must provide a written 

policy in a form and manner determined 

by CMS for the provision of attributed 

patient engagement incentives. The 

IOTA participant’s written policy must 

be approved by CMS before the PY in 

which an attributed patient engagement 

incentive is first made available, and 

must be revalidated by CMS, in a form 

and manner specified by CMS, prior to 

each PY in which an IOTA participant 

wishes to offer an attributed patient 

engagement incentive subsequently. The 

IOTA participant’s written policy must 

describe the items or services the IOTA 

participant plans to provide, an 

explanation of how each item or service 

that would be an attributed patient 

engagement incentive has a reasonable 

connection to, at minimum, one of the 

following: (1) achieving or maintaining 

active status on a kidney transplant 

waitlist; (2) accessing the kidney 

transplant procedure; or (3) the health of 

the attributed patient or the kidney 

transplant in the post-transplant period, 

and a justification for the need for the 

attributed patient engagement 

incentives that is specific to the IOTA 

participant’s attributed patient 

population. The IOTA participant’s 

written policy must also include an 

attestation that items that are attributed 

patient engagement incentives would be 

provided directly to an attributed 

patient, meaning that third parties 

would be precluded from providing an 

item that is an attributed patient 

engagement incentive to an attributed 

patient. We are not requiring an IOTA 

participant to provide any such 

attestation pertaining to services that are 

attributed patient engagement 

incentives because we acknowledge that 

services such as communication 

services, mental health services and inhome care services are generally 

provided by third parties. The IOTA 

participant would, however, be required 

to attest in its written policy that the 

IOTA participant would pay the service 

provider directly for services. Finally, 

the IOTA participant’s written policy 

must also include an attestation that any 

items or services acquired by the IOTA 

participant that would be furnished as 

attributed patient engagement 

incentives would be acquired for the 

minimum amount necessary for an 

attributed patient to achieve or maintain 

active status on the kidney transplant 

waitlist, access the kidney transplant 

procedure, or support the health of the 

attributed patient or the kidney 

transplant in the post-transplant period. 

At § 512.458(c) of the proposed rule, 

we proposed the following restrictions 

on the provision of attributed patient 

engagement incentives. An IOTA 

participant must provide items that are 

attributed patient engagement 

incentives must be provided directly to 

an attributed patient and an IOTA 

participant must pay a service provider 

directly for any services that are offered 

as attributed patient engagement 

incentives. An IOTA participant must 

not offer attributed patient engagement 

incentives that are tied to the receipt of 

items of services from a particular 

provider or supplier or advertise or 

promote items or services that are 

attributed patient engagement 

incentives, except to make an attributed 

patient aware of the availability of the 

items or services at the time an 

attributed patient could reasonably 

benefit from them. An IOTA participant 

must not receive donations directly or 

indirectly to purchase attributed patient 

engagement incentives. Finally, items 

that are attributed patient engagement 

incentives must be retrieved from the 

attributed patient when the attributed 

patient is no longer eligible for that item 

or at the conclusion of the IOTA Model, 

whichever is earlier. Documented, 

diligent, good faith attempts to retrieve 

items that are attributed patient 

engagement incentives are deemed to 

meet the retrieval requirement. 

At § 512.458(c) of the proposed rule, 

we proposed the following, additional 

restrictions pertaining to attributed 

patient engagement incentives that are 

communication devices, because we 

believe that such items may be 

especially susceptible to abuse. An 

IOTA participant’s purchase of items 

that are communication devices must 

not exceed $1000 in retail value for any 

one attributed patient in any one PY. 

Items that are communication devices 

must remain the property of the IOTA 

participant. An IOTA participant must 

retrieve the item that is a 

communication device either when the 

attributed patient is no longer eligible 

for the communication device or at the 

conclusion of the IOTA Model, 

whichever is earlier. Items that are 

communication devices must be 

retrieved from an attributed patient 

before another communication device 

may be provided to the same attributed 

patient. This restriction applies across 

PYs. In other words, an IOTA 

participant may not offer another 

communication device to the same 

attributed patient across all IOTA Model 

years until the first communication 

device has been retrieved. We believed 

these additional restrictions on 

communication devices that are offered 

under the attributed patient engagement 

incentive policy are necessary to ensure 

that IOTA participants are not providing 

communication devices for purposes 

that are not aligned with the goals of the 

IOTA Model. 

At § 512.458(d) of the proposed rule, 

we also proposed documentation 

requirements that pertain to the 

provision of attributed patient 

engagement incentives. The IOTA 

participant must maintain 

contemporaneous documentation of 

items and services furnished as 

attributed patient engagement 

incentives that includes, at minimum, 

the date an attributed patient 

engagement incentive is provided and 

the identity of the attributed patient to 


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341 Kwak, E.J., Kim, D.J., Choi, Y., Joo, D.J., & 

Park, W. (2020). Importance of oral health and 

dental treatment in organ transplant recipients. 

International Dental Journal, 70(6), 477–481. 

https://doi.org/10.1111/idj.12585. 

whom the item or service was provided. 

In accordance with the retrieval 

requirements for items that attributed 

patient engagement incentives, IOTA 

participants must document all retrieval 

attempts of items that are attributed 

patient engagement incentives, 

including the ultimate date of retrieval. 

IOTA participants must retain all 

records pertaining to the furnishing of 

attributed patient engagement 

incentives and make those records 

available to the Federal Government in 

accordance with section III.C.12. of this 

final rule. 

Taken together, we believed the 

safeguards described in this section are 

necessary to ensure that attributed 

patient engagement incentives offered 

by an IOTA participant are provided in 

compliance with the intent of the 

proposed policy and, if met, the Federal 

anti-kickback statute safe harbor for 

CMS-sponsored model patient 

incentives (§ 1001.952(ii)(2)) is available 

to protect these attributed patient 

engagement incentives. 

We considered not allowing IOTA 

participants to offer attributed patient 

engagement incentives for attributed 

patients in the IOTA Model, which 

would simplify the IOTA Model (89 FR 

43518). Further, having no attributed 

patient engagement incentive policy 

would allow IOTA participants to direct 

available resources to the proposed Part 

B and Part D immunosuppressive drug 

cost sharing support policy described in 

section III.C.11.g(1) of this final rule. We 

took these considerations into account; 

however, we believed allowing for the 

maximum amount of flexibility possible 

for IOTA participants to meet the needs 

of attributed patients that relate to 

accessing a kidney transplant is 

consistent with the model’s goals. In 

addition, we were unable to find any 

literature to suggest that one type of 

item or service, for example, cost 

sharing subsidies under Part B and Part 

D immunosuppressive drug cost sharing 

support, is of greater value to an 

individual waiting for a kidney 

transplant or having received a kidney 

transplant than another, for example, an 

attributed patient engagement incentive. 

We also considered including dental 

services as a service that may be offered 

as an attributed patient engagement 

incentive (89 FR 43518). Sources of oral 

infection must be resolved before an 

individual can receive a kidney 

transplant because post-transplant 

immunosuppression puts a kidney 

transplant recipient at greater risk for 

oral infections that can spread to the 

rest of the body.341 We did not include 

dental services as an allowable 

attributed patient engagement incentive 

because we understand that sources of 

oral infection must be resolved before 

an individual can be waitlisted for a 

kidney transplant; in other words, prior 

to the ability of an individual to be 

attributed to the IOTA Model. We were 

interested in receiving comments on the 

extent to which dental issues emerge 

once an individual has been listed for a 

kidney transplant and whether we 

should consider dental services as an 

attributed patient engagement incentive 

under the auspices of the IOTA Model. 

We solicited feedback on our proposal 

to allow IOTA participants to offer 

attributed patient engagement 

incentives in a manner that complies 

with the restrictions and safeguards in 

this section. We further solicited 

feedback on other barriers to remaining 

active on the kidney transplant waitlist, 

receiving organ offers, and adhering to 

pre- and post-transplant care that we 

may be able to address by expanding the 

attributed patient engagement 

incentives available to attributed 

patients through future rulemaking. 

The following is a summary of the 

comments received on our proposed 

provisions for attributed patient 

engagement incentives, and our 

responses: 

Comment: A few commenters 

expressed concern about the patient 

engagement incentives, as they would 

require significant planning and 

resources, and suggested that CMS 

should clarify whether coverage of 

dental services is included in the 

provision. 

Response: We thank the commenters 

for their feedback. We understand the 

concerns about the potential burdens 

these incentives may place on IOTA 

participants. IOTA participants can 

choose whether to offer these patient 

engagement incentives. As such, if the 

logistical challenges and financial 

burden for IOTA participants exceeds 

the benefits for the IOTA participants, 

then the benefit does not need to be 

provided. Our goal is to ensure that 

beneficiary incentives effectively 

support patient care without imposing 

unnecessary burdens on IOTA 

participants. 

We considered but did not ultimately 

include dental services as an allowable 

attributed patient engagement incentive 

because sources of oral infection must 

be resolved before an individual can be 

waitlisted for a kidney transplant; in 

other words, prior to the ability of an 

individual to be attributed to the IOTA 

Model. 

We are finalizing this policy as 

proposed. However, we appreciate these 

insights and will take them into account 

in future rulemaking cycles. 

Comment: Several commenters 

suggested the provision should also 

address health-related social needs 

(HRSNs) for patients on the waitlist and 

provide full living donor cost 

reimbursement including costs not 

covered by other payers, include 

mechanisms to help offset the cost of 

providing these incentives, and provide 

more flexibility. 

Response: We thank the commenters 

for their suggestion. As described and 

finalized in § 512.446(a) of this final 

rule, IOTA participants may voluntarily 

submit a health equity for all PYs of the 

IOTA Model. We direct readers to 

section III.C.8.c of this final rule for 

further discussion on health equity 

plans in the IOTA Model. We believe 

that these health equity plans address 

HRSNs for patients on the waitlist. If in 

the future CMS requires the collection 

of HRSN data from Medicare provider 

and suppliers more widely and 

strengthens the availability of HRSN 

data, we will consider if there is 

sufficient and high-quality HRSN data 

available in future baseline years as we 

consider potential future changes to the 

model design. 

Regarding living donor cost 

reimbursement, we note that Medicare 

or the kidney recipient’s private 

insurance will generally cover the 

medical costs of testing and surgery for 

a living kidney donor. We understand, 

however, that there are often costs that 

are not reimbursed, such as meals, 

lodging, and transportation costs. As 

discussed later in this section, we are 

not issuing any fraud and abuse waivers 

in this final rule. A model provision 

protecting such reimbursement could be 

susceptible to abuse by potentially 

impermissibly steering beneficiaries in 

their selection of kidney transplant 

hospitals so as to mitigate costs for their 

donors, disadvantaging smaller kidney 

transplant hospitals without resources 

to provide this remuneration, and 

incentivizing donation decisions. 

Comment: Several commenters 

suggested that CMS change the 

attributed patient engagement 

incentives to include additional services 

such as Medical Nutrition Therapy, 

dental coverage, and home phlebotomy 

and infusion services. 

Response: We thank the commenters 

for their suggestion. The suggested 

expansion of Medical Nutrition 


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342Section III.C.11.h did not appear in the notice 

of proposed rulemaking, and the general payment 

waivers were instead discussed in section III.C.11.i, 

which also addressed fraud and abuse waivers and 

OIG safe harbor authority. This section III.C.11.h 

has been added here to address the general payment 

waivers separately, as they are distinct from the 

fraud and abuse waivers. As we stated in the 

proposed rule, the general payment waivers are 

necessary to make the upside risk payments and 

downside risk payments under the IOTA model. 

The proposed regulatory text regarding the general 

payment waivers at § 512.470 is not changed. 

Therapy, home phlebotomy and 

infusion services was not included in 

the proposed rule, and we therefore are 

not finalizing these expansions 

suggested by the commenters in this 

final rule. We did not include dental 

services as an allowable attributed 

patient engagement incentive because 

we understand that sources of oral 

infection must be resolved before an 

individual can be waitlisted for a kidney 

transplant; in other words, prior to the 

ability of an individual to be attributed 

to the IOTA Model. 

We are finalizing this policy as 

proposed with one exception. The 

reference to section III.C.g(2) for the Part 

B and Part D immunosuppressive drug 

cost sharing support was incorrect. We 

clarify that the Part B and Part D 

immunosuppressive drug cost sharing 

support is described in section 

III.C.11.g(1) of this final rule. 

After consideration of the public 

comments received, we are finalizing 

our proposed provision for attributed 

patient engagement incentives, with a 

minor technical correction to update the 

section numbering in our regulation at 

§ 512.458. 

h. General Payment Waivers 342

We stated in the proposed rule that 

we would need to waive certain 

Medicare program regulations in order 

to make the upside risk payments and 

downside risk payments discussed in 

the proposed rule and in sections 

III.C.6.c.(2)(a) and III.C.6.c.(2)(b) of this 

final rule, respectively. 

Therefore, in accordance with the 

authority granted to the Secretary in 

section 1115A(d)(1) of the Act to waive 

certain requirements as may be 

necessary solely for purposes of testing 

models, and consistent with other 

mandatory models such as the ETC 

Model and the CJR Model, we proposed 

at 89 FR 43597 to waive requirements of 

section 1881(b) of the Act only to the 

extent necessary to make the upside risk 

payments and downside risk payments 

under the IOTA model. Section 1881(b) 

of the Act determines how Medicare 

FFS pays for services such as dialysis, 

transplantation, and home dialysis 

support services for individuals with 

ESRD. Waiving requirements of section 

1881(b) of the Act is necessary for the 

upside risk payments and downside risk 

payments to be made to or collected 

from the IOTA Participants. These 

model payments will be made in 

addition to, and not in lieu of, the 

Medicare FFS payments provided under 

section 1881(b) of the Act. 

We proposed to waive this 

requirement under section 1881(b) of 

the Act because these statutory 

provisions establish the current 

Medicare FFS payment methodology, 

which does not include the upside risk 

payments and downside risk payments. 

Without waiving these specific 

provisions of the Act to permit the 

upside risk payments and downside risk 

payments, we would not be able to 

implement and test whether the 

payment methodology of the model was 

effective at reducing program 

expenditures while preserving or 

enhancing the quality of care. 

We also proposed at 89 FR 43597 to 

waive sections 1833(a) and 1833(b) of 

the Act to the extent necessary to make 

payments under the IOTA Model. The 

purpose of this proposed waiver was to 

ensure that the upside risk payments 

and downside risk payments, as 

described in sections III.C.6.c.(2)(a) and 

III.C.6.c.(2)(b), respectively, in this final 

rule, would not alter the beneficiary 

cost-sharing requirements for the related 

Part B services received by IOTA 

participants. We did not propose to alter 

the existing Medicare beneficiary cost 

sharing structure, and this waiver would 

maintain that existing structure while 

enabling the upside risk payments and 

downside risk payments under the 

IOTA model. 

Therefore, we proposed to waive the 

requirements of sections 1881(b), 

1833(a), and 1833(b) of the Act to the 

extent necessary to make the payments 

we proposed under the IOTA Model (89 

FR 43597). We sought comment on our 

proposed waivers of Medicare payment 

requirements related to the upside risk 

payment and downside risk payment 

and beneficiary cost sharing. 

We received no public comments on 

these proposed waivers. As such, we are 

finalizing our proposal to waive sections 

1881(b), 1833(a) and 1833(b) of the Act 

only to the extent necessary to make 

payments under the IOTA Model at 

§ 512.470 without modification. 

i. Fraud and Abuse Waiver and OIG Safe 

Harbor Authority 

Under section 1115A(d)(1) of the Act, 

the Secretary may waive such 

requirements of Titles XI and XVIII and 

of sections 1902(a)(1), 1902(a)(13), 

1903(m)(2)(A)(iii) of the Act, and certain 

provisions of section 1934 of the Act as 

may be necessary solely for purposes of 

carrying out section 1115A of the Act 

with respect to testing models described 

in section 1115A(b) of the Act. 

For this model and consistent with 

the authority under section 1115A(d)(1) 

of the Act, the Secretary may consider 

issuing waivers of certain fraud and 

abuse provisions in sections 1128A, 

1128B, and 1877 of the Act. No fraud or 

abuse waivers are being issued in this 

document; fraud and abuse waivers, if 

any, would be set forth in separately 

issued documentation. Any such waiver 

would apply solely to the IOTA Model 

and could differ in scope or design from 

waivers granted for other programs or 

models. Thus, notwithstanding any 

provision of this final rule, IOTA 

participants and IOTA collaborators 

must comply with all applicable laws 

and regulations, except as explicitly 

provided in any such separately 

documented waiver issued pursuant to 

section 1115A(d)(1) of the Act 

specifically for the IOTA Model. 

In addition to or in lieu of a waiver 

of certain fraud and abuse provisions in 

sections 1128A and 1128B of the Act, at 

§ 512.470 of the proposed rule, CMS 

proposed to waive sections 1881(b) and 

1833(a) and 1833(b) of the Act only to 

the extent necessary to make certain 

payments under the IOTA Model. These 

waivers, while originally included in 

this section of the proposed rule, are 

general payment waivers and not fraud 

and abuse waivers. As such, this 

discussion has been moved to section 

III.C.11.h of this final rule. 

CMS has made a determination, in 

this final rule, that the Federal antikickback statute safe harbor for CMSsponsored model arrangements and 

CMS-sponsored model patient 

incentives (§ 1001.952(ii)(1) and (2)) is 

available to protect remuneration 

exchanged pursuant to certain financial 

arrangements and patient incentives 

that may be permitted under the final 

rule. Specifically, we determined that 

the CMS-sponsored models safe harbor 

would be available to protect the 

following financial arrangements and 

incentives: the IOTA Model Sharing 

Arrangement’s gainsharing payments 

and alignment payments, the 

Distribution Arrangement’s distribution 

payments, the Part B and Part D 

immunosuppressive drug cost sharing 

support policy and attributed patient 

engagement incentives. 

We considered not allowing use of the 

safe harbor provisions (89 FR 43518). 

However, we determined that use of the 

safe harbor would encourage the goals 

of the model. We believed that a 

successful model requires integration 


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and coordination among IOTA 

participants and other health care 

providers and suppliers. We believed 

the use of the safe harbor would 

encourage and improve beneficiary 

experience of care and coordination of 

care among providers and suppliers. We 

also believed the safe harbor offers 

flexibility for innovation and 

customization. The safe harbor allows 

for emerging arrangements that reflect 

up-to-date understandings in medicine, 

science, and technology. 

We sought comment on this proposal, 

including that the Federal anti-kickback 

statute safe harbor for CMS-sponsored 

model arrangements (§ 1001.952(ii)(1)) 

be available to IOTA participants and 

IOTA collaborators. 

The following is a summary of the 

public comments received on these 

proposals and our responses: 

Comment: A few commenters 

expressed support for the fraud and 

abuse provision, stating that the IOTA 

participants needed protections in place 

to form financial arrangements 

necessary for the model. 

Response: We thank the commenters 

for their support. 

After consideration of the public 

comments received, we are finalizing 

our proposed provision for application 

of the CMS-sponsored model 

arrangements and patient incentives 

safe harbor at § 512.459. 

12. Audit Rights and Record Retention 

By virtue of their participation in an 

Innovation Center model, IOTA 

participants and IOTA collaborators 

may receive model-specific payments, 

access to Medicare payment waivers, or 

some other model-specific flexibility, 

such as the ability to provide cost 

sharing support to eligible attributed 

patients for the proposed Part B and Part 

D immunosuppressive drug cost sharing 

support policy. It is therefore necessary 

and appropriate for CMS to audit, 

inspect, investigate, and evaluate 

records and other materials related to 

participation in the IOTA Model. CMS 

must be able to audit, inspect, 

investigate, and evaluate records and 

materials related to participation in the 

IOTA Model to allow us to ensure that 

IOTA participants are in no way 

denying or limiting the coverage or 

provision of benefits for beneficiaries as 

part of their participation in the IOTA 

Model. We proposed to define ‘‘modelspecific payment’’ to mean a payment 

made by CMS only to IOTA 

participants, or a payment adjustment 

made only to payments made to IOTA 

participants, under the terms of the 

IOTA Model that is not applicable to 

any other providers or suppliers; the 

term ‘‘model-specific payment’’ would 

include, unless otherwise specified, the 

model upside risk payment and 

downside risk payment, described in 

section III.C.6 of this final rule. It is 

necessary to propose this definition to 

distinguish payments and payment 

adjustments applicable to IOTA 

participants as part of their participation 

in the IOTA Model, from payments and 

payment adjustments applicable to 

IOTA participants as well as other 

providers and suppliers, as certain 

provisions of proposed part 512 would 

apply only to the former category of 

payments and payment adjustments. 

There are audit and record retention 

requirements under the Medicare 

Shared Savings Program (see 42 CFR 

425.314) and in other models being 

tested under section 1115A of the Act 

(see, for example, 42 CFR 510.110 and 

§ 512.135). 

We proposed to adopt audit and 

record retention requirements for the 

IOTA Model. Specifically, as a result of 

our proposal to revise the scope of the 

general provisions of 42 CFR part 512 

Subpart A to include the IOTA Model, 

see proposed 42 CFR 512.100, we 

proposed to apply § 512.135(a) through 

(c) to each IOTA participant and its 

IOTA collaborators. In applying 

§ 512.135(a) to the IOTA Model, the 

Federal Government, including, but not 

limited to, CMS, HHS, and the 

Comptroller General, or their designees, 

would have a right to audit, inspect, 

investigate, and evaluate any documents 

and other evidence regarding 

implementation of an Innovation Center 

model. In applying existing § 512.135(b) 

and (c) to the IOTA Model, an IOTA 

participant and its IOTA collaborators 

would be required to: 

• Maintain and give the Federal 

Government, including, but not limited 

to, CMS, HHS, and the Comptroller 

General, or their designees, access to all 

documents (including books, contracts, 

and records) and other evidence 

sufficient to enable the audit, 

evaluation, inspection, or investigation 

of the IOTA Model, including, without 

limitation, documents and other 

evidence regarding all of the following: 

++ Compliance by the IOTA 

participant and its IOTA collaborators 

with the terms of the IOTA Model, 

including proposed new subpart A of 

proposed part 512. 

++ The accuracy of model-specific 

payments made under the IOTA Model. 

++ The IOTA participant’s downside 

risk payments owed to CMS under the 

IOTA Model. 

++ Quality measure information and 

the quality of services performed under 

the terms of the IOTA Model, including 

proposed new subpart A of proposed 

part 512. 

++ Utilization of items and services 

furnished under the IOTA Model. 

++ The ability of the IOTA participant 

to bear the risk of potential losses and 

to repay any losses to CMS, as 

applicable. 

++ Where cost sharing support is 

furnished under the Part B and Part D 

immunosuppressive drug cost sharing 

support policy, the IOTA participant 

must maintain contemporaneous 

documentation that includes the 

identity of the eligible attributed patient 

to whom Part B and Part D 

immunosuppressive drug cost sharing 

support was provided, the date or dates 

on which Part B and Part D 

immunosuppressive drug cost sharing 

support was provided, and the amount 

or amounts of Part B and Part D 

immunosuppressive drug cost sharing 

support that was provided. 

++ Contemporaneous documentation 

of items and services furnished as 

attributed patient engagement 

incentives in accordance with § 512.458 

that includes, at minimum, the date the 

attributed patient engagement incentive 

is provided and the identity of the 

attributed patient to whom the item or 

service was provided. 

++ Patient safety. 

++ Any other program integrity 

issues. 

• Maintain the documents and other 

evidence for a period of 6 years from the 

last payment determination for the 

IOTA participant under the IOTA Model 

or from the date of completion of any 

audit, evaluation, inspection, or 

investigation, whichever is later, 

unless— 

++ CMS determines there is a special 

need to retain a particular record or 

group of records for a longer period and 

notifies the IOTA participant at least 30 

days before the normal disposition date; 

or 

++ There has been a termination, 

dispute, or allegation of fraud or similar 

fault against the IOTA participant or its 

IOTA collaborators, in which case the 

records must be maintained for an 

additional 6 years from the date of any 

resulting final resolution of the 

termination, dispute, or allegation of 

fraud or similar fault. 

If CMS notifies the IOTA participant 

of a special need to retain a record or 

group of records at least 30 days before 

the normal disposition date, the IOTA 

participant would be required to 

maintain the records for such period of 

time determined by CMS. If CMS 

notifies the IOTA participant of a 

special need to retain records or there 

has been a termination, dispute, or 


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allegation of fraud or similar fault 

against the IOTA participant or its IOTA 

collaborators, the IOTA participant 

would be required to notify its IOTA 

collaborators of the need to retain 

records for the additional period 

specified by CMS. This provision would 

ensure that the government has access 

to the records. 

We note that we previously adopted 

a rule at 42 CFR 512.110 defining the 

term ‘‘days,’’ as used in 42 CFR 512.135, 

to mean calendar days. 

We solicited public comment on these 

proposals regarding audits and record 

retention. 

The following is a summary of the 

comments received on our proposed 

provisions for auditing and record 

retention, and our responses: 

Comment: CMS received a comment 

asking to use HIPAA documentation 

retention standards. 

Response: We thank the commenter 

for this feedback. By applying 

§ 512.135(a) through (c), CMS ensures 

that IOTA participants are in no way 

denying or limiting the coverage or 

provision of benefits for beneficiaries as 

part of their participation in the IOTA 

Model. We believe that the current 

document retention time is reasonable. 

After consideration of the public 

comment we received, we are finalizing 

our proposal for Audit Rights and 

Record Retention as proposed at 

§ 512.460. We are also finalizing 

without modification the proposed 

definition of model-specific payment at 

§ 512.402. 

13. Compliance and Monitoring 

a. General 

We proposed in § 512.462 of the 

proposed rule that CMS, or its approved 

designees, would conduct compliance 

monitoring activities, to ensure 

compliance by the IOTA participant and 

IOTA collaborators with the terms of the 

IOTA Model, including to understand 

IOTA participants’ use of model-specific 

payments and to promote the safety of 

attributed patients and the integrity of 

the IOTA Model. Such monitoring 

activities would include, but not be 

limited to— 

• Documentation requests sent to the 

IOTA participant and its IOTA 

collaborators, including surveys and 

questionnaires; 

• Audits of claims data, quality 

measures, medical records, and other 

data from the IOTA participant and its 

IOTA collaborators; 

• Interviews with the IOTA 

participant, including leadership 

personnel, medical staff, other 

associates, and its IOTA collaborators; 

• Interviews with attributed patients 

and their caregivers; 

• Site visits to the IOTA participant 

and its IOTA collaborators, which 

would be performed in accordance with 

§ 512.462(c), described in section 

III.C.13.b of this final rule; 

• Monitoring quality outcomes and 

attributed patient data; 

• Tracking beneficiary complaints 

and appeals; 

• Monitoring the definition of and 

justification for the subpopulation of the 

IOTA participant’s eligible attributed 

patients that may receive Part B and Part 

D immunosuppressive drug cost sharing 

support in accordance with § 512.456; 

and 

• Monitoring the provision of 

attributed patient engagement 

incentives provided in accordance with 

§ 512.458. 

Additionally, CMS is concerned about 

IOTA participants bypassing the match 

run, as defined in section III.C.5.d(1)(a) 

of this final rule, the rank order list of 

transplant candidates to be offered an 

organ. This practice, known as ‘‘list 

diving,’’ can improve efficiency in 

placing organs, but may undermine the 

mechanisms promoting fairness in 

rationing this scarce resource, if 

overused. We proposed that CMS would 

monitor out of sequence allocation of 

kidneys by assessing how often topranked attributed patients receive the 

organ that was offered to them and if 

they did not receive it, what the reason 

for that was. 

We believe these specific monitoring 

activities, which align with those 

currently used in other models being 

tested by the Innovation Center, are 

necessary to ensure compliance with the 

terms of the IOTA Model and can 

protect attributed patients from 

potential harm that may result from the 

activities of the IOTA participant or its 

IOTA collaborators, such as attempts to 

reduce access to or the provision of 

medically necessary covered services. 

We proposed at § 512.462 of the 

proposed rule that when CMS is 

conducting compliance monitoring and 

oversight activities, CMS or its 

designees would be authorized to use 

any relevant data or information, 

including without limitation Medicare 

claims submitted for items or services 

furnished to attributed patients who are 

Medicare beneficiaries. We believe that 

it is necessary to have all relevant 

information available to CMS during 

compliance monitoring and oversight 

activities, including any information 

already available to CMS through the 

Medicare program. 

IOTA participants would remain 

subject to all existing requirements and 

conditions for Medicare participation as 

set out in Federal statutes and 

regulations and provider and supplier 

agreements, unless waived under the 

authority of section 1115A(d)(1) of the 

Act solely for purposes of testing the 

IOTA Model. 

b. Site Visits 

In § 512.462(c) of the proposed rule, 

we proposed that IOTA participants 

would be required to cooperate in 

periodic site visits conducted by CMS or 

its designee. Such site visits would be 

conducted to facilitate the model 

evaluation performed pursuant to 

section 1115A(b)(4) of the Act and to 

monitor compliance with the IOTA 

Model requirements. We further 

proposed that CMS or its designee 

would provide the IOTA participant 

with no less than 15 days advance 

notice of a site visit, to the extent 

practicable. Furthermore, we proposed 

that, to the extent practicable, CMS 

would attempt to accommodate a 

request that a site visit be conducted on 

a particular date, but that the IOTA 

participant would be prohibited from 

requesting a date that was more than 60 

days after the date of the initial site visit 

notice from CMS. We believe the 60-day 

period would reasonably accommodate 

IOTA participant schedules while not 

interfering with the operation of the 

IOTA Model. Further, in § 512.462 of 

the proposed rule, we proposed to 

require the IOTA participant to ensure 

that personnel with the appropriate 

responsibilities and knowledge 

pertaining to the purpose of the site visit 

be available during any and all site 

visits. We believe this proposal is 

necessary to ensure an effective site visit 

and prevent the need for unnecessary 

follow-up site visits. 

Further, we proposed in § 512.462 of 

the proposed rule that nothing in the 

previous sections would limit CMS from 

performing other site visits as allowed 

or required by applicable law. We 

believe that CMS must retain the ability 

to timely investigate concerns related to 

the health or safety of attributed patients 

or program integrity issues, and to 

perform functions required or 

authorized by law. In particular, we 

believe that it is necessary for CMS to 

monitor, and for IOTA participants to be 

compliant with our monitoring efforts, 

to ensure that they are not denying or 

limiting the coverage or provision of 

medically necessary covered services to 

attributed patients in an attempt to 

change model results or their modelspecific payments, including 

discrimination in the provision of 

services to at-risk patients (for example, 


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due to eligibility for Medicare based on 

disability). 

In the alternative, we considered 

allowing unannounced site visits for 

any reason. However, we determined 

that giving advanced notice for site 

visits for routine monitoring would 

allow the IOTA participant to ensure 

that the personnel with the applicable 

knowledge is available and would allow 

the IOTA participant the flexibility to 

arrange these site visits around their 

operations. However, we proposed in 

§ 512.462 of the proposed rule that if 

there is a concern regarding issues that 

may pose risks to the health or safety of 

attributed patients or to the integrity of 

the IOTA Model, unannounced site 

visits would be warranted. We believe 

this would allow us to address any 

potential concerns in a timely manner 

without a delay that may increase those 

potential risks. 

We direct readers to section III.C.13.c 

of this final rule for a summary of the 

comments received on our proposals 

regarding site visits and our responses. 

c. Reopening of Payment 

Determinations 

To protect the financial integrity of 

the IOTA Model, we proposed in 

§ 512.462(d) that if CMS discovers that 

it has made or receives a request from 

the IOTA participant about an incorrect 

model payment, CMS may make 

payment to, or demand payment from, 

the IOTA participant. 

CMS’ interests include ensuring the 

integrity and sustainability of the IOTA 

Model and the underlying Medicare 

program, from both a financial and 

policy perspective, as well as protecting 

the rights and interests of Medicare 

beneficiaries. For these reasons, CMS or 

its designee needs the ability to monitor 

IOTA participants to assess compliance 

with model terms and with other 

applicable Medicare program laws and 

policies. We believe our monitoring 

efforts help ensure that IOTA 

participants are furnishing medically 

necessary covered services and are not 

falsifying data, increasing program 

costs, or taking other actions that 

compromise the integrity of the IOTA 

Model or are not in the best interests of 

the IOTA Model, the Medicare program, 

or Medicare beneficiaries. 

We invited public comment on these 

proposed provisions regarding 

monitoring of the IOTA Model and 

alternatives considered. 

The following is a summary of the 

public comments received on these 

proposals and our responses: 

Comment: A few commenters 

expressed support for the monitoring 

measures proposed to ensure that IOTA 

participants comply with the model 

requirements and the program is 

improving patient care. 

Response: We thank the commenters 

for their support of this proposed 

policy. 

Comment: A few commenters 

indicated concern that the compliance 

monitoring provision will negatively 

impact smaller transplant programs, 

cause interruptions in the quality and 

continuity of patient care and create 

significant administrative burdens. 

Response: We understand the 

concerns facing smaller transplant 

programs; however, we disagree that the 

compliance monitoring provision will 

negatively impact smaller transplant 

programs. The IOTA Model’s 

compliance monitoring activities align 

with those currently used in other 

models being tested by the Innovation 

Center as well as those any hospital 

would have under Medicare. Ensuring 

the integrity and sustainability of the 

IOTA Model as well as promoting the 

safety and protection of attributed 

patients is the purpose of the 

compliance monitoring provision 

regardless of the size of the transplant 

hospital. 

Comment: We received a comment 

suggesting that the IOTA Model should 

establish a robust feedback mechanism 

that allows transplant hospitals and 

other stakeholders to provide ongoing 

input on the implementation and 

impact of the IOTA Model. The 

commenter believes that feedback 

would be crucial for adapting the model 

to real-world challenges and achieving 

its intended outcomes. 

Response: We appreciate the 

comment and plan to have transparent 

and ongoing communications with all 

the participants as the model progresses 

to achieve the intended outcomes. 

Comment: A commenter asked CMS 

to provide greater notice than 15 days 

prior to a site visit. 

Response: We appreciate the 

commenters’ feedback and support. As 

noted in the proposed rule, we believe 

that providing at least 15 days of notice 

before a site visit is sufficient. 

Furthermore, we proposed that, to the 

extent practicable, CMS would attempt 

to accommodate a request that a site 

visit be conducted on a particular date, 

but that the IOTA participant would be 

prohibited from requesting a date that 

was more than 60 days after the date of 

the initial site visit notice from CMS. 

We believe the 60-day period would 

reasonably accommodate IOTA 

participant schedules while not 

interfering with the operation of the 

IOTA Model. 

After consideration of the public 

comment we received, we are finalizing 

the proposed monitoring practices, 

compliance with laws, site visits, and 

reopening of payments policies at 

§ 512.462 with minor technical 

corrections to update cross references. 

Specifically, at § 512.462(d)(1) we are 

removing the cross reference to 

§ 512.462 and replacing it to reflect 

§ 405.986 of this chapter. At 

§ 512.462(d)(1), we are also removing 

the cross reference to § 512.464 and 

replacing it to reflect § 405.902 of this 

chapter. 

14. Evaluation 

Section 1115A(b)(4) of the Act 

requires the Secretary to evaluate each 

model tested under the authority of 

section 1115A of the Act and to publicly 

report the evaluation results in a timely 

manner. The evaluation must include an 

analysis of the quality of care furnished 

under the model and the changes in 

program spending that occurred due to 

the model. Models tested by the 

Innovation Center are rigorously 

evaluated. For example, when 

evaluating models tested under section 

1115A of the Act, we require the 

production of information that is 

representative of a wide and diverse 

group of model participants and 

includes data regarding potential 

unintended or undesirable effects. The 

Secretary must take the evaluation into 

account if making any determinations 

regarding the expansion of a model 

under section 1115A(c) of the Act. In 

addition to model evaluations, the 

Innovation Center regularly monitors 

model participants for compliance with 

model requirements. 

For the reasons described in section 

III.C.13 of this final rule, these 

compliance monitoring activities are an 

important and necessary part of the 

model test. Therefore, we note that 

IOTA participants and their IOTA 

collaborators must comply with the 

requirements of 42 CFR 403.1110(b) 

(regarding the obligation of entities 

participating in the testing of a model 

under section 1115A of the Act to report 

information necessary to monitor and 

evaluate the model), and must otherwise 

cooperate with CMS’ model evaluation 

and monitoring activities as may be 

necessary to enable CMS to evaluate the 

Innovation Center model in accordance 

with section 1115A(b)(4) of the Act. 

This participation in the evaluation may 

include, but is not limited to, 

responding to surveys and participating 

in focus groups. Subsequent to the 

publication of the proposed rule, we 

wish to clarify that the evaluation 


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343End Stage Renal Disease Treatment Choices 

Learning Collaborative—End Stage Renal Disease 

Treatment Choices Learning Collaborative— 

QualityNet Confluence. (n.d.). 

Qnetconfluence.cms.gov. Retrieved May 30, 2023, 

from https://qnetconfluence.cms.gov/display/ 

ETCLC/End+Stage+Renal+Disease+

Treatment+Choices+Learning+Collaborative. 

344 Ibid. 

activities may also include site visits 

and case studies. 

We received no comments on the 

proposed evaluation approach and 

therefore are finalizing this provision 

without modification. 

15. Learning 

In the Specialty Care Models final 

rule (85 FR 61114), we established the 

voluntary ETC Learning Collaborative 

(ETCLC). The goals of the ETCLC are to 

increase the supply and use of deceased 

donor kidneys by convening OPOs, 

transplant hospitals, donor hospitals, 

and patients and families to reduce the 

variation in OPO and transplant 

hospital performance and reduce kidney 

non-use.343 The ETCLC is addressing 

three national aims over a 5-year period: 

(1) achieve a 28 percent absolute 

increase in the number of deceased 

donor kidneys with a KDPI greater than 

or equal to 60 recovered for transplant 

from the 2021 OPTN/SRTR baseline of 

11,284; (2) decrease the current national 

non-use rate of all procured kidneys 

with a KDPI ≥ 60 by 20 percent; and (3) 

decrease the current national discard 

rate of all procured kidneys with a KDPI 

< 60 by 4 percent. The ETCLC has 

developed Quality Improvement (QI) 

Teams that are identifying and 

implementing best practices based on 

the ETCLC Kidney Donation and 

Utilization Change Package. As of June 

2023, 54 OPOs and 181 transplant 

hospitals were enrolled in ETCLC.344

While we considered continuing the 

ETCLC under the auspices of the IOTA 

Model in section III.C.15 of the 

proposed rule, we proposed to conclude 

the ETCLC at the end of the ETC Model 

test and implement a learning system 

specific to the IOTA Model. An IOTA 

Model learning system would deal only 

with issues specific to the IOTA Model 

and would have neither national aims 

nor include other providers in the 

transplant ecosystem such as OPOs or 

donor hospitals as regular participants. 

The advantages of this approach are that 

CMS could provide a forum for IOTA 

participants to discuss elements of the 

model, share experiences implementing 

IOTA Model provisions, and solicit 

support from peers in overcoming 

challenges that may arise. Since most 

transplant hospitals have less 

experience with Innovation Center 

models than other provider types, we 

believe an independent learning system 

would provide unique value to IOTA 

participants. 

In section III.C.15 of the proposed 

rule, we also considered continuing 

ETCLC under the aegis of the IOTA 

Model. We believed many IOTA 

participants would already be enrolled 

in the ETCLC and dedicating staff and 

time to participating in QI Teams and 

engaging with the Kidney Donation and 

Utilization Change Package. We also 

believed that there may be overlap 

between the QI work being undertaken 

by ETCLC participants and the issues 

that would be of interest to IOTA 

participants. We further considered 

whether the ETCLC needed more time 

to achieve its national aims that could 

be provided by continuing the ETCLC 

under the IOTA Model. 

We solicited feedback on our proposal 

to conclude the ETCLC with the ETC 

Model and implement a new learning 

system specific to the IOTA Model. We 

sought feedback on the following 

questions: 

• What are specific examples of how 

ETCLC is supporting transplant hospital 

QI to increase access to kidney 

transplant? 

• What features of a new learning 

system would be important for IOTA 

participants? 

• Could the ETCLC meet IOTA 

participants’ need for QI support to 

succeed in the model? 

The following is a summary of the 

comments received on our proposed 

learning system for the IOTA Model, our 

proposal to end the ETCLC at the 

completion of the ETC Model, feedback 

on the questions we posed in the 

proposed rule at 89 FR 43600, and our 

responses: 

Comment: A commenter was in favor 

of supporting the CMS proposal to 

develop an IOTA-specific learning 

system, instead of relying on the 

methods used by the ETCLC in the ETC 

Model. Additionally, a commenter 

supported finalizing the ETCLC with the 

ETC Model. 

Response: We appreciate the feedback 

and support for a learning system 

specific to the IOTA Model. We agree it 

is important to provide specialized 

support due to the importance of the 

subject matter and due to prior limited 

interaction transplant programs may 

have had with other Innovation Center 

models or alternative payment models. 

After consideration of the public 

comments we received, for the reasons 

set forth in this rule, we are finalizing 

a voluntary learning system focused on 

increasing kidney transplant access, as 

described in section III.C.15 of this final 

rule. This learning system will be 

independent of the ETCLC, which will 

conclude at the end of the ETC Model 

test. We intend for the learning system 

to support IOTA participants and IOTA 

collaborators throughout the model 

performance period. While we did not 

specifically include IOTA collaborators 

in the proposed rule, we believe it is 

important to allow IOTA collaborators 

to participate if they would like to due 

to their close relationship with and their 

contributions to IOTA participants and 

their performance. 

Additionally, we note that we did not 

receive any public comments regarding 

the questions we sought feedback on in 

the proposed rule at 89 FR 43600. 

16. Remedial Action and Termination 

a. Remedial Action 

At § 512.464 of the proposed rule, we 

proposed the Standard Provisions for 

Innovation Center Models relating to 

remedial actions, originally finalized as 

general provisions in the Code of 

Federal Regulations (42 CFR part 512 

subpart A) that applied to specific 

Innovation Center models but that we 

proposed for expansion to all 

Innovation Center Models with model 

performance periods that begin on or 

after January 1, 2025, in section II.B. of 

this final rule would apply to the IOTA 

Model. We proposed that CMS could 

impose one or more remedial actions on 

the IOTA participant if CMS determines 

that— 

• The IOTA participant has failed to 

furnish 11 or more transplants during 

the PY or any baseline years; 

• The IOTA participant or its IOTA 

collaborator has failed to comply with 

any of the terms of the IOTA Model; 

• The IOTA participant has failed to 

comply with transparency requirements 

as listed in section III.C.8.a. of this final 

rule; 

• The IOTA participant or its IOTA 

collaborator has failed to comply with 

any applicable Medicare program 

requirement, rule, or regulation; 

• The IOTA participant or its IOTA 

collaborator has taken any action that 

threatens the health or safety of an 

attributed patient; 

• The IOTA participant or its IOTA 

collaborator has submitted false data or 

made false representations, warranties, 

or certifications in connection with any 

aspect of the IOTA Model; 

• The IOTA participant or its IOTA 

collaborator has undergone a change in 

control, as described in section 

III.C.17.b of this final rule, that presents 

a program integrity risk; 

• The IOTA participant or its IOTA 

collaborator is subject to any sanctions 


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345At § 512.468(b)(2), we proposed that CMS may 

terminate an IOTA participant from the IOTA 

Model if the IOTA participant undergoes a change 

of an accrediting organization or a 

Federal, State, or local government 

agency; 

• The IOTA participant or its IOTA 

collaborator is subject to investigation or 

action by HHS (including the HHS–OIG 

or CMS) or the Department of Justice 

due to an allegation of fraud or 

significant misconduct, including being 

subject to the filing of a complaint or 

filing of a criminal charge, being subject 

to an indictment, being named as a 

defendant in a False Claims Act qui tam 

matter in which the Federal 

Government has intervened, or similar 

action; 

• The IOTA participant or its IOTA 

collaborator has failed to demonstrate 

improved performance following any 

remedial action imposed by CMS; or 

• The IOTA participant has misused 

or disclosed beneficiary-identifiable 

data in a manner that violates any 

applicable statutory or regulatory 

requirements or that is otherwise noncompliant with the provisions of the 

applicable data sharing agreement. 

At § 512.464 of the proposed rule, we 

proposed that CMS may take one or 

more of the following remedial actions 

if CMS determines that one or more of 

the grounds for remedial action 

described in section III.C.16.a. of this 

final rule has taken place: 

• Notify the IOTA participant and, if 

appropriate, require the IOTA 

participant to notify its IOTA 

collaborators of the violation; 

• Require the IOTA participant to 

provide additional information to CMS 

or its designees; 

• Subject the IOTA participant to 

additional monitoring, auditing, or both; 

• Prohibit the IOTA participant from 

distributing model-specific payments, as 

applicable; 

• Require the IOTA participant to 

terminate, immediately or by a deadline 

specified by CMS, its sharing 

arrangement with an IOTA collaborator 

with respect to the IOTA Model; 

• Terminate the IOTA participant 

from the IOTA Model; 

• Suspend or terminate the ability of 

the IOTA participant to provide Part B 

and Part D immunosuppressive drug 

cost sharing support, or attributed 

patient engagement incentives in 

accordance with sections III.C.11.g(1) 

and (2) of this final rule. 

• Require the IOTA participant to 

submit a corrective action plan (CAP) in 

a form and manner and by a deadline 

specified by CMS; 

• Discontinue the provision of data 

sharing and reports to the IOTA 

participant; 

• Recoup model-specific payments; 

• Reduce or eliminate a modelspecific payment otherwise owed to the 

IOTA participant, as applicable; or 

• Such other action as may be 

permitted under the terms of the IOTA 

Model. 

As part of the Innovation Center’s 

monitoring and assessment of the 

impact of models tested under the 

authority of section 1115A of the Act, 

CMS has a special interest in ensuring 

that these model tests do not interfere 

with the program integrity interests of 

the Medicare program. For this reason, 

CMS monitors actions of IOTA 

participants for compliance with model 

terms, as well as other Medicare 

program rules. When CMS becomes 

aware of noncompliance with these 

requirements, it is necessary for CMS to 

have the ability to impose certain 

administrative remedial actions on a 

noncompliant model participant. 

In the alternative, we considered a 

policy where the IOTA participant 

would remain in the IOTA Model 

regardless of any noncompliance. 

However, if there are circumstances in 

which the IOTA participant has 

engaged, or is engaged in, egregious 

actions, we proposed that CMS may 

terminate the IOTA participant, as 

further described in section III.C.16.b. of 

this final rule. In addition, we 

considered allowing IOTA participants 

access to their data and reports 

regardless of their compliance with the 

requirements of the IOTA Model, 

however, we proposed to discontinue 

data sharing and reports as a potential 

remedial action if there are grounds for 

doing so. 

We sought comment on these 

proposed provisions regarding the 

proposed grounds for remedial actions, 

remedial actions generally, and whether 

additional types of remedial action 

would be appropriate. 

The following is a summary of the 

public comments received on these 

proposals and our responses: 

Comment: A few commenters 

expressed support for the IOTA Model 

grounds for remedial action and types of 

remedial action. 

Response: We thank commenters for 

their feedback and support. 

Comment: A commenter suggested 

that modest penalties for opting out of 

the IOTA Model could be bypassed in 

an economically rational way and 

ultimately threaten efforts to accurately 

assess the model. 

Response: Participation in the IOTA 

Model is mandatory, so a participant 

cannot opt out. If a participant does not 

comply with the participation 

requirements of the IOTA Model, there 

will be remedial actions, which could 

include reducing or eliminating model 

specific payments or discontinuing data 

sharing and reports. 

Comment: A commenter suggested 

that CMS should remove the risk that a 

program failing to meet the HEP 

requirements are subject to remedial 

action. 

Response: We are no longer requiring 

health equity plans so participants will 

not be subject to remedial action for not 

submitting a plan. 

After consideration of the public 

comments, for the reasons set forth in 

this final rule, we are finalizing our 

proposal on remedial actions as 

proposed at § 512.464 with a slight 

modification to update language to 

accurately reflect what we proposed at 

89 FR 43618. Specifically, we are 

modifying the regulatory text at 

§ 512.464(a)(1) to specify that CMS may 

impose remedial actions if CMS 

determines that the IOTA participant 

has failed to furnish 11 or more kidney 

transplants for patients aged 18 years or 

older, regardless of payer, during a PY 

or any baseline years. 

b. Termination of IOTA participant 

From the IOTA Model by CMS 

At proposed § 512.466(a), we 

proposed that CMS may immediately or 

with advance notice terminate an IOTA 

participant from participation in the 

IOTA Model if: 

• CMS determines that it no longer 

has the funds to support the IOTA 

Model; 

• CMS modifies or terminates the 

model pursuant to section 

1115A(b)(3)(B) of the Act; 

• CMS determines that the IOTA 

participant— 

++ Has failed to comply with any 

model requirement or any other 

Medicare program requirement, rule, or 

regulation; 

++ Has failed to comply with a 

monitoring or auditing plan or both; 

++ Has failed to submit, obtain 

approval for, implement or fully comply 

with the terms of a CAP; 

++Has failed to demonstrate improved 

performance following any remedial 

action; 

++ Has taken any action that threatens 

the health or safety of a Medicare 

beneficiary or other patient; 

++Has submitted false data or made 

false representations, warranties, or 

certifications in connection with any 

aspect of the IOTA Model; 

++ Has undergone a change in 

control; 345 or 


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of control. For consistency, in this final rule, we 

have added a corresponding provision at 

§ 512.466(a)(3)(vii). 

++ Assigns or purports to assign any 

of the rights or obligations under the 

model, voluntarily or involuntarily, 

whether by merger, consolidation, 

dissolution, operation of law, or any 

other manner, without the written 

consent of CMS. 

• Poses significant program integrity 

risks, including but not limited to: 

++ Is subject to sanctions or other 

actions of an accrediting organization or 

a Federal, State, or local government 

agency; or 

++ Is subject to investigation or action 

by HHS (including OIG or CMS) or the 

Department of Justice due to an 

allegation of fraud or significant 

misconduct, including being subject to 

the filing of a complaint, filing of a 

criminal charge, being subject to an 

indictment, being named as a defendant 

in a False Claims Act qui tam matter in 

which the government has intervened, 

or similar action. 

We requested comment and feedback 

on the proposal for termination of an 

IOTA participant from participating in 

the IOTA Model. 

The following is a summary of the 

public comments received on these 

proposals and our responses: 

Comment: A few commenters 

expressed concern that the termination 

provision may allow transplant 

programs not interested in the model to 

simply accept a fine and exit the model 

and offers no downside to enrolled 

participants. 

Response: Participation in the IOTA 

Model is mandatory, so a participant 

cannot exit the model. There are 

downside consequences if a participant 

does not comply with the requirements 

of the IOTA Model, such as remedial 

actions, which could include reducing 

or eliminating model specific payments 

or discontinuing data sharing and 

reports. The participant would not be 

able to accept a fine and exit the model, 

but rather negative financial 

consequences would be imposed, and 

continue to be imposed in subsequent 

Performance Years, on the participant. 

The participant would also be required 

to continue its participation in the IOTA 

Model. 

After considering public comments, 

for the reasons set forth in this rule, we 

are finalizing our policy for termination 

of an IOTA participant from the IOTA 

Model by CMS as proposed in our 

regulation at § 512.466(a), with slight 

modifications. Specifically, we are 

redesignating what was proposed at 

§ 512.466(a)(3)(vii) to be 

§ 512.466(a)(3)(viii). We are also 

redesignating what was proposed at 

§ 512.466(a)(3)(viii) to be 

§ 512.466(a)(3)(ix). Lastly, at 

§ 512.468(b)(2), we proposed that CMS 

may terminate an IOTA participant from 

the IOTA Model if the IOTA participant 

undergoes a change of control. As such, 

we have added a corresponding 

provision at § 512.466(a)(3)(vii), which 

allows for termination for a change in 

control consistent with § 512.468(b)(2). 

c. Termination of Model Participation 

by IOTA Participant 

Given the mandatory nature of this 

model, we proposed at § 512.466(b) of 

the proposed rule that an IOTA 

participant would not be able to 

terminate its own participation in the 

model. Maintaining a cohort of 

participants as close to 50 percent of 

eligible kidney transplant hospitals 

across the country is critical to 

evaluation of the IOTA Model. As such, 

while we proposed CMS may terminate 

an IOTA participant for reasons such as 

failure to meet eligibility criteria or 

change in kidney transplant hospital 

status, as described in section III.C.16.b. 

of this final rule, we did not propose 

voluntary termination by the IOTA 

participant. 

We considered allowing an IOTA 

participant to voluntarily terminate 

their participation in the model; 

however, we felt this went against the 

mandatory nature of the model and 

jeopardized our ability to evaluate 

model success and savings. 

We solicited comment and feedback 

on our proposal not to allow IOTA 

participants to terminate their 

participation in the IOTA Model. 

The following is a summary of the 

public comments received on these 

proposals and our responses: 

Comment: A commenter shared their 

support for not allowing participants to 

terminate themselves from the model. 

Response: We appreciate your 

feedback and support. 

After considering public comments, 

we are finalizing our policy for 

termination of model participation by 

IOTA participant as proposed in our 

regulation at § 512.466(b). 

d. Financial Settlement Upon 

Termination 

In section III.C.16.d of the proposed 

rule, we proposed that if CMS 

terminates the IOTA participant’s 

participation in the IOTA Model or CMS 

terminates the IOTA Model, CMS would 

calculate the final performance score 

and any upside risk payment or 

downside risk payment, if applicable, 

for the entire PY in which the IOTA 

participant’s participation in the model 

or the IOTA Model was terminated. 

We proposed that if CMS terminates 

an IOTA participant for any reason 

listed in section III.C.16.b of this final 

rule, CMS shall not make any payments 

of upside risk payment for the PY in 

which the IOTA participant was 

terminated, and the IOTA participant 

shall remain liable for payment of any 

downside risk payment up to and 

including the PY in which termination 

becomes effective (89 FR 43602). We 

proposed that CMS would determine 

the IOTA participant’s effective date of 

termination. 

We considered that in the event of 

termination, CMS would not pay any 

upside risk payments for the year in 

which the IOTA participant was 

terminated, but also only keep the IOTA 

participant liable for paying CMS any 

downside risk payments for completed 

PYs and not the year in which the IOTA 

participant is terminated (89 FR 43602). 

However, to deter poor or noncompliant performance, we believe it 

necessary to also keep the IOTA 

participant liable for paying to CMS any 

downside risk payment for the PY in 

which the IOTA participant is 

terminated. 

We solicited comment on this 

proposal and alternative considered. 

We received no comments on our 

proposed financial settlement upon 

termination policies and therefore are 

finalizing these proposals at § 512.466(c) 

without modification. 

e. Termination of the IOTA Model 

In the proposed rule, we proposed 

that the general provisions relating to 

termination of the model by CMS in 42 

CFR 512.165 would apply to the IOTA 

Model (89 FR 43602). Consistent with 

these provisions, in the event we 

terminate the IOTA Model, we would 

provide written notice to IOTA 

participants specifying the grounds for 

termination and the effective date of 

such termination. As provided by 

section 1115A(d)(2) of the Act and 

§ 512.170(e), termination of the model 

under section 1115A(b)(3)(B) of the Act 

would not be subject to administrative 

or judicial review. We proposed that in 

the event of termination of the model, 

financial settlement terms would be the 

same as those set forth in section 

III.C.16.d. of this final rule. 

We solicited public comment on these 

proposals regarding termination of the 

IOTA Model. 

We received no comments on the 

proposed policies for termination of the 

IOTA Model, and therefore are 

finalizing these proposals with slight 

modification at § 512.466(d) to clarify 


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that, as stated in this section and in the 

proposed rule at 89 FR 43602, 

termination of the IOTA Model under 

section 1115A(b)(3)(B) of the Act is not 

subject to administrative or judicial 

review. 

17. Miscellaneous Provisions on 

Bankruptcy and Other Notifications 

a. Notice of Bankruptcy 

In the proposed rule, we proposed 

that if an IOTA participant has filed a 

bankruptcy petition, whether voluntary 

or involuntary, the IOTA participant 

must provide written notice of the 

bankruptcy to CMS and to the U.S. 

Attorney’s Office in the district where 

the bankruptcy was filed, unless final 

payment has been made by either CMS 

or the IOTA participant under the terms 

of each model tested under section 

1115A of the Act in which the IOTA 

participant is participating or has 

participated and all administrative or 

judicial review proceedings relating to 

any payments under such models have 

been fully and finally resolved (89 FR 

43602). We proposed the notice of 

bankruptcy must be sent by certified 

mail no later than 5 days after the 

petition has been filed and must contain 

a copy of the filed bankruptcy petition 

(including its docket number), and a list 

of all models tested under section 

1115A of the Act in which the IOTA 

participant is participating or has 

participated. This list would not need to 

identify a model tested under section 

1115A of the Act in which the IOTA 

participant participated if final payment 

has been made under the terms of the 

model and all administrative or judicial 

review proceedings regarding modelspecific payments between the IOTA 

participant and CMS have been fully 

and finally resolved with respect to that 

model. The notice to CMS would be 

addressed to the CMS Office of 

Financial Management, Mailstop C3– 

01–24, 7500 Security Boulevard, 

Baltimore, Maryland 21244 or to such 

other address as may be specified on the 

CMS website for purposes of receiving 

such notices. 

We received no comments on these 

proposals and therefore are finalizing 

these provisions at § 512.468(a), without 

modification. 

b. Change in Control 

We proposed that CMS could 

terminate an IOTA participant from the 

model if the IOTA participant 

undergoes a change in control. We 

proposed that the IOTA participant 

shall provide written notice to CMS at 

least 90 days before the effective date of 

any change in control. For purposes of 

this rule, we proposed a ‘‘change in 

control’’ would mean at least one of the 

following: (1) the acquisition by any 

‘‘person’’ (as such term is used in 

Sections 13(d) and 14(d) of the 

Securities Exchange Act of 1934) of 

beneficial ownership (within the 

meaning of Rule 13d–3 promulgated 

under the Securities Exchange Act of 

1934), directly or indirectly, of voting 

securities of the IOTA participant 

representing more than 50 percent of the 

IOTA participant’s outstanding voting 

securities or rights to acquire such 

securities; (2) the acquisition of the 

IOTA participant by any individual or 

entity; (3) any merger, division, 

dissolution, or expansion of the IOTA 

participant (4) the sale, lease, exchange 

or other transfer (in one transaction or 

a series of transactions) of all or 

substantially all of the assets of the 

IOTA participant; or (5) the approval 

and completion of a plan of liquidation 

of the IOTA participant, or an agreement 

for the sale or liquidation of the IOTA 

participant. 

We received no comments on these 

proposals and therefore are finalizing 

these provisions at § 512.468(b) as 

proposed, with a slight modification to 

include a cross-reference to § 512.466 at 

§ 512.468(b)(2). We are also finalizing 

without modification the proposed 

definition of change in control at 

§ 512.402. 

c. Prohibition on Assignment 

We proposed that except with the 

prior written consent of CMS, an IOTA 

participant shall not transfer, including 

by merger (whether the IOTA 

participant is the surviving or 

disappearing entity), consolidation, 

dissolution, or otherwise: (1) any 

discretion granted it under the model; 

(2) any right that it has to satisfy a 

condition under the model; (3) any 

remedy that it has under the model; or 

(4) any obligation imposed on it under 

the model. We proposed that the IOTA 

participant provide CMS 90 days 

advance written notice of any such 

proposed transfer. We proposed this 

obligation remains in effect after the 

expiration or termination of the model 

or the IOTA participant’s participation 

in the model and until final payment by 

the IOTA participant under the model 

has been made. We proposed CMS may 

condition its consent to such transfer on 

full or partial reconciliation of upside 

risk payments and downside risk 

payments. We proposed that any 

purported transfer in violation of this 

requirement is voidable at the discretion 

of CMS. 

We received no comments on these 

proposals and therefore we are 

finalizing these provisions, as proposed 

without modification, at § 512.468(c). 

D. Requests for Information (RFIs) on 

Topics Relevant to the IOTA Model 

In the proposed rule (89 FR 43603), 

we sought input on several requests for 

information (RFIs). 

1. Patient-Reported Outcome 

Performance Measures (PRO–PM) 

In the proposed rule (89 FR 43603), 

we sought comment on the potential use 

of patient-reported outcome 

performance measures in the IOTA 

Model. Specifically, we sought feedback 

on the following questions: 

• For a meaningful evaluation of 

transplant program outcomes from the 

recipient point of view, are there 

currently any validated PROMs of 

quality of life that are appropriate for 

use in the IOTA Model? 

• Are there specific aspects of quality 

of life (QOL) that are particularly 

important to include for these 

populations? Why are these aspect(s) of 

QOL a high priority for inclusion in a 

survey? What should these metrics be 

(that is, measurement tools, 

instruments, concepts)? How should 

they be measured? 

• For kidney transplant recipients: 

What other topic area(s) should be 

included in a new patient-reported 

outcome measure or performance 

measure assessing quality of life? 

• For kidney transplant recipients: 

What domains of HRQOL can be 

influenced or improved by actions taken 

by transplant hospital and thus may be 

appropriate for performance 

measurement? 

In addition, we sought input on the 

questions later in this section on 

existing PROMs and quality measures 

that are currently being used by 

transplant hospitals. 

• Which patient-reported outcomes 

measure(s) that assess quality of life in 

kidney transplant recipients are 

currently being used? 

++ What information is collected in 

these PROMs? How well do these 

surveys perform? What are the strengths 

of the survey(s) currently in use? 

++ What content area(s) are missing 

from these survey(s) that are currently 

in use? 

++ Which content area(s) are low 

priority or not useful in these currently 

used survey(s)? Why are they not 

useful? 

++ How are the results and findings 

of these current survey(s) used to 

evaluate and improve quality of life/ 

care? Are the results and findings of 

these current survey(s) used for other 

purposes? 


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346Organ Procurement and Transplantation 

Network. Kidney Donor Profile Index (KDPI) Guide 

for Clinicians. https://optn.transplant.hrsa.gov/ 

professionals/by-topic/guidance/kidney-donorprofile-index-kdpi-guide-for-clinicians/; United 

States Renal Data System. 2022. USRDS Annual 

Report. Volume 2. End-stage Renal Disease (ESRD) 

in the United States, Chapter 9: Healthcare 

Expenditures for Persons with ESRD. Figure 9.11. 

347 King, K.L., Husain, S.A., Schold, J.D., Patzer, 

R.E., Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., 

Pastan, S.O., & Mohan, S. (2020). Major Variation 

across Local Transplant Centers in Probability of 

Kidney Transplant for Wait-Listed Patients. Journal 

of the American Society of Nephrology, 31(12), 

2900–2911. https://doi.org/10.1681/ 

ASN.2020030335. 

• Are there any other PROMs or 

PRO–PMs that CMS should consider 

using to measure a transplant program’s 

performance? 

• Are there any other quality 

measures in general that CMS should 

consider using to measure a transplant 

program’s performance? 

• For transplant hospitals: Can PROs 

be effectively used to assess 

performance? 

• For transplant hospitals: Does a 

reporting requirement effectively 

incentivize a transplant hospital to 

improve patient quality of life without 

tying payment to performance? 

• When is the appropriate time to 

measure HRQOL post-transplantation? 

• For transplant hospitals: What, if 

any, challenge(s) are there to collecting 

information about patient quality of life? 

• For kidney transplant recipients: 

What, if any, challenge(s) are there to 

reporting information about patient 

quality of life? 

• For transplant hospitals: What 

actions or approaches by transplant 

hospitals would facilitate the collection 

of quality-of-life information? 

++ What data collection approach(es) 

would be most likely to promote 

participation by transplant recipients to 

a survey (for example, web-based, 

paper-and-pencil, etc.)? 

++ How much time would transplant 

hospitals need to build processes to 

collect and use data in a meaningful 

way? 

• For transplant hospitals: How could 

CMS support transplant hospitals in 

introducing a measure like this into the 

model? 

While we are not be responding to 

specific comments submitted in 

response to this RFI, we intend to use 

this input to inform any future quality 

measure efforts. 

2. Access to Waitlist Measure 

In the proposed rule (89 FR 43604), 

we sought comment on the potential use 

of an access to waitlist measure in the 

IOTA Model. Specifically, we sought 

feedback on the following questions: 

• For kidney transplant hospitals: 

What existing measures are currently 

being used to measure access to the 

waitlist? 

++ What are the strengths and 

weaknesses of those measures? 

++ What are the domains of those 

measures? 

• For kidney transplant recipients 

and dialysis and ESRD patients: Why is 

a quality measure that looks at access to 

waitlist important to include? 

• When measuring access to waitlist, 

what components should be analyzed 

(for example, time from referral to 

waitlist, time from waitlist to 

transplant)? 

• What data would be necessary to 

create a measure on those specified 

components? How could that data be 

transmitted to CMS that minimizes 

additional burden to transplant 

hospitals? 

• What data would be necessary to 

create a measure of time to referral to 

waitlist, time from referral to waitlist 

and time from waitlist to transplant? 

How could that data be transmitted to 

CMS that reduces burden to transplant 

hospitals? 

While we are not be responding to 

specific comments submitted in 

response to this RFI, we intend to use 

this input to inform any future quality 

measure efforts. 

3. Interoperability 

In the proposed rule (89 FR 43605), 

we sought comment on interoperability 

requirements in the IOTA Model. 

Specifically, we sought comment on 

how CMS can promote interoperability 

in the proposed IOTA Model; in 

particular, we sought comment on the 

extent to which participants are 

planning on participating in the Trusted 

Exchange Framework and Common 

Agreement (TEFCA) in the next 1–2 

years, as well as other means by which 

interoperability may support care 

coordination in the IOTA Model. We 

noted that any further proposals related 

to interoperability in the IOTA Model 

would be proposed through future 

notice and comment rulemaking. 

We received no comments on this 

RFI. 

IV. Collection of Information 

Requirements 

The Standard Provisions for 

Innovation Center Models and the 

Increasing Organ Transplant Access 

(IOTA) Model would be implemented 

and tested under the authority of the 

CMS Innovation Center. Section 1115A 

of the Act authorizes the CMS 

Innovation Center to test innovative 

payment and service delivery models 

that preserve or enhance the quality of 

care furnished to Medicare, Medicaid, 

and Children’s Health Insurance 

Program beneficiaries while reducing 

program expenditures. As stated in 

section 1115A(d)(3) of the Act, Chapter 

35 of title 44, United States Code, shall 

not apply to the testing and evaluation 

of models under section 1115A of the 

Act. As a result, the information 

collection requirements contained in 

this final rule would need not be 

reviewed by the Office of Management 

and Budget. 

V. Regulatory Impact Analysis 

A. Statement of Need 

The best treatment for most patients 

with kidney failure is transplantation. 

Kidney transplants provide improved 

survival and quality of life relative to 

dialysis and generates savings to the 

Medicare Trust Fund over 10 years, but 

only 30 percent of patients with endstage renal disease (ESRD) are living 

with one.346 The underutilization of 

kidney transplantation is particularly 

prominent among structurally 

disadvantaged populations. The kidney 

transplant process involves silos of care, 

gaps in accountability, disparities, and 

misaligned financial incentives that we 

believe value-based care incentives are 

well positioned to target.347

The IOTA Model will be a mandatory 

payment model, beginning on July 1, 

2025, and ending June 30, 2031, that 

tests whether upside and downside 

performance-based payments (‘‘upside 

risk payments’’ and ‘‘downside risk 

payments’’) increase the number of 

kidney transplants performed by select 

IOTA participants (that is, transplant 

hospitals). Performance would be 

measured across three domains: (1) 

Achievement; (2) Efficiency; and (3) 

Quality. The achievement domain 

would assess each selected IOTA 

participant on the overall number of 

kidney transplants performed relative to 

a participant-specific target. The 

efficiency domain would assess the 

kidney organ offer acceptance rates of 

each selected IOTA participant relative 

to a national rate. The quality domain 

would assess the quality of care 

provided by the selected IOTA 

participant based on the composite graft 

survival rate. Each selected IOTA 

participant’s performance score across 

these three domains would determine 

the amount of the performance-based 

payment that CMS would pay to the 

selected IOTA participant, or that the 

selected IOTA participant would pay to 

CMS. The upside risk payment would 

be a lump sum payment paid by CMS 

to the selected IOTA participants with 


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348Organ Procurement and Transplant Network/ 

Scientific Registry of Transplant (OPTN/SRTR). 

‘‘OPTN/SRTR YYYY Annual Data Report: Kidney. 

Supplemental Data Tables.’’ Where YYYY is for 

report years 2015, 2018, 2019, 2020, and 2021. 

https://www.srtr.org/reports/optnsrtr-annual-datareport/. 

349HHS. 2023. ‘‘HRSA Announces Organ 

Procurement and Transplantation Network 

Modernization Initiative.’’ https://www.hhs.gov/ 

about/news/2023/03/22/hrsa-announces-organprocurement-transplantation-networkmodernization-initiative.html. 

350CMS. 2022. ‘‘Medicare Program; Implementing 

Certain Provisions of the Consolidated 

Appropriations Act, 2021 and Other Revisions to 

Medicare Enrollment and Eligibility Rules. Final 

Rule.’’ Federal Register 87 FR 66454: 66454–66511. 351Hariharan S, Irani AK, Danovitch G (2023). 

‘‘Long-Term Survival after Kidney 

Transplantation.’’ New England Journal of 

Medicine. 385:729–43. https://www.nejm.org/doi/ 

full/10.1056/NEJMra2014530. 

high final performance scores. 

Conversely, the downside risk payment 

would be a lump sum payment paid to 

CMS by the selected IOTA participants 

with low final performance scores. 

1. Analytic Baseline 

Historical data for the analytic 

baseline are from the Organ 

Procurement and Transplant Network/ 

Scientific Registry of Transplant 

Recipients (OPTN/SRTR).348 There were 

24,667 total adult kidney transplants in 

the United States in 2021, with a growth 

rate of 7.3 percent from 2020 to 2021. 

Similarly, the 5-year compound annual 

growth rate (CAGR) for the prepandemic years of 2015–2019 was 7.1 

percent. The majority, 86.7 percent, of 

adult kidney transplants were from 

deceased donors in 2021. The trend in 

growth for deceased donor kidney 

transplants has been steadily increasing 

since the revision of the kidney 

allocation system in 2014, while the 

trend in growth for living donor kidney 

transplants has been relatively stable. 

The number of adult deceased donor 

kidney transplants increased 5.7 percent 

from 2020 to 2021, a slowdown from the 

2015–2019 CAGR of 7.8 percent. 

Among the 18,931 adult deceased 

donor kidney transplant recipients in 

2021, 64.7 percent reported Medicare as 

their primary payer (stable from 64.8 

percent in 2020) and 24.0 percent 

reported private insurance as their 

primary payer (down from 25.7 percent 

in 2020). Deceased donor kidney 

transplant recipients had 2015–2019 

CAGR of 6.9 percent for Medicare as 

their primary payer and 11.6 percent for 

private insurance as their primary 

payer. The age distribution of the 18,931 

adult deceased donor kidney transplant 

recipients in 2021 showed that the 

majority of recipients are younger than 

the aged Medicare population. 

Specifically, 11.5 percent of recipients 

were ages 18–34 years, 26.1 percent 

were ages 35–49 years, 40.5 percent 

were ages 50–64 years, and 21.9 percent 

were at least 65 years of age at the time 

of transplant. The 2015–2019 CAGR was 

greatest for the two latter age categories, 

at 9.3 percent and 14.4 percent for ages 

50–64 years and 65+ years, respectively. 

The supply of donated kidneys has 

not grown with the demand from kidney 

transplant recipient candidates. There 

were a total of 96,130 adult kidney 

transplant candidates on the transplant 

waitlist at the end of the year in 2021, 

which included 41,765 newly added 

candidates. The number of newly added 

adult candidates to the waitlist 

increased 11.7 percent from 2020 to 

2021, recovering from the pandemicrelated decline in the prior year, and 

exceeding the 2015 to 2019 CAGR of 9.2 

percent. 

For the model, we assumed an 

average of $40,000 in savings to 

Medicare over a 10-year period for each 

additional kidney transplant furnished 

to a Medicare beneficiary compared to 

remaining on dialysis. For the 50 

percent of IOTA participants proposed 

to be randomly selected to participate in 

the model, we assume that the total 

number of kidney transplants from all 

payers over the 6-year model 

performance period would have a CAGR 

of 6.6 percent in the absence of the 

model (for example, if the rule is not 

finalized). We also assume that the 6- 

year model performance period CAGR 

for the total number of kidney 

transplants furnished to beneficiaries 

with Medicare as the primary payer 

would be 7.0 percent. The baseline 

share of deceased donor kidneys that are 

currently discarded is roughly 20 

percent. If the IOTA Model were not 

implemented, then IOTA participants 

would not have the performance-based 

upside and downside risk payments to 

increase their organ offer acceptance 

rate. Therefore, pre-pandemic growth 

rates for deceased donor kidney 

transplants would be expected to 

continue during the projection period. 

The living donor kidney transplant 

growth rate is also expected to continue 

close to pre-pandemic rates in the 

absence of the model. 

One initiative and one recent reform 

have the potential to impact the IOTA 

study population, even in the absence of 

the model. First, the OPTN 

Modernization Initiative that HRSA 

announced in March 2023 includes 

several actions to strengthen 

accountability, transparency, equity, 

and performance in the OPTN.349 Some 

of the proposed OPTN Modernization 

Initiative actions that are relevant to the 

IOTA Model’s target population include 

data dashboards detailing individual 

transplant center and organ 

procurement organization data on organ 

retrieval, waitlist outcomes, and 

transplants, and demographic data on 

organ donation and transplant will be 

made available to patients. In the 

absence of the IOTA Model, the OPTN 

Modernization Initiative has the 

potential to incentivize IOTA 

participants to improve upon some of 

the IOTA Model’s incentive domains, 

such as improving the organ offer 

acceptance rate and post-transplant 

outcomes. 

Second, the Comprehensive 

Immunosuppressive Drug Coverage for 

Kidney Transplant Patients Act (H.R. 

5534; also known as the Immuno Bill) 

passed in November 2020, which 

stipulates lifelong coverage for 

immunosuppressive drugs for kidney 

transplant recipients, has the potential 

to improve patient survival.350

Beginning January 1, 2023, the Medicare 

Part B Immunosuppressive Drug benefit 

covers immunosuppressive drugs 

beyond 36 months for eligible kidney 

transplant recipients that do not have 

other health coverage for 

immunosuppressive drugs. The most 

current statistics of post-transplant 

patient survival are reported by 

Hariharan et al.351 The authors used 

data from the OPTN/SRTR and found 

that post-deceased donor kidney 

transplant patient survival rates at years 

1 and 3 are 97.1 percent and 93.3 

percent, respectively, for transplantation 

taking place during 2016–2019. Postliving donor kidney transplant patient 

survival rates are 99.1 percent and 96.5 

percent during the same period. These 

rates decrease over the longer term. For 

kidney transplantation during 2008– 

2011, patient survival rates at 10 years 

are 66.9 percent for deceased donor 

kidney transplants and 81.3 percent for 

living donor kidney transplants. The 

authors project that survival rates will 

continue to improve, explaining that the 

decline in survival starting 3 years after 

transplantation has been attributed to, 

and coincides with, the discontinuation 

of insurance coverage for long-term 

immunosuppressive medications. 

B. Overall Impact 

We have examined the impacts of this 

rule under Executive Order 12866 on 

Regulatory Planning and Review 

(September 30, 1993), Executive Order 

13563 on Improving Regulation and 

Regulatory Review (January 18, 2011), 

Executive Order 14094 titled 

‘‘Modernizing Regulatory Review’’ 

(April 6, 2023), the Regulatory 


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352Cooper, M. et. al. (2018). Report of the 

National Kidney Foundation Consensus Conference 

to Decrease Kidney Discards. Journal of Clinical 

Transplantation and Translational Research, 

https://doi.org/10.1111/ctr.13419. 353Scientific Registry of Transplant Recipients. 

Adult Recipient Transplants By Donor Type, 

Center: U.S. Transplants Performed: January 1, 

1988–September 30, 2024; For Organ = Kidney; 

Include: Transplant Year & Recipient Primary 

Source of Payment. https://

optn.transplant.hrsa.gov/data/view-data-reports/ 

national-data/. Accessed October 22, 2024. 354Scientific Registry of Transplant Recipients. 

National Center Level Data by Organ: Kidney CSRS 

Final Tables, Table B11 & Figures B10–B14. https:// 

www.srtr.org/reports/program-specific-reports/. 

Accessed May 25, 2023. 

355Scientific Registry of Transplant Recipients. 

National Center Level Data by Organ: Kidney CSRS 

Final Tables, Tables C5–C12 Figures C1–C20. 

https://www.srtr.org/reports/program-specificreports/. Accessed May 25, 2023. 

Flexibility Act (RFA) (September 19, 

1980, Pub. L. 96–354), section 1102(b) of 

the Social Security Act, section 202 of 

the Unfunded Mandates Reform Act of 

1995 (March 22, 1995; Pub. L. 104–4), 

Executive Order 13132 on Federalism 

(August 4, 1999), and the Congressional 

Review Act (5 U.S.C. 804(2)). 

Executive Orders 12866 and 13563 

direct agencies to assess all costs and 

benefits of available regulatory 

alternatives and, if regulation is 

necessary, to select regulatory 

approaches that maximize net benefits 

(including potential economic, 

environmental, public health and safety 

effects, distributive impacts, and 

equity). The Executive Order 14094 

titled ‘‘Modernizing Regulatory Review’’ 

(hereinafter, the Modernizing E.O.) 

amends section 3(f)(1) of Executive 

Order 12866 (Regulatory Planning and 

Review). The amended section 3(f) of 

Executive Order 12866 defines a 

‘‘significant regulatory action’’ as an 

action that is likely to result in a rule: 

(1) having an annual effect on the 

economy of $200 million or more in any 

1 year (adjusted every 3 years by the 

Administrator of OIRA for changes in 

gross domestic product), or adversely 

affect in a material way the economy, a 

sector of the economy, productivity, 

competition, jobs, the environment, 

public health or safety, or State, local, 

territorial, or tribal governments or 

communities; (2) creating a serious 

inconsistency or otherwise interfering 

with an action taken or planned by 

another agency; (3) materially altering 

the budgetary impacts of entitlement 

grants, user fees, or loan programs or the 

rights and obligations of recipients 

thereof; or (4) raise legal or policy issues 

for which centralized review would 

meaningfully further the President’s 

priorities or the principles set forth in 

this Executive order, as specifically 

authorized in a timely manner by the 

Administrator of OMB’s Office of 

Information and Regulatory Affairs 

(OIRA) in each case. 

We have prepared a regulatory impact 

analysis (RIA) for major rules with 

significant regulatory action/s and/or 

that are significant under section 3(f)(1) 

of Executive order 12866 ($200 million 

or more in any 1 year). Based on our 

estimates from the CMS Office of the 

Actuary, OMB’s OIRA has determined 

that this rulemaking is not significant 

per section 3(f)(1). We have prepared an 

RIA that to the best of our ability 

presents the costs and benefits of the 

rulemaking. In accordance with the 

Congressional Review Act), OMB’s 

OIRA has also determined that this rule 

does not meet the criteria set forth in 5 

U.S.C. 804(2). We solicited comment on 

the RIA and provide our responses to 

each comment later in the RIA. 

C. Detailed Economic Analysis 

Several important factors have been 

identified that lead to the discard of 

donated kidneys, including significant 

increased cost to hospitals for 

transplanting organs from older donors 

and/or donors with comorbidities. 

Value-based payments that reward 

hospitals for increasing the number of 

transplants as well as related quality 

and process measures may improve the 

acceptance of offered organs and 

outcomes for patients.352 A stochastic 

model was constructed to estimate the 

financial impact of the IOTA Model. 

When possible, assumptions were 

informed by historical data. Transplant 

hospital adult transplant counts by 

donor type and recipients’ primary 

source of payment were obtained from 

the SRTR dashboard.353 Organ offer 

acceptance ratios 354 and the composite 

graft survival rate 355 were analyzed 

from SRTR’s program-specific statistics 

and transplant hospital-level data on 

kidney transplants. The SRTR data 

source includes data on all transplant 

donors, candidates, and recipients in 

the U.S. 

IOTA participants would receive 

upside or downside risk payments 

based on their performance across three 

domains: achievement, efficiency, and 

quality. The three domains would 

measure certain metrics and award 

points as shown in the following Table 

I: 

The upside risk payment would be a 

lump sum payment paid by CMS to the 

IOTA participants that achieve high 

final performance scores. Conversely, 

the downside risk payment would be a 

lump sum payment paid to CMS by the 

IOTA participants with low final 

performance scores. The performancebased payments would be based on the 

following thresholds. Total scores of 60 

and above would result in a maximum 

upside risk payment of $15,000, as 

shown in equation 7. Scores below 60 

would fall into the neutral zone with no 

upside or downside risk payment in PY 

1. After the first PY, scores from 41 to 

59 would fall in the neutral zone, and 

scores of 40 and below would receive a 

downside risk payment. The maximum 

downside risk payment in the model 

would be $2,000, as shown in equation 

8. This performance-based payment 

would then be multiplied by the total 

number of kidney transplants furnished 

by the IOTA participant to attributed 

patients for which model payments 

apply during the PY. 

Equation 7: IOTA Upside Risk Payment 

for Scores of 60 and Above 


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TABLE I: IOTA PERFORMANCE DOMAINS 

Domain Metrics Description Points 

Achievement The number of transplants performed relative to an IOTA participant-specific target. Rolling baseline. 60 

Efficiency Organ offer acceptance rate, which is a ratio of observed versus expected organ offer acceptances. 20 

Quality Composite graft survival rate. 20 

Total Possible 100 
96438 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

356Li MT, King KL, Husain SA, et al. 2021. 

‘‘Deceased Donor Kidneys Utilization and Discard 

Rates During COVID–19 Pandemic in the United 

States.’’ Kidney Int Rep; 6(9): 2463–2467. https://

www.ncbi.nlm.nih.gov/pmc/articles/PMC8419126/. 

357Robinson A, Booker S, Gauntt K, UNOS 

Research Department. 2022. ‘‘Eliminate Use of DSA 

and Region from Kidney Allocation One Year PostImplementation Monitoring Report.’’ OPTN Kidney 

Transplantation Descriptive Data Report. https://

optn.transplant.hrsa.gov/media/p2oc3ada/data_

report_kidney_full_20220624_1.pdf. 

Equation 8: IOTA Downside Risk 

Payment for Scores of 40 and Below 

We randomly selected half of all 

DSAs in the country and all eligible 

IOTA participants within those DSAs 

and applied assumptions for transplant 

growth and performance on other 

domains affecting the incentive formula 

for purposes of estimating impacts in 

this portion of the rule. Random 

variables accounted for variation in 

transplant growth and transplant 

hospital-level performance on other 

measures. A pivotal uncertainty relates 

to the potential growth in transplants as 

a result of upside and downside risk 

payments presented by the model. The 

current share of deceased donated 

kidneys that are discarded is roughly 20 

percent.356 357 Such growth was 

assumed to phase in over a 2- to 5-year 

period using a skewed distribution, with 

a gradual phase-in of 5 years being the 

most likely outcome. 

Comment: A few commenters 

provided justification for a revised 

payment methodology. A commenter 

recommended that CMS increase the 

maximum upside risk payment from 

$8,000 to $15,125 and the maximum 

downside risk payment from $2,000 to 

$3,750 and to apply these proposed 

payments for performance scores based 

on the national growth rate instead of to 

the IOTA participant’s own past peak 

performance. The commenter expected 

that these modifications would likely 

yield significantly more savings. A few 

commenters additionally urged CMS to 

revise potential financial incentives for 

IOTA participants upward in 

congruence with the potential new 

savings assumption but did not offer 

any specific alternative payment 

amounts. A few commenters 

recommended that the transplant target 

should be based on the arithmetic mean 

of volume for the 3-year baseline period 

instead of the peak performance during 

the baseline period. The commenter 

stated that the proposed targets are 

likely to result in the imposition of 

significant penalties on high-performing 

participants. 

Response: The maximum upside risk 

payment was increased from $8,000 in 

the proposed rule to $15,000 in the final 

rule (refer to section III.C.6. of this final 

rule (Payment) for the rationale behind 

the increase in the maximum risk 

payment amount). The maximum 

downside risk payment remained at 

$2,000. For clarification, in the 

proposed rule, the transplant target was 

equal to the highest number of deceased 

or living donor kidney transplants 

performed during the three-year 

baseline period trended forward by the 

national growth rate. In the final rule, 

the transplant target was updated to 

equal to the average number of 

transplants performed during baseline 

years trended forward by the national 

growth rate. Changing the transplant 

target to be the average of the baseline 

years instead of the highest number 

should set the base within reach for 

IOTA participants to achieve their 

targets. 

For IOTA participants randomized 

into the model, assumptions were also 

made for gradual improvement over 

baseline kidney acceptance rates, with 

individual IOTA participants assumed 

to have, in year 1, up to a 10-percent 

chance (up to a 20-percent chance by 

year 2, etc.) of increasing their 

acceptance ratio by between 20 to 80 

percentage points and maintaining such 

simulated improvement in ensuing 

model years. The share of IOTA 

participants receiving passing 

confidence intervals for the 1-year post 

transplant composite graft survival ratio 

was assumed to be roughly 95 percent 

in year 1, gradually improving by about 

half of a percentage point per year. 

Please see section III.C.5.e.(1). of this 

rule for the discussion on posttransplant outcomes. 

Tables II, III, and IV show the possible 

point allocations for performance 

relative to target for the Achievement 

Domain, Efficiency Domain, and Quality 

Domain, respectively. For the 

Achievement Domain (Table II), the 

transplant target is the average number 

of transplants performed during 

baseline years trended forward by the 

national growth rate. For the Efficiency 

Domain (Table III), in recognition that 

all IOTA participants may not be able to 

achieve the highest national rank, but 

still may be performing beyond their 

previous standards, this domain will be 

scored in two ways: achievement 

scoring and improvement scoring (not 

displayed in Table III). IOTA 

participants will be awarded points 

based on the scoring system that yields 

the highest allocation. In Table III, 

organ-offer acceptance will be 

calculated as a rate ratio of observed 

organ offer acceptances versus expected 

organ offer acceptances. Performance 

will be assessed across all centers 


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IOTA Lump Sum Payment 

$ (

Final Performance Score - 60) 

= 15,000 * 40 

* Medicare Kidney Transplants 

IOTA Performance Payment 

_ * (40 - Final Performance Score) - $2,000 40 

* Medicare Kidney Tranplants 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96439 

nationally. In the Quality Domain (Table 

IV), the composite graft survival rate is 

equal to the total number of functioning 

grafts divided by the total number of 

completed kidney transplants. 

Table V later in this section shows the 

projected impacts for upside and 

downside risk payments, transplants, 

and Federal spending. Although 

transplant recipients with any type of 

insurance may benefit from a transplant 

hospital’s participation in the model, 

model payments will be based on the 

number of transplant recipients who are 

beneficiaries with Medicare fee-forservice (FFS) coverage including 

beneficiaries enrolled in Medicare as a 

secondary payer. Just over one-third of 

IOTA participants are projected to 

receive upside risk payments in the first 

year, rising to about 43 percent over the 

succeeding 5 model years, with only a 

small fraction of participants projected 

to owe downside risk payments in any 

of years 2 through 6 (ranging from 16 to 

18 percent). The magnitude of the 

average downside risk payment is 

relatively small, and the cumulative 

projected upside risk payments to IOTA 

participants, amounting to $117 million, 

are over 100 times the magnitude of a 

cumulative $1 million in projected 

receipts from downside risk payments 

from IOTA participants to CMS. The 

amount of projected savings from new 

transplants was greater than the net cost 

of payments in about 58 percent of 

simulation trials. The mean 3,683 added 

transplants over the 6-year model 

performance period is an increase from 

the proposed rule for the following 

reasons: (1) a more effective response in 

terms of added transplants was assumed 

in the final rule due to the larger 

maximum per-transplant incentive; and 

(2) more hospitals were estimated to 

receive a positive incentive any given 

year because the scoring thresholds 

were made more gradual and the 

surrounding quality scoring 

methodology would make higher scores 

more attainable. Overall, mean net 

savings totaled $28 million over 6 years, 

ranging from a savings of $152 million 

to a cost of $77 million at the 10th and 

90th percentiles. 


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TABLE II: ACHIEVEMENT DOMAIN - SCORING FOR TRANSPLANT 

TARGET 

Performance Relative to Tar2et Points Earned 

;::: 125% 60 

120% < X < 125% 55 

115% :Sx < 120% 50 

l05% <x < 115% 40 

95% :Sx < 105% 30 

85% <x < 95% 20 

75% :Sx < 85% IO 

<75% 0 

TABLE III: EFFICIENCY DOMAIN - ACHIEVEMENT SCORING FOR 

ORGAN OFFER ACCEPTANCE RA TE 

Performance Relative to Tar2et Points Earned 

;::: 80th Percentile 20 

60th < x < 80th Percentile 15 

40th :S x < 60th Percentile IO 

20th < x < 40th Percentile 6 

0 :S x < 20th Percentile 0 

TABLE IV: QUALITY DOMAIN - SCORING FOR 

COMPOSITE GRAFT SURVIVAL RATE 

Performance Relative to Tar2et Points Earned 

> 80th Percentile 20 

60th :S x < 80th Percentile 18 

40th < x < 60th Percentile 16 

20th :S x < 40th Percentile 14 

10th < x < 20th Percentile 12 

0 :S x < 10th Percentile IO 
96440 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

358Axelrod DA, Schnitzler MA, Xiao H, et al. 

2018. ‘‘An Economic Assessment of Contemporary 

Kidney Transplant Practice.’’ American Journal of 

Transplantation 18: 1168–1176. https://

pubmed.ncbi.nlm.nih.gov/29451350/. 

359Medicare Program; Specialty Care Models To 

Improve Quality of Care and Reduce Expenditures, 

85 FR 61335 (September 29, 2020) (codified at 45 

CFR part 512, subpart A). 

In Table V, negative spending reflects 

a reduction in Medicare spending, while 

positive spending reflects an increase in 

Medicare spending. The mean net 

savings results were generated from the 

average of 10,000 individual simulation 

trials and the results for the percentiles 

are from the top 10th and 90th 

percentiles of the 10,000 individual 

simulations. The outcomes in each row 

do not necessarily flow from the same 

trial in the model at the 10th and 90th 

percentiles. For example, the 90th 

percentile for added transplants more 

likely corresponds to the trial that 

produced the 10th percentile in impact 

on FFS spending from those transplants 

(because spending is reduced when 

transplants grow). 

There is a wide range of potential 

changes in Federal spending for each 

new transplant. Savings on avoided 

dialysis may in many cases be exceeded 

when transplants are especially 

complex and post-transplant 

complications are more likely, for 

example when deceased organs have a 

high kidney donor profile index and/or 

recipients are of advanced age.358 But 

even in such cases Federal savings can 

be substantial if Medicare is not primary 

payer at time of transplant or the 

beneficiary eventually returns to private 

insurance post-transplant. We relied on 

the savings per transplant estimate 

published in the ESRD Treatment 

Choices (ETC) Model final rule 359 to 

account for different primary payer 

scenarios at the time of transplant, as 

well as the likelihood that the 

beneficiary would have remained on 

Medicare after transplantation. For the 

ETC Model, OACT produced a 10-year 

savings to Medicare of approximately 

$32,000 per beneficiary for a deceased 

donor kidney transplant with a highkidney donor profile index. For the 

proposed IOTA Model, we assumed the 

average Federal spending impact could 

range from a cautious $20,000 increase 

to optimistically at most a $100,000 

savings per additional transplant (mean 

assumption being a $40,000 savings). 

The mean assumption of $40,000 in 

savings is marginally higher than the 

ETC Model’s 10-year estimated savings 

to Medicare of approximately $32,000 

per beneficiary for a deceased donor 

kidney transplant with a high-kidney 

donor profile index because it includes 

at least some potential for an increase in 

other types of transplants. The 10-year 

estimated savings to Medicare of 

approximately $32,000 per beneficiary 

used in the ETC Model based on 

deceased donor, high-kidney donor 

profile transplants was assumed because 

of the relatively limited focus that 

model appeared to have on improving 

the number of transplants and outcomes 

for transplants. By comparison, the 

estimate for the IOTA Model still 

focused on deceased donor kidneys, but 

this model warranted a marginally 

higher savings per transplant estimate, 

allowing for the mean assumption of 

$40,000 in savings. To determine the 

outer bounds of the assumption, we 

identified individual points in our 

organ-type/payer matrix that ranged 

from a $100,000 increase in costs to 

$200,000 (or wider) in savings, so the 

bounds we chose for the estimate were 

based on realizing new transplants were 

going to be mixed across the matrix and 

not all congregated at an extreme end on 

one side or the other (keeping in mind 

that they will likely come mostly from 

decedent donor kidneys). We assumed 

that kidney transplant savings would 

accumulate in the year of the transplant 

even though the cost of the transplant 

would, in practice, lead to higher 

spending in the first year (unless 

Medicare was not the primary payer). It 

would likely take longer than the 6 

model years for the cumulative net 

savings projected in Table III to 

ultimately materialize. The timing of 

when savings would accumulate could 

not be estimated with more precision for 

the following reasons. Savings could 

range from being virtually immediate if 

new transplants occur when a 

beneficiary is not Medicare primary 

payer status, to being backloaded if the 

beneficiary receives the transplant when 

Medicare is primary payer, to being a 

net cost if the beneficiary transplant 

fails within a short period after 

transplant. Given those uncertainties, 

and the underlying uncertainties about 

where the new transplants will 

materialize from (by donor and 

recipient), we were not able to imply 

more precision than we were able to 

model from the evidence. 

Comment: Some commenters 

recommended that CMS increase the 

proposed estimate of $40,000 in savings 

to Medicare over a 10-year period for 

each additional kidney transplant 

furnished to a Medicare beneficiary 

compared to remaining on dialysis. The 

commenters expressed that the estimate 

understates Medicare savings resulting 

from kidney transplantation and a few 

commenters noted it is inconsistent 

with estimates calculated by 

commenters using United States Renal 

Data System (USRDS) data to compare 

costs for patients receiving a kidney 

transplant to those on dialysis. A few 

commenters cited published literature 

that also used USRDS data to support 

their concern that the savings to 

Medicare estimate may be in error. 

These commenters also noted that the 

published study used as an input for the 

savings assumption did not account for 

costs of death on the waiting list. 


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TABLE V: PROJECTED IMPACT OF UPSIDE/DOWNSIDE RISK PAYMENTS, 

KIDNEY TRANSPLANTS, AND NET FEDERAL SPENDING 

k/'i;.,/'··· ""'!::.,.,.",.··; •••.· .•,<~•·•·<,·; 

7/1/25- 7/1/26- 7/1/27- 7/1/28- 7/1/29- 7/1/30- 't~t\t, ~ it:~ 1~·{:· 6/30/26 6/30/27 6/30/28 6/30/29 6/30/30 6/30/31 

Upside Risk Payments $15 $17 $20 $21 $21 $23 $117 $90 $144 

Downside Risk Payments $0 $0 $0 $0 $0 $0 -$1 -$2 -$1 

Total Net Payments $15 $17 $19 $21 $21 $23 $116 $89 $142 

Added Transplants 161 343 546 761 913 959 3,683 1,372 6,261 

Impact on FFS Spending -$5 -$12 -$20 -$-29 -$37 -$40 -$144 -$152 -$37 

Mean Net Savings $9 $5 -$1 -$8 -$15 -$18 -$28 -$152 $77 

(Projected savings allocated to year of transplant; dollars in millions) 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96441 

360 Guidelines for the adjustment in base wages is 

based on the following report: Office of the 

Assistant Secretary for Planning and Evaluation 

(ASPE). 2017. ‘‘Valuing Time in U.S. Department of 

Health and Human Services Regulatory Impact 

Analyses: Conceptual Framework and Best 

Practices.’’ https://aspe.hhs.gov/reports/valuingtime-us-department-health-human-servicesregulatory-impact-analyses-conceptual-framework. 

Response: In response to the 

commenters, we investigated the 

methodology and data sources in the 

Axelrod et al. (2018) study that was 

used as an input in our calculations. 

Ultimately, we decided to keep the 

proposed estimate of $40,000 in savings 

to Medicare over a 10-year period for 

each additional kidney transplant 

furnished to a Medicare beneficiary 

compared to remaining on dialysis. The 

key validity of the Axelrod et al. (2018) 

study is that the authors focused strictly 

on costs involving either—(1) 

maintenance dialysis as a service (that 

is, the payment to dialysis facilities for 

regular maintenance dialysis); or (2) 

kidney transplant surgery (including 

related costs before and after transplant 

surgery) as reported on hospital cost 

reports and potential downstream costs 

related to graft failure and return to 

dialysis. Some commenters appeared to 

assume the study was accounting for all 

other Part A and Part B costs outside of 

these categories, which is not the case. 

Several commenters incorrectly 

assumed that the Axelrod et al. (2018) 

study did not include the costs of death 

on the waiting list; however, the mean 

costs of death were included in the 

authors’ modeling for the following: 

death after transplantation, death on the 

waiting list, and death with function. 

In addition to the type of costs 

included in the Axelrod et al. (2018) 

study, another reason why we cannot 

make direct comparisons to the USRDS 

data is that the Axelrod et al. (2018) 

study used two sources for their 

economic data: (1) Medicare claims data 

from the USRDS and estimates from a 

novel data set linking national registry 

data; and (2) hospital cost-accounting 

data from the University HealthSystem 

Consortium corporation. The authors 

explained that the latter source was 

included because Medicare diagnosisrelated group (DRG)-based payments are 

poorly correlated with the actual cost of 

the transplantation procedure. In 

response, we investigated using hospital 

reported costs instead of Medicare paid 

amounts for transplant costs for our 

savings to Medicare estimate 

calculation. We found that this only 

made a material difference for some of 

the living donor kidney transplants, 

which are expected to be very small 

percentage of increased transplants in 

the model, so we did not see a need to 

adjust our assumptions in response to 

this detail. 

Last, we considered additional factors 

that could potentially impact our 

estimate. Medicare spending extraneous 

to dialysis/transplant could be increased 

by transplantation because of positive 

impacts on longevity, for example, but 

on the other hand Medicare spending 

could be reduced to the extent that nondisabled recipients under the age of 65 

would return to private health insurance 

after transplant. These (and other) 

opposing forces could push the average 

net Medicare impact materially higher 

or lower than the strict comparison in 

Axelrod et al. (2018). This is highly 

dependent on the mix of organs and 

patients that ultimately represent the 

increased transplant population in the 

model. Significant continued 

uncertainty in these areas necessitates a 

wide range for assuming the net 

spending impact per new transplant, 

and revisiting the evidence did not 

convince us the range should 

necessarily be updated in either 

direction. 

Comment: A commenter suggested 

that there may be an error in Table III 

of the proposed rule. The commenter 

stated that the projected $100 million 

impact on FFS spending should be $105 

million (assuming $40,000 per 

transplant × assuming 2,625 additional 

transplants = $105,000,000), yielding a 

mean net savings of $70 million to 

Medicare after projected net payments 

of $35 million to IOTA participants. 

Response: The commenter incorrectly 

assumed that the row labeled, ‘‘Impact 

on FFS Spending’’ in Table III of the 

proposed rule was a direct calculation 

of the mean savings per transplant 

multiplied by the number of additional 

transplants. Instead, we assumed the 

average Federal spending impact could 

range from a cautious $20,000 increase 

to optimistically at most a $100,000 

savings per additional transplant with a 

mode (as well as the mean) assumption 

being $40,000 savings. The mean of 

$100,000 reported for the Impact on FFS 

Spending in the 6-year total column in 

Table III of the proposed rule is from the 

average of 400 individual simulation 

trials, where the savings per additional 

transplant is a number between $20,000 

and $100,000 generated by our actuarial 

model. 

D. Estimated Burden on Participant 

Hospitals 

While the model is focused on 

transplant outcome measures that 

would be calculated by CMS, there 

would likely be some additional burden 

for compliance for the IOTA 

participants (that is, transplant 

hospitals). To estimate the compliance 

cost we focused on § 512.442(c) that 

requires IOTA participants to review 

organ offer acceptance criteria with 

IOTA waitlist patients who are 

Medicare beneficiaries at least every 6 

months that the Medicare beneficiary is 

on their waitlist. For this estimate, we 

assume that the IOTA participant will 

take a total of 15 minutes per patient per 

year to review the criteria at least twice 

a year with each patient. This 

assumption likely yields an upper 

estimate since the method (for example, 

patient visit, phone, email, or mail) of 

how the IOTA participant 

communicates the review with the 

patient is up to the IOTA participant 

and will likely vary by IOTA 

participant, potentially reducing the 

time to conduct the review. In addition, 

the patient may decline the review, 

resulting in the IOTA participant having 

fewer Medicare waitlist patients than 

what is used in our estimate. 

We estimate that the average IOTA 

participant would have 200 waitlist 

patients who are Medicare primary 

payer or Medicare secondary payer 

beneficiaries per year and that it would 

take a clinician 15 minutes to review 

organ offer acceptance criteria with each 

patient each year. Using base wage 

information from BLS for a nurse 

practitioner (series 29–1171), we 

estimate the cost of completing these 

reviews to be $61.78 per hour. The base 

wage is then doubled [$61.78 × 2] to 

account for fringe benefits and overhead 

to equal an estimated cost of $123.56 

per hour.360 The cost of completing 

these reviews would then be $6,178.00 

per hospital per year [200 Medicare 

waitlist patients × 0.25 hour per review 

each year × $123.56 hourly wage]. 

Therefore, the total cost would come out 

to $556,020.00 to complete the review of 

organ offer acceptance criteria based on 

the assumption that 90 active transplant 

hospitals will be selected as IOTA 

participants [$6,178.00 × 90 hospitals = 

$556,020.00]. Average total revenue for 

the transplant hospitals that may be 

selected to be an IOTA participant using 

inpatient hospital codes DRG–008 

simultaneous pancreas-kidney 

transplant and DRG–652 kidney 

transplant generated from adult 

Medicare FFS beneficiaries with 

Medicare as their primary payer was 

$1.0 million in calendar year (CY) 2023. 

Therefore, the $6,178.00 cost per IOTA 

participant to review the organ offer 

acceptance criteria would represent 0.6 

percent of the estimated total annual 

revenue per IOTA participant from 


ddrumheller on DSK120RN23PROD with RULES2
96442 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

361Bureau of Labor Statistics (BLS). May 2023. 

‘‘Occupational Employment and Wage Statistics.’’ 

https://www.bls.gov/oes/current/oes_nat.htm. 

362https://optn.transplant.hrsa.gov. 

363Hariharan S, Irani AK, Danovitch G (2023). 

‘‘Long-Term Survival after Kidney 

Transplantation.’’ New England Journal of 

Medicine. 385:729–43. https://www.nejm.org/doi/ 

full/10.1056/NEJMra2014530. 364Axelrod DA, Schnitzler MA, Xiao H, et al. 

2018. ‘‘An Economic Assessment of Contemporary 

Kidney Transplant Practice.’’ American Journal of 

Transplantation 18: 1168–1176. https://

pubmed.ncbi.nlm.nih.gov/29451350/. 

DRGs 653 and 008 when Medicare is the 

primary payer. 

E. Regulatory Review Cost Estimation 

We estimate the time it will take for 

a medical and health services manager 

to review the rule to be 13.33 hours 

[200,000 words/250 words per minute/ 

60 minutes = 13.33 hours]. Using the 

wage information from the Bureau Labor 

of Statistics (BLS) for medical and 

health service managers (series 11– 

9111), we estimate that the cost of 

reviewing this rule is $129.28 per hour, 

including overhead and fringe 

benefits.361 The cost of reviewing the 

rule would therefore be a $1,723.30 per 

hospital [13.33 hours × $129.28 per hour 

= $1,723.30] or a total cost of 

$155,097.00 [$1,723.30 × 90 hospitals = 

$155,097.00]. Using information from 

the OPTN, we estimate 230 active 

kidney transplant hospitals that are the 

potential IOTA participants would 

review this rule for a total cost of 

$396,359.00 [$1,723.30 per hospital × 

230 hospitals = $396,359.00].362 In 

addition, the $1,723.30 cost per IOTA 

participant to complete the regulatory 

review would represent 0.1 percent of 

the estimated total annual revenue from 

DRGs 653 and 008 from adult Medicare 

FFS beneficiaries with Medicare as their 

primary payer. 

F. Alternatives Considered 

The proposed rule in 42 CFR part 512 

[CMS–5535–P] dated May 17, 2024 can 

be used as an example of alternatives 

considered for the IOTA Model prior to 

finalizing the rule. The main changes 

between the proposed rule and final 

rule are summarized in this section. The 

Achievement Domain included the 

following components in the proposed 

rule which were modified in the final 

rule: 

• The transplant target was the 

highest number of deceased or living 

donor kidney transplants performed 

during baseline years trended forward 

by the national growth rate. 

• The transplant count included a 

health equity performance adjustment. 

Any transplants performed for the 

underserved population identified in 

the equity paper (uninsured, Medicaid, 

dual eligible, Medicare LIS, NLDACeligible transplants) counted as 1.2 

transplants. 

• The thresholds used in the points 

allocation for the transplant targets 

included five cutoffs with a range of 

zero to 60 possible points awarded. 

In the final rule, these components 

were changed to—(1) the transplant 

target was updated to equal to the 

average number of transplants 

performed during baseline years trended 

forward by the national growth rate; (2) 

the health equity performance 

adjustment was removed; and (3) the 

thresholds used in the point allocation 

for the transplant targets include eight 

cutoffs with a range of zero to 60 

possible points awarded (see Table II). 

The Efficiency Domain was finalized 

as proposed. The Quality Domain 

included the following components in 

the proposed rule which were modified 

in the final rule: (1) a Quality Measures 

Set (10 possible points) that included 

the CollaboRATE Shared DecisionMaking Score, a 3-Item Care Transition 

Measure, and Colorectal Cancer 

Screening; and (2) a Composite Graft 

Survival Rate (10 possible points) was 

based on performance relative to 

national ranking with five cutoffs and a 

range of zero to 10 possible points 

awarded. In the final rule these 

components were changed to: (1) the 

Quality Measures Set was removed; and 

(2) the Composite Graft Survival Rate 

(20 possible points) is based on 

performance relative to target with six 

cutoffs and a range of 10 to 20 possible 

points awarded (see Table IV). 

Last, for the payment methodology, 

the following component in the 

proposed rule was modified in the final 

rule: The maximum upside risk 

payment was $8,000 and downside risk 

payment was $2,000. In the final rule, 

this component was changed to: The 

maximum upside risk payment was 

increased to $15,000 and the maximum 

downside risk payment remained at 

$2,000 (see equations 7 and 8). 

When these components were 

implemented together in modeling the 

proposed rule, the mean net projected 

savings of the IOTA Model totaled $65 

million over 6 years, ranging from a 

savings of $151 million to a cost of $11 

million at the 10th and 90th percentiles. 

Although the mean projected savings 

decreased after accounting for the final 

rule policies, significantly increased 

incentives are expected to increase the 

number of new transplants generated by 

the model and create a potential for 

slightly greater overall savings at the 

optimistic end of the projection range 

(the final rule 10th percentile is $152 

million savings). Detailed explanation 

for why these model components 

changed from the proposed rule to the 

final rule is provided throughout 

various sections of the final rule. 

Comment: A commenter requested 

that CMS predict what savings in the 

model would be if we were to include 

a pre-emptive transplant multiplier that 

would drive an uptick in pre-emptive 

transplantation and related savings. 

Response: In the proposed rule, we 

stated that we considered offering 

differential credit for transplants by 

type. With this methodology, IOTA 

participants would receive bonus points 

and score higher for transplants that fit 

into categories that lead to more savings, 

such as living donor kidney transplants 

(LDK), high KDPI donors, or preemptive transplants, compared to other 

transplants. Addressing the comment 

directly, the pre-emptive nature of some 

transplants is only one of many complex 

and uncertain factors contributing to the 

financial impact of the average 

transplant potentially added in response 

to model incentives. However, we 

believe that counting all transplants the 

same would maximize flexibility for 

transplant hospitals in meeting their 

targets and minimizes the potential 

harm and unintended consequences the 

alternative system would create. 

Therefore, a pre-emptive transplant 

multiplier was not included in the final 

rule. 

G. Impact on Beneficiaries 

The upside and downside risk 

payments in this model are expected to 

at least marginally increase the number 

of kidney transplants provided to 

beneficiaries with ESRD. This model is 

projected to result in approximately 

3,700 new transplants over the 6-year 

model performance period. Evidence 

shows that kidney transplants extend 

patients’ lives and that such benefits 

have been increasing despite 

unfavorable trends in terms of donor 

and recipient risk factors.363 Even if 

added transplants most often were to 

involve high Kidney Donor Profile 

Index (KDPI) organs (that are most often 

discarded historically), the average 

recipient would still be expected to 

benefit from increased quality of life 

and longevity.364 In addition—though 

we did not explicitly assume specific 

benefits to beneficiaries—the model 

would include quality measures aimed 

at improving outcomes even for 

transplants that would have otherwise 

occurred absent the model. IOTA 

participants would be incentivized to 

improve the composite graft survival 

rate. The model could also improve the 


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efficiency with which hospitals interact 

with organ procurement organizations 

and reduce the time from deceased 

organ donation to transplant surgery. 

These and other elements of the model 

have the potential to improve outcomes 

for the wider group of transplant 

patients beyond the fraction assumed to 

receive transplants under the model. 

H. Accounting Statement and Table 

The annualized monetized benefits 

and transfers in Table VI were 

calculated based on constant payments 

and constant discount interest rates. 

Using the row labeled Total as an 

example for how the results were 

calculated, the primary estimate of $4 

million in total savings was based on a 

2 percent discount rate, with a 6-year 

study period, and a net present value of 

$24 million in savings. Net present 

value for the primary estimate was 

based on the IOTA Model’s mean net 

savings estimate for years July 1, 2025 

through June 30, 2031 reported in the 

bottom row of Table V. The minimum 

and maximum annualized monetized 

total benefits and transfers reported in 

Table VI use the same calculation as the 

primary estimate, with the exception of 

the annual mean net savings replaced 

with the IOTA Model’s annual mean net 

savings for the 10th and 90th 

percentiles. 

I. Regulatory Flexibility Act (RFA) 

Effects on IOTA participants in the 

model include the potential for 

additional upside risk payments from 

CMS to the IOTA participant of up to 

$15,000 per eligible kidney transplant or 

downside risk payments from the IOTA 

participant to CMS of up to $2,000 per 

eligible kidney transplant (refer to 

section IV.C. of this final rule (Detailed 

Economic Analysis) for a description of 

how upside and downside risk 

payments are calculated in the model). 

We project that payouts will far exceed 

the relatively small sum of downside 

risk payments expected over the 6-year 

model performance period. Only about 

$1 million in total downside risk 

payments are expected over 6 years 

spread across approximately 16 to 18 

percent of IOTA participants expected 

to be charged downside risk payments 

from year to year. By contrast, we 

project over 6 years that $117 million in 

total upside risk payments would be 

made to between 33 to 43 percent of 

IOTA participants expected to earn 

payments in the model from year to 

year. 

Under the RFA, agencies are to 

analyze options for regulatory relief of 

small entities, if a rule has a significant 

impact on a substantial number of small 

entities. The great majority of hospitals 

and most other health care providers 

and suppliers are small entities, either 

by being nonprofit organizations or by 

meeting the SBA definition of a small 

business (having revenues of less than 

$8.0 million to $41.5 million in any 1 

year). Although many IOTA participants 

(that is, transplant hospitals with NAICS 

622110 General Medical and Surgical 

Hospitals) may be small entities as that 

term is used in the RFA, kidney 

transplants only represent a small 

fraction of the revenue such hospitals 

generate, and even the largest per 

transplant downside risk payment of 

$2,000 (which notably is expected to be 

a very rare outcome in general) would 

not represent a significant economic 

impact. Additional sources of financial 

burden on IOTA participants to 

consider include the estimated cost of 

$6,178.00 per IOTA participant per year 

to review the organ offer acceptance 

criteria with IOTA waitlist patients who 

are Medicare beneficiaries and the onetime cost of $1,723.00 per IOTA 

participant to have their medical and 

health services manager review this 

rule. Refer to the section titled, 

‘‘Estimated Burden on Participant 

Hospitals’’ in the final rule for an 

explanation of how these burden 

estimates were determined. No 

comments were received during the 

public comment period on the RFA 

section on regulatory relief for small 

entities. 

As its measure of significant 

economic impact on a substantial 

number of small entities, HHS uses a 

change in revenue of more than 3 to 5 

percent. The $6,178.00 cost per IOTA 

participant to review the organ offer 

acceptance criteria and the $1,723.30 

cost per IOTA participant to complete 

the regulatory review would represent 

0.6 percent and 0.1 percent, 

respectively, of the estimated total 

annual revenue per IOTA participant 

from DRGs 653 and 008 when Medicare 

is the primary payer. Based on these 

estimates, we do not believe that this 

threshold will be reached by the 

requirements in this final rule. 


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TABLE VI: ACCOUNTING STATEMENT 

Annualized monetized benefits and transfers (negative indicates savings). Dollars in millions. 

Primary Minimum Maximum Source 

Estimate Estimate Estimate Citation 

Costs to Medicare for Upside Risk Payments to IOTA Participants $19 $14 $25 RIA Table V 

Costs to IOTA Participants for Downside Risk Payments $0 $0 $0 RIA Table V 

Benefits via Savings from Increased Transplants -$24 -$44 -$6 RIA Table V 

Total -$4 -$25 $14 RIA TableV 

Notes: The total may not equal the sum of the preceding rows due to rounding. The costs to IOTA participants for 

negative payments are less than a million dollars for the primary, minimum, and maximum estimates. 

TABLE VII: ADDITIONAL ESTIMATED COSTS FOR2025-2031 

Total costs reported for all IOTA participants. Dollars are not reported in millions. 

Category Costs Frequency Source Citation 

Burden to IOTA participants $556,020 Annual Section IV.D. Estimated Burden on Participant Hospitals 

Regulatory review $396,359 One-time Section IV.E. Regulatory Review Cost Estimation 
96444 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

Therefore, the Secretary has certified 

that this final rule will not have a 

significant economic impact on a 

substantial number of small entities. 

In addition, under section 1102(b) of 

the Act, a regulatory impact analysis 

should be prepared if a rule may have 

a significant impact on the operations of 

a substantial number of small rural 

hospitals. This analysis must conform to 

the provisions of section 603604 of the 

RFA. For purposes of section 1102(b) of 

the Act, we define a small rural hospital 

as a hospital that is located outside of 

a metropolitan statistical area and has 

fewer than 100 beds. We believe this 

final rule will not have a significant 

impact on small rural hospitals since 

small rural hospitals do not have the 

resources to perform kidney transplants. 

Therefore, the Secretary has certified 

that this final rule will not have a 

significant impact on the operations of 

a substantial number of small rural 

hospitals. 

J. Unfunded Mandates Reform Act 

(UMRA) 

Section 202 of the Unfunded 

Mandates Reform Act of 1995 (UMRA) 

also requires that agencies assess 

anticipated costs and benefits before 

issuing any rule whose mandates 

require spending in any 1 year of $100 

million in 1995 dollars, updated 

annually for inflation. In 2024, that 

threshold is approximately $183 

million. This final rule does not 

mandate any requirements for State, 

local, or tribal governments, or for the 

private sector. 

K. Federalism 

Executive Order 13132 establishes 

certain requirements that an agency 

must meet when it promulgates a 

proposed rule (and subsequent final 

rule) that imposes substantial direct 

requirement costs on State and local 

governments, preempts State law, or 

otherwise has Federalism implications. 

This final rule will not have a 

substantial direct effect on State or local 

governments, preempt States, or 

otherwise have a Federalism 

implication. 

Chiquita Brooks-LaSure, 

Administrator of the Centers for 

Medicare & Medicaid Services, 

approved this document on October 23, 

2024. 

List of Subjects in 42 CFR Part 512 

Administrative practice and 

procedure, Health facilities, Medicare, 

Recordkeeping requirements. 

For the reasons set forth in the 

preamble the Centers for Medicare & 

Medicaid Services amends 42 CFR part 

512 as follows: 

■ 1. The part heading for part 512 is 

revised to read as follows: 

PART 512—STANDARD PROVISIONS 

FOR MANDATORY INNOVATION 

CENTER MODELS AND SPECIFIC 

PROVISIONS FOR THE RADIATION 

ONCOLOGY MODEL AND THE END 

STAGE RENAL DISEASE TREATMENT 

CHOICES MODEL 

■ 2. The authority for part 512 

continues to read as follows: 

Authority: 42 U.S.C. 1302, 1315a, and 

1395hh. 

■ 3. The heading of subpart A is revised 

to read as follows: 

Subpart A—Standard Provisions for 

Mandatory Innovation Center Models 

■ 4. Revise § 512.100 to read as follows. 

§ 512.100 Basis and scope. 

(a) Basis. This subpart implements 

standard provisions for certain 

Innovation Center models, as that term 

is defined in this subpart. 

(b) Scope. (1) The regulations in this 

subpart apply to the Radiation Oncology 

Model implemented under subpart B, 

the End-Stage Renal Disease (ESRD) 

Treatment Choices Model implemented 

under subpart C, and each Innovation 

Center model for which participation by 

Model participants is mandatory that 

begins its first performance period on or 

after January 1, 2025. 

(2) This subpart sets forth the 

following: 

(i) Basis and scope. 

(ii) Definitions. 

(iii) Beneficiary protections. 

(iv) Cooperation in model evaluation 

and monitoring. 

(v) Audits and record retention. 

(vi) Rights in data and intellectual 

property. 

(vii) Monitoring and compliance. 

(viii) Remedial action. 

(ix) Innovation Center model 

termination by CMS. 

(x) Limitations on review. 

(xi) Miscellaneous provisions on 

bankruptcy and other notifications. 

(xii) Reconsideration review 

processes. 

(3) Except as specifically noted in this 

subpart, these regulations do not affect 

the applicability of other provisions 

affecting providers and suppliers under 

Medicare FFS, including provisions 

regarding payment, coverage, or 

program integrity. 

■ 5. Section 512.110 is amended by— 

■ a. Adding, in alphabetical order, the 

definition of ‘‘Governing 

documentation’’; 

■ b. Revising the definitions of 

‘‘Innovation Center model,’’ ‘‘Innovation 

Center model activities,’’ ‘‘Model 

beneficiary,’’ and ‘‘Model participant’’; 

and 

■ c. Adding, in alphabetical order, the 

definitions of ‘‘Performance period’’ and 

‘‘Standard provisions for Innovation 

Center models’’. 

The additions and revisions read as 

follows: 

§ 512.110 Definitions. 

* * * * * 

Governing documentation means the 

applicable Federal regulations, and the 

model-specific participation agreement, 

cooperative agreement, and any 

addendum to an existing contract with 

CMS, that collectively specify the terms 

of the Innovation Center model. 

* * * * * 

Innovation Center model means an 

innovative payment and service 

delivery model tested under the 

authority of section 1115A(b) of the Act, 

including a model expansion under 

section 1115A(c) of the Act. 

* * * * * 

Innovation Center model activities 

mean any activities affecting the care of 

model beneficiaries related to the test of 

the Innovation Center model. 

* * * * * 

Model beneficiary means a beneficiary 

attributed to a model participant or 

otherwise included in an Innovation 

Center model. 

* * * * * 

Model participant means an 

individual or entity that is identified as 

a participant in the Innovation Center 

model. 

* * * * * 

Performance period means the period 

of time during which an Innovation 

Center model is tested and model 

participants are held accountable for 

cost and quality of care; the 

performance period for each Innovation 

Center model is specified in the 

governing documentation. 

* * * * * 

Standard provisions for Innovation 

Center models mean the provisions 

codified in 42 CFR part 512 subpart A. 

* * * * * 

■ 6. Section 512.190 is added to read as 

follows: 

§ 512.190 Reconsideration review process. 

(a) Applicability of this section. 

Section 512.190 is only applicable to the 

following: 

(1) Innovation Center models that 

have waived section 1869 of the Act, or 

where section 1869 of the Act is not 

applicable for model participants. 


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(2) Model participants, unless the 

governing documentation for the 

Innovation Center model states 

otherwise. 

(b) Right to reconsideration. The 

model participant may request 

reconsideration of a determination made 

by CMS in accordance with an 

Innovation Center model’s governing 

documentation only if such 

reconsideration is not precluded by 

section 1115A(d)(2) of the Act, this 

subpart, or the governing 

documentation for the Innovation 

Center model for which CMS made the 

initial determination. 

(1) A request for reconsideration by 

the model participant must satisfy all of 

the following criteria: 

(i) Must be submitted to a designee of 

CMS (reconsideration official) who— 

(A) Is authorized to receive such 

requests; and 

(B) Did not participate in the 

determination that is the subject of the 

reconsideration request, or, if 

applicable, the timely error notice 

review process. 

(ii)(A) Must include a copy of the 

initial determination issued by CMS; 

and 

(B) Must contain a detailed, written 

explanation of the basis for the dispute, 

including supporting documentation. 

(iii) Must be made within 30 days of 

the date of the initial determination for 

which reconsideration is being 

requested via email to an address as 

specified by CMS in the governing 

documentation for the Innovation 

Center model for which CMS made the 

initial determination. 

(2) Requests that do not meet the 

requirements of paragraph (b)(1) of this 

section are denied. 

(3) Within 10 business days of 

receiving a request for reconsideration, 

the reconsideration official sends CMS 

and the model participant a written 

acknowledgement of receipt of the 

reconsideration request. This 

acknowledgement sets forth all of the 

following: 

(i) The review procedures. 

(ii) A schedule that permits each party 

to submit position papers and 

documentation in support of the party’s 

position for consideration by the 

reconsideration official. 

(4) If the request is regarding a modelspecific payment and the governing 

documentation specifies an initial 

timely error notice process, the model 

participant must satisfy the timely error 

notice requirements specified in the 

governing documentation before 

submitting a reconsideration request 

under paragraph (b) of this section. In 

the event that the model participant 

fails to timely submit an error notice 

with respect to a particular modelspecific payment, the reconsideration 

review process would not be available 

to the model participant with regard to 

that model-specific payment. 

(c) Standards for reconsideration. (1) 

The parties must continue to fulfill all 

responsibilities and obligations under 

the governing documentation during the 

course of any dispute arising under the 

governing documentation. 

(2) The reconsideration consists of a 

review of documentation that is 

submitted timely and in accordance 

with the standards specified by the 

reconsideration official and are 

enumerated in paragraph (b)(3) of this 

section. 

(3) The burden of proof is on the 

model participant to demonstrate to the 

reconsideration official with clear and 

convincing evidence that the 

determination is inconsistent with the 

terms of the governing documentation. 

(d) Reconsideration determination. (1) 

The reconsideration determination is 

based solely upon both of the following: 

(i) Position papers and supporting 

documentation that meet both of the 

following: 

(A) Submitted timely to the 

reconsideration official in accordance 

with the schedule specified in 

paragraph (b)(3)(ii) of this section. 

(B) The standards for submission 

under paragraph (b)(1) of this section. 

(ii) Documents and data that were 

timely submitted to CMS in the required 

format before CMS made the 

determination that is the subject of the 

reconsideration request. 

(2)(i) The reconsideration official 

issues the reconsideration 

determination to CMS and to the model 

participant in writing. 

(ii) Absent unusual circumstances, in 

which case the reconsideration official 

reserves the right to an extension upon 

written notice to the model participant, 

the reconsideration determination is 

issued within 60 days of receipt of 

timely filed position papers and 

supporting documentation in 

accordance with the schedule specified 

in paragraph (b)(3)(ii) of this section. 

(3) The reconsideration determination 

is final and binding 30 days after its 

issuance, unless the model participant 

or CMS timely requests review of the 

reconsideration determination in 

accordance with paragraphs (e)(1) and 

(2) of this section. 

(e) CMS Administrator review. The 

model participant or CMS may request 

that the CMS Administrator review the 

reconsideration determination. The 

request must meet both of the following: 

(1) Be made via email within 30 days 

of the date of the reconsideration 

determination to the address specified 

by CMS. 

(2) Include a copy of the 

reconsideration determination and a 

detailed written explanation of why the 

model participant or CMS disagrees 

with the reconsideration determination. 

(3) The CMS Administrator promptly 

sends the parties a written 

acknowledgement of receipt of the 

request for review. 

(4) The CMS Administrator sends the 

parties notice of the following: 

(i) Whether the request for review is 

granted or denied. 

(ii) If the request for review is granted, 

the review procedures and a schedule 

that permits each party to submit a brief 

in support of the party’s position for 

consideration by the CMS 

Administrator. 

(4) If the request for review is denied, 

the reconsideration determination is 

final and binding as of the date the 

request for review is denied. 

(5) If the request for review is granted 

all of the following occur: 

(i) The record for review consists 

solely of— 

(A) Timely submitted briefs and the 

evidence contained in the record of the 

proceedings before the reconsideration 

official; and 

(B) Evidence as set forth in the 

documents and data described in 

paragraph (d)(1)(ii) of this section. 

(ii) The CMS Administrator reviews 

the record and issues to CMS and to the 

model participant a written 

determination. 

(iii) The written determination of the 

CMS Administrator is final and binding 

as of the date the written determination 

is sent. 

■ 7. Adding Subpart D to read as 

follows: 

Subpart D—Increasing Organ Transplant 

Access (IOTA) Model 

Sec. 

512.400 Basis and scope. 

512.402 Definitions. Increasing Organ 

Transplant Access Model Scope and 

Participation. 

512.412 Participant eligibility and 

selection. 

512.414 Patient population. Performance 

Assessment and Scoring 

512.422 Overview of performance 

assessment and scoring. 

512.424 Achievement Domain. 

512.426 Efficiency Domain. 

512.428 Quality Domain Payment. 

512.430 Upside risk payment, downside 

risk payment, and neutral zone. 

512.434 Targeted review. 

512.436 Extreme and uncontrollable 

circumstances. Data Sharing. 

512.440 Data sharing. 


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512.442 Transparency requirements. 

512.446 Health Equity Plans. Beneficiary 

Protections, Financial Arrangements, 

Beneficiary Incentives, and Compliance. 

512.450 Required beneficiary notifications. 

512.452 Financial sharing arrangements 

and attributed patient engagement 

incentives. 

512.454 Distribution arrangements. 

512.455 Enforcement authority. 

512.456 Beneficiary incentive: Part B and 

Part D immunosuppressive drug cost 

sharing support. 

512.458 Attributed patient engagement 

incentives. 

512.459 Application of the CMS-sponsored 

Model Arrangements and Patient 

Incentives Safe Harbor. 

512.460 Audit rights and records retention. 

512.462 Compliance and monitoring. 

512.464 Remedial action. 

512.466 Termination. 

512.468 Bankruptcy and other notifications. 

Waivers. 

512.470 Waivers. 

Subpart D—Increasing Organ 

Transplant Access (IOTA) Model 

§ 512.400 Basis and scope. 

(a) Basis. This subpart implements the 

test of the Increasing Organ Transplant 

Access (IOTA) Model under section 

1115A(b) of the Act. 

(b) Scope. This subpart sets forth the 

following: 

(1) The method for selecting IOTA 

participants. 

(2) The patient population. 

(3) The methodology for IOTA 

participant performance assessment and 

scoring for purposes of the achievement 

domain, efficiency domain, and quality 

domain, including beneficiary 

attribution and transplant target 

calculation. 

(4) The schedule and methodologies 

for the upside risk payment and 

downside risk payment. 

(5) Data sharing. 

(6) Other IOTA Model requirements. 

(7) Beneficiary protections. 

(8) Financial arrangements. 

(9) Monitoring. 

(10) Evaluation. 

(11) Termination. 

(12) Except as specifically noted in 

this subpart, the regulations under this 

subpart do not affect the applicability of 

other provisions affecting providers and 

suppliers under Medicare fee for 

service, including the applicability of 

provisions regarding payment, coverage, 

or program integrity. 

(c) Applicability. IOTA participants 

are subject to the standard provisions 

for Innovation Center models specified 

in subpart A of this part 512 and in 

subpart K of part 403 of this chapter. 

§ 512.402 Definitions. 

For purposes of this subpart, the 

following definitions apply. 

Achievement domain means the 

performance assessment category in 

which CMS assesses the IOTA 

participant’s performance based on the 

number of transplants performed 

relative to the transplant target. 

Alignment payment means a payment 

from an IOTA collaborator to an IOTA 

participant that is made in accordance 

with a sharing arrangement. 

Annual attribution reconciliation 

means the yearly process in which 

CMS— 

(1) Creates the final list of each IOTA 

participant’s attributed patients for the 

prior performance year by 

retrospectively de-attributing from each 

IOTA participant any attributed patients 

that satisfy a criterion for de-attribution 

under § 512.414(c); and 

(2) Creates a final list of each IOTA 

participant’s attributed patients who 

remain attributed for the performance 

year being reconciled, subject to the 

attribution criteria under 

§§ 512.414(b)(1) and (2). 

Annual attribution reconciliation list 

means the final cumulative record of 

attributed patients that CMS generates 

annually for whom each IOTA 

participant is accountable for during the 

applicable PY as described at 

§ 512.414(c)(2). 

Attributed patient means an IOTA 

waitlist patient or an IOTA transplant 

patient. 

Attribution means the process by 

which CMS identifies the patients for 

whom each IOTA participant is 

accountable during the model 

performance period, as described in 

§ 512.414. 

Baseline year means a 12-month 

period within a 3-year historical 

baseline period, that begins 48 months 

(or 4 years) before the start of each 

model PY and ends 12 months (or 1 

year) before the start of each model PY, 

as described in § 512.424. 

Bypassed response means an organ 

offer not received due to expedited 

placement or a decision by a kidney 

transplant hospital to have all of its 

kidney transplant waitlist patients 

skipped during the organ allocation 

process based on a set of pre-defined 

filters selected by the kidney transplant 

hospital matching the characteristics of 

the potential organ to be transplanted. 

Critical access hospital (CAH) means 

a hospital as defined in section 

1861(mm)(1) of the Act. 

Change in control means at least one 

of the following: 

(1) The acquisition by any ‘‘person’’ 

(as this term is used in sections 13(d) 

and 14(d) of the Securities Exchange Act 

of 1934) of beneficial ownership (within 

the meaning of Rule 13d–3 promulgated 

under the Securities Exchange Act of 

1934), directly or indirectly, of voting 

securities of the IOTA participant 

representing more than 50 percent of the 

IOTA participant’s outstanding voting 

securities or rights to acquire such 

securities. 

(2) The acquisition of the IOTA 

participant by any other individual or 

entity. 

(3) Any merger, division, dissolution, 

or expansion of the IOTA participant. 

(4) The sale, lease, exchange, or other 

transfer (in one transaction or a series of 

transactions) of all or substantially all 

the assets of the IOTA participant. 

(5)(i) The approval and completion of 

a plan of liquidation of the IOTA 

participant; or 

(ii) An agreement for the sale or 

liquidation of the IOTA participant. 

Collaboration agent means an 

individual or entity that is not an IOTA 

collaborator and that is a member of a 

PGP, NPPGP, or TGP that has entered 

into a distribution arrangement with the 

same PGP, NPPGP, or TGP in which he 

or she is an owner or employee, and 

where the PGP, NPPGP, or TGP is an 

IOTA collaborator. 

Composite graft survival rate means 

the rolling unadjusted total number of 

functioning grafts relative to the total 

number of adult kidney transplants 

performed, as described in § 512.428. 

CORF stands for comprehensive 

outpatient rehabilitation facility. 

Days means calendar days unless 

otherwise specified by CMS. 

Distribution arrangement means a 

financial arrangement between an IOTA 

collaborator that is an PGP, NPPGP, or 

TGP and a collaboration agent for the 

sole purpose of distributing some or all 

of a gainsharing payment received by 

the PGP, NPPGP, or TGP. 

Distribution payment means a 

payment from an IOTA collaborator that 

is a PGP, NPPGP, or TGP to a 

collaboration agent, under a distribution 

arrangement, composed only of 

gainsharing payments. 

Donation service area (DSA) means a 

geographical area of sufficient size to 

ensure maximum effectiveness in the 

procurement and equitable distribution 

of organs and that either includes an 

entire metropolitan statistical area 

(MSA) or does not include any part of 

such an area and that meets the 

standards of 42 CFR part 486 subpart G 

as defined in 42 CFR 486.302. 

Downside risk payment means the 

lump sum payment the IOTA 

participant must pay to CMS after the 

close of a performance year if the IOTA 

participant’s final performance score 

falls within the ranges specified in 

§ 512.430. 


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Efficiency domain means the 

performance assessment category in 

which CMS assesses the IOTA 

participant’s performance using the 

organ offer acceptance rate ratio as 

described in § 512.426. 

EFT stands for electronic funds 

transfer. 

Eligible attributed patient means an 

attributed patient that receives 

immunosuppressive drug coverage 

through Part B or Part D but that does 

not have secondary insurance that could 

provide cost sharing support. 

Final performance score means the 

sum total of the scores earned by the 

IOTA participant across the 

achievement domain, efficiency 

domain, and quality domain for a given 

PY. 

Gainsharing payment means a 

payment that is made from an IOTA 

participant to an IOTA collaborator, 

under a sharing arrangement as set forth 

in § 512.452 and in accordance with 

§ 512.452(c). 

Health equity goals mean the targeted 

outcomes relative to the health equity 

plan performance measures for the first 

PY and all subsequent PYs. 

Health equity plan intervention means 

the initiative(s) the IOTA participant 

creates and implements to reduce target 

health disparities. 

Health equity plan performance 

measure(s) means one or more 

quantitative metrics that the IOTA 

participant uses to measure the 

reductions in target health disparities 

arising from the health equity plan 

interventions. 

Health equity project plan means the 

timeline for the IOTA participant to 

implement the IOTA participant’s 

health equity plan. 

HHA means a Medicare-enrolled 

home health agency. 

Hospital has the meaning set forth in 

section 1861(e) of the Act. 

Improvement benchmark rate means 

120 percent of the IOTA participants’ 

performance on the organ offer 

acceptance rate ratio as specified under 

§ 512.426(c)(1)(ii)(A). 

Initial attribution means the process 

by which CMS identifies and 

prospectively attributes patients who 

meet the criteria specified under 

§ 512.414(a)(2)(b) to an IOTA participant 

prior to the model start date. 

IOTA activities mean the activities 

related to promoting accountability for 

the quality, cost, and overall care for 

attributed patients and performance 

across the achievement domain, 

efficiency domain and quality domain, 

including any of the following: 

(1) Managing and coordinating care. 

(2) Encouraging investment in 

infrastructure and redesigned care 

processes for high quality and efficient 

service delivery. 

(3) The provision of items and 

services pre- or post-transplant in a 

manner that reduces costs and improves 

quality. 

(4) Carrying out any other obligation 

or duty under the IOTA Model. 

IOTA collaborator means the 

following Medicare-enrolled providers 

and suppliers that enter into a sharing 

arrangement with an IOTA participant: 

(1) Nephrologist. 

(2) ESRD facility. 

(3) Skilled nursing facility (SNF). 

(4) Home health agency (HHA). 

(5) Long-term care hospital (LTCH). 

(6) Inpatient rehabilitation facility 

(IRF). 

(7) Physician. 

(8) Nonphysician practitioner. 

(9) Therapist in a private practice. 

(10) CORF. 

(11) Provider or supplier of outpatient 

therapy services. 

(12) Physician group practice (PGP). 

(13) Hospital. 

(14) CAH. 

(15) Non-physician provider group 

practice (NPPGP). 

(16) Therapy group practice (TGP). 

IOTA participant means a kidney 

transplant hospital, as defined at 

§ 512.402, that is required to participate 

in the IOTA Model under § 512.412. 

IOTA transplant patient means a 

kidney transplant patient who receives 

a kidney transplant at the age of 18 

years of age or older from an IOTA 

participant at any time during the model 

performance period and meets the 

criteria set forth in § 512.414(b)(2). 

IOTA waitlist patient means a kidney 

transplant waitlist patient, regardless of 

payer type and waitlist status, who 

meets all of the following: 

(1) Is alive. 

(2) 18 years of age or older. 

(3) Registered on a waitlist (as defined 

in § 512.402) to one or more IOTA 

participants, as identified by the OPTN 

computer match program. 

IRF stands for inpatient rehabilitation 

facility which must meet all of the 

following: 

(1) The general criteria set forth in 

§ 412.22. 

(2) The criteria to be classified as a 

rehabilitation hospital or rehabilitation 

unit set forth in §§ 412.23(b), 412.25, 

and 412.29 for exclusion from the 

inpatient hospital prospective payment 

systems specified in § 412.1(a)(1). 

Kidney transplant means the 

procedure in which a kidney is 

surgically transplanted from a living or 

deceased donor to a transplant 

recipient, either alone or in conjunction 

with any other organ(s). 

Kidney transplant hospital means a 

transplant hospital with a Medicare 

approved kidney transplant program. 

Kidney transplant patient means a 

patient who was a transplant candidate, 

as defined in § 121.2, and received a 

kidney transplant furnished by a kidney 

transplant hospital, regardless of payer 

type. 

Kidney transplant waitlist patient 

means a patient who is a transplant 

candidate, as defined in § 121.2, and 

who is registered to a waitlist for a 

kidney at one or more kidney transplant 

hospitals. 

LTCH stands for long-term care 

hospital that meets the requirements as 

stated in 42 CFR part 483 subpart B. 

Match run means a computerized 

ranking of transplant candidates based 

upon donor and candidate medical 

compatibility and criteria defined in 

OPTN policies. 

Medicare kidney transplant means a 

kidney transplant furnished to a 

attributed patient in the IOTA Model 

whose primary or secondary insurance 

is Medicare fee for service (FFS), as 

identified in Medicare FFS claims with 

MS–DRGs 008, 019, 650, 651, and 652. 

Member of the NPPGP or NPPGP 

member means a nonphysician 

practitioner or therapist who is an 

owner or employee of an NPPGP and 

who has reassigned to the NPPGP their 

right to receive Medicare payment. 

Member of the PGP or PGP member 

means a physician, nonphysician 

practitioner, or therapist who is an 

owner or employee of the PGP and who 

has reassigned to the PGP their right to 

receive Medicare payment. 

Member of the TGP or TGP member 

means a therapist who is an owner or 

employee of a TGP and who has 

reassigned to the TGP their right to 

receive Medicare payment. 

Missing responses means organ offers 

that a kidney transplant hospital 

received from the OPO but did not 

submit a response (accepting or 

rejecting) in the allotted 1-hour 

timeframe from the time the offer was 

made per OPTN policy 5.6.B. 

Model performance period means the 

72-month period from the model start 

date and is comprised of 6 individual 

performance years. 

Model-specific payment means a 

payment made by CMS only to IOTA 

participants, or a payment adjustment 

made only to payments made to IOTA 

participants, under the terms of the 

IOTA Model that is not applicable to 

any other providers or suppliers and 

includes, unless otherwise specified, 

both of the following: 


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(1) The IOTA Model upside risk 

payment. 

(2) The IOTA Model downside risk 

payment. 

Model start date means the date on 

which the model performance period 

begins, July 1, 2025. 

National growth rate means the 

percentage increase or decrease in the 

number of kidney transplants performed 

over a 12-month period by all kidney 

transplant hospitals except for pediatric 

kidney transplant hospitals, as defined 

at § 512.402. 

National Provider Identifier (NPI) 

means the standard unique health 

identifier used by health care providers 

for billing payors, assigned by the 

National Plan and Provider 

Enumeration System (NPPES) in 

accordance with 45 CFR part 162. 

Neutral zone means the final 

performance score range in which the 

IOTA participant neither owes a 

downside risk payment to CMS nor 

receives an upside-risk payment from 

CMS, in accordance with 

§ 512.430(b)(2). 

Non-pediatric facility means a kidney 

transplant hospital that furnishes more 

than 50 percent of their kidney 

transplants annually to patients 18 years 

of age or older. 

Nonphysician practitioner means 

(except for purposes of 42 CFR part 510 

subpart G) one of the following: 

(1) A physician assistant who satisfies 

the qualifications set forth at 

§ 410.74(a)(2)(i) and (ii) of this chapter. 

(2) A nurse practitioner who satisfies 

the qualifications set forth at § 410.75(b) 

of this chapter. 

(3) A clinical nurse specialist who 

satisfies the qualifications set forth at 

§ 410.76(b) of this chapter. 

(4) A certified registered nurse 

anesthetist (as defined at § 410.69(b)). 

(5) A clinical social worker (as 

defined at § 410.73(a)). 

(6) A registered dietician or nutrition 

professional (as defined at § 410.134). 

NPPGP means an entity that is 

enrolled in Medicare as a group 

practice, includes at least one owner or 

employee who is a nonphysician 

practitioner, does not include a 

physician owner or employee, and has 

a valid and active TIN. 

OPTN computer match program 

means a set of computer-based 

instructions which compares data on a 

cadaveric organ donor with data on 

transplant candidates on the waiting list 

and ranks the candidates according to 

OPTN policies to determine the priority 

for allocating the donor organ(s). 

Organ procurement and 

transplantation network or OPTN means 

the network established under section 

372 of the Public Health Service Act. 

Organ procurement organization or 

OPO means an entity designated by the 

Secretary under section 1138(b) of the 

Act and under 42 CFR 486.304. 

Part B and Part D immunosuppressive 

drug cost sharing support means cost 

sharing support related to 

immunosuppressive drugs covered by 

Medicare Part B, the Medicare Part B 

Immunosuppressive Drug Benefit (Part 

B–ID), or Medicare Part D that is 

provided by an IOTA participant to an 

eligible attributed patient as codified at 

§ 512.456. 

Pediatric kidney transplant hospital 

means a kidney transplant hospital that 

performs 50 percent or more of its 

transplants in a 12-month period on 

patients under the age of 18. 

Performance year (PY) means a 12- 

month period beginning on July 1 and 

ending on June 30 of each year during 

the model performance period. 

PGP stands for physician group 

practice. 

Physician has the meaning set forth in 

section 1861(r) of the Act. 

Post-transplant period means the 90- 

day period following an attributed 

patient’s receipt of a kidney transplant. 

Preliminary performance assessment 

and payment calculations means the 

process by which CMS— 

(1) Assesses each IOTA participant’s 

performance in accordance with 

§§ 512.424, 512.426, 512.428; and 

(2) Calculates performance-based 

payments in accordance with § 512.430. 

Provider of outpatient therapy 

services means an entity that is enrolled 

in Medicare as a provider of therapy 

services and furnishes one or more of 

the following: 

(1) Outpatient physical therapy 

services as defined in § 410.60 of this 

chapter. 

(2) Outpatient occupational therapy 

services as defined in § 410.59 of this 

chapter. 

(3) Outpatient speech-language 

pathology services as defined in 

§ 410.62 of this chapter. 

Quality domain means the 

performance assessment category in 

which CMS assesses the IOTA 

participant’s performance using a 

performance measure focused on 

improving the quality of transplant care 

as described in § 512.428. 

Quality Health Information Network 

(QHIN) means a network of 

organizations that agrees to common 

terms and conditions regarding data 

exchange with each other (a ‘‘Common 

Agreement’’) and to the functional and 

technical requirements for such data 

exchange (as specified in the QHIN 

Technical Framework or ‘‘QTF’’) under 

section 4003(b) of the 21st Century 

Cures Act (Pub. L. 114–255). 

Quarterly attribution list means the 

quarterly CMS-generated attributed 

patient list that CMS provides to the 

IOTA participant in advance of each 

quarter during the model performance 

period in accordance with 

§ 512.414(c)(ii)(2). 

Resource gap analysis means the 

resources needed to implement the 

health equity plan interventions and 

identifies any gaps in the IOTA 

participant’s current resources and the 

additional resources needed. 

Scientific Registry of Transplant 

Recipients or SRTR means the registry 

of information on transplant recipients 

established under section 373 of the 

Public Health Service Act. 

Selected DSAs means those DSAs 

selected by CMS for purposes of 

selecting kidney transplant hospitals for 

participation in the IOTA Model. 

Sharing arrangement means a 

financial arrangement to only share the 

upside risk payment and the downside 

risk payment lump-sum amount as set 

forth in § 512.452. 

SNF stands for skilled nursing facility 

that meets all applicable requirements 

in section of 1819 of the Act. 

Target health disparities mean health 

disparities experienced by one or more 

communities within the IOTA 

participant’s population of attributed 

patients that the IOTA participant aims 

to reduce. 

Targeted review process means the 

process in which an IOTA participant 

may dispute performance and payment 

calculations made, and issued, by CMS 

as set forth in § 512.434. 

TGP means an entity that is enrolled 

in Medicare as a therapy group in 

private practice, includes at least one 

owner or employee who is a therapist in 

private practice, does not include an 

owner or employee who is a physician 

or nonphysician practitioner, and has a 

valid and active TIN. 

Therapist means one of the following 

individuals as defined at § 484.4 of this 

chapter: 

(1) Physical therapist. 

(2) Occupational therapist. 

(3) Speech-language pathologist. 

Therapist in private practice means a 

therapist that complies with one of the 

following special provisions: 

(1) For physical therapists in private 

practice in § 410.60(c) of this chapter. 

(2) For occupational therapists in 

private practice in § 410.59(c) of this 

chapter. 

(3) For speech-language pathologists 

in private practice in § 410.62(c) of this 

chapter. 

Taxpayer identification number (TIN) 

means a Federal taxpayer identification 


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number or employer identification 

number as defined by the Internal 

Revenue Service in 26 CFR 301.6109–1. 

Transplant hospital means a hospital 

that furnishes organ transplants as 

defined in 42 CFR 121.2. 

Transplant physician means a 

physician who provides non-surgical 

care and treatment to transplant patients 

before and after transplant as defined in 

42 CFR 121.2. 

Transplant program means a 

component within a transplant hospital 

which provides transplantation of a 

particular type of organ as defined in 42 

CFR 121.2. 

Transplant recipient means a person 

who has received an organ transplant as 

defined in 42 CFR 121.2. 

Transplant target means the target 

number of kidney transplants calculated 

by CMS for the IOTA participant to 

measure the IOTA participant’s 

performance in the achievement 

domain, as described in § 512.424. 

Underserved communities mean 

populations sharing a particular 

characteristic, as well as geographic 

communities, that have been 

systematically denied a full opportunity 

to participate in aspects of economic, 

social, and civic life as defined by 

Executive Order 13985 of January 20, 

2021. 

Upside risk payment means the lump 

sum payment CMS makes to an IOTA 

participant if the IOTA participant’s 

final performance score for a 

performance year falls within the 

payment range specified in § 512.430. 

Waitlist means a list of transplant 

candidates, as defined in 42 CFR 121.2, 

registered to the waiting list, as defined 

in 42 CFR 121.2, maintained by a 

transplant hospital in accordance with 

42 CFR 482.94(b). 

Increasing Organ Transplant Access 

Model Scope and Participation 

§ 512.412 Participant eligibility and 

selection. 

(a) Participant eligibility. A kidney 

transplant hospital is eligible to be 

selected as an IOTA participant, in 

accordance with the methodology 

described in paragraph (c) of this 

section, if the kidney transplant hospital 

meets both of the following criteria: 

(1) The kidney transplant hospital 

annually performed 11 or more kidney 

transplants for patients aged 18 years or 

older, regardless of payer, each of the 

baseline years. 

(2) The kidney transplant hospital 

annually performed more than 50 

percent of its kidney transplants on 

patients 18 years of age or older each of 

the baseline years. 

(b) IOTA participant selection. CMS 

uses the following process to select 

IOTA participants for inclusion in the 

model. 

(1) DSA stratification criteria. CMS 

uses the following criteria to stratify 

DSAs using the list of DSAs as of 

January 1, 2024: 

(i) Census division of the DSA. 

(ii) Total number of adult kidney 

transplants performed per year across 

eligible kidney transplant hospitals in 

the DSA during PY 1’s baseline years. 

(2) DSA stratification process. Prior to 

sampling DSAs, CMS uses the following 

steps to group DSAs into mutually 

exclusive groups. 

(i) CMS assigns each DSA to one of 

the nine Census Divisions. CMS assigns 

each DSA to the Census Division where 

the majority of the DSA’s population 

resides. CMS determines each DSA’s 

population, and the share of a DSA’s 

population in the applicable Census 

Division(s) using data from the 2020 

Census. 

(A) CMS assigns the Puerto Rico DSA 

to the South Atlantic Census Divisions. 

(B) CMS combines the Middle 

Atlantic and New England Census 

Divisions and all DSAs therewithin 

creating eight groups of Census 

Divisions. 

(ii) CMS identifies all kidney 

transplant hospitals located in each 

DSA within each Census Division 

group. 

(iii) For each DSA within its assigned 

Census Division group, CMS identifies 

the eligible kidney transplant hospitals 

using the criteria specified in paragraph 

(a) of this section. 

(iv) Using data from each of the 

baseline years for PY 1, CMS determines 

the average number of adult kidney 

transplants performed annually by 

eligible transplant hospitals located in 

each DSA as follows: 

(A) Sums the number of adult kidney 

transplants performed across eligible 

kidney transplant hospitals in a DSA 

during each of the baseline years for PY 

1; and 

(B) Divides each DSA’s sum resulting 

from the calculation in paragraph 

(b)(2)(iv)(A) of this section by three to 

determine the average number of adult 

kidney transplants furnished during the 

baseline years for PY 1. 

(v) CMS separates DSAs in each 

Census Division group into two 

mutually exclusive groups of the same 

size, based on the average number of 

adult kidney transplants performed 

annually across the baseline years for 

PY 1, except where there are an odd 

number of DSAs within a Census 

Division group: 

(A) DSAs with a higher number of 

adult kidney transplants per year across 

the baseline years for PY 1. 

(B) DSAs with a lower number of 

adult kidney transplants per year across 

the baseline years for PY 1. 

(vi) Where there are an odd number 

of DSAs within a Census Division group 

CMS uses the methodology set forth in 

paragraph (b)(3) of this section. 

(3) Random sampling of DSAs. (i) For 

each DSA group within a Census 

Division group containing an odd 

number of DSAs, CMS randomly selects 

one DSA and determines its 

participation in the IOTA Model with a 

50 percent probability. 

(ii) CMS randomly samples, without 

replacement, 50 percent of the 

remaining DSAs in each group within 

each Census Division group created in 

paragraph (b)(2)(v) of this section. 

(c) Selection of IOTA participants in 

selected DSAs. All eligible kidney 

transplant hospitals in the selected 

DSAs are required to participate in the 

IOTA Model. 

(d) Notification of participation. CMS 

notifies IOTA participants of their 

selection to participate in the IOTA 

Model in a form and manner chosen by 

CMS at least 3 months prior to the start 

of the model performance period. 

§ 512.414 P Patient population. 

(a) General. (1) CMS attributes kidney 

transplant waitlist patients and kidney 

transplant patients to IOTA participants 

based on the attribution criteria as 

described in paragraphs (b)(1) and (b)(2) 

of this section, for all of the following 

purposes: 

(i) Sharing Medicare claims data for 

attributed beneficiaries with IOTA 

participants. 

(ii) Assessing each IOTA participant’s 

performance across the achievement 

domain, efficiency domain, and quality 

domain. 

(iii) Determining performance-based 

payments paid to or by IOTA 

participants. 

(2) Once a kidney transplant waitlist 

patient or kidney transplant patient is 

attributed to an IOTA participant, that 

respective patient may not opt out of 

attribution to an IOTA participant and 

remains attributed to the IOTA 

participant for the duration of the model 

performance period, unless the 

attributed patient meets the deattribution criteria under paragraph 

(b)(3) of this section during annual 

attribution reconciliation as described 

in paragraph (b)(3) of this section. 

(b) Patient attribution and deattribution criteria—(1) IOTA waitlist 

patient attribution. (i) At the time CMS 

conducts attribution, as described in 


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paragraph (c) of this section, if a kidney 

transplant waitlist patient meets the 

definition of an IOTA waitlist patient, as 

defined at § 512.402, CMS attributes the 

kidney transplant waitlist patient as an 

IOTA waitlist patient to an IOTA 

participant. 

(2) IOTA transplant patient 

attribution. (i) At the time CMS 

conducts attribution, as described in 

paragraph (c) of this section, CMS 

attributes a kidney transplant patient as 

an IOTA transplant patient if the kidney 

transplant patient meets all of the 

following: 

(A) The definition of an IOTA 

transplant patient, as defined at 

§ 512.402. 

(B) Is 18 years of age or older at the 

time of the patient’s kidney transplant. 

(C) Is alive. 

(3) De-attribution from an IOTA 

participant. During annual attribution 

reconciliation, CMS uses the fourth 

quarter attribution list for each IOTA 

participant and de-attributes any 

attributed patients who, as of the last 

day of the PY being reconciled, meet 

any of the following de-attribution 

criteria: 

(A) An IOTA waitlist patient that was 

removed from and remains unregistered 

on an IOTA participant’s kidney 

transplant waitlist. 

(B) An IOTA waitlist patient that has 

died at any point during the PY. 

(C) An IOTA transplant patient that 

has died at any point during the PY. 

(D) An IOTA transplant patient who 

experiences transplant failure at any 

point during the model performance 

period and has not rejoined an IOTA 

participant’s kidney transplant waitlist 

or received another transplant from an 

IOTA participant before the last day of 

the respective PY. 

(c) Attribution methodology. CMS 

employs the following methodology to 

attribute kidney waitlist patients and 

kidney transplant patients to an IOTA 

participant after identifying all kidney 

waitlist patients and kidney transplant 

patients that meet the attribution criteria 

as specified in paragraphs (b)(1) and 

(b)(2) of this section: 

(1)(i) Initial attribution. Prior to the 

model start date, CMS conducts initial 

attribution, as defined at § 512.402. 

(ii) Initial attribution list. (A) CMS 

provides the initial attribution list to the 

IOTA participant no later than 15 days 

prior to the start of PY 1 and in a form 

and manner as determined by CMS. 

(B) The initial attribution list includes 

a list of IOTA waitlist patients identified 

through initial attribution, effective on 

the model start date. 

(2)(i) Quarterly attribution. CMS 

conducts attribution, as defined at 

§ 512.402, on a quarterly basis after the 

model start date, and updates the 

quarterly attribution list, as defined at 

§ 512.402, for each IOTA participant, 

except in the event of termination in 

accordance with § 512.466. 

(ii) Quarterly attribution list. CMS 

provides the quarterly attribution list, as 

defined at § 512.402, to the IOTA 

participant no later than 15 days prior 

to the start of each quarter and in a form 

and manner determined by CMS. The 

quarterly attribution list includes, at 

minimum, all of the following: 

(A) A list of all newly attributed 

patients, whose attribution to the IOTA 

participant becomes effective on the 

first day of the relevant upcoming 

quarter. 

(B) A list of all attributed patients 

who continue to be attributed to the 

IOTA participant from the previous 

quarter. 

(C) The dates in which attribution 

began, changed, or ended, where 

applicable for attributed patients. 

(D) The attributed patient’s data 

sharing preferences under § 512.440(b). 

(3)(i) Annual attribution 

reconciliation. After the fourth quarter 

of each PY, CMS conducts annual 

attribution reconciliation as defined at 

§ 512.402. 

(ii) Annual attribution reconciliation 

list. CMS provides the annual 

reconciliation list to the IOTA 

participant before the second quarter of 

the following PY. Using the fourth 

quarter quarterly attribution list for each 

IOTA participant, the annual attribution 

reconciliation list identifies, at a 

minimum, all of the following, where 

applicable: 

(A) A list of all attributed patients 

who remain attributed to the IOTA 

participant because they satisfied the 

attribution criteria under 

§§ 512.414(b)(1) and (2) for the 

respective PY. 

(B) The dates in which attribution 

began, changed, or ended, where 

applicable. 

(C) A list of all attributed patients 

who are de-attributed because they 

failed to satisfy the attribution criteria 

under § 512.414(b)(1) and (2). 

(D) A list of all attributed patients 

who are de-attributed because they 

satisfy a de-attribution criterion under 

§ 512.414(b)(3). 

(E) The dates on which each 

attributed patient satisfied a deattribution criterion as specified under 

§ 512.414(b)(3). 

(F) A list of the de-attribution 

criterion each attributed patient 

satisfied under § 512.414(b)(3). 

Performance Assessment and Scoring 

§ 512.422 Overview of performance 

assessment and scoring. 

(a) General. (1) CMS establishes the 

performances measures described in 

§§ 512.424, 512.426, and 512.428 to 

assess IOTA participants in the 

achievement domain, efficiency domain 

and quality domain. 

(2) CMS assigns each set of metrics 

within a domain a point value with the 

total possible points awarded to an 

IOTA participant across the three 

domains equaling 100, as described in 

§§ 512.424, 512.426, and 512.428. 

(b) Data sources. (1) CMS uses 

Medicare claims data and Medicare 

administrative data about beneficiaries, 

providers, suppliers, and data from the 

OPTN, to calculate performance for the 

IOTA participant based on the 

methodologies under §§ 512.424, 

512.426, and 512.428. 

(2) CMS may also use model-specific 

data reported by an IOTA participant to 

CMS under the IOTA Model to calculate 

IOTA participant performance in the 

domains. 

§ 512.424 Achievement domain. 

(a) General. (1) After each PY, CMS 

calculates the number of kidney 

transplants that each IOTA participant 

performed for the respective PY, in 

accordance with the provisions in 

paragraph (d) of this section. 

(2) CMS compares the number of 

kidney transplants that an IOTA 

participant performed during the PY to 

the IOTA participant’s transplant target 

to determine the IOTA participant’s 

score for the achievement domain. 

(b) Transplant target methodology. 

CMS determines the IOTA participant’s 

transplant target for each PY as follows: 

(1) Analysis of baseline years. CMS 

analyzes the baseline years for the 

relevant PY and identifies: 

(i) The mean number of deceased 

donor kidney transplants furnished by 

the IOTA participant to patients 18 

years of age or older across the baseline 

years, as defined at § 512.402; and 

(ii) The mean number of living donor 

kidney transplants furnished by the 

IOTA participant to patients 18 years of 

age or older across the baseline years, as 

defined at § 512.402. 

(2) Mean of kidney transplants. CMS 

sums the numbers in paragraphs (b)(1)(i) 

and (ii) of this section. 

(3) National growth rate calculation. 

CMS calculates the national growth rate, 

as defined at § 512.402, using the 

baseline years for the relevant PY as 

follows: 

(i) Subtracts the total number of 

kidney transplants furnished to patients 


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18 years of age or older during the 

second baseline year from the total 

number of kidney transplants furnished 

to patients 18 years of age or older 

during the third baseline year. 

(ii) Divides the amount resulting from 

the calculation in paragraph (b)(3)(i) of 

this section by the total number of 

kidney transplants furnished to patients 

18 years of age or older during the third 

baseline year. The resulting amount is 

the national growth rate for the relevant 

PY. 

(4) Calculation of transplant target. If 

the national growth rate calculated in 

paragraph (b)(3) of this section is— 

(i) Positive, CMS multiples that 

national growth rate by the sum 

calculated in paragraph (b)(2) of this 

section. The resulting amount is an 

IOTA participant’s transplant target for 

the relevant PY; or 

(ii) Negative, CMS does not multiply 

the national growth rate by the sum 

calculated in paragraph (b)(2) of this 

section. The IOTA participant’s 

transplant target for the relevant PY is 

the sum calculated in paragraph (b)(2) of 

this section. 

(c) Notification of transplant target. 

CMS notifies the IOTA participant of 

the transplant target by the first day of 

the start of each PY in a form and 

manner determined by CMS. 

(d) Calculation of kidney transplants 

performed during the PY. (1)(i) After 

each PY, CMS counts the number of 

kidney transplants performed by the 

IOTA participant on patients who were 

18 years of age or older at the time of 

transplant, during the PY. 

(ii) CMS identifies kidney transplants 

performed by the IOTA participant 

using OPTN data, regardless of payer, 

and Medicare claims data. 

(2) CMS counts each kidney 

transplant described in paragraph (d)(1) 

of this section as one transplant. 

(e) [Reserved] 

(f) Achievement domain scoring. For 

each PY, CMS awards the IOTA 

participant zero to 60 points for its 

performance in the achievement 

domain. 

(1) CMS compares the total number of 

kidney transplants identified under 

paragraph (d)(2) of this section to the 

IOTA participant’s transplant target, as 

described in paragraph (b) of this 

section. 

(2) CMS uses the following scoring 

methodology to determine an IOTA 

participant’s score on the achievement 

domain. 

Table 1 to Paragraph (f)(2)—IOTA 

Model Achievement Domain Scoring 

Methodology 

§ 512.426 Efficiency domain. 

(a) General. For each PY, CMS 

assesses each IOTA participant on the 

metric described in paragraph (b) of this 

section to determine the IOTA 

participant’s score for the efficiency 

domain. 

(b) Metric included in the efficiency 

domain. For each PY, CMS assesses the 

IOTA participant on the following 

metric: 

(1) Organ-offer acceptance rate ratio. 

For each PY, CMS calculates the organoffer acceptance rate ratio by dividing 

the number of kidneys the IOTA 

participant accepted by the riskadjusted number of expected organ-offer 

acceptances using SRTR’s methodology 

as described in equation 1 to paragraph 

(b)(1) introductory text of this section. 

Equation 1 to Paragraph (b)(1) 

introductory text: Organ Offer 

Acceptance Rate Ratio 

(i) CMS uses both of the following: 

(A) SRTR data to calculate the organoffer acceptance rate ratio. 

(B) SRTR’s adult kidney model strata 

risk-adjustment methodology and most 

available set of coefficients to calculate 

the number of expected organ-offer 

acceptances. 

(ii) CMS includes all of the following 

kidney offers when calculating the 

organ-offer acceptance rate ratio for the 

IOTA participant: 

(A) Offers that are ultimately accepted 

and transplanted. 

(B) Offers to candidates on a single 

organ waitlist (except for kidney/ 

pancreas candidates that are also listed 

for kidney alone). 

(iii) CMS excludes the following 

kidney offers when calculating the 

organ-offer acceptance rate: 

(A) Offers with multiple match runs 

from the same donor combined and 

duplicate offers. 

(B) Offers with no match run 

acceptances. 

(C) Offers that occurred after the last 

acceptance in a match run. 

(D) Offers with a missing or bypassed 

response. 

(E) Offers to multi-organ candidates 

(except for kidney/pancreas candidates 

that are also listed for kidney alone). 

(c) Efficiency domain scoring. For 

each PY, CMS awards the IOTA 

participant 0 to 20 points for its 

performance in the efficiency domain. 


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Performance Relative to Lower Bound Upper Bound 

Transplant Target Condition Condition Points Earned 

125% of transplant target Equals 125% Greater than 125% 60 

120% of transplant target Equals 120% Less than 125% 55 

115% of transplant target Equals 115% Less than 120% 50 

105% of transplant target Equals 105% Less than 115% 40 

95% of transplant target Equals 95% Less than 105% 30 

85% of transplant target Equals 85% Less than 95% 20 

75% of transplant target Equals 75% Less than 85% 10 

75% of transplant target NIA Less than 75% 0 

Organ Offer Acceptance Rate Ratio 

Number of Acceptances + 2 

Number of Expected Acceptances + 2 
96452 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

(1) General. CMS determines the 

IOTA participant’s score for the 

efficiency domain for each PY by taking 

the IOTA participant’s score for the 

organ offer acceptance rate ratio, as 

described under paragraph (c)(2) of this 

section. This number is the IOTA 

participant’s score for the efficiency 

domain for the PY. 

(2) Scoring for organ offer acceptance 

rate ratio. CMS calculates the IOTA 

participant’s achievement score, as 

described in paragraph (c)(2)(i) of this 

section, and improvement score, as 

described under paragraph (c)(2)(ii) of 

this section, for the organ offer 

acceptance rate ratio, compares the 

IOTA participant’s achievement score 

and improvement score and awards to 

the IOTA participant the points that 

correspond to the higher score. 

(i) Achievement scoring. CMS 

calculates the IOTA participant’s 

achievement score based on the IOTA 

participant’s performance on organ offer 

acceptance rate ratio relative to national 

ranking, including all eligible kidney 

transplant hospitals, using the scoring 

methodology described in table 1 to 

paragraph (c)(1)(i) of this section. 

Table 1 to Paragraph (c)(1)(i)—IOTA 

Model Organ Offer Acceptance Rate 

Ratio Achievement Scoring 

(ii) Improvement scoring. CMS 

compares the IOTA participant’s organ 

offer acceptance rate ratio during the 

PY, calculated as described under 

paragraph (c)(1)(i) of this section, to the 

IOTA participant’s improvement 

benchmark rate, calculated as described 

under paragraph (c)(1)(ii)(A) of this 

section. 

(A) Improvement benchmark rate. 

CMS calculates an improvement 

benchmark rate for the IOTA 

participant. To determine an IOTA 

participant’s improvement benchmark 

rate for a given PY, CMS multiplies an 

IOTA participant’s organ offer 

acceptance rate ratio during the third 

baseline year by 120 percent. 

(B) Improvement score calculation. 

For each PY, CMS uses the following 

methodology to determine each IOTA 

participant’s improvement score on the 

organ offer acceptance rate ratio: 

(1) If the IOTA participant’s organoffer acceptance rate ratio is greater than 

or equal to the improvement benchmark 

rate, CMS awards the IOTA participant 

15 points in the efficiency domain. 

(2) If the IOTA participant’s organ 

offer acceptance rate ratio is equal to or 

less than the IOTA participant’s organoffer acceptance rate ratio in the third 

baseline year for that respective PY, 

CMS awards the IOTA participant 0 

points in the efficiency domain. 

(3) If the IOTA participant’s organ 

offer acceptance rate ratio is greater than 

the IOTA participant’s organ-offer 

acceptance rate ratio in the third 

baseline year for that respective PY but 

less than the improvement benchmark 

rate, CMS uses the following equation: 

Equation 2 to Paragraph (c)(2)(ii)(B)(3)— 

IOTA Model Organ Offer Acceptance 

Rate Ratio Improvement Scoring 

Equation 

§ 512.428 Quality domain. 

(a) General. For each PY, CMS 

assesses each IOTA participant on the 

metric described under paragraph (b)(1) 

of this section to determine the IOTA 

participant’s quality domain score, as 

described under paragraphs (c) through 

(e) of this section, for the quality 

domain. 

(b) Metrics included in the quality 

domain. For each PY, CMS assesses 

each IOTA participant using the 

following quality metrics: 

(1) Post-transplant graft survival. For 

each PY, CMS calculates an IOTA 

participant’s composite graft survival 

rate by dividing the cumulative number 

of all functioning kidney grafts for the 

IOTA participant’s IOTA transplant 

patients by the cumulative number of all 

kidney transplants performed by the 

IOTA participant during the first PY and 

all subsequent PYs on patients 18 years 

or older at the time of the transplant, as 

described in equation 1 to paragraph 

(b)(1) introductory text of this section. 

Equation 1 to Paragraph (b)(1) 

introductory Text: Composite Graft 

Survival Rate 

(i) For the first PY, CMS calculates the 

IOTA participant’s composite graft 

survival rate based solely on the number 

of functioning grafts furnished to IOTA 

transplant patients during that PY and 

the number of completed kidney 

transplants during that PY, as described 

in paragraph (b)(1) of this section. 

(ii) For all subsequent PYs, CMS 

calculates the IOTA participant’s 

cumulative composite graft survival rate 

using the same calculation methodology 

described in paragraph (b)(1) of this 

section. 

(iii) CMS excludes the following from 

the numerator when calculating the 

composite graft survival rate: 

(A) Graft failure, based on OPTN adult 

kidney transplant recipient follow-up 


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Performance Relative to National Ranking Lower Bound Condition Uooer Bound Condition 

80th Percentile 

60th Percentile 

40th Percentile 

20th Percentile 

20th Percentile 

Equals 80th percentile Greater than 80th percentile 

Equals 60th percentile Less than 80th percentile 

Eauals 40th percentile Less than 60th percentile 

Equals 20th percentile Less than 40th percentile 

NIA Less than 20th percentile 

Rate Earned in Performance Year - Third Baseline Year Rate 

15 x Improvment Benchmark Rate - Third Baseline Year Rate 

# of Functioning Grafts 

Points Earned 

20 

15 

10 

6 

0 

Composite Graft Survival Rate 

# of Completed Kidney Transplants 
Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96453 

forms for all completed kidney 

transplants to determine failed grafts as 

defined by SRTR. 

(B) Re-transplant. 

(C) Death. 

(D) Patients who are under the age of 

18 years of age at the time of the kidney 

transplant. 

(E) Offers to multi-organ candidates 

(except for kidney/pancreas candidates 

that are also listed for kidney alone). 

(iv)(A) When calculating the 

composite graft survival rate, CMS only 

includes kidney transplants for patients 

who are 18 years of age and older at the 

time of the kidney transplant in the 

number of kidney transplants performed 

by the IOTA participant during each PY 

in the denominator. 

(B) CMS identifies kidney transplants 

performed by the IOTA participant 

using OPTN data, regardless of payer, 

and Medicare claims data. 

(2) [Reserved] 

(3) [Reserved] 

(c) Quality domain scoring. For each 

PY, CMS awards the IOTA participant 

zero to 20 points for the IOTA 

participant’s performance in the quality 

domain, in accordance with the 

following: 

(1) For composite graft survival rate, 

as described under paragraph (d) of this 

section, the IOTA participant may 

receive up to 20 points. 

(2) [Reserved] 

(d) Composite graft survival rate 

scoring. CMS awards points to the IOTA 

participant based on the IOTA 

participant’s performance on the 

composite graft survival rate, as 

described in paragraph (b)(1) of this 

section, ranked nationally, inclusive of 

all eligible kidney transplant hospitals. 

CMS awards points to the IOTA 

participant for composite graft survival 

rate as described in table 1 to paragraph 

(d) of this section: 

Table 1 to Paragraph (d)—IOTA Model 

Composite Graft Survival Rate Scoring 

Payment 

§ 512.430 Upside risk payment, downside 

risk payment, and neutral zone. 

(a) General. CMS determines if an 

IOTA participant qualifies for an upside 

risk payment, downside risk payment, 

or the neutral zone for each PY based on 

the IOTA participant’s final 

performance score, in accordance with 

paragraphs (b)(1) through (3) of this 

section. 

(b) Upside risk payment, neutral zone, 

and downside risk payment calculation 

methodology—(1) Upside risk payment 

calculation methodology. If in PYs 1–6 

the IOTA participant’s final 

performance score is 60 points or above, 

CMS calculates the IOTA participant’s 

upside risk payment as follows: 

(i) Subtracts 60 from the IOTA 

participant’s final performance score. 

(ii) Divides the amount resulting from 

the calculation in paragraph (b)(1)(i) of 

this section by 40. 

(iii) Multiplies the amount resulting 

from the calculation in paragraph 

(b)(1)(ii) of this section by $15,000. 

(iv) Multiplies the amount resulting 

from the calculation in paragraph 

(b)(1)(iii) of this section by the total 

number of Medicare kidney transplants 

performed by the IOTA participant 

during the PY. 

(2) Neutral zone. (i) For PY 1, an 

IOTA participant with a final 

performance score below 60 points 

qualifies for the neutral zone and 

neither owes a downside risk payment 

to CMS nor receives an upside risk 

payment from CMS. 

(ii) For PYs 2 through 6, if an IOTA 

participant’s final performance is 

between 41 to 59 points (inclusive), the 

IOTA participant qualifies for the 

neutral zone. 

(3) Downside risk payment 

calculation methodology. If an IOTA 

participant is at or below 40 points in 

PYs 1 through 6, the IOTA participant 

qualifies for a downside risk payment. 

The downside risk payment is 

calculated as follows: 

(i) For PY 1, this paragraph does not 

apply, and the IOTA participant does 

not owe a downside risk payment to 

CMS. 

(ii) For PYs 2 through 6, CMS 

calculates the IOTA participant’s 

downside risk payment as follows: 

(A) Subtracts the IOTA participant’s 

final performance score from 40. 

(B) Divides the amount resulting from 

the calculation in paragraph (b)(3)(ii)(A) 

of this section by 40. 

(C) Multiplies the amount resulting 

from the calculation in paragraph 

(b)(3)(ii)(B) of this section by $2,000. 

(D) Multiplies the amount resulting 

from the calculation in paragraph 

(b)(3)(ii)(C) of this section by the total 

number of Medicare kidney transplants 

performed by the IOTA participant 

during the PY to calculate the amount 

of the IOTA participant’s downside risk 

payment. 

(c) [Reserved] 

(d) Upside risk payment and 

downside risk payment timeline. (1) 

CMS conducts and calculates 

preliminary performance assessment 

and payment calculations at least 3 to 6 

months after the end of each PY. 

(2) CMS notifies the IOTA participant 

of their preliminary performance 

assessment and payment calculations in 

a form and manner determined by CMS 

at least 5 to 9 months after the end of 

each PY. 

(3) CMS gives IOTA participants 30 

days to review preliminary performance 

assessment and payment calculations 

and request targeted reviews under 

§ 512.434. 

(4) CMS notifies the IOTA participant 

of their final performance score and any 

associated upside risk payment or 

downside risk payment at least 30 days 

after notifying the IOTA participant of 

their preliminary performance 

assessment and payment calculations. 

(5) Upside risk payment. After CMS 

notifies the IOTA participant of their 

final performance score and any 

associated upside risk payment, and by 

a date determined by CMS, CMS issues 

the upside risk payment to the tax 

identification number (TIN) on file for 

the IOTA participant in the Medicare 

Provider Enrollment, Chain, and 

Ownership System (PECOS). 

(6) Downside risk payment. After CMS 

notifies the IOTA participant of their 

final performance score and any 

associated downside risk payment and 

by a date determined by CMS, CMS 


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Performance Relative to 

National Rankin2 Lower Bound Condition Unner Bound Condition Points Earned 

80th Percentile Eauals 80th percentile Greater than 80th percentile 20 

60th Percentile Equals 60th percentile Less than 80th percentile 18 

40th Percentile Equals 40th percentile Less than 60th percentile 16 

20th Percentile Eauals 20th percentile Less than 40th percentile 14 

10th Percentile Equals 10th percentile Less than 20th percentile 12 

10th Percentile NIA Less than 10th percentile 10 
96454 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

issues a demand letter to the TIN on file 

for the IOTA participant in PECOS for 

any downside risk payment owed to 

CMS. 

(i) CMS includes all of the following 

details in the demand letter: 

(A) IOTA participant performance in 

the model. 

(B) Amount of downside risk payment 

owed to CMS by the IOTA participant. 

(C) How the IOTA participant may 

make payments to CMS. 

(ii) The IOTA participant must pay 

the downside risk payment to CMS in 

a single payment at least 60 days after 

the date which the demand letter is 

issued. 

§ 512.434 Targeted review. 

(a) General. Subject to the limitations 

on review in paragraph (c) of this 

section, an IOTA participant may 

submit a targeted review request for one 

or more calculations made, and issued 

by, CMS within the preliminary 

performance assessment and payment 

calculations, if either of the following 

occur: 

(1) The IOTA participant believes an 

error occurred in calculations due to 

data quality or other issues. 

(2) The IOTA participant believes an 

error occurred in calculations due to 

misapplication of methodology. 

(b) Requirements. The request must 

satisfy the following criteria: 

(1) Be submitted within 30 days, or 

another time period as specified by 

CMS, of receiving its preliminary 

performance assessment and payment 

calculations from CMS. 

(2) Include supporting information in 

a form and manner as specified by CMS. 

(c) Limitations on review. (1) CMS 

does not provide IOTA participants the 

ability to dispute the policy or 

methodology, as the targeted review 

process would be limited to the dispute 

of calculations. CMS would not 

consider targeted review requests 

regarding, without limitation, the 

following: 

(i) The selection of the kidney 

transplant hospital to be an IOTA 

participant. 

(ii) The attribution of IOTA waitlist 

patients and the attribution of IOTA 

transplant patients to the IOTA 

participant, or to any other kidney 

transplant hospital selected for 

participation in the IOTA Model, or to 

any kidney transplant hospital not 

selected for participation in the IOTA 

Model. 

(iii) The methodology used for 

determining the achievement domain, 

efficiency domain, and quality domain. 

(iv) The methodology used for 

calculating and assigning points for 

each metric within the achievement 

domain, efficiency domain, and quality 

domain. 

(v) The methodology used for 

calculating the payment amount per 

Medicare kidney transplant paid to an 

IOTA participant. 

(2) CMS may review a targeted review 

request that includes one or more of the 

limitations in paragraph (c)(1) of this 

section, provided that all remaining 

considerations of the request meet all 

other criteria for consideration by CMS 

in this section. 

(d) Targeted review process. The 

IOTA participant must submit a request 

for targeted review in accordance with 

paragraphs (a) through (c) of this 

section. The process for a targeted 

review is as follows: 

(1) Initial and final assessments. 

Upon receipt of a targeted review 

request from an IOTA participant CMS 

conducts an initial and final assessment 

as follows: 

(i) Initial assessment. (A) CMS 

determines if the targeted review 

request meets the targeted review 

requirements in paragraph (b) of this 

section and contains sufficient 

information to substantiate the request. 

(B) If the request is not compliant 

with paragraphs (a) through (c) of this 

section or requires additional 

information: 

(1) CMS follows up with the IOTA 

participant to request additional 

information in a form and manner as 

specified by CMS. 

(2) The IOTA participant must 

respond within 30 days of CMS’s 

request for additional information in a 

form and manner as specified by CMS. 

(3) An IOTA participant’s nonresponsiveness to the request for 

additional information from CMS may 

result in the closure of the targeted 

review request. 

(ii) Final assessment. (A) Upon 

completion of an initial assessment, as 

described in paragraph (d)(1)(i) of this 

section, CMS determines whether it 

erred in calculation, as disputed by the 

IOTA participant. 

(B) If a calculation error is found as 

a result of an IOTA participant’s 

targeted review request— 

(1) CMS— 

(i) Notifies the IOTA participant 

within 30 days of any findings in a form 

and manner as specified by CMS; and 

(ii) Resolves and corrects any 

resulting error or discrepancy in the 

amount of the upside risk payment or 

downside risk payment in a time and 

manner as determined by CMS. 

(2) CMS’ correction of any error or 

discrepancy may delay the effective date 

of an IOTA participant’s upside risk 

payments or downside risk payments. 

(2) Targeted review decisions. 

Targeted review decisions made by CMS 

are final, unless submitted for 

administrative review as described in 

§ 512.190. 

§ 512.436 Extreme and uncontrollable 

circumstances. 

(a) General. CMS— 

(1) Applies determinations made 

under the Quality Payment Program 

with respect to whether an extreme and 

uncontrollable circumstance has 

occurred and the affected area during 

the PY; and 

(2) Has sole discretion to determine 

the period during which an extreme and 

uncontrollable circumstance occurred 

and the percentage of attributed patients 

residing in affected areas. 

(b) Downside risk payment. In the 

event of an extreme and uncontrollable 

circumstance, as determined by the 

Quality Payment Program, CMS may 

reduce the amount of the IOTA 

participant’s downside risk payment, if 

applicable, prior to recoupment. CMS 

determines the amount of the reduction 

by multiplying the downside risk 

payment by both of the following: 

(1) The percentage of total months 

during the PY affected by the extreme 

and uncontrollable circumstance. 

(2) The percentage of attributed 

patients who reside in an area affected 

by the extreme and uncontrollable 

circumstance. 

Data Sharing 

§ 512.440 Data sharing. 

(a) General. CMS shares certain 

beneficiary-identifiable data as 

described in paragraph (b) of this 

section and certain aggregate data as 

described in paragraph (c) of this 

section with IOTA participants 

regarding attributed patients who are 

Medicare beneficiaries and performance 

under the model. 

(b) Beneficiary-identifiable data. CMS 

shares beneficiary-identifiable data with 

IOTA participants as follows: 

(1) CMS makes available certain 

beneficiary-identifiable data described 

in paragraphs (b)(4) and (5) of this 

section for IOTA participants to request 

for purposes of conducting health care 

operations work that falls within the 

first or second paragraph of the 

definition of health care operations at 45 

CFR 164.501 on behalf of their 

attributed patients who are Medicare 

beneficiaries. 

(2) An IOTA participant that wishes 

to receive beneficiary-identifiable data 

for its attributed patients who are 


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Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 96455 

Medicare beneficiaries must do all of 

the following: 

(i) Submit a formal request for the 

data, on an annual basis in a manner 

and form and by a date specified by 

CMS, which identifies the data being 

requested and attests that— 

(A) The IOTA participant is 

requesting this beneficiary-identifiable 

data as a HIPAA covered entity or as a 

business associate, as those terms are 

defined at 45 CFR 160.103, to the IOTA 

participant’s providers and suppliers 

who are HIPAA covered entities; and 

(B) The IOTA participant’s request 

reflects the minimum data necessary, as 

set forth in paragraph (b)(6) of this 

section, for the IOTA participant to 

conduct health care operations work 

that falls within the first or second 

paragraph of the definition of health 

care operations at 45 CFR 164.501. 

(ii) Limit the request to Medicare 

beneficiaries whose name appears on 

the quarterly attribution list who have 

been notified in compliance with 

§ 512.450 that the IOTA participant has 

requested access to beneficiaryidentifiable data, and who did not 

decline having their claims data shared 

with the IOTA participant as provided 

in paragraph (b)(7) of this section. 

(iii) Sign and submit a data sharing 

agreement with CMS as set forth in 

paragraph (b)(8) of this section. 

(3) CMS shares beneficiaryidentifiable data with an IOTA 

participant on the condition that the 

IOTA participant, its IOTA 

collaborators, and other individuals or 

entities performing functions or services 

related to the IOTA participant’s 

activities observe all relevant statutory 

and regulatory provisions regarding the 

appropriate use of data and the 

confidentiality and privacy of 

individually identifiable health 

information and comply with the terms 

of the data sharing agreement described 

in paragraph (b)(8) of this section. 

(4) CMS omits from the beneficiaryidentifiable data any information that is 

subject to the regulations in 42 CFR part 

2 governing the confidentiality of 

substance use disorder patient records. 

(5) The beneficiary-identifiable data 

will include, when available, the 

following information: 

(i) Quarterly attribution lists. For the 

relevant PY, CMS shares with the IOTA 

participant the quarterly attribution 

lists, which will include but may not be 

limited to the following information for 

each attributed patient: 

(A) The year that CMS attributed the 

patient to the IOTA participant. 

(B) The effective date of the patient’s 

attribution to the IOTA participant. 

(C) The effective date of the patient’s 

de-attribution from the IOTA participant 

and the reason for such removal (if 

applicable). 

(D) For Medicare beneficiaries, the 

attributed patient’s data sharing 

preference. 

(ii) Beneficiary-identifiable claims 

data. CMS makes available certain 

beneficiary-identifiable claims data for 

retrieval by IOTA participants no later 

than 1 month after the start of each PY, 

in a form and manner specified by CMS. 

IOTA participants may retrieve the 

following data at any point during the 

relevant PY. This claims data includes 

all of the following: 

(A) Three years of historical Parts A, 

B, and D claims data files from the 36 

months immediately preceding the 

effective date of each attributed patient 

who is a Medicare beneficiary’s 

attribution to the IOTA participant. 

(B) Monthly Parts A, B, and D claims 

data files for attributed patients who are 

Medicare beneficiaries. 

(C) Monthly Parts A, B, and D claims 

data files for Medicare beneficiaries who 

have been de-attributed from the IOTA 

participant for claims with a date of 

service before the date the Medicare 

beneficiary was de-attributed from the 

IOTA participant. 

(6) The IOTA participant must limit 

its attributed Medicare beneficiary 

identifiable data requests to the 

minimum necessary to accomplish a 

permitted use of the data. 

(i) The minimum necessary Parts A 

and B data elements may include but 

are not limited to the following data 

elements: 

(A) Medicare beneficiary identifier 

(ID). 

(B) Procedure code. 

(C) Gender. 

(D) Diagnosis code. 

(E) Claim ID. 

(F) The from and through dates of 

service. 

(G) The provider or supplier ID. 

(H) The claim payment type. 

(I) Date of birth and death, if 

applicable. 

(J) Tax identification number (TIN). 

(K) National provider identifier (NPI). 

(ii) The minimum necessary Part D 

data elements may include but are not 

limited to the following data elements: 

(A) Beneficiary ID. 

(B) Prescriber ID. 

(C) Drug service date. 

(D) Drug product service ID. 

(E) Quantity dispensed. 

(F) Days supplied. 

(G) Brand name. 

(H) Generic name. 

(I) Drug strength. 

(J) TIN. 

(K) NPI. 

(L) Indication if on formulary. 

(M) Gross drug cost. 

(7)(i)(A) IOTA participants must send 

Medicare beneficiaries a notification 

about the IOTA Model and the 

opportunity to decline claims data 

sharing as required under § 512.450. 

(B) Such notifications must do both of 

the following: 

(1) State that the IOTA participant 

may have requested beneficiaryidentifiable claims data about the 

Medicare beneficiary for purposes of its 

care coordination, quality improvement 

work, and population-based activities 

relating to improving health or reducing 

health care costs. 

(2) Inform the Medicare beneficiary 

how to decline having his or her claims 

information shared with the IOTA 

participant in the form and manner 

specified by CMS. 

(ii) Medicare beneficiary requests to 

decline claims data sharing remain in 

effect unless and until a beneficiary 

subsequently contacts CMS to amend 

that request to permit claims data 

sharing with IOTA participants. 

(iii) The opportunity to decline 

having claims data shared with an IOTA 

participant under paragraph (b)(7)(i) of 

this section does not apply to any of the 

following: 

(A) The aggregate data that CMS 

provides to IOTA participants under 

paragraph (c) of this section. 

(B) The initial attribution lists that 

CMS provides to IOTA participants as 

defined at § 512.402 and specified under 

§ 512.414(c)(1)(ii). 

(C) The quarterly attribution lists that 

CMS provides to IOTA participants as 

defined at § 512.402 and specified under 

§ 512.414(c)(2)(ii). 

(D) The annual attribution 

reconciliation list that CMS provides to 

IOTA participants as defined at 

§ 512.402 and specified under 

§ 512.414(c)(3)(ii). 

(8)(i) If an IOTA participant wishes to 

retrieve any beneficiary-identifiable data 

specified in paragraph (b) of this 

section, the IOTA participant must 

complete and submit, on an annual 

basis, a signed data sharing agreement, 

to be provided in a form and manner 

specified by CMS, under which the 

IOTA participant agrees to all of the 

following: 

(A) To comply with the requirements 

for use and disclosure of this 

beneficiary-identifiable data that are 

imposed on covered entities by the 

HIPAA regulations at 45 CFR part 160 

and part 164, subparts A and E, and the 

requirements of the IOTA Model set 

forth in this part. 


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96456 Federal Register / Vol. 89, No. 233 / Wednesday, December 4, 2024 / Rules and Regulations 

(B) To comply with additional 

privacy, security, breach notification, 

and data retention requirements 

specified by CMS in the data sharing 

agreement. 

(C) To contractually bind each 

downstream recipient of the beneficiaryidentifiable data that is a business 

associate of the IOTA participant, 

including all IOTA collaborators, to the 

same terms and conditions to which the 

IOTA participant is itself bound in its 

data sharing agreement with CMS as a 

condition of the business associate’s 

receipt of the beneficiary-identifiable 

data retrieved by the IOTA participant 

under the IOTA Model. 

(D) That if the IOTA participant 

misuses or discloses the beneficiaryidentifiable data in a manner that 

violates any applicable statutory or 

regulatory requirements or that is 

otherwise non-compliant with the 

provisions of the data sharing 

agreement, CMS may do all of the 

following: 

(1) Deem the IOTA participant 

ineligible to retrieve the beneficiaryidentifiable data under paragraph (b) of 

this section for any amount of time. 

(2) Terminate the IOTA participant’s 

participation in the IOTA Model under 

§ 512.466. 

(3) Subject the IOTA participant to 

additional sanctions and penalties 

available under the law. 

(ii) An IOTA participant must comply 

with all applicable laws and the terms 

of the data sharing in order to retrieve 

beneficiary-identifiable data. 

(c) Aggregate data. (1) CMS shares 

aggregate performance data with IOTA 

participants, in a form and manner to be 

specified by CMS, which has been deidentified in accordance with 45 CFR 

164.514(b). This aggregate data includes, 

when available, certain de-identified 

data detailing the IOTA participant’s 

performance against the transplant 

target information for each PY. 

§ 512.442 Transparency requirements. 

(a) Publication of transplant patient 

selection criteria. The IOTA participant 

must publicly post on its website the 

criteria used by the IOTA participant for 

evaluating and selecting patients for 

addition to their kidney transplant 

waitlist by the end of PY 1. 

(b) [Reserved] 

(c) Review of acceptance criteria. 

IOTA participants must review 

transplant organ offer acceptance 

criteria with their IOTA waitlist patients 

who are Medicare beneficiaries at least 

once every 6 months that the Medicare 

beneficiary is on their waitlist. 

(1) The IOTA participant must 

conduct this review via patient visit, 

phone, email or mail on an individual 

basis, unless the Medicare beneficiary 

declines this review. 

(2) [Reserved] 

§ 512.446 Health equity plans. 

(a) For each PY, an IOTA participant 

may voluntarily submit a health equity 

plan, by a date and in a form and 

manner determined by CMS, that meets 

the following requirements: 

(1) Identifies target health disparities. 

(2) Identifies the data sources used to 

inform the identification of target health 

disparities. 

(3) Describes the health equity plan 

intervention. 

(4) Includes a resource gap analysis. 

(5) Includes a health equity project 

plan. 

(6) Identifies health equity plan 

performance measure(s). 

(7) Identifies health equity goals and 

describes how the IOTA participant will 

use the health equity goals to monitor 

and evaluate progress in reducing 

targeted health disparities. 

(b) [Reserved] 

Beneficiary Protections and Financial 

Arrangements, Beneficiary Incentives, 

and Compliance. 

§ 512.450 Required beneficiary 

notifications. 

(a) General. (1) IOTA participants 

must provide notice to attributed 

patients that they are participating in 

the IOTA Model. 

(2) CMS provides a notification 

template that IOTA participants must 

use. The template, at minimum does all 

of the following: 

(i) Indicates content that the IOTA 

participant must not change. 

(ii) Indicates where the IOTA 

participant may insert its own content. 

(iii) Includes information regarding 

the attributed patient’s opportunity to 

opt-out of data sharing with IOTA 

participants and how they may opt out 

if they choose to do so. 

(3) To notify attributed patients of 

their rights and protections and that the 

IOTA participant is participating in the 

IOTA Model, the IOTA participant must 

do all of the following: 

(i) Prominently display informational 

materials in each of their office or 

facility locations where attributed 

patients receive treatment. 

(ii) Include this notification in a clear 

manner on its public facing website. 

(iii) Provide this notification to each 

attributed patient in a paper format. 

(b) Applicability of general Innovation 

Center model provisions. (1) The 

requirements described in § 512.120(c) 

do not apply to the CMS-provided 

materials described in paragraph (a) of 

this section. 

(2) All other IOTA participant 

communications that are descriptive 

model materials and activities as 

defined under § 512.110 must meet the 

requirements described in § 512.120(c). 

§ 512.452 Financial sharing arrangements 

and attributed patient engagement 

incentives. 

(a) General. (1) The IOTA 

participant— 

(i) May enter into a sharing 

arrangement with an IOTA collaborator 

to make a gainsharing payment, or to 

receive an alignment payment, or both; 

and 

(ii) Must not make a gainsharing 

payment or receive an alignment 

payment except in accordance with a 

sharing arrangement. 

(2) A sharing arrangement must 

comply with the provisions of this 

section and all other applicable laws 

and regulations, including the 

applicable fraud and abuse laws and all 

applicable payment and coverage 

requirements. 

(3) The IOTA participant must 

develop, maintain, and use a set of 

written policies for selecting providers 

and suppliers to be IOTA collaborators. 

(i) The selection criteria must include 

the quality of care delivered by the 

potential IOTA collaborator. 

(ii) The selection criteria cannot be 

based directly or indirectly on the 

volume or value of referrals or business 

otherwise generated by, between or 

among any of the following: 

(A) The IOTA participant. 

(B) Any IOTA collaborator. 

(C) Any collaboration agent. 

(D) Any individual or entity affiliated 

with an IOTA participant, IOTA 

collaborator, or collaboration agent. 

(iii) The written policies must contain 

criteria related to, and inclusive of, the 

anticipated contribution to performance 

across the achievement domain, 

efficiency domain, and quality domain 

by the potential IOTA collaborator. 

(4) The board or other governing body 

of the IOTA participant must have 

responsibility for overseeing the IOTA 

participant’s participation in the IOTA 

Model, including but not limited to all 

of the following: 

(i) Arrangements with IOTA 

collaborators. 

(ii) Payment of gainsharing payments. 

(iii) Receipt of alignment payments. 

(iv) Use of beneficiary incentives in 

the IOTA Model. 

(5) If an IOTA participant enters into 

a sharing arrangement, its compliance 

program must include oversight of 

sharing arrangements and compliance 

with the applicable requirements of the 

IOTA Model. 


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(b) Requirements. (1) A sharing 

arrangement must be— 

(i) In writing; 

(ii) Signed by the parties; and 

(iii) Entered into before care is 

furnished to an attributed patient during 

the PY under the sharing arrangement. 

(2) Participation in a sharing 

arrangement must be voluntary and 

without penalty for nonparticipation. 

(3) Participation in the sharing 

arrangement must require the IOTA 

collaborator to comply with the 

requirements of this model, as those 

pertain to their actions and obligations. 

(4) The sharing arrangement— 

(i) Must set out the mutually agreeable 

terms for the financial arrangement 

between the parties to guide and reward 

model care redesign for future 

performance across the achievement 

domain, efficiency domain, and quality 

domain; 

(ii) Must not reflect the results of 

model PYs that have already occurred; 

and 

(iii) Where the financial outcome of 

the sharing arrangement terms are 

known before signing. 

(5) The sharing arrangement must 

require the IOTA collaborator and its 

employees, contractors (including 

collaboration agents), and 

subcontractors to comply with all of the 

following: 

(i) The applicable provisions of this 

part (including requirements regarding 

beneficiary notifications, access to 

records, record retention, and 

participation in any evaluation, 

monitoring, compliance, and 

enforcement activities performed by 

CMS or its designees). 

(ii) All applicable Medicare provider 

enrollment requirements at § 424.500 of 

this chapter, including having a valid 

and active TIN or NPI, during the term 

of the sharing arrangement. 

(iii) All other applicable laws and 

regulations. 

(6) The sharing arrangement must 

require the IOTA collaborator to have or 

be covered by a compliance program 

that includes oversight of the sharing 

arrangement and compliance with the 

requirements of the IOTA Model that 

apply to its role as an IOTA 

collaborator, including any distribution 

arrangements. 

(7) The sharing arrangement must not 

pose a risk to beneficiary access, 

beneficiary freedom of choice, or quality 

of care. 

(8) The written agreement 

memorializing a sharing arrangement 

must specify all of the following: 

(i) The purpose and scope of the 

sharing arrangement. 

(ii) The identities and obligations of 

the parties, including specified IOTA 

activities and other services to be 

performed by the parties under the 

sharing arrangement. 

(iii) The date of the sharing 

arrangement. 

(iv) Management and staffing 

information, including type of 

personnel or contractors that would be 

primarily responsible for carrying out 

IOTA activities. 

(v) The financial or economic terms 

for payment, including all of the 

following: 

(A) Eligibility criteria for a 

gainsharing payment. 

(B) Eligibility criteria for an alignment 

payment. 

(C) Frequency of gainsharing or 

alignment payment. 

(D) Methodology and accounting 

formula for determining the amount of 

a gainsharing payment that is 

substantially based on performance 

across the achievement domain, 

efficiency domain and quality domain, 

and the provision of IOTA activities. 

(E) Methodology and accounting 

formula for determining the amount of 

an alignment payment. 

(9) The sharing arrangement must 

not— 

(i) Induce— 

(A) The IOTA participant; 

(B) The IOTA collaborator; or 

(C) Any employees, contractors, or 

subcontractors of the IOTA participant 

or IOTA collaborator to reduce or limit 

medically necessary services to any 

attributed patient; or 

(ii) Restrict the ability of an IOTA 

collaborator to make decisions in the 

best interests of its patients, including 

the selection of devices, supplies, and 

treatments. 

(c) Gainsharing payments and 

alignment payments. (1) Gainsharing 

payments, if any, must meet all of the 

following: 

(i) Be derived solely from upside risk 

payments. 

(ii) Be distributed on an annual basis 

(not more than once per performance 

year). 

(iii) Not be a loan, advance payment, 

or payment for referrals or other 

business. 

(iv) Be clearly identified as a 

gainsharing payment at the time it is 

paid. 

(2) To be eligible to receive a 

gainsharing payment an IOTA 

collaborator must contribute to 

performance across the achievement 

domain, efficiency domain or quality 

domain for the PY for which the IOTA 

participant earned the upside risk 

payment that comprises the gainsharing 

payment. The contribution to 

performance across the achievement 

domain, efficiency domain, or quality 

domain criteria must be established by 

the IOTA participant and directly 

related to the care of attributed patients. 

(3) To be eligible to receive a 

gainsharing payment, or to be required 

to make an alignment payment: 

(i) An IOTA collaborator other than 

PGP, NPPGP, or TGP must have directly 

furnished a billable item or service to an 

attributed patient that occurred in the 

same PY for which the IOTA participant 

earned the upside risk payment that 

comprises the gainsharing payment or 

incurred a downside risk payment. 

(ii) An IOTA collaborator that is a 

PGP, NPPGP, or TGP must meet the 

following criteria: 

(A) The PGP, NPPGP, or TGP must 

have billed for an item or service that 

was rendered by one or more PGP 

member, NPPGP member, or TGP 

member respectively to an attributed 

patient that occurred during the same 

PY for which the IOTA participant 

earned the upside risk payment that 

comprises the gainsharing payment or 

incurred a downside risk payment. 

(B) The PGP, NPPGP, or TGP must 

have contributed to IOTA activities and 

been clinically involved in the care of 

attributed patients during the same PY 

for which the IOTA participant earned 

the upside risk payment that comprises 

the gainsharing payment or incurred a 

downside risk payment. 

(4) The total amount of a gainsharing 

payment for a PY paid to an IOTA 

collaborator that is a physician or 

nonphysician practitioner must not 

exceed 50 percent of the Medicareapproved amounts under the PFS for 

items and services billed by that 

physician or nonphysician practitioner 

to the IOTA participant’s attributed 

patients during the same PY for which 

the IOTA participant earned the upside 

risk payment that comprises the 

gainsharing payment being made. 

(5) The total amount of a gainsharing 

payment for a PY paid to an IOTA 

collaborator that is a PGP, NPPGP, or 

TGP must not exceed 50 percent of the 

Medicare-approved amounts under the 

PFS for items and services billed by that 

PGP, NPPGP, or TGP and furnished to 

the IOTA participant’s attributed 

patients by the PGP members, NPPGP 

members, or TGP members respectively 

during the same PY for which the IOTA 

participant earned the upside risk 

payment that comprises the gainsharing 

payment being made. 

(6) The amount of any gainsharing 

payments must be determined in 

accordance with a methodology that is 

substantially based on contribution to 

the performance across the achievement 

domain, efficiency domain or quality 


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domain and the provision of IOTA 

activities. The methodology may take 

into account the amount of such IOTA 

activities provided by an IOTA 

collaborator relative to other IOTA 

collaborators. 

(7) For a PY, the aggregate amount of 

all gainsharing payments that are 

derived from the upside risk payment 

the IOTA participant receives from CMS 

must not exceed the amount of that 

upside risk payment. 

(8) No entity or individual, whether a 

party to a sharing arrangement or not, 

may condition the opportunity to make 

or receive gainsharing payments or to 

make or receive alignment payments 

directly or indirectly on the volume or 

value of referrals or business otherwise 

generated by, between or among the 

IOTA participant, any IOTA 

collaborator, any collaboration agent, or 

any individual or entity affiliated with 

an IOTA participant, IOTA collaborator, 

or collaboration agent. 

(9) An IOTA participant must not 

make a gainsharing payment to an IOTA 

collaborator that is subject to any action 

for noncompliance with this part, or the 

fraud and abuse laws, or for the 

provision of substandard care to 

attributed patients or other integrity 

problems. 

(10) The sharing arrangement must 

require the IOTA participant to recoup 

any gainsharing payment that contained 

funds derived from a CMS overpayment 

on an upside risk payment or was based 

on the submission of false or fraudulent 

data. 

(11) Alignment payments from an 

IOTA collaborator to an IOTA 

participant may be made at any interval 

that is agreed upon by both parties, and 

must not be— 

(i) Issued, distributed, or paid prior to 

the calculation by CMS of a payment 

amount reflected in the notification of 

the downside risk payment; 

(ii) Loans, advance payments, or 

payments for referrals or other business; 

or 

(iii) Assessed by an IOTA participant 

if the IOTA participant does not owe a 

downside risk payment. 

(12) The IOTA participant must not 

receive any amounts under a sharing 

arrangement from an IOTA collaborator 

that are not alignment payments. 

(13) For a PY, the aggregate amount of 

all alignment payments received by the 

IOTA participant must not exceed 50 

percent of the IOTA participant’s 

downside risk payment amount. 

(14) The aggregate amount of all 

alignment payments from a single IOTA 

collaborator to the IOTA participant 

may not be greater than 25 percent of 

the IOTA participant’s downside risk 

payment over the course of a single PY 

for an IOTA collaborator. 

(15) The amount of any alignment 

payments must be determined in 

accordance with a methodology that 

does not directly account for the volume 

or value of referrals or business 

otherwise generated by, between or 

among the IOTA participant, any IOTA 

collaborator, any collaboration agent, or 

any individual or entity affiliated with 

an IOTA participant, IOTA collaborator, 

or collaboration agent. 

(16) All gainsharing payments and 

any alignment payments must be 

administered by the IOTA participant in 

accordance with generally accepted 

accounting principles (GAAP) and 

Government Auditing Standards (The 

Yellow Book). 

(17) All gainsharing payments and 

alignment payments must be made by 

check, EFT, or another traceable cash 

transaction. 

(d) Documentation requirements. (1) 

The IOTA participant must do all of the 

following: 

(i) Document the sharing arrangement 

contemporaneously with the 

establishment of the arrangement. 

(ii) Maintain accurate current and 

historical lists of all IOTA collaborators, 

including IOTA collaborator names and 

addresses. With respect to these lists the 

IOTA participant must— 

(A) Update such lists on at least a 

quarterly basis; and 

(B) On a web page on the IOTA 

participant’s website, the IOTA 

participant must— 

(1) Publicly report the current and 

historical lists of IOTA collaborators; 

and 

(2) Include any written policies for 

selecting individuals and entities to be 

IOTA collaborators required by the 

IOTA participant. 

(iii) Maintain and require each IOTA 

collaborator to maintain 

contemporaneous documentation with 

respect to the payment or receipt of any 

gainsharing payment or alignment 

payment that includes at a minimum all 

of the following: 

(A) Nature of the payment 

(gainsharing payment or alignment 

payment). 

(B) Identity of the parties making and 

receiving the payment. 

(C) Date of the payment. 

(D) Amount of the payment. 

(E) Date and amount of any 

recoupment of all or a portion of an 

IOTA collaborator’s gainsharing 

payment. 

(F) Explanation for each recoupment, 

such as whether the IOTA collaborator 

received a gainsharing payment that 

contained funds derived from a CMS 

overpayment of an upside risk payment 

or was based on the submission of false 

or fraudulent data. 

(2) The IOTA participant must keep 

records of all of the following: 

(i) Its process for determining and 

verifying its potential and current IOTA 

collaborators’ eligibility to participate in 

Medicare. 

(ii) A description of current health 

information technology, including 

systems to track upside risk payments 

and downside risk payments. 

(iii) Its plan to track gainsharing 

payments and alignment payments. 

(3) The IOTA participant must retain 

and provide access to, and must require 

each IOTA collaborator to retain and 

provide access to, the required 

documentation in accordance with 

§§ 512.460 and 1001.952(ii). 

§ 512.454 Distribution arrangements. 

(a) General. (1) An IOTA collaborator 

may distribute all or a portion of any 

gainsharing payment it receives from 

the IOTA participant only in accordance 

with a distribution arrangement, as 

defined at § 512.402. 

(2) All distribution arrangements must 

comply with the provisions of this 

section and all other applicable laws 

and regulations, including the fraud and 

abuse laws. 

(b) Requirements. (1) All distribution 

arrangements must be in writing and 

signed by the parties, contain the date 

of the agreement, and be entered into 

before care is furnished to attributed 

patients under the distribution 

arrangement. 

(2) Participation in a distribution 

arrangement must be voluntary and 

without penalty for nonparticipation. 

(3) The distribution arrangement must 

require the collaboration agent to 

comply with all applicable laws and 

regulations. 

(4) The opportunity to make or 

receive a distribution payment must not 

be conditioned directly or indirectly on 

the volume or value of referrals or 

business otherwise generated by, 

between or among the IOTA participant, 

any IOTA collaborator, any 

collaboration agent, or any individual or 

entity affiliated with an IOTA 

participant, IOTA collaborator, or 

collaboration agent. 

(5) The amount of any distribution 

payments from an NPPGP to an NPPGP 

member, or from a TGP to a TGP 

member must be determined in 

accordance with a methodology that is 

substantially based on contribution to 

performance across the achievement 

domain, efficiency domain, and quality 

domain and the provision of IOTA 

activities and that may take into account 


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the amount of such IOTA activities 

provided by a collaboration agent 

relative to other collaboration agents. 

(6) The amount of any distribution 

payments from a PGP must be 

determined either in a manner that 

complies with § 411.352(g) of this 

chapter or in accordance with a 

methodology that is substantially based 

on contribution to performance across 

the achievement domain, efficiency 

domain and quality domain and the 

provision of IOTA activities and that 

may take into account the amount of 

such IOTA activities provided by a 

collaboration agent relative to other 

collaboration agents. 

(7) Except for a distribution payment 

from a PGP to a PGP member that 

complies with § 411.352(g) of this 

chapter, a collaboration agent is eligible 

to receive a distribution payment only if 

the collaboration agent furnished or 

billed for an item or service rendered to 

an attributed patient that occurred 

during the same PY for which the IOTA 

participant earned the upside risk 

payment that comprises the gainsharing 

payment being distributed. 

(8) Except for a distribution payment 

from a PGP to a PGP member that 

complies with § 411.352(g) of this 

chapter, the total amount of distribution 

payments for a PY paid to a 

collaboration agent must not exceed 50 

percent of the total Medicare-approved 

amounts under the PFS for items and 

services billed by that PGP, NPPGP or 

TGP for items and services furnished by 

PGP members, NPPGP members or TGP 

members respectively to attributed 

patients that occurred during the same 

PY for which the IOTA participant 

earned the upside risk payment that 

comprises the gainsharing payment 

being distributed. 

(9) With respect to the distribution of 

any gainsharing payment received by a 

PGP, NPPGP, or TGP, the total amount 

of all distribution payments must not 

exceed the amount of the gainsharing 

payment received by the IOTA 

collaborator from the IOTA participant. 

(10) All distribution payments must 

be made by check, electronic funds 

transfer, or another traceable cash 

transaction. 

(11) The collaboration agent must 

retain the ability to make decisions in 

the best interests of the patient, 

including the selection of devices, 

supplies, and treatments. 

(12) The distribution arrangement 

must not— 

(i) Induce the collaboration agent to 

reduce or limit medically necessary 

items and services to any Medicare 

beneficiary; or 

(ii) Reward the provision of items and 

services that are medically unnecessary. 

(13) The IOTA collaborator must 

maintain contemporaneous 

documentation regarding distribution 

arrangements in accordance with 

§ 512.454, including the following: 

(i) The relevant written agreements. 

(ii) The date and amount of any 

distribution payment(s). 

(iii) The identity of each collaboration 

agent that received a distribution 

payment. 

(iv) A description of the methodology 

and accounting formula for determining 

the amount of any distribution payment. 

(14) The IOTA collaborator may not 

enter into a distribution arrangement 

with any collaboration agent that has a 

sharing arrangement with the same 

IOTA participant. 

(15) The IOTA collaborator must 

retain and provide access to and must 

require collaboration agents to retain 

and provide access to, the required 

documentation in accordance with 

§ 512.460. 

§ 512.455 Enforcement authority. 

(a) OIG authority. Nothing contained 

in the terms of the IOTA Model or this 

part limits or restricts the authority of 

the HHS Office of Inspector General, 

including its authority to audit, 

evaluate, investigate, or inspect the 

IOTA participant, IOTA collaborators, 

or any other person or entity or their 

records, data, or information, without 

limitation. 

(b) Other authority. Nothing 

contained in the terms of the IOTA 

Model or this part limits or restricts the 

authority of any government agency 

permitted by law to audit, evaluate, 

investigate, or inspect the participant 

hospital, IOTA collaborators, or any 

other person or entity or their records, 

data, or information, without limitation. 

§ 512.456 Beneficiary incentive: Part B and 

Part D immunosuppressive drug cost 

sharing support. 

(a) Cost sharing support for Part B and 

Part D immunosuppressive drugs. For 

immunosuppressive drugs covered 

under Medicare Part B or Medicare Part 

D and prescribed to an attributed 

patient, the IOTA participant may 

subsidize, in whole or in part, the cost 

sharing associated with the 

immunosuppressive drugs under Part B 

and Part D immunosuppressive drug 

cost sharing support defined at 

§ 512.402 if all of the following 

conditions are met: 

(1) The attributed patient is an eligible 

attributed patient as defined at 

§ 512.402. 

(2) The IOTA participant must 

provide a written policy in a form and 

manner specified by CMS for the 

provision of Part B and Part D 

immunosuppressive drug cost sharing 

support that is approved by CMS before 

the PY in which the cost sharing 

support is made available. 

(i) The IOTA participant must 

revalidate the written policy with CMS 

and in a form and manner specified by 

CMS for the provision of Part B and Part 

D immunosuppressive drug cost sharing 

support before its provision in a 

subsequent PY. 

(ii) The IOTA participant’s initial 

written policy and the revalidation of 

the written policy must establish and 

justify the criteria that qualify an 

eligible attributed patient to receive Part 

B and Part D immunosuppressive drug 

cost sharing support. 

(iii) The IOTA participant’s written 

policy and the revalidation of the 

written policy must include an 

attestation that the IOTA participant 

will not, in providing Part B and Part D 

immunosuppressive drug cost sharing 

support, take into consideration the 

type, cost, generic status, or 

manufacturer of the immunosuppressive 

drug(s) or limit an eligible attributed 

patients’ choice of pharmacy. 

(b) Restrictions. (1) An IOTA 

participant must not take into 

consideration the type, cost, generic 

status, or manufacturer of the 

immunosuppressive drug(s) or limit an 

eligible attributed patients’ choice of 

pharmacy when providing Part B and 

Part D immunosuppressive drug cost 

sharing support. 

(2) An IOTA participant may not 

receive financial or operational support 

for Part B and Part D 

immunosuppressive drug cost sharing 

support from pharmacies and 

pharmaceutical manufacturers. 

(c) Documentation. (1) An IOTA 

participant must maintain 

contemporaneous documentation that 

includes all of the following: 

(i) The identity of the eligible 

attributed patient to whom Part B and 

Part D immunosuppressive drug cost 

sharing support was provided. 

(ii) The date or dates on which Part 

B and Part D immunosuppressive drug 

cost sharing support was provided. 

(iii) The amount or amounts of Part B 

and Part B immunosuppressive drug 

cost sharing support that was provided. 

(2) An IOTA participant must retain 

and make available records pertaining to 

Part B and Part D immunosuppressive 

drug cost sharing support to the Federal 

Government in accordance with 

§ 512.460. 


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§ 512.458 Attributed patient engagement 

incentives. 

(a) General. An IOTA participant may 

choose to provide any or all of the 

following types of attributed patient 

engagement incentives to an attributed 

patient under the conditions described 

in paragraph (b) of this section: 

(1) Communication devices and 

related communication services directly 

pertaining to communication with an 

IOTA participant or IOTA collaborator 

to improve communication between an 

attributed patient and an IOTA 

participant or IOTA collaborator. 

(2) Transportation to and from an 

IOTA participant and between other 

providers and suppliers involved in the 

provision of ESRD care. 

(3) Mental health services to address 

an attributed patient’s behavioral health 

symptoms pre- and post-transplant. 

(4) In-home care to support the health 

of the attributed patient or the kidney 

transplant in the post-transplant period. 

(b) Conditions. An IOTA participant 

may provide attributed patient 

engagement incentives of the type 

described in paragraphs (a)(1) through 

(4) of this section when all of the 

following conditions are met: 

(1) An IOTA participant provides a 

written policy, in a form and manner 

specified by CMS, for the provision of 

attributed patient engagement 

incentives. 

(2) CMS approves an IOTA 

participants written policy before the 

first PY in which an attributed patient 

engagement incentive is first made 

available. 

(3) CMS revalidates the IOTA 

participant’s written policy in a form 

and manner specified by CMS prior to 

each PY in which an attributed patient 

engagement incentive is offered 

subsequently. 

(4) The IOTA participant includes in 

its written policy: 

(i) A description of the items or 

services that will be provided as 

attributed patient engagement 

incentives. 

(ii) An explanation of how each item 

or service that will be an attributed 

patient engagement incentive has a 

reasonable connection to any of the 

following: 

(A) An attributed patient achieving 

and maintaining active status on a 

kidney transplant waitlist. 

(B) An attributed patient accessing the 

kidney transplant procedure. 

(C) The health of the attributed 

patient or the kidney transplant in the 

post-transplant period. 

(D) A justification for the need for the 

attributed patient engagement 

incentives that is specific to the IOTA 

participant’s attributed patient 

population. 

(iii) An attestation that items that are 

attributed patient engagement 

incentives will be provided directly to 

an attributed patient. 

(iv) An attestation that the IOTA 

participant will pay service providers 

directly for services that are attributed 

patient engagement incentives. 

(v) An attestation that any items or 

services acquired by the IOTA 

participant that will be furnished as 

attributed patient engagement 

incentives will be acquired for the 

minimum amount necessary for an 

attributed patient to achieve the goals 

described in paragraphs (3)(ii)(A) 

through (C) of this paragraph. 

(c) Restrictions. (1) An IOTA 

participant must provide items that are 

attributed patient engagement 

incentives directly to an attributed 

patient. 

(2) An IOTA participant must pay 

service providers directly for any 

services that are offered as attributed 

patient engagement incentive. 

(3) An IOTA participant must not 

offer an attributed patient engagement 

incentive that is tied to the receipt of 

items or services from a particular 

provider or supplier. 

(4) An IOTA participant must not 

advertise or promote an item or service 

that is an attributed patient engagement 

incentive, except to make an attributed 

patient aware of the availability of the 

items or services at the time an 

attributed patient could reasonably 

benefit from them. 

(5) An IOTA participant must not 

receive donations directly or indirectly 

to purchase attributed patient 

engagement incentives. 

(6) An IOTA participant must retrieve 

items that that are attributed patient 

engagement incentives from the 

attributed patient when the attributed 

patient is no longer eligible for the that 

item or at the conclusion of the IOTA 

Model, whichever is earlier. 

(i) Documented, diligent, good faith 

attempts to retrieve items that are 

attributed patient engagement 

incentives are deemed to meet the 

retrieval requirement. 

(ii) [Reserved] 

(7) Items that are communication 

devices: 

(i) May not exceed $1,000 in retail 

value for any one attributed patient in 

any one PY; 

(ii) Must remain the property of the 

IOTA participant; 

(iii) Must be retrieved from the 

attributed patient by the IOTA 

participant— 

(A) When the attributed patient is no 

longer eligible for the communication 

device or at the conclusion of the IOTA 

Model, whichever is earlier; and 

(B) Before another communication 

device may be made available to the 

same attributed patient. 

(d) Documentation. The IOTA 

participant must do all of the following: 

(1) Maintain contemporaneous 

documentation of items and services 

furnished as attributed patient 

engagement incentives that includes, at 

minimum all of the following: 

(i) The date the attributed patient 

engagement incentive is provided. 

(ii) The identity of the attributed 

patient to whom the item or service was 

provided. 

(2) Document all retrieval attempts of 

items that are attributed patient 

engagement incentives, including the 

ultimate date of retrieval. 

(3)(i) Retain records pertaining to 

furnished attributed patient engagement 

incentives. 

(ii) Make the records available to the 

Federal Government in accordance with 

§ 512.460. 

§ 512.459 Application of the CMSsponsored Model Arrangements and Patient 

Incentives Safe Harbor. 

(a) Application of the CMS-sponsored 

Model Arrangements Safe Harbor. CMS 

has determined that the Federal antikickback statute safe harbor for CMSsponsored model arrangements (42 CFR 

1001.952(ii)(1)) is available to protect 

remuneration furnished in the IOTA 

Model in the form of the Sharing 

Arrangement’s gainsharing payments, 

the Sharing Arrangement’s alignment 

payments, and the Distribution 

Arrangement’s distribution payments 

that meet all safe harbor requirements 

set forth in 42 CFR 1001.952(ii), 

512.452, and 512.454. 

(b) Application of the CMS-sponsored 

Model Patient Incentives Safe Harbor. 

CMS has determined that the Federal 

anti-kickback statute safe harbor for 

CMS-sponsored model patient 

incentives (42 CFR 1001.952(ii)(2)) is 

available to protect remuneration 

furnished in the IOTA Model in the 

form of Part B and Part D 

immunosuppressive drug cost sharing 

support and the attributed patient 

engagement incentives that meet all safe 

harbor requirements set forth in 42 CFR 

1001.952(ii), 512.456 and 512.458. 

§ 512.460 Audit rights and records 

retention. 

(a) Right to audit. The Federal 

Government, including CMS, HHS, and 

the Comptroller General, or their 

designees, has the right to audit, 

inspect, investigate, and evaluate any 

documents and other evidence 


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regarding implementation of the IOTA 

Model. 

(b) Access to records. The IOTA 

participant and its IOTA collaborators 

must maintain and give the Federal 

Government, including, but not limited 

to, CMS, HHS, and the Comptroller 

General, or their designees, access to all 

such documents (including books, 

contracts, and records) and other 

evidence sufficient to enable the audit, 

evaluation, inspection, or investigation 

of the implementation of the IOTA 

Model, including without limitation, 

documents, and other evidence 

regarding all of the following: 

(1) Compliance by the IOTA 

participant and its IOTA collaborators 

with the terms of the IOTA Model. 

(2) The accuracy of model-specific 

payments made under the IOTA Model. 

(3) The IOTA participant’s downside 

risk payments owed to CMS under the 

IOTA Model. 

(4) Quality measure information and 

the quality of services performed under 

the terms of the IOTA Model. 

(5) Utilization of items and services 

furnished under the IOTA Model. 

(6) The ability of the IOTA participant 

to bear the risk of potential losses and 

to repay any losses to CMS, as 

applicable. 

(7) Contemporaneous documentation 

of cost sharing support furnished under 

Part B and Part D immunosuppressive 

drug cost sharing support that includes 

the following: 

(i) The identity of the eligible 

attributed patient to whom Part B and 

Part D immunosuppressive drug cost 

sharing support was provided. 

(ii) The date or dates on which Part 

B and Part D immunosuppressive drug 

cost sharing support was provided. 

(iii) The amount or amounts of the 

cost sharing support provided to the 

attributed patient. 

(8) Contemporaneous documentation 

of items and services furnished as 

attributed patient engagement 

incentives in accordance with § 512.458 

that includes all of the following, at 

minimum: 

(i) The date the attributed patient 

engagement incentive is provided. 

(ii) The identity of the attributed 

patient to whom the item or service was 

provided. 

(9) Patient safety. 

(10) Any other program integrity 

issues. 

(c) Record retention. (1) The IOTA 

participant and its IOTA collaborators 

must maintain the documents and other 

evidence described in paragraph (b) of 

this section and other evidence for a 

period of 6 years from the last payment 

determination for the IOTA participant 

under the IOTA Model or from the date 

of completion of any audit, evaluation, 

inspection, or investigation, whichever 

is later, unless— 

(i) CMS determines there is a special 

need to retain a particular record or 

group of records for a longer period and 

notifies the IOTA participant at least 30 

days before the normal disposition date; 

or 

(ii) There has been a termination, 

dispute, or allegation of fraud or similar 

fault against the IOTA participant or its 

IOTA collaborators, in which case the 

records must be maintained for an 

additional 6 years from the date of any 

resulting final resolution of the 

termination, dispute, or allegation of 

fraud or similar fault. 

(2)(i) If CMS notifies the IOTA 

participant of the special need to retain 

a record or group of records in 

accordance with paragraph (c)(1)(i) of 

this section, the IOTA participant must 

maintain the records for such period of 

time as determined by CMS. 

(ii) If CMS notifies the IOTA 

participant of a special need to retain 

records in accordance with paragraph 

(c)(1)(ii) of this section, the IOTA 

participant must notify its IOTA 

collaborators of this need to retain 

records for the additional period 

specified by CMS. 

§ 512.462 Compliance and monitoring. 

(a) Compliance with laws. The IOTA 

participant must comply with all 

applicable laws and regulations. 

(b) CMS monitoring activities. (1) 

CMS, or its approved designee, may 

conduct monitoring activities to ensure 

compliance by the IOTA participant and 

IOTA collaborators with the terms of the 

IOTA Model under this subpart to— 

(i) Understand IOTA participants’ use 

of model-specific payments; and 

(ii) Promote the safety of attributed 

patients and the integrity of the IOTA 

Model. 

(2) Monitoring activities may include, 

without limitation, all of the following: 

(i) Documentation requests sent to the 

IOTA participant and its IOTA 

collaborators, including surveys and 

questionnaires. 

(ii) Audits of claims data, quality 

measures, medical records, and other 

data from the IOTA participant and its 

IOTA collaborators. 

(iii) Interviews with the IOTA 

participant, including leadership 

personnel, medical staff, other 

associates, and its IOTA collaborators. 

(iv) Interviews with attributed 

patients and their caregivers. 

(v) Site visits to the IOTA participant 

and its IOTA collaborators, performed 

in a manner consistent with paragraph 

(c) of this section. 

(vi) Monitoring quality outcomes and 

attributed patient data. 

(vii) Tracking beneficiary complaints 

and appeals. 

(viii) Monitoring the definition of and 

justification for the subpopulation of the 

IOTA participant’s eligible attributed 

patients that may receive Part B and Part 

D immunosuppressive drug cost sharing 

support in accordance with § 512.456. 

(ix) Monitoring the provision of 

attributed patient engagement 

incentives provided in accordance with 

§ 512.458. 

(x) Monitoring out of sequence 

allocation of kidneys by— 

(A) Assessing the frequency at which 

IOTA waitlist patients, top-ranked on an 

IOTA participant’s kidney transplant 

waitlist, receive the organ that was 

initially offered to them; and 

(B) Determining the reasons behind 

cases where IOTA waitlist patients 

identified in paragraph (b)(x)(A) of this 

section, did not receive the kidney 

offered to them. 

(3) In conducting monitoring and 

oversight activities, CMS or its 

designees may use any relevant data or 

information including without 

limitation all Medicare claims 

submitted for items or services 

furnished to IOTA transplant patients or 

IOTA waitlist patients or both. 

(c) Site visits. (1) The IOTA 

participant must cooperate in periodic 

site visits performed by CMS or its 

designees in order to facilitate the 

evaluation of the IOTA Model in 

accordance with section 1115A(b)(4) of 

the ACT and the monitoring of the IOTA 

participant’s compliance with the terms 

of the IOTA Model, including this 

subpart. 

(2) When scheduling the site visit, 

CMS or its designee provides, to the 

extent practicable, the IOTA participant 

with no less than 15 days advance 

notice of any site visit. CMS— 

(i) Attempts, to the extent practicable, 

to accommodate a request for particular 

dates in scheduling site visits; and 

(ii) Does not accept a date request 

from the IOTA participant that is more 

than 60 days after the date of the initial 

site visit notice from CMS. 

(3) The IOTA participant must ensure 

that personnel with the appropriate 

responsibilities and knowledge 

associated with the purpose of the site 

visit are available during all site visits. 

(4) CMS may perform unannounced 

site visits at the office of the IOTA 

participant at any time to investigate 

concerns about the health or safety of 

attributed patients or other program 

integrity issues. 

(5) Nothing in this part may be 

construed to limit or otherwise prevent 


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CMS from performing site visits 

permitted or required by applicable law. 

(d) Reopening of payment 

determinations. (1) CMS may reopen an 

IOTA Model-specific payment 

determination on its own motion or at 

the request of the IOTA participant, 

within 4 years from the date of the 

determination, for good cause (as 

defined at § 405.986 of this chapter) 

except if there exists reliable evidence 

that the determination was procured by 

fraud or similar fault as defined at 

§ 405.902 of this chapter. In the case of 

fraud or similar fault, CMS may reopen 

an IOTA Model specific payment 

determination at any time. 

(2) CMS’ decision regarding whether 

to reopen a model-specific payment 

determination is binding and not subject 

to appeal. 

§ 512.464 Remedial action. 

(a) Grounds for remedial action. CMS 

may impose one or more remedial 

actions described in paragraph (b) of 

this section if CMS determines that: 

(1) The IOTA participant has failed to 

furnish 11 or more kidney transplants 

for patients aged 18 years or older, 

regardless of payer, during a PY or any 

baseline years. 

(2) The IOTA participant or its IOTA 

collaborator has failed to comply with 

any of the terms of the IOTA Model, 

including this subpart. 

(3) The IOTA participant has failed to 

comply with transparency requirements 

described at § 512.442. 

(4) The IOTA participant or its IOTA 

collaborator has failed to comply with 

any applicable Medicare program 

requirement, rule, or regulation. 

(5) The IOTA participant or its IOTA 

collaborator has taken any action that 

threatens the health or safety of an 

attributed patient. 

(6) The IOTA participant or its IOTA 

collaborator has submitted false data or 

made false representations, warranties, 

or certifications in connection with any 

aspect of the IOTA Model. 

(7) The IOTA participant or its IOTA 

collaborator has undergone a change in 

control that presents a program integrity 

risk. 

(8) The IOTA participant or its IOTA 

collaborator is subject to any sanctions 

of an accrediting organization or a 

Federal, State, or local government 

agency. 

(9) The IOTA participant or its IOTA 

collaborator is subject to investigation or 

action by HHS (including the HHS 

Office of Inspector General or CMS) or 

the Department of Justice due to an 

allegation of fraud or significant 

misconduct, including any of the 

following: 

(i) Being subject to the filing of a 

complaint or filing of a criminal charge. 

(ii) Being subject to an indictment. 

(iii) Being named as a defendant in a 

False Claims Act qui tam matter in 

which the Federal Government has 

intervened, or similar action. 

(10) The IOTA participant or its IOTA 

collaborator has failed to demonstrate 

improved performance following any 

remedial action imposed under this 

section. 

(11) The IOTA participant has 

misused or disclosed beneficiaryidentifiable data in a manner that 

violates any applicable statutory or 

regulatory requirements or that is 

otherwise non-compliant with the 

provisions of the applicable data sharing 

agreement. 

(b) Remedial actions. If CMS 

determines that one or more grounds for 

remedial action described in paragraph 

(a) of this section has taken place, CMS 

may take one or more of the following 

remedial actions: 

(1) Notify the IOTA participant and, if 

appropriate, require the IOTA 

participant to notify its IOTA 

collaborators of the violation. 

(2) Require the IOTA participant to 

provide additional information to CMS 

or its designees. 

(3) Subject the IOTA participant to 

additional monitoring, auditing, or both. 

(4) Prohibit the IOTA participant from 

distributing model-specific payments, as 

applicable. 

(5) Require the IOTA participant to 

terminate, immediately or by a deadline 

specified by CMS, its sharing 

arrangement with an IOTA collaborator 

with respect to the IOTA Model. 

(6) Terminate the IOTA participant 

from the IOTA Model. 

(7) Suspend or terminate the ability of 

the IOTA participant to provide Part B 

and Part D immunosuppressive drug 

cost sharing support in accordance with 

§ 512.456 or attributed patient 

engagement incentives in accordance 

with § 512.458. 

(8) Require the IOTA participant to 

submit a corrective action plan in a form 

and manner and by a deadline specified 

by CMS. 

(9) Discontinue the provision of data 

sharing and reports to the IOTA 

participant. 

(10) Recoup model-specific payments. 

(11) Reduce or eliminate a modelspecific payment otherwise owed to the 

IOTA participant. 

(13) Any other action as may be 

permitted under the terms of this part. 

§ 512.466 Termination. 

(a) Termination of IOTA participant 

from the IOTA Model by CMS. CMS may 

immediately or with advance notice 

terminate an IOTA participant from 

participation in the model if CMS does 

any of the following: 

(1) Determines that it no longer has 

the funds to support the IOTA Model. 

(2) Modifies or terminates the IOTA 

Model in accordance with section 

1115A(b)(3)(B) of the Act. 

(3) Determines that the IOTA 

participant has done any of the 

following: 

(i) Failed to comply with any model 

requirements or any other Medicare 

program requirement, rule, or 

regulation. 

(ii) Failed to comply with a 

monitoring or auditing plan or both. 

(iii) Failed to submit, obtain approval 

for, implement or fully comply with the 

terms of a corrective action plan. 

(iv) Failed to demonstrate improved 

performance following any remedial 

action. 

(v) Taken any action that threatens the 

health or safety of a Medicare 

beneficiary or other patient. 

(vi) Submitted false data or made false 

representations, warranties, or 

certifications in connection with any 

aspect of the IOTA Model. 

(vii) Undergoes a change in control. 

(viii) Assigns or purports to assign 

any of the rights or obligations under 

the IOTA Model, voluntarily or 

involuntarily, whether by merger, 

consolidation, dissolution, operation of 

law, or any other manner, without the 

written consent of CMS. 

(ix) Poses significant program 

integrity risks, including but not limited 

to— 

(A) Is subject to sanctions or other 

actions of an accrediting organization or 

a Federal, State, or local government 

agency; or 

(B) Is subject to investigation or action 

by HHS (including OIG and CMS) or the 

Department of Justice due to an 

allegation of fraud or significant 

misconduct, including being subject to 

the filing of a complaint, filing of a 

criminal charge, being subject to an 

indictment, being named as a defendant 

in a False Claims Act qui tam matter in 

which the government has intervened, 

or similar action. 

(b) Termination of Model 

participation by IOTA participant. The 

IOTA participant may not terminate 

their participation in the IOTA Model. 

(c) Financial settlement upon 

termination. If CMS terminates the 

IOTA participant’s participation in the 

IOTA Model, CMS calculates the final 

performance score and any upside risk 

payment or downside risk payment, if 

applicable, for the entire PY in which 

the IOTA participant’s participation in 

the model was terminated. 


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(1) If CMS terminates the IOTA 

participant’s participation in the IOTA 

Model, CMS determines the IOTA 

participant’s effective date of 

termination. 

(2) If CMS terminates the IOTA 

participant for any reasons listed under 

§ 512.466: 

(i) CMS does not make any payments 

of upside risk payment for the PY in 

which the IOTA participant was 

terminated; and 

(ii) The IOTA participant will remain 

liable for payment of any downside risk 

payment up to and including the PY in 

which termination becomes effective. 

(d) Termination of the IOTA Model by 

CMS. (1) The general provisions for the 

Innovation Center model termination by 

CMS listed under § 512.165 apply to the 

IOTA Model. 

(i) CMS may terminate the IOTA 

Model for reasons including, but not 

limited to, those set forth in 

§ 512.165(a). 

(ii) If CMS terminates the IOTA 

Model, CMS provides written notice to 

IOTA participants specifying the 

grounds for model termination and the 

effective date of such termination. 

(2) In accordance with section 

1115A(d)(2) of the Act and § 512.170(e), 

termination of the IOTA Model under 

section 1115A(b)(3)(B) of the Act is not 

subject to administrative or judicial 

review. 

(3) If CMS terminates the IOTA 

Model, the financial settlement terms 

described in paragraph (c) of this 

section apply. 

§ 512.468 Bankruptcy and other 

notifications. 

(a) Notice of bankruptcy. (1) If the 

IOTA participant has filed a bankruptcy 

petition, whether voluntary or 

involuntary, the IOTA participant must 

provide written notice of the bankruptcy 

to CMS and to the U.S. Attorney’s Office 

in the district where the bankruptcy was 

filed, unless final payment has been 

made by either CMS or the IOTA 

participant under the terms of each 

model tested under section 1115A of the 

Act in which the IOTA participant is 

participating or has participated and all 

administrative or judicial review 

proceedings relating to any payments 

under such models have been fully and 

finally resolved. 

(2) The notice of bankruptcy must 

meet all of the following: 

(i) Be sent by certified mail no later 

than 5 days after the petition has been 

filed. 

(ii) Contain— 

(A) A copy of the filed bankruptcy 

petition (including its docket number); 

and 

(B) A list of all models tested under 

section 1115A of the Act in which the 

IOTA participant is participating or has 

participated. 

(b) Change in control. (1) The IOTA 

participant must provide written notice 

to CMS at least 90 days before the 

effective date of any change in control. 

(2) CMS may terminate an IOTA 

participant from the IOTA Model under 

§ 512.466 if the IOTA participant 

undergoes a change in control. 

(c) Prohibition on assignment. (1) 

Unless CMS provides prior written 

consent, an IOTA participant must not 

transfer, including by merger (whether 

the IOTA participant is the surviving or 

disappearing entity), consolidation, 

dissolution, or otherwise any— 

(i) Discretion granted it under the 

model; 

(ii) Right that it has to satisfy a 

condition under the model; 

(iii) Remedy that it has under the 

model; or 

(iv) Obligation imposed on it under 

the model. 

(2) The IOTA participant must 

provide CMS 90 days advance written 

notice of any such proposed transfer. 

(3) This obligation remains in effect 

after the expiration or termination of the 

model, or the IOTA participant’s 

participation in the model, and until 

final payment by the IOTA participant 

under the model has been made. 

(4) CMS may condition its consent to 

such transfer on full or partial 

reconciliation of upside risk payments 

and downside risk payments. 

(5) Any purported transfer in 

violation of this requirement is voidable 

at the discretion of CMS. 

Waivers 

§ 512.470 Waivers. 

CMS waives the requirements of 

sections 1881(b), 1833(a) and 1833(b) of 

the Act only to the extent necessary to 

make the payments under the IOTA 

Model described in this subpart. 

Xavier Becerra, 

Secretary, Department of Health and Human 

Services. 

[FR Doc. 2024–27841 Filed 11–26–24; 4:15 pm] 

BILLING CODE 4120–01–P 


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