```

[Federal Register Volume 89, Number 233 (Wednesday, December 4, 2024)]
[Rules and Regulations]
[Pages 96280-96463]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2024-27841]

[[Page 96279]]

Vol. 89

Wednesday,

No. 233

December 4, 2024

Part II

Department of Health and Human Services

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Centers for Medicare & Medicaid Services

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42 CFR Part 512

Medicare Program; Alternative Payment Model Updates and the Increasing 
Organ Transplant Access (IOTA) Model; Final Rule

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

[[Page 96280]]

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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.

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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 End-Stage 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.
    [email protected] for questions related to the Increasing 
Organ Transplant Access Model.
    [email protected] 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[supreg] codes and 
descriptions to refer to a variety of services. We note that 
CPT[supreg] codes and descriptions are copyright 2020 American Medical 
Association (AMA). All Rights Reserved. CPT[supreg] 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.
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    \1\ U.S. Congress. (1940) United States Code: Social Security 
Act, 42 U.S.C. 1315a(b)(2)(a).
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    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

[[Page 96281]]

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. Model-specific 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.
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    \2\ End-Stage Renal Disease (ESRD) [verbar] CMS. (n.d.). https://www.cms.gov/medicare/coordination-benefits-recovery/overview/end-stage-renal-disease-esrd.
    \3\ United 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.
    \4\ Tonelli, 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.
    \5\ Cheng, 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.
    \6\ Al 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.
    \7\ Mohan, 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.
    \8\ https://doi.org/10.1016/j.ekir.2023.02.1081.
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    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.

[[Page 96282]]

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 performance-based 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 
performance-based 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

[[Page 96284]]

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.
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    \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 Sec.  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 Sec.  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.
---------------------------------------------------------------------------

    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: 
Sec.  512.120 Beneficiary protections; Sec.  512.130 Cooperation in 
model evaluation and monitoring; Sec.  512.135 Audits and record 
retention; Sec.  512.140 Rights in data and intellectual property: 
Sec.  512.150 Monitoring and compliance; Sec.  512.160 Remedial action; 
Sec.  512.165 Innovation center model termination by CMS; Sec.  512.170 
Limitations on review; and Sec.  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

[[Page 96285]]

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 Sec.  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 Sec.  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-for-
service, 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 Sec.  
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 Sec.  
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 Sec.  512.100(a)--``Basis''--to provide that 
the standard provisions apply to ``certain'' Innovation Center models. 
At Sec.  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 Sec.  512.110 to mean, ``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.'' We proposed to add a new definition, ``standard provisions for 
Innovation Center models,'' at Sec.  512.110 to mean the provisions 
codified in 42 CFR part 512 subpart A. We proposed to add a new 
definition, ``performance period,'' at Sec.  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

[[Page 96286]]

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 Sec.  512.110 
without modification.

E. Proposed Reconsideration Review Process

    We proposed to add a new Sec.  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 
Sec.  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 Sec.  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 model-specific 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 Sec.  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 Sec.  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 Sec.  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 Sec.  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 Sec.  512.190(b)(2), we proposed that requests that 
do not meet the requirements of paragraph (b)(1) would be denied.
    We proposed at Sec.  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 Sec.  512.190(b)(4) that, to access the 
reconsideration process for a determination concerning a model-specific 
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 Sec.  
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 Sec.  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 Sec.  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 Sec.  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 Sec.  512.190(b)(3)(ii) and that meet 
the standards of submission under proposed Sec.  512.190(b)(1) as well 
as any

[[Page 96287]]

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 Sec.  
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 
Sec.  512.190(b)(3)(ii). Under proposed Sec.  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 Sec. Sec.  512.190(e)(1) 
and (2).
    We proposed to codify at Sec.  512.190(e) a process for the CMS 
Administrator to review reconsideration determinations made under Sec.  
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 
Sec.  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 Sec.  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 performance-based 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.
---------------------------------------------------------------------------

    \10\ Mohan, 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.
---------------------------------------------------------------------------

    The achievement domain will assess the number of kidney transplants 
performed relative to a participant-specific 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:

[[Page 96288]]

     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\
---------------------------------------------------------------------------

    \11\ Moody-Williams, J.D., & Nair, S. (2023, September 15). 
Organ Transplantation Affinity Group (OTAG): Strengthening 
accountability, equity, and performance [verbar] CMS. BLOG. https://www.cms.gov/blog/organ-transplantation-affinity-group-otag-strengthening-accountability-equity-and-performance.
---------------------------------------------------------------------------

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.
---------------------------------------------------------------------------

    \12\ Penn 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-discarded-in-us-before-transplantationwww.pennmedicine.org.
    \13\ Hariharan, 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.
    \14\ Stewart, 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.
    \15\ Mohan, 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.
---------------------------------------------------------------------------

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.
---------------------------------------------------------------------------

    \16\ Moody-Williams, J.D., & Nair, S. (2023, September 15). 
Organ Transplantation Affinity Group (OTAG): Strengthening 
accountability, equity, and performance [verbar] CMS. BLOG. https://www.cms.gov/blog/organ-transplantation-affinity-group-otag-strengthening-accountability-equity-and-performance.
---------------------------------------------------------------------------

    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

[[Page 96289]]

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\
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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.
    \18\ Chadban, 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.
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    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\
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    \19\ National kidney Foundation. (2017, February 10). The Kidney 
Transplant Waitlist--What You Need to Know. National Kidney 
Foundation. https://www.kidney.org/atoz/content/transplant-waitlist.
    \20\ The kidney transplant waitlist. (n.d.). Transplant Living. 
https://transplantliving.org/kidney/the-kidney-transplant-waitlist/.
    \21\ National kidney Foundation. (2019, June 12). Understanding 
the transplant waitlist. National Kidney Foundation. https://www.kidney.org/content/understanding-transplant-waitlist.
    \22\ National kidney Foundation. (2016, August 4). Multiple 
Listing for Kidney Transplant. National Kidney Foundation. https://www.kidney.org/atoz/content/multiple-listing.
    \23\ Transplant Nephrology Fellowship. (n.d.). 
www.hopkinsmedicine.org. Retrieved May 30, 2023, from https://www.hopkinsmedicine.org/nephrology/education/transplant-fellowship.
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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

[[Page 96290]]

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\
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    \24\ On 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.
    \25\ Mission, Vision, and Values. (n.d.). www.srtr.org. https://www.srtr.org/about-srtr/mission-vision-and-values/.
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    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.
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    \26\ U.S. Congress. (1934) United States Code: Social Security 
Act, 42 U.S.C. 301-Suppl. 4 1934.
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    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.
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    \27\ Bylaws-OPTN. (n.d.). Optn.transplant.hrsa.gov. Retrieved 
September 13, 2024, from https://optn.transplant.hrsa.gov/media/lgbbmahi/optn_bylaws.pdf.
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    Medicare covers certain transplant-related 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 three-years 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 re-approval 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\
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    \28\ The 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.
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    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.
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    \29\ One 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).
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    We published a request for information in the Federal Register on

[[Page 96291]]

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 in-center 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 health-related outcomes for patients with 
late-stage 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.
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    \31\ The 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.
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    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 dialysis-related 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

[[Page 96292]]

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).
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    \32\ Centers for Medicare & Medicaid Services. https://innovation.cms.gov/innovation-models/esrd-treatment-choices-model.
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    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\
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    \33\ The 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/innovation-models/kidney-care-choices-kcc-model.
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    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.
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    \34\ HRSA Announces Organ Procurement and Transplantation 
Network Modernization Initiative [verbar] HRSA. (n.d.). 
www.hrsa.gov. Retrieved August 20, 2023, from https://www.hrsa.gov/optn-modernization/march-2023.
    \35\ The 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/.
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    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\
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    \36\ OPTN. (n.d.). Bylaws. Retrieved September 15, 2024 from 
https://optn.transplant.hrsa.gov/media/lgbbmahi/optn_bylaws.pdf.
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     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

[[Page 96293]]

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--
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    \37\ Moody-Williams, J.D., & Nair, S. (2023, December 13). Organ 
Transplantation Affinity Group (OTAG): Strengthening accountability, 
equity, and performance [verbar] CMS. BLOG. https://www.cms.gov/blog/organ-transplantation-affinity-group-otag-strengthening-accountability-equity-and-performance.
    \38\ Moody-Williams, J.D., & Nair, S. (2023, December 13). Organ 
Transplantation Affinity Group (OTAG): Strengthening accountability, 
equity, and performance [verbar] CMS. BLOG. https://www.cms.gov/blog/organ-transplantation-affinity-group-otag-strengthening-accountability-equity-and-performance.
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     Reduce variation of pre-transplant and referral practices; 
\39\
---------------------------------------------------------------------------

    \39\ Pre-transplant/referral practices are inclusive of the 
referring physician's assessment criteria, patient education, and 
feedback to the referring physician from the transplant assessment.
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     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

[[Page 96294]]

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\
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    \40\ United States Renal Data System. 2023. End Stage Renal 
Disease: Chapter 1. Figure 1.5.
    \41\ United States Renal Data System. 2023. End Stage Renal 
Disease: Chapter 1. Figure 1.7.
    \42\ United States Renal Data System. 2023. End Stage Renal 
Disease: Chapter 1. Figure 1.8.
    \43\ United States Renal Data System. 2023. End Stage Renal 
Disease. Chapter 1. Table 1.3.
    \44\ National Kidney Foundation. (2016, January 7). Race, 
Ethnicity and Kidney Disease. National Kidney Foundation. https://www.kidney.org/atoz/content/minorities-KD.
    \45\ United States Renal Data System. 2023. End Stage Renal 
Disease. Chapter 1. Figure 1.1.
    \46\ Strohmaier, 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 Transplant-Eligible Patients 
With Kidney Failure. JAMA Network Open, 5(10), e2234971. https://doi.org/10.1001/jamanetworkopen.2022.34971.
    \47\ Tonelli, 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.
    \48\ United States Renal Data System. 2023. End Stage Renal 
Disease: Chapter 7. Figure 7.16.
    \49\ United States Renal Data System. 2023. End Stage Renal 
Disease: Chapter 7. Figures 7.1 and 7.2.
    \50\ United States Renal Data System. 2022. End Stage Renal 
Disease: Chapter 9.
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    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.
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    \51\ According 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-data-reports/national-data/.
    \52\ Health 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.
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    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\
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    \53\ United 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.
    \54\ United 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.
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    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 long-term 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
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    \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/transplant-update/2019/july/kidney-transplant-facts-before-dialysis.
    \56\ Organ Procurement and Transplantation Network. Kidney Donor 
Profile Index (KDPI) Guide for Clinicians. https://optn.transplant.hrsa.gov/professionals/by-topic/guidance/kidney-donor-profile-index-kdpi-guide-for-clinicians/#:~:https://optn.transplant.hrsa.gov/professionals/by-topic/guidance/kidney-donor-profile-index-kdpi-guide-for-clinicians/.
    \57\ Tonelli, 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.
    \59\ United 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.
    \60\ United 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.
    \61\ Nemati, 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.
    \62\ United 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.
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    A cost advantage also arises with kidney transplantation. Per-
person per-

[[Page 96295]]

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\
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    \63\ 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.
    \64\ Fu, R., Sekercioglu, N., Berta, W., & Coyte, P.C. (2020). 
Cost-effectiveness of Deceased-donor Renal Transplant Versus 
Dialysis to Treat End-stage Renal Disease. Transplantation Direct, 
6(2), e522. https://doi.org/10.1097/txd.0000000000000974.
    \65\ Khan, S., Tighiouart, H., Kalra, A., Raman, G., Rohrer, 
R.J., & Pereira, B.J.G. (2003). Resource utilization among kidney 
transplant recipients. Kidney International, 64(2), 657-664. https://doi.org/10.1046/j.1523-1755.2003.00102.x.
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    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.
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    \66\ United States Renal Data System. 2022 Annual Data Report. 
Volume 2. End Stage Renal Disease Chapter 7 Transplantation Figure 
7.16.
    \67\ United States Renal Data System. 2018. Annual Data Report. 
Volume 2. Chapter 1: Incidence, Prevalence, Patient Characteristics, 
and Treatment Modalities. Figure 1.2. Retrieved from https://www.niddk.nih.gov/about-niddk/strategic-plans-reports/usrds/prior-data-reports/2018.
    \68\ United States Renal Data System. 2022. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 11.17b.
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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 cost-effective 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.
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    \69\ United 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.Volume 2: End-
stage Renal Disease (ESRD) in the United States, Chapter 1: 
Incidence, Prevalence, Patient Characteristics.
    \70\ Scientific Registry of Transplant Recipients. Program 
Specific Reports. www.srtr.org. Retrieved June 15, 2023, from 
https://www.srtr.org/reports/program-specific-reports/.
    \71\ Penn 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-discarded-in-us-before-transplantation.
    \72\ United States Renal Data System. 2022 Annual Data Report. 
Volume 2. End Stage Renal Disease Chapter 7 Transplantation Figure 
7.4.
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    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\
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    \73\ Hariharan, 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.
    \74\ Durand, C.M., Bowring, M.G., Thomas, A.G., Kucirka, L.M., 
Massie, A.B., Cameron, A., Desai, N.M., Sulkowski, M., & Segev, D.L. 
(2018). The Drug Overdose Epidemic and Deceased-Donor 
Transplantation in the United States: A National Registry Study. 
Annals of Internal Medicine, 168(10), 702-711. https://doi.org/10.7326/M17-2451.
    \75\ United States Renal Data System. 2021. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.11.
    \76\ United States Renal Data System. 2021. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.7.
    \77\ United States Renal Data System. 2022. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.10b.
    \78\ United States Renal Data System. 2022. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.16.
    \79\ United States Renal Data System. 2023. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.1.
    \80\ United States Renal Data System. 2023. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.2.
---------------------------------------------------------------------------

    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

[[Page 96296]]

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\
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    \81\ United States Renal Data System. 2012. Annual Data Report. 
Atlas ESRD. Table 7.1.
    \82\ United States Renal Data System. 2023. Annual Data report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.10a.
    \83\ United States Renal Data System. 2022. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.10a.
    \84\ Charnow, J.A. (2021, June 8). Living Donor Kidney 
Transplants Declined in the Last Decade. Renal and Urology News. 
https://www.renalandurologynews.com/news/living-donor-kidney-transplantation-decreased-after-2010-united-states-trends/.
    \85\ Rodrigue, 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.0b013e318298fa61.
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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.
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    \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.2020030335.
    \87\ Melanson 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).
    \88\ United States Renal Data System. 2022. Annual Data Report. 
Supplements: COVID-19, Racial and Ethnic Disparities Figures 14.14 
and 14.15.
    \89\ Wesselman, 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.
    \90\ Ng, 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.
    \91\ With 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.
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    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.
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    \97\ Melanson 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).
---------------------------------------------------------------------------

    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\
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    \98\ United States Renal Data System. 2022. Annual Data Report. 
Supplements: COVID-19, Racial and Ethnic Disparities Figures 14.14 
and 14.15.
    \99\ National Kidney Foundation. (2016, January 7). Race, 
Ethnicity, & Kidney Disease. National Kidney Foundation. https://www.kidney.org/atoz/content/minorities-KD.
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    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

[[Page 96297]]

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.
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    \100\ Patzer, 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.
    \101\ Patzer, 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.
    \102\ Wesselman, 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.
    \103\ Ng, 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.
    \104\ Schold, 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.
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    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.
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    \105\ Reed, 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.
    \106\ National 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.
    \107\ Centers 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-at-cdc.html?CDC_AAref_Val=https://www.cdc.gov/about/sdoh/index.html.
    \108\ Wesselman et al, 2021.
    \109\ Ng et al, 2020.
    \110\ Centers 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-at-cdc.html?CDC_AAref_Val=https://www.cdc.gov/about/sdoh/index.html.
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    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.
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    \111\ Ng Y et al. 2020. 1453.
    \112\ Wesselman et al, 2021. 271.
    \113\ Wesselman et al. 2021. 262.
    \114\ Schold et al, 2021.
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    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
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    \115\ Wesselman et al, 2021. 270.
    \116\ United States Renal Data System. 2022. Annual Data Report. 
End Stage Renal Disease Chapter 7 Transplantation Figure 7.10a.
    \117\ Purnell, 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.
    \118\ Rodrigue, 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.
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    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\
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    \119\ Purnell, 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.
    \120\ Hall, 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.
    \122\ Rodrigue et al. 2015.
    \123\ Purnell et al. 2015. 58.
    \124\ Purnell et al. 2015. 59.
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    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

[[Page 96298]]

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\
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    \125\ Hall et al. 2012. 855.
    \126\ Hall et al. 2012. 855.
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    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\
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    \127\ See, 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-transplant-discrimination-against-people-with-disabilities.
    \128\ Id. at 38-40.
    \129\ Am. 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.
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    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\
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    \130\ United States Renal Data System. 2023. Annual Data Report. 
Volume 2. End Stage Renal Disease. Transplantation. Figures 7.19a 
and 7.19b.
    \131\ United States Renal Data System. 2023. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figures 7.20a and 7.20b.
    \132\ United States Renal Data System. 2023. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.21a.
    \133\ United States Renal Data System. 2023. Annual Data Report 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.21b.
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    A study published in the New England Journal of Medicine in 2021 
shows the advantage of transplantation using deceased donor organs over 
long-term 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\
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    \134\ Hariharan, 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.
    \135\ Hariharan, 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.
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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

[[Page 96299]]

in non-utilization.\141\ Within the context of the COVID-19 pandemic, 
the non-utilization 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 C-positive donors.142 143 
According to one analysis, the deceased donor kidney discard rate 
peaked at 27 percent during the fourth quarter of 2021.\144\
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    \136\ Mohan, 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.
    \137\ Aubert, 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.
    \139\ Stewart, 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.
    \140\ Health 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/two-year-analysis-shows-effects-of-kidney-allocation-system/.
    \141\ Mohan, Chiles et al. (2018).
    \142\ Lentine, 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.
    \143\ Following 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 HCV-Negative Recipients'' August 31, 
2020 https://www.pennmedicine.org/news/news-releases/2020/august/penn-researchers-advance-transplantation-hepatitis-c-virus-infected-kidneys-hcv-negative-recipients.
    \144\ Cron, 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.
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    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 post-transplant 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 zero-to-100 scale. Lower KDPI scores are associated with 
greater expected post-transplant longevity, while higher KDPI scores 
are associated with a worse expected outcome in this regard.\148\
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    \145\ OPTN 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.
    \146\ OPTN. (n.d.) The New Kidney Allocation System (KAS) 
Frequently Asked Questions. https://optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. p. 4.
    \147\ OPTN. (n.d.). The New Kidney Allocation System Frequently 
Asked Questions. https://optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. pp. 8-9.
    \148\ OPTN. (n.d.). The New Kidney Allocation System Frequently 
Asked Questions . https://optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. p. 4.
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    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\
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    \149\ OPTN. (n.d.). The New Kidney Allocation System Frequently 
Asked Questions. https://optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. p. 4.
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    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\
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    \150\ OPTN. (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-analysis-shows-effects-of-kidney-allocation-system/.
    \151\ OPTN. (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-analysis-shows-effects-of-kidney-allocation-system/.
---------------------------------------------------------------------------

    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\
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    \152\ Potluri, 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.
    \153\ Penn 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/penn-physician-blog/2021/november/change-in-organ-allocation-designed-to-increase-equity-in-us-kidney-and-pancreas-transplantation.
    \154\ Potluri, Bloom. (2021). 897-898.
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    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

[[Page 96300]]

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\
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    \155\ Potluri, 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.
    \157\ Chow, E.M., DiBrito, S.R., Luo, X., Wickliffe, C., Massie, 
A.B., Locke, J.E., Gentry, S.E., Garonzik-Wang, 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.
    \158\ Adler, 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.
    \159\ Adler et al., 2021. 2012.
    \160\ Cron, 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.
---------------------------------------------------------------------------

    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
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    \161\ Mohan, Chiles et al. 2018. p. 192.
    \162\ Mohan et al. 2018. p. 195.
    \163\ Mohan et al. 2018. 192.
    \164\ Ojo, A.O., Hanson, J.A., Herwig Ulf Meier-Kriesche, 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.
    \165\ Massie, 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.
    \166\ Cohen, 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.
---------------------------------------------------------------------------

    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 non-utilization 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\
---------------------------------------------------------------------------

    \167\ Stewart et al. (2017). 575.
    \168\ Stewart et al. (2017). 585.
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    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\
---------------------------------------------------------------------------

    \169\ National kidney Foundation. (2017, February 10). The 
Kidney Transplant Waitlist--What You Need to Know. National Kidney 
Foundation. https://www.kidney.org/atoz/content/transplant-waitlist.
    \170\ Husain, 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.
    \171\ Husain et al. 2019.
    \172\ Husain et al. 2019.
---------------------------------------------------------------------------

    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 
non-acceptance 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

[[Page 96301]]

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.
---------------------------------------------------------------------------

    \173\ Wolfe, R.A., Laporte, F., Rodgers, A.M., Roys, E., Fant, 
G., & Leichtman, A.B. (2007). Developing Organ Offer and Acceptance 
Measures: When ``Good'' Organs Are Turned Down. American Journal of 
Transplantation, 7, 1404-1411. https://doi.org/10.1111/j.1600-6143.2007.01784.x.
---------------------------------------------------------------------------

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\
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    \174\ OPTN/SRTR 2020 Annual Data Report. 2020. Liver. Figures LI 
49, 50.
    \175\ OPTN/SRTR 2021 Annual Data Report. Pancreas. Figures PA 
39, 43.
    \176\ OPTN/SRTR 2021 Annual Data Report. Heart. Figure HR 52.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \177\ Merion, 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.
    \178\ Ross, K., Patzer, R.E., Goldberg, D.S., & Lynch, R.J. 
(2017). Sociodemographic Determinants of Waitlist and Posttransplant 
Survival Among End-Stage Liver Disease Patients. American Journal of 
Transplantation, 17(11), 2879-2889. https://doi.org/10.1111/ajt.14421.
    \179\ Lai, 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.
---------------------------------------------------------------------------

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.
---------------------------------------------------------------------------

    \180\ Moody-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-transplantation-affinity-group-otag-strengthening-accountability-equity-and-performance.
---------------------------------------------------------------------------

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

[[Page 96302]]

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 six-year 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.
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    \181\ https://www.hrsa.gov/about/news/press-releases/organ-procurement-transplantation-network-modernization-initiative.
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    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 Sec.  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 Sec.  512.402 with slight 
modification to specify a July 1, 2025, model start date, and 
finalizing our proposed definition for performance year at Sec.  
512.402 with modification to specify a 12-month period beginning on 
July 1 and ending

[[Page 96303]]

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 
performance-based 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 Sec.  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 
Sec. Sec.  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 Sec.  
512.402.
3. IOTA Participants
a. Proposed Participants
    We proposed to define ``IOTA participant'' as a kidney transplant 
hospital, as defined at Sec.  512.402, that is required to participate 
in the IOTA Model pursuant to Sec.  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 post-
transplant 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 cost-effective treatment. The IOTA 
Model aims to improve quality of care for ESRD patients on the waiting 
list pre-transplant, 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

[[Page 96304]]

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 Sec.  
512.402, that is required to participate in the IOTA Model pursuant to 
Sec.  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 safety-net 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).
---------------------------------------------------------------------------

    \182\ James. (2024, January 31). FAQ: New Multi-organ polices in 
effect. UNOS. https://unos.org/news/faq-safety-net-policies-for-multi-organ-transplantation/ 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/public-comment/establish-
eligibility-criteria-and-safety-net-for-heart-kidney-and-lung-
kidney-allocation/
#:~:text=At%20a%20glance&text=The%20eligibility%20is%20based%20on,saf
ety%20net%E2%80%9D%20for%20these%20patients.
---------------------------------------------------------------------------

    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 Sec.  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 Sec.  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

[[Page 96305]]

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 dual-
eligible 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

[[Page 96306]]

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 
dual-eligibles 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 two-sided 
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 lower-volume 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.

[[Page 96307]]

    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 Sec.  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.

[[Page 96308]]

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 Sec.  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.
---------------------------------------------------------------------------

    \183\ This 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.
---------------------------------------------------------------------------

    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

[[Page 96309]]

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 
low-volume 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 low-volume 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 year-to-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.
---------------------------------------------------------------------------

    \184\ A 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.
---------------------------------------------------------------------------

    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

[[Page 96310]]

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 pre-emptive 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

[[Page 96311]]

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 non-utilization 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 Sec.  512.412(a) without 
modification. We received no comments for the proposed definition of 
non-pediatric facility and are finalizing the proposed definitions of 
non-pediatric facility, and baseline years at Sec.  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.
---------------------------------------------------------------------------

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

    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).
---------------------------------------------------------------------------

    \186\ A 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).
---------------------------------------------------------------------------

     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

[[Page 96312]]

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

[[Page 96313]]

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 Sec.  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

[[Page 96314]]

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 low-
volume 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

[[Page 96315]]

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 low-
volume 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 Sec. Sec.  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 Sec.  
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 Sec.  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 Sec.  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 Sec.  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 post-transplant.
    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 non-Medicare 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.

[[Page 96316]]

    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 Sec.  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 
Sec.  512.414 with slight modification. Specifically, we are modifying 
the regulatory text at Sec.  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 Sec.  512.402. We are also making a minor technical 
correction to the proposed definition of IOTA transplant patient at 
Sec.  512.402 to update the cross reference. Specifically, we are 
removing the cross reference to Sec.  512.412(b)(2) and replacing it 
with Sec.  512.414(b)(2). As such, we are finalizing the definition of 
IOTA transplant patient at Sec.  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 Sec.  
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.

[[Page 96317]]

    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 Sec.  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 Sec.  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 re-transplant 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 Sec.  512.414(a) and the definitions of 
attribution and attributed patient at Sec.  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

[[Page 96318]]

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.
---------------------------------------------------------------------------

    \187\ Lentine, 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.
---------------------------------------------------------------------------

    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 Sec.  
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

[[Page 96319]]

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 Sec.  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 de-attribute 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 de-
attribution 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 re-transplant 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 Sec.  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 Sec.  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 Sec.  
512.414(c)(1) and the definition of initial attribution at Sec.  
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

[[Page 96320]]

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 Sec.  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 Sec.  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 de-
attribution pursuant to Sec.  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 Sec. Sec.  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 Sec.  512.414(c)(3), with a minor 
technical correction to update the cross references in the regulation 
text at Sec. Sec.  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 Sec.  
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 
Sec. Sec.  512.414(c)(1)(ii),

[[Page 96321]]

512.414(c)(2)(ii), 512.414(c)(3)(ii) and the definition of days at 
Sec.  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\
---------------------------------------------------------------------------

    \188\ https://optn.transplant.hrsa.gov/about/committees/membership-professional-standards-committee-mpsc/.
---------------------------------------------------------------------------

    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\
---------------------------------------------------------------------------

    \189\ https://optn.transplant.hrsa.gov/about/committees/membership-professional-standards-committee-mpsc/ and Burden 
Reduction. Federal Register. https://www.federalregister.gov/d/2018-19599/p-215.
    \190\ https://optn.transplant.hrsa.gov/media/4777/transplant_program_performance_monitoring_public_comment_aug2021.pdf.

    \191\ Ibid.
---------------------------------------------------------------------------

    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 Sec.  512.422(a), 
without modification. We did not receive any comments regarding

[[Page 96322]]

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 Sec.  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 Sec.  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 
post-transplant 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

[[Page 96323]]

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 post-transplant 
care at the IOTA participant level. In a performance scoring 
methodology focused on the net effect of increased transplants and 
post-transplant 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 performance-based 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 performance-based 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

[[Page 96324]]

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.
---------------------------------------------------------------------------

    \192\ Scientific Registry of Transplant Recipients. (n.d.). Risk 
Adjustment Model: Offer Acceptance. Offer acceptance. https://www.srtr.org/tools/offer-acceptance/.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \193\ Ibid.
---------------------------------------------------------------------------

    Comment: Several commenters conveyed concern that CMS should 
exclude hospice patients from the one-year 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 post-transplant 
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

[[Page 96325]]

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 post-transplant care. Approaches may look 
very different depending on the size, location and resources of an IOTA 
participant. For example, well-established 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 
pre-emptive 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 
post-transplant 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 
non-utilization.
    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 
non-

[[Page 96326]]

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 Sec.  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 
non-participating 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 
high-volume 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 co-morbidities. 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 Sec.  512.422(a), without modification. We are also codifying the 
proposed definition of final performance score at Sec.  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 
participant-specific 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

[[Page 96327]]

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.
---------------------------------------------------------------------------

    \194\ For additional information on SRTR's transplant rate 
measure, please see https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports#figurea2.
    \195\ 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.
    \196\ 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.
---------------------------------------------------------------------------

    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 ``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 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 multi-pronged 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

[[Page 96328]]

their kidney transplant volume in a way that best suits their 
transplant program and community.
---------------------------------------------------------------------------

    \197\ United 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.
---------------------------------------------------------------------------

    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 post-
transplant. 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.
---------------------------------------------------------------------------

    \198\ Penn 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-discarded-in-us-before-transplantation.
---------------------------------------------------------------------------

    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.

[[Page 96329]]

    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 post-transplant. 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 well-established 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 Sec.  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 Sec.  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 Sec.  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 Sec.  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 Sec.  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

[[Page 96330]]

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 up-to-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.

[[Page 96331]]

[GRAPHIC] [TIFF OMITTED] TR04DE24.000

    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.
[GRAPHIC] [TIFF OMITTED] TR04DE24.001

    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 year-over-year (89 FR 43518). 
However, we believe that a fixed baseline may reward a one-time 
investment, rather than continuous improvement, and may not

[[Page 96332]]

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.
---------------------------------------------------------------------------

    \199\ Potluri, 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.
---------------------------------------------------------------------------

    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

[[Page 96333]]

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 Sec.  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

[[Page 96334]]

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 Sec.  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

[[Page 96335]]

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 Sec.  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 Sec.  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 Sec.  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 Sec.  512.424(b) 
that for each PY, CMS will determine the transplant

[[Page 96336]]

target for the achievement domain, as proposed.
    We are codifying in our regulation at Sec.  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 Sec.  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 Sec.  
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 Sec.  512.402.
    We are finalizing our regulation at Sec.  512.424(b)(2) that CMS 
sums the numbers in sections Sec. Sec.  512.424(b)(1)(i) and (ii), 
without modification. We are also finalizing as proposed our provisions 
for calculating the national growth rate at Sec.  512.424(b)(3), 
calculation of transplant target at Sec.  512.582(b)(4), notification 
of transplant target at Sec.  512.424(c) and the definitions of 
transplant target, and pediatric kidney transplant hospitals at Sec.  
512.402. In response to public comments, we are finalizing our proposed 
definition of national growth rate at Sec.  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 Sec.  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 Sec.  
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.
[GRAPHIC] [TIFF OMITTED] TR04DE24.002

    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 pre-emptive 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

[[Page 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 improvement-only 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 year-over-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 Sec.  
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

[[Page 96338]]

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 Sec.  
512.424(f)(2) to reflect the updated points allocation, as illustrated 
in Table 4.
[GRAPHIC] [TIFF OMITTED] TR04DE24.003

    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).

[[Page 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

[[Page 96340]]

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 Sec.  512.424(a) with slight 
modification. Specifically, we are modifying the regulatory text at 
Sec.  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 Sec.  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 Sec.  512.424(f)(1). In particular, we are removing the 
cross reference to the health equity performance adjustment and 
replacing it to reflect Sec.  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 Sec.  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

[[Page 96341]]

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 Sec.  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 Sec.  512.424 of the 
proposed rule). For purposes of the model, we proposed to define the 
``low-income 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 low-income 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\
---------------------------------------------------------------------------

    \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-care-service-utilization.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \201\ United 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.
    \202\ Lentine, 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.
---------------------------------------------------------------------------

    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 low-income 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 low-income 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 low-income 
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 low-income 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.
---------------------------------------------------------------------------

    \203\ Neighborhood Atlas--Home. (2018). Wisc.edu. https://www.neighborhoodatlas.medicine.wisc.edu/.
    \204\ https://www2.census.gov/geo/pdfs/reference/GARM/Ch11GARM.pdf.
---------------------------------------------------------------------------

    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

[[Page 96342]]

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 low-income 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

[[Page 96343]]

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 low-income, citing their 
frequent socioeconomic barriers, and urged CMS to revise the proposed 
definition of low-income 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, 
Medicare-Medicaid 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 low-income. 
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

[[Page 96344]]

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 low-income 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 low-income 
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

[[Page 96345]]

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 Sec.  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 Sec. Sec.  512.424(d)(1)(i) and (2) to remove the cross 
reference to the health equity performance adjustment.
d. Efficiency Domain
    At Sec.  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 Sec.  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.
---------------------------------------------------------------------------

    \205\ MN, 1Scientific R. of T.R., Hennepin Healthcare Research 
Institute, Minneapolis. (n.d.). Kidney. Srtr.transplant.hrsa.gov. 
Retrieved June 19, 2023, from https://srtr.transplant.hrsa.gov/annual_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 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.
    \207\ 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.
---------------------------------------------------------------------------

    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\
---------------------------------------------------------------------------

    \208\ Enhance 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.

---------------------------------------------------------------------------

    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

[[Page 96346]]

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 decision-making.
---------------------------------------------------------------------------

    \209\ Schold, 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., & Goldfarb-Rumyantzev, 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.
---------------------------------------------------------------------------

    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\
---------------------------------------------------------------------------

    \210\ Husain, 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.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \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.
    \212\ Shepherd, 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.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \213\ Paul, 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.
    \214\ Shepherd, 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., Pe[ntilde]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.
---------------------------------------------------------------------------

    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\

[[Page 96347]]

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.
---------------------------------------------------------------------------

    \215\ 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.
    \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 Kidney Transplantation Among Patients With End-Stage Renal 
Disease in Georgia. JAMA, 314(6), 582. https://doi.org/10.1001/jama.2015.8897.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \217\ Cheng, 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.
---------------------------------------------------------------------------

    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. Pre-existing 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.
---------------------------------------------------------------------------

    \218\ Mohan, 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.
    \219\ Wood, 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.
    \220\ UNOS. (2023, September 5). Research in focus: Examining 
organ offers. Retrieved October 11, 2024 from https://unos.org/news/in-focus/organ-offers/#Impact.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \221\ OPTN. (2023, September 14). New pre-transplant performance 
metric now in effect, offer acceptance rate ratio. Retrieved August 
15, 2024 from https://optn.transplant.hrsa.gov/news/new-pre-transplant-performance-metric-now-in-effect-offer-acceptance-rate-ratio/.
---------------------------------------------------------------------------

    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

[[Page 96348]]

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 non-use 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 non-use 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

[[Page 96349]]

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 Sec. Sec.  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 Sec.  
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 Sec.  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 Sec.  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\
---------------------------------------------------------------------------

    \222\ OPTN. (2022). OPTN Enhanced Transplant Program Performance 
Metrics. https://optn.transplant.hrsa.gov/media/r5lmmgcl/mpsc_performancemetrics_3242022b.pdf.
    \223\ Mpsc-enhance-transplant-program-performance-monitoring-
system_srtr-metrics.pdf. (n.d.). Retrieved December 28, 2022, from 
https://optn.transplant.hrsa.gov/media/qfuj3osi/mpsc-enhance-transplant-program-performance-monitoring-system_srtr-metrics.pdf.
---------------------------------------------------------------------------

Equation 1: Organ Offer Acceptance Rate Ratio \224\
---------------------------------------------------------------------------

    \224\ Ibid.
    [GRAPHIC] [TIFF OMITTED] TR04DE24.004
    
    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.
---------------------------------------------------------------------------

    \225\ Scientific Registry of Transplant Recipients. (n.d.). Risk 
Adjustment Model: Offer Acceptance. Offer acceptance. https://www.srtr.org/tools/offer-acceptance/.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \226\ Ibid.
    \227\ SRTR. (2023). Srtr.org. https://tools.srtr.org/OAModelApp_2205/; Ibid.
---------------------------------------------------------------------------

    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\
---------------------------------------------------------------------------

    \228\ CMS 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 (https://optn.transplant.hrsa.gov/media/eavh5bf3/optn_policies.pdf.
    \230\ Expedited 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 [verbar] The New MPSC Metric. 
(n.d.). The Organ Donation and Transplantation Alliance. Retrieved 
February 23, 2024, from https://www.organdonationalliance.org/insights/quality-corner/new-mpsc-metric/.

---------------------------------------------------------------------------

[[Page 96351]]

[GRAPHIC] [TIFF OMITTED] TR04DE24.006

    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.
---------------------------------------------------------------------------

    \232\ OPTN. (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.
---------------------------------------------------------------------------

    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.

[[Page 96352]]

    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.
---------------------------------------------------------------------------

    \233\ Liyanage, 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.
---------------------------------------------------------------------------

    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 non-
viable 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

[[Page 96353]]

results warrant a new or updated policy, we will address it pursuant to 
future rulemaking.
---------------------------------------------------------------------------

    \234\ OPTN. (2023, September 14). New pre-transplant performance 
metric now in effect, offer acceptance rate ratio. Retrieved August 
15, 2024 from https://optn.transplant.hrsa.gov/news/new-pre-transplant-performance-metric-now-in-effect-offer-acceptance-rate-ratio/.
---------------------------------------------------------------------------

    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 Sec.  
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 Sec.  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 two-scoring 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\
---------------------------------------------------------------------------

    \235\ Subsequent 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.
---------------------------------------------------------------------------

    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.

[[Page 96354]]

[GRAPHIC] [TIFF OMITTED] TR04DE24.007

    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
[GRAPHIC] [TIFF OMITTED] TR04DE24.008

    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 high-achieving 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

[[Page 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 post-transplant 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 Sec.  
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 Sec.  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 Sec.  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
[GRAPHIC] [TIFF OMITTED] TR04DE24.009

    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

[[Page 96356]]

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 Sec.  
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 Sec.  512.426(c)(2)(i) and in Table 
1 to Paragraph (c)(1)(i) at our regulation at Sec.  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

[[Page 96357]]

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-of-sequence 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 non-use, 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

[[Page 96358]]

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 Sec.  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 Sec.  512.426(c)(2)(i) and in Table 1 
to Paragraph (c)(1)(i) at our regulation at Sec.  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 Sec.  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 Sec.  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 Sec.  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 Sec.  512.426(c)(1)(ii)(A) rather than 120 
percent of the IOTA participants' performance on organ offer acceptance 
rate ratio, as specified under Sec.  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 post-
transplantation. 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 outcome-based 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 Sec.  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 Sec.  512.424(a). Specifically, we 
are removing the cross reference to the proposed quality measure set at 
Sec.  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 Sec.  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

[[Page 96359]]

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 post-transplant 
complications, including infection, cardiovascular disease, and kidney 
failure.\240\
---------------------------------------------------------------------------

    \239\ Stewart, 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., B[uuml]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.
---------------------------------------------------------------------------

    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\
---------------------------------------------------------------------------

    \241\ Medicare 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-and-medicaid-programs-regulatory-provisions-to-promote-program-efficiency-transparency-and.
    \242\ Scientific Registry of Transplant Recipients. Request for 
Information. Requested on 05/02/2023. https://www.srtr.org/.
---------------------------------------------------------------------------

    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 post-transplant outcomes using SRTR's 
methodology at 90 days,\243\ and constructing 5-year and 10-year post-
transplant 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.
---------------------------------------------------------------------------

    \243\ Mpsc-enhance-transplant-program-performance-monitoring-
system_srtr-metrics.pdf. (n.d.). Retrieved December 28, 2022, from 
https://optn.transplant.hrsa.gov/media/qfuj3osi/mpsc-enhance-transplant-program-performance-monitoring-system_srtr-metrics.pdf.
---------------------------------------------------------------------------

    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 post-transplant 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

[[Page 96360]]

clinical care.\244\ Despite the fact that studies indicate eGFR's 
potential as a reliable predictor of long-term post-transplant 
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\
---------------------------------------------------------------------------

    \244\ Mayne, 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.
    \246\ Majerol, 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.
---------------------------------------------------------------------------

    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-to-high 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 post-transplant outcome conditional on 
90-day survival measure and 3-year post-transplant 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 post-transplant 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 post-transplant 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 post-transplant 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 re-
transplant (for example, greater than 20 mL/min) such as 25 or 30 mL/
min. Another commenter suggested that eGFR more accurately conveys 
long-term 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

[[Page 96361]]

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 risk-adjusted measures that could be considered for 
measuring post-transplant 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\
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    \247\ Majerol, 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.
---------------------------------------------------------------------------

    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 post-transplant 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 post-transplant 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 post-transplant 
outcomes using the composite graft survival rate at Sec.  
512.428(b)(1), without modification. We are also finalizing without 
modification the definition of composite graft survival rate at Sec.  
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 
post-transplant 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

[[Page 96362]]

composite graft survival rate of 0.8 (48 divided by 60).
Equation 4: Composite Graft Survival Rate
[GRAPHIC] [TIFF OMITTED] TR04DE24.010

    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 re-
transplant dates are used instead); (2) re-transplant (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 post-transplant care.
---------------------------------------------------------------------------

    \248\ Technical 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-specific-reports/ reports/; OPTN. (2022). OPTN Enhanced Transplant Program 
Performance Metrics. https://optn.transplant.hrsa.gov/media/r5lmmgcl/mpsc_performancemetrics_3242022b.pdf.
    \249\ Technical 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-specific-reports/ reports/.
    \250\ https://unos.org/wp-content/uploads/Adult-TRF-Kidney.pdf.
---------------------------------------------------------------------------

    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 
post-transplant 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 post-transplant 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 risk-adjust 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.
---------------------------------------------------------------------------

    \251\ Zhang, 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.
---------------------------------------------------------------------------

    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.

[[Page 96363]]

    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.
---------------------------------------------------------------------------

    \252\ CDC/ATSDR Social Vulnerability Index (CDC/ATSDR SVI). 
(2024, June 14). cdc.gov. https://www.atsdr.cdc.gov/placeandhealth/svi/index.html.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \253\ Poggio, 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.
---------------------------------------------------------------------------

    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 lower-quality 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 post-transplant 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

[[Page 96364]]

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 Sec.  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.
[GRAPHIC] [TIFF OMITTED] TR04DE24.011

    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 top-level performance on 
this metric.
    We considered a strategy similar to the proposed organ offer 
acceptance methodology which would apply a two-scoring 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 post-transplant 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

[[Page 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 post-transplant 
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.
[GRAPHIC] [TIFF OMITTED] TR04DE24.012

    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 Sec.  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 Sec.  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 post-transplant 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

[[Page 96366]]

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 Sec.  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 Sec.  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.
---------------------------------------------------------------------------

    \254\ collaboRATE. (2019). Glyn Elwyn. http://www.glynelwyn.com/collaborate.html.
    \255\ Colorectal Cancer Screening--NCQA. (2018). NCQA. https://www.ncqa.org/hedis/measures/colorectal-cancer-screening/https://www.ncqa.org/hedis/measures/colorectal-cancer-screening/.
    \256\ THE 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.
    \257\ Supplemental Material to the CMS Measures Management 
System (MMS) Hub CMS Consensus-Based Entity (CBE) Endorsement and 
Maintenance. (2022). https://www.cms.gov/files/document/blueprint-nqf-endorsement-maintenance.pdf.
---------------------------------------------------------------------------

    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\
---------------------------------------------------------------------------

    \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.
---------------------------------------------------------------------------

    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[supreg]) 
(CBE ID: 2483) (89 FR 43518). The PAM[supreg] 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[supreg] 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.
---------------------------------------------------------------------------

    \260\ Pre-Rulemaking [verbar] The Measures Management System. 
(n.d.). Mmshub.cms.gov. Retrieved May 12, 2023, from https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/overview.
---------------------------------------------------------------------------

    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

[[Page 96367]]

focus on depression can improve health-related 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.
---------------------------------------------------------------------------

    \261\ Feroze, 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.
    \262\ 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.
    \263\ Tong, 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.
    \265\ CMS ESRD Measures Manual for the 2023 Performance Period. 
(2022). https://www.cms.gov/files/document/esrd-measures-manual-v81.pdf.
---------------------------------------------------------------------------

    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 pre-waitlist 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.
---------------------------------------------------------------------------

    \266\ 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.
    \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.
    \268\ Szeifert, 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.
---------------------------------------------------------------------------

    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

[[Page 96368]]

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, person-
centered, 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[supreg] 
in the IOTA Model. A couple commenters noted that while the PAM[supreg] 
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[supreg] Measure could encourage IOTA 
participants and IOTA Collaborators, as defined at Sec.  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[supreg] 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[supreg] in the IOTA Model. 
Specifically, they asserted that the PAM[supreg] 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[supreg] 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[supreg], 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'' Sub-
Measure.
    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

[[Page 96369]]

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 post-transplant 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 post-transplant 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, patient-informed 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 patient-
reported 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 Sec.  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

[[Page 96370]]

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 
pre-transplant processes of care. We suggest these measures will 
support the goals of the IOTA Model to improve quality and equity of 
care.
---------------------------------------------------------------------------

    \269\ Schick-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.
---------------------------------------------------------------------------

    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 Sec.  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

[[Page 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 Sec.  
512.428(b)(2)(ii), our proposed process for adding, removing or 
replacing a quality measure at Sec.  512.428(b)(3) or the definition of 
survey and reporting windows at Sec.  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 
pre- and 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 Sec.  512.428(b)(2)(ii), our 
proposed process for adding, removing or replacing a quality measure at 
Sec.  512.428(b)(3) or the definition of survey and reporting windows 
at Sec.  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

[[Page 96372]]

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 Sec.  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 Sec.  
512.428(b)(2)(ii) or the definition of survey and reporting windows at 
Sec.  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 Decision-Making 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 decision-making with the patient could reduce kidney non-
utilization, improve equity, and increase the number of kidney 
transplants.\273\
---------------------------------------------------------------------------

    \271\ Jones, E.L., Shakespeare, K., McLaughlin, L., & 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 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; 
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.
    \272\ Stephenson, 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 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.

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[[Page 96373]]

    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 de-listed.\274\
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    \274\ Massie, 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.
---------------------------------------------------------------------------

    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 patient-centricity 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 non-utilization, 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 Decision-Making 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 Decision-Making 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 non-utilization, 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

[[Page 96374]]

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
---------------------------------------------------------------------------

    \275\ Rama, I., & Griny[oacute], 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.
    \277\ Privitera, 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.
    \278\ Farrugia, 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.
---------------------------------------------------------------------------

    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\
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    \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.
    \280\ Cancer Moonshot. (n.d.). The White House. https://www.whitehouse.gov/cancermoonshot/.
---------------------------------------------------------------------------

    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 transplant-specific 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 self-management; 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

[[Page 96375]]

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 post-transplant outcomes.
---------------------------------------------------------------------------

    \281\ Covert, 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.
    \282\ Covert, 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.
---------------------------------------------------------------------------

    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'' Sub-Measure 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

[[Page 96376]]

receive up to 4 points for performance on the CollaboRATE Shared 
Decision-Making 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 claims-based 
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-for-
performance'' method for PY 3--PY 6. Table 10 illustrates our proposed 
pay-for-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.
[GRAPHIC] [TIFF OMITTED] TR04DE24.013

    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 
Sec.  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.
[GRAPHIC] [TIFF OMITTED] TR04DE24.014

    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

[[Page 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

[[Page 96378]]

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.
---------------------------------------------------------------------------

    \284\ National Committee for Quality Assurance. ``Colorectal 
Cancer Screening--NCQA.'' NCQA, 2024, www.ncqa.org/hedis/measures/colorectal-cancer-screening/.
---------------------------------------------------------------------------

    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 Sec. Sec.  
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
[GRAPHIC] [TIFF OMITTED] TR04DE24.015

    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 Sec.  
512.428(e) of the proposed rule, or our proposed definition of response 
rate threshold, as described at Sec.  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

[[Page 96379]]

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.

0
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\
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    \285\ https://www.cms.gov/priorities/innovation/key-concepts/risk-arrangements-health-care.
---------------------------------------------------------------------------

    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

[[Page 96380]]

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 Sec.  
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)(a-c) 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
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    \286\ https://hcp-lan.org/workproducts/apm-refresh-whitepaper-final.pdf.
    \287\ https://hcp-lan.org/workproducts/apm-refresh-whitepaper-final.pdf.
---------------------------------------------------------------------------

    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.

[[Page 96381]]

[GRAPHIC] [TIFF OMITTED] TR04DE24.016

    We proposed to base performance-based 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-for-reporting 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-for-performance 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

[[Page 96382]]

(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 Sec.  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.
---------------------------------------------------------------------------

    \288\ For instance, Aetna's criteria is here: https://www.aetna.com/content/dam/aetna/pdfs/aetnacom/healthcare-professionals/documents-forms/Aetna-Institutes-of-Excellence.pdf.
---------------------------------------------------------------------------

    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

[[Page 96383]]

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 Sec.  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 
performance-based 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 performance-based 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 value-based 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 Sec.  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 Sec.  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 Sec.  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 phased-in 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.

[[Page 96384]]

[GRAPHIC] [TIFF OMITTED] TR04DE24.017

    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 Sec.  512.430(a). 
Additionally, we are finalizing as proposed the definitions of upside 
risk payment, and neutral zone at Sec.  512.402 without modification. 
Finally, we are finalizing as proposed the definition of downside risk 
payment Sec.  512.402, with a minor technical correction to include the 
complete cross reference to Sec.  512.430.
(2) Apply Payment Calculation Formula to Final Performance Score
    In the proposed rule at Sec.  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 Sec.  
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

[[Page 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 
Sec.  512.430(b)(1), with slight modifications. Specifically, we are 
making a technical correction at Sec.  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 Sec.  512.430(b)(1)(i) that CMS subtracts 
60 from the IOTA participant's final performance score. We are also 
modifying our regulation at Sec.  512.430(b)(1)(iii) to reflect a 
maximum upside risk payment multiplier amount of $15,000 (see Equation 
7).

[[Page 96386]]

    Lastly, we are finalizing our proposed definition of Medicare 
kidney transplants at Sec.  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
[GRAPHIC] [TIFF OMITTED] TR04DE24.018

(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 one-twelfth, 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 downside-risk 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

[[Page 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 Sec.  
512.430(b)(3), without modification.. We also note that we are 
finalizing, as proposed, the definition of Medicare kidney transplants 
at Sec.  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 Sec.  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

[[Page 96388]]

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 Sec.  512.430(d). We are also finalizing the 
definition of preliminary performance assessment and payment 
calculations at Sec.  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 Sec.  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 Sec.  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 Sec. Sec.  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 Sec.  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 Sec.  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 Sec.  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 Sec.  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 Sec.  512.434(c)(2) that a targeted review request that 
includes one or more of the exclusions under Sec.  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 Sec.  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 Sec.  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 Sec.  
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

[[Page 96389]]

modification. We are also finalizing the definition of targeted review 
process at Sec.  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 Sec.  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 Sec.  
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 Sec.  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 beneficiary-identifiable 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 beneficiary-identifiable 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 beneficiary-identifiable 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 (beneficiary-specific) 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,

[[Page 96390]]

eligibility or enrollment transactions. In light of these 
relationships, as discussed in the proposed rule, we believe that the 
proposed disclosure of the beneficiary-identifiable 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 
beneficiary-identifiable 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 
beneficiary-identifiable 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 beneficiary-

[[Page 96391]]

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 
Sec.  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 
Sec.  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 Sec.  512.440(b) and certain aggregate data as described 
in Sec.  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 Sec.  512.440(b)(3) 
to correct a grammatical error.
(2) Quarterly Attribution Lists
    We proposed that this beneficiary-identifiable 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 de-attribution 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 Sec.  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 beneficiary-
identifiable claims data with IOTA participants at Sec.  
512.440(b)(5)(ii).
    The following is a summary of the public comments we received on 
the proposal to share beneficiary-identifiable 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 Sec.  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 beneficiary-
identifiable claims data necessary for IOTA participants to request for 
purposes of conducting permissible health care operations purposes 
under this model.

[[Page 96392]]

    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 Sec.  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 Sec.  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

[[Page 96393]]

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 Sec.  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 Sec.  512.440, without modification. In addition, we 
are finalizing at Sec.  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 
beneficiary-identifiable data from CMS.
    We are also finalizing at Sec.  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 beneficiary-identifiable 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 Sec.  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 beneficiary-identifiable 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 beneficiary-identifiable 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 beneficiary-
identifiable 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 beneficiary-identifiable 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

[[Page 96394]]

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 Sec.  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 Sec.  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\
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    \289\ https://www.ecfr.gov/current/title-42/section-482.90.
    \290\ Ibid.
    \291\ Ibid.
    \292\ Ibid.
    \293\ Ibid.
    \294\ OPTN. (n.d.). OPTN Policies--Living Donation, Chapter 14. 
https://optn.transplant.hrsa.gov/media/eavh5bf3/optn_policies.pdf.
    \295\ AMA 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.
    \296\ https://www.ecfr.gov/current/title-42/section-482.90.
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    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.
---------------------------------------------------------------------------

    \297\ Park, 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.
    \298\ Epstein, 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.
    \299\ Ng, 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.
    \300\ Ahern, 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.
    \301\ Wadhwani, 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.
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    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

[[Page 96395]]

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 patient-centered, 
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.
---------------------------------------------------------------------------

    \302\ https://www.ecfr.gov/current/title-42/section-482.90.
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    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 self-reported kidney transplant 
hospital listing criteria and the actual characteristics of their 
listed patients for transplant. While we acknowledge that

[[Page 96396]]

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.
---------------------------------------------------------------------------

    \303\ https://www.ecfr.gov/current/title-42/section-482.90.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \304\ https://www.ecfr.gov/current/title-42/section-482.90.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \305\ https://www.ecfr.gov/current/title-42/section-482.90.
---------------------------------------------------------------------------

    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 Sec.  512.442(a), without modification. 
We intend to use

[[Page 96397]]

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 decision-making 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.
---------------------------------------------------------------------------

    \306\ Optimizing Usage of Kidney Offer Filters--OPTN. (n.d.). 
Optn.transplant.hrsa.gov. Retrieved March 11, 2023, from https://optn.transplant.hrsa.gov/policies-bylaws/public-comment/optimizing-usage-of-kidney-offer-filters/.
---------------------------------------------------------------------------

    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 Sec.  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.

[[Page 96398]]

    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 Sec.  
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 re-evaluation, 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 
Sec.  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

[[Page 96399]]

criteria provision at Sec.  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 Sec.  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 Sec.  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 Sec.  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 Sec.  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 patient-staff 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 Sec.  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

[[Page 96400]]

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 Sec.  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 Sec.  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 Sec.  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 Sec.  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

[[Page 96401]]

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 Sec.  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

[[Page 96402]]

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 
Sec.  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 patient-
centered 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 Sec.  512.442(b).
    We are, however, finalizing the provisions as proposed at Sec.  
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 Sec.  512.442(c). Additionally, at Sec.  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.

[[Page 96403]]

(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 Sec.  512.150, in 
Sec.  512.140(a) we would use any data obtained in accordance with 
Sec.  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 de-identified 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

[[Page 96404]]

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 well-known and widely used standardized procedures, including but 
not limited to, root cause analysis, plan-do-study-act (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\
---------------------------------------------------------------------------

    \307\ IOM (Institute of Medicine). 2009. Race, Ethnicity, and 
Language Data: Standardization for Health Care Quality Improvement 
(p.287). The National Academies Press https://www.ahrq.gov/sites/default/files/publications/files/iomracereport.pdf.
    \308\ Sivashanker, 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.
    \309\ Weinick, 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.
    \310\ American Society for Quality. (2019). What is root cause 
analysis (RCA)? Asq.org. https://asq.org/quality-resources/root-cause-analysis.
    \311\ Agency 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 [verbar] 
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.
    \314\ Sivashanker, 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.
---------------------------------------------------------------------------

    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, community-wide efforts to ensure the 
availability of and access to community services that are responsive to 
the needs of Medicare beneficiaries.
---------------------------------------------------------------------------

    \315\ Booske, 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/differentPerspectivesForAssigningWeightsToDeterminantsOfHealth.pdf.
    \316\ ROI 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-EVIDENCE-REVIEW-7-1-19.pdf.
    \317\ 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 NPRM (citing A Guide to Using the Accountable Health 
Communities Health-Related Social Needs Screening Tool) 87 FR 38554 
(Jun. 28, 2022).
---------------------------------------------------------------------------

    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

[[Page 96405]]

disparities in the comprehensiveness and quality of care.
---------------------------------------------------------------------------

    \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-of-Science-Report%5B55%5D.pdf.
    \319\ Ibid.
---------------------------------------------------------------------------

    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).

[[Page 96406]]

     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 race-neutral 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.

[[Page 96407]]

    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 IOTA-specific 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 Sec.  512.444(a)(1-7) with slight 
modifications. Specifically, we are redesignating what was proposed at 
Sec.  512.444 to be Sec.  512.446. Additionally, we proposed at Sec.  
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 Sec.  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 Sec.  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 Sec.  
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 Sec.  
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

[[Page 96408]]

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 post-transplant 
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

[[Page 96409]]

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 self-
reported 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.
---------------------------------------------------------------------------

    \320\ Sumit 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.
---------------------------------------------------------------------------

    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 re-approval 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\
---------------------------------------------------------------------------

    \321\ https://www.federalregister.gov/d/2019-20736/p-87.
---------------------------------------------------------------------------

    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.''
---------------------------------------------------------------------------

    \322\ Request 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-for-information-health-and-safety-requirements-for-transplant-programs-organ-procurement.
---------------------------------------------------------------------------

    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 risk-adjusted 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:
---------------------------------------------------------------------------

    \323\ OPTN 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/optn-board-adopts-new-transplant-program-performance-metrics/.
---------------------------------------------------------------------------

    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

[[Page 96410]]

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.
---------------------------------------------------------------------------

    \324\ https://optn.transplant.hrsa.gov/media/5j5dov5s/what_to_expect_performance_reviews.pdf.
---------------------------------------------------------------------------

     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\
---------------------------------------------------------------------------

    \325\ Mohan, 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.
---------------------------------------------------------------------------

     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

[[Page 96411]]

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-of-sequence 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\
---------------------------------------------------------------------------

    \326\ U.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/agency-information-collection-activities-proposed-collection-public-comment-request-information.
---------------------------------------------------------------------------

    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

[[Page 96412]]

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 value-based 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 post-acute 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 Sec.  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, CMS-developed, 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 Sec.  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

[[Page 96413]]

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 
Sec.  512.450, with minor technical corrections to update the spacing 
in the regulation and provide clarification, including the removal of 
duplicative text, at Sec.  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

[[Page 96414]]

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 Sec.  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 Sec.  512.402. We 
are also finalizing as proposed the definitions for the types of IOTA 
collaborator Medicare-enrolled providers or suppliers at Sec.  512.402 
with minor technical corrections to update cross references. 
Specifically, we are finalizing our proposed definition of nonphysician 
practitioner at Sec.  512.402 with a minor technical correction to 
include the full cross reference. Additionally, we are finalizing our 
proposed definition of therapist at Sec.  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 Sec.  512.402 with a technical 
correction to specify that hospital has the meaning set forth in Sec.  
1861(e) of the Act.\327\
---------------------------------------------------------------------------

    \327\ Subsequent 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 Sec.  1861(e) of 
the Act.
---------------------------------------------------------------------------

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 
(Sec.  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 Sec.  
512.452. We are also finalizing without modification the proposed 
definitions of sharing

[[Page 96415]]

arrangements, gainsharing payment, and alignment payment at Sec.  
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 Sec.  
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 Sec. Sec.  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 Sec.  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

[[Page 96416]]

coordinating care; encouraging investment in infrastructure and 
redesigned care processes for high quality and efficient service 
delivery; the provision of items and services pre- or 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 Sec.  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 Sec.  
512.452 with slight modifications. Specifically, we are redesignating 
what was proposed at Sec. Sec.  512.452(b)(5), (6), (7), and (8) to be 
Sec. Sec.  512.452(b)(6), (7), (8), and (9). We are also finalizing 
without modification the proposed definition of IOTA activities at 
Sec.  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

[[Page 96417]]

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

[[Page 96418]]

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 Sec.  
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 Sec.  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 Sec.  
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

[[Page 96419]]

    ++ 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 
Sec.  512.460 and Sec.  1001.952(ii).
    The proposals for the requirements for documentation of sharing 
arrangements under the model are included in Sec.  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 Sec.  
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 (Sec.  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 Sec.  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 Sec.  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 Sec.  
512.454. We are also finalizing without modification the proposed 
definitions of distribution arrangement, collaboration agent, and 
distribution payment at Sec.  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 Sec.  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 Sec.  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 Sec.  411.352 
to its members that comply with Sec.  411.352(g) are appropriate.
    We sought comment on this proposal and specifically on whether 
there are additional safeguards or a different

[[Page 96420]]

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 Sec.  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 Sec.  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 
Sec.  411.352(g).
    Except for a distribution payment from a PGP to a PGP member that 
complies with Sec.  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 Medicare-approved 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 
Sec.  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 Sec.  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 Sec.  512.460.
    The proposals for requirements for distribution arrangements under 
the model are included in Sec.  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.

[[Page 96421]]

    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 Sec.  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 
Sec.  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 Sec.  512.455 with slight modification to remove a stray 
reference to the CJR Model at Sec.  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 Sec.  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\
---------------------------------------------------------------------------

    \328\ James, A., & Mannon, R.B. (2015). The Cost of Transplant 
Immunosuppressant Therapy: Is This Sustainable? Current 
Transplantation Reports, 2(2), 113-121. https://doi.org/10.1007/s40472-015-0052-y.
    \329\ The kidney transplant waitlist. (n.d.). Transplant Living. 
https://transplantliving.org/kidney/the-kidney-transplant-waitlist/.
    \330\ Park, 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.
    \331\ Evans, 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.
    \332\ Assessing the Costs and Benefits of Extending Coverage of 
Immunosuppressive Drugs under Medicare. (n.d.). ASPE. https://aspe.hhs.gov/reports/assessing-costs-benefits-extending-coverage-immunosuppressive-drugs-under-medicare.
---------------------------------------------------------------------------

    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.
---------------------------------------------------------------------------

    \333\ United 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.
---------------------------------------------------------------------------

    At Sec.  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 (Sec.  
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 Sec.  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 Sec.  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

[[Page 96422]]

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-of-Pocket (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 Sec.  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 Sec.  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 Sec.  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 Sec.  
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.

[[Page 96423]]

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-of-Pocket (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 
low-income 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

[[Page 96424]]

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 Sec.  512.456. We are finalizing the 
proposed definition of eligible attributed patient at Sec.  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 Sec.  512.402 with a 
minor technical correction to update the cross reference. Specifically, 
we are removing the cross reference to Sec.  512.458 and replacing it 
to reflect Sec.  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 Sec.  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 Sec.  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 post-
transplant period because it may take up to 3 months for many 
individuals to fully recover from a kidney transplant.\335\ At Sec.  
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.
---------------------------------------------------------------------------

    \335\ Recovery after transplant surgery [verbar] American Kidney 
Fund. (2021, December 14). www.kidneyfund.org. https://www.kidneyfund.org/kidney-donation-and-transplant/life-after-transplant-rejection-prevention-and-healthy-tips/recovery-after-transplant-surgery.
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    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 post-transplant, as well as to and from the 
dialysis center for treatments pre-transplant, 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.
---------------------------------------------------------------------------

    \336\ Browne, 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.
---------------------------------------------------------------------------

    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

[[Page 96425]]

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 post-transplant period to enhance 
recovery.
---------------------------------------------------------------------------

    \339\ Corruble, 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.
    \340\ Szeifert, 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.
---------------------------------------------------------------------------

    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 post-transplant 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 (Sec.  
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 Sec.  512.459 and the conditions of 
the safe harbor for CMS-sponsored model patient incentives.
    At Sec.  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 in-home 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 Sec.  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 Sec.  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 Sec.  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

[[Page 96426]]

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 
(Sec.  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.
---------------------------------------------------------------------------

    \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.
---------------------------------------------------------------------------

    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 Sec.  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

[[Page 96427]]

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 Sec.  512.458.
h. General Payment Waivers \342\
---------------------------------------------------------------------------

    \342\ Section 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 Sec.  512.470 is not 
changed.
---------------------------------------------------------------------------

    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 Sec.  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 Sec.  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 
anti-kickback statute safe harbor for CMS-sponsored model arrangements 
and CMS-sponsored model patient incentives (Sec.  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

[[Page 96428]]

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 
(Sec.  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 Sec.  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 ``model-specific 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 Sec.  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 Sec.  
512.135(a) through (c) to each IOTA participant and its IOTA 
collaborators. In applying Sec.  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 Sec.  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 Sec.  
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

[[Page 96429]]

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 
Sec.  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 Sec.  512.460. We are also finalizing without modification 
the proposed definition of model-specific payment at Sec.  512.402.
13. Compliance and Monitoring
a. General
    We proposed in Sec.  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 Sec.  
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 Sec.  512.456; and
     Monitoring the provision of attributed patient engagement 
incentives provided in accordance with Sec.  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 top-ranked 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 Sec.  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 Sec.  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 Sec.  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 Sec.  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 model-specific payments, 
including discrimination in the provision of services to at-risk 
patients (for example,

[[Page 96430]]

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 Sec.  
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 Sec.  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 Sec.  512.462 with 
minor technical corrections to update cross references. Specifically, 
at Sec.  512.462(d)(1) we are removing the cross reference to Sec.  
512.462 and replacing it to reflect Sec.  405.986 of this chapter. At 
Sec.  512.462(d)(1), we are also removing the cross reference to Sec.  
512.464 and replacing it to reflect Sec.  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

[[Page 96431]]

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 Qnetconfluence.cms.gov. Retrieved May 30, 2023, from https://qnetconfluence.cms.gov/display/ETCLC/End+Stage+Renal+Disease+Treatment+Choices+Learning+Collaborative.
    \344\ Ibid.
---------------------------------------------------------------------------

    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 Sec.  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

[[Page 96432]]

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 non-compliant with the 
provisions of the applicable data sharing agreement.
    At Sec.  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 model-specific 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 Sec.  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 Sec.  
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 Sec.  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
---------------------------------------------------------------------------

    \345\ At Sec.  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. For consistency, in this final rule, 
we have added a corresponding provision at Sec.  512.466(a)(3)(vii).

---------------------------------------------------------------------------

[[Page 96433]]

    ++ 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 
Sec.  512.466(a), with slight modifications. Specifically, we are 
redesignating what was proposed at Sec.  512.466(a)(3)(vii) to be Sec.  
512.466(a)(3)(viii). We are also redesignating what was proposed at 
Sec.  512.466(a)(3)(viii) to be Sec.  512.466(a)(3)(ix). Lastly, at 
Sec.  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 
Sec.  512.466(a)(3)(vii), which allows for termination for a change in 
control consistent with Sec.  512.468(b)(2).
c. Termination of Model Participation by IOTA Participant
    Given the mandatory nature of this model, we proposed at Sec.  
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 Sec.  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 non-compliant 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 
Sec.  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 Sec.  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 Sec.  512.466(d) to clarify

[[Page 96434]]

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 
model-specific 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 Sec.  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 Sec.  512.468(b) as proposed, with a 
slight modification to include a cross-reference to Sec.  512.466 at 
Sec.  512.468(b)(2). We are also finalizing without modification the 
proposed definition of change in control at Sec.  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 Sec.  
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?

[[Page 96435]]

     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 
end-stage 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\
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    \346\ Organ Procurement and Transplantation Network. Kidney 
Donor Profile Index (KDPI) Guide for Clinicians. https://optn.transplant.hrsa.gov/professionals/by-topic/guidance/kidney-donor-profile-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.
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    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

[[Page 96436]]

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 pre-pandemic 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.
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    \348\ Organ 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-data-report/.
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    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 pandemic-related 
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.
---------------------------------------------------------------------------

    \349\ HHS. 2023. ``HRSA Announces Organ Procurement and 
Transplantation Network Modernization Initiative.'' https://www.hhs.gov/about/news/2023/03/22/hrsa-announces-organ-procurement-transplantation-network-modernization-initiative.html.
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    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. Post-
living 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.
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    \350\ CMS. 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.
    \351\ Hariharan 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.
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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

[[Page 96437]]

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.
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    \352\ Cooper, 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.
    \353\ Scientific 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.
    \354\ Scientific 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.
    \355\ Scientific 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-specific-reports/. Accessed May 25, 2023.
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    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:
[GRAPHIC] [TIFF OMITTED] TR04DE24.019

    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 
performance-based 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

[[Page 96438]]

[GRAPHIC] [TIFF OMITTED] TR04DE24.020

Equation 8: IOTA Downside Risk Payment for Scores of 40 and Below
[GRAPHIC] [TIFF OMITTED] TR04DE24.021

    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.
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    \356\ Li 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/.
    \357\ Robinson A, Booker S, Gauntt K, UNOS Research Department. 
2022. ``Eliminate Use of DSA and Region from Kidney Allocation One 
Year Post-Implementation Monitoring Report.'' OPTN Kidney 
Transplantation Descriptive Data Report. https://optn.transplant.hrsa.gov/media/p2oc3ada/data_report_kidney_full_20220624_1.pdf.
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    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 post-transplant 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

[[Page 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.
[GRAPHIC] [TIFF OMITTED] TR04DE24.022

[GRAPHIC] [TIFF OMITTED] TR04DE24.023

[GRAPHIC] [TIFF OMITTED] TR04DE24.024

    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-for-service (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.

[[Page 96440]]

[GRAPHIC] [TIFF OMITTED] TR04DE24.025

    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 high-kidney 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).
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    \358\ Axelrod 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/.
    \359\ Medicare 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).
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    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.

[[Page 96441]]

    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 diagnosis-related 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 non-disabled 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 x 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 Sec.  
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 x 
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 x 0.25 hour per review each year x $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 x 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

[[Page 96442]]

DRGs 653 and 008 when Medicare is the primary payer.
---------------------------------------------------------------------------

    \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/valuing-time-us-department-health-human-services-regulatory-impact-analyses-conceptual-framework.
---------------------------------------------------------------------------

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 x $129.28 per hour = $1,723.30] or a total cost 
of $155,097.00 [$1,723.30 x 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 x 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.
---------------------------------------------------------------------------

    \361\ Bureau of Labor Statistics (BLS). May 2023. ``Occupational 
Employment and Wage Statistics.'' https://www.bls.gov/oes/current/oes_nat.htm.
    \362\ https://optn.transplant.hrsa.gov.
---------------------------------------------------------------------------

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, NLDAC-eligible 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 Decision-Making 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 pre-emptive 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

[[Page 96443]]

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.
---------------------------------------------------------------------------

    \363\ Hariharan 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.
    \364\ Axelrod 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/.
---------------------------------------------------------------------------

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.
[GRAPHIC] [TIFF OMITTED] TR04DE24.026

[GRAPHIC] [TIFF OMITTED] TR04DE24.027

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 one-
time 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.

[[Page 96444]]

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:

0
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

0
2. The authority for part 512 continues to read as follows:

    Authority:  42 U.S.C. 1302, 1315a, and 1395hh.

0
3. The heading of subpart A is revised to read as follows:

Subpart A--Standard Provisions for Mandatory Innovation Center 
Models

0
4. Revise Sec.  512.100 to read as follows.

Sec.  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.

0
5. Section 512.110 is amended by--
0
a. Adding, in alphabetical order, the definition of ``Governing 
documentation'';
0
b. Revising the definitions of ``Innovation Center model,'' 
``Innovation Center model activities,'' ``Model beneficiary,'' and 
``Model participant''; and
0
c. Adding, in alphabetical order, the definitions of ``Performance 
period'' and ``Standard provisions for Innovation Center models''.
    The additions and revisions read as follows:

Sec.  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.
* * * * *

0
6. Section 512.190 is added to read as follows:

Sec.  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.

[[Page 96445]]

    (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 model-specific 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 model-specific 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.

0
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.

[[Page 96446]]

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

Sec.  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.

Sec.  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 Sec.  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 Sec. Sec.  
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 Sec.  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 Sec.  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 Sec.  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 Sec.  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 Sec.  512.430.

[[Page 96447]]

    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 Sec.  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 Sec.  512.452 and in accordance with Sec.  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 Sec.  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 
Sec.  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 
Sec.  512.402, that is required to participate in the IOTA Model under 
Sec.  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 Sec.  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 Sec.  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 Sec.  412.22.
    (2) The criteria to be classified as a rehabilitation hospital or 
rehabilitation unit set forth in Sec. Sec.  412.23(b), 412.25, and 
412.29 for exclusion from the inpatient hospital prospective payment 
systems specified in Sec.  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 Sec.  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 Sec.  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:

[[Page 96448]]

    (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 Sec.  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 Sec.  
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 Sec.  410.74(a)(2)(i) and (ii) of this chapter.
    (2) A nurse practitioner who satisfies the qualifications set forth 
at Sec.  410.75(b) of this chapter.
    (3) A clinical nurse specialist who satisfies the qualifications 
set forth at Sec.  410.76(b) of this chapter.
    (4) A certified registered nurse anesthetist (as defined at Sec.  
410.69(b)).
    (5) A clinical social worker (as defined at Sec.  410.73(a)).
    (6) A registered dietician or nutrition professional (as defined at 
Sec.  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 Sec.  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 
Sec. Sec.  512.424, 512.426, 512.428; and
    (2) Calculates performance-based payments in accordance with Sec.  
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 Sec.  410.60 
of this chapter.
    (2) Outpatient occupational therapy services as defined in Sec.  
410.59 of this chapter.
    (3) Outpatient speech-language pathology services as defined in 
Sec.  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 Sec.  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 Sec.  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 Sec.  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 Sec.  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 
Sec.  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 Sec.  410.60(c) 
of this chapter.
    (2) For occupational therapists in private practice in Sec.  
410.59(c) of this chapter.
    (3) For speech-language pathologists in private practice in Sec.  
410.62(c) of this chapter.
    Taxpayer identification number (TIN) means a Federal taxpayer 
identification

[[Page 96449]]

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 
Sec.  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 Sec.  
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

Sec.  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.

Sec.  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 de-
attribution 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 de-attribution criteria--(1) IOTA 
waitlist patient attribution. (i) At the time CMS conducts attribution, 
as described in

[[Page 96450]]

paragraph (c) of this section, if a kidney transplant waitlist patient 
meets the definition of an IOTA waitlist patient, as defined at Sec.  
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 
Sec.  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 Sec.  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 Sec.  512.402, on a quarterly basis after the model start date, and 
updates the quarterly attribution list, as defined at Sec.  512.402, 
for each IOTA participant, except in the event of termination in 
accordance with Sec.  512.466.
    (ii) Quarterly attribution list. CMS provides the quarterly 
attribution list, as defined at Sec.  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 Sec.  
512.440(b).
    (3)(i) Annual attribution reconciliation. After the fourth quarter 
of each PY, CMS conducts annual attribution reconciliation as defined 
at Sec.  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 
Sec. Sec.  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 Sec.  
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 Sec.  512.414(b)(3).
    (E) The dates on which each attributed patient satisfied a de-
attribution criterion as specified under Sec.  512.414(b)(3).
    (F) A list of the de-attribution criterion each attributed patient 
satisfied under Sec.  512.414(b)(3).

Performance Assessment and Scoring

Sec.  512.422  Overview of performance assessment and scoring.

    (a) General. (1) CMS establishes the performances measures 
described in Sec. Sec.  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 Sec. Sec.  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 Sec. Sec.  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.

Sec.  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 Sec.  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 Sec.  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 Sec.  512.402, using the baseline years for 
the relevant PY as follows:
    (i) Subtracts the total number of kidney transplants furnished to 
patients

[[Page 96451]]

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
[GRAPHIC] [TIFF OMITTED] TR04DE24.028

Sec.  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 organ-offer acceptance rate ratio by dividing the number of kidneys 
the IOTA participant accepted by the risk-adjusted 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
[GRAPHIC] [TIFF OMITTED] TR04DE24.029

    (i) CMS uses both of the following:
    (A) SRTR data to calculate the organ-offer 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.

[[Page 96452]]

    (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
[GRAPHIC] [TIFF OMITTED] TR04DE24.030

    (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 organ-offer 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 organ-offer 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
[GRAPHIC] [TIFF OMITTED] TR04DE24.031

Sec.  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
[GRAPHIC] [TIFF OMITTED] TR04DE24.032

    (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

[[Page 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
[GRAPHIC] [TIFF OMITTED] TR04DE24.033

Payment

Sec.  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 Sec.  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

[[Page 96454]]

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.

Sec.  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 non-responsiveness 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 Sec.  512.190.

Sec.  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

Sec.  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

[[Page 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 Sec.  512.450 that the IOTA participant has requested access to 
beneficiary-identifiable 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 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 paragraph (b)(8) of this section.
    (4) CMS omits from the beneficiary-identifiable 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 Sec.  512.450.
    (B) Such notifications must do both of the following:
    (1) State that the IOTA participant may have requested beneficiary-
identifiable 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 Sec.  512.402 and specified under Sec.  
512.414(c)(1)(ii).
    (C) The quarterly attribution lists that CMS provides to IOTA 
participants as defined at Sec.  512.402 and specified under Sec.  
512.414(c)(2)(ii).
    (D) The annual attribution reconciliation list that CMS provides to 
IOTA participants as defined at Sec.  512.402 and specified under Sec.  
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.

[[Page 96456]]

    (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 
beneficiary-identifiable 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 
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 do all of 
the following:
    (1) Deem the IOTA participant ineligible to retrieve the 
beneficiary-identifiable data under paragraph (b) of this section for 
any amount of time.
    (2) Terminate the IOTA participant's participation in the IOTA 
Model under Sec.  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 de-identified 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.

Sec.  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]

Sec.  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.

Sec.  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 Sec.  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 Sec.  512.110 must meet 
the requirements described in Sec.  512.120(c).

Sec.  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.

[[Page 96457]]

    (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 
Sec.  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 Medicare-approved 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

[[Page 96458]]

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 Sec. Sec.  512.460 and 
1001.952(ii).

Sec.  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 Sec.  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

[[Page 96459]]

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 Sec.  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 Sec.  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 Sec.  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 
Sec.  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 Sec.  512.460.

Sec.  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.

Sec.  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 Sec.  512.402 if 
all of the following conditions are met:
    (1) The attributed patient is an eligible attributed patient as 
defined at Sec.  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 Sec.  512.460.

[[Page 96460]]

Sec.  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 Sec.  512.460.

Sec.  512.459  Application of the CMS-sponsored Model Arrangements and 
Patient Incentives Safe Harbor.

    (a) Application of the CMS-sponsored Model Arrangements Safe 
Harbor. CMS has determined that the Federal anti-kickback statute safe 
harbor for CMS-sponsored 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.

Sec.  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

[[Page 96461]]

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 Sec.  
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.

Sec.  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 Sec.  512.456.
    (ix) Monitoring the provision of attributed patient engagement 
incentives provided in accordance with Sec.  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

[[Page 96462]]

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 Sec.  405.986 of this 
chapter) except if there exists reliable evidence that the 
determination was procured by fraud or similar fault as defined at 
Sec.  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.

Sec.  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 Sec.  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 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 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 Sec.  512.456 or attributed patient engagement 
incentives in accordance with Sec.  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 model-specific payment otherwise owed to 
the IOTA participant.
    (13) Any other action as may be permitted under the terms of this 
part.

Sec.  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.

[[Page 96463]]

    (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 Sec.  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 Sec.  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 Sec.  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 Sec.  
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.

Sec.  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 
Sec.  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

Sec.  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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