42608 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

DEPARTMENT OF HEALTH AND 

HUMAN SERVICES 

Centers for Medicare & Medicaid 

Services 

42 CFR Part 412 

[CMS–1750–F] 

RIN 0938–AU40 

Medicare Program; FY 2022 Inpatient 

Psychiatric Facilities Prospective 

Payment System and Quality 

Reporting Updates for Fiscal Year 

Beginning October 1, 2021 (FY 2022) 

AGENCY: Centers for Medicare & 

Medicaid Services (CMS), HHS. 

ACTION: Final rule. 

SUMMARY: This final rule updates the 

prospective payment rates, the outlier 

threshold, and the wage index for 

Medicare inpatient hospital services 

provided by Inpatient Psychiatric 

Facilities (IPF), which include 

psychiatric hospitals and excluded 

psychiatric units of an acute care 

hospital or critical access hospital. This 

rule also updates and clarifies the IPF 

teaching policy with respect to IPF 

hospital closures and displaced 

residents and finalizes a technical 

change to one of the 2016-based IPF 

market basket price proxies. In addition, 

this final rule finalizes proposals on 

quality measures and reporting 

requirements under the Inpatient 

Psychiatric Facilities Quality Reporting 

(IPFQR) Program. We note that this final 

rule does not finalize two proposals to 

remove quality measures. The changes 

finalized in this rule for the IPFQR 

Program are effective for IPF discharges 

occurring during the Fiscal Year (FY) 

beginning October 1, 2021 through 

September 30, 2022 (FY 2022). 

DATES: These regulations are effective 

on October 1, 2021. 

FOR FURTHER INFORMATION CONTACT:

The IPF Payment Policy mailbox at 

IPFPaymentPolicy@cms.hhs.gov for 

general information. 

Mollie Knight (410) 786–7948 or Eric 

Laib (410) 786–9759, for information 

regarding the market basket update or 

the labor related share. 

Nick Brock (410) 786–5148 or Theresa 

Bean (410) 786–2287, for information 

regarding the regulatory impact 

analysis. 

Lauren Lowenstein, (410) 786–4507, 

for information regarding the inpatient 

psychiatric facilities quality reporting 

program. 

SUPPLEMENTARY INFORMATION: 

Availability of Certain Tables 

Exclusively Through the Internet on the 

CMS Website 

Addendum A to this final rule 

summarizes the FY 2022 IPF PPS 

payment rates, outlier threshold, cost of 

living adjustment factors (COLA) for 

Alaska and Hawaii, national and upper 

limit cost-to-charge ratios, and 

adjustment factors. In addition, the B 

Addenda to this final rule shows the 

complete listing of ICD–10 Clinical 

Modification (CM) and Procedure 

Coding System (PCS) codes, the FY 

2022 IPF PPS comorbidity adjustment, 

and electroconvulsive therapy (ECT) 

procedure codes. The A and B Addenda 

are available online at: https://

www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/ 

InpatientPsychFacilPPS/tools.html. 

Tables setting forth the FY 2022 Wage 

Index for Urban Areas Based on CoreBased Statistical Area (CBSA) Labor 

Market Areas and the FY 2022 Wage 

Index Based on CBSA Labor Market 

Areas for Rural Areas are available 

exclusively through the internet, on the 

CMS website at https://www.cms.gov/ 

Medicare/Medicare-Fee-for-ServicePayment/IPFPPS/WageIndex.html. 

I. Executive Summary 

A. Purpose 

This final rule updates the 

prospective payment rates, the outlier 

threshold, and the wage index for 

Medicare inpatient hospital services 

provided by Inpatient Psychiatric 

Facilities (IPFs) for discharges occurring 

during FY 2022 beginning October 1, 

2021 through September 30, 2022. This 

rule also updates and clarifies the IPF 

teaching policy with respect to IPF 

hospital closures and displaced 

residents and finalizes a technical 

change to one of the 2016-based IPF 

market basket price proxies. In addition, 

the final rule finalizes proposals to 

adopt quality measures and reporting 

requirements under the Inpatient 

Psychiatric Facilities Quality Reporting 

(IPFQR) Program. 

B. Summary of the Major Provisions 

1. Inpatient Psychiatric Facilities 

Prospective Payment System (IPF PPS) 

For the IPF PPS, we are finalizing our 

proposal to— 

• Update IPF PPS teaching policy 

with respect to IPF hospital closures 

and displaced residents. 

• Replace one of the price proxies 

currently used for the For-profit Interest 

cost category in the 2016-based IPF 

market basket with a similar price 

proxy. 

• Adjust the 2016-based IPF market 

basket update (2.7 percent) for 

economy-wide productivity (0.7 

percentage point) as required by section 

1886(s)(2)(A)(i) of the Social Security 

Act (the Act), resulting in a final IPF 

payment rate update of 2.0 percent for 

FY 2022. 

• Make technical rate setting changes: 

The IPF PPS payment rates will be 

adjusted annually for inflation, as well 

as statutory and other policy factors. 

This final rule updates: 

++ The IPF PPS Federal per diem 

base rate from $815.22 to $832.94. 

++ The IPF PPS Federal per diem 

base rate for providers who failed to 

report quality data to $816.61. 

++ The Electroconvulsive therapy 

(ECT) payment per treatment from 

$350.97 to $358.60. 

++ The ECT payment per treatment 

for providers who failed to report 

quality data to $351.57. 

++ The labor-related share from 77.3 

percent to 77.2 percent. 

++ The wage index budget-neutrality 

factor from 0.9989 to 1.0017. 

++ The fixed dollar loss threshold 

amount from $14,630 to $14,470 to 

maintain estimated outlier payments at 

2 percent of total estimated aggregate 

IPF PPS payments. 

2. Inpatient Psychiatric Facilities 

Quality Reporting (IPFQR) Program 

In this final rule, we are: 

• Adopting voluntary patient-level 

data reporting for chart-abstracted 

measures for data submitted for the FY 

2023 payment determination and 

mandatory patient-level data reporting 

for chart-abstracted measures for the FY 

2024 payment determination and 

subsequent years; 

• Revising our regulations at 42 CFR 

412.434(b)(3) by replacing the term 

‘‘QualityNet system administrator’’ with 

‘‘QualityNet security official’’; 

• Adopting the Coronavirus disease 

2019 (COVID–19) Vaccination Coverage 

Among Health Care Personnel (HCP) 

measure for the FY 2023 payment 

determination and subsequent years; 

• Adopting the Follow-up After 

Psychiatric Hospitalization (FAPH) 

measure for the FY 2024 payment 

determination and subsequent years; 

and 

• Removing the following two 

measures for FY 2024 payment 

determination and subsequent years: 

++ Timely Transmission of 

Transition Record (Discharges from an 

Inpatient Facility to Home/Self Care or 

Any Other Site of Care) measure and 

++ Follow-up After Hospitalization 

for Mental Illness (FUH) measure. 

• Not finalizing our proposals to 

remove the following two measures for 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42609 

FY 2024 payment determination and 

subsequent years: 

++ Alcohol Use Brief Intervention 

Provided or Offered and Alcohol Use 

Brief Intervention Provided (SUB–2/2a) 

measure; and 

++ Tobacco Use Treatment Provided 

or Offered and Tobacco Use Treatment 

(TOB–2/2a) measure. 

C. Summary of Impacts 

II. Background 

A. Overview of the Legislative 

Requirements of the IPF PPS 

Section 124 of the Medicare, 

Medicaid, and State Children’s Health 

Insurance Program Balanced Budget 

Refinement Act of 1999 (BBRA) (Pub. L. 

106–113) required the establishment 

and implementation of an IPF PPS. 

Specifically, section 124 of the BBRA 

mandated that the Secretary of the 

Department of Health and Human 

Services (the Secretary) develop a per 

diem Prospective Payment System (PPS) 

for inpatient hospital services furnished 

in psychiatric hospitals and excluded 

psychiatric units including an adequate 

patient classification system that reflects 

the differences in patient resource use 

and costs among psychiatric hospitals 

and excluded psychiatric units. 

‘‘Excluded psychiatric unit’’ means a 

psychiatric unit of an acute care 

hospital or of a Critical Access Hospital 

(CAH), which is excluded from payment 

under the Inpatient Prospective 

Payment System (IPPS) or CAH 

payment system, respectively. These 

excluded psychiatric units will be paid 

under the IPF PPS. 

Section 405(g)(2) of the Medicare 

Prescription Drug, Improvement, and 

Modernization Act of 2003 (MMA) (Pub. 

L. 108–173) extended the IPF PPS to 

psychiatric distinct part units of CAHs. 

Sections 3401(f) and 10322 of the 

Patient Protection and Affordable Care 

Act (Pub. L. 111–148) as amended by 

section 10319(e) of that Act and by 

section 1105(d) of the Health Care and 

Education Reconciliation Act of 2010 

(Pub. L. 111–152) (hereafter referred to 

jointly as ‘‘the Affordable Care Act’’) 

added subsection (s) to section 1886 of 

the Act. 

Section 1886(s)(1) of the Act titled 

‘‘Reference to Establishment and 

Implementation of System,’’ refers to 

section 124 of the BBRA, which relates 

to the establishment of the IPF PPS. 

Section 1886(s)(2)(A)(i) of the Act 

requires the application of the 

productivity adjustment described in 

section 1886(b)(3)(B)(xi)(II) of the Act to 

the IPF PPS for the rate year (RY) 

beginning in 2012 (that is, a RY that 

coincides with a FY) and each 

subsequent RY. 

Section 1886(s)(2)(A)(ii) of the Act 

required the application of an ‘‘other 

adjustment’’ that reduced any update to 

an IPF PPS base rate by a percentage 

point amount specified in section 

1886(s)(3) of the Act for the RY 

beginning in 2010 through the RY 

beginning in 2019. As noted in the FY 

2020 IPF PPS final rule, for the RY 

beginning in 2019, section 1886(s)(3)(E) 

of the Act required that the other 

adjustment reduction be equal to 0.75 

percentage point; this was the final year 

the statute required the application of 

this adjustment. Because FY 2021, was 

a RY beginning in 2020, FY 2021 was 

the first-year section 1886(s)(2)(A)(ii) 

did not apply since its enactment. 

Sections 1886(s)(4)(A) through (D) of 

the Act require that for RY 2014 and 

each subsequent RY, IPFs that fail to 

report required quality data with respect 

to such a RY will have their annual 

update to a standard Federal rate for 

discharges reduced by 2.0 percentage 

points. This may result in an annual 

update being less than 0.0 for a RY, and 

may result in payment rates for the 

upcoming RY being less than such 

payment rates for the preceding RY. 

Any reduction for failure to report 

required quality data will apply only to 

the RY involved, and the Secretary will 

not take into account such reduction in 

computing the payment amount for a 

subsequent RY. More information about 

the specifics of the current Inpatient 

Psychiatric Facilities Quality Reporting 

(IPFQR) Program is available in the FY 

2020 IPF PPS and Quality Reporting 

Updates for Fiscal Year Beginning 

October 1, 2019 final rule (84 FR 38459 

through 38468). 

To implement and periodically 

update these provisions, we have 

published various proposed and final 

rules and notices in the Federal 

Register. For more information 

regarding these documents, see the 

Center for Medicare & Medicaid (CMS) 

website at https://www.cms.gov/ 

Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/ 

index.html?redirect=/ 

InpatientPsychFacilPPS/. 

B. Overview of the IPF PPS 

The November 2004 IPF PPS final 

rule (69 FR 66922) established the IPF 

PPS, as required by section 124 of the 

BBRA and codified at 42 CFR part 412, 

subpart N. The November 2004 IPF PPS 

final rule set forth the Federal per diem 

base rate for the implementation year 

(the 18-month period from January 1, 

2005 through June 30, 2006), and 

provided payment for the inpatient 

operating and capital costs to IPFs for 

covered psychiatric services they 

furnish (that is, routine, ancillary, and 

capital costs, but not costs of approved 

educational activities, bad debts, and 


lotter on DSK11XQN23PROD with RULES5ER04AU21.169</GPH>

Provision Description Total Transfers & Cost 

Reductions 

FY 2022 IPF PPS The overall economic impact of this 

payment update final rule is an estimated $80 

million in increased payments to 

IPFs during FY 2022. 

FY 2023 IPFQR The overall economic impact of the 

Program update. IPFQR Program provisions of this 

final rule is an estimated $512,065 

reduction in information collection 

burden. 
42610 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

other services or items that are outside 

the scope of the IPF PPS). Covered 

psychiatric services include services for 

which benefits are provided under the 

fee-for-service Part A (Hospital 

Insurance Program) of the Medicare 

program. 

The IPF PPS established the Federal 

per diem base rate for each patient day 

in an IPF derived from the national 

average daily routine operating, 

ancillary, and capital costs in IPFs in FY 

2002. The average per diem cost was 

updated to the midpoint of the first year 

under the IPF PPS, standardized to 

account for the overall positive effects of 

the IPF PPS payment adjustments, and 

adjusted for budget-neutrality. 

The Federal per diem payment under 

the IPF PPS is comprised of the Federal 

per diem base rate described previously 

and certain patient- and facility-level 

payment adjustments for characteristics 

that were found in the regression 

analysis to be associated with 

statistically significant per diem cost 

differences with statistical significance 

defined as p less than 0.05. A complete 

discussion of the regression analysis 

that established the IPF PPS adjustment 

factors can be found in the November 

2004 IPF PPS final rule (69 FR 66933 

through 66936). 

The patient-level adjustments include 

age, Diagnosis-Related Group (DRG) 

assignment, and comorbidities; 

additionally, there are adjustments to 

reflect higher per diem costs at the 

beginning of a patient’s IPF stay and 

lower costs for later days of the stay. 

Facility-level adjustments include 

adjustments for the IPF’s wage index, 

rural location, teaching status, a cost-ofliving adjustment for IPFs located in 

Alaska and Hawaii, and an adjustment 

for the presence of a qualifying 

emergency department (ED). 

The IPF PPS provides additional 

payment policies for outlier cases, 

interrupted stays, and a per treatment 

payment for patients who undergo 

electroconvulsive therapy (ECT). During 

the IPF PPS mandatory 3-year transition 

period, stop-loss payments were also 

provided; however, since the transition 

ended as of January 1, 2008, these 

payments are no longer available. 

C. Annual Requirements for Updating 

the IPF PPS 

Section 124 of the BBRA did not 

specify an annual rate update strategy 

for the IPF PPS and was broadly written 

to give the Secretary discretion in 

establishing an update methodology. 

Therefore, in the November 2004 IPF 

PPS final rule, we implemented the IPF 

PPS using the following update strategy: 

• Calculate the final Federal per diem 

base rate to be budget-neutral for the 18- 

month period of January 1, 2005 

through June 30, 2006. 

• Use a July 1 through June 30 annual 

update cycle. 

• Allow the IPF PPS first update to be 

effective for discharges on or after July 

1, 2006 through June 30, 2007. 

In November 2004, we implemented 

the IPF PPS in a final rule that 

published on November 15, 2004 in the 

Federal Register (69 FR 66922). In 

developing the IPF PPS, and to ensure 

that the IPF PPS can account adequately 

for each IPF’s case-mix, we performed 

an extensive regression analysis of the 

relationship between the per diem costs 

and certain patient and facility 

characteristics to determine those 

characteristics associated with 

statistically significant cost differences 

on a per diem basis. That regression 

analysis is described in detail in our 

November 28, 2003 IPF proposed rule 

(68 FR 66923; 66928 through 66933) and 

our November 15, 2004 IPF final rule 

(69 FR 66933 through 66960). For 

characteristics with statistically 

significant cost differences, we used the 

regression coefficients of those variables 

to determine the size of the 

corresponding payment adjustments. 

In the November 15, 2004 final rule, 

we explained the reasons for delaying 

an update to the adjustment factors, 

derived from the regression analysis, 

including waiting until we have IPF PPS 

data that yields as much information as 

possible regarding the patient-level 

characteristics of the population that 

each IPF serves. We indicated that we 

did not intend to update the regression 

analysis and the patient-level and 

facility-level adjustments until we 

complete that analysis. Until that 

analysis is complete, we stated our 

intention to publish a notice in the 

Federal Register each spring to update 

the IPF PPS (69 FR 66966). 

On May 6, 2011, we published a final 

rule in the Federal Register titled, 

‘‘Inpatient Psychiatric Facilities 

Prospective Payment System—Update 

for Rate Year Beginning July 1, 2011 (RY 

2012)’’ (76 FR 26432), which changed 

the payment rate update period to a RY 

that coincides with a FY update. 

Therefore, final rules are now published 

in the Federal Register in the summer 

to be effective on October 1. When 

proposing changes in IPF payment 

policy, a proposed rule would be issued 

in the spring, and the final rule in the 

summer to be effective on October 1. For 

a detailed list of updates to the IPF PPS, 

we refer readers to our regulations at 42 

CFR 412.428. 

The most recent IPF PPS annual 

update was published in a final rule on 

August 4, 2020 in the Federal Register 

titled, ‘‘Medicare Program; FY 2021 

Inpatient Psychiatric Facilities 

Prospective Payment System and 

Special Requirements for Psychiatric 

Hospitals for Fiscal Year Beginning 

October 1, 2020 (FY 2021)’’ (85 FR 

47042), which updated the IPF PPS 

payment rates for FY 2021. That final 

rule updated the IPF PPS Federal per 

diem base rates that were published in 

the FY 2020 IPF PPS Rate Update final 

rule (84 FR 38424) in accordance with 

our established policies. 

III. Provisions of the FY 2022 IPF PPS 

Final Rule and Responses to Comments 

A. Final Update to the FY 2021 Market 

Basket for the IPF PPS 

1. Background 

Originally, the input price index that 

was used to develop the IPF PPS was 

the ‘‘Excluded Hospital with Capital’’ 

market basket. This market basket was 

based on 1997 Medicare cost reports for 

Medicare participating inpatient 

rehabilitation facilities (IRFs), IPFs, 

long-term care hospitals (LTCHs), 

cancer hospitals, and children’s 

hospitals. Although ‘‘market basket’’ 

technically describes the mix of goods 

and services used in providing health 

care at a given point in time, this term 

is also commonly used to denote the 

input price index (that is, cost category 

weights and price proxies) derived from 

that market basket. Accordingly, the 

term market basket as used in this 

document, refers to an input price 

index. 

Since the IPF PPS inception, the 

market basket used to update IPF PPS 

payments has been rebased and revised 

to reflect more recent data on IPF cost 

structures. We last rebased and revised 

the IPF market basket in the FY 2020 

IPF PPS rule, where we adopted a 2016- 

based IPF market basket, using Medicare 

cost report data for both Medicare 

participating freestanding psychiatric 

hospitals and psychiatric units. We refer 

readers to the FY 2020 IPF PPS final 

rule for a detailed discussion of the 

2016-based IPF PPS market basket and 

its development (84 FR 38426 through 

38447). References to the historical 

market baskets used to update IPF PPS 

payments are listed in the FY 2016 IPF 

PPS final rule (80 FR 46656). 

2. Final FY 2022 IPF Market Basket 

Update 

For FY 2022 (that is, beginning 

October 1, 2021 and ending September 

30, 2022), we proposed to update the 

IPF PPS payments by a market basket 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42611 

increase factor with a productivity 

adjustment as required by section 

1886(s)(2)(A)(i) of the Act. In the FY 

2022 IPF proposed rule (86 FR 19483), 

we proposed to use the same 

methodology described in the FY 2021 

IPF PPS final rule (85 FR 47045 through 

47046), with one proposed modification 

to the 2016-based IPF market basket. 

For the price proxy for the For-profit 

Interest cost category of the 2016-based 

IPF market basket, we proposed to use 

the iBoxx AAA Corporate Bond Yield 

index instead of the Moody’s AAA 

Corporate Bond Yield index. Effective 

for December 2020, the Moody’s AAA 

Corporate Bond series is no longer 

available for use under license to IHS 

Global Inc. (IGI), the nationally 

recognized economic and financial 

forecasting firm with which we contract 

to forecast the components of the market 

baskets and multi-factor productivity 

(MFP). Since IGI is no longer licensed 

to use and publish the Moody’s series, 

IGI was required to discontinue the 

publication of the associated historical 

data and forecasts of this series. 

Therefore, IGI constructed a bond yield 

index (iBoxx) that closely replicates the 

Moody’s corporate bond yield indices 

currently used in the market baskets. 

In the FY 2022 IPF PPS proposed rule, 

we stated that because the iBoxx AAA 

Corporate Bond Yield index captures 

the same technical concept as the 

current corporate bond proxy and tracks 

similarly to the current measure that is 

no longer available, we believed that the 

iBoxx AAA Corporate Bond Yield index 

is technically appropriate to use in the 

2016-based IPF market basket. 

Based on IGI’s fourth quarter 2020 

forecast with historical data through the 

third quarter of 2020, the proposed 

2016-based IPF market basket increase 

factor for FY 2022 was projected to be 

2.3 percent. We also proposed that if 

more recent data became available after 

the publication of the proposed rule and 

before the publication of this final rule 

(for example, a more recent estimate of 

the market basket update or MFP), we 

would use such data, if appropriate, to 

determine the FY 2022 market basket 

update in this final rule. 

Section 1886(s)(2)(A)(i) of the Act 

requires that, after establishing the 

increase factor for a FY, the Secretary 

shall reduce such increase factor for FY 

2012 and each subsequent FY, by the 

productivity adjustment described in 

section 1886(b)(3)(B)(xi)(II) of the Act. 

Section 1886(b)(3)(B)(xi)(II) of the Act 

sets forth the definition of this 

productivity adjustment. The statute 

defines the productivity adjustment to 

be equal to the 10-year moving average 

of changes in annual economy-wide, 

private nonfarm business MFP (as 

projected by the Secretary for the 10- 

year period ending with the applicable 

FY, year, cost reporting period, or other 

annual period) (the ‘‘productivity 

adjustment’’). The U.S. Department of 

Labor’s Bureau of Labor Statistics (BLS) 

publishes the official measure of private 

nonfarm business MFP. Please see 

http://www.bls.gov/mfp for the BLS 

historical published MFP data. A 

complete description of the MFP 

projection methodology is available on 

the CMS website at https://

www.cms.gov/Research-StatisticsDataand-Systems/Statistics-TrendsandReports/ 

MedicareProgramRatesStats/ 

MarketBasketResearch.html. We note 

that effective with FY 2022 and forward, 

CMS is changing the name of this 

adjustment to refer to it as the 

productivity adjustment rather than the 

MFP adjustment. We note that the 

adjustment relies on the same 

underlying data and methodology. This 

new terminology is more consistent 

with the statutory language described in 

section 1886(s)(2)(A)(i) of the Act. 

Using IGI’s fourth quarter 2020 

forecast, the productivity adjustment for 

FY 2022 was projected to be 0.2 percent. 

We proposed to then reduce the 

proposed 2.3 percent IPF market basket 

update by the estimated productivity 

adjustment for FY 2022 of 0.2 

percentage point. Therefore, the 

proposed FY 2022 IPF update was equal 

to 2.1 percent (2.3 percent market basket 

update reduced by the 0.2 percentage 

point productivity adjustment). 

Furthermore, we proposed that if more 

recent data became available after the 

publication of the proposed rule and 

before the publication of this final rule 

(for example, a more recent estimate of 

the market basket or MFP), we would 

use such data, if appropriate, to 

determine the FY 2022 market basket 

update and productivity adjustment in 

this final rule. 

Based on the more recent data 

available for this FY 2022 IPF final rule 

(that is, IGI’s second quarter 2021 

forecast of the 2016-based IPF market 

basket with historical data through the 

first quarter of 2021), we estimate that 

the IPF FY 2022 market basket update 

is 2.7 percent. The current estimate of 

the productivity adjustment for FY 2022 

is 0.7 percentage point. Therefore, the 

current estimate of the FY 2022 IPF 

increase factor is equal to 2.0 percent 

(2.7 percent market basket update 

reduced by 0.7 percentage point 

productivity adjustment). 

We invited public comment on our 

proposals for the FY 2022 market basket 

update and productivity adjustment. 

The following is a summary of the 

public comments received on the 

proposed FY 2022 market basket update 

and productivity adjustment and our 

responses: 

Comment: One commenter supported 

the update to the IPF payment rates of 

2.1 percent. 

Response: We thank the commenter 

for their support. 

Comment: One commenter stated that 

given the growing behavioral health and 

substance abuse crisis made worse by 

the COVID–19 Public Health Emergency 

(PHE), that CMS should provide 

additional payment for IPFs in the 

future. 

Response: We understand the 

commenter’s concern. We acknowledge 

that the COVID–19 PHE has amplified 

the growing need for behavioral health 

services in this country and remain 

committed to trying to find ways to 

mitigate its impact on IPFs. Our goal is 

to ensure that the IPF payment rates 

accurately reflect the best available data. 

For example, as discussed in section 

VI.C.3 of this final rule, in comparing 

and analyzing FY 2019 and FY 2020 

claims, we determined that the COVID– 

19 PHE appears to have significantly 

impacted the FY 2020 IPF claims such 

that the FY 2019 claims are the best 

available data to set the outlier fixed 

dollar loss threshold for FY 2022. 

Therefore, we deviated from our 

longstanding practice of using the most 

recent available year of claims, that is, 

FY 2020 claims, for estimating IPF PPS 

payments in FY 2022. We will continue 

to analyze more recent available IPF 

claims data to better understand both 

the short- and long-term effects of the 

COVID–19 PHE on the IPF PPS. 

Final Decision: After consideration of 

the comments we received, we are 

finalizing a FY 2022 IPF update equal to 

2.0 percent based on the more recent 

data available. 

3. Final FY 2022 IPF Labor-Related 

Share 

Due to variations in geographic wage 

levels and other labor-related costs, we 

believe that payment rates under the IPF 

PPS should continue to be adjusted by 

a geographic wage index, which would 

apply to the labor-related portion of the 

Federal per diem base rate (hereafter 

referred to as the labor-related share). 

The labor-related share is determined by 

identifying the national average 

proportion of total costs that are related 

to, influenced by, or vary with the local 

labor market. We proposed to continue 

to classify a cost category as laborrelated if the costs are labor-intensive 

and vary with the local labor market. 


lotter on DSK11XQN23PROD with RULES5
42612 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

Based on our definition of the laborrelated share and the cost categories in 

the 2016-based IPF market basket, we 

proposed to calculate the labor-related 

share for FY 2022 as the sum of the FY 

2022 relative importance of Wages and 

Salaries; Employee Benefits; 

Professional Fees: Labor-related; 

Administrative and Facilities Support 

Services; Installation, Maintenance, and 

Repair Services; All Other: Labor-related 

Services; and a portion of the CapitalRelated relative importance from the 

2016-based IPF market basket. For more 

details regarding the methodology for 

determining specific cost categories for 

inclusion in the 2016-based IPF laborrelated share, see the FY 2020 IPF PPS 

final rule (84 FR 38445 through 38447). 

The relative importance reflects the 

different rates of price change for these 

cost categories between the base year 

(FY 2016) and FY 2022. Based on IGI’s 

fourth quarter 2020 forecast of the 2016- 

based IPF market basket, the sum of the 

FY 2022 relative importance for Wages 

and Salaries; Employee Benefits; 

Professional Fees: Labor-related; 

Administrative and Facilities Support 

Services; Installation Maintenance & 

Repair Services; and All Other: Labor 

related Services was 74.0 percent. We 

proposed that the portion of CapitalRelated costs that are influenced by the 

local labor market is 46 percent. Since 

the relative importance for CapitalRelated costs was 6.7 percent of the 

2016-based IPF market basket for FY 

2022, we proposed to take 46 percent of 

6.7 percent to determine the laborrelated share of Capital-Related costs for 

FY 2022 of 3.1 percent. Therefore, we 

proposed a total labor-related share for 

FY 2022 of 77.1 percent (the sum of 74.0 

percent for the labor-related share of 

operating costs and 3.1 percent for the 

labor-related share of Capital-Related 

costs). We also proposed that if more 

recent data became available after 

publication of the proposed rule and 

before the publication of this final rule 

(for example, a more recent estimate of 

the labor-related share), we would use 

such data, if appropriate, to determine 

the FY 2022 IPF labor-related share in 

the final rule. 

Based on IGI’s second quarter 2021 

forecast of the 2016-based IPF market 

basket, the sum of the FY 2022 relative 

importance for Wages and Salaries; 

Employee Benefits; Professional Fees: 

Labor-related; Administrative and 

Facilities Support Services; Installation 

Maintenance & Repair Services; and All 

Other: Labor-related Services is 74.1 

percent. Since the relative importance 

for Capital-Related costs is 6.7 percent 

of the 2016-based IPF market basket for 

FY 2022, we take 46 percent of 6.7 

percent to determine the labor-related 

share of Capital-Related costs for FY 

2022 of 3.1 percent. Therefore, the 

current estimate of the total laborrelated share for FY 2022 is equal to 

77.2 percent (the sum of 74.1 percent for 

the labor-related share of operating costs 

and 3.1 percent for the labor-related 

share of Capital-Related costs). Table 1 

shows the final FY 2022 labor-related 

share and the final FY 2021 laborrelated share using the 2016-based IPF 

market basket relative importance. 

We invited public comments on the 

proposed labor-related share for FY 

2022. 

Comment: Several commenters 

supported the decrease in the laborrelated share from 77.3 percent in FY 

2021 to 77.1 percent in FY 2022 noting 

that it will help any facility that has a 

wage index less than 1.0. The 

commenters stated that, across this 

country there is a growing disparity 

between high-wage and low-wage states. 

Recognizing this disparity and slightly 

lowering the labor-related share 

provides some aid to hospitals in many 

rural and underserved communities. 

Response: We thank the commenter 

for their support. We agree with the 

commenters that the labor-related share 

should reflect the proportion of costs 

that are attributable to labor and vary 

geographically to account for differences 

in labor-related costs across geographic 

areas. More recent data became 

available; therefore, based on IGI’s 

second quarter 2021 forecast with 

historical data through the first quarter 

2021 the FY 2022 labor-related share for 

the final rule is 77.2 percent as shown 

in Table 1. 

After consideration of comments 

received, we are finalizing the use of the 

sum of the FY 2022 relative importance 


lotter on DSK11XQN23PROD with RULES5ER04AU21.170</GPH>

TABLE 1: FY 2022 IPF Labor-Related Share and FY 2021 IPF Labor-Related Share 

Relative importance, Relative importance, 

labor-related share, labor-related share, 

FY 2021 1 FY20222 

Wa~es and Salaries 52.9 52.8 

Employee Benefits 13.6 13.6 

Professional Fees: Labor- 4.3 4.3 

related 

Administrative and Facilities 0.6 0.6 

Support Services 

Installation, Maintenance and 1.3 1.3 

Repair 

All Other Labor-related 1.5 1.5 

Services 

Capital-related (.46) 3.1 3.1 

Total 77.3 77.2 

l. Bued on the~ q~lOlOfflS Global Im:. ~of the 2016-1-ed lPFmnbt batbt.. 

l. Bued on the~ ~2021 ms Global Im:,~ of the 2016-1-edlPF mm:ct basbt. 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42613 

for the labor-related cost categories 

based on the most recent forecast (IGI’s 

second quarter 2021 forecast) of the 

2016-based IPF market basket laborrelated share cost weights, as proposed. 

B. Final Updates to the IPF PPS Rates 

for FY Beginning October 1, 2021 

The IPF PPS is based on a 

standardized Federal per diem base rate 

calculated from the IPF average per 

diem costs and adjusted for budgetneutrality in the implementation year. 

The Federal per diem base rate is used 

as the standard payment per day under 

the IPF PPS and is adjusted by the 

patient-level and facility-level 

adjustments that are applicable to the 

IPF stay. A detailed explanation of how 

we calculated the average per diem cost 

appears in the November 2004 IPF PPS 

final rule (69 FR 66926). 

1. Determining the Standardized 

Budget-Neutral Federal per Diem Base 

Rate 

Section 124(a)(1) of the BBRA 

required that we implement the IPF PPS 

in a budget-neutral manner. In other 

words, the amount of total payments 

under the IPF PPS, including any 

payment adjustments, must be projected 

to be equal to the amount of total 

payments that would have been made if 

the IPF PPS were not implemented. 

Therefore, we calculated the budgetneutrality factor by setting the total 

estimated IPF PPS payments to be equal 

to the total estimated payments that 

would have been made under the Tax 

Equity and Fiscal Responsibility Act of 

1982 (TEFRA) (Pub. L. 97–248) 

methodology had the IPF PPS not been 

implemented. A step-by-step 

description of the methodology used to 

estimate payments under the TEFRA 

payment system appears in the 

November 2004 IPF PPS final rule (69 

FR 66926). 

Under the IPF PPS methodology, we 

calculated the final Federal per diem 

base rate to be budget-neutral during the 

IPF PPS implementation period (that is, 

the 18-month period from January 1, 

2005 through June 30, 2006) using a July 

1 update cycle. We updated the average 

cost per day to the midpoint of the IPF 

PPS implementation period (October 1, 

2005), and this amount was used in the 

payment model to establish the budgetneutrality adjustment. 

Next, we standardized the IPF PPS 

Federal per diem base rate to account 

for the overall positive effects of the IPF 

PPS payment adjustment factors by 

dividing total estimated payments under 

the TEFRA payment system by 

estimated payments under the IPF PPS. 

In addition, information concerning this 

standardization can be found in the 

November 2004 IPF PPS final rule (69 

FR 66932) and the RY 2006 IPF PPS 

final rule (71 FR 27045). We then 

reduced the standardized Federal per 

diem base rate to account for the outlier 

policy, the stop loss provision, and 

anticipated behavioral changes. A 

complete discussion of how we 

calculated each component of the 

budget-neutrality adjustment appears in 

the November 2004 IPF PPS final rule 

(69 FR 66932 through 66933) and in the 

RY 2007 IPF PPS final rule (71 FR 27044 

through 27046). The final standardized 

budget-neutral Federal per diem base 

rate established for cost reporting 

periods beginning on or after January 1, 

2005 was calculated to be $575.95. 

The Federal per diem base rate has 

been updated in accordance with 

applicable statutory requirements and 

§ 412.428 through publication of annual 

notices or proposed and final rules. A 

detailed discussion on the standardized 

budget-neutral Federal per diem base 

rate and the electroconvulsive therapy 

(ECT) payment per treatment appears in 

the FY 2014 IPF PPS update notice (78 

FR 46738 through 46740). These 

documents are available on the CMS 

website at https://www.cms.gov/ 

Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/ 

index.html. 

IPFs must include a valid procedure 

code for ECT services provided to IPF 

beneficiaries in order to bill for ECT 

services, as described in our Medicare 

Claims Processing Manual, Chapter 3, 

Section 190.7.3 (available at https://

www.cms.gov/Regulations-andGuidance/Guidance/Manuals/ 

Downloads/clm104c03.pdf.) There were 

no changes to the ECT procedure codes 

used on IPF claims as a result of the 

final update to the ICD–10–PCS code set 

for FY 2022. Addendum B to this final 

rule shows the ECT procedure codes for 

FY 2022 and is available on our website 

at https://www.cms.gov/Medicare/ 

Medicare-Fee-for-Service-Payment/ 

InpatientPsychFacilPPS/tools.html. 

2. Final Update of the Federal Per Diem 

Base Rate and Electroconvulsive 

Therapy Payment per Treatment 

The current (FY 2021) Federal per 

diem base rate is $815.22 and the ECT 

payment per treatment is $350.97. For 

the final FY 2022 Federal per diem base 

rate, we applied the payment rate 

update of 2.0 percent—that is, the 2016- 

based IPF market basket increase for FY 

2022 of 2.7 percent less the productivity 

adjustment of 0.7 percentage point—and 

the wage index budget-neutrality factor 

of 1.0017 (as discussed in section III.D.1 

of this final rule) to the FY 2021 Federal 

per diem base rate of $815.22, yielding 

a final Federal per diem base rate of 

$832.94 for FY 2022. Similarly, we 

applied the 2.0 percent payment rate 

update and the 1.0017 wage index 

budget-neutrality factor to the FY 2021 

ECT payment per treatment of $350.97, 

yielding a final ECT payment per 

treatment of $358.60 for FY 2022. 

Section 1886(s)(4)(A)(i) of the Act 

requires that for RY 2014 and each 

subsequent RY, in the case of an IPF 

that fails to report required quality data 

with respect to such RY, the Secretary 

will reduce any annual update to a 

standard Federal rate for discharges 

during the RY by 2.0 percentage points. 

Therefore, we are applying a 2.0 

percentage point reduction to the 

Federal per diem base rate and the ECT 

payment per treatment as follows: 

• For IPFs that fail requirements 

under the IPFQR Program, we applied a 

0.0 percent payment rate update—that 

is, the IPF market basket increase for FY 

2022 of 2.7 percent less the productivity 

adjustment of 0.7 percentage point for 

an update of 2.0 percent, and further 

reduced by 2 percentage points in 

accordance with section 1886(s)(4)(A)(i) 

of the Act—and the wage index budgetneutrality factor of 1.0017 to the FY 

2021 Federal per diem base rate of 

$815.22, yielding a Federal per diem 

base rate of $816.61 for FY 2022. 

• For IPFs that fail to meet 

requirements under the IPFQR Program, 

we applied the 0.0 percent annual 

payment rate update and the 1.0017 

wage index budget-neutrality factor to 

the FY 2021 ECT payment per treatment 

of $350.97, yielding an ECT payment 

per treatment of $351.57 for FY 2022. 

C. Final Updates to the IPF PPS PatientLevel Adjustment Factors 

1. Overview of the IPF PPS Adjustment 

Factors 

The IPF PPS payment adjustments 

were derived from a regression analysis 

of 100 percent of the FY 2002 Medicare 

Provider and Analysis Review 

(MedPAR) data file, which contained 

483,038 cases. For a more detailed 

description of the data file used for the 

regression analysis, see the November 

2004 IPF PPS final rule (69 FR 66935 

through 66936). We are finalizing our 

proposal to continue to use the existing 

regression-derived adjustment factors 

established in 2005 for FY 2022. 

However, we have used more recent 

claims data to simulate payments to 

finalize the outlier fixed dollar loss 

threshold amount and to assess the 

impact of the IPF PPS updates. 


lotter on DSK11XQN23PROD with RULES5
42614 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

2. IPF PPS Patient-Level Adjustments 

The IPF PPS includes payment 

adjustments for the following patientlevel characteristics: Medicare Severity 

Diagnosis Related Groups (MS–DRGs) 

assignment of the patient’s principal 

diagnosis, selected comorbidities, 

patient age, and the variable per diem 

adjustments. 

a. Final Update to MS–DRG Assignment 

We believe it is important to maintain 

for IPFs the same diagnostic coding and 

Diagnosis Related Group (DRG) 

classification used under the IPPS for 

providing psychiatric care. For this 

reason, when the IPF PPS was 

implemented for cost reporting periods 

beginning on or after January 1, 2005, 

we adopted the same diagnostic code set 

(ICD–9–CM) and DRG patient 

classification system (MS–DRGs) that 

were utilized at the time under the IPPS. 

In the RY 2009 IPF PPS notice (73 FR 

25709), we discussed CMS’ effort to 

better recognize resource use and the 

severity of illness among patients. CMS 

adopted the new MS–DRGs for the IPPS 

in the FY 2008 IPPS final rule with 

comment period (72 FR 47130). In the 

RY 2009 IPF PPS notice (73 FR 25716), 

we provided a crosswalk to reflect 

changes that were made under the IPF 

PPS to adopt the new MS–DRGs. For a 

detailed description of the mapping 

changes from the original DRG 

adjustment categories to the current 

MS–DRG adjustment categories, we 

refer readers to the RY 2009 IPF PPS 

notice (73 FR 25714). 

The IPF PPS includes payment 

adjustments for designated psychiatric 

DRGs assigned to the claim based on the 

patient’s principal diagnosis. The DRG 

adjustment factors were expressed 

relative to the most frequently reported 

psychiatric DRG in FY 2002, that is, 

DRG 430 (psychoses). The coefficient 

values and adjustment factors were 

derived from the regression analysis 

discussed in detail in the November 28, 

2003 IPF proposed rule (68 FR 66923; 

66928 through 66933) and the 

November 15, 2004 IPF final rule (69 FR 

66933 through 66960). Mapping the 

DRGs to the MS–DRGs resulted in the 

current 17 IPF MS–DRGs, instead of the 

original 15 DRGs, for which the IPF PPS 

provides an adjustment. For FY 2022, 

we did not propose any changes to the 

IPF MSDRG adjustment factors. 

Therefore, we are finalizing our 

proposal to maintain the existing IPF 

MS–DRG adjustment factors. 

In the FY 2015 IPF PPS final rule 

published August 6, 2014 in the Federal 

Register titled, ‘‘Inpatient Psychiatric 

Facilities Prospective Payment 

System—Update for FY Beginning 

October 1, 2014 (FY 2015)’’ (79 FR 

45945 through 45947), we finalized 

conversions of the ICD–9–CM-based 

MS–DRGs to ICD–10–CM/PCS-based 

MS–DRGs, which were implemented on 

October 1, 2015. Further information on 

the ICD–10–CM/PCS MS–DRG 

conversion project can be found on the 

CMS ICD–10–CM website at https://

www.cms.gov/Medicare/Coding/ICD10/ 

ICD-10-MS-DRG-ConversionProject.html. 

For FY 2022, we are finalizing our 

proposal to continue to make the 

existing payment adjustment for 

psychiatric diagnoses that group to one 

of the existing 17 IPF MS–DRGs listed 

in Addendum A. Addendum A is 

available on our website at https://

www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/ 

InpatientPsychFacilPPS/tools.html. 

Psychiatric principal diagnoses that do 

not group to one of the 17 designated 

MS–DRGs will still receive the Federal 

per diem base rate and all other 

applicable adjustments, but the payment 

will not include an MS–DRG 

adjustment. 

The diagnoses for each IPF MS–DRG 

will be updated as of October 1, 2021, 

using the final IPPS FY 2022 ICD–10– 

CM/PCS code sets. The FY 2022 IPPS/ 

LTCH PPS final rule includes tables of 

the changes to the ICD–10–CM/PCS 

code sets, which underlie the FY 2022 

IPF MS–DRGs. Both the FY 2022 IPPS 

final rule and the tables of final changes 

to the ICD–10–CM/PCS code sets, which 

underlie the FY 2022 MS–DRGs, are 

available on the CMS IPPS website at 

https://www.cms.gov/Medicare/ 

Medicare-Fee-for-Service-Payment/ 

AcuteInpatientPPS/index.html. 

Code First 

As discussed in the ICD–10–CM 

Official Guidelines for Coding and 

Reporting, certain conditions have both 

an underlying etiology and multiple 

body system manifestations due to the 

underlying etiology. For such 

conditions, the ICD–10–CM has a 

coding convention that requires the 

underlying condition be sequenced first 

followed by the manifestation. 

Wherever such a combination exists, 

there is a ‘‘use additional code’’ note at 

the etiology code, and a ‘‘code first’’ 

note at the manifestation code. These 

instructional notes indicate the proper 

sequencing order of the codes (etiology 

followed by manifestation). In 

accordance with the ICD–10–CM 

Official Guidelines for Coding and 

Reporting, when a primary (psychiatric) 

diagnosis code has a ‘‘code first’’ note, 

the provider will follow the instructions 

in the ICD–10–CM Tabular List. The 

submitted claim goes through the CMS 

processing system, which will identify 

the principal diagnosis code as nonpsychiatric and search the secondary 

codes for a psychiatric code to assign a 

DRG code for adjustment. The system 

will continue to search the secondary 

codes for those that are appropriate for 

comorbidity adjustment. 

For more information on the code first 

policy, we refer our readers to the 

November 2004 IPF PPS final rule (69 

FR 66945) and see sections I.A.13 and 

I.B.7 of the FY 2020 ICD–10–CM Coding 

Guidelines, available at https://

www.cdc.gov/nchs/data/icd/ 

10cmguidelines-FY2020_final.pdf. In 

the FY 2015 IPF PPS final rule, we 

provided a code first table for reference 

that highlights the same or similar 

manifestation codes where the code first 

instructions apply in ICD–10–CM that 

were present in ICD–9–CM (79 FR 

46009). In FY 2018, FY 2019 and FY 

2020, there were no changes to the final 

ICD–10–CM codes in the IPF Code First 

table. For FY 2021, there were 18 ICD– 

10–CM codes deleted from the final IPF 

Code First table. For FY 2022 there are 

18 codes finalized for deletion from the 

ICD–10–CM codes in the IPF Code First 

table. The final FY 2022 Code First table 

is shown in Addendum B on our 

website at https://www.cms.gov/ 

Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/ 

tools.html. 

b. Final Payment for Comorbid 

Conditions 

The intent of the comorbidity 

adjustments is to recognize the 

increased costs associated with 

comorbid conditions by providing 

additional payments for certain existing 

medical or psychiatric conditions that 

are expensive to treat. In our RY 2012 

IPF PPS final rule (76 FR 26451 through 

26452), we explained that the IPF PPS 

includes 17 comorbidity categories and 

identified the new, revised, and deleted 

ICD–9–CM diagnosis codes that generate 

a comorbid condition payment 

adjustment under the IPF PPS for RY 

2012 (76 FR 26451). 

Comorbidities are specific patient 

conditions that are secondary to the 

patient’s principal diagnosis and that 

require treatment during the stay. 

Diagnoses that relate to an earlier 

episode of care and have no bearing on 

the current hospital stay are excluded 

and must not be reported on IPF claims. 

Comorbid conditions must exist at the 

time of admission or develop 

subsequently, and affect the treatment 

received, length of stay (LOS), or both 

treatment and LOS. 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42615 

For each claim, an IPF may receive 

only one comorbidity adjustment within 

a comorbidity category, but it may 

receive an adjustment for more than one 

comorbidity category. Current billing 

instructions for discharge claims, on or 

after October 1, 2015, require IPFs to 

enter the complete ICD–10–CM codes 

for up to 24 additional diagnoses if they 

co-exist at the time of admission, or 

develop subsequently and impact the 

treatment provided. 

The comorbidity adjustments were 

determined based on the regression 

analysis using the diagnoses reported by 

IPFs in FY 2002. The principal 

diagnoses were used to establish the 

DRG adjustments and were not 

accounted for in establishing the 

comorbidity category adjustments, 

except where ICD–9–CM code first 

instructions applied. In a code first 

situation, the submitted claim goes 

through the CMS processing system, 

which will identify the principal 

diagnosis code as non-psychiatric and 

search the secondary codes for a 

psychiatric code to assign an MS–DRG 

code for adjustment. The system will 

continue to search the secondary codes 

for those that are appropriate for 

comorbidity adjustment. 

As noted previously, it is our policy 

to maintain the same diagnostic coding 

set for IPFs that is used under the IPPS 

for providing the same psychiatric care. 

The 17 comorbidity categories formerly 

defined using ICD–9–CM codes were 

converted to ICD–10–CM/PCS in our FY 

2015 IPF PPS final rule (79 FR 45947 

through 45955). The goal for converting 

the comorbidity categories is referred to 

as replication, meaning that the 

payment adjustment for a given patient 

encounter is the same after ICD–10–CM 

implementation as it will be if the same 

record had been coded in ICD–9–CM 

and submitted prior to ICD–10–CM/PCS 

implementation on October 1, 2015. All 

conversion efforts were made with the 

intent of achieving this goal. For FY 

2022, we are finalizing our proposal to 

continue to use the same comorbidity 

adjustment factors in effect in FY 2021, 

which are found in Addendum A, 

available on our website at https://

www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/ 

InpatientPsychFacilPPS/tools.html. 

We have updated the ICD–10–CM/ 

PCS codes, which are associated with 

the existing IPF PPS comorbidity 

categories, based upon the final FY 2022 

update to the ICD–10–CM/PCS code set. 

The final FY 2022 ICD–10–CM/PCS 

updates include: 8 ICD–10–CM 

diagnosis codes added to the Poisoning 

comorbidity category, 4 codes deleted, 

and 4 changes to Poisoning comorbidity 

long descriptions; 2 ICD–10–CM 

diagnosis codes added to the 

Developmental Disabilities comorbidity 

category and 1 code deleted; and 3 ICD– 

10–PCS codes added to the Oncology 

Procedures comorbidity category. These 

updates are detailed in Addenda B of 

this final rule, which are available on 

our website at https://www.cms.gov/ 

Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/ 

tools.html. 

In accordance with the policy 

established in the FY 2015 IPF PPS final 

rule (79 FR 45949 through 45952), we 

reviewed all new FY 2022 ICD–10–CM 

codes to remove codes that were site 

‘‘unspecified’’ in terms of laterality from 

the FY 2022 ICD–10–CM/PCS codes in 

instances where more specific codes are 

available. As we stated in the FY 2015 

IPF PPS final rule, we believe that 

specific diagnosis codes that narrowly 

identify anatomical sites where disease, 

injury, or a condition exists should be 

used when coding patients’ diagnoses 

whenever these codes are available. We 

finalized in the FY 2015 IPF PPS rule, 

that we would remove site 

‘‘unspecified’’ codes from the IPF PPS 

ICD–10–CM/PCS codes in instances 

when laterality codes (site specified 

codes) are available, as the clinician 

should be able to identify a more 

specific diagnosis based on clinical 

assessment at the medical encounter. 

None of the finalized additions to the 

FY 2022 ICD–10–CM/PCS codes were 

site ‘‘unspecified’’ by laterality, 

therefore, we are not removing any of 

the new codes. 

Comment: A commenter requested 

that CMS add 13 ICD–10–CM codes for 

infectious diseases to the list of codes 

that qualify for the IPF PPS comorbidity 

adjustment. 

Response: As noted previously, the 

intent of the comorbidity adjustments is 

to recognize the increased costs 

associated with comorbid conditions by 

providing additional payments for 

certain existing medical or psychiatric 

conditions that are expensive to treat. 

Also, the comorbidity adjustments were 

derived through a regression analysis, 

which also includes other IPF PPS 

adjustments (for example, the age 

adjustment). Our established policy is to 

annually update the ICD–10–CM/PCS 

codes, which are associated with the 

existing IPF PPS comorbidity categories. 

Adding or removing codes to the 

existing comorbidity categories that are 

not part of the annual coding update 

would occur as part of a larger IPF PPS 

refinement. We did not propose to 

refine the IPF PPS in the FY 2022 IPF 

PPS proposed rule, and therefore, are 

not changing the policy in this final 

rule. However, we will consider the 

comment to potentially inform future 

refinements. 

c. Final Patient Age Adjustments 

As explained in the November 2004 

IPF PPS final rule (69 FR 66922), we 

analyzed the impact of age on per diem 

cost by examining the age variable 

(range of ages) for payment adjustments. 

In general, we found that the cost per 

day increases with age. The older age 

groups are costlier than the under 45 age 

group, the differences in per diem cost 

increase for each successive age group, 

and the differences are statistically 

significant. For FY 2022, we are 

finalizing our proposal to continue to 

use the patient age adjustments 

currently in effect in FY 2021, as shown 

in Addendum A of this rule (see https:// 

www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/ 

InpatientPsychFacilPPS/tools.html). 

d. Final Variable Per Diem Adjustments 

We explained in the November 2004 

IPF PPS final rule (69 FR 66946) that the 

regression analysis indicated that per 

diem cost declines as the length of stay 

(LOS) increases. The variable per diem 

adjustments to the Federal per diem 

base rate account for ancillary and 

administrative costs that occur 

disproportionately in the first days after 

admission to an IPF. As discussed in the 

November 2004 IPF PPS final rule, we 

used a regression analysis to estimate 

the average differences in per diem cost 

among stays of different lengths (69 FR 

66947 through 66950). As a result of this 

analysis, we established variable per 

diem adjustments that begin on day 1 

and decline gradually until day 21 of a 

patient’s stay. For day 22 and thereafter, 

the variable per diem adjustment 

remains the same each day for the 

remainder of the stay. However, the 

adjustment applied to day 1 depends 

upon whether the IPF has a qualifying 

ED. If an IPF has a qualifying ED, it 

receives a 1.31 adjustment factor for day 

1 of each stay. If an IPF does not have 

a qualifying ED, it receives a 1.19 

adjustment factor for day 1 of the stay. 

The ED adjustment is explained in more 

detail in section III.D.4 of this rule. 

For FY 2022, we are finalizing our 

proposal to continue to use the variable 

per diem adjustment factors currently in 

effect, as shown in Addendum A of this 

rule (available at https://www.cms.gov/ 

Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/ 

tools.html). A complete discussion of 

the variable per diem adjustments 

appears in the November 2004 IPF PPS 

final rule (69 FR 66946). 


lotter on DSK11XQN23PROD with RULES5
42616 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

D. Final Updates to the IPF PPS FacilityLevel Adjustments 

The IPF PPS includes facility-level 

adjustments for the wage index, IPFs 

located in rural areas, teaching IPFs, 

cost of living adjustments for IPFs 

located in Alaska and Hawaii, and IPFs 

with a qualifying ED. 

1. Wage Index Adjustment 

a. Background 

As discussed in the RY 2007 IPF PPS 

final rule (71 FR 27061), RY 2009 IPF 

PPS (73 FR 25719) and the RY 2010 IPF 

PPS notices (74 FR 20373), in order to 

provide an adjustment for geographic 

wage levels, the labor-related portion of 

an IPF’s payment is adjusted using an 

appropriate wage index. Currently, an 

IPF’s geographic wage index value is 

determined based on the actual location 

of the IPF in an urban or rural area, as 

defined in § 412.64(b)(1)(ii)(A) and (C). 

Due to the variation in costs and 

because of the differences in geographic 

wage levels, in the November 15, 2004 

IPF PPS final rule, we required that 

payment rates under the IPF PPS be 

adjusted by a geographic wage index. 

We proposed and finalized a policy to 

use the unadjusted, pre-floor, prereclassified IPPS hospital wage index to 

account for geographic differences in 

IPF labor costs. We implemented use of 

the pre-floor, pre-reclassified IPPS 

hospital wage data to compute the IPF 

wage index since there was not an IPFspecific wage index available. We 

believe that IPFs generally compete in 

the same labor market as IPPS hospitals 

so the pre-floor, pre-reclassified IPPS 

hospital wage data should be reflective 

of labor costs of IPFs. We believe this 

pre-floor, pre-reclassified IPPS hospital 

wage index to be the best available data 

to use as proxy for an IPF specific wage 

index. As discussed in the RY 2007 IPF 

PPS final rule (71 FR 27061 through 

27067), under the IPF PPS, the wage 

index is calculated using the IPPS wage 

index for the labor market area in which 

the IPF is located, without considering 

geographic reclassifications, floors, and 

other adjustments made to the wage 

index under the IPPS. For a complete 

description of these IPPS wage index 

adjustments, we refer readers to the FY 

2019 IPPS/LTCH PPS final rule (83 FR 

41362 through 41390). Our wage index 

policy at § 412.424(a)(2), requires us to 

use the best Medicare data available to 

estimate costs per day, including an 

appropriate wage index to adjust for 

wage differences. 

When the IPF PPS was implemented 

in the November 15, 2004 IPF PPS final 

rule, with an effective date of January 1, 

2005, the pre-floor, pre-reclassified IPPS 

hospital wage index that was available 

at the time was the FY 2005 pre-floor, 

pre-reclassified IPPS hospital wage 

index. Historically, the IPF wage index 

for a given RY has used the pre-floor, 

pre-reclassified IPPS hospital wage 

index from the prior FY as its basis. 

This has been due in part to the prefloor, pre-reclassified IPPS hospital 

wage index data that were available 

during the IPF rulemaking cycle, where 

an annual IPF notice or IPF final rule 

was usually published in early May. 

This publication timeframe was 

relatively early compared to other 

Medicare payment rules because the IPF 

PPS follows a RY, which was defined in 

the implementation of the IPF PPS as 

the 12-month period from July 1 to June 

30 (69 FR 66927). Therefore, the best 

available data at the time the IPF PPS 

was implemented was the pre-floor, prereclassified IPPS hospital wage index 

from the prior FY (for example, the RY 

2006 IPF wage index was based on the 

FY 2005 pre-floor, pre-reclassified IPPS 

hospital wage index). 

In the RY 2012 IPF PPS final rule, we 

changed the reporting year timeframe 

for IPFs from a RY to the FY, which 

begins October 1 and ends September 30 

(76 FR 26434 through 26435). In that FY 

2012 IPF PPS final rule, we continued 

our established policy of using the prefloor, pre-reclassified IPPS hospital 

wage index from the prior year (that is, 

from FY 2011) as the basis for the FY 

2012 IPF wage index. This policy of 

basing a wage index on the prior year’s 

pre-floor, pre-reclassified IPPS hospital 

wage index has been followed by other 

Medicare payment systems, such as 

hospice and inpatient rehabilitation 

facilities. By continuing with our 

established policy, we remained 

consistent with other Medicare payment 

systems. 

In FY 2020, we finalized the IPF wage 

index methodology to align the IPF PPS 

wage index with the same wage data 

timeframe used by the IPPS for FY 2020 

and subsequent years. Specifically, we 

finalized to use the pre-floor, prereclassified IPPS hospital wage index 

from the FY concurrent with the IPF FY 

as the basis for the IPF wage index. For 

example, the FY 2020 IPF wage index 

was based on the FY 2020 pre-floor, prereclassified IPPS hospital wage index 

rather than on the FY 2019 pre-floor, 

pre-reclassified IPPS hospital wage 

index. 

We explained in the FY 2020 

proposed rule (84 FR 16973), that using 

the concurrent pre-floor, pre-reclassified 

IPPS hospital wage index will result in 

the most up-to-date wage data being the 

basis for the IPF wage index. It will also 

result in more consistency and parity in 

the wage index methodology used by 

other Medicare payment systems. The 

Medicare SNF PPS already used the 

concurrent IPPS hospital wage index 

data as the basis for the SNF PPS wage 

index. Thus, the wage adjusted 

Medicare payments of various provider 

types will be based upon wage index 

data from the same timeframe. CMS 

proposed similar policies to use the 

concurrent pre-floor, pre-reclassified 

IPPS hospital wage index data in other 

Medicare payment systems, such as 

hospice and inpatient rehabilitation 

facilities. For FY 2022, we proposed to 

continue to use the concurrent pre-floor, 

pre-reclassified IPPS hospital wage 

index as the basis for the IPF wage 

index. 

Comment: Several commenters 

expressed concerns with our proposal to 

continue using the concurrent pre-floor, 

pre-reclassified IPPS hospital wage 

index as the basis for the IPF wage 

index. Three commenters recommended 

CMS extend the transition for the 

reductions in payment for certain IPFs 

resulting from the wage index changes 

adopted in the FY 2021 IPF PPS final 

rule. Another commenter also 

recommended that CMS apply a nonbudget neutral 5 percent cap on 

decreases to a hospital’s wage index 

value to help mitigate wide annual 

swings that are beyond a hospital’s 

ability to control. 

Response: We did not propose to 

modify the transition policy that was 

finalized in the FY 2021 IPF PPS final 

rule; therefore, we are not changing the 

previously adopted policy in this final 

rule. As we discussed in the FY 2021 

IPF PPS final rule (85 FR 47058 through 

47059), the transition policy caps the 

estimated reduction in an IPF’s wage 

index to 5 percent in FY 2021, with no 

cap applied in FY 2022. We stated our 

belief that implementing updated wage 

index values along with the revised 

OMB delineations will result in wage 

index values being more representative 

of the actual costs of labor in a given 

area. As evidenced by the detailed 

economic analysis (85 FR 47065 through 

47068), we estimated that implementing 

these wage index changes would have 

distributional effects, both positive and 

negative, among IPF providers. We 

continue to believe that applying the 5- 

percent cap transition policy in year one 

provided an adequate safeguard against 

any significant payment reductions, has 

allowed for sufficient time to make 

operational changes for future FYs, and 

provided a reasonable balance between 

mitigating some short-term instability in 

IPF payments and improving the 

accuracy of the payment adjustment for 

differences in area wage levels. 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42617 

We note that certain changes to wage 

index policy may significantly affect 

Medicare payments. These changes may 

arise from revisions to the OMB 

delineations of statistical areas resulting 

from the decennial census data, periodic 

updates to the OMB delineations in the 

years between the decennial censuses, 

or other wage index policy changes. 

While we consider how best to address 

these potential scenarios in a consistent 

and thoughtful manner, we reiterate that 

our policy principles with regard to the 

wage index include generally using the 

most current data and information 

available and providing that data and 

information, as well as any approaches 

to addressing any significant effects on 

Medicare payments resulting from these 

potential scenarios, in notice and 

comment rulemaking. 

Comment: Two commenters 

recommended that CMS incorporate a 

frontier state floor into the IPF wage 

index. Another commenter requested 

that CMS implement policies to address 

the disparity in payments between rural 

and urban IPFs, similar to policies that 

have been adopted for IPPS hospitals. 

Response: We appreciate commenters’ 

suggestions regarding opportunities to 

improve the accuracy of the IPF wage 

index. We did not propose the specific 

policies that commenters have 

suggested, but we will take them into 

consideration to potentially inform 

future rulemaking. 

Final Decision: For FY 2022, we are 

finalizing the proposal to continue to 

use the concurrent pre-floor, prereclassified IPPS hospital wage index as 

the basis for the IPF wage index. Since 

we did not propose any changes to the 

2-year transition that was finalized in 

the FY 2021 IPF PPS final rule, there 

will be no cap applied to the reduction 

in the wage index for the second year 

(that is, FY 2022). 

We will apply the IPF wage index 

adjustment to the labor-related share of 

the national base rate and ECT payment 

per treatment. The labor-related share of 

the national rate and ECT payment per 

treatment will change from 77.3 percent 

in FY 2021 to 77.2 percent in FY 2022. 

This percentage reflects the laborrelated share of the 2016-based IPF 

market basket for FY 2022 (see section 

III.A.4 of this rule). 

b. Office of Management and Budget 

(OMB) Bulletins 

(i.) Background 

The wage index used for the IPF PPS 

is calculated using the unadjusted, prereclassified and pre-floor IPPS wage 

index data and is assigned to the IPF on 

the basis of the labor market area in 

which the IPF is geographically located. 

IPF labor market areas are delineated 

based on the Core-Based Statistical Area 

(CBSAs) established by the OMB. 

Generally, OMB issues major 

revisions to statistical areas every 10 

years, based on the results of the 

decennial census. However, OMB 

occasionally issues minor updates and 

revisions to statistical areas in the years 

between the decennial censuses through 

OMB Bulletins. These bulletins contain 

information regarding CBSA changes, 

including changes to CBSA numbers 

and titles. OMB bulletins may be 

accessed online at https://

www.whitehouse.gov/omb/informationfor-agencies/bulletins/. In accordance 

with our established methodology, the 

IPF PPS has historically adopted any 

CBSA changes that are published in the 

OMB bulletin that corresponds with the 

IPPS hospital wage index used to 

determine the IPF wage index and, 

when necessary and appropriate, has 

proposed and finalized transition 

policies for these changes. 

In the RY 2007 IPF PPS final rule (71 

FR 27061 through 27067), we adopted 

the changes discussed in the OMB 

Bulletin No. 03–04 (June 6, 2003), 

which announced revised definitions 

for MSAs, and the creation of 

Micropolitan Statistical Areas and 

Combined Statistical Areas. In adopting 

the OMB CBSA geographic designations 

in RY 2007, we did not provide a 

separate transition for the CBSA-based 

wage index since the IPF PPS was 

already in a transition period from 

TEFRA payments to PPS payments. 

In the RY 2009 IPF PPS notice, we 

incorporated the CBSA nomenclature 

changes published in the most recent 

OMB bulletin that applied to the IPPS 

hospital wage index used to determine 

the current IPF wage index and stated 

that we expected to continue to do the 

same for all the OMB CBSA 

nomenclature changes in future IPF PPS 

rules and notices, as necessary (73 FR 

25721). 

Subsequently, CMS adopted the 

changes that were published in past 

OMB bulletins in the FY 2016 IPF PPS 

final rule (80 FR 46682 through 46689), 

the FY 2018 IPF PPS rate update (82 FR 

36778 through 36779), the FY 2020 IPF 

PPS final rule (84 FR 38453 through 

38454), and the FY 2021 IPF PPS final 

rule (85 FR 47051 through 47059). We 

direct readers to each of these rules for 

more information about the changes that 

were adopted and any associated 

transition policies. 

In part due to the scope of changes 

involved in adopting the CBSA 

delineations for FY 2021, we finalized a 

2-year transition policy consistent with 

our past practice of using transition 

policies to help mitigate negative 

impacts on hospitals of certain wage 

index policy changes. We applied a 5- 

percent cap on wage index decreases to 

all IPF providers that had any decrease 

in their wage indexes, regardless of the 

circumstance causing the decline, so 

that an IPF’s final wage index for FY 

2021 will not be less than 95 percent of 

its final wage index for FY 2020, 

regardless of whether the IPF was part 

of an updated CBSA. We refer readers 

to the FY 2021 IPF PPS final rule (85 FR 

47058 through 47059) for a more 

detailed discussion about the wage 

index transition policy for FY 2021. 

On March 6, 2020 OMB issued OMB 

Bulletin 20–01 (available on the web at 

https://www.whitehouse.gov/wpcontent/uploads/2020/03/Bulletin-20- 

01.pdf). In considering whether to adopt 

this bulletin, we analyzed whether the 

changes in this bulletin would have a 

material impact on the IPF PPS wage 

index. This bulletin creates only one 

Micropolitan statistical area. As 

discussed in further detail in section 

III.D.1.b.ii, since Micropolitan areas are 

considered rural for the IPF PPS wage 

index, this bulletin has no material 

impact on the IPF PPS wage index. That 

is, the constituent county of the new 

Micropolitan area was considered rural 

effective as of FY 2021 and would 

continue to be considered rural if we 

adopted OMB Bulletin 20–01. 

Therefore, we did not propose to adopt 

OMB Bulletin 20–01 in the FY 2022 IPF 

PPS proposed rule. 

(ii.) Micropolitan Statistical Areas 

OMB defines a ‘‘Micropolitan 

Statistical Area’’ as a CBSA associated 

with at least one urban cluster that has 

a population of at least 10,000, but less 

than 50,000 (75 FR 37252). We refer to 

these as Micropolitan Areas. After 

extensive impact analysis, consistent 

with the treatment of these areas under 

the IPPS as discussed in the FY 2005 

IPPS final rule (69 FR 49029 through 

49032), we determined the best course 

of action would be to treat Micropolitan 

Areas as ‘‘rural’’ and include them in 

the calculation of each state’s IPF PPS 

rural wage index. We refer the reader to 

the FY 2007 IPF PPS final rule (71 FR 

27064 through 27065) for a complete 

discussion regarding treating 

Micropolitan Areas as rural. 

c. Final Adjustment for Rural Location 

In the November 2004 IPF PPS final 

rule, (69 FR 66954) we provided a 17 

percent payment adjustment for IPFs 

located in a rural area. This adjustment 

was based on the regression analysis, 

which indicated that the per diem cost 


lotter on DSK11XQN23PROD with RULES5
42618 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

of rural facilities was 17 percent higher 

than that of urban facilities after 

accounting for the influence of the other 

variables included in the regression. 

This 17 percent adjustment has been 

part of the IPF PPS each year since the 

inception of the IPF PPS. For FY 2022, 

we proposed to continue to apply a 17 

percent payment adjustment for IPFs 

located in a rural area as defined at 

§ 412.64(b)(1)(ii)(C) (see 69 FR 66954 for 

a complete discussion of the adjustment 

for rural locations). 

Comment: We received one comment 

in favor of the proposed extension of the 

17 percent payment adjustment for rural 

IPFs. The commenter acknowledged 

CMS’ efforts to avoid disparities in 

payments to facilities in rural and 

underserved communities. 

Response: We appreciate this 

comment of support. Since the 

inception of the IPF PPS, we have 

applied a 17 percent adjustment for IPFs 

located in rural areas. As stated in the 

previous paragraph, this adjustment was 

derived from the results of our 

regression analysis and was 

incorporated into the payment system in 

order to ensure the accuracy of 

payments to rural IPFs. CMS continues 

to look for ways to ensure accuracy of 

payments to rural IPFs. 

Final Decision: For FY 2022, we are 

finalizing our proposal to continue to 

apply a 17 percent payment adjustment 

for IPFs located in a rural area as 

defined at § 412.64(b)(1)(ii)(C). 

d. Final Budget Neutrality Adjustment 

Changes to the wage index are made 

in a budget-neutral manner so that 

updates do not increase expenditures. 

Therefore, for FY 2022, we are finalizing 

our proposal to continue to apply a 

budget-neutrality adjustment in 

accordance with our existing budgetneutrality policy. This policy requires 

us to update the wage index in such a 

way that total estimated payments to 

IPFs for FY 2022 are the same with or 

without the changes (that is, in a 

budget-neutral manner) by applying a 

budget neutrality factor to the IPF PPS 

rates. We use the following steps to 

ensure that the rates reflect the FY 2022 

update to the wage indexes (based on 

the FY 2018 hospital cost report data) 

and the labor-related share in a budgetneutral manner: 

Step 1: Simulate estimated IPF PPS 

payments, using the FY 2021 IPF wage 

index values (available on the CMS 

website) and labor-related share (as 

published in the FY 2021 IPF PPS final 

rule (85 FR 47043)). 

Step 2: Simulate estimated IPF PPS 

payments using the final FY 2022 IPF 

wage index values (available on the 

CMS website) and final FY 2022 laborrelated share (based on the latest 

available data as discussed previously). 

Step 3: Divide the amount calculated 

in step 1 by the amount calculated in 

step 2. The resulting quotient is the FY 

2022 budget-neutral wage adjustment 

factor of 1.0017. 

Step 4: Apply the FY 2022 budgetneutral wage adjustment factor from 

step 3 to the FY 2021 IPF PPS Federal 

per diem base rate after the application 

of the market basket update described in 

section III.A of this rule, to determine 

the FY 2022 IPF PPS Federal per diem 

base rate. 

2. Final Teaching Adjustment 

a. Background 

In the November 2004 IPF PPS final 

rule, we implemented regulations at 

sect; 412.424(d)(1)(iii) to establish a 

facility-level adjustment for IPFs that 

are, or are part of, teaching hospitals. 

The teaching adjustment accounts for 

the higher indirect operating costs 

experienced by hospitals that 

participate in graduate medical 

education (GME) programs. The 

payment adjustments are made based on 

the ratio of the number of full-time 

equivalent (FTE) interns and residents 

training in the IPF and the IPF’s average 

daily census (ADC). 

Medicare makes direct GME payments 

(for direct costs such as resident and 

teaching physician salaries, and other 

direct teaching costs) to all teaching 

hospitals including those paid under a 

PPS, and those paid under the TEFRA 

rate-of-increase limits. These direct 

GME payments are made separately 

from payments for hospital operating 

costs and are not part of the IPF PPS. 

The direct GME payments do not 

address the estimated higher indirect 

operating costs teaching hospitals may 

face. 

The results of the regression analysis 

of FY 2002 IPF data established the 

basis for the payment adjustments 

included in the November 2004 IPF PPS 

final rule. The results showed that the 

indirect teaching cost variable is 

significant in explaining the higher 

costs of IPFs that have teaching 

programs. We calculated the teaching 

adjustment based on the IPF’s ‘‘teaching 

variable,’’ which is (1 + (the number of 

FTE residents training in the IPF/the 

IPF’s ADC)). The teaching variable is 

then raised to the 0.5150 power to result 

in the teaching adjustment. This 

formula is subject to the limitations on 

the number of FTE residents, which are 

described in this section of this rule. 

We established the teaching 

adjustment in a manner that limited the 

incentives for IPFs to add FTE residents 

for the purpose of increasing their 

teaching adjustment. We imposed a cap 

on the number of FTE residents that 

may be counted for purposes of 

calculating the teaching adjustment. The 

cap limits the number of FTE residents 

that teaching IPFs may count for the 

purpose of calculating the IPF PPS 

teaching adjustment, not the number of 

residents teaching institutions can hire 

or train. We calculated the number of 

FTE residents that trained in the IPF 

during a ‘‘base year’’ and used that FTE 

resident number as the cap. An IPF’s 

FTE resident cap is ultimately 

determined based on the final 

settlement of the IPF’s most recent cost 

report filed before November 15, 2004 

(publication date of the IPF PPS final 

rule). A complete discussion of the 

temporary adjustment to the FTE cap to 

reflect residents due to hospital closure 

or residency program closure appears in 

the RY 2012 IPF PPS proposed rule (76 

FR 5018 through 5020) and the RY 2012 

IPF PPS final rule (76 FR 26453 through 

26456). In section III.D.2.b of this final 

rule, we discuss finalized updates to the 

IPF policy on temporary adjustment to 

the FTE cap. 

In the regression analysis, the 

logarithm of the teaching variable had a 

coefficient value of 0.5150. We 

converted this cost effect to a teaching 

payment adjustment by treating the 

regression coefficient as an exponent 

and raising the teaching variable to a 

power equal to the coefficient value. We 

note that the coefficient value of 0.5150 

was based on the regression analysis 

holding all other components of the 

payment system constant. A complete 

discussion of how the teaching 

adjustment was calculated appears in 

the November 2004 IPF PPS final rule 

(69 FR 66954 through 66957) and the 

RY 2009 IPF PPS notice (73 FR 25721). 

As with other adjustment factors 

derived through the regression analysis, 

we do not plan to rerun the teaching 

adjustment factors in the regression 

analysis until we more fully analyze IPF 

PPS data. Therefore, in this FY 2022 

final rule, we are finalizing our proposal 

to continue to retain the coefficient 

value of 0.5150 for the teaching 

adjustment to the Federal per diem base 

rate. 

b. Final Update to IPF Teaching Policy 

on IPF Program Closures and Displaced 

Residents 

For FY 2022, we proposed to change 

the IPF policy regarding displaced 

residents from IPF closures and closures 

of IPF teaching programs. Specifically, 

we proposed to adopt conforming 

changes to the IPF PPS teaching policy 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42619 

to align with the policy changes that the 

IPPS finalized in the FY 2021 IPPS final 

rule (85 FR 58865 through 58870). We 

believe that the IPF IME policy relating 

to hospital closure and displaced 

students is susceptible to the same 

vulnerabilities as IPPS GME policy. 

Hence, if an IPF with a large number of 

residents training in its residency 

program announces that it is closing, 

these residents will become displaced 

and will need to find alternative 

positions at other IPF hospitals or risk 

being unable to become Board-certified. 

Although we proposed to adopt a policy 

under the IPF PPS that is consistent 

with an applicable policy under the 

IPPS, the actual caps under the two 

payment systems may not be 

commingled. In other words, the 

resident cap applicable under the IPPS 

is separate from the resident cap 

applicable under the IPF PPS; moreover, 

a provider cannot add its IPF resident 

cap to its IPPS resident cap in order to 

increase the number of residents it 

receives payment for under either 

payment system. 

As stated in the November 2004 IPF 

PPS final rule (69 FR 66922), we 

implemented regulations at 

§ 412.424(d)(1)(iii) to establish a facilitylevel adjustment for IPFs that are, or are 

part of, teaching hospitals. The facilitylevel adjustment we are providing for 

teaching hospitals under IPF PPS 

parallels the IME payments paid under 

the IPPS. Both payments are add on 

adjustments to the amount per case and 

both are based in part on the number of 

full-time equivalent (FTE) residents 

training at the facility. 

The regulation at 42 CFR 

412.424(d)(1)(iii)(F) permits an IPF to 

temporarily adjust its FTE cap to reflect 

residents added because of another 

hospital or program’s closure. We first 

implemented regulations regarding 

residents displaced by teaching hospital 

and program closures in the May 6, 

2011 IPF PPS final rule (76 FR 26431). 

In that final rule, we adopted the IPPS 

definition of ‘‘closure of a hospital’’ at 

42 CFR 413.79(h)(1)(i) to apply to IPF 

closures as well, and to mean that the 

IPF terminates its Medicare provider 

agreement as specified in 42 CFR 

489.52. In the proposed rule, we 

proposed to codify this definition, as 

well as, the definition of an IPF program 

closure, at § 412.402. 

Although not explicitly stated in 

regulatory text, our current policy is that 

a displaced resident is one that is 

physically present at the hospital 

training on the day prior to or the day 

of hospital or program closure. This 

longstanding policy derived from the 

fact that in the regulations text, there are 

requirements that the receiving hospital 

identifies the residents ‘‘who have come 

from the closed IPF’’ 

(§ 412.424(d)(1)(iii)(F)(1)(ii)) or 

identifies the residents ‘‘who have come 

from another IPF’s closed program’’ 

(§ 412.424(d)(1)(iii)(F)(2)(i)), and that 

the IPF that closed its program identifies 

‘‘the residents who were in training at 

the time of the program’s closure’’ 

(§ 412.424(d)(1)(iii)(F)(2)(ii)). We 

considered the residents who were 

physically present at the IPF to be those 

residents who were ‘‘training at the time 

of the program’s closure,’’ thereby 

granting them the status of ‘‘displaced 

residents.’’ Although we did not want to 

limit the ‘‘displaced residents’’ to only 

those physically present at the time of 

closure, it becomes much more 

administratively challenging for the 

following groups of residents at closing 

IPFs/programs to continue their 

training: (1) Residents who leave the 

program after the closure is publicly 

announced to continue training at 

another IPF, but before the actual 

closure; (2) residents assigned to and 

training at planned rotations at other 

IPFs who will be unable to return to 

their rotations at the closing IPF or 

program; and (3) individuals (such as 

medical students or would-be fellows) 

who matched into resident programs at 

the closing IPF or program but have not 

yet started training at the closing IPF or 

program. Other groups of residents who, 

under current policy, are already 

considered ‘‘displaced residents’’ 

include—(1) residents who are 

physically training in the IPF on the day 

prior to or day of program or IPF 

closure; and (2) residents who would 

have been at the closing IPF or IPF 

program on the day prior to or of closure 

but were on approved leave at that time, 

and are unable to return to their training 

at the closing IPF or IPF program. 

We proposed to amend the IPF policy 

with regard to closing teaching IPFs and 

closing residency programs to address 

the needs of residents attempting to find 

alternative IPFs in which to complete 

their training. Additionally, this 

proposal addresses the incentives of 

originating and receiving IPFs with 

regard to ensuring we appropriately 

account for their indirect teaching costs 

by way of an appropriate IPF teaching 

adjustment based on each program’s 

resident FTEs. We proposed to change 

two aspects of the current IPF policy, 

which are discussed in the following 

section. 

First, rather than link the status of 

displaced residents, for the purpose of 

the receiving IPF’s request to increase 

their FTE cap, to the resident’s presence 

at the closing IPF or program on the day 

prior to or the day of program or IPF 

closure, we proposed that the ideal day 

will be the day that the closure was 

publicly announced, (for example, via a 

press release or a formal notice to the 

Accreditation Council on Graduate 

Medical Education (ACGME)). This will 

provide greater flexibility for the 

residents to transfer while the IPF 

operations or residency programs were 

winding down, rather than waiting until 

the last day of IPF or program operation. 

This will address the needs of the first 

group of residents as previously 

described: Residents who leave the IPF 

program after the closure was publicly 

announced to continue training at 

another IPF, but before the day of actual 

closure. 

Second, by removing the link between 

the status of displaced residents and 

their presence at the closing IPF or 

program on the day prior to or the day 

of program or IPF closure, we proposed 

to also allow the second and third group 

of residents who are not physically at 

the closing IPF/closing program, but had 

intended to train at (or return to training 

at, in the case of residents on rotation) 

to be considered displaced residents. 

Thus, we proposed to revise our 

teaching policy with regard to which 

residents can be considered ‘‘displaced’’ 

for the purpose of the receiving IPF’s 

request to increase their FTE cap in the 

situation where an IPF announces 

publicly that it is closing or that it is 

closing an IPF residency program(s). 

Specifically, we are adopting the 

definitions of ‘‘closure of a hospital’’, 

‘‘closure of a hospital residency training 

program’’, and ‘‘displaced resident’’ as 

defined at 42 CFR 413.79(h) but with 

respect to IPFs and for the purposes of 

accounting for indirect teaching costs. 

In addition, we proposed to change 

another detail of the IPF teaching policy 

specific to the requirements for the 

receiving IPF. To apply for the 

temporary increase in the FTE resident 

cap, the receiving IPF will have to 

submit a letter to its Medicare 

Administrative Contractor (MAC) 

within 60 days of beginning the training 

of the displaced residents. As 

established under existing regulation at 

§ 412.424(d)(1)(iii)(F)(1)(ii) and 

§ 412.424(d)(1)(iii)(F)(2)(i), this letter 

must identify the residents who have 

come from the closed IPF or program 

that have caused the receiving IPF to 

exceed its cap, and the receiving IPF 

must specify the length of time the 

adjustment is needed. Moreover, we 

want to propose clarifications on how 

the information will be delivered in this 

letter. Consistent with IPPS teaching 

policy, we proposed that the letter from 

the receiving IPF will have to include: 


lotter on DSK11XQN23PROD with RULES5
42620 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

(1) The name of each displaced resident; 

(2) the last four digits of each displaced 

resident’s social security number; (3) the 

IPF and program in which each resident 

was training previously; and (4) the 

amount of the cap increase needed for 

each resident (based on how much the 

receiving IPF is in excess of its cap and 

the length of time for which the 

adjustments are needed). We proposed 

to require the receiving hospital to only 

supply the last four digits of each 

displaced resident’s social security 

number to reduce the amount of 

personally identifiable information (PII) 

included in these agreements. 

We also clarified, as previously 

discussed in the May 6, 2011 IPF PPS 

final rule (76 FR 26455), the maximum 

number of FTE resident cap slots that 

could be transferred to all receiving IPFs 

is the number of FTE resident cap slots 

belonging to the IPF that has the closed 

program or that is closing. Therefore, if 

the originating IPF is training residents 

in excess of its cap, then being a 

displaced resident does not guarantee 

that a cap slot will be transferred along 

with that resident. Therefore, if there are 

more IPF displaced residents than 

available cap slots, the slots may be 

apportioned according to the closing 

IPF’s discretion. The decision to transfer 

a cap slot if one is available will be 

voluntary and made at the sole 

discretion of the originating IPF. 

However, if the originating IPF decides 

to do so, then it will be the originating 

IPF’s responsibility to determine how 

much of an available cap slot will go 

with a particular resident (if any). We 

also note, as we previously discussed in 

the May 6, 2011 IPF PPS final rule (76 

FR 25455), only to the extent a receiving 

IPF would exceed its FTE cap by 

training displaced residents would it be 

eligible for a temporary adjustment to its 

resident FTE cap. Displaced residents 

are factored into the receiving IPF’s ratio 

of resident FTEs to the facility’s average 

daily census. 

Comment: We received 3 comments 

on our proposed updates to IPF teaching 

policy. All commenters appreciate the 

alignment of IPF teaching policy with 

IPPS. They believe it is important to 

protect medical education. Therefore, 

decreasing confusion and streamlining 

the process gives residents and program 

directors more time to find a new 

program or rotation site, which can only 

help the transfer process. 

Response: We thank these 

commenters for their support. 

Final Decision: For FY 2022, we are 

finalizing the closure policy as 

proposed. Section 124 of the BBRA 

gives the Secretary broad discretion to 

determine the appropriate adjustment 

factors for the IPF PPS. We are finalizing 

our proposal to implement the policy 

regarding IPF resident caps and closures 

to remain consistent with the way that 

the IPPS teaching policy calculates FTE 

resident caps in the case of a receiving 

hospital that obtains a temporary IME 

and direct GME cap adjustment for 

assuming the training of displaced 

residents due to another hospital or 

residency program’s closure. We are 

also finalizing our proposal that in the 

future, we will deviate from IPPS 

teaching policy as it pertains to 

counting displaced residents for the 

purposes of the IPF teaching adjustment 

only when it is necessary and 

appropriate for the IPF PPS. 

In addition, we are finalizing our 

proposal to amend the IPF policy with 

regard to closing teaching IPFs and 

closing residency programs to address 

the needs of residents attempting to find 

alternative IPFs in which to complete 

their training. This proposal addresses 

the incentives of originating and 

receiving IPFs with regard to ensuring 

we appropriately account for their 

indirect teaching costs by way of an 

appropriate IPF teaching adjustment 

based on each program’s resident FTEs. 

We are also finalizing our proposal to 

change two aspects of the current IPF 

policy, which are discussed in the 

following section. 

First, rather than link the status of 

displaced residents for the purpose of 

the receiving IPF’s request to increase 

their FTE cap to the resident’s presence 

at the closing IPF or program on the day 

prior to or the day of program or IPF 

closure, we are finalizing our proposal 

that the ideal day will be the day that 

the closure was publicly announced, 

(for example, via a press release or a 

formal notice to the Accreditation 

Council on Graduate Medical Education 

(ACGME)). This will provide greater 

flexibility for the residents to transfer 

while the IPF operations or residency 

programs were winding down, rather 

than waiting until the last day of IPF or 

program operation. This will address 

the needs of the first group of residents 

as previously described: Residents who 

leave the IPF program after the closure 

was publicly announced to continue 

training at another IPF, but before the 

day of actual closure. 

Second, by removing the link between 

the status of displaced residents and 

their presence at the closing IPF or 

program on the day prior to or the day 

of program or IPF closure, we are 

finalizing to also allow the second and 

third group of residents who are not 

physically at the closing IPF/closing 

program, but had intended to train at (or 

return to training at, in the case of 

residents on rotation) to be considered 

a displaced resident. Thus, we are 

finalizing our proposal to revise our 

teaching policy with regard to which 

residents can be considered ‘‘displaced’’ 

for the purpose of the receiving IPF’s 

request to increase their FTE cap in the 

situation where an IPF announces 

publicly that it is closing or that it is 

closing an IPF residency program(s). 

Specifically, we are adopting the 

definitions of ‘‘closure of a hospital’’, 

‘‘closure of a hospital residency training 

program’’, and ‘‘displaced resident’’ as 

defined at 42 CFR 413.79(h) but with 

respect to IPFs and for the purposes of 

accounting for indirect teaching costs. 

In addition, we are finalizing our 

proposal to change another detail of the 

IPF teaching policy specific to the 

requirements for the receiving IPF. To 

apply for the temporary increase in the 

FTE resident cap, the receiving IPF will 

have to submit a letter to its Medicare 

Administrative Contractor (MAC) 

within 60 days of beginning the training 

of the displaced residents. As 

established under existing regulation at 

§ 412.424(d)(1)(iii)(F)(1)(ii) and 

§ 412.424(d)(1)(iii)(F)(2)(i), this letter 

must identify the residents who have 

come from the closed IPF or program 

that have caused the receiving IPF to 

exceed its cap, and the receiving IPF 

must specify the length of time the 

adjustment is needed. Moreover, we are 

finalizing the clarifications on how the 

information will be delivered in this 

letter. Consistent with IPPS teaching 

policy, the letter from the receiving IPF 

will have to include: (1) The name of 

each displaced resident; (2) the last four 

digits of each displaced resident’s social 

security number; (3) the IPF and 

program in which each resident was 

training previously; and (4) the amount 

of the cap increase needed for each 

resident (based on how much the 

receiving IPF is in excess of its cap and 

the length of time for which the 

adjustments are needed). We are also 

finalizing our proposal to require the 

receiving hospital to only supply the 

last four digits of each displaced 

resident’s social security number to 

reduce the amount of personally 

identifiable information (PII) included 

in these agreements. 

We are also finalizing the clarification 

that the maximum number of FTE 

resident cap slots that could be 

transferred to all receiving IPFs is the 

number of FTE resident cap slots 

belonging to the IPF that has the closed 

program or that is closing. Therefore, if 

the originating IPF is training residents 

in excess of its cap, then being a 

displaced resident does not guarantee 

that a cap slot will be transferred along 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42621 

with that resident. Therefore, if there are 

more IPF displaced residents than 

available cap slots, the slots may be 

apportioned according to the closing 

IPF’s discretion. The decision to transfer 

a cap slot if one is available will be 

voluntary and made at the sole 

discretion of the originating IPF. 

However, if the originating IPF decides 

to do so, then it will be the originating 

IPF’s responsibility to determine how 

much of an available cap slot will go 

with a particular resident (if any). We 

also note that, as we previously 

discussed in the May 6, 2011 IPF PPS 

final rule (76 FR 25455), only to the 

extent a receiving IPF would exceed its 

FTE cap by training displaced residents 

would it be eligible for a temporary 

adjustment to its resident FTE cap. 

Displaced residents are factored into the 

receiving IPF’s ratio of resident FTEs to 

the facility’s average daily census. 

3. Final Cost of Living Adjustment for 

IPFs Located in Alaska and Hawaii 

The IPF PPS includes a payment 

adjustment for IPFs located in Alaska 

and Hawaii based upon the area in 

which the IPF is located. As we 

explained in the November 2004 IPF 

PPS final rule, the FY 2002 data 

demonstrated that IPFs in Alaska and 

Hawaii had per diem costs that were 

disproportionately higher than other 

IPFs. Other Medicare prospective 

payment systems (for example, the IPPS 

and LTCH PPS) adopted a COLA to 

account for the cost differential of care 

furnished in Alaska and Hawaii. 

We analyzed the effect of applying a 

COLA to payments for IPFs located in 

Alaska and Hawaii. The results of our 

analysis demonstrated that a COLA for 

IPFs located in Alaska and Hawaii will 

improve payment equity for these 

facilities. As a result of this analysis, we 

provided a COLA in the November 2004 

IPF PPS final rule. 

A COLA for IPFs located in Alaska 

and Hawaii is made by multiplying the 

non-labor-related portion of the Federal 

per diem base rate by the applicable 

COLA factor based on the COLA area in 

which the IPF is located. 

The COLA factors through 2009 were 

published by the Office of Personnel 

Management (OPM), and the OPM 

memo showing the 2009 COLA factors 

is available at https://www.chcoc.gov/ 

content/nonforeign-area-retirementequity-assurance-act. 

We note that the COLA areas for 

Alaska are not defined by county as are 

the COLA areas for Hawaii. In 5 CFR 

591.207, the OPM established the 

following COLA areas: 

• City of Anchorage, and 80-kilometer 

(50-mile) radius by road, as measured 

from the Federal courthouse. 

• City of Fairbanks, and 80-kilometer 

(50-mile) radius by road, as measured 

from the Federal courthouse. 

• City of Juneau, and 80-kilometer 

(50-mile) radius by road, as measured 

from the Federal courthouse. 

• Rest of the state of Alaska. 

As stated in the November 2004 IPF 

PPS final rule, we update the COLA 

factors according to updates established 

by the OPM. However, sections 1911 

through 1919 of the Non-foreign Area 

Retirement Equity Assurance Act, as 

contained in subtitle B of title XIX of the 

National Defense Authorization Act 

(NDAA) for FY 2010 (Pub. L. 111–84, 

October 28, 2009), transitions the Alaska 

and Hawaii COLAs to locality pay. 

Under section 1914 of NDAA, locality 

pay was phased in over a 3-year period 

beginning in January 2010, with COLA 

rates frozen as of the date of enactment, 

October 28, 2009, and then 

proportionately reduced to reflect the 

phase-in of locality pay. 

When we published the proposed 

COLA factors in the RY 2012 IPF PPS 

proposed rule (76 FR 4998), we 

inadvertently selected the FY 2010 

COLA rates, which had been reduced to 

account for the phase-in of locality pay. 

We did not intend to propose the 

reduced COLA rates because that would 

have understated the adjustment. Since 

the 2009 COLA rates did not reflect the 

phase-in of locality pay, we finalized 

the FY 2009 COLA rates for RY 2010 

through RY 2014. 

In the FY 2013 IPPS/LTCH final rule 

(77 FR 53700 through 53701), we 

established a new methodology to 

update the COLA factors for Alaska and 

Hawaii, and adopted this methodology 

for the IPF PPS in the FY 2015 IPF final 

rule (79 FR 45958 through 45960). We 

adopted this new COLA methodology 

for the IPF PPS because IPFs are 

hospitals with a similar mix of 

commodities and services. We think it 

is appropriate to have a consistent 

policy approach with that of other 

hospitals in Alaska and Hawaii. 

Therefore, the IPF COLAs for FY 2015 

through FY 2017 were the same as those 

applied under the IPPS in those years. 

As finalized in the FY 2013 IPPS/LTCH 

PPS final rule (77 FR 53700 and 53701), 

the COLA updates are determined every 

4 years, when the IPPS market basket 

labor-related share is updated. Because 

the labor-related share of the IPPS 

market basket was updated for FY 2018, 

the COLA factors were updated in FY 

2018 IPPS/LTCH rulemaking (82 FR 

38529). As such, we also updated the 

IPF PPS COLA factors for FY 2018 (82 

FR 36780 through 36782) to reflect the 

updated COLA factors finalized in the 

FY 2018 IPPS/LTCH rulemaking. 

For FY 2022, we are finalizing our 

proposal to update the COLA factors 

published by OPM for 2009 (as these are 

the last COLA factors OPM published 

prior to transitioning from COLAs to 

locality pay) using the methodology that 

we finalized in the FY 2013 IPPS/LTCH 

PPS final rule and adopted for the IPF 

PPS in the FY 2015 IPF final rule. 

Specifically, we are finalizing our 

proposal to update the 2009 OPM COLA 

factors by a comparison of the growth in 

the Consumer Price Indices (CPIs) for 

the areas of Urban Alaska and Urban 

Hawaii, relative to the growth in the CPI 

for the average U.S. city as published by 

the Bureau of Labor Statistics (BLS). We 

note that for the prior update to the 

COLA factors, we used the growth in the 

CPI for Anchorage and the CPI for 

Honolulu. Beginning in 2018, these 

indexes were renamed to the CPI for 

Urban Alaska and the CPI for Urban 

Hawaii due to the BLS updating its 

sample to reflect the data from the 2010 

Decennial Census on the distribution of 

the urban population (https://

www.bls.gov/regions/west/factsheet/ 

2018cpirevisionwest.pdf, accessed 

January 22, 2021). The CPI for Urban 

Alaska area covers Anchorage and 

Matanuska-Susitna Borough in the State 

of Alaska and the CPI for Urban Hawaii 

covers Honolulu in the State of Hawaii. 

BLS notes that the indexes are 

considered continuous over time, 

regardless of name or composition 

changes. 

Because BLS publishes CPI data for 

only Urban Alaska and Urban Hawaii, 

using the methodology we finalized in 

the FY 2013 IPPS/LTCH PPS final rule 

and adopted for the IPF PPS in the FY 

2015 IPF final rule, we are finalizing our 

proposal to use the comparison of the 

growth in the overall CPI relative to the 

growth in the CPI for those areas to 

update the COLA factors for all areas in 

Alaska and Hawaii, respectively. We 

believe that the relative price 

differences between these urban areas 

and the U.S. (as measured by the CPIs) 

are appropriate proxies for the relative 

price differences between the ‘‘other 

areas’’ of Alaska and Hawaii and the 

U.S. 

BLS publishes the CPI for All Items 

for Urban Alaska, Urban Hawaii, and for 

the average U.S. city. However, 

consistent with our methodology 

finalized in the FY 2013 IPPS/LTCH 

PPS final rule and adopted for the IPF 

PPS in the FY 2015 IPF final rule, we 

are finalizing our proposal to create 

reweighted CPIs for each of the 

respective areas to reflect the underlying 


lotter on DSK11XQN23PROD with RULES5
42622 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

composition of the IPPS market basket 

nonlabor-related share. The current 

composition of the CPI for All Items for 

all of the respective areas is 

approximately 40 percent commodities 

and 60 percent services. However, the 

IPPS nonlabor-related share is 

comprised of a different mix of 

commodities and services. Therefore, 

we are finalizing our proposal to create 

reweighted indexes for Urban Alaska, 

Urban Hawaii, and the average U.S. city 

using the respective CPI commodities 

index and CPI services index and 

proposed shares of 57 percent 

commodities/43 percent. We created 

reweighted indexes using BLS data for 

2009 through 2020—the most recent 

data available at the time of this final 

rulemaking. In the FY 2018 IPPS/LTCH 

PPS final rule (82 FR 38530), we created 

reweighted indexes based on the 2014- 

based IPPS market basket (which was 

adopted for the FY 2018 IPPS update) 

and BLS data for 2009 through 2016 (the 

most recent BLS data at the time of the 

FY 2018 IPPS/LTCH PPS rulemaking), 

and we updated the IPF PPS COLA 

factors accordingly for FY 2018. 

We continue to believe this 

methodology is appropriate because we 

continue to make a COLA for hospitals 

located in Alaska and Hawaii by 

multiplying the nonlabor-related 

portion of the standardized amount by 

a COLA factor. We note that OPM’s 

COLA factors were calculated with a 

statutorily mandated cap of 25 percent. 

As stated in the FY 2018 IPPS/LTCH 

PPS final rule (82 FR 38530), under the 

COLA update methodology we finalized 

in the FY 2013 IPPS/LTCH PPS final 

rule, we exercised our discretionary 

authority to adjust payments to 

hospitals in Alaska and Hawaii by 

incorporating this cap. In applying this 

finalized methodology for updating the 

COLA factors, for FY 2022, we are 

finalizing our proposal to continue to 

use such a cap, as our policy is based 

on OPM’s COLA factors (updated by the 

methodology described above). 

Applying this methodology, the 

COLA factors that we are finalizing our 

proposal to establish for FY 2022 to 

adjust the nonlabor-related portion of 

the standardized amount for IPFs 

located in Alaska and Hawaii are shown 

in Table 2. For comparison purposes, 

we also are showing the COLA factors 

effective for FY 2018 through FY 2021. 

The final IPF PPS COLA factors for 

FY 2022 are also shown in Addendum 

A to this final rule, and is available at 

https://www.cms.gov/Medicare/ 

Medicare-Fee-for-Service-Payment/ 

InpatientPsychFacilPPS/tools.html. 

4. Final Adjustment for IPFs with a 

Qualifying Emergency Department (ED) 

The IPF PPS includes a facility-level 

adjustment for IPFs with qualifying EDs. 

We provide an adjustment to the 

Federal per diem base rate to account 

for the costs associated with 

maintaining a full-service ED. The 

adjustment is intended to account for 

ED costs incurred by a psychiatric 

hospital with a qualifying ED or an 

excluded psychiatric unit of an IPPS 

hospital or a CAH, for preadmission 

services otherwise payable under the 

Medicare Hospital Outpatient 

Prospective Payment System (OPPS), 

furnished to a beneficiary on the date of 

the beneficiary’s admission to the 

hospital and during the day 

immediately preceding the date of 

admission to the IPF (see § 413.40(c)(2)), 

and the overhead cost of maintaining 

the ED. This payment is a facility-level 

adjustment that applies to all IPF 

admissions (with one exception which 

we described), regardless of whether a 

particular patient receives preadmission 

services in the hospital’s ED. 

The ED adjustment is incorporated 

into the variable per diem adjustment 

for the first day of each stay for IPFs 

with a qualifying ED. Those IPFs with 

a qualifying ED receive an adjustment 

factor of 1.31 as the variable per diem 

adjustment for day 1 of each patient 

stay. If an IPF does not have a qualifying 

ED, it receives an adjustment factor of 

1.19 as the variable per diem adjustment 

for day 1 of each patient stay. 

The ED adjustment is made on every 

qualifying claim except as described in 

this section of the proposed rule. As 

specified in § 412.424(d)(1)(v)(B), the ED 

adjustment is not made when a patient 

is discharged from an IPPS hospital or 

CAH and admitted to the same IPPS 

hospital’s or CAH’s excluded 

psychiatric unit. We clarified in the 

November 2004 IPF PPS final rule (69 

FR 66960) that an ED adjustment is not 

made in this case because the costs 

associated with ED services are reflected 

in the DRG payment to the IPPS hospital 

or through the reasonable cost payment 

made to the CAH. 

Therefore, when patients are 

discharged from an IPPS hospital or 

CAH and admitted to the same 

hospital’s or CAH’s excluded 


lotter on DSK11XQN23PROD with RULES5ER04AU21.171</GPH>

TABLE 2: Comparison oflPF PPS Cost-of-Living Adjustment Factors: IPFs Located in 

Alaska and Hawaii 

FY 2018 FY2022 

Area through through 

FY 2021 FY2025 

Alaska: 

City of Anchorage and 80-kilometer (50-mile) radius by road 1.25 1.22 

City of Fairbanks and 80-kilometer (50-mile) radius by road 1.25 1.22 

City of Juneau and 80-kilometer (50-mile) radius by road 1.25 1.22 

Rest of Alaska 1.25 1.24 

Hawaii: 

City and County of Honolulu 1.25 1.25 

County of Hawaii 1.21 1.22 

County of Kauai 1.25 1.25 

County of Maui and County of Kalawao 1.25 1.25 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42623 

psychiatric unit, the IPF receives the 

1.19 adjustment factor as the variable 

per diem adjustment for the first day of 

the patient’s stay in the IPF. For FY 

2022, we are finalizing our proposal to 

continue to retain the 1.31 adjustment 

factor for IPFs with qualifying EDs. A 

complete discussion of the steps 

involved in the calculation of the ED 

adjustment factors are in the November 

2004 IPF PPS final rule (69 FR 66959 

through 66960) and the RY 2007 IPF 

PPS final rule (71 FR 27070 through 

27072). 

F. Other Final Payment Adjustments 

and Policies 

1. Outlier Payment Overview 

The IPF PPS includes an outlier 

adjustment to promote access to IPF 

care for those patients who require 

expensive care and to limit the financial 

risk of IPFs treating unusually costly 

patients. In the November 2004 IPF PPS 

final rule, we implemented regulations 

at § 412.424(d)(3)(i) to provide a percase payment for IPF stays that are 

extraordinarily costly. Providing 

additional payments to IPFs for 

extremely costly cases strongly 

improves the accuracy of the IPF PPS in 

determining resource costs at the patient 

and facility level. These additional 

payments reduce the financial losses 

that would otherwise be incurred in 

treating patients who require costlier 

care, and therefore, reduce the 

incentives for IPFs to under-serve these 

patients. We make outlier payments for 

discharges in which an IPF’s estimated 

total cost for a case exceeds a fixed 

dollar loss threshold amount 

(multiplied by the IPF’s facility-level 

adjustments) plus the Federal per diem 

payment amount for the case. 

In instances when the case qualifies 

for an outlier payment, we pay 80 

percent of the difference between the 

estimated cost for the case and the 

adjusted threshold amount for days 1 

through 9 of the stay (consistent with 

the median LOS for IPFs in FY 2002), 

and 60 percent of the difference for day 

10 and thereafter. The adjusted 

threshold amount is equal to the outlier 

threshold amount adjusted for wage 

area, teaching status, rural area, and the 

COLA adjustment (if applicable), plus 

the amount of the Medicare IPF 

payment for the case. We established 

the 80 percent and 60 percent loss 

sharing ratios because we were 

concerned that a single ratio established 

at 80 percent (like other Medicare PPSs) 

might provide an incentive under the 

IPF per diem payment system to 

increase LOS in order to receive 

additional payments. 

After establishing the loss sharing 

ratios, we determined the current fixed 

dollar loss threshold amount through 

payment simulations designed to 

compute a dollar loss beyond which 

payments are estimated to meet the 2 

percent outlier spending target. Each 

year when we update the IPF PPS, we 

simulate payments using the latest 

available data to compute the fixed 

dollar loss threshold so that outlier 

payments represent 2 percent of total 

estimated IPF PPS payments. 

2. Final Update to the Outlier Fixed 

Dollar Loss Threshold Amount 

In accordance with the update 

methodology described in § 412.428(d), 

we are finalizing our proposal to update 

the fixed dollar loss threshold amount 

used under the IPF PPS outlier policy. 

Based on the regression analysis and 

payment simulations used to develop 

the IPF PPS, we established a 2 percent 

outlier policy, which strikes an 

appropriate balance between protecting 

IPFs from extraordinarily costly cases 

while ensuring the adequacy of the 

Federal per diem base rate for all other 

cases that are not outlier cases. 

Our longstanding methodology for 

updating the outlier fixed dollar loss 

threshold involves using the best 

available data, which is typically the 

most recent available data. For this final 

rulemaking, the most recent available 

data are the FY 2020 claims. However, 

during FY 2020, the U.S. healthcare 

system undertook an unprecedented 

response to the PHE declared by the 

Health and Human Services Secretary 

on January 31, 2020 in response to the 

outbreak of respiratory disease caused 

by a novel (new) coronavirus that has 

been named ‘‘SARS CoV 2’’ and the 

disease it causes, which has been named 

‘‘coronavirus disease 2019’’ (abbreviated 

‘‘COVID–19’’). Therefore, as discussed 

in section VI.C.3 of the FY 2022 IPF PPS 

proposed rule (86 FR 19524 through 

195266), we considered whether the 

most recent available year of claims, FY 

2020, or the prior year, FY 2019, would 

be the best for estimating IPF PPS 

payments in FY 2021 and FY 2022. We 

compared the two years’ claims 

distributions as well as the impact 

results, and based on that analysis 

determined that the FY 2019 claims 

appeared to be the best available data at 

this time. We refer the reader to section 

VI.C.3 of the FY 2022 IPF PPS proposed 

rule (86 FR 19524 through 195266 FR) 

for a detailed discussion of that 

analysis. 

Comment: We received 2 comments 

on our analysis of the FY 2019 and FY 

2020 claims in determining the best 

available data for estimating IPF PPS 

payments in FY 2021 and FY 2022. Both 

comments were supportive of our 

proposal to use the FY 2019 claims for 

this purpose. One of these commenters 

expressed appreciation for the proposed 

reduction in the outlier fixed dollar loss 

threshold. Another commenter agreed 

with our assessment that FY 2020 

claims were heavily impacted by the 

intensity of the COVID–19 pandemic. 

Response: We appreciate these 

commenters’ support. Based on the 

revised impact analysis discussed in 

section VI.C.3 of this final rule, we 

continue to believe that the FY 2019 

claims are the best available data for 

estimating FY 2021 and FY 2022 

payments. 

Final Decision: We are finalizing as 

proposed to use the June 2020 update of 

the FY 2019 IPF claims for updating the 

outlier fixed dollar loss threshold. 

Based on an analysis of the June 2020 

update of FY 2019 IPF claims and the 

FY 2021 rate increases, we believe it is 

necessary to update the fixed dollar loss 

threshold amount to maintain an outlier 

percentage that equals 2 percent of total 

estimated IPF PPS payments. We are 

finalizing our proposal to update the IPF 

outlier threshold amount for FY 2022 

using FY 2019 claims data and the same 

methodology that we used to set the 

initial outlier threshold amount in the 

RY 2007 IPF PPS final rule (71 FR 27072 

and 27073), which is also the same 

methodology that we used to update the 

outlier threshold amounts for years 2008 

through 2021. Based on an analysis of 

these updated data, we estimate that IPF 

outlier payments as a percentage of total 

estimated payments are approximately 

1.9 percent in FY 2021. Therefore, we 

are finalizing our proposal to update the 

outlier threshold amount to $14,470 to 

maintain estimated outlier payments at 

2 percent of total estimated aggregate 

IPF payments for FY 2022. This final 

update is a decrease from the FY 2021 

threshold of $14,630. In contrast, using 

the FY 2020 claims to estimate 

payments, the final outlier fixed dollar 

loss threshold for FY 2022 would be 

$22,720, which would have been an 

increase from the FY 2021 threshold of 

$14,630. We refer the reader to section 

VI.C.3 of this final rule for a detailed 

discussion of the estimated impacts of 

the final update to the outlier fixed 

dollar loss threshold. 

We note that our use of the FY 2019 

claims to set the final outlier fixed 

dollar loss threshold for FY 2022 

deviates from what has been our 

longstanding practice of using the most 

recent available year of claims, which is 

FY 2020 data. However, we are 

finalizing this policy in a way that 

remains otherwise consistent with the 


lotter on DSK11XQN23PROD with RULES5
42624 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

1We note that the statute uses the term ‘‘rate 

year’’ (RY). However, beginning with the annual 

update of the inpatient psychiatric facility 

prospective payment system (IPF PPS) that took 

effect on July 1, 2011 (RY 2012), we aligned the IPF 

PPS update with the annual update of the ICD 

codes, effective on October 1 of each year. This 

change allowed for annual payment updates and 

the ICD coding update to occur on the same 

schedule and appear in the same Federal Register 

document, promoting administrative efficiency. To 

reflect the change to the annual payment rate 

update cycle, we revised the regulations at 42 CFR 

412.402 to specify that, beginning October 1, 2012, 

the IPF PPS RY means the 12-month period from 

October 1 through September 30, which we refer to 

as a ‘‘fiscal year’’ (FY) (76 FR 26435). Therefore, 

with respect to the IPFQR Program, the terms ‘‘rate 

year,’’ as used in the statute, and ‘‘fiscal year’’ as 

used in the regulation, both refer to the period from 

October 1 through September 30. For more 

information regarding this terminology change, we 

refer readers to section III. of the RY 2012 IPF PPS 

final rule (76 FR 26434 through 26435). 

established outlier update methodology. 

As discussed in this section and in 

section VI.C.3 of this final rule, we are 

finalizing our proposal to update the 

outlier fixed dollar loss threshold based 

on FY 2019 IPF claims in order to 

maintain the appropriate outlier 

percentage in FY 2022. We are finalizing 

our proposal to deviate from our 

longstanding practice of using the most 

recent available year of claims only 

because, and to the extent that, the 

COVID–19 PHE appears to have 

significantly impacted the FY 2020 IPF 

claims. As discussed in section VI.C.3 of 

this final rule, we have analyzed more 

recent available IPF claims data and 

continue to believe that using FY 2019 

IPF claims is appropriate for the FY 

2022 update. We intend to continue to 

analyze further data in order to better 

understand both the short-term and 

long-term effects of the COVID–19 PHE 

on IPFs. 

3. Final Update to IPF Cost-to-Charge 

Ratio Ceilings 

Under the IPF PPS, an outlier 

payment is made if an IPF’s cost for a 

stay exceeds a fixed dollar loss 

threshold amount plus the IPF PPS 

amount. In order to establish an IPF’s 

cost for a particular case, we multiply 

the IPF’s reported charges on the 

discharge bill by its overall cost-tocharge ratio (CCR). This approach to 

determining an IPF’s cost is consistent 

with the approach used under the IPPS 

and other PPSs. In the FY 2004 IPPS 

final rule (68 FR 34494), we 

implemented changes to the IPPS policy 

used to determine CCRs for IPPS 

hospitals, because we became aware 

that payment vulnerabilities resulted in 

inappropriate outlier payments. Under 

the IPPS, we established a statistical 

measure of accuracy for CCRs to ensure 

that aberrant CCR data did not result in 

inappropriate outlier payments. 

As we indicated in the November 

2004 IPF PPS final rule (69 FR 66961), 

we believe that the IPF outlier policy is 

susceptible to the same payment 

vulnerabilities as the IPPS; therefore, we 

adopted a method to ensure the 

statistical accuracy of CCRs under the 

IPF PPS. Specifically, we adopted the 

following procedure in the November 

2004 IPF PPS final rule: 

• Calculated two national ceilings, 

one for IPFs located in rural areas and 

one for IPFs located in urban areas. 

• Computed the ceilings by first 

calculating the national average and the 

standard deviation of the CCR for both 

urban and rural IPFs using the most 

recent CCRs entered in the most recent 

Provider Specific File (PSF) available. 

For FY 2022, we are finalizing our 

proposal to continue to follow this 

methodology. 

To determine the rural and urban 

ceilings, we multiplied each of the 

standard deviations by 3 and added the 

result to the appropriate national CCR 

average (either rural or urban). The 

upper threshold CCR for IPFs in FY 

2022 is 2.0261 for rural IPFs, and 1.6879 

for urban IPFs, based on CBSA-based 

geographic designations. If an IPF’s CCR 

is above the applicable ceiling, the ratio 

is considered statistically inaccurate, 

and we assign the appropriate national 

(either rural or urban) median CCR to 

the IPF. 

We apply the national median CCRs 

to the following situations: 

• New IPFs that have not yet 

submitted their first Medicare cost 

report. We continue to use these 

national median CCRs until the facility’s 

actual CCR can be computed using the 

first tentatively or final settled cost 

report. 

• IPFs whose overall CCR is in excess 

of three standard deviations above the 

corresponding national geometric mean 

(that is, above the ceiling). 

• Other IPFs for which the MAC 

obtains inaccurate or incomplete data 

with which to calculate a CCR. 

We are finalizing our proposal to 

continue to update the FY 2022 national 

median and ceiling CCRs for urban and 

rural IPFs based on the CCRs entered in 

the latest available IPF PPS PSF. 

Specifically, for FY 2022, to be used in 

each of the three situations listed 

previously, using the most recent CCRs 

entered in the CY 2021 PSF, we provide 

an estimated national median CCR of 

0.5720 for rural IPFs and a national 

median CCR of 0.4200 for urban IPFs. 

These calculations are based on the 

IPF’s location (either urban or rural) 

using the CBSA-based geographic 

designations. A complete discussion 

regarding the national median CCRs 

appears in the November 2004 IPF PPS 

final rule (69 FR 66961 through 66964). 

IV. Inpatient Psychiatric Facilities 

Quality Reporting (IPFQR) Program 

A. Background and Statutory Authority 

We refer readers to the FY 2019 IPF 

PPS final rule (83 FR 38589) for a 

discussion of the background and 

statutory authority 1 of the IPFQR 

Program. 

B. Covered Entities 

In the FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53645), we established that 

the IPFQR Program’s quality reporting 

requirements cover those psychiatric 

hospitals and psychiatric units paid 

under Medicare’s IPF PPS 

(§ 412.404(b)). Generally, psychiatric 

hospitals and psychiatric units within 

acute care and critical access hospitals 

that treat Medicare patients are paid 

under the IPF PPS. Consistent with 

previous regulations, we continue to use 

the terms ‘‘facility’’ or IPF to refer to 

both inpatient psychiatric hospitals and 

psychiatric units. This usage follows the 

terminology in our IPF PPS regulations 

at § 412.402. For more information on 

covered entities, we refer readers to the 

FY 2013 IPPS/LTCH PPS final rule (77 

FR 53645). 

C. Previously Finalized Measures and 

Administrative Procedures 

The current IPFQR Program includes 

14 measures. For more information on 

these measures, we refer readers to 

Table 5 of this final rule and the 

following final rules: 

• The FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53646 through 53652); 

• The FY 2014 IPPS/LTCH PPS final 

rule (78 FR 50889 through 50897); 

• The FY 2015 IPF PPS final rule (79 

FR 45963 through 45975); 

• The FY 2016 IPF PPS final rule (80 

FR 46695 through 46714); 

• The FY 2017 IPPS/LTCH PPS final 

rule (81 FR 57238 through 57247); 

• The FY 2019 IPF PPS final rule (83 

FR 38590 through 38606); and 

• The FY 2020 IPF PPS final rule (84 

FR 38459 through 38467). 

For more information on previously 

adopted procedural requirements, we 

refer readers to the following rules: 

• The FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53653 through 53660); 

• The FY 2014 IPPS/LTCH PPS final 

rule (78 FR 50897 through 50903); 

• The FY 2015 IPF PPS final rule (79 

FR 45975 through 45978); 

• The FY 2016 IPF PPS final rule (80 

FR 46715 through 46719); 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42625 

2 Joynt KE, Orav E, Jha AK. Thirty-Day 

Readmission Rates for Medicare Beneficiaries by 

Race and Site of Care. JAMA. 2011;305(7):675–681. 3Lindenauer PK, Lagu T, Rothberg MB, et al. 

Income Inequality and 30 Day Outcomes After 

Acute Myocardial Infarction, Heart Failure, and 

Pneumonia: Retrospective Cohort Study. British 

Medical Journal. 2013;346. 4Trivedi AN, Nsa W, Hausmann LRM, et al. 

Quality and Equity of Care in U.S. Hospitals. New 

England Journal of Medicine. 2014;371(24):2298– 

2308. 

5Polyakova, M., et al. Racial Disparities In Excess 

All-Cause Mortality During The Early COVID–19 

Pandemic Varied Substantially Across States. 

Health Affairs. 2021; 40(2): 307–316. 

6Rural Health Research Gateway. Rural 

Communities: Age, Income, and Health Status. 

Rural Health Research Recap. November 2018. 

7https://www.minorityhealth.hhs.gov/assets/ 

PDF/Update_HHS_Disparities_Dept-FY2020.pdf. 

8www.cdc.gov/mmwr/volumes/70/wr/ 

mm7005a1.htm. 

9Poteat TC, Reisner SL, Miller M, Wirtz AL. 

COVID–19 Vulnerability of Transgender Women 

With and Without HIV Infection in the Eastern and 

Southern U.S. Preprint. medRxiv. 

2020;2020.07.21.20159327. Published 2020 Jul 24. 

doi:10.1101/2020.07.21.20159327. 

10Martino, SC, Elliott, MN, Dembosky, JW, 

Hambarsoomian, K, Burkhart, Q, Klein, DJ, Gildner, 

J, and Haviland, AM. Racial, Ethnic, and Gender 

Disparities in Health Care in Medicare Advantage. 

Baltimore, MD: CMS Office of Minority Health. 

2020. 

11 Guide to Reducing Disparities in Readmissions. 

CMS Office of Minority Health. Revised August 

2018. Available at: https://www.cms.gov/AboutCMS/Agency-Information/OMH/Downloads/OMH_

Readmissions_Guide.pdf. 

12Singh JA, Lu X, Rosenthal GE, Ibrahim S, Cram 

P. Racial disparities in knee and hip total joint 

arthroplasty: an 18-year analysis of national 

Medicare data. Ann Rheum Dis. 2014 

Dec;73(12):2107–15. 

13Rivera-Hernandez M, Rahman M, Mor V, 

Trivedi AN. Racial Disparities in Readmission Rates 

among Patients Discharged to Skilled Nursing 

Facilities. J Am Geriatr Soc. 2019 Aug;67(8):1672– 

1679. 

14 Joynt KE, Orav E, Jha AK. Thirty-Day 

Readmission Rates for Medicare Beneficiaries by 

Race and Site of Care. JAMA. 2011;305(7):675–681. 

15Tsai TC, Orav EJ, Joynt KE. Disparities in 

surgical 30-day readmission rates for Medicare 

beneficiaries by race and site of care. Ann Surg. Jun 

2014;259(6):1086–1090. 

16Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha 

AK. Readmission rates for Hispanic Medicare 

beneficiaries with heart failure and acute 

myocardial infarction. Am Heart J. Aug 

2011;162(2):254–261 e253. 

17Centers for Medicare and Medicaid Services. 

Medicare Hospital Quality Chartbook: Performance 

Report on Outcome Measures; 2014. 

18 Guide to Reducing Disparities in Readmissions. 

CMS Office of Minority Health. Revised August 

2018. Available at: https://www.cms.gov/AboutCMS/Agency-Information/OMH/Downloads/OMH_

Readmissions_Guide.pdf. 

19Prieto-Centurion V, Gussin HA, Rolle AJ, 

Krishnan JA. Chronic obstructive pulmonary 

disease readmissions at minority-serving 

institutions. Ann Am Thorac Soc. Dec 

2013;10(6):680–684. 

20 Joynt KE, Orav E, Jha AK. Thirty-Day 

Readmission Rates for Medicare Beneficiaries by 

Race and Site of Care. JAMA. 2011;305(7):675–681. 

21HHS. Heart disease and African Americans. 

(March 29, 2021). https://www.minorityhealth.hhs.

gov/omh/browse.aspx?lvl=4&lvlid=19. 

22https://www.cms.gov/files/document/medicarecovid-19-data-snapshot-fact-sheet.pdf. 

23Ochieng N, Cubanski J, Neuman T, Artiga S, 

and Damico A. Racial and Ethnic Health Inequities 

and Medicare. Kaiser Family Foundation. February 

2021. Available at: https://www.kff.org/medicare/ 

report/racial-and-ethnic-health-inequities-andmedicare/. 

24https://www.cdc.gov/coronavirus/2019-ncov/ 

community/health-equity/race-ethnicity.html. 

25https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/ 

QualityInitiativesGenInfo/Downloads/CMS-QualityStrategy.pdf. 

• The FY 2017 IPPS/LTCH PPS final 

rule (81 FR 57248 through 57249); 

• The FY 2018 IPPS/LTCH PPS final 

rule (82 FR 38471 through 38474); 

• The FY 2019 IPF PPS final rule (83 

FR 38606 through 38608); and 

• The FY 2020 IPF PPS final rule (84 

FR 38467 through 38468). 

D. Closing the Health Equity Gap in 

CMS Quality Programs—Request for 

Information (RFI) 

Persistent inequities in health care 

outcomes exist in the U.S., including 

among Medicare patients. In recognition 

of persistent health disparities and the 

importance of closing the health equity 

gap, we requested information on 

revising several CMS programs to make 

reporting of health disparities based on 

social risk factors and race and ethnicity 

more comprehensive and actionable for 

facilities, providers, and patients. The 

RFI that was included in the proposed 

rule is part of an ongoing effort across 

CMS to evaluate appropriate initiatives 

to reduce health disparities. Feedback 

will be used to inform the creation of a 

future, comprehensive, RFI focused on 

closing the health equity gap in CMS 

programs and policies. 

The RFI contained four parts: 

• Background: This section provided 

information describing our commitment 

to health equity, and existing initiatives 

with an emphasis on reducing health 

disparities. 

• Current CMS Disparity Methods: 

This section described the methods, 

measures, and indicators of social risk 

currently used with the CMS Disparity 

Methods. 

• Future potential stratification of 

quality measure results: This section 

described four potential future 

expansions of the CMS Disparity 

Methods, including (1) Stratification of 

Quality Measure Results—Dual 

Eligibility; (2) Stratification of Quality 

Measure Results—Race and Ethnicity; 

(3) Improving Demographic Data 

Collection; and (4) Potential Creation of 

a Facility Equity Score to Synthesize 

Results Across Multiple Social Risk 

Factors. 

• Solicitation of public comment: 

This section specified 12 requests for 

feedback on these topics. We reviewed 

feedback on these topics and note our 

intention for an additional RFI or 

rulemaking on this topic in the future. 

1. Background 

Significant and persistent inequities 

in health care outcomes exist in the U.S. 

Belonging to a racial or ethnic minority 

group; living with a disability; being a 

member of the lesbian, gay, bisexual, 

transgender, and queer (LGBTQ+) 

community; living in a rural area; or 

being near or below the poverty level, is 

often associated with worse health 

outcomes.23456789 Such disparities in 

health outcomes are the result of 

number of factors, but importantly for 

CMS programs, although not the sole 

determinant, poor access and provision 

of lower quality health care contribute 

to health disparities. For instance, 

numerous studies have shown that 

among Medicare beneficiaries, racial 

and ethnic minority individuals often 

receive lower quality of care, report 

lower experiences of care, and 

experience more frequent hospital 

readmissions and operative 

complications.10 11 12 13 14 15 Readmission 

rates for common conditions in the 

Hospital Readmissions Reduction 

Program are higher for Black Medicare 

beneficiaries and higher for Hispanic 

Medicare beneficiaries with Congestive 

Heart Failure and Acute Myocardial 

Infarction.16 17 18 19 20 Studies have also 

shown that African Americans are 

significantly more likely than white 

Americans to die prematurely from 

heart disease, and stroke.21 The COVID– 

19 pandemic has further illustrated 

many of these longstanding health 

inequities with higher rates of infection, 

hospitalization, and mortality among 

Black, Latino, and Indigenous and 

Native American persons relative to 

White persons.22 23 As noted by the 

Centers for Disease Control ‘‘longstanding systemic health and social 

inequities have put many people from 

racial and ethnic minority groups at 

increased risk of getting sick and dying 

from COVID–19.’’ 24 One important 

strategy for addressing these important 

inequities is improving data collection 

to allow for better measurement and 

reporting on equity across our programs 

and policies. 

We are committed to achieving equity 

in health care outcomes for our 

beneficiaries by supporting providers in 

quality improvement activities to reduce 

health inequities, enabling them to 

make more informed decisions, and 

promoting provider accountability for 

health care disparities.25 For the 

purposes of this final rule, we are using 

a definition of equity established in 


lotter on DSK11XQN23PROD with RULES5
42626 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

26https://www.federalregister.gov/documents/ 

2021/01/25/2021-01753/advancing-racial-equityand-support-for-underserved-communities-throughthe-Federal-government. 

27Centers for Medicare and Medicaid Services 

Office of Minority Health. The CMS Equity Plan for 

Improving Quality in Medicare. 2015. https://

www.cms.gov/About-CMS/Agency-Information/ 

OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_

090615.pdf. 

28Centers for Medicare and Medicaid Services 

Office of Minority Health. The CMS Equity Plan for 

Improving Quality in Medicare. 2015. https://

www.cms.gov/About-CMS/Agency-Information/ 

OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_

090615.pdf. 

29Centers for Medicare Services. CMS Quality 

Strategy. 2016. https://www.cms.gov/Medicare/ 

Quality-Initiatives-Patient-Assessment-Instruments/ 

QualityInitiativesGenInfo/Downloads/CMS-QualityStrategy.pdf. 

30https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/

QualityInitiativesGenInfo/MMF/General-info-SubPage. 

31https://www.cms.gov/About-CMS/AgencyInformation/OMH/OMH-Mapping-MedicareDisparities. 

32https://www.cms.gov/About-CMS/AgencyInformation/OMH/research-and-data/statistics-anddata/stratified-reporting. 

33Centers for Medicare and Medicaid Services. 

Rural-Urban Disparities in Health Care in Medicare. 

2019. https://www.cms.gov/About-CMS/AgencyInformation/OMH/Downloads/Rural-UrbanDisparities-in-Health-Care-in-Medicare-Report.pdf. 

34 Guide to Reducing Disparities in Readmissions. 

CMS Office of Minority Health. Revised August 

2018. Available at: https://www.cms.gov/AboutCMS/Agency-Information/OMH/Downloads/OMH_

Readmissions_Guide.pdf. 

35National Academies of Sciences, Engineering, 

and Medicine. 2016. Accounting for Social Risk 

Factors in Medicare Payment: Identifying Social 

Risk Factors. Washington, DC: The National 

Academies Press. https://doi.org/10.17226/21858. 

36https://aspe.hhs.gov/pdf-report/reportcongress-social-risk-factors-and-performanceunder-medicares-value-based-purchasingprograms. 

37https://aspe.hhs.gov/pdf-report/reportcongress-social-risk-factors-and-performanceunder-medicares-value-based-purchasingprograms. 

Executive Order 13985, as ‘‘the 

consistent and systematic fair, just, and 

impartial treatment of all individuals, 

including individuals who belong to 

underserved communities that have 

been denied such treatment, such as 

Black, Latino, and Indigenous and 

Native American persons, Asian 

Americans and Pacific Islanders and 

other persons of color; members of 

religious minorities; lesbian, gay, 

bisexual, transgender, and queer 

(LGBTQ+) persons; persons with 

disabilities; persons who live in rural 

areas; and persons otherwise adversely 

affected by persistent poverty or 

inequality.’’ 26 We note that this 

definition was recently established by 

the current administration, and provides 

a useful, common definition for equity 

across different areas of government, 

although numerous other definitions of 

equity exist. 

Our ongoing commitment to closing 

the equity gap in CMS quality programs 

is demonstrated by a portfolio of 

programs aimed at making information 

on the quality of health care providers 

and services, including disparities, more 

transparent to consumers and providers. 

The CMS Equity Plan for Improving 

Quality in Medicare outlines a path to 

equity which aims to support Quality 

Improvement Networks and Quality 

Improvement Organizations (QIN–QIOs) 

in their efforts to engage with and assist 

providers that care for vulnerable 

populations; Federal, state, local, and 

tribal organizations; providers; 

researchers; policymakers; beneficiaries 

and their families; and other 

stakeholders in activities to achieve 

health equity.27 The CMS Equity Plan 

for Improving Quality in Medicare 

focuses on three core priority areas 

which inform our policies and 

programs: (1) Increasing understanding 

and awareness of health disparities; (2) 

developing and disseminating solutions 

to achieve health equity; and (3) 

implementing sustainable actions to 

achieve health equity.28 The CMS 

Quality Strategy 29 and Meaningful 

Measures Framework 30 include 

elimination of racial and ethnic 

disparities as a central principle. Our 

efforts aimed at closing the health 

equity gap to date have included 

providing transparency about health 

disparities, supporting providers with 

evidence-informed solutions to achieve 

health equity, and reporting to providers 

on gaps in quality through the following 

reports and programs: 

• The CMS Mapping Medicare 

Disparities Tool, which is an interactive 

map that identifies areas of disparities 

and a starting point to understand and 

investigate geographical, racial and 

ethnic differences in health outcomes 

for Medicare patients.31

• The Racial, Ethnic, and Gender 

Disparities in Health Care in Medicare 

Advantage Stratified Report, which 

highlights racial and ethnic differences 

in health care experiences and clinical 

care, compares quality of care for 

women and men, and looks at racial and 

ethnic differences in quality of care 

among women and men separately for 

Medicare Advantage plans.32

• The Rural-Urban Disparities in 

Health Care in Medicare Report, which 

details rural-urban differences in health 

care experiences and clinical care.33

• The Standardized Patient 

Assessment Data Elements for certain 

post-acute care Quality Reporting 

Programs, which now includes data 

reporting for race and ethnicity and 

preferred language, in addition to 

screening questions for social needs (84 

FR 42536 through 42588). 

• The CMS Innovation Center’s 

Accountable Health Communities 

Model, which include standardized data 

collection of health-related social needs 

data. 

• The Guide to Reducing Disparities 

which provides an overview of key 

issues related to disparities in 

readmissions and reviews sets of 

activities that can help hospital leaders 

reduce readmissions in diverse 

populations.34

• The CMS Disparity Methods, which 

provide hospital-level confidential 

results stratified by dual eligibility for 

condition-specific readmission 

measures currently included in the 

Hospital Readmission Reduction 

Program (84 FR 42496 through 42500). 

These programs are informed by 

reports by the National Academies of 

Science, Engineering and Medicine 

(NASEM) 35 and the Office of the 

Assistant Secretary for Planning and 

Evaluation (ASPE) 36 which have 

examined the influence of social risk 

factors on several of our quality 

programs. In this RFI, we addressed 

only the seventh initiative listed, the 

CMS Disparity Methods, which we have 

implemented for measures in the 

Hospital Readmissions Reduction 

Program and are considering in other 

programs, including the IPFQR Program. 

We discussed the implementation of 

these methods to date and present 

considerations for continuing to 

improve and expand these methods to 

provide providers and ultimately 

consumers with actionable information 

on disparities in health care quality to 

support efforts at closing the equity gap. 

2. Current CMS Disparity Methods 

We first sought public comment on 

potential confidential and public 

reporting of IPFQR program measure 

data stratified by social risk factors in 

the FY 2018 IPPS/LTCH PPS proposed 

rule (82 FR 20121). We initially focused 

on stratification by dual eligibility, 

which is consistent with 

recommendations from ASPE’s First 

Report to Congress which was required 

by the Improving Medicare Post-Acute 

Care Transformation (IMPACT) Act of 

2014 (Pub. L. 113–185).37 This report 

found that in the context of value-based 

purchasing (VBP) programs, dual 

eligibility was among the most powerful 

predictors of poor health outcomes 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42627 

38Centers for Medicare Services. CMS Quality 

Strategy. 2016. https://www.cms.gov/Medicare/ 

Quality-Initiatives-Patient-Assessment-Instruments/ 

QualityInitiativesGenInfo/Downloads/CMS-QualityStrategy.pdf. 

39National Academies of Sciences, Engineering, 

and Medicine. 2016. Accounting for Social Risk 

Factors in Medicare Payment: Identifying Social 

Risk Factors. Washington, DC: The National 

Academies Press. https://doi.org/10.17226/21858. 

40https://aspe.hhs.gov/pdf-report/reportcongress-social-risk-factors-and-performanceunder-medicares-value-based-purchasingprograms. 

41https://aspe.hhs.gov/basic-report/transitionscare-and-service-use-among-medicare-beneficiariesinpatient-psychiatric-facilities-issue-brief. 

42https://www.cms.gov/Medicare-MedicaidCoordination/Medicare-and-MedicaidCoordination/Medicare-Medicaid-CoordinationOffice/DataStatisticalResources/Downloads/ 

MedicareMedicaidDualEnrollmentEverEnrolled

TrendsDataBrief2006-2018.pdf. 

among those social risk factors that 

ASPE examined and tested. 

In the FY 2018 IPPS/LTCH PPS final 

rule we also solicited feedback on two 

potential methods for illuminating 

differences in outcomes rates among 

patient groups within a provider’s 

patient population that would also 

allow for a comparison of those 

differences, or disparities, across 

providers for the Hospital IQR Program 

(82 FR 38403 through 38409). The first 

method (the Within-Hospital disparity 

method) promotes quality improvement 

by calculating differences in outcome 

rates among patient groups within a 

hospital while accounting for their 

clinical risk factors. This method also 

allows for a comparison of the 

magnitude of disparity across hospitals, 

permitting hospitals to assess how well 

they are closing disparity gaps 

compared to other hospitals. The second 

methodological approach (the AcrossHospital method) is complementary and 

assesses hospitals’ outcome rates for 

dual-eligible patients only, across 

hospitals, allowing for a comparison 

among hospitals on their performance 

caring for their patients with social risk 

factors. In the FY 2018 IPPS/LTCH PPS 

proposed rule under the IPFQR Program 

(82 FR 20121), we also specifically 

solicited feedback on which social risk 

factors provide the most valuable 

information to stakeholders. Overall, 

comments supported the use of dual 

eligibility as a proxy for social risk, 

although commenters also suggested 

investigation of additional social risk 

factors, and we continue to consider 

which risk factors provide the most 

valuable information to stakeholders. 

Concurrent with our comment 

solicitation on stratification in the 

IPFQR Program, we have considered 

methods for stratifying measure results 

for other quality reporting programs. For 

example, in the FY 2019 IPPS/LTCH 

PPS final rule (82 FR 41597 through 

41601), we finalized plans to provide 

confidential hospital-specific reports 

(HSRs) containing stratified results of 

the Pneumonia Readmission (NQF 

#0506) and Pneumonia Mortality (NQF 

#0468) measures including both the 

Across-Hospital Disparity Method and 

the Within-Hospital Disparity Method 

(disparity methods), stratified by dual 

eligibility. In the FY 2019 IPPS/LTCH 

PPS final rule (83 FR 41554 through 

41556), we also removed six condition/ 

procedure specific readmissions 

measures, including the Pneumonia 

Readmission measure (NQF #0506) and 

five mortality measures, including the 

Pneumonia Mortality measure (NQF 

#0468) (83 FR 41556 through 41558) 

from the Hospital IQR Program. 

However, the Pneumonia Readmission 

(NQF #0506) and the other condition/ 

procedure readmissions measures 

remained in the Hospital Readmissions 

Reduction Program. In 2019, we 

provided hospitals with results of the 

Pneumonia Readmission measure 

(NQF#0506) stratified using dual 

eligibility. We provided this information 

in annual confidential HSRs for claimsbased measures. 

We then, in the FY 2020 IPPS/LTCH 

PPS Final Rule (84 FR 42388 through 

42390), finalized the proposal to 

provide confidential hospital specific 

reports (HSRs) containing data stratified 

by dual-eligible status for all six 

readmission measures included in the 

Hospital Readmission Reduction 

Program. 

3. Potential Expansion of the CMS 

Disparity Methods 

We are committed to advancing 

health equity by improving data 

collection to better measure and analyze 

disparities across programs and 

policies.38 As we previously noted, we 

have been considering, among other 

things, expanding our efforts to provide 

stratified data for additional social risk 

factors and measures, optimizing the 

ease-of-use of the results, enhancing 

public transparency of equity results, 

and building towards provider 

accountability for health equity. We 

sought public comment on the potential 

stratification of quality measures in the 

IPFQR Program across two social risk 

factors: Dual eligibility and race/ 

ethnicity. 

a. Stratification of Quality Measure 

Results—Dual Eligibility 

As described previously in this 

section, landmark reports by the 

National Academies of Science, 

Engineering and Medicine (NASEM) 39

and the Office of the Assistant Secretary 

for Planning and Evaluation (ASPE),40

which have examined the influence of 

social risk factors on several of our 

quality programs, have shown that in 

the context of value-based purchasing 

(VBP) programs, dual eligibility, as an 

indicator of social risk, is a powerful 

predictor of poor health outcomes. We 

noted that the patient population of IPFs 

has a higher percentage of dually 

eligible patients than the general 

Medicare population. Specifically, over 

half (56 percent) of Medicare patients in 

IPFs are dually eligible 41 while 

approximately 20 percent of all 

Medicare patients are dually eligible.42

We are considering stratification of 

quality measure results in the IPFQR 

Program and are considering which 

measures would be most appropriate for 

stratification and if dual eligibility 

would be a meaningful social risk factor 

for stratification. 

For the IPFQR Program, we would 

consider disparity reporting using two 

disparity methods derived from the 

Within-Hospital and Across-Hospital 

methods, described in section IV.D.2 of 

this final rule. The first method (based 

on the Within-Facility disparity 

method) would aim to promote quality 

improvement by calculating differences 

in outcome rates between dual and nondual eligible patient groups within a 

facility while accounting for their 

clinical risk factors. This method would 

allow for a comparison of those 

differences, or disparities, across 

facilities, so facilities could assess how 

well they are closing disparity gaps 

compared to other facilities. The second 

approach (based on the Across-Facility 

method) would be complementary and 

assesses facilities’ outcome rates for 

subgroups of patients, such as dual 

eligible patients, across facilities, 

allowing for a comparison among 

facilities on their performance caring for 

their patients with social risk factors. 

b. Stratification of Quality Measure 

Results—Race and Ethnicity 

The Administration’s Executive Order 

on Advancing Racial Equity and 

Support for Underserved Communities 

Through the Federal Government 

directs agencies to assess potential 

barriers that underserved communities 

and individuals may face to enrollment 

in and access to benefits and services in 

Federal Programs. As summarized in 

section IV.D of this final rule, studies 

have shown that among Medicare 

beneficiaries, racial and ethnic minority 

persons often experience worse health 

outcomes, including more frequent 

hospital readmissions and operative 


lotter on DSK11XQN23PROD with RULES5
42628 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

43Executive Office of the President Office of 

Management and Budget, Office of Information and 

Regulatory Affairs. Revisions to the standards for 

the classification of Federal data on race and 

ethnicity. Vol 62. Federal Register. 1997:58782– 

58790 

44https://www.census.gov/topics/population/ 

hispanic-origin/about.html. 

45https://phinvads.cdc.gov/vads/ 

ViewValueSet.action?id=67D34BBC-617F-DD11- 

B38D-00188B398520. 

46ONC criteria for certified health IT products: 

https://www.healthit.gov/isa/representing-patientrace-and-ethnicity. 

47Eicheldinger, C., & Bonito, A. (2008). More 

accurate racial and ethnic codes for Medicare 

administrative data. Health Care Financing Review, 

29(3), 27–42. 

48Filice CE, Joynt KE. Examining Race and 

Ethnicity Information in Medicare Administrative 

Data. Med Care. 2017;55(12):e170–e176. 

doi:10.1097/MLR.0000000000000608. 

49Eicheldinger, C., & Bonito, A. (2008). More 

accurate racial and ethnic codes for Medicare 

administrative data. Health Care Financing Review, 

29(3), 27–42. 

50Centers for Medicare and Medicaid Services. 

Building an Organizational Response to Health 

Disparities Inventory of Resources for Standardized 

Demographic and Language Data Collection. 2020. 

https://www.cms.gov/About-CMS/AgencyInformation/OMH/Downloads/Data-CollectionResources.pdf. 

51Centers for Medicare and Medicaid Services. 

Building an Organizational Response to Health 

Disparities Inventory of Resources for Standardized 

Demographic and Language Data Collection. 2020. 

https://www.cms.gov/About-CMS/AgencyInformation/OMH/Downloads/Data-CollectionResources.pdf. 

52https://pubmed.ncbi.nlm.nih.gov/18567241/, 

https://pubmed.ncbi.nlm.nih.gov/30506674/, 

Eicheldinger C, Bonito A. More accurate racial and 

ethnic codes for Medicare administrative data. 

Health Care Finance Rev. 2008;29(3):27–42. Haas A, 

Elliott MN, Dembosky JW, et al. Imputation of race/ 

ethnicity to enable measurement of HEDIS 

performance by race/ethnicity. Health Serv Res. 

2019;54(1):13–23. doi:10.1111/1475–6773.13099. 

53https://aspe.hhs.gov/pdf-report/second-impactreport-to-congress. 

complications. An important part of 

identifying and addressing inequities in 

health care is improving data collection 

to allow us to better measure and report 

on equity across our programs and 

policies. We are considering 

stratification of quality measure results 

in the IPFQR Program by race and 

ethnicity and are considering which 

measures would be most appropriate for 

stratification. 

As outlined in the 1997 Office of 

Management and Budget (OMB) 

Revisions to the Standards for the 

Collection of Federal Data on Race and 

Ethnicity, the racial and ethnic 

categories, which may be used for 

reporting the disparity methods are 

considered to be social and cultural, not 

biological or genetic.43 The 1997 OMB 

Standard lists five minimum categories 

of race: (1) American Indian or Alaska 

Native; (2) Asian; (3) Black or African 

American; (4) Native Hawaiian or Other 

Pacific Islander; (5) and White. In the 

OMB standards, Hispanic or Latino is 

the only ethnicity category included, 

and since race and ethnicity are two 

separate and distinct concepts, persons 

who report themselves as Hispanic or 

Latino can be of any race.44 Another 

example, the ‘‘Race & Ethnicity—CDC’’ 

code system in Public Health 

Information Network (PHIN) Vocabulary 

Access and Distribution System 

(VADS) 45 permits a much more granular 

structured recording of a patient’s race 

and ethnicity with its inclusion of over 

900 concepts for race and ethnicity. The 

recording and exchange of patient race 

and ethnicity at such a granular level 

can facilitate the accurate identification 

and analysis of health disparities based 

on race and ethnicity. Further, the 

‘‘Race & Ethnicity—CDC’’ code system 

has a hierarchy that rolls up to the OMB 

minimum categories for race and 

ethnicity and, thus, supports 

aggregation and reporting using the 

OMB standard. ONC includes both the 

CDC and OMB standards in its criterion 

for certified health IT products.46 For 

race and ethnicity, a certified health IT 

product must be able to express both 

detailed races and ethnicities using any 

of the 900 plus concepts in the ‘‘Race & 

Ethnicity—CDC’’ code system in the 

PHIN VADS, as well as aggregate each 

one of a patient’s races and ethnicities 

to the categories in the OMB standard 

for race and ethnicity. This approach 

can reduce burden on providers 

recording demographics using certified 

products. 

Self-reported race and ethnicity data 

remain the gold standard for classifying 

an individual according to race or 

ethnicity. However, CMS does not 

consistently collect self-reported race 

and ethnicity for the Medicare program, 

but instead gets the data from the Social 

Security Administration (SSA) and the 

data accuracy and comprehensiveness 

have proven challenging despite 

capabilities in the marketplace via 

certified health IT products. Historical 

inaccuracies in Federal data systems 

and limited collection classifications 

have contributed to the limited quality 

of race and ethnicity information in 

Medicare’s administrative data 

systems.47 In recent decades, to address 

these data quality issues, we have 

undertaken numerous initiatives, 

including updating data taxonomies and 

conducting direct mailings to some 

beneficiaries to enable more 

comprehensive race and ethnic 

identification.48 49 Despite those efforts, 

studies reveal varying data accuracy in 

identification of racial and ethnic 

groups in Medicare administrative data, 

with higher sensitivity for correctly 

identifying White and Black 

individuals, and lower sensitivity for 

correctly identifying individuals of 

Hispanic ethnicity or of Asian/Pacific 

Islander and American Indian/Alaskan 

Native race.50 Incorrectly classified race 

or ethnicity may result in 

overestimation or underestimation in 

the quality of care received by certain 

groups of beneficiaries. 

We continue to work with Federal 

and private partners to better collect and 

leverage data on social risk to improve 

our understanding of how these factors 

can be better measured in order to close 

the health equity gap. Among other 

things, we have developed an Inventory 

of Resources for Standardized 

Demographic and Language Data 

Collection 51 and supported collection 

of specialized International 

Classification of Disease, 10th Revision, 

Clinical Modification (ICD–10–CM) 

codes for describing the socioeconomic, 

cultural, and environmental 

determinants of health, and sponsored 

several initiatives to statistically 

estimate race and ethnicity information 

when it is absent.52 The Office of the 

National Coordinator for Health 

Information Technology (ONC) included 

social, psychological, and behavioral 

standards in the 2015 Edition health 

information technology (IT) certification 

criteria (2015 Edition), providing 

interoperability standards (LOINC 

(Logical Observation Identifiers Names 

and Codes) and SNOMED CT 

(Systematized Nomenclature of 

Medicine—Clinical Terms)) for financial 

strain, education, social connection and 

isolation, and others. Additional 

stakeholder efforts underway to expand 

capabilities to capture additional social 

determinants of health data elements 

include the Gravity Project to identify 

and harmonize social risk factor data for 

interoperable electronic health 

information exchange for EHR fields, as 

well as proposals to expand the ICD–10 

(International Classification of Diseases, 

Tenth Revision) Z codes, the 

alphanumeric codes used worldwide to 

represent diagnoses.53

While development of sustainable and 

consistent programs to collect data on 

social determinants of health can be 

considerable undertakings, we recognize 

that another method to identify better 

race and ethnicity data is needed in the 

short term to address the need for 

reporting on health equity. In working 

with our contractors, two algorithms 

have been developed to indirectly 

estimate the race and ethnicity of 

Medicare beneficiaries (as described 

further in the following paragraphs). We 

feel that using indirect estimation can 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42629 

54 IOM. 2009. Race, Ethnicity, and Language Data: 

Standardization for Health Care Quality 

Improvement. Washington, DC: The National 

Academies Press. 

55 IOM. 2009. Race, Ethnicity, and Language Data: 

Standardization for Health Care Quality 

Improvement. Washington, DC: The National 

Academies Press. 

56Bonito AJ, Bann C, Eicheldinger C, Carpenter 

L. Creation of New Race-Ethnicity Codes and 

Socioeconomic Status (SES) Indicators for Medicare 

Beneficiaries. Final Report, Sub-Task 2. (Prepared 

by RTI International for the Centers for Medicare 

and Medicaid Services through an interagency 

agreement with the Agency for Healthcare Research 

and Policy, under Contract No. 500–00–0024, Task 

No. 21) AHRQ Publication No. 08–0029–EF. 

Rockville, MD, Agency for Healthcare Research and 

Quality. January 2008. 

57Haas, A., Elliott, M. et al (2018). Imputation of 

race/ethnicity to enable measurement of HEDIS 

performance by race/ethnicity. Health Services 

Research, 54:13–23. 

58The Office of Minority Health (2020). Racial, 

Ethnic, and Gender Disparities in Health Care in 

Medicare Advantage, The Centers for Medicare and 

Medicaid Services, (pg vii). https://www.cms.gov/ 

About-CMS/Agency-Information/OMH/researchand-data/statistics-and-data/stratified-reporting. 

59MBISG 2.1 validation results performed under 

contract #GS–10F–0012Y/HHSM–500–2016– 

00097G). Pending public release of the 2021 Part C 

and D Performance Data Stratified by Race, 

Ethnicity, and Gender Report, available at: https:// 

www.cms.gov/About-CMS/Agency-Information/ 

OMH/research-and-data/statistics-and-data/ 

stratified-reporting. 

60Haas, A., Elliott, M. et al (2018). Imputation of 

race/ethnicity to enable measurement of HEDIS 

performance by race/ethnicity. Health Services 

Research, 54:13–23 and Bonito AJ, Bann C, 

Eicheldinger C, Carpenter L. Creation of New RaceEthnicity Codes and Socioeconomic Status (SES) 

Indicators for Medicare Beneficiaries. Final Report, 

Sub-Task 2. (Prepared by RTI International for the 

Centers for Medicare and Medicaid Services 

through an interagency agreement with the Agency 

for Healthcare Research and Policy, under Contract 

No. 500–00–0024, Task No. 21) AHRQ Publication 

No. 08–0029–EF. Rockville, MD, Agency for 

Healthcare Research and Quality. January 2008. 

61The Centers for Medicare & Medicaid Services. 

CMS Quality Strategy. 2016. https://www.cms.gov/ 

Medicare/Quality-Initiatives-Patient-AssessmentInstruments/QualityInitiativesGenInfo/Downloads/ 

CMS-Quality-Strategy.pdf. 

62The Office of the National Coordinator for 

Health Information Technology. United State Core 

Data for Interoperability Draft Version 2. 2021. 

https://www.healthit.gov/isa/sites/isa/files/2021-01/ 

Draft-USCDI-Version-2-January-2021-Final.pdf. 

help to overcome the current limitations 

of demographic information and enable 

timelier reporting of equity results until 

longer term collaborations to improve 

demographic data quality across the 

health care sector materialize. The use 

of indirectly estimated race and 

ethnicity for conducting stratified 

reporting does not place any additional 

collection or reporting burdens on 

facilities as these data are derived using 

existing administrative and censuslinked data. 

Indirect estimation relies on a 

statistical imputation method for 

inferring a missing variable or 

improving an imperfect administrative 

variable using a related set of 

information that is more readily 

available.54 Indirectly estimated data are 

most commonly used at the population 

level (such as the facility or health planlevel), where aggregated results form a 

more accurate description of the 

population than existing, imperfect data 

sets. These methods often estimate race 

and ethnicity using a combination of 

other data sources which are predictive 

of self-identified race and ethnicity, 

such as language preference, 

information about race and ethnicity in 

our administrative records, first and last 

names matched to validated lists of 

names correlated to specific national 

origin groups, and the racial and ethnic 

composition of the surrounding 

neighborhood. Indirect estimation has 

been used in other settings to support 

population-based equity measurement 

when self-identified data are not 

available.55

As described in section IV.D.2, we 

have previously supported the 

development of two such methods of 

indirect estimation of race and ethnicity 

of Medicare beneficiaries. One indirect 

estimation approach, developed by our 

contractor, uses Medicare 

administrative data, first name and 

surname matching, derived from the 

U.S. Census and other sources, with 

beneficiary language preference, state of 

residence, and the source of the race 

and ethnicity code in Medicare 

administrative data to reclassify some 

beneficiaries as Hispanic or Asian/ 

Pacific Islander (API).56 In recent years, 

we have also worked with another 

contractor to develop a new approach, 

the Medicare Bayesian Improved 

Surname Geocoding (MBISG), which 

combines Medicare administrative data, 

first and surname matching, geocoded 

residential address linked to the 2010 

U.S. Census, and uses both Bayesian 

updating and multinomial logistic 

regression to estimate the probability of 

belonging to each of six racial/ethnic 

groups.57

The MBISG model is currently used to 

conduct the national, contract-level, 

stratified reporting of Medicare Part C & 

D performance data for Medicare 

Advantage Plans by race and 

ethnicity.58 Validation testing reveals 

concordances with self-reported race 

and ethnicity of 0.96 through 0.99 for 

API, Black, Hispanic, and White 

beneficiaries for MBISG version 2.1.59

The algorithms under consideration are 

considerably less accurate for 

individuals who self-identify as 

American Indian/Alaskan Native or 

multiracial.60 Indirect estimation can be 

a statistically reliable approach for 

calculating population-level equity 

results for groups of individuals (such 

as the facility-level) and is not intended, 

nor being considered, as an approach for 

inferring the race and ethnicity of an 

individual. 

However, despite the high degree of 

statistical accuracy of the indirect 

estimation algorithms under 

consideration there remains the small 

risk of unintentionally introducing bias. 

For example, if the indirect estimation 

is not as accurate in correctly estimating 

race and ethnicity in certain geographies 

or populations it could lead to some 

bias in the method results. Such bias 

might result in slight overestimation or 

underestimation of the quality of care 

received by a given group. We feel this 

amount of bias is considerably less than 

would be expected if stratified reporting 

was conducted using the race and 

ethnicity currently contained in our 

administrative data. Indirect estimation 

of race and ethnicity is envisioned as an 

intermediate step, filling the pressing 

need for more accurate demographic 

information for the purposes of 

exploring inequities in service delivery, 

while allowing newer approaches, as 

described in the next section, for 

improving demographic data collection 

to progress. We expressed interest in 

learning more about, and solicited 

comments about, the potential benefits 

and challenges associated with 

measuring facility equity using an 

imputation algorithm to enhance 

existing administrative data quality for 

race and ethnicity until self-reported 

information is sufficiently available. 

c. Improving Demographic Data 

Collection 

Stratified facility-level reporting using 

dual eligibility and indirectly estimated 

race and ethnicity would represent an 

important advance in our ability to 

provide equity reports to facilities. 

However, self-reported race and 

ethnicity data remain the gold standard 

for classifying an individual according 

to race or ethnicity. The CMS Quality 

Strategy outlines our commitment to 

strengthening infrastructure and data 

systems by ensuring that standardized 

demographic information is collected to 

identify disparities in health care 

delivery outcomes.61 Collection and 

sharing of a standardized set of social, 

psychological, and behavioral data by 

facilities, including race and ethnicity, 

using electronic data definitions which 

permit nationwide, interoperable health 

information exchange, can significantly 

enhance the accuracy and robustness of 

our equity reporting.62 This could 

potentially include expansion to 


lotter on DSK11XQN23PROD with RULES5
42630 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

63https://minorityhealth.hhs.gov/assets/pdf/ 

checked/1/Fact_Sheet_Section_4302.pdf. 

64https://www.healthit.gov/sites/default/files/ 

2020-08/2015EdCures_Update_CCG_USCDI.pdf. 

65Agniel D, Martino SC, Burkhart Q, et al. 

Incentivizing Excellent Care to At-Risk Groups with 

a Health Equity Summary Score. J Gen Intern Med. 

Published online November 11, 2019 Nov 11. doi: 

10.1007/s11606–019–05473–x. 

additional social risk factors, such as 

disability status, where accuracy of 

administrative data is currently limited. 

We are mindful that additional 

resources, including data collection and 

staff training may be necessary to ensure 

that conditions are created whereby all 

patients are comfortable answering all 

demographic questions, and that 

individual preferences for non-response 

are maintained. 

We are also interested in learning 

about and solicited comments on 

current data collection practices by 

facilities to capture demographic data 

elements (such as race, ethnicity, sex, 

sexual orientation and gender identity 

(SOGI), primary language, and disability 

status). Further, we are interested in 

potential challenges facing facility 

collection, at the time of admission, of 

a minimum set of demographic data 

elements in alignment with national 

data collection standards (such as the 

standards finalized by the Affordable 

Care Act) 63 and standards for 

interoperable exchange (such as the U.S. 

Core Data for Interoperability 

incorporated into certified health IT 

products as part of the 2015 Edition of 

health IT certification criteria).64

Advancing data interoperability through 

collection of a minimum set of 

demographic data collection, and 

incorporation of this demographic 

information into quality measure 

specifications, has the potential for 

improving the robustness of the 

disparity method results, potentially 

permitting reporting using more 

accurate, self-reported information, such 

as race and ethnicity, and expanding 

reporting to additional dimensions of 

equity, including stratified reporting by 

disability status. 

d. Potential Creation of a Facility Equity 

Score To Synthesize Results Across 

Multiple Social Risk Factors 

As we describe in section IV.D.3.a of 

this final rule, we are considering 

expanding the disparity methods to IPFs 

and to include two social risk factors 

(dual eligibility and race/ethnicity). 

This approach would improve the 

comprehensiveness of health equity 

information provided to facilities. 

Aggregated results from multiple 

measures and multiple social risk 

factors, from the CMS Disparity 

Methods, in the format of a summary 

score, can improve the usefulness of the 

equity results. In working with our 

contractors, we recently developed an 

equity summary score for Medicare 

Advantage contract/plans, the Health 

Equity Summary Score (HESS), with 

application to stratified reporting using 

two social risk factors: Dual eligibility 

and race and as described in 

Incentivizing Excellent Care to At-Risk 

Groups with a Health Equity Summary 

Score.65

The HESS calculates standardized 

and combined performance scores 

blended across the two social risk 

factors. The HESS also combines results 

of the within-plan (similar to the 

Within-Facility method) and across-plan 

method (similar to the Across-Facility 

method) across multiple performance 

measures. 

We are considering building a 

‘‘Facility Equity Score,’’ not yet 

developed, which would be modeled off 

the HESS but adapted to the context of 

risk-adjusted facility outcome measures 

and potentially other IPF quality 

measures. We envision that the Facility 

Equity Score would synthesize results 

for a range of measures and using 

multiple social risk factors, using 

measures and social risk factors, which 

would be reported to facilities as part of 

the CMS Disparity Methods. We believe 

that creation of the Facility Equity Score 

has the potential to supplement the 

overall measure data already reported 

on the Care Compare or successor 

website, by providing easy to interpret 

information regarding disparities 

measured within individual facilities 

and across facilities nationally. A 

summary score would decrease burden 

by minimizing the number of measure 

results provided and providing an 

overall indicator of equity. 

The Facility Equity Score under 

consideration would potentially: 

• Summarize facility performance 

across multiple social determinants of 

health (initially dual eligibility and 

indirectly estimated race and ethnicity); 

and 

• Summarize facility performance 

across the two disparity methods (that 

is, the Within-Facility Disparity Method 

and the Across-Facility Disparity 

Method) and potentially for multiple 

measures. 

Prior to any future public reporting, if 

we determine that a Facility Equity 

Score can be feasibly and accurately 

calculated, we would provide results of 

the Facility Equity Score, in confidential 

facility specific reports, which facilities 

and their QIN–QIOs would be able to 

download. Any potential future 

proposal to display the Facility Equity 

Score on the Care Compare or successor 

website would be made through future 

RFI or rulemaking. 

c. Solicitation of Public Comment 

We solicited public comments on the 

possibility of stratifying IPFQR Program 

measures by dual eligibility and race 

and ethnicity. We also solicited public 

comments on mechanisms of 

incorporating co-occurring disability 

status into such stratification as well. 

We sought public comments on the 

application of the within-facility or 

across-facility disparities methods 

IPFQR Program measures if we were to 

stratify IPFQR Program measures. We 

also solicited comment on the 

possibility of facility collection of 

standardized demographic information 

for the purposes of potential future 

quality reporting and measure 

stratification. In addition, we solicited 

public comments on the potential 

design of a facility equity score for 

calculating results across multiple social 

risk factors and measures, including 

race and disability. Any data pertaining 

to these areas that are recommended for 

collection for measure reporting for a 

CMS program and any potential public 

disclosure on Care Compare or 

successor website would be addressed 

through a separate and future noticeand-comment rulemaking. We plan to 

continue working with ASPE, facilities, 

the public, and other key stakeholders 

on this important issue to identify 

policy solutions that achieve the goals 

of attaining health equity for all patients 

and minimizing unintended 

consequences. We also noted our 

intention for additional RFIs or 

rulemaking on this topic in the future. 

Specifically, we solicited public 

comment on the following: 

Future Potential Stratification of Quality 

Measure Results 

• The possible stratification of 

facility-specific reports for IPFQR 

program measure data by dual-eligibility 

status given that over half of the patient 

population in IPFs are dually eligible, 

including, which measures would be 

most appropriate for stratification; 

• The potential future application of 

indirect estimation of race and ethnicity 

to permit stratification of measure data 

for reporting facility-level disparity 

results until more accurate forms of selfidentified demographic information are 

available; 

• Appropriate privacy safeguards 

with respect to data produced from the 

indirect estimation of race and ethnicity 

to ensure that such data are properly 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42631 

identified if/when they are shared with 

providers; 

• Ways to address the challenges of 

defining and collecting accurate and 

standardized self-identified 

demographic information, including 

information on race and ethnicity and 

disability, for the purposes of reporting, 

measure stratification and other data 

collection efforts relating to quality. 

• Recommendations for other types of 

readily available data elements for 

measuring disadvantage and 

discrimination for the purposes of 

reporting, measure stratification and 

other data collection efforts relating to 

quality, in addition, or in combination 

with race and ethnicity. 

• Recommendations for types of 

quality measures or measurement 

domains to prioritize for stratified 

reporting by dual eligibility, race and 

ethnicity, and disability. 

• Examples of approaches, methods, 

research, and considerations or any 

combination of these for use of datadriven technologies that do not facilitate 

exacerbation of health inequities, 

recognizing that biases may occur in 

methodology or be encoded in datasets. 

We received comments on these 

topics. 

Comments: Many commenters 

expressed support for the collection of 

data to support stratifying or otherwise 

measuring disparities in care related to 

dual-eligibility, race and ethnicity, and 

disability. Some commenters 

specifically supported the confidential 

reporting of stratified results to 

facilities. Several commenters urged 

CMS to expand data collection and 

measure stratification to include factors 

such as language preference, veteran 

status, health literacy, gender identity, 

and sexual orientation to provide a more 

comprehensive assessment of health 

equity. One commenter urged CMS to 

collect data on race and ethnicity 

specifically for patients suffering from 

psychiatric disorders, while another 

noted that for the IPF patient population 

risk factors, such as substance abuse, 

may be of more importance. One 

commenter also provided examples of 

how their health system has 

successfully collected and begun to 

analyze patient-level demographic data. 

Another commenter referred to an 

existing effort by the National 

Committee for Quality Assurance to 

improve the collection of race and 

ethnicity data as a possible model for 

improving data collection. This 

commenter also supported the use of 

indirect estimation of race and ethnicity 

for Medicare beneficiaries, noting some 

concern about the lack of granularity, 

especially with respect to Native 

American and Asian populations. One 

commenter urged CMS to explore how 

to best identify social determinants of 

health using current claims data. 

While many commenters expressed 

support for stratification of claims-based 

measures, many commenters expressed 

concern that the existing chartabstracted measures would face 

limitations when stratified and thus felt 

the burden of collecting stratification 

data for these measures significantly 

outweighed any potential benefit of 

doing so. Specifically, commenters 

noted that stratifying the IPF patient 

population is more vulnerable to 

statistical concerns during the 

stratification process than other patient 

populations (for example, numbers of 

patients in one or more strata may be 

insufficient for reliable sampling and 

calculations) due to low patient volume 

in some facilities. One commenter 

suggested that for this and other reasons 

CMS should develop disparities 

reporting specifically for the IPF 

program rather than adopt an approach 

developed for a different program. A 

few commenters also questioned the 

value of stratification of these measures 

given the current high levels of 

performance by many IPFs. 

One commenter noted that stratified 

claims-based measures would exclude 

all privately insured care and thus be 

less useful. Several commenters stated 

that interoperability issues such as a 

lack of EHRs, particularly for IPFs that 

are smaller or not part of a large hospital 

or health system, further add to the 

burden of stratifying chart-abstracted 

measures and may contribute to bias in 

the data. 

Several commenters also noted that 

stratification may be challenging due to 

differences in the patient population 

served by IPFs compared to other 

Medicare programs such as acute and 

long-term care hospitals, for example, 

age, proportion and reason for dualeligibility (income versus disability), 

and substance abuse disorder 

prevalence. However, several 

commenters noted many of these same 

characteristics, as well as the mental 

and behavioral health needs of patients 

cared for by IPFs, are evidence of the 

need to improve data collection and 

measurement in IPFs. A commenter also 

recommended further analysis on the 

predictive power of social risk factors 

on mental and behavioral health patient 

outcomes compared to that of the 

diagnosis requiring treatment. Several 

commenters recommended CMS further 

address issues related to the potential 

stratification of data such as: Patient 

privacy and the collection and sharing 

of social risk factors from patient 

records or through indirect estimation, 

differing requirements for collection of 

race and ethnicity data, transparency 

regarding indirect estimation methods, 

and differing Medicaid eligibility 

requirements by state. One commenter 

related these concerns to public 

reporting, suggesting support for 

confidential reporting until these issues 

are addressed. 

We appreciate all of the comments 

and interest in this topic. We believe 

that this input is very valuable in the 

continuing development of the CMS 

health equity quality measurement 

efforts. We will continue to take all 

concerns, comments, and suggestions 

into account for future development and 

expansion of our health equity quality 

measurement efforts. 

Improving Demographic Data Collection 

• Experiences of users of certified 

health IT regarding local adoption of 

practices for collection of social, 

psychological, and behavioral data 

elements, the perceived value of using 

these data for improving decisionmaking and care delivery, and the 

potential challenges and benefits of 

collecting more granular, structured 

demographic information, such as the 

‘‘Race & Ethnicity—CDC’’ code system. 

• The possible collection of a 

minimum set of social, psychological, 

and behavioral data elements by 

hospitals at the time of admission using 

structured, interoperable data standards, 

for the purposes of reporting, measure 

stratification and other data collection 

efforts relating to quality. 

We received comments on these 

topics. 

Comments: We received mixed 

feedback regarding demographic data 

collection. Many commenters supported 

the need for and use of such data, noting 

that structured, interoperable electronic 

health data are the gold standard. They 

also noted that many barriers exist to 

adopting electronic health information 

technology systems necessary for 

capture of these data, particularly in 

freestanding psychiatric facilities. A 

commenter stated that the commenter’s 

organization cannot support 

demographic data collection due to the 

workload burden it would place on both 

the IPF and patients and their families. 

This commenter also noted that the 

likelihood of patients and families 

comfortably answering multiple 

sensitive demographic questions is low, 

especially upon admission. Another 

commenter expressed concerns with the 

current capabilities of the industry to 

collect these data, specifying a lack of 

standardization in screening and data 

collection and need for staff training. 


lotter on DSK11XQN23PROD with RULES5
42632 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

Multiple commenters expressed concern 

about the patient and family’s 

perception of the organization if given a 

data collection questionnaire upon 

admission, noting that they may think 

the organization is more focused on data 

collection rather than care. 

Other commenters noted the 

importance of closing the health equity 

gap through measurement of 

demographic characteristics. A 

commenter suggested that agencies 

leverage the role of nurses in identifying 

sociodemographic factors and barriers to 

health equity. Another commenter 

supported this method, noting that 

although this may add another step to 

data collection processes, it would be 

valuable in addressing health equity 

gaps. To reduce possible workload 

burden on organizations that are new to 

this process, a commenter 

recommended a staggered approach to 

data collection, suggesting CMS require 

providers and facilities to collect data 

on age and sex by the end of 2022, race 

and ethnicity by the end of 2023, etc., 

with the goal of at least 80 percent data 

completeness with 80 percent accuracy. 

In addition, commenters suggested 

reducing burden by adopting 

standardized screening tools to collect 

this information, such as ICD–Z-codes, 

which in practice would allow patients 

to be referred to resources and 

initiatives when appropriate. Several 

commenters encouraged collection of 

comprehensive social determinants of 

health and demographic information in 

addition to race and ethnicity, such as 

disability, sexual orientation, and 

primary language. Several commenters 

provided feedback on the potential use 

of an indirect estimation algorithm 

when race and ethnicity are missing/ 

incorrect, and emphasized the 

sensitivity of demographic information 

and recommended that CMS use caution 

when using estimates from the 

algorithm, including assessing for 

potential bias, reporting the results of 

indirect estimation alongside direct selfreport at the organizational level for 

comparison, and establishing a timeline 

to transition to entirely directly 

collected data. Commenters also advised 

that CMS be transparent with 

beneficiaries and explain why data are 

being collected and the plans to use 

these data. A commenter noted that 

information technology infrastructure 

should be established in advance to 

ensure that this information is being 

used and exchanged appropriately. 

We appreciate all of the comments 

and interest in this topic. We believe 

that this input is very valuable in the 

continuing development of the CMS 

health equity quality measurement 

efforts. We will continue to take all 

concerns, comments, and suggestions 

into account for future development and 

expansion of our health equity quality 

measurement efforts. 

Potential Creation of a Facility Equity 

Score To Synthesize Results Across 

Multiple Social Risk Factors 

• The possible creation and 

confidential reporting of a Facility 

Equity Score to synthesize results across 

multiple social risk factors and disparity 

measures. 

• Interventions facilities could 

institute to improve a low facility equity 

score and how improved demographic 

data could assist with these efforts. 

We received comments on these 

topics. 

Comments: Commenters generally 

supported ongoing thoughtful 

investigation into best practices for 

measuring health equity. 

Many commenters expressed 

concerns about the potential Facility 

Equity Score. Commenters argued that 

the current approach used to generate 

the composite score may not lead to 

aggregate results, which would not be 

actionable for many facilities. 

Commenters also raised concerns about 

risk adjustment, limitations in 

stratification variables, and the 

appropriateness of the current measure 

set. A commenter noted that although 

they support thoughtful efforts to 

categorize performance, the HESS has 

been established only as a ‘‘proof of 

concept’’ and will require considerable 

time and resources to produce a valid 

and actionable measure. The same 

commenter also noted that HESS 

scoring was only feasible for less than 

one-half of Medicare Advantage (MA) 

plans and as such, may not be practical 

for many smaller facilities, or facilities 

whose enrolled populations differ in 

social risk factor distribution patterns 

compared to typical MA plans. 

Commenters generally did not 

support use of the Facility Equity Score 

in public reporting or payment 

incentive programs, suggesting that it is 

imperative to first understand any 

unintended consequences prior to 

implementation. More specifically, 

several commenters gave the example of 

facilities failing to raise the quality of 

care for at-risk patients while appearing 

to achieve greater equity due to lower 

quality of care for patients that are not 

at risk. A commenter stated the belief 

that CMS should begin their initiative to 

improve health equity by using 

structural health equity measures. 

Commenters also raised concerns about 

use of dual-eligibility as a social risk 

factor due to variations in state-level 

eligibility for Medicaid, making national 

comparisons, or benchmarking of 

facility scores unreliable. Additionally, 

commenters who expressed data 

reliability concerns recommended that 

CMS focus its resources on improving 

standardized data collection and 

reporting procedures for 

sociodemographic data before moving 

forward with a Facility Equity Score. 

We appreciate all of the comments 

and interest in this topic. We believe 

that this input is very valuable in the 

continuing development of the CMS 

health equity quality measurement 

efforts. We will continue to take all 

concerns, comments, and suggestions 

into account for future development and 

expansion of our health equity quality 

measurement efforts. 

We also received comments on the 

general topic of health equity in the 

IPFQR Program. 

Comments: Many commenters 

expressed overall support of CMS’ goals 

to advance health equity. There were 

some comments regarding the need to 

further extend and specify the definition 

of equity provided in the proposed rule. 

Commenters also noted that equity 

initiatives should be based on existing 

disparities and population health goals, 

be mindful of the needs of the 

communities served, and work to bridge 

hospitals with post-acute and 

community-based providers. Several 

commenters encouraged CMS to be 

mindful about whether collection of 

additional quality measures and 

standardized patient assessment 

elements might increase provider 

burden. Several commenters noted 

support for consideration of a measure 

of organizational commitment to health 

equity, outlining how infrastructure 

supports delivery of equitable care. A 

commenter noted the importance of 

focusing programming on inequities in 

vaccine-preventable illness. Another 

commenter noted that CMS may expand 

their view of equity beyond quality 

reporting to payment and coverage 

policies. 

We appreciate all of the comments 

and interest in this topic. We believe 

that this input is very valuable in the 

continuing development of the CMS 

health equity quality measurement 

efforts. We will continue to take all 

concerns, comments, and suggestions 

into account for future development and 

expansion of our health equity quality 

measurement efforts. 

E. Measure Adoption 

We strive to put consumers and 

caregivers first, ensuring they are 

empowered to make decisions about 

their own healthcare along with their 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42633 

66This measure was previously titled, ‘‘SARS– 

CoV–2 Vaccination Coverage among Healthcare 

Personnel.’’ 

67U.S. Dept of Health and Human Services, Office 

of the Assistant Secretary for Preparedness and 

Response. (2020). Determination that a Public 

Health Emergency Exists. Available at: https://

www.phe.gov/emergency/news/healthactions/phe/ 

Pages/2019-nCoV.aspx. 

68Centers for Disease Control and Prevention. 

(2020). Your Health: Symptoms of Coronavirus. 

Available at: https://www.cdc.gov/coronavirus/ 

2019-ncov/symptoms-testing/symptoms.html. 

69Centers for Disease Control and Prevention. 

(2020). Your Health: Symptoms of Coronavirus. 

Available at https://www.cdc.gov/coronavirus/2019- 

ncov/symptoms-testing/symptoms.html. 

70Centers for Disease Control and Prevention. 

(2020). CDC COVID Data Tracker. Accessed on 

April 3, 2021 at: https://covid.cdc.gov/covid-datatracker/#cases_casesper100klast7days. 

71Associated Press. Tired to the Bone. Hospitals 

Overwhelmed with Virus Cases. November 18, 

2020. Accessed on December 16, 2020, at https:// 

apnews.com/article/hospitals-overwhelmedcoronavirus-cases74a1f0dc3634917a5dc13408455cd895. Also see: 

New York Times. Just how full are U.S. intensive 

care units? New data paints an alarming picture. 

November 18, 2020. Accessed on December 16, 

2020, at: https://www.nytimes.com/2020/12/09/ 

world/just-how-full-are-us-intensive-care-units-newdata-paints-an-alarming-picture.html. 

72U.S. Currently Hospitalized | The COVID 

Tracking Project https://covidtracking.com/data/ 

charts/us-currently-hospitalized. 

73Centers for Disease Control and Prevention. 

(2021). How COVID–19 Spreads. Accessed on April 

3, 2021 at: https://www.cdc.gov/coronavirus/2019- 

ncov/prevent-getting-sick/how-covid-spreads.html. 

74Centers for Disease Control and Prevention. 

(2021). How COVID–19 Spreads. Accessed on April 

3, 2021 at: https://www.cdc.gov/coronavirus/2019- 

ncov/prevent-getting-sick/how-covid-spreads.html. 

75Centers for Disease Control and Prevention. 

(2021). How COVID–19 Spreads. Accessed on April 

3, 2021 at: https://www.cdc.gov/coronavirus/2019- 

ncov/prevent-getting-sick/how-covid-spreads.html. 

76Centers for Disease Control and Prevention. 

(2021). How COVID–19 Spreads. Accessed on April 

3, 2021 at: https://www.cdc.gov/coronavirus/2019- 

ncov/prevent-getting-sick/how-covid-spreads.html. 

77Centers for Disease Control and Prevention. 

(2021). How COVID–19 Spreads. Accessed on April 

3, 2021 at: https://www.cdc.gov/coronavirus/2019- 

ncov/prevent-getting-sick/how-covid-spreads.html. 

78Centers for Disease Control and Prevention. 

(2021). How COVID–19 Spreads. Accessed on July 

15, 2021 at: https://www.cdc.gov/coronavirus/2019- 

ncov/prevent-getting-sick/how-covid-spreads.html. 

79Centers for Disease Control and Prevention. 

(2021). When to Quarantine. Accessed on April 3, 

2021 at: https://www.cdc.gov/coronavirus/2019- 

ncov/if-you-are-sick/quarantine.html. 

80Centers for Disease Control and Prevention. 

(2020). Interim U.S. Guidance for Risk Assessment 

and Work Restrictions for Healthcare Personnel 

with Potential Exposure to COVID–19. Accessed on 

April 2, 2021 at: https://www.cdc.gov/coronavirus/ 

2019-ncov/hcp/faq.html#Transmission. 

clinicians using information from datadriven insights that are increasingly 

aligned with meaningful quality 

measures. We support technology that 

reduces burden and allows clinicians to 

focus on providing high-quality 

healthcare for their patients. We also 

support innovative approaches to 

improve quality, accessibility, and 

affordability of care while paying 

particular attention to improving 

clinicians’ and beneficiaries’ 

experiences when interacting with our 

programs. In combination with other 

efforts across the Department of Health 

and Human Services (HHS), we believe 

the IPFQR Program helps to incentivize 

facilities to improve healthcare quality 

and value while giving patients and 

providers the tools and information 

needed to make the best decisions for 

them. Consistent with these goals, our 

objective in selecting quality measures 

is to balance the need for information on 

the full spectrum of care delivery and 

the need to minimize the burden of data 

collection and reporting. We have 

primarily focused on measures that 

evaluate critical processes of care that 

have significant impact on patient 

outcomes and support CMS and HHS 

priorities for improved quality and 

efficiency of care provided by IPFs. 

When possible, we also propose to 

incorporate measures that directly 

evaluate patient outcomes and 

experience. We refer readers to section 

VIII.F.4.a. of the FY 2013 IPPS/LTCH 

PPS final rule (77 FR 53645 through 

53646) for a detailed discussion of the 

considerations taken into account in 

selecting quality measures. 

1. Measure Selection Process 

Before being proposed for inclusion in 

the IPFQR Program, measures are placed 

on a list of measures under 

consideration (MUC), which is 

published annually on behalf of CMS by 

the National Quality Forum (NQF). 

Following publication on the MUC list, 

the Measure Applications Partnership 

(MAP), a multi-stakeholder group 

convened by the NQF, reviews the 

measures under consideration for the 

IPFQR Program, among other Federal 

programs, and provides input on those 

measures to the Secretary. We consider 

the input and recommendations 

provided by the MAP in selecting all 

measures for the IPFQR Program. In our 

evaluation of the IPFQR Program 

measure set, we identified two measures 

that we believe are appropriate for the 

IPFQR Program. 

2. COVID–19 Vaccination Coverage 

Among Health Care Personnel (HCP) 66

Measure for the FY 2023 Payment 

Determination and Subsequent Years 

a. Background 

On January 31, 2020, the Secretary 

declared a PHE for the U.S. in response 

to the global outbreak of SARS–CoV–2, 

a novel (new) coronavirus that causes a 

disease named ‘‘coronavirus disease 

2019’’ (COVID–19).67 COVID–19 is a 

contagious respiratory illness 68 that can 

cause serious illness and death. Older 

individuals and those with underlying 

medical conditions are considered to be 

at higher risk for more serious 

complications from COVID–19.69

As of April 2, 2021, the U.S. had 

reported over 30 million cases of 

COVID–19 and over 550,000 COVID–19 

deaths.70 Hospitals and health systems 

saw significant surges of COVID–19 

patients as community infection levels 

increased.71 From December 2, 2020 

through January 30, 2021, more than 

100,000 Americans were in the hospital 

with COVID–19 at the same time.72

Evidence indicates that COVID–19 

primarily spreads when individuals are 

in close contact with one another.73 The 

virus is typically transmitted through 

respiratory droplets or small particles 

created when someone who is infected 

with the virus coughs, sneezes, sings, 

talks, or breathes.74 Thus, the CDC 

advises that infections mainly occur 

through exposure to respiratory droplets 

when a person is in close contact with 

someone who has COVID–19.75 Experts 

believe that COVID–19 spreads less 

commonly through contact with a 

contaminated surface (although that is 

not thought to be a common way that 

COVID–19 spreads),76 and that in 

certain circumstances, infection can 

occur through airborne transmission.77

Subsequent to the publication of the 

proposed rule, the CDC confirmed that 

the three main ways that COVID–19 is 

spread are: (1) Breathing in air when 

close to an infected person who is 

exhaling small droplets and particles 

that contain the virus; (2) Having these 

small droplets and particles that contain 

virus land on the eyes, nose, or mouth, 

especially through splashes and sprays 

like a cough or sneeze; and (3) Touching 

eyes, nose, or mouth with hands that 

have the virus on them.78 According to 

the CDC, those at greatest risk of 

infection are persons who have had 

prolonged, unprotected close contact 

(that is, within 6 feet for 15 minutes or 

longer) with an individual with 

confirmed SARS–CoV–2 infection, 

regardless of whether the individual has 

symptoms.79 Although personal 

protective equipment (PPE) and other 

infection-control precautions can reduce 

the likelihood of transmission in health 

care settings, COVID–19 can spread 

between health care personnel (HCP) 

and patients, or from patient to patient 

given the close contact that may occur 

during the provision of care.80 The CDC 

has emphasized that health care 

settings, including long-term care 


lotter on DSK11XQN23PROD with RULES5
42634 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

81 Dooling, K, McClung, M, et al. ‘‘The Advisory 

Committee on Immunization Practices’ Interim 

Recommendations for Allocating Initial Supplies of 

COVID–19 Vaccine—United States, 2020.’’ Morb 

Mortal Wkly Rep. 2020; 69(49): 1857–1859. 

82Centers for Disease Control and Prevention. 

(2020). COVID–19 Vaccination Program Interim 

Playbook for Jurisdiction Operations. Accessed on 

April 3, 2021 at: https://www.cdc.gov/vaccines/imzmanagers/downloads/COVID-19-VaccinationProgram-Interim_Playbook.pdf. 

83U.S. Food and Drug Administration. (2020). 

Pfizer-BioNTech COVID–19 Vaccine EUA Letter of 

Authorization. Available at https://www.fda.gov/ 

media/144412/download. (as reissued on May 10, 

2021). 

84U.S. Food and Drug Administration. (2020). 

Moderna COVID–19 Vaccine EUA Letter of 

Authorization. Available at https://www.fda.gov/ 

media/144636/download (as reissued on July 7, 

2021); U.S. Food and Drug Administration. (2021). 

Janssen COVID–19 Vaccine EUA Letter of 

Authorization. Available at https://www.fda.gov/

media/146303/download (as reissued on June 10, 

2021). 

85U.S. Food and Drug Administration. (2020). 

Pfizer-BioNTech COVID–19 Vaccine EUA Letter of 

Authorization. Available at https://www.fda.gov/ 

media/144412/download (as reissued on May 10, 

2021) and U.S. Food and Drug Administration. 

(2020). Moderna COVID–19 Vaccine EUA Letter of 

Authorization. Available at https://www.fda.gov/ 

media/144636/download (as reissued on July 7, 

2021); U.S. Food and Drug Administration. (2021). 

Janssen COVID–19 Vaccine EUA Letter of 

Authorization. Available at https://www.fda.gov/ 

media/146303/download (as reissued on June 10, 

2021). 

86https://www.whitehouse.gov/briefing-room/ 

speeches-remarks/2021/03/29/remarks-bypresident-biden-on-the-covid-19-response-and-thestate-of-vaccinations/. 

87Health and Human Services, Department of 

Defense. (2020) From the Factory to the Frontlines: 

The Operation Warp Speed Strategy for Distributing 

a COVID–19 Vaccine. Accessed December 18 at: 

https://www.hhs.gov/sites/default/files/strategy-fordistributing-covid-19-vaccine.pdf; Centers for 

Disease Control (2020). COVID–19 Vaccination 

Program Interim Playbook for Jurisdiction 

Operations. Accessed December 18 at: https://

www.cdc.gov/vaccines/imz-managers/downloads/ 

COVID-19-Vaccination-Program-Interim_

Playbook.pdf. 

88 Dooling, K, McClung, M, et al. ‘‘The Advisory 

Committee on Immunization Practices’ Interim 

Recommendations for Allocating Initial Supplies of 

COVID–19 Vaccine—United States, 2020.’’ Morb. 

Mortal Wkly Rep. 2020; 69(49): 1857–1859. ACIP 

also recommended that long-term care residents be 

prioritized to receive the vaccine, given their age, 

high levels of underlying medical conditions, and 

congregate living situations make them high risk for 

severe illness from COVID–19. 

89 Kates, J, Michaud, J, Tolbert, J. ‘‘How Are States 

Prioritizing Who Will Get the COVID–19 Vaccine 

First?’’ Kaiser Family Foundation. December 14, 

2020. Accessed on December 16 at https://

www.kff.org/policy-watch/how-are-statesprioritizing-who-will-get-the-covid-19-vaccine-first/. 

90Associated Press. ‘Healing is Coming:’ US 

Health Workers Start Getting Vaccine. December 15, 

2020. Accessed on December 16 at: https://

apnews.com/article/us-health-workers-coronavirusvaccine-56df745388a9fc12ae93c6f9a0d0e81f. 

91https://www.cdc.gov/niosh/topics/healthcare/ 

default.html#:∼:text=

HEALTHCARE%20WORKERS,- 

Related%20Pages&text=

Healthcare%20is%20the%20fastest%2Dgrowing,

of%20the%20healthcare%20work%20force. 

92CDC. COVID Data Tracker. COVID–19 

Vaccinations in the United States. Accessed on 4/ 

4/21 at: https://covid.cdc.gov/covid-data-tracker/ 

#vaccinations. 

93CDC. COVID Data Tracker. COVID–19 

Vaccinations in the United States. Accessed on 7/ 

6/2021 at: https://covid.cdc.gov/covid-data-tracker/ 

#vaccinations. 

94The White House. Remarks by President Biden 

on the Administration’s COVID–19 Vaccination 

Efforts. Accessed March 18, 2021 at: https://

www.whitehouse.gov/briefing-room/speechesremarks/2021/03/02/remarks-by-president-bidenon-the-administrations-covid-19-vaccinationefforts/. 

95Press Briefing by White House COVID–19 

Response Team and Public Health Officials | The 

White House. 

96Centers for Disease Control and Prevention. 

Overview of Influenza Vaccination among Health 

Care Personnel. October 2020. (2020) Accessed 

March 16, 2021 at: https://www.cdc.gov/flu/toolkit/ 

long-term-care/why.htm. 

97Measure Application Committee Coordinating 

Committee Meeting Presentation. March 15, 2021. 

(2021) Accessed March 16, 2021 at: http://

www.qualityforum.org/Project_Pages/MAP_

Coordinating_Committee.aspx. 

settings, can be high-risk places for 

COVID–19 exposure and transmission.81

Vaccination is a critical part of the 

nation’s strategy to effectively counter 

the spread of COVID–19 and ultimately 

help restore societal functioning.82 On 

December 11, 2020, FDA issued the first 

Emergency Use Authorization (EUA) for 

a COVID–19 vaccine in the U.S.83

Subsequently, FDA issued EUAs for 

additional COVID–19 vaccines.84

FDA determined that it was 

reasonable to conclude that the known 

and potential benefits of each vaccine, 

when used as authorized to prevent 

COVID–19, outweighed its known and 

potential risks.85

As part of its national strategy to 

address COVID–19, the Biden 

Administration stated that it would 

work with states and the private sector 

to execute an aggressive vaccination 

strategy and has outlined a goal of 

administering 200 million shots in 100 

days.86 Although the goal of the U.S. 

government is to ensure that every 

American who wants to receive a 

COVID–19 vaccine can receive one, 

Federal agencies recommended that 

early vaccination efforts focus on those 

critical to the PHE response, including 

HCP providing direct care to patients 

with COVID–19, and individuals at 

highest risk for developing severe 

illness from COVID–19.87 For example, 

the CDC’s Advisory Committee on 

Immunization Practices (ACIP) 

recommended that HCP should be 

among those individuals prioritized to 

receive the initial, limited supply of the 

COVID–19 vaccination given the 

potential for transmission in health care 

settings and the need to preserve health 

care system capacity.88 Research 

suggests most states followed this 

recommendation,89 and HCP began 

receiving the vaccine in mid-December 

of 2020.90

There are approximately 18 million 

healthcare workers in the U.S.91 As of 

April 3, 2021 the CDC reported that over 

162 million doses of COVID–19 vaccine 

had been administered, and 

approximately 60 million people had 

received a complete vaccination course 

as described in IV.E.b.i of this final 

rule.92 By July 15, 2021 the CDC 

reported that over 336,000,000 doses 

had been administered, and 

approximately 160,000,000 people had 

received a complete vaccination 

course.93 President Biden indicated on 

March 2, 2021 that the U.S. is on track 

to have sufficient vaccine supply for 

every adult by the end of May 2021.94

Subsequent to the publication of the IPF 

PPS proposed rule, on June 3, 2021, the 

White House confirmed that there was 

sufficient vaccine supply for all 

Americans.95

We believe it is important to require 

that IPFs report HCP vaccination in 

their facilities in order to assess whether 

they are taking steps to protect health 

care workers and to help sustain the 

ability of IPFs to continue serving their 

communities throughout the PHE and 

beyond. Therefore, we proposed a new 

measure, COVID–19 Vaccination 

Coverage Among HCP, beginning with 

the FY 2023 program year. For that 

program year, IPFs would be required to 

report data on the measure for the fourth 

quarter of 2021 (October 1, 2021 through 

December 31, 2021). For more 

information about the reporting period, 

see section V.E.2.c of this final rule. The 

measure would assess the proportion of 

an IPF’s health care workforce that has 

been vaccinated against COVID–19. 

Although at the time of the proposed 

rule, data to show the effectiveness of 

COVID–19 vaccines to prevent 

asymptomatic infection or transmission 

of SARS–CoV–2 were limited, we stated 

our belief that IPFs should report the 

level of vaccination among their HCP as 

part of their efforts to assess and reduce 

the risk of transmission of COVID–19 

within their facilities. HCP vaccination 

can potentially reduce illness that leads 

to work absence and limit disruptions to 

care.96 Data from influenza vaccination 

demonstrates that provider uptake of the 

vaccine is associated with that provider 

recommending vaccination to 

patients,97 and we believe HCP COVID– 

19 vaccination in IPFs could similarly 

increase uptake among that patient 

population. We also believe that 

publishing the HCP vaccination rates 

would be helpful to many patients, 

including those who are at high-risk for 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42635 

98Centers for Disease Control and Prevention. 

Contraindications and precautions. https://

www.cdc.gov/vaccines/covid-19/info-by-product/ 

clinical-considerations.html#Contraindications. 

99Measure Application Partnership Coordinating 

Committee Meeting Presentation. March 15, 2021. 

(2021) Accessed March 16, 2021 at: http://

www.qualityforum.org/Project_Pages/MAP_

Coordinating_Committee.aspx. 

100https://www.qualityforum.org/WorkArea/ 

linkit.aspx?LinkIdentifier=id&ItemID=94212. 

101Measure Applications Partnership. MAP 

Preliminary Recommendations 2020–2021. 

Accessed on January 24, 2021 at: http://

www.qualityforum.org/Project_Pages/MAP_

Hospital_Workgroup.aspx. 

102Measure Applications Partnership. MAP 

Preliminary Recommendations 2020–2021. 

Accessed on January 24, 2021 at: http://

www.qualityforum.org/Project_Pages/MAP_

Hospital_Workgroup.aspx. 

103Measure Applications Partnership. MAP 

Preliminary Recommendations 2020–2021. 

Accessed on January 24, 2021 at: http://

www.qualityforum.org/Project_Pages/MAP_

Hospital_Workgroup.aspx. 

104Measure Applications Partnership. MAP 

Preliminary Recommendations 2020–2021. 

Accessed on January 24, 2021 at: http://

www.qualityforum.org/Project_Pages/MAP_

Hospital_Workgroup.aspx. 

105Measure Applications Partnership. 2020–2021 

MAP Final Recommendations. Accessed on 

February 3, 2021 at: http://www.qualityforum.org/ 

Setting_Priorities/Partnership/Measure_

Applications_Partnership.aspx. 

106Measure Applications Partnership. 2020–2021 

MAP Final Recommendations. Accessed on 

February 23, 2021 at: http://www.qualityforum.org/ 

Project_Pages/MAP_Hospital_Workgroup.aspx. 

107 Ibid. 

108For more information on testing results and 

other measure updates, please see the Meeting 

Materials (including Agenda, Recording, 

Presentation Slides, Summary, and Transcript) of 

the March 15, 2021 meeting available at https://

www.qualityforum.org/ 

ProjectMaterials.aspx?projectID=75367. 

109Measure Applications Partnership. 2020–2021 

MAP Final Recommendations. Accessed on 

February 23, 2021 at: http://www.qualityforum.org/ 

Project_Pages/MAP_Hospital_Workgroup.aspx. 

developing serious complications from 

COVID–19, as they choose facilities 

from which to seek treatment. Under 

CMS’ Meaningful Measures Framework, 

the COVID–19 measure addresses the 

quality priority of ‘‘Promote Effective 

Prevention and Treatment of Chronic 

Disease’’ through the Meaningful 

Measure Area of ‘‘Preventive Care.’’ 

b. Overview of Measure 

The COVID–19 Vaccination Coverage 

Among HCP measure (‘‘COVID–19 HCP 

vaccination measure’’) is a process 

measure developed by the CDC to track 

COVID–19 vaccination coverage among 

HCP in facilities such as IPFs. 

(1). Measure Specifications 

The denominator is the number of 

HCP eligible to work in the IPF for at 

least 1 day during the reporting period, 

excluding persons with 

contraindications to COVID–19 

vaccination that are described by the 

CDC.98

The numerator is the cumulative 

number of HCP eligible to work in the 

IPF for at least 1 day during the 

reporting period and who received a 

completed vaccination course against 

COVID–19 since the vaccine was first 

available or on a repeated interval if 

revaccination on a regular basis is 

needed.99 Vaccination coverage for the 

purposes of this measure is defined as 

the estimated percentage of HCP eligible 

to work at the IPF for at least 1 day who 

received a completed vaccination 

course. A completed vaccination course 

may require one or more doses 

depending on the EUA for the specific 

vaccine used. 

The finalized specifications for this 

measure are available at https://

www.cdc.gov/nhsn/nqf/index.html. 

(2). Review by the Measure Applications 

Partnership 

The COVID–19 HCP vaccination 

measure was included on the publicly 

available ‘‘List of Measures under 

Consideration for December 21, 

2020,’’ 100 a list of measures under 

consideration for use in various 

Medicare programs. When the Measure 

Applications Partnership (MAP) 

Hospital Workgroup convened on 

January 11, 2021, it reviewed the MUC 

List and the COVID–19 HCP vaccination 

measure. The MAP recognized that the 

proposed measure represents a 

promising effort to advance 

measurement for an evolving national 

pandemic and that it would bring value 

to the IPFQR Program measure set by 

providing transparency about an 

important COVID–19 intervention to 

help prevent infections in HCP and 

patients.101 The MAP also stated that 

collecting information on COVID–19 

vaccination coverage among HCP and 

providing feedback to facilities would 

allow facilities to benchmark coverage 

rates and improve coverage in their IPF, 

and that reducing rates of COVID–19 in 

HCP may reduce transmission among 

patients and reduce instances of staff 

shortages due to illness.102

In its preliminary recommendations, 

the MAP Hospital Workgroup did not 

support this measure for rulemaking, 

subject to potential for mitigation.103 To 

mitigate its concerns, the MAP believed 

that the measure needed welldocumented evidence, finalized 

specifications, testing, and NQF 

endorsement prior to 

implementation.104 Subsequently, the 

MAP Coordinating Committee met on 

January 25, 2021, and reviewed the 

COVID–19 Vaccination Coverage 

Among HCP measure. In the 2020–2021 

MAP Final Recommendations, the MAP 

offered conditional support for 

rulemaking contingent on CMS bringing 

the measures back to MAP once the 

specifications are further refined.105 The 

MAP specifically stated, ‘‘the 

incomplete specifications require 

immediate mitigation and further 

development should continue.’’ 106 The 

spreadsheet of final recommendations 

no longer cited concerns regarding 

evidence, testing, or NQF 

endorsement.107 In response to the MAP 

final recommendation request that CMS 

bring the measure back to the MAP once 

the specifications were further refined, 

CMS and the CDC met with MAP 

Coordinating committee on March 15th. 

Additional information was provided to 

address vaccine availability, alignment 

of the COVID–19 Vaccination Coverage 

Among HCP measure as closely as 

possible with the data collection for the 

Influenza HCP vaccination measure 

(NQF 0431), and clarification related to 

how HCP are defined. At this meeting, 

CMS and the CDC presented 

preliminary findings from the testing of 

the numerator of COVID–19 Vaccination 

Coverage Among HCP, which was in 

process at that time. These preliminary 

findings showed numerator data should 

be feasible and reliable. Testing of the 

numerator of the number of healthcare 

personnel vaccinated involves a 

comparison of the data collected 

through NHSN and independently 

reported through the Federal pharmacy 

partnership program for delivering 

vaccination to LTC facilities. These are 

two completely independent data 

collection systems. In initial analyses of 

the first month of vaccination, the 

number of healthcare workers 

vaccinated in approximately 1,200 

facilities, which had data from both 

systems, the number of healthcare 

personnel vaccinated was highly 

correlated between these 2 systems with 

a correlation coefficient of nearly 90 

percent in the second two weeks of 

reporting.108 The MAP further noted 

that the measure would add value to the 

program measure set by providing 

visibility into an important intervention 

to limit COVID–19 infections in 

healthcare personnel and the patients 

for whom they provide care.109

We value the recommendations of the 

MAP and considered these 

recommendations carefully. Section 

1890A(a)(4) of the Act requires the 

Secretary to take into consideration 

input from multi-stakeholder groups in 

selecting certain quality and efficiency 

measures. While we value input from 

the MAP, we believe it is important to 

propose the measure as quickly as 


lotter on DSK11XQN23PROD with RULES5
42636 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

110We note that the proposed rule incorrectly 

read ‘‘annual reporting periods’’ however the 

section of the proposed rule on data submission 

(IV.J.2.a) correctly described the data submission 

process and timelines. 

111Centers for Disease Control and Prevention. 

Surveillance for Weekly HCP COVID–19 

Vaccination. Accessed at: https://www.cdc.gov/ 

nhsn/hps/weekly-covid-vac/index.html. on 

February 10, 2021. 

112 Dooling, K, McClung, M, et al. ‘‘The Advisory 

Committee on Immunization Practices’ Interim 

Recommendations for Allocating Initial Supplies of 

COVID–19 Vaccine—United States, 2020.’’ Morb 

Mortal Wkly Rep. 2020; 69(49): 1857–1859. 

113Centers for Disease Control and Prevention. 

(2020). Interim U.S. Guidance for Risk Assessment 

and Work Restrictions for Healthcare Personnel 

with Potential Exposure to COVID–19. Accessed on 

April 2, 2021 at: https://www.cdc.gov/coronavirus/ 

2019-ncov/hcp/faq.html#Transmission. 

114https://www.cdc.gov/coronavirus/2019-ncov/ 

science/science-briefs/fully-vaccinated-people.html. 

possible to address the urgency of the 

COVID–19 PHE and its impact on 

vulnerable populations, including IPFs. 

We continue to engage with the MAP to 

mitigate concerns and appreciate the 

MAP’s conditional support for the 

measure. 

(3). NQF Endorsement 

Under section 1886(s)(4)(D)(i) of the 

Act, unless the exception of clause (ii) 

applies, measures selected for the 

quality reporting program must have 

been endorsed by the entity with a 

contract under section 1890(a) of the 

Act. The NQF currently holds this 

contract. Section 1886(s)(4)(D)(ii) of the 

Act provides an exception to the 

requirement for NQF endorsement of 

measures: In the case of a specified area 

or medical topic determined appropriate 

by the Secretary for which a feasible and 

practical measure has not been endorsed 

by the entity with a contract under 

section 1890(a) of the Act, the Secretary 

may specify a measure that is not so 

endorsed as long as due consideration is 

given to measures that have been 

endorsed or adopted by a consensus 

organization identified by the Secretary. 

This measure is not NQF endorsed 

and has not been submitted to NQF for 

endorsement consideration. The CDC, in 

collaboration with CMS, are planning to 

submit the measure for consideration in 

the NQF Fall 2021 measure cycle. 

Because this measure is not NQFendorsed, we considered other available 

measures. We found no other feasible 

and practical measures on the topic of 

COVID–19 vaccination among HCP, 

therefore, we believe the exception in 

Section 1186(s)(4)(D)(ii) of the Act 

applies. 

c. Data Collection, Submission and 

Reporting 

Given the time-sensitive nature of this 

measure considering the PHE, in the FY 

2022 IPF PPS proposed rule, we 

proposed that IPFs would be required to 

begin reporting data on the proposed 

COVID–19 Vaccination Coverage 

Among HCP measure beginning October 

1, 2021 for the FY 2023 IPFQR Program 

year (86 FR 19504). Thereafter, we 

proposed quarterly 110 reporting periods. 

To report this measure, facilities 

would report COVID–19 vaccination 

data to the NHSN for at least one week 

each month, beginning in October 2021 

for the October 1, 2021 through 

December 31, 2021 reporting period 

affecting FY 2023 payment 

determination and continuing for each 

quarter in subsequent years. For more 

details on data submission, we refer 

readers to section V.J.2.a of this final 

rule. 

We proposed that IPFs would report 

the measure through the CDC National 

Healthcare Safety Network (NHSN) webbased surveillance system.111 While the 

IPFQR Program does not currently 

require use of the NHSN web-based 

surveillance system, we have previously 

required use of this system. We refer 

readers to the FY 2015 IPF PPS final 

rule in which we adopted the Influenza 

Vaccination Coverage Among 

Healthcare Personnel (NQF #0431) 

measure for additional information on 

reporting through the NHSN web-based 

surveillance system (79 FR 45968 

through 45970). 

IPFs would report COVID–19 

vaccination data in the NHSN 

Healthcare Personnel Safety (HPS) 

Component by reporting the number of 

HCP eligible to have worked at the IPF 

that week (denominator) and the 

number of those HCP who have received 

a completed vaccination course of a 

COVID–19 vaccination (numerator). For 

additional information about the data 

reporting requirements, see IV.J.4. of 

this final rule. 

We invited public comment on our 

proposal to add a new measure, COVID– 

19 Vaccination Coverage Among HCP, 

to the IPFQR Program for the FY 2023 

payment determination and subsequent 

years. 

Comment: Some commenters 

supported the proposed COVID–19 

Vaccination Coverage Among 

Healthcare Personnel measure. One 

commenter observed that data on 

vaccination coverage are important for 

patients and for individuals seeking 

employment at IPFs. Several 

commenters noted the importance of 

vaccines to reduce transmission, and 

one commenter specifically observed 

that vaccination is particularly 

important in settings such as IPFs 

because non-pharmaceutical 

interventions are challenging in such 

institutional settings. Another 

commenter expressed the belief that the 

measure is methodologically sound. 

Response: We thank these 

commenters for their support. 

Comment: Many commenters 

expressed concern that using NHSN for 

reporting is too burdensome and 

disproportionately affects smaller and 

freestanding IPFs. Some of these 

commenters further expressed that 

requiring reporting through NHSN is 

inconsistent with the removal of 

Influenza Vaccine Coverage among HCP 

measure because the rationale for 

removing the Influenza Vaccine 

Coverage among HCP measure was the 

high reporting burden associated with 

NHSN reporting. 

Response: We believe that there are 

many significant benefits to collecting 

and reporting data on COVID–19 

vaccination coverage among HCP that 

outweigh its burden. As discussed in 

our proposal to adopt this measure, HCP 

vaccination can potentially reduce 

illness that leads to work absence and 

limit disruptions to care (86 FR 19502). 

The CDC has emphasized that health 

care settings can be high-risk places for 

COVID–19 exposure and 

transmission.112 In these settings, 

COVID–19 can spread between health 

care personnel (HCP) and patients, or 

from patient to patient given the close 

contact that may occur during the 

provision of care.113

Subsequent to the publication of the 

IPF PPS proposed rule, the CDC 

updated its Science Brief on COVID–19 

Vaccines and Vaccination and observed 

that the growing body of evidence 

indicates that people who are fully 

vaccinated with an mRNA vaccine are 

less likely to have asymptomatic 

infection or to transmit SARS–CoV–2 to 

others. The CDC further noted that the 

studies are continuing on the benefits of 

the Johnson & Johnson/Janssen 

vaccine.114 Therefore we believe that 

vaccination coverage among HCP will 

reduce the risk of contracting COVID–19 

for patients in IPFs, and that IPFs 

reporting this information can help 

patients identify IPFs where they may 

have lower risk of COVID–19 exposure. 

Publishing the HCP vaccination rates 

will be helpful to many patients, 

including those who are at high-risk for 

developing serious complications from 

COVID–19, as they choose IPFs from 

which to seek treatment. 

While we agree with the commenters 

that there is some burden associated 

with reporting this measure (see Section 

(V)(A)(2)(c) of this final rule), we believe 

the benefits of data collection and 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42637 

115http://www.qualityforum.org/Projects/n-r/ 

Population_Health_Prevention/0431_

InfluenzaImmunizationHCPersonnelForm_

CDC.aspx. 116COVID–19 Vaccination Non-LTC Healthcare 

Personnel TOI (cdc.gov). 

reporting on COVID–19 vaccination 

coverage among HCP are sufficient to 

outweigh this burden. In addition, 

commenters are correct in noting that 

when we removed the Influenza 

Vaccination Coverage Among 

Healthcare Personnel (NQF #0431) 

measure from the IPFQR Program in the 

FY 2019 IPF PPS final rule, we observed 

that reporting measure data through the 

NHSN is relatively more burdensome 

for IPFs than for acute care hospitals 

and that this may be especially true for 

independent or freestanding IPFs (83 FR 

38593 through 38595). However, in our 

analysis of facilities that did not receive 

full payment updates for FY 2018 and 

FY 2019 and the reasons these facilities 

did not receive full payment updates we 

observed that 98.24 percent and 99.05 

percent of IPFs respectively, including 

small, independent, and freestanding 

IPFs, successfully reported data for the 

Influenza Vaccination Coverage Among 

Health Care Personnel (NQF #0431) 

measure prior to its removal from the 

IPFQR Program. For the reasons 

outlined above, the COVID–19 

pandemic and associated PHE has had 

a much more significant effect on most 

aspects of society, including the ability 

of the healthcare system to operate 

smoothly, than influenza, making the 

benefits of the COVID–19 Vaccination 

Among HCP measure greater than those 

of the Influenza Vaccination Coverage 

Among Health Care Personnel (NQF 

#0431) measure. 

Comment: Other commenters 

expressed concern that facilities face 

duplicative reporting requirements 

given that other agencies are requiring 

reporting through systems other than 

NHSN, such as the HHS TeleTracking 

site. A few of these commenters 

recommended that CMS use the 

TeleTracking site for data reporting and 

consumer information as opposed to 

adopting a quality measure. Other 

commenters recommended that CMS 

sunset TeleTracking and use NHSN for 

reporting COVID–19 vaccination 

coverage data. One commenter 

recommended that CMS collaborate 

with CDC to ensure minimal reporting 

burden. 

Response: We recognize that this 

measure may lead to duplicative 

reporting requirements if facilities 

voluntarily report COVID–19 HCP 

vaccination information to data 

reporting systems other than NHSN, and 

we are collaborating with other HHS 

agencies, including the CDC, to ensure 

minimal reporting burden and to 

eliminate duplicative requirements to 

the extent feasible. 

Comment: Some commenters 

expressed concern about the measure 

specifications leading to increased 

reporting burden. Several of these 

commenters expressed that the 

proposed quarterly reporting of three 

weeks of data (one week per month) is 

excessively burdensome. Other 

commenters expressed concern that the 

measure specifications are not aligned 

with the Influenza Vaccination Coverage 

Among Healthcare Personnel measure 

(NQF #0431), specifically noting that 

the COVID Vaccination Coverage 

Among HCP measure requires data 

elements (such as contraindications) 

that are not required for Influenza 

Vaccination Coverage Among 

Healthcare Personnel measure (NQF 

#0431). One commenter observed that 

including all staff (not just clinical staff 

or staff directly employed by the IPF) 

makes the measure unduly burdensome. 

Another commenter observed that 

tracking location is challenging in large 

organizations with staff that work across 

locations. 

Response: We recognize commenters’ 

concern regarding reporting burden 

associated with the specifications of this 

measure. We believe that, given the 

public health importance of vaccination 

in addressing the COVID–19 PHE, the 

benefits of requiring reporting outweigh 

the burden. We believe that reporting 

these data on a frequent interval would 

increase their value by allowing the 

CDC to better track these important 

public health data while also being a 

valuable quality measure that supports 

consumer choice and IPF improvement 

initiatives. Because the CDC requests 

data reported on a monthly basis for one 

week per month, we believe this is an 

appropriate reporting frequency for our 

quality measure to ensure that IPFs do 

not have duplicative reporting 

requirements to meet the CDC’s need for 

public health data and CMS’ quality 

measure reporting requirements. We 

further note that while we have sought 

to align this measure with the Influenza 

Vaccination Coverage Among HCP 

measure (NQF #0431), each measure 

addresses different public health 

initiatives and therefore complete 

alignment may not be possible. For 

example, because influenza 

vaccinations are provided during the 

influenza season (that is, October 1 

through March 31) these measures have 

different reporting periods. 

Further, we note that while the 

Influenza Vaccination Coverage Among 

HCP measure (NQF #0431) does not 

have a denominator exclusion for HCP 

with contraindications to the influenza 

vaccine, there is a numerator category 

for these HCP. Specifically, the 

numerator description is as follows: 

‘‘HCP in the denominator population 

who during the time from October 1 (or 

when the vaccine became available) 

through March 31 of the following year: 

. . . (b) were determined to have a 

medical contraindication/condition of 

severe allergic reaction to eggs or to 

other component(s) of the vaccine, or a 

history of Guillain-Barre Syndrome 

within 6 weeks after a previous 

influenza vaccination . . .’’ 115 We 

believe that this numerator element 

requires the IPF to track HCP’s 

contraindications to the influenza 

vaccination. Therefore, we disagree with 

the commenter’s statement that the 

COVID–19 Vaccination Coverage 

Among HCP measure is more 

burdensome than the Influenza 

Vaccination Coverage Among HCP 

measure due to requiring IPFs to track 

HCP’s contraindications to the vaccine. 

Finally, we note that CDC’s guidance 

for entering data requires submission of 

HCP count at the IPF level 116 and the 

measure requires reporting consistent 

with that guidance. We proposed the 

reporting schedule of monthly reporting 

of data from only one week a month to 

provide COVID–19 vaccination coverage 

data on a more timely basis than annual 

influenza vaccination coverage (NQF 

#0431) while also reducing burden on 

facilities of weekly reporting which has 

been the reporting cycle for many 

COVID–19-related metrics during the 

pandemic. As described in response to 

previous commenters, we believe that 

the public health benefits to having 

these data available are high, and that 

they therefore outweigh the burden of 

reporting for systems with multiple 

facilities or locations. In summary, we 

recognize that there may be some 

elements of the measure specifications 

that increase burden for some IPFs, 

however given the impact that the 

COVID–19 PHE has had on society and 

the healthcare system, we believe that 

the benefits outweigh this reporting 

burden. 

Comment: Some commenters 

expressed concern that having some 

vaccinations require two doses creates 

undue reporting burden for IPFs. One 

commenter recommended modelling 

this measure on the measure under 

consideration for patient vaccination 

coverage within the Merit-Based 

Incentive Payment System (MIPS) 

program which would require reporting 

based on receipt of one dose, as opposed 

to requiring reporting on receipt of a full 

course of the vaccine. Some commenters 


lotter on DSK11XQN23PROD with RULES5
42638 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

117https://www.fda.gov/vaccines-blood-biologics/ 

vaccines/emergency-use-authorization-vaccinesexplained. 

118CDC COVID Data Tracker. 

119https://www.fda.gov/emergency-preparednessand-response/coronavirus-disease-2019-covid-19/ 

pfizer-biontech-covid-19-vaccine, https://

www.fda.gov/emergency-preparedness-andresponse/coronavirus-disease-2019-covid-19/ 

moderna-covid-19-vaccine, https://www.fda.gov/ 

emergency-preparedness-and-response/ 

coronavirus-disease-2019-covid-19/janssen-covid19-vaccine. 

expressed concern that because it can 

take up to 28 days for an individual to 

be fully vaccinated, requiring reporting 

for HCP who have worked only one day 

of the reporting period is burdensome or 

that this disparately affects facilities 

without access to the one-dose vaccine. 

Response: We believe that it is 

appropriate to require data on HCP who 

have received complete COVID–19 

vaccination courses, because an IPF has 

more long-term and regular contact with 

the HCP who work there than an 

ambulatory care provider, such as those 

being evaluated under the MIPS 

Program, has with their patient 

population. This gives the IPF more 

ability to track and encourage HCP to 

receive their complete vaccination 

course. 

We recognize that since a complete 

vaccination course could take up to 28 

days, some IPFs may initially appear to 

have lower performance than others 

(based on having access to two dose 

vaccinations as opposed to one dose 

vaccination). However, we believe that 

with the reporting frequency these 

providers should show rapid 

improvement as their staff become fully 

vaccinated. We note that given the 

highly infectious nature of the COVID– 

19 virus, we believe it is important to 

encourage all personnel within the IPF, 

regardless of patient contact, role, or 

employment type, to receive the 

COVID–19 vaccination to prevent 

outbreaks within the IPF which may 

affect resource availability and have a 

negative impact on patient access to 

care. 

Comment: Some commenters 

recommended deferring measurement of 

vaccine coverage among HCP until there 

is at least one vaccine that has received 

full FDA approval (as opposed to an 

EUA). A few commenters expressed 

concern that the long-term effects of the 

vaccines are unknown and that some 

HCP concerned about the risk of serious 

adverse events; one commenter further 

expressed concerns regarding the rapid 

development and EUA timelines. A few 

commenters expressed concerns 

regarding HCP being unwilling to 

receive a vaccine which has not 

received full FDA approval. 

Response: We support widespread 

vaccination coverage, and note that in 

issuing the EUAs for these vaccines 

FDA has established that the known and 

potential benefits of these vaccines 

outweigh the known and potential 

risks.117 Furthermore, as July 15, 2021, 

more than 336,000,000 doses have been 

administered in the United States.118

Although COVID–19 vaccines are 

authorized for emergency use prevent 

COVID–19 and serious health outcomes 

associated with COVID–19, including 

hospitalization and death,119 we 

understand that some HCP may be 

concerned about receiving the COVID– 

19 vaccine prior to the vaccine receiving 

full FDA approval. We also understand 

that some HCP may be concerned about 

long-term effects. We note that the 

COVID–19 Vaccination Coverage 

Among HCP measure does not require 

HCP to receive the vaccination, nor does 

this measure reward or penalize IPFs for 

the rate of HCP who have received a 

COVID–19 vaccine. The COVID–19 

Vaccination Coverage Among HCP 

measure requires IPFs to collect and 

report COVID–19 vaccination data that 

would support public health tracking 

and provide beneficiaries and their 

caregivers information to support 

informed decision making. Therefore, 

we believe that it is appropriate to 

collect and report these data as soon as 

possible. 

Comment: One commenter observed 

that there are interventions through 

which an IPF can promote vaccination 

coverage, such as by removing barriers 

to access (through means such as 

extended vaccine clinic hours). This 

commenter recommended encouraging 

these interventions as opposed to 

promoting vaccination coverage among 

HCP by adopting the COVID–19 

Vaccination Coverage Among HCP 

measure. 

Response: We agree with the 

commenter that there are interventions 

through which an IPF can increase 

vaccination coverage by reducing 

barriers to access. However, we believe 

that it is appropriate to propose this 

measure for the IPFQR Program to 

encourage such interventions by 

collecting data on vaccination coverage 

among HCP. We believe that vaccination 

is an important health intervention that 

can protect the health of vulnerable 

patients and the availability of the 

healthcare system (that is, limiting the 

number of HCP absent from work due to 

illness to ensure that patients have 

access to care). 

Comment: Some commenters 

expressed the belief that it is 

inappropriate to use IPF payment 

policies to drive vaccination coverage 

among HCP. Some commenters 

expressed concern that this measure 

could lead facilities to mandate vaccines 

for staff, with potential unintended 

consequences (specifically, staff quitting 

or legal risk for facilities for staff 

experiencing adverse events). One 

commenter expressed the belief that the 

tie to public reporting and potentially 

IPF payment is an indirect vaccine 

mandate. 

Several commenters recommended 

CMS not consider this measure for payfor-reporting because state laws 

regarding mandates vary and therefore 

could lead to inconsistent performance 

through no fault of facilities. One 

commenter expressed the belief that this 

measure was developed for public 

health tracking and is not appropriate 

for quality assessment. 

Response: We note that this measure 

does not require vaccination coverage 

among HCP at IPFs; it requires IPFs to 

report of COVID–19 vaccination rates. 

Therefore, we believe it is incorrect to 

characterize this measure as a ‘‘vaccine 

mandate.’’ Furthermore, we note that 

the historical national average of 

providers who had received the 

influenza vaccination, as reported on 

the then Hospital Compare website was 

85 percent, 80 percent, and 82 percent 

respectively for the FY 2017, FY 2018, 

and FY 2019 payment determinations 

prior to removal of the Influenza 

Vaccination Coverage among Healthcare 

Personnel measure from the IPFQR 

Program. We do not believe that this 

represents performance that would be 

consistent with a widespread ‘‘vaccine 

mandate’’ and therefore we do not 

believe that a vaccination coverage 

among HCP measure, including the 

COVID–19 Vaccination Coverage among 

HCP measure, inherently leads to 

‘‘vaccine mandates.’’ However, we 

believe that data regarding COVID–19 

vaccination coverage among HCP are 

important to empower patients to make 

health care decisions that are best for 

them. 

Comment: Some commenters 

expressed concern that the measure 

does not fully account for potential 

reasons that HCP may not receive 

COVID–19 vaccinations. One 

commenter recommended expanding 

the exclusions to the measure’s 

calculation, specifically citing religious 

objections as an exclusion category. 

Another commenter observed that there 

is uncertainty about how effective 

vaccines are for certain populations, 

such as those with underlying 

conditions. 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42639 

120https://www.cdc.gov/nhsn/forms/instr/57.220- 

toi-508.pdf. 

121https://www.cdc.gov/coronavirus/2019-ncov/ 

science/science-briefs/fully-vaccinatedpeople.htmla. 

122https://www.cdc.gov/coronavirus/2019-ncov/ 

vaccines/recommendations/underlyingconditions.html. 

123Home—Centers for Medicare & Medicaid 

Services | CMS. 

Response: We recognize that there are 

many reasons, including religious 

objections or concerns regarding an 

individual provider’s specific health 

status, which may lead individual HCP 

to decline vaccination. The CDC’s 

NHSN tool allows facilities to report on 

the number of HCP who were offered a 

vaccination but declined for reasons 

including religious or philosophical 

objections.120 We agree that there is 

uncertainty about effectiveness among 

certain patient populations, including 

those with underlying conditions. The 

CDC has found that there is evidence of 

reduced antibody response to or 

reduced immunogenicity of COVID–19 

mRNA vaccine among some 

immunosuppressed people.121

However, we note that COVID–19 

vaccines may be administered to most 

people with underlying medical 

conditions.122 Therefore, we believe that 

individual HCP who may have 

underlying conditions that could affect 

vaccine efficacy should make the 

decision of whether to receive the 

COVID–19 vaccination in discussion 

with their individual care provider. We 

believe that vaccination coverage rates 

are meaningful data for beneficiaries to 

use in choosing an IPF which can also 

be used for public health tracking. 

Comment: One commenter expressed 

the concern that this may have an 

adverse impact on HCP as it is unclear 

whether in the future individual HCP 

will be required to pay for the 

vaccination themselves. 

Response: We understand the 

commenter’s concerns that individual 

HCP may potentially have to pay for the 

COVID–19 vaccine in the future. In 

alignment with our pledge to put 

patients first in all our programs, we 

believe that it is important to empower 

patients to work with their doctors and 

make health care decisions that are best 

for them.123 This includes the belief that 

HCP should be empowered to work with 

their own healthcare providers to make 

the health care decisions that are best 

for them, based on the totality of their 

circumstances, including potential costs 

to receive the vaccine and their 

increased risks of contracting COVID–19 

based on occupational exposure. 

Comment: Many commenters 

expressed concern that this measure 

should not be adopted until there is 

clarity around the impact of future 

boosters. These commenters also noted 

that booster availability could have an 

impact on vaccination coverage among 

HCP. One commenter specifically 

expressed concern regarding past 

supply chain disruptions and observed 

that similar issues may affect booster 

availability in the future. 

Response: The COVID–19 Vaccination 

Coverage among HCP measure is a 

measure of a completed vaccination 

course (as defined in section IV.E.2.b.(1) 

of the FY 2022 IPF PPS proposed rule 

(86 FR 19502 through 19503) and does 

not address booster shots. Currently, the 

need for COVID–19 booster doses has 

not been established, and no additional 

doses are currently recommended for 

HCP. However, we believe that the 

numerator is sufficiently broad to 

include potential future boosters as part 

of a ‘‘complete vaccination course’’ and 

therefore the measure is sufficiently 

specified to address boosters. We 

acknowledge the potential for supply 

chain disruptions or other factors that 

affect vaccine availability, but we 

believe that the urgency of adopting the 

measure to address the current COVID– 

19 PHE outweighs these potential 

concerns. 

Comment: Some commenters 

expressed that collecting the data to 

report this measure is challenging. 

These commenters observed that 

because, unlike influenza vaccinations, 

HCP have received COVID vaccinations 

from settings outside their places of 

employment, employers may still be 

attaining vaccination records from 

employees. One commenter observed 

that the data for HCP is housed in 

separate systems from those typically 

used for quality reporting. 

Response: We recognize that some 

IPFs may still be obtaining vaccination 

records from their employees and other 

personnel that work within their 

facilities. However, most healthcare 

settings, including IPFs, have been 

reporting COVID–19 data to Federal or 

state agencies for some time and 

therefore have established the 

appropriate workflows or other means 

to obtain these records from employees 

or other personnel that work within the 

IPF. Therefore, we believe that IPFs 

must have the means to obtain the data, 

either directly from HCP or from other 

systems in which these data are housed, 

and that it is appropriate to require IPFs 

to report these data. 

Comment: Another commenter 

expressed concern that the shortened 

performance period for the first year 

may lead to incomplete data. One 

commenter recommended allowing 

voluntary reporting without publicly 

reporting data for the first performance 

year to account for potential data gaps. 

Response: Given that results would be 

calculated quarterly for this measure, 

facilities should show rapid progress as 

they obtain more complete data on 

vaccination coverage for their HCP. 

While we understand the desire for a 

year of voluntary reporting to account 

for potential data gaps, we believe that 

the importance of providing patients 

and their caregivers with data on 

COVID–19 Vaccination Coverage among 

HCP at individual IPFs in a timely 

manner outweighs this concern and 

should be accomplished as soon as 

practical. 

Comment: A few commenters 

expressed concern that due to the delay 

between data collection (which takes 

place during a quarter) and public 

reporting (which follows the reporting 

of the data collected during the quarter, 

the deadline for which is 4.5 months 

after the end of the quarter) the data 

would not be useful by the time they are 

publicly reported either because they 

are too old or because the trajectory of 

the pandemic has changed. One 

commenter opposed public reporting 

until data has been reported for several 

years. 

Response: We believe that it is 

important to make these data available 

as soon as possible. We agree with 

commenters that observe that there is a 

delay between data collection and 

public reporting for this measure, and 

note that such a delay exists for all 

measures in the IPFQR Program. 

However, we believe that the data will 

provide meaningful information to 

consumers in making healthcare 

decisions because the data will be able 

to reflect differences between IPFs in 

COVID–19 vaccination coverage among 

HCP even if the data do not reflect the 

current vaccination rates and we believe 

it will benefit consumers to have these 

data available as early as possible. We 

proposed the shortened reporting period 

for the first performance period to make 

the COVID–19 Vaccination among HCP 

measure data available as quickly as 

possible. 

Comment: One commenter observed 

that the data would not provide 

consumers a complete picture of 

infection control procedures because 

vaccines are only one tactic to prevent 

and control infections. Another 

commenter observed that public 

reporting may lead to comparisons 

between facilities. An additional 

commenter recommended a validation 

process to ensure that consumers can 

rely on the data. 


lotter on DSK11XQN23PROD with RULES5
42640 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

124COVID–19 Vaccination Non-LTC Healthcare 

Personnel TOI (cdc.gov). 

Response: While we recognize that 

the data may not fully represent all 

activities to prevent and control 

infections, we believe that the data 

would be useful to consumers in 

choosing IPFs, including making 

comparisons between facilities. We note 

that we do not currently have a 

validation process for any measures in 

the IPFQR Program and refer readers to 

section IV.J.3 of this final rule where we 

discuss considerations for a validation 

program for the IPFQR Program. 

Comment: Some commenters 

recommended deferring the measure 

until it has been fully tested and NQF 

endorsed. One commenter observed that 

the MAP reviewed the measure concept, 

not the full measure, and therefore it is 

premature to include it in the IPFQR 

Program without further review. 

Another commenter observed that such 

rapid measure adoption may set a 

precedent for future rapid measure 

adoption. 

Response: We believe that given the 

current COVID–19 PHE, it is important 

to adopt this measure as quickly as 

possible to allow tracking and reporting 

of COVID–19 Vaccination Coverage 

Among HCP in IPFs. This tracking 

would provide consumers with 

important information. We refer readers 

to FY 2022 IPF PPS proposed rule 

where we discuss our consideration of 

NQF endorsed measures on the topic of 

COVID–19 vaccination coverage among 

healthcare personnel for additional 

information (86 FR 19503 through 

19504). We note that the MAP had the 

opportunity to review and provide 

feedback on the full measure in the 

March 15th meeting. The CDC, in 

collaboration with CMS, is planning to 

submit the measure for consideration in 

the NQF Fall 2021 measure cycle. 

Finally, we evaluate all measures on a 

case-by-case basis and therefore the 

pace at which we propose to adopt one 

measure is dependent on the measure 

and the purpose for adopting it. 

Comment: One commenter requested 

clarification for the reporting frequency. 

Response: We recognize that the 

proposed required frequency for 

reporting, may have been unclear 

because we referred to ‘‘annual 

reporting’’ periods two times in the 

proposed rule. Specifically, we 

referenced annual reporting periods in 

the first paragraph of section IV.E.2.c 

(86 FR 19504) and in our burden 

estimate for the measure (86 FR 19519). 

Our description of data submission 

under IV.J.2.a in which we stated that 

facilities would be required to report the 

vaccination data to the NHSN for at 

least one week each month and that if 

they reported more than one week, the 

most recent week’s data would be used 

(86 FR 19513) is correct. In that section, 

we further noted that the CDC would 

calculate a single quarterly result for 

summarizing the data reported monthly. 

In summary, the measure would require 

monthly reporting of at least one week’s 

data per month. This would be 

calculated into quarterly results. We 

note that IPFs are required to report to 

NHSN sufficient data (that is, 

vaccination data for at least one week in 

each month per quarter) to calculate 

four quarterly results per year, except 

for the first performance period which 

depends on only one quarter of data (the 

vaccination data for at least one week in 

each month in Q1 of FY 2022). While 

IPFs can report data to the NHSN at any 

time, they must report by 4.5 months 

following the preceding quarter for the 

purposes of measure calculation. For the 

first performance period for this 

measure (that is Q1 of FY 2022), 4.5 

months following the end of the quarter 

is May 15, 2022. 

Comment: One commenter requested 

clarification on which provider types 

are considered healthcare personnel. 

Response: The provider types that are 

considered healthcare personnel, along 

with the specifications for this measure, 

are available at https://www.cdc.gov/ 

nhsn/nqf/index.html. The categories of 

HCP included in this measure are 

ancillary services employees; nurse 

employees; aide, assistant, and 

technician employees; therapist 

employees; physician and licensed 

independent practitioner employees; 

and other HCP. For more detail about 

each of these categories we refer readers 

to the Table of Instructions for 

Completion of the Weekly Healthcare 

Personnel COVID–19 Cumulative 

Vaccination Summary Form for NonLong-Term Care Facilities available at 

https://www.cdc.gov/nhsn/forms/instr/ 

57.220-toi-508.pdf. 

Comment: One commenter observed 

that the definition of ‘‘location’’ for 

measure calculation is unclear. 

Response: CDC’s guidance for 

entering data requires submission of 

HCP count at the IPF level, not at the 

location level within the IPF.124

After consideration of the public 

comments, we are finalizing the COVD– 

19 Vaccination Coverage Among 

Healthcare Personnel measure as 

proposed for the FY 2023 payment 

determination and subsequent years. 

3. Follow-Up After Psychiatric 

Hospitalization (FAPH) Measure for the 

FY 2024 Payment Determination and 

Subsequent Years 

a. Background 

We proposed one new measure, 

Follow-Up After Psychiatric 

Hospitalization (FAPH), for the FY 2024 

payment determination and subsequent 

years. The FAPH measure would use 

Medicare fee-for-service (FFS) claims to 

determine the percentage of inpatient 

discharges from an inpatient psychiatric 

facility (IPF) stay with a principal 

diagnosis of select mental illness or 

substance use disorders (SUDs) for 

which the patient received a follow-up 

visit for treatment of mental illness or 

SUD. Two rates would be calculated for 

this measure: (1) The percentage of 

discharges for which the patient 

received follow-up within 7 days of 

discharge; and (2) the percentage of 

discharges for which the patient 

received follow-up within 30 days of 

discharge. 

The FAPH measure is an expanded 

and enhanced version of the Follow-Up 

After Hospitalization for Mental Illness 

(FUH, NQF #0576) measure currently in 

the IPFQR Program. We proposed to 

adopt the FAPH measure and replace 

the FUH measure and refer readers to 

section IV.F.2.d of the FY 2022 IPF PPS 

proposed rule for our proposal to 

remove the FUH measure contingent on 

adoption of the FAPH measure (86 FR 

19510). The FUH (NQF #0576) measure 

uses Medicare FFS claims to determine 

the percentage of inpatient discharges 

from an IPF stay with a principal 

diagnosis of select mental illness 

diagnoses for which the patient received 

a follow-up visit for treatment of mental 

illness, and it excludes patients with 

primary substance use diagnoses. 

During the 2017 comprehensive review 

of NQF #0576, the NQF Behavioral 

Health Standing Committee (BHSC) 

recommended expanding the measure 

population to include patients 

hospitalized for drug and alcohol 

disorders, because these patients also 

require follow-up care after they are 

discharged. 

In 2018, CMS began development of 

a measure to expand the IPFQR FUH 

population to include patients with 

principal SUD diagnoses to address the 

NQF BHSC recommendation and the 

CMS Meaningful Measures priority to 

promote treatment of SUDs. The FAPH 

measure would expand the number of 

discharges in the denominator by about 

35 percent over the current FUH 

measure by adding patients with SUD or 

dementia as principal diagnoses 

(including patients with any 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42641 

125Tong, L., Arnold, T., Yang, J., Tian, X., 

Erdmann, C., & Esposito, T. (2018). The association 

between outpatient follow-up visits and all-cause 

non-elective 30-day readmissions: A retrospective 

observational cohort study. PloS one, 13(7), 

e0200691. https://doi.org/10.1371/ 

journal.pone.0200691. 

126Terman, S. W., Reeves, M. J., Skolarus, L. E., 

& Burke, J. F. (2018). Association Between Early 

Outpatient Visits and Readmissions After Ischemic 

Stroke. Circulation. Cardiovascular quality and 

outcomes, 11(4), e004024. https://doi.org/10.1161/ 

CIRCOUTCOMES.117.004024. 

127First Outpatient Follow-Up After Psychiatric 

Hospitalization: Does One Size Fit All? (2014). 

Psychiatric Services, 66(6), 364–372. https://

doi.org/10.1176/appi.ps.201400081. 

128Terman, S. W., Reeves, M. J., Skolarus, L. E., 

& Burke, J. F. (2018). Association Between Early 

Outpatient Visits and Readmissions After Ischemic 

Stroke. Circulation. Cardiovascular quality and 

outcomes, 11(4), e004024. https://doi.org/10.1161/ 

CIRCOUTCOMES.117.004024. 

129 Jackson, C., Shahsahebi, M., Wedlake, T., & 

DuBard, C. A. (2015). Timeliness of outpatient 

follow-up: An evidence-based approach for 

planning after hospital discharge. Annals of family 

medicine, 13(2), 115–122. https://doi.org/10.1370/ 

afm.1753. 

130Hernandez, A. F., Greiner, M. A., Fonarow, G. 

C., Hammill, B. G., Heidenreich, P. A., Yancy, C. 

W., Peterson, E. D., & Curtis, L. H. (2010). 

Relationship between early physician follow-up 

and 30-day readmission among Medicare 

beneficiaries hospitalized for heart failure. JAMA, 

303(17), 1716–1722. https://doi.org/10.1001/ 

jama.2010.533. 

131Nadereh Pourat, Xiao Chen, Shang-Hua Wu 

and Anna C. Davis. Timely Outpatient Follow-up Is 

Associated with Fewer Hospital Readmissions 

among Patients with Behavioral Health Conditions. 

The Journal of the American Board of Family 

Medicine. May 2019, 32 (3) 353–361; DOI: https:// 

doi.org/10.3122/jabfm.2019.03.180244. 

132 Germack, H.D., et al. (2019, January). 

Association of comorbid serious mental illness 

diagnosis with 30-day medical and surgical 

readmissions. JAMA Psychiatry. 

133First Outpatient Follow-Up After Psychiatric 

Hospitalization: Does One Size Fit All? (2014). 

Psychiatric Services, 66(6), 364–372. https://

doi.org/10.1176/appi.ps.201400081. 

134First Outpatient Follow-Up After Psychiatric 

Hospitalization: Does One Size Fit All? (2014). 

Psychiatric Services, 66(6), 364–372. https://

doi.org/10.1176/appi.ps.201400081. 

135Benjenk, I., & Chen, J. (2018). Effective mental 

health interventions to reduce hospital readmission 

rates: A systematic review. Journal of hospital 

management and health policy, 2, 45. https://

doi.org/10.21037/jhmhp.2018.08.05. 

136American Psychiatric Association. Practice 

guideline for the treatment of patients with 

substance use disorders. 2010. http://

psychiatryonline.org/pb/assets/raw/sitewide/ 

practice_guidelines/guidelines/substanceuse.pdf. 

137 Kurdyak P, Vigod SN, Newman A, Giannakeas 

V, Mulsant BH, Stukel T. Impact of Physician 

Follow-Up Care on Psychiatric Readmission Rates 

in a Population-Based Sample of Patients With 

Schizophrenia. Psychiatr Serv. 2018;69(1):61–68. 

doi: 10.1176/appi.ps.201600507. 

138Marcus SC, Chuang CC, Ng-Mak DS, Olfson M. 

Outpatient follow-up care and risk of hospital 

readmission in schizophrenia and bipolar disorder. 

Psychiatr Serv. 2017;68(12):1239–1246. doi: 

10.1176/appi.ps.201600498. 

139Batscha C, McDevitt J, Weiden P, Dancy B. 

The effect of an inpatient transition intervention on 

attendance at the first appointment post discharge 

from a psychiatric hospitalization. J Am Psychiatr 

Nurses Assoc. 2011;17(5):330–338. doi: 10.1177/ 

1078390311417307. 

140Agarin T, Okorafor E, Kailasam V, et al. 

Comparing kept appointment rates when calls are 

made by physicians versus behavior health 

technicians in inner city hospital: literature review 

and cost considerations. Community Ment Health J. 

2015;51(3):300–304. doi: 10.1007/s10597–014– 

9812-x. 

141Olfson M, Mechanic D, Boyer CA, Hansell S. 

Linking inpatients with schizophrenia to outpatient 

care. Psychiatr Serv. 1998;49(7):911–917. doi: 

10.1176/ps.49.7.911. Quality AFHRA. 2017 

National Healthcare Quality and Disparities Report. 

Rockville, MD: Services USDoHaH; 2018. 

142https://data.cms.gov/provider-data/archiveddata/hospitals. 

combination of SUD, dementia, or 

behavioral health disorders), 

populations that also benefit from 

timely follow-up care. 

Furthermore, compared to the criteria 

for provider type in the current FUH 

measure, the FAPH measure does not 

limit the provider type for the follow-up 

visit if it is billed with a diagnosis of 

mental illness or SUD. During the 

measure’s testing, the most frequent 

provider types for the FAPH measure 

were family or general practice 

physicians, internal medicine 

physicians, nurse practitioners, and 

physician assistants. The technical 

expert panel (TEP) convened by our 

contractor agreed that these provider 

types should be credited by the measure 

for treating mental illness and SUD and 

confirmed that this is aligned with 

integrated care models that aim to treat 

the whole patient. The TEP further 

noted that in areas where there are 

shortages of mental health or SUD 

clinicians, other types of providers are 

often the only choice for follow-up 

treatment. Allowing visits to these types 

of providers to count towards the 

numerator allows the measure to 

capture the rates of appropriate followup care more accurately in areas with 

provider shortages. 

Performance on the FAPH measure 

indicates that follow-up rates for 

patients hospitalized with mental 

illness or SUD are less than optimal and 

that room for improvement is ample. 

The clinical benefits of timely follow-up 

care after hospitalization, including 

reduced risk of readmission and 

improved adherence to medication, are 

well-documented in the published 

literature.125 126 127 128 129 130 131

Behavioral health patients in 

particular have a number of risk factors 

that underscore the need for timely 

follow-up and continuity of care: 

Behavioral health patients have higher 

baseline hospitalization rates, higher 

hospital readmission rates, and higher 

health care costs as compared with the 

general population of patients.132 133

Among patients with serious mental 

illness, 90 percent have comorbid 

clinical conditions such as 

hypertension, cardiovascular disease, 

hyperlipidemia, or diabetes.134 Among 

patients hospitalized for general 

medical conditions, those who also have 

a mental illness are 28 percent more 

likely to be readmitted within 30 days 

than their counterparts without a 

psychiatric comorbidity.135 The high 

prevalence of clinical comorbidities 

among behavioral health patients, 

combined with the compounding effect 

of mental illness on patients with 

general medical conditions, suggests 

that behavioral health patients are 

uniquely vulnerable and supports the 

intent of the measure to increase followup after hospitalization. 

In addition, clinical practice 

guidelines stress the importance of 

continuity of care between settings for 

patients with mental illness and SUD. 

For the treatment of SUD patients, the 

2010 guidelines of the American 

Psychiatric Association (APA) state: ‘‘It 

is important to intensify the monitoring 

for substance use during periods when 

the patient is at a high risk of relapsing, 

including during the early stages of 

treatment, times of transition to less 

intensive levels of care, and the first 

year after active treatment has 

ceased.’’ 136 This statement is 

accompanied by a grade of [I], which 

indicates the highest level of APA 

endorsement: ‘‘recommended with 

substantial clinical evidence.’’ 

Evidence supports that outpatient 

follow-up care and interventions after 

hospital discharges are associated with 

a decreased risk of readmissions for 

patients with mental illness.137 138 IPFs 

can influence rates of follow-up care for 

patients hospitalized for mental illness 

or SUD. Three studies reported that 

with certain interventions—such as predischarge transition interviews, 

appointment reminder letters or 

reminder phone calls, meetings with 

outpatient clinicians before discharge, 

and meetings with inpatient staff 

familiar to patients at the first postdischarge appointment—facilities 

achieved 30-day follow-up rates of 88 

percent or more.139 140 141 This is 

substantially higher than the national 

rate of about 52 percent observed in the 

current FUH measure for Medicare FFS 

discharges between July 1, 2016, and 

June 30, 2017.142 Medicare FFS data 

from July 1, 2016, to June 30, 2017, 

show the national 7-day follow-up rate 

to be 35.5 percent and the 30-day rate 

to be 61.0 percent. These data reveal 

wide variation in follow-up rates across 

facilities, with a 16.9 percent absolute 

difference between the 25th and 75th 


lotter on DSK11XQN23PROD with RULES5
42642 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

143https://nhqrnet.ahrq.gov/inhqrdr/resources/ 

methods#Benchmarks. 

144Quality AfHRa. 2017 National Healthcare 

Quality and Disparities Report. Rockville, MD: 

Services USDoHaH; 2018. 

145https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/MMS/ 

Downloads/IPF_-Follow-Up-After-PsychiatricHospitalization_Public-Comment-Summary.pdf. 

146Mathematica. FAPH public comment 

summary. April 2019. 

147For additional information on reliability tests 

see http://www.qualityforum.org/Measuring_

Performance/Improving_NQF_Process/Measure_

Testing_Task_Force_Final_Report.aspx. 

percentiles for the 7-day rate and a 17.4 

percent absolute difference for the 30- 

day rate. If all facilities achieved the 

benchmark follow-up rates for their 

Medicare FFS patients (as calculated 

using the AHRQ Achievable 

Benchmarks of Care method,) 143 53,841 

additional discharges would have a 7- 

day follow-up visit, and 47,552 would 

have a 30-day follow-up visit.144

During the development process, we 

used the CMS Quality Measures Public 

Comment Page to ask for public 

comments on the measure.145 We 

accepted public comments from January 

25, 2019, to February 13, 2019. During 

this period, we received comments from 

29 organizations or individuals. Many 

commenters acknowledged the 

importance of developing a measure 

that assesses acute care providers for 

follow-up post-hospitalization. Some 

commenters expressed skepticism about 

the measure’s appropriateness as a tool 

for evaluating the performance of 

discharging IPFs due to factors beyond 

the IPFs’ control that can affect whether 

a patient receives timely post-discharge 

follow-up care. Ten stakeholders 

expressed support for the measure based 

on the expanded list of qualifying 

diagnoses in the denominator and the 

inclusion of more patients who could 

benefit from post-discharge follow-up 

visits.146

We reviewed the comments we 

received with the TEP, whose members 

shared similar feedback regarding the 

importance of follow-up for patients 

with both mental health diagnoses and 

substance use disorders, as well as 

concerns about the ability of IPFs to 

influence follow-up care. We agree with 

commenters that some factors that 

influence follow-up are outside of an 

IPF’s control. However, as described 

previously in this section, we believe 

that there are interventions (such as predischarge transition interviews, 

appointment reminder letters or 

reminder phone calls, meetings with 

outpatient clinicians before discharge, 

and meetings with inpatient staff 

familiar to patients at the first postdischarge appointment) that allow 

facilities to improve their follow-up 

adherence. We remain committed to 

monitoring follow-up to improve health 

outcomes and view this measure as an 

expansion of our ability to measure 

appropriate follow-up care established 

by FUH. 

b. Overview of Measure 

(1). Measure Calculation 

The FAPH measure would be 

calculated by dividing the number of 

discharges that meet the numerator 

criteria by the number that meet the 

denominator criteria. Two rates are 

reported for this measure: the 7-day rate 

and the 30-day rate. 

(a) Numerator 

The first rate that would be reported 

for this measure includes discharges 

from an IPF that are followed by an 

outpatient visit for treatment of mental 

illness or SUD within 7 days. The 

second rate reported for this measure 

would include discharges from an IPF 

that are followed by an outpatient visit 

for treatment of mental illness or SUD 

within 30 days. Outpatient visits are 

defined as outpatient visits, intensive 

outpatient encounters, or partial 

hospitalization and are defined by the 

Current Procedural Terminology (CPT), 

Healthcare Common Procedure Coding 

System (HCPCS), and Uniform Billing 

(UB) Revenue codes. Claims with codes 

for emergency room visits do not count 

toward the numerator. 

(b) Denominator 

The denominator includes discharges 

paid under the IPF prospective payment 

system during the performance period 

for Medicare FFS patients with a 

principal diagnosis of mental illness or 

SUD. Specifically, the measure includes 

IPF discharges for which the patient 

was: 

• Discharged with a principal 

diagnosis of mental illness or SUD that 

would necessitate outpatient follow-up 

care, 

• Alive at the time of discharge, 

• Enrolled in Medicare Parts A and B 

during the month of the discharge date 

and at least one month after the 

discharge date to ensure that data are 

available to capture the index admission 

and follow-up visits, and 

• Age 6 or older on the date of 

discharge, because follow-up treatment 

for mental illness or SUD might not 

always be recommended for younger 

children. 

The denominator excludes IPF 

discharges for patients who: 

• Were admitted or transferred to 

acute and non-acute inpatient facilities 

within the 30-day follow-up period, 

because admission or transfer to other 

institutions could prevent an outpatient 

follow-up visit from taking place, 

• Were discharged against medical 

advice, because the IPF could have 

limited opportunity to complete 

treatment and prepare for discharge, 

• Died during the 30-day follow-up 

period, or 

• Use hospice services or elect to use 

a hospice benefit at any time during the 

measurement year regardless of when 

the services began, because hospice 

patients could require different followup services. 

The FAPH measure differs from FUH 

mostly in the expansion of the measure 

population to include SUD and other 

mental health diagnoses in the 

measure’s denominator, but it includes 

some additional differences: 

• The FAPH measure simplifies the 

exclusion of admission or transfer to 

acute or non-acute inpatient facilities 

within 30 days after discharge by 

aligning with the HEDIS® Inpatient Stay 

Value Set used in both the HEDIS® FUH 

and the HEDIS® Follow-Up After 

Emergency Department Visit for Alcohol 

and Other Drug Abuse or Dependence 

(FUA) measures to identify acute and 

non-acute inpatient stays. A discharge is 

excluded from the FAPH measure if it 

is followed by an admission or a transfer 

with one of the codes in the value set. 

• The FAPH measure uses Medicare 

UB Revenue codes (rather than inpatient 

discharge status code, which the FUH 

measure uses) to identify discharge or 

transfer to other health care institutions. 

This is to align better with the intent of 

the HEDIS® FUH and HEDIS® FUA 

measures. 

• The FAPH measure allows mental 

illness or SUD diagnoses in any position 

on the follow-up visit claim to count 

toward the numerator and does not 

require that it be in the primary position 

as the FUH measure does. 

(2) Measure Reliability and Validity 

In 2019, CMS used the final measure 

specifications to complete reliability 

and validity testing, which revealed that 

the FAPH measure provides reliable and 

valid IPF-level rates of follow-up after 

psychiatric hospitalization. We 

evaluated measure reliability based on a 

signal-to-noise analysis,147 in which a 

score of 0.0 implies that all variation is 

attributed to measurement error (noise), 

and a score of 1.0 implies that all 

measure score variation is caused by a 

real difference in performance across 

IPFs. Using that approach, we 

established a minimum denominator 

size of 40 discharges to attain an overall 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42643 

148Face validity is defined as a subjective 

determination by experts that the measure appears 

to reflect quality of care, done through a systematic 

and transparent process, that explicitly addresses 

whether performance scores resulting from the 

measure as specified can be used to distinguish 

good from poor quality, with degree of consensus 

and any areas of disagreement provided/discussed: 

https://www.qualityforum.org/Measuring_

Performance/Scientific_Methods_Panel/Docs/ 

Evaluation_Guidance.aspx. 

149 If data availability or operational issues 

prevent use of this performance period, we would 

announce the updated performance period through 

subregulatory communications including 

announcement on a CMS website and/or on our 

applicable listservs. 

reliability score of 0.7 for both the 7-day 

and the 30-day rate. These analyses 

revealed that the measure can reliably 

distinguish differences in performance 

between IPFs with adequate 

denominator size. 

We evaluated the validity of the 

measure based on its correlation to two 

conceptually related measures in the 

IPFQR Program: The 30-Day All-Cause 

Unplanned Readmission After 

Psychiatric Discharge from an IPF (IPF 

Readmission) measure, and the 

Medication Continuation Following 

Inpatient Psychiatric Discharge 

(Medication Continuation) measure. We 

observed a weak negative correlation 

between FAPH and the IPF Readmission 

measure for both 7-day (—0.11) and 30- 

day (—0.18) measure rates. This 

negative correlation is expected because 

a higher score is indicative of better 

quality of care for the FAPH, while a 

lower score is indicative of better 

quality of care for the IPF readmission 

measure (that is, a lower rate of 

unplanned readmissions). High rates of 

follow-up after visits after discharge and 

low rates of unplanned readmissions 

both indicate good care coordination 

during the discharge process. We 

observed a weak positive correlation 

between the 7-day FAPH measure rate 

and the Medication Continuation 

measure (0.32), and between the 30-day 

FAPH measure rate and the Medication 

Continuation measure (0.42). This result 

is expected because for both the FAPH 

and the Medication Continuation 

measures higher scores are indicative of 

better-quality care. Follow-up visits 

after discharge and continuation of 

medication after discharge both indicate 

good care coordination during the 

discharge process. After reviewing these 

results and the proposed measure 

specifications, all 13 TEP members who 

were present agreed that the measure 

had face validity.148

(3) Review by the Measure Applications 

Partnership and NQF 

Under section 1890A(a)(2) of the Act, 

this measure was included in a publicly 

available document: ‘‘List of Measures 

Under Consideration for December 1, 

2019,’’ available at: https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/QualityMeasures/ 

Downloads/Measures-underConsideration-List-for-2018.pdf. 

On January 15, 2020, the MAP 

Coordinating Committee rated the 

measure as ‘‘Conditional Support for 

Rulemaking’’ contingent upon NQF 

endorsement. We submitted the 

measure to the NQF for endorsement in 

the spring 2020 cycle. However, some 

members of the NQF Behavioral Health 

and Substance Use Standing Committee 

were concerned about the measure’s 

exclusions for patients who died during 

the 30-day follow-up period or who 

were transferred. In addition, some 

members objected to combining persons 

with a diagnosis of SUD and those with 

a diagnosis for a mental health disorder 

into a single measure of follow-up care. 

Therefore, the NQF declined to endorse 

this measure. We noted that the 

exclusions for patients who died or who 

were admitted or transferred to an acute 

or non-acute inpatient facility during 

the 30-day follow up period align with 

the FUH measure currently in the 

IPFQR Program. 

Section 1886(s)(4)(D)(ii) of the Act 

authorizes the Secretary to specify a 

measure for the IPFQR Program that is 

not endorsed by NQF. The exception to 

the requirement to specify an endorsed 

measure states that in the case of a 

specified area or medical topic 

determined appropriate by the Secretary 

for which a feasible and practical 

measure has not been endorsed by the 

entity with a contract under section 

1890(a) of the Act, the Secretary may 

specify a measure that is not so 

endorsed as long as due consideration is 

given to measures that have been 

endorsed or adopted by a consensus 

organization. 

The FAPH measure is not NQF 

endorsed. We have reviewed NQFendorsed and other consensus-endorsed 

measures related to follow-up care and 

identified the FUH measure (NQF 

#0576) currently in the IPFQR Program 

and Continuity of Care after Inpatient or 

| Residential Treatment for SUD (NQF 

#3453), we believe that the FAPH 

measure is an improvement over the 

current FUH measure and over the 

Continuity of Care after Inpatient or 

Residential Treatment of Substance Use 

Disorder because we believe that it is 

important to ensure appropriate access 

to follow-up treatment for the largest 

patient population possible and the 

FAPH measure applies to a larger 

patient population than either of the 

measures we considered. Therefore, we 

proposed to adopt the FAPH measure 

described in this section for the FY 2024 

payment determination and subsequent 

years. 

c. Data Collection, Submission and 

Reporting 

FAPH uses Medicare FFS Part A and 

Part B claims that are received by 

Medicare for payment purposes. The 

measure links Medicare FFS claims 

submitted by IPFs and subsequent 

outpatient providers for Medicare FFS 

IPF discharges. Therefore, no additional 

data collection would be required from 

IPFs. For additional information on data 

submission for this measure, see section 

IV.J.2.b of this final rule. The 

performance period used to identify 

cases in the denominator is 12 months. 

Data from this period and 30 days 

afterward are used to identify follow-up 

visits in the numerator. Consistent with 

other claims-based measures in the 

IPFQR Program, the performance period 

for this measure is July 1 through June 

30. For example, for the FY 2024 

payment determination, the 

performance period would include 

discharges between July 1, 2021 and 

June 30, 2022.149

We invited public comment on our 

proposal to add a new measure, FollowUp After Psychiatric Hospitalization, to 

the IPFQR Program, beginning with the 

FY 2024 payment determination and 

subsequent years. 

We received the following comments 

on our proposal. 

Comment: Many commenters 

supported the adoption of the FAPH 

measure. Some commenters expressed 

that the expanded cohort would 

improve the measure’s value. Some 

commenters expressed that expanding 

the eligible provider types for the 

follow-up visit would improve care 

because of the shortage of psychiatrists. 

A few commenters observed that care 

transitions are important, and that 

outpatient follow-up serves to improve 

the value of the inpatient services 

provided. One commenter expressed 

that adoption of this measure is timely 

due to the increased behavioral health 

needs associated with the COVID–19 

pandemic. One commenter 

recommended using this measure at the 

health system level to better identify 

care coordination, access, and referral 

network adequacy. 

Response: We thank these 

commenters for their support. We agree 

that the expanded definitions would 

improve the measure’s applicability and 

capture more follow-up visits. 

Regarding the commenter’s 


lotter on DSK11XQN23PROD with RULES5
42644 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

recommendation on using this measure 

at the health system level, we believe 

the commenter is recommending 

adopting this measure to evaluate 

performance of regional or local health 

systems (such as those affiliated with 

large hospital networks). We note that 

the IPFQR Program applies to Medicare 

participating freestanding psychiatric 

hospitals and psychiatric units and we 

believe that health systems that have 

IPFs that participate in the IPFQR 

Program would find this measure useful 

as they assess access and referral 

network adequacy within their systems. 

Comment: Some commenters 

observed that some follow-ups, 

especially for substance use disorders, 

may not be identifiable in claims. A few 

commenters specifically noted that 

some providers who often provide 

follow-ups are not covered by Medicare 

(for example, therapists) or that some 

follow-ups may be covered by other 

insurers. These commenters observed 

that this may lead the measure to 

undercount follow-ups provided. A few 

of these commenters did not support 

measure adoption because of this 

undercount. However, one commenter 

that expressed this concern supported 

measure adoption because the 

commenter believes that burden 

reduction associated with claims 

reporting outweighs the potential 

undercounting. 

Response: We acknowledge that, like 

the Follow-Up After Hospitalization for 

Mental Illness (FUH, NQF #0576) 

measure that we proposed to replace 

with the FAPH measure, the FAPH 

measure would not be able to capture 

follow-up visits provided by 

professionals outside of Medicare, or if 

the patient uses another payer or selfpay to cover the patient’s follow-up 

care, which could lead to an 

undercount. However, we believe that 

the data captured by the measure would 

be sufficient to inform consumers and to 

provide data for quality improvement 

initiatives. Further, we agree with the 

commenter that the burden reduction 

associated with using claims-based 

measures outweighs the potential 

undercounting. 

Comment: Some commenters 

expressed concern that this measure 

may be difficult for some IPFs to 

perform well on due to factors outside 

of the IPF’s control. One commenter 

observed that many rural hospitals lack 

community resources and therefore 

cannot refer patients to outpatient 

psychiatrists. Another commenter 

observed that some patients may be 

unwilling to see an outpatient 

psychiatrist. Other commenters 

observed that this measure captures 

patient behavior, not provider actions. 

Some of these commenters observed 

that lack of transportation, access 

barriers, homelessness or other patient 

characteristics outside of the IPF’s 

control may affect performance. Some of 

these commenters expressed preference 

for a process measure that tracks 

whether IPFs performed interventions to 

improve follow-up rates before or 

during discharge. 

Response: We recognize that there is 

regional variation in access to outpatient 

resources and that patients have varying 

comfort levels with different provider 

types. However, we believe that this 

updated measure helps to address some 

of the commenters’ concerns. 

Specifically, we note that this measure 

expands the definition of follow-up to 

include a wider range of outpatient 

providers, including family or general 

practice physicians, internal medicine 

physicians, nurse practitioners, and 

physician assistants. We agree with 

commenters that there are factors that 

influence follow-up that are outside of 

an IPF’s control (including patient 

behavior, lack of transportation, access 

barriers, homelessness, among others). 

As described in the FY 2022 IPF PPS 

proposed rule (86 FR 19504 through 

19505), there are interventions that 

allow facilities to improve their followup adherence. We believe it is 

incumbent upon facilities to identify 

potential barriers to follow-up 

adherence and apply appropriate 

interventions to improve adherence. We 

believe that this measure is preferable to 

a process measure because it provides 

insight into the success of interventions 

by identifying follow-up rates. As 

discussed in the FY 2014 IPPS/LTCH 

PPS final rule (78 FR 50894 through 

50895) and the FY 2022 IPF PPS 

proposed rule in our proposal to adopt 

the FAPH measure (86 FR 19504 

through 19507) we do not expect 100 

percent of patients discharged from IPFs 

to receive follow-up care within 7 or 30 

days of discharge because of factors both 

within and outside of the control of 

facilities such as availability of 

providers in the referral network. 

Comment: Some commenters opposed 

the FAPH measure because it is not 

NQF endorsed and because it was not 

fully supported by the MAP. A few 

commenters observed that the measure 

may undergo changes to achieve NQF 

endorsement which would create 

burden if the measure were in the 

program when these changes occurred. 

Some commenters recommended 

delaying implementation until NQF’s 

concerns are fully addressed. One 

commenter observed that the similar 

NQF-endorsed FUH measure is 

available and therefore CMS has not 

properly considered available consensus 

endorsed measures. 

Response: We appreciate the 

commenters’ concerns about the FAPH 

measure’s lack of NQF endorsement. As 

we stated in the proposed rule, after 

having given due consideration to 

similar measures, FUH measure (NQF 

#0576) and Continuity of Care after 

Inpatient or Residential Treatment for 

SUD (NQF #3453), we believe that the 

FAPH measure is an improvement over 

the FUH measure currently in the 

IPFQR Program (86 FR 19507). The 

FAPH measure expands the number of 

discharges in the denominator by 

adding patients with SUD or dementia, 

populations that also benefit from 

timely follow-up care. We propose 

updates to the IPFQR program measure 

set on an annual basis through the 

rulemaking process. During the measure 

evaluation process, we carefully 

consider the potential burden to 

clinicians, health systems, and patients 

of any updates that are under 

consideration. 

The primary concerns of some NQF 

Behavioral Health and Substance Use 

Standing Committee members with the 

FAPH measure were exclusions for 

patients who died during the 30-day 

follow-up period or who were 

transferred. While we respect the NQF’s 

concerns, we note that these same 

exclusions align with the exclusions in 

the Follow-Up After Hospitalization for 

Mental Illness (FUH, NQF #0576) 

measure which is already NQF 

endorsed, and which we adopted under 

the IPFQR Program in the FY 2014 

IPPS/LTCH PPS final rule. This measure 

has a very similar denominator (78 FR 

50893 through 50895). The clinical 

expert work group and technical expert 

panel convened by our contractor 

supported these exclusions as being 

appropriate for both measures. 

After having given due consideration 

to similar measures, FUH measure (NQF 

#0576) and Continuity of Care after 

Inpatient or Residential Treatment for 

SUD (NQF #3453), we believe that the 

FAPH measure is an improvement over 

the FUH measure which is currently in 

the IPFQR Program, because it includes 

patients with SUD or dementia, 

populations that also benefit from 

timely follow-up care (86 FR 19504 

through 19506). 

Comment: Some commenters 

recommended further research or 

testing. Some commenters 

recommended that CMS continue to 

consider evidence supporting the 

expanded patient cohort. 

Response: We thank commenters for 

these recommendations and will 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42645 

150American Psychiatric Association. Practice 

guideline for the treatment of patients with 

substance use disorders. 2010. http://

psychiatryonline.org/pb/assets/raw/sitewide/ 

practice_guidelines/guidelines/substanceuse.pdf. 

151https://www.cms.gov/medicare/fraud-andabuse/physicianselfreferral. 

continue to evaluate them as part of our 

measure monitoring and evaluation 

process. We believe that the evidence 

cited in our proposal, including the 

evidence supporting the APA grade of 

[I] applied to the 2010 guidelines for the 

treatment of SUD patients that state ‘‘It 

is important to intensify the monitoring 

for substance use during periods when 

the patient is at a high risk of relapsing, 

including during the early stages of 

treatment, times of transition to less 

intensive levels of care, and the first 

year after active treatment has 

ceased’’ 150 is sufficient evidence to 

support measuring follow up after 

hospitalization for SUD. We note that 

because discharge from an IPF is a time 

of transition to less intensive levels of 

care these guidelines apply to discharge 

from an IPF and support the expanded 

patient cohort. 

Comment: One commenter requested 

CMS specifically consider the impact of 

the physician self-referral law 

(commonly referred to as ‘‘the Stark 

Law’’) on an IPF’s ability to ensure 

necessary SUD follow-up care. Some 

commenters recommended that CMS 

evaluate additional risk adjustment for 

social risk factors. One commenter 

further expressed that this measure may 

not be a successful strategy for reducing 

readmissions. Another commenter 

recommended that CMS investigate 

whether FAPH is an appropriate 

replacement for the Alcohol & Other 

Drug Use Disorder Treatment Provided 

or Offered at Discharge and Alcohol & 

Other Drug Use Disorder Treatment at 

Discharge (SUB–3/3a) measure. 

Response: Section 1877 of the Act, 

also known as the physician self-referral 

law: (1) Prohibits a physician from 

making referrals for certain designated 

health services payable by Medicare to 

an entity with which he or she (or an 

immediate family member) has a 

financial relationship, unless an 

exception applies; and (2) prohibits the 

entity from filing claims with Medicare 

(or billing another individual, entity, or 

third party payer) for those referred 

services. A financial relationship is an 

ownership or investment interest in the 

entity or a compensation arrangement 

with the entity.151 We believe that the 

comment regarding the physician selfreferral law relates to compensation 

arrangements between IPFs (which 

qualify as hospitals, and ‘‘entities’’, for 

purposes of the physician self-referral 

law) and physicians who provide postdischarge SUD follow-up care that may 

implicate the physician self-referral law. 

To the extent an IPF enters into a 

compensation arrangement with a 

physician who provides SUD follow-up 

care to patients discharged from the 

hospital, we note that there are 

exceptions to the physician self-referral 

law applicable to such compensation 

arrangements, including recently 

finalized exceptions for value-based 

arrangements. 

We will consider this measure for 

potential risk adjustment or 

stratification as we seek to close the 

equity gap as described in section IV.D 

of this final rule. We note that a 

reduction in readmissions is this 

measure’s objective, though improved 

follow-up adherence may serve to 

reduce readmissions because of 

improved continuity of care. Finally, we 

will evaluate whether the FAPH 

measure is an appropriate replacement 

for Alcohol & Other Drug Use Disorder 

Treatment Provided or Offered at 

Discharge and Alcohol & Other Drug 

Use Disorder Treatment at Discharge 

(SUB–3/3a). 

Comment: Some commenters 

requested clarification regarding visits 

that would be considered post-discharge 

follow-up. Some commenters requested 

clarification regarding whether 

telehealth visits, specifically audio-only 

telehealth visits, would be considered 

follow-up for purposes of the measure. 

A few commenters requested 

clarification regarding whether visits 

implemented through collaborative 

agreements with mental health 

providers would be considered followups. These commenters further observed 

that including these visits would 

incentivize community partnerships. 

One commenter requested clarification 

regarding whether a visit to any HCP 

(including physicians, clinics, etc.) 

would be considered follow-up for 

purposes of the measure. This 

commenter further requested 

clarification regarding whether specific 

diagnosis codes would be required to be 

present on the follow-up claim. 

Response: Regarding the request for 

clarification about the eligibility of 

telehealth visits for FAPH measure, both 

in-person and telehealth outpatient 

visits are acceptable, including audioonly visits. The FAPH numerator 

defines qualifying outpatient visits as 

outpatient visits, intensive outpatient 

encounters or partial hospitalizations 

that occur within 7 or 30 days of 

discharge and are defined by the 

Current Procedural Terminology (CPT), 

Healthcare Common Procedure Coding 

System (HCPCS), and Uniform Billing 

(UB) Revenue codes, with or without 

the GT telehealth modifier. The CPT 

codes 99441, 99442, and 99443, which 

represent telephone E/M visits, are 

included in the list of codes to identify 

eligible outpatient visits. With respect to 

the request for clarification regarding 

collaborative agreements, the measure is 

agnostic to relationships between 

mental health providers, other 

providers, and health systems. The 

codes used to identify outpatient visits 

for the FAPH measure are not limited to 

mental health providers. The outpatient 

visit may be any outpatient visit, 

intensive outpatient encounter or partial 

hospitalization that occurs within 7 or 

30 days of discharge as defined in 

section IV.E.3.b.(1). This visit must be 

paired with a qualifying ICD–10–CM 

diagnosis of mental illness or substance 

use disorder used to define the 

denominator. 

Comment: One commenter observed 

that historical trending would no longer 

be available due to the transition from 

FUH to FAPH. 

Response: We agree with the 

commenter that replacing FUH with 

FAPH would mean that historical 

trending would no longer be available. 

However, we believe that the benefits 

associated with the expanded patient 

population and the expanded provider 

types for follow-up appointments 

outweigh the loss of trend data. 

After consideration of the public 

comments, we are finalizing the FAPH 

measure as proposed for the FY 2024 

payment determination and subsequent 

years. 

F. Removal or Retention of IPFQR 

Program Measures 

1. Background 

In the FY 2018 IPPS/LTCH PPS final 

rule (82 FR 38463 through 38465), we 

adopted considerations for removing or 

retaining measures within the IPFQR 

Program and criteria for determining 

when a measure is ‘‘topped out.’’ In the 

FY 2019 IPF PPS final rule (83 FR 38591 

through 38593), we adopted one 

additional measure removal factor. We 

did not propose any changes to these 

removal factors, topped-out criteria, or 

retention factors and refer readers to the 

FY 2018 IPPS/LTCH PPS final rule (82 

FR 38463 through 38465) and the FY 

2019 IPF PPS final rule (83 FR 38591 

through 38593) for more information. 

We will continue to retain measures 

from each previous year’s IPFQR 

Program measure set for subsequent 

years’ measure sets, except when we 

specifically propose to remove or 

replace a measure. We will continue to 

use the notice-and-comment rulemaking 


lotter on DSK11XQN23PROD with RULES5
42646 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

process to propose measures for removal 

or replacement, as we described upon 

adopting these factors in the FY 2018 

IPPS/LTCH PPS final rule (82 FR 38464 

through 38465). 

In the FY 2022 IPF PPS proposed rule 

we described that in our continual 

evaluation of the IPFQR Program 

measure set under our Meaningful 

Measures Framework and according to 

our measure removal and retention 

factors, we identified four measures that 

we believed were appropriate to 

propose removing from the IPFQR 

Program for the FY 2024 payment 

determination and subsequent years (86 

FR 19507). Our discussion of these 

measures follows. 

2. Measures Proposed for Removal in 

the FY 2022 IPF PPS Proposed Rule 

a. Retention of the Alcohol Use Brief 

Intervention Provided or Offered and 

Alcohol Use Brief Intervention (SUB– 

2/2a) Measure Beginning With FY 2024 

Payment Determination 

We proposed to remove the Alcohol 

Use Brief Intervention Provided or 

Offered (SUB–2) and subset measure 

Alcohol Use Brief Intervention (SUB2a) 

collectively referred to as the SUB–2/2a 

measure from the IPFQR Program 

beginning with the FY 2024 payment 

determination under our measure 

removal Factor 8, ‘‘The costs associated 

with a measure outweigh the benefit of 

its continued use in the program.’’ We 

adopted the Alcohol Use Brief 

Intervention Provided or Offered and 

Alcohol Use Brief Intervention (SUB– 

2/2a) measure in the FY 2016 IPF PPS 

final rule (80 FR 46699 through 46701) 

because we believe it is important to 

address the common comorbidity of 

alcohol use among IPF patients. This 

measure requires facilities to chartabstract measure data on a sample of IPF 

patient records, in accordance with 

established sampling policies (80 FR 

46717 through 46719). 

We have previously stated our intent 

to move away from chart-abstracted 

measures to reduce information 

collection burden in this and other CMS 

quality programs (78 FR 50808; 79 FR 

50242; 80 FR 49693). When we adopted 

the SUB–2/2a measure to the IPFQR 

Program, the benefits of this measure 

were high because IPF performance was 

not consistent. Therefore, the measure 

provided a means of distinguishing IPF 

performance and incentivized facilities 

to improve rates of treatment for this 

common comorbidity. Between the FY 

2018 payment determination (the first 

year that SUB–2/2a was included in the 

IPFQR Program measure set) and the FY 

2019 payment determination, we saw 

substantial performance improvement 

on the SUB–2 measure (which is the 

portion of the SUB–2/2a measure that 

assesses whether the IPF provided or 

offered a brief intervention for alcohol 

use). However, for the FY 2019 and FY 

2020 payment determinations, the rate 

of improvement has leveled off to 

consistently high performance, as 

indicated in Table 3. These data further 

show that at this time there is little 

room for improvement in the SUB 2 

measure, and that the quality 

improvement benefits from the measure 

have greatly diminished. 

As stated in the proposed rule, we 

continue to believe that alcohol use is 

an important comorbidity to address in 

the IPF setting, and that brief 

interventions are a key component of 

addressing this comorbidity. However, 

based on these data, we believe that 

most IPFs routinely offer alcohol use 

brief interventions, and that IPFs will 

continue to offer these interventions to 

patients, regardless of whether the SUB– 

2/2a measure is in the IPFQR Program 

measure set, because it has become an 

embedded part of their clinical 

workflows. 

In the proposed rule, we noted that 

while the measure does not meet our 

criteria for ‘‘topped-out’’ status because 

of the TCV higher than 0.1, we believe 

that this measure no longer 

meaningfully supports the program 

objectives of informing beneficiary 

choice and driving improvement in IPF 

interventions for alcohol use because it 

is no longer showing significant 

improvement in IPF performance (that 

is, in providing or offering alcohol use 

brief interventions). Furthermore, as we 

stated in the FY 2019 IPF PPS final rule, 

costs are multi-faceted and include not 

only the burden associated with 

reporting, but also the costs associated 

with implementing and maintaining the 

program (83 FR 38592). For example, it 

may be costly for health care providers 

to maintain general administrative 

knowledge to report this measure. 

Additionally, CMS must expend 

resources in maintaining information 

collection systems, analyzing reported 

data, and providing public reporting of 

the collected information. 

Here, IPF information collection 

burden and related costs associated with 

reporting the SUB 2/2a measure to CMS 

are high because it is a chart-abstracted 

measure. Furthermore, CMS incurs costs 

associated with the program oversight of 

the measure for public display. As a 

result, we believe that the costs and 

burdens associated with this chartabstracted measure outweigh the benefit 

of its continued use in the program. 

Therefore, we proposed to remove the 

Alcohol Use Brief Intervention Provided 

or Offered and Alcohol Use Brief 

Intervention (SUB–2/2a) measure from 

the IPFQR Program beginning with the 

FY 2024 payment determination. We 

welcomed public comments on our 

proposal to remove the SUB–2/2a 

measure from the IPFQR Program. 

We received the following comments 

on our proposal. 

Comment: Many commenters 

supported our proposal to remove the 

Alcohol Use Brief Intervention Provided 

or Offered and Alcohol Use Brief 

Intervention (SUB–2/2a) measure. Some 

commenters agreed with our rationale 

that the costs of this measure outweigh 

the benefit of its continued use in the 

IPFQR Program. A few commenters 

recommended that CMS remove the 

measure immediately, rather than 

beginning with FY 2024 payment 

determination as proposed, to further 

reduce burden. One commenter agreed 


lotter on DSK11XQN23PROD with RULES5ER04AU21.172</GPH>

TABLE 3: -Performance Analysis for Alcohol Use Brief Intervention Provided or 

Offered (SUB-2) 

Year Mean Median 75th 90th Truncated 

percentile percentile Coefficient 

of Variation 

(TCV) 

2016 (2018 Payment Determination) 66.96 77 96 100 0.49 

2017 (2019 Payment Determination) 77.11 88 99 100 0.28 

2018 (2020 Payment Determination) 79.49 91 100 100 0.25 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42647 

152Pollard et. al., Changes in Adult Alcohol Use 

and Consequences During the COVID–19 Pandemic 

in the US, JAMA Network Open, 

2020;3(9):e2022942. doi:10.1001/ 

jamanetworkopen.2020.22942. 

153Alcohol Consumption Rises Sharply During 

Pandemic Shutdown; Heavy Drinking by Women 

Rises 41%, RAND, https://www.rand.org/news/ 

press/2020/09/29.html. 

154Nemani et al., Association of Psychiatric 

Disorders With Mortality Among Patients With 

COVID–19, JAMA Psychiatry. 2021;78(4):380–386. 

doi:10.1001/jamapsychiatry.2020.4442; COVID–19 

and people at increased risk, CDC, https://

www.cdc.gov/drugoverdose/resources/covid-drugsQA.html; U. Saengow et. al. 

155Wang et. al., COVID–19 risk and outcomes in 

patients with substance use disorders: Analyses 

from electronic health records in the United States, 

Molecular Psychiatry volume 26, pages 30–39 

(2021), https://www.nature.com/articles/s41380- 

020-00880-7. 

156 Vai et. al., Mental disorders and risk of 

COVID–19-related mortality, hospitalisation, and 

intensive care unit admission: A systematic review 

and meta-analysis, Lancet Psychiatry, https://

www.thelancet.com/pdfs/journals/lanpsy/PIIS2215- 

0366(21)00232-7.pdf. 

157https://www.samhsa.gov/sbirt; https://

www.samhsa.gov/sbirt/coding-reimbursement. 

158For FY 2018 payment determination, the mean 

performance nationally was approximately 80 

percent of patients who screened positive for 

alcohol use disorder were offered or provided a 

brief intervention. 

that providers will continue these 

interventions after the measure has been 

removed. Another commenter also 

supported removal because the measure 

is no longer NQF endorsed and was not 

specified for this setting. 

Response: We thank the commenters 

for their support. While we continue to 

believe that the performance on the 

SUB–2/2a measure in recent years 

indicates that IPFs routinely offer 

alcohol use brief interventions, we 

recognize that we will not be able to 

monitor whether IPFs continue these 

interventions if we remove this 

measure. We considered proposing to 

remove the measure sooner, but because 

data are currently being collected to 

report during CY 2022 to inform the FY 

2023 payment determination, we 

proposed removing the measure 

following that payment determination, 

that is, for the FY 2024 payment 

determination. 

The commenter is correct that the 

measure is no longer NQF endorsed and 

is not specified for the IPF setting. 

However, we continue to believe that 

this measure is appropriate for the IPF 

setting. We reiterate that we proposed to 

remove this measure because of the 

belief that the costs of the measure 

outweigh its continued benefits in the 

IPFQR Program, not because it is no 

longer NQF endorsed nor because it was 

not specified for this setting. 

Comment: One commenter supported 

removal of the SUB–2/2a measure, but 

recommended development of more 

meaningful measures than SUB–2/2a 

and the Alcohol & Other Drug Use 

Disorder Treatment Provided or Offered 

at Discharge and Alcohol & Other Drug 

Use Treatment at Discharge (SUB–3/3a) 

measure to address screening and 

intervention for substance use. Another 

commenter recommended that CMS 

consult with consumers to ascertain the 

benefits of measures in the IPFQR 

Program prior to proposing to remove 

any such measures, this commenter 

specifically recommended that CMS not 

finalize removal of the SUB–2/2a 

measure until fully considering input 

from consumers. 

Response: We appreciate this 

commenter’s input and are continually 

seeking to improve our measure set by 

developing more meaningful and less 

burdensome measures. As we evaluate 

areas appropriate for measure 

development, we will consider 

additional measures or measure 

concepts that more meaningfully 

address alcohol use disorder treatment 

for the IPF patient population. 

In response to the request that we 

consult with consumers to ascertain the 

benefits of the measure, we note that we 

evaluate input from all stakeholders, 

including consumers, patients, 

caregivers, and patient advocacy groups 

that we receive in response to our 

proposals to adopt or remove measures 

from the IPFQR Program. As part of this 

process, we have reviewed input from 

consumers regarding the benefits of the 

measure and considered this input in 

our analysis. 

Comment: Some commenters 

expressed concern about removing the 

measure. A few of these commenters 

stated that not all facilities perform well 

on the measure and, therefore, there is 

still room for improvement. One 

commenter stated that the COVID–19 

pandemic has led to increased alcohol 

use and expressed the belief that 

removing the measure now is poorly 

timed. 

Response: We note that we proposed 

to remove the measure because of the 

belief that the benefits of retaining it 

have lessened to the point that its costs 

outweigh those benefits, not because the 

measure is topped out. We agree with 

commenters that not all facilities 

perform uniformly well on the Alcohol 

Use Disorder Brief Intervention 

Provided or Offered and Alcohol Use 

Disorder Brief Intervention Provided 

(SUB–2/2a) measure. 

We also agree that alcohol use has 

increased during the COVID–19 

pandemic.152 153 154 In our literature 

review regarding this comment, we also 

identified evidence that individuals 

with mental health and substance use 

conditions may be at an increased risk 

of COVID–19 complications and 

appropriate substance use disorder 

treatment may help mitigate these 

complications.155 156 To ensure that 

providers would continue to address 

alcohol use disorders among this patient 

population, we have maintained the 

Alcohol & Other Drug Use Disorder 

Treatment Provided or Offered at 

Discharge and Alcohol & Other Drug 

Use Treatment at Discharge (SUB–3/3a) 

measure. However, we note that a 

prominent model to ensure those with 

alcohol use disorder are identified and 

referred to treatment include both brief 

interventions and referrals.157 Given the 

increased need for alcohol use brief 

interventions due to the pandemic, the 

current performance levels 158 (for FY 

2018 payment determination, the mean 

performance nationally was 

approximately 80 percent of patients 

who screened positive for alcohol use 

disorder were offered or provided a brief 

intervention), and the importance of 

providing alcohol use brief 

interventions to improve the efficacy of 

alcohol use treatment at discharge, we 

believe that the benefits of retaining the 

Alcohol Use Brief Intervention Provided 

or Offered and Alcohol Use Brief 

Intervention (SUB–2/2a) measure are 

greater than we initially estimated in 

our proposal to remove this measure 

and that the measure should not be 

removed from the program at this time. 

Comment: One commenter observed 

that this measure may be useful for 

future stratification based on race and 

ethnicity. 

Response: We agree with the 

commenter that this measure may be 

useful for future stratification based on 

race and ethnicity. While we do not 

believe it would be appropriate to retain 

this measure specifically for the purpose 

of potential future stratification, we 

agree that this potential is another 

benefit of the measure that we had not 

considered in our previous analysis of 

the benefits versus the costs of retaining 

the measure. 

Comment: One commenter observed 

that there are benefits to retaining this 

measure because IPFs and health 

systems use performance data on this 

measure as part of quality improvement 

initiatives to reduce alcohol use and 

that removal may affect these programs. 

Response: We thank the commenter 

for this input. We note that IPFs are 

responsible for abstracting the data for 

this measure, so we believe that IPFs 

who use these data for their own quality 

improvement initiatives have access to 

these data regardless of whether the 

measure is in the IPFQR Program. 


lotter on DSK11XQN23PROD with RULES5
42648 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

159We note that the proposed rule incorrectly 

referred to this measure as the Tobacco Use Brief 

Intervention Provided or Offered and Tobacco Use Brief Intervention (TOB–2/2a) measure, we have 

corrected it here and throughout this final rule. 

However, we recognize that such IPFs 

and health systems would not have 

access to publicly reported data 

regarding other IPFs and that these data 

may be useful for baselining. Therefore, 

we agree that such IPF level and 

systemic programs to reduce alcohol use 

is a benefit to retaining the measure that 

we had not evaluated in our proposal to 

remove this measure. 

Comment: One commenter observed 

that this measure is less burdensome 

than the newly proposed COVID–19 

vaccination measure and therefore the 

commenter believes that removing this 

measure because the costs, especially 

the information collection burden, 

outweigh benefits is inconsistent. 

Response: We evaluate measures on a 

case-by-case basis looking at the overall 

benefits of the measure versus the 

overall costs of the measure. Therefore, 

measures are not evaluated based on 

whether they are more or less 

burdensome than other measures. 

However, we now believe that the 

benefits of retaining this measure are 

greater than we had considered in our 

proposal to remove the measure from 

the IPFQR Program measure set. 

After consideration of the public 

comments, we now believe that the 

benefits of retaining this measure, 

which include the potential for IPFs to 

continue improving performance on this 

measure, the importance of substance 

use interventions due to increased 

substance use during the COVID–19 

pandemic, and this measure’s potential 

influence on other quality improvement 

activities related to substance use are 

greater than we had considered in our 

proposal to remove the measure from 

the IPFQR Program measure set. 

Accordingly, we are not finalizing our 

proposal to remove the Alcohol Use 

Brief Intervention Provided or Offered 

and Alcohol Use Brief Intervention 

(SUB–2/2a) measure beginning with the 

FY 2024 payment determination. That 

is, we are retaining the Alcohol Use 

Disorder Brief Intervention Provided or 

Offered and Alcohol Use Disorder Brief 

Intervention Provided (SUB–2/2a) 

measure in the IPFQR Program measure 

set. 

After consideration of the public 

comments, we are not finalizing our 

proposal to remove the Alcohol Use 

Brief Intervention Provided or Offered 

and Alcohol Use Brief Intervention 

(SUB–2/2a) measure beginning with the 

FY 2024 payment determination. That 

is, we are retaining the Alcohol Use 

Disorder Brief Intervention Provided or 

Offered and Alcohol Use Disorder Brief 

Intervention Provided (SUB–2/2a) 

measure in the IPFQR Program measure 

set. 

b. Retention of the Tobacco Use 

Treatment Provided or Offered and 

Tobacco Treatment (TOB–2/2a) Measure 

Beginning With FY 2024 Payment 

Determination 159

We proposed to remove the Tobacco 

Use Treatment Provided or Offered 

(TOB–2) and Treatment (TOB–2a), 

collectively referred to as the TOB–2/2a 

measure from the IPFQR Program 

beginning with the FY 2024 payment 

determination under our measure 

removal Factor 8, ‘‘The costs associated 

with a measure outweigh the benefit of 

its continued use in the program.’’ We 

adopted the Tobacco Use Treatment 

Provided or Offered and Tobacco Use 

Treatment (TOB–2/2a) measure in the 

FY 2015 IPF PPS final rule (79 FR 45971 

through 45972) because we believe it is 

important to address the common 

comorbidity of tobacco use among IPF 

patients. Like SUB–2/2a described in 

the previous subsection, this measure 

requires facilities to chart-abstract 

measure data on a sample of IPF patient 

records, in accordance with established 

sampling policies (80 FR 46717 through 

46719). 

When we introduced the TOB–2/2a 

measure to the IPFQR Program, the 

benefits of this measure were high, 

because IPF performance was not 

consistent and therefore the measure 

provided a means of distinguishing IPF 

performance and incentivized facilities 

to improve rates of treatment for this 

common comorbidity. Between the FY 

2017 payment determination (the first 

year that TOB–2/2a was included in the 

IPFQR Program’s measure set) and the 

FY 2019 payment determination we saw 

substantial performance improvement 

on TOB–2. However, between the FY 

2019 and FY 2020 payment 

determinations, that improvement has 

leveled off to consistently high 

performance, as indicated in Table 4. 

These data further show that currently 

there is little room for improvement in 

the TOB–2 measure, and that the quality 

improvement benefits from the measure 

have greatly diminished. We continue to 

believe that tobacco use is an important 

comorbidity to address in the IPF 

setting, and that brief interventions are 

a key component of addressing this 

comorbidity. However, based on these 

data, we stated in the proposed rule that 

we believe that most IPFs routinely offer 

tobacco use brief interventions, and that 

IPFs will continue to offer these 

interventions to patients, regardless of 

whether the TOB–2/2a measure is in the 

IPFQR Program measure set, because it 

has become an embedded part of their 

clinical workflows. 

While the measure does not meet our 

criteria for ‘‘topped-out’’ status because 

of the TCV higher than 0.1, we believe 

that this measure no longer 

meaningfully supports the program 

objectives of informing beneficiary 

choice and driving improvement in IPF 

interventions for tobacco use because it 

is no longer showing significant 

improvement in IPF performance (that 

is, in providing or offering tobacco use 

brief interventions). Furthermore, as we 


lotter on DSK11XQN23PROD with RULES5ER04AU21.173</GPH>

TABLE 4: Performance Analysis for Tobacco Use Treatment Provided or Offered 

(TOB-2) 

Year Mean Median 75th 90th Truncated 

percentile percentile Coefficient of 

Variation 

(TCV) 

2015 (2017 Payment Determination) 63.83 71.5 91 99 0.49 

2016 (2018 Payment Determination) 74.72 84 95 100 0.28 

2017 (2019 Payment Determination) 79.04 88 97 100 0.22 

2018 (2020 Payment Determination) 79.08 88 98 100 0.22 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42649 

160 Giovenco et. al., Multi-level drivers of tobacco 

use and purchasing behaviors during COVID–19 

‘‘lockdown’’: A qualitative study in the United 

States, International Journal of Drug Policy, Volume 

94, August 2021, 103175. 

161https://www.who.int/news/item/11-05-2020- 

who-statement-tobacco-use-and-covid-19. 

162For the FY 2018 payment determination, the 

mean performance nationally was approximately 79 

percent of patients who screened positive for 

tobacco use were provided or offered treatment 

while inpatients. 

stated in the FY 2019 IPF PPS final rule, 

costs are multi-faceted and include not 

only the burden associated with 

reporting, but also the costs associated 

with implementing and maintaining the 

program (83 FR 38592). For example, it 

may be costly for health care providers 

to maintain general administrative 

knowledge to report this measure. 

Additionally, CMS must expend 

resources in maintaining information 

collection systems, analyzing reported 

data, and providing public reporting of 

the collected information. Here, IPF 

information collection burden and 

related costs associated with reporting 

this measure to CMS are high because 

the measure is a chart-abstracted 

measure. Furthermore, CMS incurs costs 

associated with the program oversight of 

the measure for public display. As a 

result, we believe that the costs and 

burdens associated with this chartabstracted measure outweigh the benefit 

of its continued use in the program. 

Therefore, we proposed to remove the 

Tobacco Use Treatment Provided or 

Offered and Tobacco Use Treatment 

(TOB–2/2a) measure from the IPFQR 

Program beginning with the FY 2024 

payment determination. We welcomed 

public comments on our proposal to 

remove the TOB–2/2a measure from the 

IPFQR Program. 

We received the following comments 

on our proposal. 

Comment: Many commenters 

supported our proposal to remove the 

Tobacco Use Treatment Provided or 

Offered and Tobacco Use Treatment 

(TOB–2/2a) measure. Some of these 

commenters agreed with our rationale 

that the costs of this measure outweigh 

the benefits of its continued use in the 

IPFQR Program. Several commenters 

recommended removing the measure 

immediately, rather than beginning with 

FY 2024 payment determination as 

proposed, to further reduce burden. One 

commenter agreed that providers will 

continue offering this intervention even 

if it is not being measured. Another 

commenter further expressed that 

removal is appropriate because the 

measure is no longer NQF endorsed and 

is not specified for this setting. 

Response: We thank the commenters 

for their support. We considered 

proposing to remove the measure 

sooner, but because data are currently 

being collected to report during CY 2022 

to inform the FY 2023 payment 

determination, we proposed to remove 

the measure following that payment 

determination, that is, for the FY 2024 

payment determination. While we 

continue to believe that the performance 

on the TOB–2/2a measure in recent 

years indicates that IPFs routinely offer 

tobacco use cessation interventions 

during the inpatient stay, we recognize 

that we will not be able to monitor 

whether IPFs continue these 

interventions if we remove this 

measure. The commenter is correct that 

the measure is no longer NQF endorsed 

and is not specified for the IPF setting. 

We reiterate that we proposed to remove 

this measure because of the belief that 

the costs of the measure outweigh its 

continued benefits in the IPFQR 

Program not because it is no longer NQF 

endorsed nor because it was not 

specified for this setting and we 

continue to believe that this measure is 

appropriate for the IPF setting. 

Comment: One commenter expressed 

the belief that progress in electronic 

reporting systems leads to lower burden 

for reporting this measure. This 

commenter expressed the belief that this 

reduced burden should factor into the 

consideration of whether costs outweigh 

benefits and recommended that CMS 

retain this measure. 

Response: We thank the commenter 

for this feedback. However, we note that 

because this is a chart-abstracted 

measure, we do not believe access to 

electronic reporting systems will 

significantly impact the burden of 

collecting and reporting this measure for 

most IPFs. 

Comment: One commenter supported 

removal of the Tobacco Use Treatment 

Provided or Offered and Tobacco Use 

Treatment Provided (TOB–2/2a) 

measure, but recommended 

development of more meaningful 

measures than TOB–2/2a and Tobacco 

Use Treatment Provided or Offered at 

Discharge and Tobacco Use Treatment 

Provided at Discharge (TOB–3/3a) to 

address screening and intervention for 

tobacco use. One commenter 

recommended that CMS seek consumer 

input on the benefit of measures before 

proposing to remove them. 

Response: We appreciate this 

commenter’s input and are continually 

seeking to improve our measure set by 

developing more meaningful and less 

burdensome measures. As we evaluate 

areas appropriate for measure 

development, we will consider 

additional measures or measure 

concepts that more meaningfully 

address tobacco use treatment for the 

IPF patient population. 

In response to the request that we 

consult with consumers to ascertain the 

benefits of the measure, we note that we 

evaluate input from all stakeholders, 

including consumers, patients, 

caregivers, and patient advocacy groups 

that we receive in response to our 

proposals to adopt or remove measures 

from the IPFQR Program. As part of this 

process, we have reviewed input from 

consumers regarding the benefits of the 

measure and considered this input in 

our analysis. 

Comment: Some commenters 

expressed concern about removing the 

TOB–2/2a measure from the IPFQR 

Program measure set. Some of these 

commenters expressed that there 

continues to be significant room for 

improvement in providing 

interventions. One commenter 

specifically observed that the measure is 

not topped out. A few commenters 

observed that the proposed removal is 

poorly timed due to the increase in 

tobacco use during the COVID–19 

pandemic. Another commenter cited 

evidence supporting the benefit of brief 

interventions as part of a comprehensive 

program to address topped out. 

We agree with commenters that not 

all facilities perform uniformly well on 

the Tobacco Use Treatment Provided or 

Offered and Tobacco Use Treatment 

Provided (TOB–2/2a) measure. We also 

agree with the commenter’s observation 

that tobacco use has increased during 

the COVID–19 pandemic.160 In our 

literature review, we also identified 

evidence that individuals who use 

tobacco may be at an increased risk of 

COVID–19 complications and tobacco 

use treatment may help mitigate these 

complications.161 To ensure that 

providers would continue to address 

tobacco use among this patient 

population, we maintained the Tobacco 

Use Treatment Provided or Offered at 

Discharge and Tobacco Use Treatment 

Provided at Discharge (TOB–3/3a). 

However, we agree with the commenter 

who expressed that these interventions 

are most effective as part of a 

comprehensive tobacco treatment 

program. Given the increased need for 

tobacco use interventions due to the 

COVID–19 pandemic, that this measure 

is not topped out and there is room for 

improvement across facilities,162 and 

the importance of providing tobacco use 

treatment during the inpatient stay to 

improve the efficacy of tobacco use 

treatment at discharge, we believe that 

the benefits of retaining the Tobacco 

Use Treatment Provided or Offered and 

Tobacco Use Treatment Provided (TOB– 

2/2a) measure are greater than we 


lotter on DSK11XQN23PROD with RULES5
42650 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

163https://www.cdc.gov/mmwr/volumes/67/wr/ 

mm6718a3.htm. 

estimated in our proposal to remove this 

measure and that the measure should 

not be removed from the program at this 

time. 

Comment: Many commenters opposed 

removal of the measure because of the 

clinical importance of treating tobacco 

use in the IPF patient population. Many 

of these commenters observed that 

tobacco use is undertreated. Some of 

these commenters referenced CDC data 

stating that only 48.9 percent of mental 

health treatment facilities reported 

screening patients for tobacco use. Some 

commenters pointed to this statistic and 

expressed concern that without 

measures related to tobacco use 

treatment this care may no longer be 

provided in IPFs. These commenters 

observed that tobacco use is nearly three 

times more prevalent in people with 

serious psychological distress than in 

those without. Some of these 

commenters observed that this 

discrepancy contributes to a shorter life 

expectancy for patients with mental 

illness who smoke. These commenters 

expressed the belief that the potential to 

increase patient life expectancy and 

quality of life outweighs the costs of 

reporting the measure. A few of these 

commenters observed there are high 

costs associated with treating tobacco 

associated illness and that these costs 

could be significantly reduced by 

increased screening, intervention, and 

treatment. 

Some commenters stated that the 

2020 Surgeon General’s report 

specifically stated that tobacco 

dependence treatment is applicable to 

the behavioral health setting. One 

commenter observed that brief 

interventions are part of the ‘‘Treating 

Tobacco Use and Dependence Clinical 

Practice Guidelines.’’ One commenter 

stated that behavioral health patients 

often have limited interaction with the 

healthcare system and therefore the 

commenter believes that it is important 

to use these interactions to drive health 

behaviors. 

Response: We agree with commenters 

that providing or offering tobacco use 

brief intervention within the IPF setting 

is a valuable intervention because of the 

prevalence of this comorbidity within 

this patient population and because of 

the ability of this intervention to 

facilitate quitting tobacco use. We 

further agree that brief interventions are 

part of clinical guidelines and are 

appropriate to provide to patients 

receiving care for behavioral health 

conditions. We note that the tobacco 

screening statistics cited by commenters 

refer to all behavioral health and 

substance use treatment facilities, 

whereas the IPFQR Program only 

requires reporting on treatment 

provided by IPFs that receive Medicare 

payment under the IPF PPS, therefore 

the statistics cited by commenters do 

not directly reflect care provided by 

IPFs.163 However, we acknowledge that 

the low performance on tobacco use 

screening in the behavioral health 

setting does indicate that tobacco 

screening and treatment performance 

may lapse in the IPF setting without 

measures to address this topic, and that 

the inpatient setting may be a uniquely 

opportune setting for providing tobacco 

cessation interventions to some patients 

due to limited access to or utilization of 

the healthcare system. We also agree 

with commenters that providing tobacco 

use brief interventions has the potential 

to increase patient life expectancy and 

quality of life while reducing healthcare 

costs associated with treating tobacco 

associated illness. Given the importance 

of tobacco use interventions in 

extending life expectancy and 

improving quality of life, the concern 

regarding potential reduction in 

performance if measures are removed 

(as demonstrated by CDC data that show 

that the provision of brief intervention 

for tobacco use cessation is not the 

current standard of care across 

behavioral health settings as only 48.9 

percent of mental health treatment 

facilities report screening patients for 

tobacco use), and the room for 

improvement in the current 

performance levels, we believe that the 

benefits of retaining the Tobacco Use 

Treatment Provided or Offered and 

Tobacco Use Treatment Provided (TOB– 

2/2a) measure are greater than we 

estimated in our proposal to remove this 

measure and that the measure should 

not be removed from the program at this 

time. 

Comment: One commenter observed 

that there are health equity concerns 

regarding tobacco use and 

recommended that CMS retain this 

measure for future stratification based 

on race and ethnicity. 

Response: We agree with the 

commenter that this measure may be 

useful for future stratification based on 

race and ethnicity. While we do not 

believe it would be appropriate to retain 

this measure specifically for the purpose 

of potential future stratification, we 

agree that this potential is another 

benefit of the measure that we had not 

considered in our previous analysis of 

the benefits versus the costs of retaining 

the measure. 

Comment: One commenter observed 

that there are benefits to retaining this 

measure because IPFs and health 

systems use performance data on this 

measure as part of quality improvement 

initiatives to reduce tobacco use and 

that measure removal may affect those 

programs. 

Response: We thank the commenter 

for this feedback. We note that IPFs are 

responsible for abstracting the data for 

this measure, so we believe that IPFs 

who use these data for their own quality 

improvement initiatives have access to 

these data regardless of whether the 

measure is in the IPFQR Program. 

However, we recognize that such IPFs 

and health systems would not have 

access to publicly reported data 

regarding other IPFs and that these data 

may be useful for baselining. Therefore, 

we agree that such IPF level and 

systemic programs to reduce tobacco 

use is a benefit to retaining the measure 

that we had not evaluated in our 

proposal to remove this measure. 

Comment: Many commenters 

expressed the belief that without this 

measure IPFs would not continue to 

provide tobacco use brief interventions. 

Some commenters expressed concern 

that removing this measure would 

reduce providers’ incentive to offer brief 

interventions. These commenters 

further observed that it would be 

difficult to determine whether IPFs 

continue to offer this intervention as the 

ability to track that depends on the 

continued collection of this measure. 

Some commenters further expressed 

concern that CMS policies drive the 

behavior of other payers and without 

this measure the healthcare system may 

lose focus on tobacco treatment for 

patients with behavioral health 

disorders. 

Response: We understand 

commenters’ concern regarding the 

potential for IPFs and other payers to no 

longer focus on tobacco treatment 

without the Tobacco Use Treatment 

Provided or Offered and Tobacco Use 

Treatment (TOB–2/2a) quality measure 

in the IPFQR Program and we agree that 

ensuring continuing focus on tobacco 

use treatment in this setting is a benefit 

of retaining this measure in the IPFQR 

program. Additionally, we agree that 

tracking whether IPFs continue to offer 

this intervention is a benefit of retaining 

the measure in the IPFQR program 

measure set. 

Comment: One commenter observed 

that the Tobacco Use Treatment 

Provided or Offered and Tobacco Use 

Treatment (TOB–2/2a) measure is not as 

burdensome as the newly proposed 

COVID–19 vaccination measure and 

therefore the commenter believes that 

removing this measure because the 

costs, especially the information 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42651 

collection burden, outweigh benefits is 

inconsistent. 

Response: We evaluate measures on a 

case-by-case basis looking at the overall 

benefits of the measure versus the 

overall costs of the measure. Therefore, 

measures are not evaluated based on 

whether they are more or less 

burdensome than other measures. 

However, we now believe that the 

benefits of retaining this measure are 

greater than we had considered in our 

proposal to remove the measure from 

the IPFQR Program measure set. 

After consideration of the public 

comments, we now believe that the 

benefits of retaining this measure, 

which include the potential for IPFs to 

continue improving performance on this 

measure, the importance of tobacco use 

interventions due to increased tobacco 

use during the COVID–19 pandemic, 

and this measure’s potential influence 

on other quality improvement activities 

related to tobacco use, are greater than 

we had considered in our proposal to 

remove the measure from the IPFQR 

Program measure set. Accordingly, we 

are not finalizing our proposal to 

remove the Tobacco Use Treatment 

Provided or Offered and Tobacco Use 

Treatment (TOB–2/2a) measure 

beginning with the FY 2024 payment 

determination. That is, we are retaining 

the Tobacco Use Treatment Provided or 

Offered and Tobacco Use Treatment 

(TOB–2/2a) measure in the IPFQR 

Program measure set. 

c. Removal of the Timely Transmission 

of Transition Record (Discharges From 

an Inpatient Facility to Home/Self Care 

or Any Other Site of Care) Measure 

Beginning With FY 2024 Payment 

Determination 

We proposed to remove the Timely 

Transmission of Transition Record 

(Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of 

Care) measure from the IPFQR Program 

beginning with the FY 2024 payment 

determination under our measure 

removal Factor 8, ‘‘The costs associated 

with a measure outweigh the benefit of 

its continued use in the program.’’ 

We adopted the Timely Transmission 

of Transition Record (Discharges from 

an Inpatient Facility to Home/Self Care 

or Any Other Site of Care) measure in 

the FY 2016 IPF PPS final rule (80 FR 

46706 through 46709) because more 

timely communication of vital 

information regarding the inpatient 

hospitalization results in better care, 

reduction of systemic medical errors, 

and improved patient outcomes. The 

Timely Transmission of Transition 

Record (Discharges from an Inpatient 

Facility to Home/Self Care or Any Other 

Site of Care) measure builds on the 

Transition Record with Specified 

Elements Received by Discharged 

Patients (Discharges from an Inpatient 

Facility to Home/Self Care or Any Other 

Site of Care) measure, which requires 

facilities to provide a discharge record 

with 11 specified elements to patients at 

discharge. 

We continue to believe that the 11 

elements required by the Transition 

Record with Specified Elements 

measure provide meaningful 

information about the quality of care 

provided by IPFs, and we therefore did 

not propose to remove that measure 

from the IPFQR Program. However, we 

believe that the benefits of requiring 

facilities to transmit the discharge 

record with 11 specified elements to the 

next level care provided within 24 

hours, as required by the Timely 

Transmission of Transition Record 

(Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of 

Care) measure, have been reduced. 

Reporting this measure requires 

facilities to chart-abstract measure data 

on a sample of IPF patient records, in 

accordance with established sampling 

policies (80 FR 46717 through 46719). 

On May 1, 2020, we updated the 

Conditions of Participation (CoPs) for 

IPFs participating in the Medicare 

program in the Medicare and Medicaid 

Programs; Patient Protection and 

Affordable Care Act; Interoperability 

and Patient Access for Medicare 

Advantage Organization and Medicaid 

Managed Care Plans, State Medicaid 

Agencies, CHIP Agencies and CHIP 

Managed Care Entities, Issuers of 

Qualified Health Plans on the Federally 

Facilitated Exchanges, and Health Care 

Providers final rule (85 FR 25588). 

In the May 1, 2020 update to the 

CoPs, we adopted a requirement for 

psychiatric hospitals that possess EHR 

or other administrative systems with the 

technical capacity to generate 

information for electronic patient event 

notifications to send electronic patient 

event notifications of a patient’s 

admission, discharge, transfer to another 

health care facility or to another 

community provider, or combination of 

patient events at the time of a patient’s 

discharge or transfer. Because these 

updated CoP requirements overlap with, 

but are not the same as, the 

requirements for the Timely 

Transmission of Transition Record 

(Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of 

Care) measure (which requires 

transmission of a discharge record with 

11 specified elements to the next level 

care provider within 24 hours of the 

patient’s discharge rather that requiring 

notification regarding the patient’s 

inpatient stay to be transmitted at 

discharge), we believe that the adoption 

of these updated CoPs increases the 

costs of the Timely Transmission of 

Transition Record (Discharges from an 

Inpatient Facility to Home/Self Care or 

Any Other Site of Care) measure while 

decreasing its benefit. Specifically, we 

believe that the costs of this measure are 

increased because facilities to which the 

new CoPs apply (that is, facilities that 

possess EHR or other administrative 

systems with the technical capacity to 

generate information for electronic 

patient event notifications as defined in 

the CoP) could bear increased cost if 

they separately implement the patient 

event notifications meeting both the 

criteria for the updated CoPs and the 

capacity to share a transition record that 

meets the requirements of our measure. 

We noted that the updated CoPs do not 

include the level of detail regarding data 

to be transferred at discharge that our 

Timely Transmission of Transition 

Record (Discharges from an Inpatient 

Facility to Home/Self Care or Any Other 

Site of Care) measure requires. While 

the set of information in the CoP 

notification policy is a minimal set of 

information, we believe that it would 

continue to be appropriate for providers 

to transmit the transition record that 

they will continue to be providing to 

patients under our Transition Record 

Received by Discharged Patients 

(Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of 

Care) measure, we further note that the 

CoPs referenced in the proposed rule are 

not an exhaustive list of data transfer 

requirements. 

We believe the different requirements 

regarding both timeliness of notification 

and contents of notification could lead 

some providers to send two separate 

discharge notifications to meet the 

separate requirements. Further, we 

believe that the benefits of the measure 

are reduced because all facilities to 

which the new CoPs apply will be 

sending patient discharge information to 

the next level of care provider as 

required by the CoPs. Therefore, the 

benefits of this measure are reduced 

because it is less likely to ensure that 

these facilities provide patient discharge 

information to the next level care 

provider, and it is less likely to provide 

information to help consumers 

differentiate quality between facilities. 

While these updated CoPs do not 

directly address transmission of patient 

event notifications for facilities that do 

not possess EHR systems with the 

capacity to generate information for 

electronic patient event notifications, 


lotter on DSK11XQN23PROD with RULES5
42652 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

such facilities should continue to 

transmit data using their existing 

infrastructure and timelines. 

Because we believe that the costs are 

now increased and the benefits are now 

reduced, we believe that the costs and 

burdens associated with this chartabstracted measure outweigh the benefit 

of its continued use in the IPFQR 

Program. 

Therefore, we proposed to remove the 

Timely Transmission of Transition 

Record (Discharges from an Inpatient 

Facility to Home/Self Care or Any Other 

Site of Care) measure from the IPFQR 

Program beginning with the FY 2024 

payment determination. We welcomed 

public comments on our proposal to 

remove the Timely Transmission of 

Transition Record (Discharges from an 

Inpatient Facility to Home/Self Care or 

Any Other Site of Care) measure from 

the IPFQR Program. 

We received the following comments 

on our proposal. 

Comment: Many commenters 

supported the removal of the Timely 

Transmission of Transition Record 

(Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of 

Care) measure. One commenter 

recommended immediate removal to 

further reduce burden. Another 

commenter expressed that this measure 

was not developed for IPFs and has 

been difficult to report because the 

specifications are not appropriate for the 

setting. Another commenter further 

noted that the measure is no longer NQF 

endorsed. 

Response: We thank the commenters 

for their support. We considered 

removing the measure sooner, but 

because data are currently being 

collected to report during CY 2022 to 

inform the FY 2023 payment 

determination, we decided to propose 

removing the measure following that 

payment determination, therefore we 

proposed removal for the FY 2024 

payment determination. The commenter 

is correct that the measure is no longer 

NQF endorsed and is not specified for 

the IPF setting; however we continue to 

believe that this measure is appropriate 

for the setting. We reiterate that removal 

of the measure is because we believe 

that the costs of the measure outweigh 

its continued benefits in the IPFQR 

Program. 

Comment: Some commenters 

observed that the updated CoPs will not 

apply to many IPFs, especially 

freestanding IPFs that are not part of 

larger healthcare facilities, because IPFs 

were excluded from Meaningful Use 

incentives and therefore often do not 

have electronic data systems capable of 

meeting the standards in the updated 

CoPs. 

Response: We acknowledge that there 

are a large number of IPFs that do not 

possess EHR systems with the technical 

capacity to generate information for 

electronic patient event notifications of 

a patient’s admission, discharge, or 

transfer to another health care facility or 

to another community provider, or 

combination of patient events at the 

time of a patient’s discharge or transfer. 

However, for those IPFs that can meet 

these requirements, we believe that 

retaining the Timely Transmission of 

Transition Record (Discharges from an 

Inpatient Facility to Home/Self Care or 

Any Other Site of Care) measure could 

be burdensome depending on how 

facilities implement new requirements. 

Therefore, while for some IPFs the 

benefits may outweigh the costs, overall, 

for the IPFQR Program we believe the 

costs now outweigh the benefits. We 

reiterate that for IPFs that do not possess 

EHR systems with the capacity to 

generate information for patient event 

notifications as defined in the CoP 

regulations set forth at 42 CFR 

482.24(d), such facilities should 

continue to transmit data using their 

existing infrastructure and timelines. 

Comment: A few commenters 

recommended that CMS retain the 

Timely Transmission of Transition 

Record (Discharges from an Inpatient 

Facility to Home/Self Care or Any Other 

Site of Care) measure. Some of these 

commenters believe that the measure’s 

benefits are more significant than the 

burden. One commenter recommended 

that CMS seek consumer input on 

benefits prior to proposing measures for 

removal. 

Response: We reiterate that we do not 

believe that the benefits of transmitting 

the transition record within 24 hours of 

discharge are reduced, or are lower than 

the costs of reporting; we believe that 

given the updates to the CoPs which 

overlap with this measure the benefits 

of retaining the Timely Transmission of 

Transition Record (Discharges from an 

Inpatient Facility to Home/Self Care or 

Any Other Site of Care) measure are no 

longer sufficient to justify retention. We 

used the notice and comment 

rulemaking process to solicit input on 

measure benefits from all stakeholders, 

including consumers. 

After consideration of the public 

comments, we are finalizing our 

proposal to remove the Timely 

Transmission of Transition Record 

(Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of 

Care) measure beginning with the FY 

2024 payment determination. 

d. Removal of the Follow-Up After 

Hospitalization for Mental Illness (FUH, 

NQF #0576) Beginning With FY 2024 

Payment Determination 

In the FY 2022 IPF PPS proposed rule 

we stated that if we finalize adoption of 

the Follow-Up After Psychiatric 

Hospitalization measure described in 

section IV.E.3, we believed that our 

current measure removal Factor 3 would 

apply to the existing Follow-Up After 

Hospitalization for Mental Illness (FUH, 

NQF #0576) measure (86 FR 19510). 

Measure removal Factor 3 applies when 

a ‘‘measure can be replaced by a more 

broadly applicable measure (across 

settings or populations) or a measure 

that is more proximal in time to desired 

patient outcomes for the particular 

topics.’’ We adopted removal factor 3 in 

the FY 2017 IPPS/LTCH PPS final rule 

(82 FR 38463 through 38465). The 

FAPH measure expands the patient 

population from patients with mental 

illness to also include patients with 

primary SUD diagnoses while 

addressing the same important aspect of 

care transitions. Because this FAPH 

measure uses the same methodology to 

address the same element of care for a 

broader patient population than the 

FUH measure, we believe that it is more 

broadly applicable across populations. 

Therefore, we proposed to remove the 

FUH measure under measure removal 

Factor 3 only if we finalized our 

proposal to adopt of the FAPH measure. 

We noted that if we did not adopt the 

FAPH measure, we would retain the 

FUH measure because we believe this 

measure addresses an important clinical 

topic. We welcomed public comments 

on our proposal to remove FUH if we 

were to adopt FAPH. 

We received the following comments 

on our proposal. 

Comment: Many commenters 

supported removal of this measure. 

Some commenters specifically noted 

that FAPH is more broadly applicable 

and therefore preferable. 

Response: We thank these 

commenters for their support. 

Comment: One commenter does not 

support either the FUH measure or the 

FAPH measure due to the belief that 

measures of follow-up after 

hospitalization are not appropriate for 

the IPFQR Program and recommended 

removing the FUH measure but not 

adopting the FAPH measure. 

Response: For the reasons set forth in 

the FY 2014 IPPS/LTCH PPS final rule 

(78 FR 50894 through 50895) and the FY 

2022 IPF PPS proposed rule in our 

proposal to adopt the FAPH measure (86 

FR 19504 through 19507), we believe 

that a measure of follow-after 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42653 

hospitalization is an important concept 

for the inpatient psychiatric setting. 

Therefore, we do not believe it would be 

appropriate to remove the FUH measure 

without adopting the FAPH measure. 

Comment: One commenter observed 

that the FUH measure is an NQFendorsed measure, while the NQF 

declined to endorse the FAPH measure. 

This commenter recommended 

retaining the FUH measure because it is 

endorsed. 

Response: The commenter is correct 

that the FUH measure is NQF endorsed 

and that the NQF declined to endorse 

the FAPH measure. However, as 

discussed in the FY 2022 IPF PPS 

proposed rule, the FUH measure does 

not apply to as broad a patient 

population, nor does it allow for followup care to be provided by as many 

provider types (86 FR 19507). Further, 

for the reasons we discussed in the FY 

2022 IPF PPS proposed rule, we believe 

the exception under section 

1886(s)(4)(D)(ii) of the Act applies (86 

FR 19507). Because the FAPH measure 

is a more broadly applicable measure 

we believe it is appropriate for adoption 

into the IPFQR Program. 

After consideration of the public 

comments, we are finalizing our 

proposal to remove Follow-Up After 

Hospitalization for Mental Illness (FUH, 

NQF #0576) measure beginning with the 

FY 2024 payment determination. 

G. Summary of IPFQR Program 

Measures 

1. IPFQR Program Measures for the FY 

2023 Payment Determination and 

Subsequent Years 

There are 14 previously finalized 

measures for the FY 2023 payment 

determination and subsequent years. In 

this final rule, we are adopting one 

measure for the FY 2023 payment 

determination and subsequent years. 

The 15 measures which will be in the 

program are shown in Table 5. 

BILLING CODE 4120–01–P 

2. IPFQR Program Measures for the FY 

2024 Payment Determination and 

Subsequent Years 

There are 14 previously finalized 

measures for the FY 2024 payment 

determination and subsequent years. In 

this final rule, we are adopting one 

measure for the FY 2023 payment 

determination and subsequent years. 

Additionally, we are finalizing our 

proposal to remove one measure and 

replace one measure for the FY 2024 

payment determination and subsequent 

years. We are not finalizing our 

proposals to remove two measures for 

the FY 2024 payment determination and 

subsequent years. The 14 measures 

which will be in the program for FY 

2024 payment determination and 

subsequent years are shown in Table 6. 


lotter on DSK11XQN23PROD with RULES5ER04AU21.174</GPH>

NQF# 

0640 

0641 

0560 

0576 

NIA* 

NIA* 

NIA* 

NIA* 

1659 

NIA* 

NIA* 

NIA 

2860 

3205 

TBD 

TABLE 5: IPFQR Program Measure Set for the FY 2023 Payment Determination 

and Subsequent Years with Finalized Measure Adoption 

Measure ID 

HBIPS-2 

HBIPS-3 

HBIPS-5 

FUH 

SUB-2 and SUB-2a 

SUB-3 and SUB-3a 

TOB-2 and TOB-2a 

TOB-3 and TOB-3a 

IMM-2 

NIA 

NIA 

NIA 

NIA 

Med Cont 

COVIDHCP 

Measure 

Hours of Physical Restraint Use 

Hours of Seclusion Use 

Patients Discharged on Multiple Antipsychotic Medications with 

Annropriate Justification 

Follow-Up After Hospitalization for Mental Illness 

Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol 

Use Brief Intervention 

Alcohol and Other Drug Use Disorder Treatment Provided or Offered at 

Discharge and SUB-3a Alcohol and Other Drug Use Disorder Treatment at 

Discharge 

Tobacco Use Treatment Provided or Offered and TOB-2a Tobacco Use 

Treatment 

Tobacco Use Treatment Provided or Offered at Discharge and TOB-3a 

Tobacco Use Treatment at Discharge 

Influenza Immunization 

Transition Record with Specified Elements Received by Discharged 

Patients (Discharges from an Inpatient Facility to Home/Self Care or Any 

Other Site of Care) 

Timely Transmission of Transition Record (Discharges from an Inpatient 

Facility to Home/Self Care or any Other Site of Care) 

Screening for Metabolic Disorders 

Thirty-Day All-Cause Unplanned Readmission Following Psychiatric 

Hospitalization in an Inpatient Psychiatric Facility 

Medication Continuation Following Inpatient Psychiatric Discharge 

COVID-19 Healthcare Personnel (HCP) Vaccination Measure 

* Measure is no longer endorsed by the NQF but was endorsed at time of adoption. Section 1886(s)(4)(D)(ii) of 

the Act authorizes the Secretary to specify a measure that is not endorsed by the NQF as long as due consideration is 

given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We 

attempted to find available measures for each of these clinical topics that have been endorsed or adopted by a 

consensus organization and found no other feasible and practical measures on the topics for the IPF setting. 
42654 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

164https://www.cms.gov/meaningful-measures20-moving-measure-reduction-modernization. 

BILLING CODE 4120–01–C 

H. Considerations for Future Measure 

Topics 

As we have previously indicated, we 

seek to develop a comprehensive set of 

quality measures to be available for 

widespread use for informed decisionmaking and quality improvement in the 

IPF setting (79 FR 45974 through 

45975). Therefore, through future 

rulemaking, we intend to propose new 

measures for development or adoption 

that will help further our goals of 

achieving better healthcare and 

improved health for individuals who 

obtain inpatient psychiatric services 

through the widespread dissemination 

and use of quality information. In 2017, 

we introduced the Meaningful Measures 

Framework as a tool to foster 

operational efficiencies and reduce costs 

including collection and reporting 

burden while producing quality 

measurement that is more focused on 

meaningful outcomes (83 FR 38591). As 

we continue to evolve the Meaningful 

Measures Framework, we have stated 

that we intend to better address health 

care priorities and gaps, emphasize 

digital quality measurement, and 

promote patient perspectives.164 As we 

work to align the IPFQR Program’s 

measure set with these priorities, we 

have identified the following areas that 

we believe are important to 

stakeholders, but which are not covered 

in the current IPFQR Program measure 

set: Patient Experience of Care, 

Functional Outcomes Measurement, and 

digital measures. As described in the 

following subsections, we sought public 

comment on each of these topics and 

other future measure considerations 

which stakeholders believe are 

important. 

We received the following public 

comment on measure considerations 

which stakeholders believe are 

important. 

Comments: Many commenters 

suggested measure areas that they 

believe are important for IPFs. These 

areas were: (1) Suicide evaluation and 

reduction; (2) patient experience; (3) 

patient improvement; (4) clinical 

processes that impact significant 

numbers of patients in important 

clinical domains; (5) patient and 

workforce safety; (6) caregiver 

engagement; (7) safety culture; (8) 

workforce engagement, (9) 

immunization status; (10) measures that 

more rigorously capture data on tobacco 

and substance use interventions; and 

(11) discharge planning measures. Some 

commenters recommended developing 

improved discharge planning measures. 

One commenter recommended that 

CMS ensure that the role of nurse 

practitioners is included in measures. 

One commenter recommend that CMS 

engage with patients and their 

caregivers to identify topics they find 

important. Another commenter 

recommended that CMS seek industry 

input on measure considerations. 

Response: We thank these 

commenters for this input. We will 

consider these recommendations as we 

seek to develop a more comprehensive 

measure set for the IPFQR Program. 

1. Patient Experience of Care Data 

Collection Instrument 

When we finalized removal of the 

Assessment of Patient Experience of 


lotter on DSK11XQN23PROD with RULES5ER04AU21.175</GPH>

TABLE 6: IPFQR Program Measure Set for the FY 2024 Payment Determination 

an dS u b sequen tY ears 

NQF# Measure ID Measure 

0640 HBIPS-2 Hours of Phvsical Restraint Use 

0641 HBIPS-3 Hours of Seclusion Use 

0560 HBIPS-5 Patients Discharged on Multiple Antipsychotic Medications with 

Annropriate Justification 

NIA FAPH Follow-Up After Psychiatric Hospitalization 

1659 IMM-2 Influenza Immunization 

NIA* SUB-2 and SUB-2a Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol 

Use Brief Intervention 

NIA* SUB-3 and SUB-3a Alcohol and Other Drug Use Disorder Treatment Provided or Offered at 

Discharge and SUB-3a Alcohol and Other Drug Use Disorder Treatment at 

Discharge 

NIA* TOB-2 and TOB-2a Tobacco Use Treatment Provided or Offered and TOB-2a Tobacco Use 

Treatment 

NIA* TOB-3 and TOB-3a Tobacco Use Treatment Provided or Offered at Discharge and TOB-3a 

Tobacco Use Treatment at Discharge 

NIA* NIA Transition Record with Specified Elements Received by Discharged 

Patients (Discharges from an Inpatient Facility to Home/Self Care or Any 

Other Site of Care) 

NIA NIA Screening for Metabolic Disorders 

2860 NIA Thirty-Day All-Cause Unplanned Readmission Following Psychiatric 

Hospitalization in an Inpatient Psychiatric Facility 

3205 Med Cont Medication Continuation Following Inpatient Psvchiatric Discharge 

TBD COVIDHCP COVID-19 Healthcare Personnel (HCP) Vaccination Measure 

* Measure is no longer endorsed by the NQF but was endorsed at time of adoption. Section 1886(s)(4)(D)(ii) of 

the Act authorizes the Secretary to specify a measure that is not endorsed by the NQF as long as due consideration is 

given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We 

attempted to find available measures for each of these clinical topics that have been endorsed or adopted by a 

consensus organization and found no other feasible and practical measures on the topics for the IPF setting. 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42655 

Care attestation measure in the FY 2019 

IPF PPS final rule (83 FR 38596) we 

stated that we believed we had collected 

sufficient information to inform 

development of a patient experience of 

care measure that would capture data on 

the results of such a survey. In the FY 

2020 IPF PPS proposed rule (84 FR 

16986 through 16987), we solicited 

input on how providers had 

implemented the Hospital Consumer 

Assessment of Healthcare Providers and 

Systems (HCAHPS) survey in their 

facilities. We also sought public 

comment on other potential surveys that 

commenters believed would be 

appropriate to adopt for the IPFQR 

Program. We received many comments 

on this subject, and many of these 

comments expressed that there is not 

one survey used predominantly across 

IPFs (84 FR 38467). Additional 

commenters expressed concerns that the 

HCAHPS survey may not be appropriate 

for the IPF setting because it does not 

include some of the unique aspects of 

inpatient psychiatric care including, 

group therapy, non-physician providers, 

and involuntary admissions. While we 

did not solicit public comment on this 

issue in the FY 2021 IPF PPS proposed 

rule, we received many comments 

addressing this issue (85 FR 47043). We 

continue to seek to identify a minimally 

burdensome patient experience of care 

instrument that would be appropriate 

for the IPF setting. Therefore, in the FY 

2022 IPF PPS proposed rule (86 FR 

19511 through 19512) we sought public 

comment on instruments currently in 

use in the IPF setting, input on whether 

the HCAHPS survey may be appropriate 

for this setting, and information on how 

facilities that currently use the HCAHPS 

survey have addressed challenges with 

using this survey within this setting 

(that is, concerns regarding unique 

aspects of inpatient psychiatric care). 

We received the following comments 

in response to our request. 

Comment: Many commenters 

expressed support for development of a 

uniform patient experience of care 

measure because this is a gap in the 

IPFQR measure set. Many commenters 

expressed that there is currently no 

patient experience of care measure in 

the IPFQR Program and expressed the 

belief that such a survey could improve 

provider accountability, show respect 

for patients, and drive quality 

improvement. Some commenters 

observed that patients should be given 

the opportunity to share their 

experiences regardless of diagnosis. One 

commenter observed that evaluations of 

patient experience of care can be a 

driver of health equity. 

Many commenters shared personal or 

family experiences in IPFs and 

indicated that being able to share such 

experiences in a formal survey would 

allow patients and caregivers to have a 

voice, provide valuable feedback, feel 

respected, provide information for 

quality improvements, and inform other 

potential patients. One commenter 

observed that allowing proxies would be 

valuable. Some commenters observed 

that not collecting patient experience of 

care data leads to the perception that 

patients’ opinions are not valid and 

expressed the concern that this message 

may further objectify and traumatize a 

vulnerable patient population in a 

stressful and potentially stigmatizing 

situation (that is, psychiatric 

hospitalization). Other commenters 

expressed that not collecting such data 

normalizes poor treatment of psychiatric 

patients. Some commenters observed 

that patients with psychiatric illness are 

not less likely to be competent to 

express their experience of care than 

patients with other acute care needs. 

Many commenters recommended that 

CMS identify a minimum set of items to 

include in surveys, as opposed to 

requiring a specific survey. These 

commenters observed that the net 

promoter score (NPS) used by the 

National Health Service in the UK may 

be a good model to consider. Some 

commenters observed that many 

facilities have designed their own 

surveys tailored to their patient 

populations (for example, pediatric 

patients, involuntarily admitted, etc.) 

and that it would be preferable for these 

facilities to add questions to meet a 

minimum set rather than to replace their 

surveys. 

Many commenters expressed that they 

do not support HCAHPS for the IPF 

setting. These commenters expressed 

that (1) the HCAHPS was developed for 

patients with non-psych primary 

diagnoses and not for behavioral health 

diagnoses therefore the questions on 

HCAHPS do not address patients’ top 

concerns regarding IPF care; (2) the 

survey protocols which allow for 

administration of the survey up to 6 

weeks post-discharge may negatively 

impact completion rates due to the 

transient nature of the patient 

population; (3) the protocols do not 

have a web-interface for survey 

administration nor email or text survey 

invites; and (4) HCAHPS does not 

account for involuntary admissions. 

Some commenters also expressed 

concern that HCAHPS is not validated, 

nor has it been through psychometric 

testing in this setting. Some commenters 

observed the HCAHPS survey is due for 

a redesign and observed that CMS could 

potentially address concerns with the 

HCAHPS survey as part of the intended 

redesign. Other commenters 

recommended that CMS develop a 

survey unique to this setting that 

addresses aspects of care specific to the 

setting (such as group therapy, 

treatment by therapists, involuntary 

admission, medication treatment, 

consistency of treatment). One 

commenter recommended that CMS 

collaborate with AHRQ in survey design 

and development. Some commenters 

recommended that CMS ensure proper 

risk adjustment because patient 

characteristic can affect patient 

experience. 

Some commenters observed that the 

questions on HCAHPS apply to IPF 

patients and recommended that CMS 

test HCAHPS for this setting. A few of 

these commenters observed that using 

the same measure across settings would 

improve behavioral health parity, 

facility comparison, and reduce burden 

for facilities that are distinct part units 

in acute care hospitals that use 

HCAHPS. A few commenters expressed 

concern that excluding psychiatric 

patients from HCAHPS is 

discrimination based on a disability 

which, because of the benefits derived 

from patient experience surveys, denies 

patients with psychiatric diagnoses 

equal treatment. Other commenters 

observed that minimizing burden is not 

a factor in establishing patient 

experience of care measures in other 

settings and that therefore it should not 

be a consideration in this setting. Some 

commenters observed that CMS has 

requested and received input on this 

subject for several years and requested 

a specific plan of action. 

A few commenters recommended that 

CMS collaborate with IPFs to determine 

how to assess patients’ experience of 

care, several commenters recommended 

that CMS establish a technical expert 

panel (TEP) with IPF members. 

One commenter recommended that 

CMS reintroduce the attestation 

measure until a solution for assessing 

patient experience of care is identified. 

Response: We thank these 

commenters for their input. We agree 

that Patient Experience of Care is a gap 

in the current IPFQR Program measure 

set and we agree with commenters that 

adoption of such a measure would be a 

meaningful step towards ensuring that 

patients have a voice regarding the care 

they receive. We appreciate the input 

from patients and their caregivers 

explaining how meaningful such a 

measure would be for these 

stakeholders. We intend to use the 

feedback provided here and in past 

requests to identify the most appropriate 


lotter on DSK11XQN23PROD with RULES5
42656 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

path forward towards adopting such a 

measure as soon as possible. 

2. Functional Outcomes Instrument for 

Use in a Patient Reported Outcomes 

Measure 

When we introduced the Meaningful 

Measures Framework, we stated that we 

wanted to focus on meaningful 

outcomes (83 FR 38591). As we have 

assessed the IPFQR Program measure set 

against the Meaningful Measures 

Framework, we have identified 

functional outcomes as a potential gap 

area in the IPFQR Program’s measure 

set. Therefore, we are evaluating 

whether a patient reported outcomes 

measure that assesses functional 

outcomes, such as global functioning, 

interpersonal problems, psychotic 

symptoms, alcohol or drug use, 

emotional lability, and self-harm, would 

be an appropriate measure to include in 

the IPFQR program measure set. If we 

were to develop such a measure, we 

would develop a measure that compares 

a patient’s responses to a standardized 

functional outcomes assessment 

instrument at admission with the 

patient’s results on the same assessment 

instrument at discharge. We sought 

public comment on the value of such a 

measure in the IPFQR program measure 

set, what would be an appropriate 

functional outcome assessment 

instrument to use in the potential 

development of such a measure, and 

any additional topics or concepts 

stakeholders believe would be 

appropriate for patient reported 

outcomes measures. 

We received the following comments 

in response to our request. 

Comment: Many commenters 

supported the concept of a functional 

outcomes measure and recommended 

preceding development of such a 

measure with an attestation measure 

which asks IPFs whether they use an 

assessment, and if so which one. 

Some commenters expressed concern 

regarding outcome measures in this 

setting. One commenter specifically 

observed that short lengths of stay often 

lead to minimal progress on outcomes. 

One commenter mentioned the lack of 

endorsed, public domain outcome 

measures for this setting. 

A few commenters recommended that 

CMS convene a technical expert panel 

(TEP) on patient reported outcomes for 

this setting. 

One commenter uses PHQ–9 to assess 

outcomes. Another commenter uses 

BASIS–32 or CABA–Y depending on the 

patient population. 

Response: We thank the commenters 

for their input and will consider this 

feedback as we continue to evaluate a 

functional outcomes measure for this 

setting. 

3. Measures for Electronic Data 

Reporting 

As we seek to improve digital 

measurement across our quality 

reporting and value-based payment 

programs, we are considering measures 

both within and appropriate to adopt for 

the IPFQR Program measure set that 

would be appropriate for digital data 

collection. In our assessment of the 

current measure set, we identified the 

Transition Record with Specified 

Elements Received by Discharged 

Patients (Discharges from an Inpatient 

Facility to Home/Self Care or Any Other 

Site of Care) measure as a potential 

option for digital data collection. We 

sought stakeholder input on the current 

data collection burden associated with 

this measure, concerns regarding 

potential electronic specification and 

data collection for this measure, and 

other measures that may be appropriate 

for electronic data collection, either 

those currently in the IPFQR Program 

measure set, or those that we could 

adopt in the future. 

We received the following comments 

in response to our request. 

Comment: Several commenters 

supported transitioning the IPFQR 

Program to electronic reporting. 

Many commenters observed that IPFs 

have not received Federal incentives to 

support EHR adoption and expressed 

the belief that electronic data reporting 

without such funding is premature. 

Some commenters observed that the 

Transition Record measure is a 

complicated measure for e-specification. 

Some of these commenters noted that 

this measure requires a large number of 

data elements, some of which are not 

available in structured fields. One 

commenter recommended considering 

Metabolic Screening or Influenza 

Immunization for electronic 

specification as these measures have 

fewer data elements and those elements 

are available in structured fields. 

Another commenter observed that especification of existing chart measures 

often does not provide comparable 

results. 

Response: We thank commenters for 

this input. We acknowledge that IPFs 

were not eligible to receive prior Federal 

incentives to support EHR adoption and 

will consider this and other input as we 

seek to transition the IPFQR Program to 

electronic data reporting. 

I. Public Display and Review 

Requirements 

We refer readers to the FY 2013 IPPS/ 

LTCH PPS final rule (77 FR 53653 

through 53654), the FY 2014 IPPS/LTCH 

PPS final rule (78 FR 50897 through 

50898), and the FY 2017 IPPS/LTCH 

PPS final rule (81 FR 57248 through 

57249) for discussion of our previously 

finalized public display and review 

requirements. We did not propose any 

changes to these requirements. 

J. Form, Manner, and Timing of Quality 

Data Submission for the FY 2022 

Payment Determination and Subsequent 

Years 

1. Procedural Requirements for the FY 

2023 Payment Determination and 

Subsequent Years 

We refer readers to the FY 2013 IPPS/ 

LTCH PPS final rule (77 FR 53654 

through 53655), the FY 2014 IPPS/LTCH 

PPS final rule (78 FR 50898 through 

50899), and the FY 2018 IPPS/LTCH 

PPS final rule (82 FR 38471 through 

38472) for our previously finalized 

procedural requirements. In this final 

rule, we are finalizing our proposal to 

use the term ‘‘QualityNet security 

official’’ instead of ‘‘QualityNet system 

administrator,’’ finalizing our proposal 

to revise § 412.434(b)(3) by replacing the 

term ‘‘QualityNet system administrator’’ 

with the term ‘‘QualityNet security 

official,’’ and clarifying our policy 

under the previously finalized 

requirement that hospitals ‘‘[i]dentify a 

QualityNet Administrator who follows 

the registration process located on the 

QualityNet website’’ (77 FR 53654). 

a. Updated References to QualityNet 

System Administrator and to No Longer 

Require Active Account To Qualify for 

Payment 

The previously finalized QualityNet 

security administrator requirements, 

including those for setting up a 

QualityNet account and the associated 

timelines, are described in the FY 2013 

IPPS/LTCH final rule (77 FR 53654). 

In the FY 2022 IPF PPS proposed rule, 

we proposed to use the term 

‘‘QualityNet security official’’ instead of 

‘‘QualityNet system administrator’’ to 

denote the exercise of authority invested 

in the role and align with the Hospital 

Outpatient Quality Reporting Program 

and other programs (86 FR 19512). The 

term ‘‘security official’’ would refer to 

‘‘the individual(s)’’ who have 

responsibilities for security and account 

management requirements for a IPF’s 

QualityNet account. To clarify, this 

update in terminology will not change 

the individual’s responsibilities or add 

burden. 

We invited public comment on our 

proposal to replace the term 

‘‘QualityNet system administrator’’ with 

‘‘QualityNet security official.’’ 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42657 

165We also noted that a basic user is a QualityNet 

user who (1) does not have the registration access 

described for security officials, (2) has the 

appropriate data entry roles and permissions for 

program participation, (3) can submit and review 

measures and non-measure data, (4) signs and 

submits the Data Accuracy Completeness 

Acknowledgement (DACA) form, and (5) refreshes 

their QualityNet account password every 180 days 

to ensure that the facility’s IPFQR Program Notice 

of Participation status is ‘‘Participating.’’ 

We did not receive any public 

comments on this proposal. 

We are finalizing our proposal to 

replace the term ‘‘Quality Net system 

administrator’’ with ‘‘QualityNet 

security official’’ as proposed. 

Additionally, we proposed to no 

longer require IPFs to maintain an active 

QualityNet security official account to 

qualify for payment. As we reviewed the 

requirements for the security official 

role and the basic user 165 role to 

identify the most appropriate language 

to describe the distinguishing authority 

invested in the security official role, we 

recognized that the QualityNet security 

official is not required for submitting 

data—a basic user can serve in this 

role—but remains necessary to set up 

QualityNet basic user accounts and for 

security purposes. Therefore, consistent 

with adopting the security official term 

to differentiate the unique security 

authority and responsibilities of the role 

from the data submission 

responsibilities of the basic user role, 

we would continue to require a 

QualityNet basic user account to meet 

IPFQR Program requirements, including 

data submission and administrative 

requirements, while recommending, but 

not requiring, that hospitals maintain an 

active QualityNet security official 

account. 

We welcomed public comments on 

our proposal to no longer require 

facilities to maintain an active 

QualityNet security official account to 

qualify for payment. 

We received the following comments 

in response to our proposal. 

Comment: Many commenters 

supported removal of the requirement to 

have an active QualityNet Security 

Official for the complete year to meet 

IPFQR Program requirements and 

therefore be eligible to receive a full 

payment update. 

Response: We thank these 

commenters for their support. We note 

that IPFs that do not meet all IPFQR 

Program requirements must receive a 2 

percent reduction to their annual 

payment update. 

After review of the public comments 

received, we are finalizing our proposal 

to no longer require facilities to 

maintain an active QualityNet security 

official account to qualify for payment 

as proposed. 

b. Updated Reference to QualityNet 

Administrator in Code of Federal 

Regulations 

We proposed to revise our regulation 

at § 412.434(b)(3) by replacing 

‘‘QualityNet system administrator’’ with 

‘‘QualityNet security official.’’ The term 

‘‘QualityNet security official’’ refers to 

the individual(s) who have 

responsibilities for security and account 

management requirements for a 

hospital’s QualityNet account. To 

clarify, this update in terminology 

would not change the individual’s 

responsibilities or add burden. The 

revised paragraph (b)(3) reads: ‘‘Contact 

information for the inpatient psychiatric 

facility’s chief executive officer and 

QualityNet security official, including 

each individual’s name, email address, 

telephone number, and physical mailing 

address.’’ 

We invited public comment on our 

proposal to replace the term 

‘‘QualityNet system administrator’’ with 

‘‘QualityNet security official’’ at 

§ 412.434(b)(3). 

We did not receive any public 

comments in response to our proposal. 

We are finalizing our proposal to no 

longer require facilities to replace the 

term ‘‘QualityNet system administrator’’ 

with ‘‘QualityNet security official’’ at 

§ 412.434(b)(3) as proposed. 

2. Data Submission Requirements 

We refer readers to the FY 2013 IPPS/ 

LTCH PPS final rule (77 FR 53655 

through 53657), the FY 2014 IPPS/LTCH 

PPS final rule (78 FR 50899 through 

50900), and the FY 2018 IPPS/LTCH 

PPS final rule (82 FR 38472 through 

38473) for our previously finalized data 

submission requirements. In this final 

rule, we are finalizing our proposal to 

adopt one measure for the FY 2023 

payment determination and subsequent 

years and one measure for the FY 2024 

payment determination and subsequent 

years. Data submission requirements for 

each of these measures are described in 

the following subsections. Additionally, 

we are finalizing our proposal to adopt 

patient level data submission for certain 

chart abstracted measures beginning 

with data submitted for the FY 2023 

payment determination and subsequent 

years; details of this proposal are in 

subsection c. of this section. 

a. Data Submission Requirements for FY 

2023 Payment Determination and 

Subsequent Years 

The measure we are finalizing for FY 

2023 payment determination and 

subsequent years (the COVID–19 

Vaccination Coverage Among HCP 

measure) requires facilities to report 

data on the number of HCP who have 

received completed vaccination course 

of a COVID–19 vaccine through the 

CDC’s National Healthcare Safety 

Network (NHSN). Specific details on 

data submission for this measure can be 

found in the CDC’s Overview of the 

Healthcare Safety Component, available 

at https://www.cdc.gov/nhsn/PDFs/ 

slides/NHSN-Overview-HPS_

Aug2012.pdf. For each CMS 

Certification Number (CCN), a 

percentage of the HCP who received a 

completed vaccine course of the 

COVID–19 vaccination would be 

calculated and publicly reported, so that 

the public would know what percentage 

of the HCP have been vaccinated in each 

IPF. 

For the COVID–19 HCP Vaccination 

measure, we proposed that facilities 

would report the numerator and 

denominator for the COVID–19 HCP 

vaccination measure to the NHSN for at 

least one week each month, beginning 

in October 2021 for the October 1, 2021 

through December 31, 2021 reporting 

period affecting the FY 2023 payment 

determination. If facilities report more 

than one week of data in a month, the 

most recent week’s data would be used 

to calculate the measure. Each quarter, 

the CDC would calculate a single 

quarterly result of COVID–19 

vaccination coverage which would 

summarize the data submitted by IPFs 

for each of the three weeks of data 

submitted over the three-month period. 

CMS will publicly report the CDC’s 

quarterly summary of COVID–19 

vaccination coverage for IPFs. 

We invited public comment on our 

proposal to require facilities to report 

the COVID–19 HCP vaccination 

measure. 

We did not receive any comments in 

response to our proposal. 

We are finalizing our proposal to 

require facilities to report the COVID–19 

HCP vaccination measure as proposed. 

b. Data Submission Requirements for FY 

2024 Payment Determination and 

Subsequent Years 

Because the Follow-Up After 

Psychiatric Hospitalization (FAPH) 

measure would be calculated by CMS 

using Medicare Fee-for-Service claims, 

there will be no additional data 

submission requirements for the FY 

2024 payment determination and 

subsequent years. Therefore, we did not 

propose any changes to our data 

submission policies associated with the 

proposal to adopt this measure. 


lotter on DSK11XQN23PROD with RULES5
42658 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

166We note that in the FY 2022 IPF PPS proposed 

rule this incorrectly read HBIPS–2 (86 FR 19514). 

We have corrected it to HBIPS–3 here. 

c. Patient-Level Reporting for Certain 

Chart-Abstracted Measures Beginning 

With FY 2024 Payment Determination 

and Subsequent Years 

In the FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53655 through 53657), we 

finalized that IPFs participating in the 

IPFQR Program must submit data to the 

Web-Based Measures Tool found in the 

Inpatient Psychiatric Facility section of 

the QualityNet website’s secure portal 

between July 1 and August 15 of each 

year. We noted that the data input forms 

within the Quality Net secure portal 

require submission of aggregate data for 

each separate quarter. In the FY 2014 

IPPS/LTCH PPS final rule, we clarified 

our intent to require that IPFs submit 

aggregate data on measures on an 

annual basis via the Web-Based 

Measures Tool found in the IPF section 

of the Quality Net website’s secure 

portal and that the forms available 

require aggregate data for each separate 

quarter (78 FR 50899 through 50900). In 

the FY 2016 IPF PPS final rule (80 FR 

46716), we updated our data submission 

requirements to require facilities to 

report data for chart-abstracted 

measures to the Web-Based Measures 

Tool on an aggregate basis by year, 

rather than by quarter. Additionally, we 

discontinued the requirement for 

reporting by age group. We updated 

these policies in the FY 2018 IPPS/ 

LTCH PPS final rule (82 FR 38472 

through 38473) to change the 

specification of the submission deadline 

from exact dates to a 45-day submission 

period beginning at least 30 days 

following the end of the data collection 

period. 

In the FY 2019 IPF PPS final rule (83 

FR 38607), we observed that reporting 

aggregate measure data increases the 

possibility of human error, such as 

making typographical errors while 

entering data, which cannot be detected 

by CMS or by data submission systems. 

We noted that unlike patient-level data 

reporting, aggregate measure data 

reporting does not allow for data 

accuracy validation, thereby lowering 

the ability to detect error. We stated that 

we were considering requiring patientlevel data reporting (data regarding each 

patient included in a measure and 

whether the patient was included in 

each numerator and denominator of the 

measure) of IPFQR measure data in the 

future. We sought public comment on 

including patient-level data collection 

in the IPFQR program. Several 

commenters expressed support for 

patient-level data collection, observing 

that it provides greater confidence in the 

data’s validity and reliability. Other 

commenters recommended that CMS 

use a system that has already been 

tested and used for IPF data reporting or 

work with IPFs in selecting a system so 

that any selected system would avoid 

additional burden. 

We believe that patient-level data 

reporting would improve the accuracy 

of the submitted and publicly reported 

data without increasing burden. As we 

considered the current IPFQR measure 

set, we determined that patient-level 

reporting of the Hours of Physical 

Restraint Use (HBIPS–2, NQF #0640) 

measure and Hours of Seclusion Use 

(HBIPS–3,166 NQF #0641) measure 

would be appropriate for the numerators 

of these measures only, because these 

measures are calculated with a 

denominator of 1,000 hours rather than 

a denominator of patients who meet 

specific criteria for inclusion in the 

measure. Therefore, we proposed to 

require reporting patient-level 

information for the numerators of these 

measures only. For the remainder of the 

chart-abstracted measures in the IPFQR 

Program we proposed to require patientlevel reporting of the both the 

numerator and the denominator. Table 7 

lists the proposed FY 2023 IPFQR 

measure set categorized by whether we 

would require patient-level data 

submission through the QualityNet 

secure portal. 

BILLING CODE 4120–01–P 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42659 

BILLING CODE 4120–01–C 

Submission of aggregate data requires 

facilities to abstract patient-level data, 

then calculate measure performance 

prior to submitting data through the 

QualityNet website’s secure portal. For 

measures for which we would require 

patient-level data submission, we would 

allow facilities to submit data using a 

tool such as the CMS Abstraction & 

Reporting Tool (CART). This is the tool 

we use in our other quality reporting 

and value-based purchasing programs, 

and therefore, we believe that many 

facilities may already have familiarity 

with using this tool to abstract and 

report data. Additionally, the tool has 

been specifically designed to facilitate 

data reporting and minimize provider 

burden. 

We note that under aggregate data 

reporting, facilities submit aggregate 

numerators and aggregate denominators 

for all measures to CMS in the Hospital 

Quality Reporting (HQR) system. These 

aggregate numerators and denominators 

are generally calculated by manually 

abstracting the medical record of each 

included patient using the algorithm, a 

paper tool, or a vendor abstraction tool. 

After each required medical record has 

been abstracted, the numerator and 

denominator results are added up and 

submitted as aggregate values in the 

HQR system. Under our patient level 

data reporting proposal, facilities would 

still manually abstract the medical 

record using either a vendor abstraction 

tool or an abstraction tool provided by 

CMS. The vendor abstraction tool or the 

CMS tool would then produce an 

individual XML file for each of the cases 

abstracted. Instead of submitting the 

aggregate data, the IPF would log into 

HQR and upload batches of XML files 

that contain patient level data for each 

measure with data from all patients 

whose records were abstracted, and 

CMS would calculate the aggregate 

numerators, aggregate denominators, 

and measure rates from those XML file 

submissions. Because facilities must 

abstract patient-level data as one step in 

calculating measure results, we do not 

believe that requiring patient-level data 

submission would increase provider 

costs or burden associated with measure 

submission. 


lotter on DSK11XQN23PROD with RULES5ER04AU21.176</GPH>

TABLE 7: Patient-level data submission requirements for FY 2024 IPFQR Program 

measure set 

NQF# Measure ID Measure Patient-Level 

Data Submission 

0640 HBIPS-2 Hours of Physical Restraint Use Yes, numerator 

only 

0641 HBIPS-3 Hours of Seclusion Use Yes, numerator 

onlv 

0560 HBIPS-5 Patients Discharged on Multiple Antipsychotic Medications Yes 

with Appropriate Justification 

0576 FUH Follow-Up After Hospitalization for Mental Illness No ( claims-based) 

NIA* SUB-2 and Alcohol Use Brief Intervention Provided or Offered and Yes 

SUB-2a SUB-2a Alcohol Use Brieflntervention 

NIA* SUB-3 and Alcohol and Other Drug Use Disorder Treatment Provided or Yes 

SUB-3a Offered at Discharge and SUB-3a Alcohol and Other Drug 

Use Disorder Treatment at Discharge 

NIA* TOB-2 and Tobacco Use Treatment Provided or Offered and TOB-2a Yes 

TOB-2a Tobacco Use Treatment 

NIA* TOB-3 and Tobacco Use Treatment Provided or Offered at Discharge and Yes 

TOB-3a TOB-3a Tobacco Use Treatment at Discharge 

1659 IMM-2 Influenza Immunization Yes 

NIA* NIA Transition Record with Specified Elements Received by Yes 

Discharged Patients (Discharges from an Inpatient Facility to 

Home/Self Care or Anv Other Site of Care) 

NIA* NIA Timely Transmission of Transition Record (Discharges from Yes 

an Inpatient Facility to Home/Self Care or any Other Site of 

Care) 

NIA NIA Screening for Metabolic Disorders Yes 

2860 NIA Thirty-Day All-Cause Unplanned Readmission Following No (claims-based) 

Psychiatric Hospitalization in an Inpatient Psychiatric Facility 

3205 Med Cont Medication Continuation Following Inpatient Psychiatric No (claims-based) 

Discharge 

TBD COVIDHCP COVID-19 Healthcare Personnel (HCP) Vaccination Measure No ( calculated for 

HCP) 

* Measure is no longer endorsed by the NQF but was endorsed at time of adoption. Section 1886(s)(4)(D)(ii) of 

the Act authorizes the Secretary to specify a measure that is not endorsed by the NQF as long as due consideration is 

given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We 

attempted to find available measures for each of these clinical topics that have been endorsed or adopted by a 

consensus organization and found no other feasible and practical measures on the topics for the IPF setting. 
42660 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

Because we believe that patient-level 

data would improve the data accuracy 

without increasing provider burden, we 

proposed to adopt patient-level data 

reporting for numerators only for the 

Hours of Physical Restraint Use (HBIPS– 

2, NQF #0640) and the Hours of 

Seclusion Use (HBIPS–3, NQF #0631) 

for numerators and denominators for the 

following 9 chart-abstracted IPFQR 

Program measures as detailed in Table 

7: Patients Discharged on Multiple 

Antipsychotic Medications with 

Appropriate Justification (NQF #0560); 

Alcohol Use Brief Intervention Provided 

or Offered and SUB–2a Alcohol Use 

Brief Intervention; Alcohol and Other 

Drug Use Disorder Treatment Provided 

or Offered at Discharge and SUB–3a 

Alcohol and Other Drug Use Disorder 

Treatment at Discharge; Tobacco Use 

Treatment Provided or Offered and 

TOB–2a Tobacco Use Treatment; 

Tobacco Use Treatment Provided or 

Offered at Discharge and TOB–3a 

Tobacco Use Treatment at Discharge; 

Influenza Immunization (NQF #1659); 

Transition Record with Specified 

Elements Received by Discharged 

Patients (discharges from an Inpatient 

Facility to Home/Self Care or Any Other 

Site of Care); Timely Transmission of 

Transition Record (Discharges from an 

Inpatient Facility to Home/Self Care or 

any Other Site of Care); and Screening 

for Metabolic Disorders. 

We believe that it is appropriate to 

transition to patient-level reporting 

incrementally. This would allow 

facilities to become familiar with the 

data submission systems and to provide 

feedback on any challenges they face in 

reporting data to us. Therefore, we 

proposed to allow voluntary patientlevel data submission for the FY 2023 

payment determination (that is, data 

submitted during CY 2022). We note 

that because participation in patientlevel reporting for these chart-abstracted 

measures would be voluntary for this 

one-year period, facilities would be able 

to choose whether to submit measure 

data in aggregate or at the patient level, 

and would not face a payment reduction 

as long as they submit all measure data 

either at the patient level or in aggregate 

for each measure for which reporting is 

required, and as long as they met all 

other IPFQR Program requirements. 

Therefore, we are proposed to allow 

voluntary patient-level reporting prior 

to requiring such data submission for 

one year prior to the FY 2024 payment 

determination. We will ensure that 

facilities have guidance available 

through our standard communications 

channels (that is, listserv 

announcements, educational webinars, 

and training material on the QualityNet 

website). 

We also proposed to require patientlevel data submission for these chartabstracted measures for the FY 2024 

payment determination (that is, data 

submitted during CY 2023) and 

subsequent years. 

We welcomed comment on our 

proposals to allow voluntary patientlevel data reporting for these chartabstracted measures for the FY 2023 

payment determination and then to 

require patient-level data reporting for 

the FY 2024 payment determination and 

subsequent years. 

We received the following comments 

in response to our proposal. 

Comment: Many commenters 

supported the adoption of patient-level 

reporting. Many of these commenters 

supported initiating the process with 

one year of voluntary participation. One 

commenter observed that having patient 

level data would help accurately 

identify trends and improve outcomes 

and with demographic data could help 

identify health disparities. One 

commenter specifically supported the 

numerator only patient-level reporting 

for HBIPS–2 and HBIPS–3. One 

commenter observed that HBIPS–2 was 

listed twice in the proposed rule (86 FR 

19514). 

Response: We thank these 

commenters for their support. 

Comment: Some commenters 

recommended that CMS use a more 

gradual transition to patient-level 

reporting. One commenter specifically 

recommended two cycles of voluntary 

reporting to ensure that the data 

submission system works properly. 

Others recommended that CMS provide 

additional guidance and education, 

including XML specifications or other 

reporting templates prior to the 

voluntary reporting period. One 

commenter recommended aligning 

guidance across programs. One 

commenter observed that the start date 

for collecting data for the mandatory 

reporting period is before the data 

submission timeframe for the voluntary 

reporting period. 

Response: We recognize that IPFs will 

need additional guidance and education 

in preparation for patient-level 

reporting. We will provide templates, 

guidance, and education and outreach 

sessions prior to beginning patient level 

reporting. We note that, to the extent 

feasible, we will align guidance across 

programs. We do not believe that it is 

necessary to have a longer voluntary 

reporting period because many IPFs also 

have experience with these tools already 

and we have extensive experience with 

patient-level reporting, both using 

electronic data reporting systems, and 

using tools such as the CMS Abstraction 

& Reporting Tool (CART) in our other 

quality reporting programs and intend 

to provide templates, guidance and 

education and outreach to IPFs. 

Comment: Some commenters 

recommended that CMS not require 

patient level reporting for measures 

proposed for removal. 

Response: We note that the measure 

being removed from the IPFQR Program 

(Timely Transmission of Transition 

Record (Discharges from an Inpatient 

Facility to Home/Self Care or any Other 

Site of Care)) is being removed for FY 

2024 payment determination and 

subsequent years. The first year of 

mandatory patient-level reporting is FY 

2024 payment determination. Therefore, 

this measure will no longer be in the 

program when patient-level reporting is 

required. We further note that we are 

not finalizing our proposals to remove 

Alcohol Use Brief Intervention Provided 

or Offered and Alcohol Use Brief 

Intervention (SUB–2/2a) and Tobacco 

Use Treatment Provided or Offered and 

Tobacco Use Treatment (TOB–2/2a); 

and therefore these patient-level data 

reporting will be required for these 

measures beginning with the FY 2024 

payment determination. 

Comment: Some commenters oppose 

patient level reporting because of a lack 

of technology. Some commenters 

observed that CMS should assist with 

development of EHRs in the same way 

they did for acute care hospitals. One 

commenter observed that patient-level 

reporting would be burdensome without 

EHR technology. 

Response: We disagree with 

commenters that EHR technology is 

necessary for patient level reporting and 

note that acute care hospitals reported 

patient-level data for the Hospital IQR 

Program prior to the introduction of the 

HITECH act and associated meaningful 

use incentives. We further note that 

because IPFs must abstract the same 

data from patient records regardless of 

whether they are reporting at the 

patient-level or in aggregate, we do not 

believe that submitting patient-level 

data is more burdensome than aggregate 

data reporting for providers whether or 

not they have EHR technology. 

Comment: One commenter requested 

clarification on the start date for 

voluntary patient-level data submission 

for FY 2023. This commenter 

specifically requested clarification on 

whether that would be for discharges 

beginning for FY 2023 or CY 2023. 

Response: The voluntary patient-level 

data submission period is for FY 2023 

payment determination. This applies to 

the data submitted during CY 2022 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42661 

(which affects FY 2023 payment 

determination). Data submitted during 

CY 2022 covers discharges that occur 

during CY 2021. 

After review of the public comments 

we received, we are finalizing our 

proposal to allow voluntary patientlevel data reporting for these chartabstracted measures for the FY 2023 

payment determination and then to 

require patient-level data reporting for 

the FY 2024 payment determination and 

subsequent years as proposed. 

3. Considerations for Data Validation 

Pilot 

As discussed in section IV.J.4 and in 

the FY 2019 IPF PPS final rule, we are 

concerned about the limitations of 

aggregate data submission (83 FR 

28607). One such concern was that the 

ability to detect error is lower for 

aggregate measure data reporting than 

for patient-level data reporting (that is, 

data regarding each patient included in 

a measure and whether the patient was 

included in the numerator and 

denominator of the measure). In the FY 

2022 IPF PPS proposed rule, we noted 

that if we finalize our proposal to adopt 

patient-level data requirements, we 

would be able to adopt a data validation 

policy for the IPFQR Program in the 

future (86 FR 19515). We believe that it 

would be appropriate to develop such a 

policy incrementally through adoption 

of a data validation pilot prior to 

national implementation of data 

validation within the IPFQR Program. 

We sought public input on elements of 

a potential data validation pilot, for 

example, the number of measures to 

validate, number of participating 

facilities, whether the pilot should be 

mandatory or voluntary, potential 

thresholds for determining measure 

accuracy, or any other policies that 

commenters believe would be 

appropriate to include in a data 

validation pilot or eventual data 

validation policy. 

We received the following comments 

in response to our request. 

Comment: Many commenters 

supported the concept of data validation 

but recommended that CMS ensure a 

stable and successful patient-level 

reporting process prior to developing a 

data validation plan. 

One commenter recommended using 

two measures and 200 hospitals to pilot 

data validation. 

Some commenters did not support 

eventual adoption of validation for the 

IPFQR program because of the belief 

that data validation would be 

burdensome. One commenter observed 

data validation is only necessary in payfor-performance programs. 

Response: We thank these 

commenters for this input and will take 

it into consideration if we develop a 

data validation program for the IPFQR 

Program. 

4. Reporting Requirements for the FY 

2022 Payment Determination and 

Subsequent Years 

We refer readers to the FY 2013 IPPS/ 

LTCH PPS final rule (77 FR 53656 

through 53657), the FY 2014 IPPS/LTCH 

PPS final rule (78 FR 50900 through 

50901), and the FY 2015 IPF PPS final 

rule (79 FR 45976 through 45977) for 

our previously finalized reporting 

requirements. We did not propose any 

changes to these policies. 

5. Quality Measure Sampling 

Requirements 

We refer readers to the FY 2013 IPPS/ 

LTCH PPS final rule (77 FR 53657 

through 53658), the FY 2014 IPPS/LTCH 

PPS final rule (78 FR 50901 through 

50902), the FY 2016 IPF PPS final rule 

(80 FR 46717 through 46719), and the 

FY 2019 IPF PPS final rule (83 FR 38607 

through 38608) for discussions of our 

previously finalized sampling policies. 

In the FY 2022 IPF PPS proposed rule, 

we noted that neither the measure we 

proposed to remove (FUH—NQF #0576) 

nor the measure we proposed to adopt 

(FAPH) if we remove the FUH–NQF 

#0576 are affected by our sampling 

policies because these are both 

calculated by CMS using Medicare Feefor-Service claims and, therefore, apply 

to all Medicare patients in the 

denominator (86 FR 19515). 

Furthermore, the denominator of the 

COVID–19 Healthcare Personnel 

Vaccination measure we are adopting in 

this final rule is all healthcare 

personnel, and therefore, this measure is 

not eligible for sampling. We did not 

propose any changes to these policies. 

6. Non-Measure Data Collection 

We refer readers to the FY 2015 IPF 

PPS final rule (79 FR 45973), the FY 

2016 IPF PPS final rule (80 FR 46717), 

and the FY 2019 IPF PPS final rule (83 

FR 38608) for our previously finalized 

non-measure data collection policies. 

We did not propose any changes to 

these policies. 

7. Data Accuracy and Completeness 

Acknowledgement (DACA) 

Requirements 

We refer readers to the FY 2013 IPPS/ 

LTCH PPS final rule (77 FR 53658) for 

our previously finalized DACA 

requirements. We did not propose any 

changes to these policies. 

K. Reconsideration and Appeals 

Procedures 

We refer readers to 42 CFR 412.434 

for the IPFQR Program’s reconsideration 

and appeals procedures. We did not 

propose any changes to these policies. 

L. Extraordinary Circumstances 

Exceptions (ECE) Policy 

We refer readers to the FY 2013 IPPS/ 

LTCH PPS final rule (77 FR 53659 

through 53660), the FY 2014 IPPS/LTCH 

PPS final rule (78 FR 50903), the FY 

2015 IPF PPS final rule (79 FR 45978), 

and the FY 2018 IPPS/LTCH PPS final 

rule (82 FR 38473 through 38474) for 

our previously finalized ECE policies. 

We did not propose any changes to 

these policies. 

V. Collection of Information 

Requirements 

Under the Paperwork Reduction Act 

of 1995 (PRA) (44 U.S.C. 3501 et seq.), 

we are required to provide 60-day notice 

in the Federal Register and solicit 

public comment before a ‘‘collection of 

information’’ (as defined under 5 CFR 

1320.3(c) of the PRA’s implementing 

regulations) requirement is submitted to 

the Office of Management and Budget 

(OMB) for review and approval. In order 

to fairly evaluate whether an 

information collection should be 

approved by OMB, section 3506(c)(2)(A) 

of the PRA requires that we solicit 

comment on the following issues: 

• The need for the information 

collection and its usefulness in carrying 

out the proper functions of our agency. 

• The accuracy of our estimate of the 

information collection burden. 

• The quality, utility, and clarity of 

the information to be collected. 

• Recommendations to minimize the 

information collection burden on the 

affected public, including automated 

collection techniques. 

In the FY 2022 IPF PPS proposed rule 

(86 FR 19480) we solicited public 

comment on each of the section 

3506(c)(2)(A)-required issues for the 

following information collection 

requirements (ICRs). As indicated in 

section V.2.c.(1) of this final rule, we 

received some comments that generally 

discuss the burden of reporting through 

NHSN, but not comments specific to our 

information collection estimates. We 

have not made any changes from what 

was proposed. 

A. Final ICRs for the (IPFQR) Program 

The following final requirement and 

burden changes will be submitted to 

OMB for approval under control number 

0938–1171 (CMS–10432). 


lotter on DSK11XQN23PROD with RULES5
42662 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

167https://www.bls.gov/oes/current/ 

oes292098.htm (Accessed on June 28, 2021). 

168http://www.whitehouse.gov/omb/circulars_

a076_a76_incl_tech_correction. 

169https://www.reginfo.gov/public/do/ 

PRAViewDocument?ref_nbr=201908-0938-011. 

1. Wage Estimates 

In the FY 2020 IPF PPS final rule (84 

FR 38468), which was the most recent 

rule in which we adopted updates to the 

IPFQR Program, we estimated that 

reporting measures for the IPFQR 

Program could be accomplished by a 

Medical Records and Health 

Information Technician (BLS 

Occupation Code: 29–2071) with a 

median hourly wage of $18.83/hr (May 

2017). In May 2019, the U.S. Bureau of 

Labor Statistics (BLS) revised their 

$18.83/hr wage figure to $20.50/hr (May 

2019).167 In response, we proposed to 

adjust our cost estimates using the 

updated median wage rate figure of 

$20.50/hr., an increase of $1.67/hr. We 

are finalizing our proposal to use the 

$20.50/hr wage in this FY 2022 final 

rule. 

Under OMB Circular A–76, in 

calculating direct labor, agencies should 

not only include salaries and wages, but 

also ‘‘other entitlements’’ such as fringe 

benefits and overhead.168 Consistent 

with our past approach, we continue to 

calculate the cost of fringe benefits and 

overhead at 100 percent of the median 

hourly wage (81 FR 57266). This is 

necessarily a rough adjustment, both 

because fringe benefits and overhead 

costs vary significantly from employer 

to employer, and methods of estimating 

these costs vary widely from study to 

study. Therefore, using these 

assumptions, we estimate an hourly 

labor cost increase from $37.66/hr 

($18.83/hr base salary + $18.83/hr fringe 

benefits and overhead) to $41.00/hr 

($20.50/hr base salary + $20.50/hr fringe 

benefits and overhead). Table 8 presents 

these assumptions. 

2. ICRs Regarding the Inpatient 

Psychiatric Facility Quality Reporting 

(IPFQR) Program 

In subsection 2.a., we restate our 

currently approved burden estimates. In 

subsection 2.b., we estimate the 

adjustments in burden associated with 

the updated BLS wage rate, our facility 

estimates, and our case estimates. In 

subsection 2.c., we estimate the changes 

in burden associated with the finalized 

policies in this rule. Finally, in 

subsection 2.d., we provide an overview 

of the total estimated burden. 

a. Currently Approved Burden 

For a detailed discussion of the 

burden for the IPFQR Program 

requirements that we have previously 

adopted, we refer readers to the 

following rules: 

• The FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53673); 

• The FY 2014 IPPS/LTCH PPS final 

rule (78 FR 50964); 

• The FY 2015 IPF PPS final rule (79 

FR 45978 through 45980); 

• The FY 2016 IPF PPS final rule (80 

FR 46720 through 46721); 

• The FY 2017 IPPS/LTCH PPS final 

rule (81 FR 57265 through 57266); 

• The FY 2018 IPPS/LTCH PPS final 

rule (82 FR 38507 through 38508); 

• The FY 2019 IPF PPS final rule (83 

FR 38609 through 38612); and 

• The FY 2020 IPF PPS final rule (84 

FR 38468 through 38476). 

Tables 9, 10, and 11 provide an 

overview of our currently approved 

burden. These tables use our previous 

estimate of $37.66/hr ($18.83/hr base 

salary plus $18.83/hr fringe benefits and 

overhead) hourly labor cost. For more 

information on our currently approved 

burden estimates, please see Supporting 

Statement A on the Office of 

Information and Regulatory Affairs 

(OIRA) website.169

BILLING CODE 4120–01–P 


lotter on DSK11XQN23PROD with RULES5ER04AU21.177</GPH>

Information Technician 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42663 


lotter on DSK11XQN23PROD with RULES5ER04AU21.178</GPH>

TABLE 9: Currently Approved Measure Collection and Reporting Burden 

0640 HBIPS- Hours of 1,283 0.25 320.75 1,679 538,539.25 20,281,388 

2 Physical 

Restraint Use 

0641 HBIPS- Hours of 1,283 0.25 320.75 1,679 538,539.25 20,281,388 

3 Seclusion Use 

0560 HBIPS- Patients 609 0.25 152.25 1,679 255,627.75 9,626,941 

5 Discharged on 

Multiple 

Antipsychotic 

Medications 

with 

Appropriate 

Justification 

NIA SUB-2 Alcohol Use 609 0.25 152.25 1,679 255,627.75 9,626,941 

and Brief 

SUB-2a Intervention 

Provided or 

Offered 

NIA SUB-3 Alcohol and 609 0.25 152.25 1,679 255,627.75 9,626,941 

and Other Drug 

SUB-3a Use Disorder 

Treatment 

Provided or 

Offered at 

Discharge and 

Alcohol and 

Other Drug 

Use Disorder 

Treatment at 

Dischar e 

0576 FUH Follow-Up 0 0 0 0 0 0 

After 

Hospitalization 

for Mental 

Illness* 

NIA TOB-2 Tobacco Use 609 0.25 152.25 1,679 255,627.75 9,626,941 

and Treatment 

TOB-2a Provided or 

Offered and 

Tobacco Use 

Treatment 

NIA TOB-3 Tobacco Use 609 0.25 152.25 1,679 255,627.75 9,626,941 

and Treatment 

TOB-3a Provided or 

Offered at 

Discharge and 

Tobacco Use 

Treatment at 

Dischar e 

1659 IMM-2 Influenza 609 0.25 152.25 1,679 255,627.75 9,626,941 

Immunization 

0647 NIA Transition 609 0.25 152.25 1,679 255,627.75 9,626,941 

Record with 

S ecified 
42664 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 


lotter on DSK11XQN23PROD with RULES5ER04AU21.179</GPH> ER04AU21.180</GPH>

Elements 

Received by 

Discharged 

Patients 

(Discharges 

from an 

Inpatient 

Facility to 

Home/Self 

Care or Any 

Other Site of 

Care 

0648 NIA Timely 609 0.25 152.25 1,679 255,627.75 9,626,941 

Transmission 

of Transition 

Record 

(Discharges 

from an 

Inpatient 

Facility to 

Home/Self 

Care or Any 

Other Site of 

Care 

NIA NIA Screening for 609 0.25 152.25 1,679 255,627.75 9,626,941 

Metabolic 

Disorders 

2860 NIA Thirty-day all- 0 0 0 0 0 0 

cause 

unplanned 

readmission 

following 

psychiatric 

hospitalization 

in an IPF* 

3205 Med Medication 0 0 0 0 0 0 

Cont Continuation 

Following 

Inpatient 

Psychiatric 

Dischar e* 

* CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not require 

facilities to submit data on any cases. 

Non-measure Data 

Collection and Submission 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42665 

b. Final Adjustments in Burden due to 

Updated Wage, Facility Count, and Case 

Count Estimates 

In the FY 2020 IPF PPS final rule (84 

FR 38468), which is the most recent 

rule, that updated the IPFQR Program 

policies, we estimated that there were 

1,679 participating IPFs and that (for 

measures that require reporting on the 

entire patient population) these 

facilities will report on an average of 

1,283 cases per facility. In this FY 2022 

rule, we are finalizing our proposal to 

update our facility count and case 

estimates by using the most recent data 

available. Specifically, we estimate that 

there are now approximately 1,634 

facilities (a decrease of 45 facilities) and 

an average of 1,346 cases per facility (an 

increase of 63 cases per facility). Tables 

12, 13, and 14, depict the effects of these 

updates, as well as the wage rate update 

to $41.00/hr described in section V.A.1 

of the preamble of this final rule, on our 

previously estimated burden. 


lotter on DSK11XQN23PROD with RULES5ER04AU21.181</GPH>

Measure Data Collection and Reporting 1,679 

Non-Measure Data Collection and 1,679 

Reporting 

Notice of Participation, Data Accuracy NIA 

Acknowledgment, and Vendor 

Authorization Form* 

13,510,913 

(8,047 responses 

or cases per 

facility * 1,679 

facilities 

6,716 (4 * 

responses per 

facility * 1,679 

facilities 

NIA 

3,377,728 127,205,245 

3,358 126,462 

NIA NIA 

* The 15 minutes per measure for chart abstraction under Measure Data Collection and Reporting also includes the 

time for completing and submitting any forms. 
42666 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 


lotter on DSK11XQN23PROD with RULES5ER04AU21.182</GPH>

TABLE 12: Measure Collection and Reporting Burden Based on Updated Wage Rate, 

Facili Count, and Case Count 

0640 HBIPS- Hours of 1,346 0.25 336.50 1,634 549,841 22,543,481 

2 Physical 

Restraint Use 

0641 HBIPS- Hours of 1,346 0.25 336.50 1,634 549,841 22,543,481 

3 Seclusion Use 

0560 HBIPS- Patients 609* 0.25 152.25 1,634 248,776.5 10,199,836.50 

5 Discharged on 

Multiple 

Antipsychotic 

Medications 

with 

Appropriate 

Justification 

NIA SUB-2 Alcohol Use 609* 0.25 152.25 1,634 248,776.5 10,199,836.50 

and Brief 

SUB-2a Intervention 

Provided or 

Offered and 

Alcohol Use 

Brief 

Intervention 

Provided 

NIA SUB-3 Alcohol and 609* 0.25 152.25 1,634 248,776.5 10,199,836.50 

and Other Drug 

SUB-3a Use Disorder 

Treatment 

Provided or 

Offered at 

Discharge and 

Alcohol and 

Other Drug 

Use Disorder 

Treatment at 

Dischar e 

0576 FUH Follow-Up 0 0 0 0 0 0 

After 

Hospitalization 

for Mental 

Illness* 

NIA TOB-2 Tobacco Use 609* 0.25 152.25 1,634 248,776.5 10,199,836.50 

and Treatment 

TOB-2a Provided or 

Offered and 

Tobacco Use 

Treatment 

NIA TOB-3 Tobacco Use 609* 0.25 152.25 1,634 248,776.5 10,199,836.50 

and Treatment 

TOB-3a Provided or 

Offered at 

Discharge and 

Tobacco Use 

Treatment at 

Dischar e 

1659 IMM-2 Influenza 609* 0.25 152.25 1,634 248,776.5 10,199,836.50 

Immunization 

0647 NIA Transition 609* 0.25 152.25 1,634 248,776.5 10,199,836.50 

Record with 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42667 


lotter on DSK11XQN23PROD with RULES5ER04AU21.183</GPH>

Specified 

Elements 

Received by 

Discharged 

Patients 

(Discharges 

from an 

Inpatient 

Facility to 

Home/Self 

Care or Any 

Other Site of 

Care 

0648 NIA Timely 609* 0.25 152.25 1,634 248,776.5 10,199,836.50 

Transmission 

of Transition 

Record 

(Discharges 

from an 

Inpatient 

Facility to 

Home/Self 

Care or Any 

Other Site of 

Care 

NIA NIA Screening for 609* 0.25 152.25 1,634 248,776.5 10,199,836.50 

Metabolic 

Disorders 

2860 NIA Thirty-day all- 0 0 0 0 0 0 

cause 

unplanned 

readmission 

following 

psychiatric 

hospitalization 

in an IPF* 

3205 Med Medication 0 0 0 0 0 0 

Cont Continuation 

Following 

Inpatient 

Psychiatric 

Dischar e* 

NIA COVID- COVID-19 0** 0 0 0 0 0 

19HCP Vaccination 

Rate Among 

Healthcare 

Personnel 

NIA FAPH Follow-Up 0 0 0 0 0 0 

After 

Psychiatric 

Hos italization 

* Under our previously finalized "global sample" (80 FR 46717 through 46718) we allow facilities to apply the 

same sampling methodology to all measures eligible for sampling. In the FY 2016 IPF PPS fmal rule (80 FR 

46718), we finalized that facilities with between 609 and 3,056 cases that choose to participate in the global sample 

would be required to report data for 609 cases. Because facilities are only required to submit data on a number 

specified by the global sampling methodology, rather than abstracting data for all patients or applying measure 

specific sampling methodologies, we believe that the number of cases under the global sample is a good 

approximation ofIPF burden associated with these measures. Therefore, for the average IPF discharge rate of 1,346 

discharges versus the previously estimated 1,283, the global sample continues to require abstraction of 609 records. 

** The COVID-19 HCP measure will be calculated using data submitted to the CDC under a separate 0MB Control 

Number (0920-1317). 
42668 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

170Section 321 of the National Childhood 

Vaccine Injury Act (NCVIA) provides the PRA 

waiver for activities that come under the NCVIA, 

including those in the NCVIA at section 2102 of the 

Public Health Service Act (42 U.S.C. 300aa–2). 

Section 321 is not codified in the U.S. Code, but 

can be found in a note at 42 U.S.C. 300aa–1. 

171https://www.bls.gov/oes/current/ 

oes436013.htm (accessed on March 30, 2021). The 

hourly rate of $36.62 includes an adjustment of 100 

percent of the median hourly wage to account for 

the cost of overhead, including fringe benefits. 

BILLING CODE 4120–01–C 

c. Changes in Burden due to This Final 

Rule 

(1) Updates Due to Final Measure 

Adoptions 

In section IV.E of this preamble, we 

are adopting the following two 

measures: 

• COVID–19 Vaccination Among HCP 

for FY 2023 Payment Determination and 

Subsequent Years; and 

• Follow-Up After Psychiatric 

Hospitalization (FAPH) for FY 2024 

Payment Determination and Subsequent 

Years. 

We are adopting the COVID–19 

Vaccination among HCP measure 

beginning with an initial reporting 

period from October 1 to December 31, 

2021 affecting the FY 2023 payment 

determination followed by quarterly 

reporting beginning with the FY 2024 

payment determination and subsequent 

years. IPFs will submit data through the 

CDC’s NHSN. The NHSN is a secure, 

internet-based system that is maintained 

by the CDC and provided free. The CDC 

does not estimate burden for COVID–19 

vaccination reporting since the 

department has been granted a waiver 

under Section 321 of the National 

Childhood Vaccine Injury Act of 1986 

(NCVIA).170

Although the burden associated with 

the COVID–19 HCP Vaccination 

measure is not accounted for due to the 

NCVIA waiver, the burden is set forth 

here and will be accounted for by the 

CDC under OMB control number 0920– 

1317. 

Consistent with the CDC’s experience 

of collecting data using the NHSN, we 

estimate that it will take each IPF on 

average approximately 1 hour per 

month to collect data for the COVID–19 

Vaccination Coverage among HCP 

measure and enter it into NHSN. We 

have estimated the time to complete this 

entire activity, since it could vary based 

on provider systems and staff 

availability. This burden is comprised of 

administrative time and wages. We 

believe it would take an Administrative 

Assistant 171 between 45 minutes (0.75 

hr) and 1 hour and 15 minutes (1.25 hr) 

to enter the data into NHSN. For the CY 

2021 reporting period (consisting of 

October 1, 2021 through December 31, 

2021) 3 months are required. For the CY 

2021 reporting period/FY 2023 payment 

determination, IPFs would incur an 

additional burden between 2.25 hours 

(0.75 hours * 3 responses at 1 response 

per month) and 3.75 hours (1.25 hours 

* 3 responses at 1 response per month) 

per IPF. For all 1,634 IPFs, the total time 

would range from 3,676.5 hours (2.25 

hours * 1,634 IPFs) and 6,127.5 hours 

(3.75 hours * 1,634 IPFs). 

Each IPF would incur an estimated 

cost of between $27.47 (0.75 hour * 

$36.62/hr) and $45.78 (1.25 hours * 

$36.62/hr) monthly and between $82.40 

(2.25 hours * $36.62/hr) and $137.33 

(3.75 hours * $36.62/hr) in total over the 

CY 2021 reporting period to complete 

this task. Thereafter, 12 months of data 

are required annually. Therefore, IPFs 

would incur an additional annual 

burden between 9 hours (0.75 hours/ 

month * 12 months) and 15 hours (1.25 

hours/month * 12 months) per IPF and 

between 14,706 hours (9 hours/IPF * 

1,634 IPFs) and 24,510 hours (15 hours/ 

IPF * 1,634 IPFs) for all IPFs. Each IPF 

would incur an estimated cost of 

between $329.58 (9 hours × $36.62/hr) 

and $549.30 annually (15 hours × 

$36.62/hr). The estimated cost across all 

1,634 IPFs would be between 

$134,641.60 ($82.40/IPF * 1,634 IPFs) 

and $224,397.22 ($137.33/IPF * 1,634 

IPFs) for the CY 2021 reporting period. 

The estimated cost across all 1,634 IPFs 

would be between $538,533.72 

($329.58/IPF * 1,634 IPFs) and 

$897,556.20 ($549.30/IPF * 1,634 IPFs) 

annually thereafter. Since the burden 

falls under the authority of the CDC, we 

have not added such burden to Table 

16. 

We recognize that many healthcare 

facilities are also reporting other 

COVID–19 data to HHS. We believe the 

benefits of requiring IPFs to report data 

on the COVID–19 HCP Vaccination 

measure to assess whether they are 

taking steps to limit the spread of 


lotter on DSK11XQN23PROD with RULES5ER04AU21.184</GPH> ER04AU21.185</GPH>

TABLE 13: Non-Measure Data Collection and Reporting Burden Based on Updated Wage 

Rate Facili Count and Case Count 

Non-measure Data 

Collection and Submission 

Measure Data 1,634 

Collection and 

Reporting (See 

Table 12 

Non-Measure 1,634 

Data Collection 

and Reporting 

13,354,682 (8,173 3,338,671 136,885,491 

responses per facility 

* 1,634 facilities) 

6,536 (4 responses per 3,268 133,988 

facility * 1,634 

facilities) 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42669 

COVID–19 among their healthcare 

workers and to help sustain the ability 

of IPFs to continue serving their 

communities throughout the PHE and 

beyond outweigh the costs of reporting. 

In our proposed rule, we welcomed 

comments on the time to collect data 

and enter it into the NHSN. While we 

did receive some comments addressing 

the burden of NHSN reporting, which 

we address in section IV.E.2 of this rule, 

we did not receive any public comments 

on the estimated time to collect and 

submit such data. 

We further note that as described in 

section IV.E.3 of this preamble, we will 

calculate the FAPH measure using 

Medicare Part A and Part B claims that 

IPFs and other providers (specifically 

outpatient providers who provide the 

follow-up care) submit for payment. 

Since this is a claims-based measure, 

there is no additional burden outside of 

submitting the claim. The claim 

submission is approved by OMB under 

control number 0938–0050 (CMS–2552– 

10). This rule does not warrant any 

changes under that control number. 

(2) Updates Due to Final Measure 

Removals 

In section IV.F. of this preamble, we 

are finalizing our proposals to remove 

the following two measures for the FY 

2024 payment determination and 

subsequent years: 

• Timely Transmission of Transition 

Record (Discharges from an Inpatient 

Facility to Home/Self Care or Any Other 

Site of Care); and 

• FUH—Follow-Up After 

Hospitalization for Mental Illness (NQF 

#0576). 

We note that we are not finalizing our 

proposals to remove the following two 

measures: 

• SUB–2—Alcohol Use Brief 

Intervention Provided or Offered and 

the subset measure SUB–2a Alcohol Use 

Brief Intervention Provided; and 

• TOB–2—Tobacco Use Treatment 

Provided or Offered and the subset 

measure TOB–2a Tobacco Use 

Treatment. 

For the FY 2024 payment 

determination, data on CY 2022 

performance would be reported during 

the summer of 2023. Therefore, we are 

applying the burden reduction that 

would occur to the FY 2023 burden 

calculation. One of the measures we are 

removing (the Timely Transmission of 

Transition Record (Discharges from an 

Inpatient Facility to Home/Self Care or 

Any Other Site of Care) measure) falls 

under our previously finalized ‘‘global 

sample’’ (80 FR 46717 through 46718) 

and, therefore, would require 

abstraction of 609 records. We estimate 

that removing this measure would result 

in a decrease in burden of 152.25 hours 

per facility (609 cases per facility * 0.25 

hours per case), or 248,776.5 hours 

(152.25 hours/facility × 1,634 facilities) 

across all IPFs. Therefore, the decrease 

in costs for each measure is 

approximately $6,242.25 per IPF 

($41.00/hr * 152.25 hours), or 

$10,199,836.50 across all IPFs 

($6,242.25/facility * 1,634 facilities). 

We have previously estimated that the 

FUH (NQF #0576) measure does not 

have any reporting burden because it is 

calculated from Medicare FFS claims. 

Therefore, we do not anticipate a 

reduction in facility burden associated 

with the removal of this measure. Table 

15 describes our estimated reduction in 

burden associated with removing these 

two measures. 


lotter on DSK11XQN23PROD with RULES5ER04AU21.186</GPH>

TABLE 15: Burden Updates Due to Final Measure Removals 

0576 FUH Follow-Up 0 0 0 1,634 0 0 

After 

Hospitalization 

for Mental 

Illness* 

0648 NIA Timely (609) 0.25 152.25 1,634 (248,776.5) (10,199,836.5050) 

Transmission 

of Transition 

Record 

(Discharges 

from an 

Inpatient 

Facility to 

Home/Self 

Care or Any 

Other Site of 

* CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not require 

facilities to submit data on any cases. 

** We note that the previously approved number ofIPFs is 1,679; however we adjusted that in Table 12 based on 

updated data. 

***At $41.00/hr 
42670 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

(3) Updates Due to Final Administrative 

Policies 

(a) Updates Associated With Final 

Updated Reference to QualityNet 

System Administrator 

In section IV.J.1.a of this preamble, we 

are finalizing our proposal to use the 

term ‘‘QualityNet security official’’ 

instead of ‘‘QualityNet system 

administrator.’’ Because this final 

update will not change the individual’s 

responsibilities, we do not believe there 

would be any changes to the 

information collection burden as a 

result of this update. We also do not 

believe that removing the requirement 

for facilities to have an active 

QualityNet security official account to 

qualify for payment updates will affect 

burden because we continue to 

recommend that facilities maintain an 

active QualityNet security official 

account. 

(b) Updates Associated With Adoption 

of Patient-Level Reporting for Certain 

Chart Abstracted Measures 

In section IV.J.2.c of this preamble, we 

are adopting patient-level data 

submission for the 11 chart-abstracted 

measures currently in the IPFQR 

Program measure set (for more details 

on these measures we refer readers to 

Table 7). Because submission of 

aggregate data requires facilities to 

abstract patient-level data, then 

calculate measure performance prior to 

submitting data through the QualityNet 

website’s secure portal, facilities must 

already abstract patient-level data. 

Therefore, we do not believe that 

submitting data that facilities must 

already calculate through a tool that 

facilities already have experience using 

will change provider burden. 

d. Overall Burden Summary 

Table 16 summarizes the estimated 

burden associated with the IPFQR 

Program. 

BILLING CODE 4120–01–P 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42671 


lotter on DSK11XQN23PROD with RULES5ER04AU21.187</GPH>

TABLE 16: Total Estimated IPFQR Program Measure Set Burden Estimates 

Hours of Physical Restraint Use (See 

Table 12 

Hours of Seclusion Use See Table 12 

Patients Discharged on Multiple 

Antipsychotic Medications with 

A ro riate Justification See Table 12 

Alcohol Use Brieflntervention 

Provided or Offered (SUB-2 and SUB2a See Table 12 

Alcohol and Other Drug Use Disorder 

Treatment Provided or Offered at 

Discharge and Alcohol and Other Drug 

Use Disorder Treatment at Discharge 

SUB-3 and SUB-3a See Table 12 

Tobacco Use Treatment Provided or 

Offered and Tobacco Use Treatment 

TOB-2 and TOB-2a See Table 12 

Tobacco Use Treatment Provided or 

Offered at Discharge and Tobacco Use 

Treatment at Discharge (TOB-3 and 

TOB-3a See Table 12 

Influenza Immunization See Table 12 

Transition Record with Specified 

Elements Received by Discharged 

Patients (Discharges from an Inpatient 

Facility to Home/Self Care or Any 

Other Site of Care See Table 12 

Screening for Metabolic Disorders (See 

Table 12 

Thirty-day all-cause unplanned 

readmission following psychiatric 

hos italization in an IPF See Table 12 

Medication Continuation Following 

Inpatient Psychiatric Discharge (See 

Table 12 

COVID-19 Vaccination Rate Among 

Healthcare Personnel See Table 12 

Follow-Up After Psychiatric 

Hos italization See Table 12 

SUBTOTAL 

Non-Measure Data Collection and 

Reporting (See Table 13) 

1,346 

1,346 

609* 

609* 

609* 

609* 

609* 

609* 

609* 

609* 

0** 

0** 

0*** 

0** 

7,564 

4 

0.25 336.50 2,199,364 549,841 

0.25 336.50 2,199,364 549,841 

0.25 152.25 995,106 248,776.5 

0.25 152.25 995,106 248,776.5 

0.25 152.25 995,106 248,776.5 

0.25 152.25 995,106 248,776.5 

0.25 152.25 995,106 248,776.5 

0.25 152.25 995,106 248,776.5 

0.25 152.25 995,106 248,776.5 

0.25 152.25 995,106 248,776.5 

0 0 0 0 

0 0 0 0 

0 0 0 0 

0 0 0 0 

NIA 1,891 12,359,576 3,089,894 

0.5 2.0 6,536 3,268 

22,543,481 

22,543,481 

10,199,836.50 

10,199,836.50 

10,199,836.50 

10,199,836.50 

10,199,836.50 

10,199,836.50 

10,199,836.50 

10,199,836.50 

0 

0 

0 

0 

126,685,654 

133,988 

* Under our previously finalized "global sample" (80 FR 46717 through 46718) we allow facilities to apply the 

same sampling methodology to all measures eligible for sampling. In the FY 2016 IPF PPS final rule (80 FR 

46718), we finalized that facilities with between 609 and 3,056 cases that choose to participate in the global sample 

would be required to report data for 609 cases. Because facilities are only required to submit data on a number 

specified by the global sampling methodology, rather than abstracting data for all patients or applying measure 

specific sampling methodologies, we believe that the number of cases under the global sample is a good 

approximation of facility burden associated with these measures. Therefore, for the average IPF discharge rate of 

1,346 discharges versus the previously estimated 1,283, the global sample continues to require abstraction of 609 

records. 

** CMS will collect these data using Medicare Part A and Part B claims; therefore, these measures will not require 

facilities to submit data on any cases. 

••• The COVID-19 HCP measure will be calculated usiug data submitted to the CDC under a separate 0MB Control Number (0920-1317). 
42672 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

The total change in burden associated 

with this final rule (including all 

updates to wage rate, case counts, 

facility numbers, and the measures and 

administrative policies) is a reduction of 

287,924 hours and $512,065 from our 

currently approved burden of 3,381,086 

hours and $127,331,707. We refer 

readers to Table 17 for details. 

BILLING CODE 4120–01–C 

VI. Regulatory Impact Analysis 

A. Statement of Need 

This rule finalizes updates to the 

prospective payment rates for Medicare 

inpatient hospital services provided by 

IPFs for discharges occurring during FY 

2022 (October 1, 2021 through 

September 30, 2022). We are finalizing 

our proposal to apply the 2016-based 

IPF market basket increase of 2.7 

percent, less the productivity 

adjustment of 0.7 percentage point as 

required by 1886(s)(2)(A)(i) of the Act 

for a final total FY 2022 payment rate 

update of 2.0 percent. In this final rule, 

we are finalizing our proposal to update 

the IPF labor-related share and update 

the IPF wage index to reflect the FY 

2022 hospital inpatient wage index. 

B. Overall Impact 

We have examined the impacts of this 

final rule as required by Executive 

Order 12866 on Regulatory Planning 

and Review (September 30, 1993), 

Executive Order 13563 on Improving 

Regulation and Regulatory Review 

(January 18, 2011), the Regulatory 

Flexibility Act (RFA) (September 19, 

1980, Pub. L. 96 354), section 1102(b) of 

the Social Security Act (the 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). 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 $100 million 

or more in any 1 year, or adversely and 

materially affecting a sector of the 

economy, productivity, competition, 

jobs, the environment, public health or 

safety, or state, local or tribal 

governments or communities (also 

referred to as ‘‘economically 

significant’’); (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) raising novel legal or 

policy issues arising out of legal 

mandates, the President’s priorities, or 

the principles set forth in the Executive 

Order. 

A regulatory impact analysis (RIA) 

must be prepared for major rules with 

significant regulatory action/s or with 

economically significant effects ($100 

million or more in any 1 year). 

We estimate that the total impact of 

these changes for FY 2022 payments 

compared to FY 2021 payments will be 

a net increase of approximately $80 

million. This reflects an $75 million 

increase from the update to the payment 

rates (+$100 million from the 2nd 

quarter 2021 IGI forecast of the 2016- 

based IPF market basket of 2.7 percent, 

and -$25 million for the productivity 

adjustment of 0.7 percentage point), as 

well as a $5 million increase as a result 

of the update to the outlier threshold 

amount. Outlier payments are estimated 

to change from 1.9 percent in FY 2021 

to 2.0 percent of total estimated IPF 

payments in FY 2022. 

Based on our estimates, OMB’s Office 

of Information and Regulatory Affairs 

has determined that this rulemaking is 

‘‘economically significant,’’ and hence 

also a major rule under Subtitle E of the 

Small Business Regulatory Enforcement 

Fairness Act of 1996 (also known as the 

Congressional Review Act). 

C. Detailed Economic Analysis 

In this section, we discuss the 

historical background of the IPF PPS 

and the impact of this final rule on the 

Federal Medicare budget and on IPFs. 

1. Budgetary Impact 

As discussed in the November 2004 

and RY 2007 IPF PPS final rules, we 

applied a budget neutrality factor to the 

Federal per diem base rate and ECT 

payment per treatment to ensure that 

total estimated payments under the IPF 

PPS in the implementation period 

would equal the amount that would 

have been paid if the IPF PPS had not 

been implemented. The budget 

neutrality factor includes the following 

components: Outlier adjustment, stoploss adjustment, and the behavioral 

offset. As discussed in the RY 2009 IPF 

PPS notice (73 FR 25711), the stop-loss 

adjustment is no longer applicable 

under the IPF PPS. 

As discussed in section III.D.1 of this 

final rule, we are updating the wage 

index and labor-related share in a 

budget neutral manner by applying a 

wage index budget neutrality factor to 

the Federal per diem base rate and ECT 

payment per treatment. Therefore, the 

budgetary impact to the Medicare 

program of this final rule will be due to 

the market basket update for FY 2022 of 

2.7 percent (see section III.A.4 of this 

final rule) less the productivity 

adjustment of 0.7 percentage point 

required by section 1886(s)(2)(A)(i) of 

the Act and the update to the outlier 

fixed dollar loss threshold amount. 

We estimate that the FY 2022 impact 

will be a net increase of $80 million in 

payments to IPF providers. This reflects 

an estimated $75 million increase from 

the update to the payment rates and a 

$5 million increase due to the update to 

the outlier threshold amount to set total 


lotter on DSK11XQN23PROD with RULES5ER04AU21.188</GPH>

TABLE 17: Summary of Final Requirements and Annual Burden Estimates Under 

0MB Control Number 0938-1171 CMS-10432 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42673 

estimated outlier payments at 2.0 

percent of total estimated payments in 

FY 2022. This estimate does not include 

the implementation of the required 2.0 

percentage point reduction of the 

market basket update factor for any IPF 

that fails to meet the IPF quality 

reporting requirements (as discussed in 

section V.A. of this final rule). 

2. Impact on Providers 

To show the impact on providers of 

the changes to the IPF PPS discussed in 

this final rule, we compare estimated 

payments under the IPF PPS rates and 

factors for FY 2022 versus those under 

FY 2021. We determined the percent 

change in the estimated FY 2022 IPF 

PPS payments compared to the 

estimated FY 2021 IPF PPS payments 

for each category of IPFs. In addition, 

for each category of IPFs, we have 

included the estimated percent change 

in payments resulting from the update 

to the outlier fixed dollar loss threshold 

amount; the updated wage index data 

including the updated labor-related 

share; and the market basket update for 

FY 2022, as reduced by the productivity 

adjustment according to section 

1886(s)(2)(A)(i) of the Act. 

Our longstanding methodology uses 

the best available data as the basis for 

our estimates of payments. Typically, 

this is the most recent update of the 

latest available fiscal year of IPF PPS 

claims, and for this final rulemaking, 

that would be the FY 2020 claims. 

However, as discussed in section III.F.2 

of this final rule, the U.S. healthcare 

system undertook an unprecedented 

response to the COVID–19 PHE during 

FY 2020. Therefore, we considered 

whether the most recent available year 

of claims, FY 2020, or the prior year, FY 

2019, would be the best for estimating 

IPF PPS payments in FY 2021 and FY 

2022. 

As discussed in the FY 2022 IPF PPS 

proposed rule (86 FR 19524 through 

19526), we examined the differences 

between the FY 2019 and FY 2020 

claims distributions to better 

understand the disparity in the estimate 

of outlier payments as a percentage of 

total PPS payments between the two 

years, which was driving the divergent 

results in our proposed rule impacts 

between FY 2019 claims and FY 2020 

claims. Based on our analysis, we stated 

that we believe it is likely that the 

response to the COVID–19 PHE in FY 

2020 has contributed to increases in 

estimated outlier payments and to 

decreases in estimated total PPS 

payments in the FY 2020 claims. 

Therefore, we proposed, in contrast to 

our usual methodology, to use the FY 

2019 claims to calculate the outlier 

fixed dollar loss threshold and wage 

index budget neutrality factor. 

We requested comments from 

stakeholders about likely explanations 

for the declines in total PPS payments, 

covered IPF days, and covered IPF stays 

in FY 2020. Additionally, we requested 

comments from stakeholders about 

likely explanations for the observed 

fluctuations and overall increases in 

covered lab charges per claim and per 

day, which we identified through our 

analysis. Lastly, we requested comments 

regarding likely explanations for the 

increases in estimated cost per stay 

relative to estimated IPF Federal per 

diem payment amounts per stay. 

Comment: We received 1 comment 

regarding our analysis of FY 2020 

claims and 3 comments in support of 

our proposal to use FY 2019 claims for 

calculating the outlier fixed dollar loss 

threshold and wage index budget 

neutrality factor for FY 2022. One 

commenter appreciated CMS’ 

recognition of the impact of the COVID– 

19 PHE on providers. Another 

commenter agreed with our analysis 

about the effect of the COVID–19 PHE 

on the FY 2020 claims, stating their 

belief that FY 2020 cases were heavily 

impacted by the intensity of the COVID– 

19 pandemic, which continues to 

subside. 

Response: We appreciate the support 

from these commenters. As we discuss 

later in this section of this final rule, 

based on the results of our final impact 

analysis, we continue to believe that the 

FY 2019 claims are the best available 

data for estimating payments in this FY 

2022 final rulemaking, due to the likely 

impact of the COVID–19 PHE on IPF 

utilization in FY 2020. We will continue 

to analyze data in order to understand 

its short-term and long-term effects on 

IPF utilization. 

Final Decision: In light of the 

comments received and after analyzing 

more recently updated FY 2020 claims, 

we are finalizing our proposal to use the 

FY 2019 claims to calculate the outlier 

fixed dollar loss threshold and wage 

index budget neutrality factor. 

To illustrate the impacts of the FY 

2022 changes in this final rule, our 

analysis presents a side-by-side 

comparison of payments estimated 

using FY 2019 claims versus payments 

estimated using FY 2020 claims. We 

begin with FY 2019 IPF PPS claims 

(based on the 2019 MedPAR claims, 

June 2020 update) and FY 2020 IPF PPS 

claims (based on the 2020 MedPAR 

claims, March 2021 update). We 

estimate FY 2021 IPF PPS payments 

using these 2019 and 2020 claims, the 

finalized FY 2021 IPF PPS Federal per 

diem base rates, and the finalized FY 

2021 IPF PPS patient and facility level 

adjustment factors (as published in the 

FY 2021 IPF PPS final rule (85 FR 47042 

through 47070)). We then estimate the 

FY 2021 outlier payments based on 

these simulated FY 2021 IPF PPS 

payments using the same methodology 

as finalized in the FY 2021 IPF PPS final 

rule (85 FR 47061 through 47062) where 

total outlier payments are maintained at 

2 percent of total estimated FY 2021 IPF 

PPS payments. 

Each of the following changes is 

added incrementally to this baseline 

model in order for us to isolate the 

effects of each change: 

• The final update to the outlier fixed 

dollar loss threshold amount. 

• The final FY 2022 IPF wage index, 

the final FY 2022 labor-related share, 

and the final updated COLA factors. 

• The final market basket update for 

FY 2022 of 2.7 percent less the 

productivity adjustment of 0.7 

percentage point in accordance with 

section 1886(s)(2)(A)(i) of the Act for a 

payment rate update of 2.0 percent. 

Our final column comparison in Table 

18 illustrates the percent change in 

payments from FY 2021 (that is, October 

1, 2020, to September 30, 2021) to FY 

2022 (that is, October 1, 2021, to 

September 30, 2022) including all the 

payment policy changes in this final 

rule. For each column, Table 18 

presents a side-by-side comparison of 

the results using FY 2019 and FY 2020 

IPF PPS claims. 

BILLING CODE 4120–01–P 


lotter on DSK11XQN23PROD with RULES5
42674 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 


lotter on DSK11XQN23PROD with RULES5ER04AU21.189</GPH>

TABLE 18: FY 2022 IPF PPS Final Payment Impacts 

[Percent Change in columns 3 through 5] 

FY 2022 Wage 

Number of Index, LRS, and Total Percent 

Facility by Type Facilities Outlier COLA Chanae1 

FY 

FY 2019 FY2020 FY 2019 FY 2020 FY 2019 2020 FY 2019 FY2020 

Claims Claims Claims Claims Claims Claims Claims Claims 

(1) (21 (3) (4] (5) 

All Facilities 1,519 1,534 0.1 -1.1 0.0 0.0 2.1 0.9 

Total Urban 1,220 1,235 0.1 -1.1 0.0 0.0 2.1 0.8 

Urban unit 739 737 0.2 -1.8 -0.1 -0.1 2.2 0.1 

Urban hospital 481 498 0.0 -0.3 0.0 0.0 2.1 1.7 

Total Rural 299 299 0.1 -0.7 0.2 0.2 2.2 1.5 

Rural unit 239 238 0.1 -0.8 0.1 0.1 2.2 1.3 

Rural hospital 60 61 0.1 -0.4 0.4 0.4 2.4 2.0 

By Type of Ownership: 

FreestandinQ IPFs 

Urban Psvchiatric Hospitals 

Government 116 123 0.2 -1.7 -0.2 -0.2 2.0 0.1 

Non-Profit 95 97 0.1 -0.5 -0.2 -0.1 1.9 1.4 

For-Profit 270 278 0.0 -0.1 0.1 0.1 2.1 2.0 

Rural Psvchiatric Hospitals 

Government 31 32 0.1 -0.8 0.5 0.6 2.6 1.8 

Non-Profit 12 12 0.2 -1.2 -0.1 0.0 2.1 0.7 

For-Profit 17 17 0.0 0.0 0.4 0.4 2.4 2.4 

IPF Units 

Urban 

Government 108 107 0.3 -3.4 0.1 0.1 2.5 -1.4 

Non-Profit 479 478 0.2 -1.7 -0.1 -0.1 2.1 0.2 

For-Profit 152 152 0.1 -0.7 -0.1 -0.1 2.0 1.2 

Rural 

Government 58 57 0.1 -0.4 0.4 0.3 2.4 1.9 

Non-Profit 132 131 0.1 -1.0 0.1 0.1 2.2 1.0 

For-Profit 49 50 0.1 -0.6 -0.2 -0.2 1.9 1.2 

By Teaching Status: 

Non-teachinQ 1,321 1,336 0.1 -0.8 0.0 0.0 2.1 1.1 

Less than 10% interns and 

residents to beds 109 109 0.2 -1.9 0.1 0.1 2.3 0.2 

10% to 30% interns and residents to 

beds 67 67 0.3 -2.4 -0.1 -0.1 2.2 -0.5 

More than 30% interns and 

residents to beds 22 22 0.4 -3.2 -0.2 -0.1 2.2 -1.3 

By Region: 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42675 

BILLING CODE 4120–01–C 

3. Impact Results 

Table 18 displays the results of our 

analysis. The table groups IPFs into the 

categories listed here based on 

characteristics provided in the Provider 

of Services file, the IPF PSF, and cost 

report data from the Healthcare Cost 

Report Information System: 

• Facility Type. 

• Location. 

• Teaching Status Adjustment. 

• Census Region. 

• Size. 

The top row of the table shows the 

overall impact on the 1,519 IPFs 

included in the analysis for FY 2019 

claims or the 1,534 IPFs included in the 

analysis for FY 2020 claims. In column 

2, we present the number of facilities of 

each type that had information available 

in the PSF and also had claims in the 

MedPAR dataset for FY 2019 or FY 

2020. The number of providers in each 

category therefore differs slightly 

between the two years. 

In column 3, we present the effects of 

the update to the outlier fixed dollar 

loss threshold amount. Based on the FY 

2019 claims, we would estimate that IPF 

outlier payments as a percentage of total 

IPF payments are 1.9 percent in FY 

2021. Alternatively, based on the FY 

2020 claims, we would estimate that IPF 

outlier payments as a percentage of total 

IPF payments are 3.1 percent in FY 

2021. 

Thus, we are finalizing our proposal 

to adjust the outlier threshold amount in 

this final rule to set total estimated 

outlier payments equal to 2.0 percent of 

total payments in FY 2022. Based on the 

FY 2019 claims, the estimated change in 

total IPF payments for FY 2022 would 

include an approximate 0.1 percent 

increase in payments because we would 

expect the outlier portion of total 

payments to increase from 

approximately 1.9 percent to 2.0 

percent. Alternatively, based on the FY 

2020 claims, the estimated change in 

total IPF payments for FY 2022 would 

include an approximate 1.1 percent 

decrease in payments because we would 

expect the outlier portion of total 

payments to decrease from 

approximately 3.1 percent to 2.0 

percent. 

The overall impact of the estimated 

increase or decrease to payments due to 

updating the outlier fixed dollar loss 

threshold (as shown in column 3 of 

Table 18), across all hospital groups, is 

0.1 percent based on the FY 2019 

claims, or –1.1 percent based on the FY 

2020 claims. Based on the FY 2019 

claims, the largest increase in payments 

due to this change is estimated to be 0.4 

percent for teaching IPFs with more 

than 30 percent interns and residents to 

beds. Among teaching IPFs, this same 

provider facility type would experience 

the largest estimated decrease in 

payments if we were to instead increase 

the outlier fixed dollar loss threshold 

based on the FY 2020 claims 

distribution. 

In column 4, we present the effects of 

the budget-neutral update to the IPF 

wage index, the Labor-Related Share 

(LRS), and the final updated COLA 

factors discussed in section III.D.3. This 

represents the effect of using the 

concurrent hospital wage data as 

discussed in section III.D.1.a of this 

final rule. That is, the impact 

represented in this column reflects the 

final updated COLA factors and the 

update from the FY 2021 IPF wage 

index to the final FY 2022 IPF wage 

index, which includes basing the FY 

2022 IPF wage index on the FY 2022 

pre-floor, pre-reclassified IPPS hospital 

wage index data and updating the LRS 

from 77.3 percent in FY 2021 to 77.2 

percent in FY 2022. We note that there 

is no projected change in aggregate 

payments to IPFs, as indicated in the 

first row of column 4; however, there 

will be distributional effects among 

different categories of IPFs. We also note 

that when comparing the results using 


lotter on DSK11XQN23PROD with RULES5ER04AU21.190</GPH>

New Enciland 106 106 0.2 -1.2 -0.4 -0.4 1.8 0.3 

Mid-Atlantic 214 216 0.2 -2.0 -0.2 -0.2 2.0 -0.2 

South Atlantic 240 243 0.1 -0.7 0.6 0.6 2.7 1.9 

East North Central 243 244 0.1 -0.7 -0.2 -0.2 1.9 1.0 

East South Central 152 155 0.1 -0.7 -0.5 -0.5 1.6 0.7 

West North Central 108 109 0.2 -1.4 0.1 0.1 2.3 0.7 

West South Central 224 227 0.1 -0.5 -0.2 -0.3 1.8 1.3 

Mountain 103 103 0.1 -0.7 0.3 0.3 2.4 1.6 

Pacific 129 131 0.2 -1.4 0.4 0.4 2.6 1.0 

By Bed Size: 

Psychiatric Hospitals 

Beds: 0-24 83 88 0.1 -0.5 0.1 0.0 2.1 1.5 

Beds: 25-49 79 83 0.1 -0.2 -0.3 -0.3 1.8 1.5 

Beds: 50-75 84 88 0.0 -0.1 0.1 0.2 2.1 2.2 

Beds: 76 + 295 300 0.1 -0.4 0.1 0.1 2.2 1.7 

Psychiatric Units 

Beds: 0-24 536 531 0.2 -1.2 0.0 0.0 2.2 0.7 

Beds: 25-49 258 259 0.2 -1.3 0.0 0.0 2.2 0.7 

Beds: 50-75 114 114 0.2 -2.0 -0.3 -0.3 2.0 -0.3 

Beds: 76 + 70 71 0.3 -2.5 0.0 0.0 2.3 -0.5 

1 This column includes the impact of the updates in columns (3) and (4) in Table 18 above, and of the final IPF market basket 

increase factor for FY 2022 (2.7 percent), reduced by 0.7 percentage point for the productivity adjustment as required by section 

1886(s)(2)(A)(i) of the Act. Note, the products of these impacts may be different from the percentage changes shown here due to 

rounding effects. 
42676 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

FY 2019 and FY 2020 claims, the 

distributional effects are very similar. 

For example, we estimate the largest 

increase in payments to be 0.6 percent 

for IPFs in the South Atlantic region, 

and the largest decrease in payments to 

be –0.5 percent for IPFs in the East 

South Central region, based on either 

the FY 2019 or FY 2020 claims. 

Finally, column 5 compares the total 

final changes reflected in this final rule 

for FY 2022 to the estimates for FY 2021 

(without these changes). The average 

estimated increase for all IPFs is 

approximately 2.1 percent based on the 

FY 2019 claims, or 0.9 percent based on 

the FY 2020 claims. These estimated net 

increases include the effects of the 2016- 

based market basket update of 2.7 

percent reduced by the productivity 

adjustment of 0.7 percentage point, as 

required by section 1886(s)(2)(A)(i) of 

the Act. They also include the overall 

estimated 0.1 percent increase in 

estimated IPF outlier payments as a 

percent of total payments from updating 

the outlier fixed dollar loss threshold 

amount. In addition, column 5 includes 

the distributional effects of the final 

updates to the IPF wage index, the 

labor-related share, and the final 

updated COLA factors, whose impacts 

are displayed in column 4. Based on the 

FY 2020 claims distribution, the 

increase to estimated payments due to 

the market basket update factor are 

offset in large part for some provider 

types by the increase to the outlier fixed 

dollar loss threshold. 

In summary, comparing the impact 

results for the FY 2019 and FY 2020 

claims, the largest difference in the 

results continues to be due to the update 

to the outlier fixed dollar loss threshold, 

which is the same result we observed in 

the FY 2022 IPF PPS proposed rule (86 

FR 19524). Estimated outlier payments 

increased and estimated total PPS 

payments decreased, when comparing 

FY 2020 to FY 2019. As a result, we 

continue to believe that FY 2019 claims, 

rather than FY 2020 claims, are the best 

available data for setting the FY 2022 

final outlier fixed dollar loss threshold. 

Furthermore, the distributional effects 

of the updates presented in column 4 of 

Table 18 (the budget-neutral update to 

the IPF wage index, the LRS, and the 

final updated COLA factors) are very 

similar when using the FY 2019 or FY 

2020 claims data. Therefore, we believe 

the FY 2019 claims are the best 

available data for estimating payments 

in this FY 2022 final rulemaking, and 

we are finalizing our proposal to use the 

FY 2019 claims to calculate the outlier 

fixed dollar loss threshold and wage 

index budget neutrality factor. 

IPF payments are therefore estimated 

to increase by 2.1 percent in urban areas 

and 2.2 percent in rural areas based on 

this finalized policy. Overall, IPFs are 

estimated to experience a net increase in 

payments as a result of the updates in 

this final rule. The largest payment 

increase is estimated at 2.7 percent for 

IPFs in the South Atlantic region. 

4. Effect on Beneficiaries 

Under the FY 2022 IPF PPS, IPFs will 

continue to receive payment based on 

the average resources consumed by 

patients for each day. Our longstanding 

payment methodology reflects the 

differences in patient resource use and 

costs among IPFs, as required under 

section 124 of the BBRA. We expect that 

updating IPF PPS rates as finalized in 

this rule will improve or maintain 

beneficiary access to high quality care 

by ensuring that payment rates reflect 

the best available data on the resources 

involved in inpatient psychiatric care 

and the costs of these resources. We 

continue to expect that paying 

prospectively for IPF services under the 

FY 2022 IPF PPS will enhance the 

efficiency of the Medicare program. 

As discussed in sections IV.E.2, 

IV.E.3, and V.A.2.d of this final rule, we 

expect that additional program 

measures will improve follow-up for 

patients with both mental health and 

substance use disorders and ensure 

health-care personnel COVID–19 

vaccinations. We also estimate an 

annualized estimate of $512,065 

reduction in information collection 

burden as a result our measure 

removals. Therefore, we expect that the 

final updates to the IPFQR program will 

improve quality for beneficiaries. 

5. Effects of Updates to the IPFQR 

Program 

As discussed in section V. of this final 

rule and in accordance with section 

1886(s)(4)(A)(i) of the Act, we will apply 

a 2 percentage point reduction to the FY 

2022 market basket update for IPFs that 

have failed to comply with the IPFQR 

Program requirements for FY 2022, 

including reporting on the required 

measures. In section V. of this final rule, 

we discuss how the 2 percentage point 

reduction will be applied. For FY 2021, 

of the 1,634 IPFs eligible for the IPFQR 

Program, 43 IPFs (2.6 percent) did not 

receive the full market basket update 

because of the IPFQR Program; 31 of 

these IPFs chose not to participate and 

12 did not meet the requirements of the 

program. We anticipate that even fewer 

IPFs would receive the reduction for FY 

2022 as IPFs become more familiar with 

the requirements. Thus, we estimate 

that the IPFQR Program will have a 

negligible impact on overall IPF 

payments for FY 2022. 

Based on the IPFQR Program policies 

finalized in this final rule, we estimate 

a total decrease in burden of 287,924 

hours across all IPFs, resulting in a total 

decrease in information collection 

burden of $512,065 across all IPFs. As 

discussed in section VI. of this final 

rule, we will attribute the cost savings 

associated with the proposals to the year 

in which these savings begin; for the 

purposes of all the policies in this final 

rule, that year is FY 2023. Further 

information on these estimates can be 

found in section VI. of this final rule. 

We intend to closely monitor the 

effects of the IPFQR Program on IPFs 

and help facilitate successful reporting 

outcomes through ongoing stakeholder 

education, national trainings, and a 

technical help desk. 

6. Regulatory Review Costs 

If regulations impose administrative 

costs on private entities, such as the 

time needed to read and interpret this 

final rule, we should estimate the cost 

associated with regulatory review. Due 

to the uncertainty involved with 

accurately quantifying the number of 

entities that will be directly impacted 

and will review this final rule, we 

assume that the total number of unique 

commenters on the most recent IPF 

proposed rule will be the number of 

reviewers of this final rule. For this FY 

2022 IPF PPS final rule, the most recent 

IPF proposed rule was the FY 2022 IPF 

PPS proposed rule, and we received 898 

unique comments on this proposed rule. 

We acknowledge that this assumption 

may understate or overstate the costs of 

reviewing this final rule. It is possible 

that not all commenters reviewed the 

FY 2021 IPF proposed rule in detail, 

and it is also possible that some 

reviewers chose not to comment on that 

proposed rule. For these reasons, we 

thought that the number of commenters 

would be a fair estimate of the number 

of reviewers who are directly impacted 

by this final rule. We solicited 

comments on this assumption. 

We also recognize that different types 

of entities are in many cases affected by 

mutually exclusive sections of this final 

rule; therefore, for the purposes of our 

estimate, we assume that each reviewer 

reads approximately 50 percent of this 

final rule. 

Using the May, 2020 mean (average) 

wage information from the BLS for 

medical and health service managers 

(Code 11–9111), we estimate that the 

cost of reviewing this final rule is 

$114.24 per hour, including overhead 

and fringe benefits (https://www.bls.gov/ 

oes/current/oes119111.htm). Assuming 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42677 

an average reading speed of 250 words 

per minute, we estimate that it would 

take approximately 128 minutes (2.13 

hours) for the staff to review half of this 

final rule, which is approximately 

32,000 words. For each IPF that reviews 

the final rule, the estimated cost is (2.13 

× $114.24) or $243.33. Therefore, we 

estimate that the total cost of reviewing 

this final rule is $ 218,510.34 ($243.33 

× 898 reviewers). 

D. Alternatives Considered 

The statute does not specify an update 

strategy for the IPF PPS and is broadly 

written to give the Secretary discretion 

in establishing an update methodology. 

We continue to believe it is appropriate 

to routinely update the IPF PPS so that 

it reflects the best available data about 

differences in patient resource use and 

costs among IPFs as required by the 

statute. Therefore, we are finalizing our 

proposal to update the IPF PPS using 

the methodology published in the 

November 2004 IPF PPS final rule; 

applying the 2016-based IPF PPS market 

basket update for FY 2022 of 2.7 

percent, reduced by the statutorily 

required productivity adjustment of 0.7 

percentage point along with the wage 

index budget neutrality adjustment to 

update the payment rates; and finalizing 

a FY 2022 IPF wage index which uses 

the FY 2022 pre-floor, pre-reclassified 

IPPS hospital wage index as its basis. 

As discussed in section VI.C.3 of this 

final rule, we also considered using FY 

2020 claims data to determine the final 

FY 2022 outlier fixed dollar loss 

threshold, wage index budget neutrality 

factor, per diem base rate, and ECT rate. 

For the reasons discussed in that 

section, we are finalizing our proposal 

to use FY 2019 claims data. 

E. Accounting Statement 

As required by OMB Circular A–4 

(available at www.whitehouse.gov/sites/ 

whitehouse.gov/files/omb/circulars/A4/ 

a-4.pdf), in Table 19, we have prepared 

an accounting statement showing the 

classification of the expenditures 

associated with the updates to the IPF 

wage index and payment rates in this 

final rule. Table 19 provides our best 

estimate of the increase in Medicare 

payments under the IPF PPS as a result 

of the changes presented in this final 

rule and based on the data for 1,519 

IPFs with data available in the PSF and 

with claims in our FY 2019 MedPAR 

claims dataset. Table 19 also includes 

our best estimate of the cost savings for 

the 1,634 IPFs eligible for the IPFQR 

Program. Lastly, Table 19 also includes 

our best estimate of the costs of 

reviewing and understanding this final 

rule. 

F. Regulatory Flexibility Act 

The RFA requires agencies to analyze 

options for regulatory relief of small 

entities if a rule has a significant impact 

on a substantial number of small 

entities. For purposes of the RFA, small 

entities include small businesses, 

nonprofit organizations, and small 

governmental jurisdictions. Most IPFs 

and most other providers and suppliers 

are small entities, either by nonprofit 

status or having revenues of $8 million 

to $41.5 million or less in any 1 year. 

Individuals and states are not included 

in the definition of a small entity. 

Because we lack data on individual 

hospital receipts, we cannot determine 

the number of small proprietary IPFs or 

the proportion of IPFs’ revenue derived 

from Medicare payments. Therefore, we 

assume that all IPFs are considered 

small entities. 

The Department of Health and Human 

Services generally uses a revenue 

impact of 3 to 5 percent as a significance 

threshold under the RFA. As shown in 

Table 18, we estimate that the overall 

revenue impact of this final rule on all 

IPFs is to increase estimated Medicare 

payments by approximately 2.1 percent. 

As a result, since the estimated impact 

of this final rule is a net increase in 

revenue across almost all categories of 

IPFs, the Secretary has determined that 

this final rule will have a positive 

revenue impact on a substantial number 

of small entities. 

In addition, section 1102(b) of the Act 

requires us to prepare a regulatory 

impact analysis 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 604 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. As discussed in 

section V.C.1 of this final rule, the rates 

and policies set forth in this final rule 

will not have an adverse impact on the 

rural hospitals based on the data of the 

239 rural excluded psychiatric units and 

60 rural psychiatric hospitals in our 

database of 1,519 IPFs for which data 

were available. 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. 

G. Unfunded Mandate 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 


lotter on DSK11XQN23PROD with RULES5ER04AU21.191</GPH>

TABLE 19: Accounting Statement: Classification of Estimated Costs, Savings, and 

Transfers 

Category Primary Low High 

Units 

estimate estimate estimate Year Discount ($million/ 

vear) 

dollars rate 

0.2 - - 2020 - Regulatory Review Costs 

-0.51 -0.38 -0.64 2019 7% 

Annualized Monetized Costs Savings 

2019 3% 

-0.44 -0.33 -0.54 

Annualized Monetized Transfers from Federal Government to TPF 80 - - FY2022 -

Medicare Providers 

Period 

covered 

FY2022 

FY 2023-

FY 2031 

FY2023-

FY 2031 

FY2022 
42678 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

million in 1995 dollars, updated 

annually for inflation. In 2021, that 

threshold is approximately $158 

million. This final rule does not 

mandate any requirements for state, 

local, or tribal governments, or for the 

private sector. This final rule would not 

impose a mandate that will result in the 

expenditure by state, local, and Tribal 

Governments, in the aggregate, or by the 

private sector, of more than $158 

million in any one year. 

H. Federalism 

Executive Order 13132 establishes 

certain requirements that an agency 

must meet when it promulgates a 

proposed rule that imposes substantial 

direct requirement costs on state and 

local governments, preempts state law, 

or otherwise has Federalism 

implications. This final rule does not 

impose substantial direct costs on state 

or local governments or preempt state 

law. 

I, Chiquita Brooks-LaSure, 

Administrator of the Centers for 

Medicare & Medicaid Services, 

approved this document on July 23, 

2021. 

List of Subjects in 42 CFR Part 412 

Administrative practice and 

procedure, Health facilities, Medicare, 

Puerto Rico, Reporting and 

recordkeeping requirements. 

For the reasons set forth in the 

preamble, the Centers for Medicare & 

Medicaid Services is amending 42 CFR 

chapter IV as set forth below: 

PART 412—PROSPECTIVE PAYMENT 

SYSTEMS FOR INPATIENT HOSPITAL 

SERVICES 

■ 1. The authority citation for part 412 

continues to read as follows: 

Authority: 42 U.S.C. 1302 and 1395hh. 

■ 2. Section 412.402 is amended by 

adding definitions for ‘‘Closure of an 

IPF’’, ‘‘Closure of an IPF’s residency 

training program’’, and ‘‘Displaced 

resident’’ in alphabetical order to read 

as follows: 

§ 412.402 Definitions. 

* * * * * 

Closure of an IPF means closure of a 

hospital as defined in § 413.79(h)(1)(i) 

by an IPF meeting the requirements of 

§ 412.404(b) for the purposes of 

accounting for indirect teaching costs. 

Closure of an IPF’s residency training 

program means closure of a hospital 

residency training program as defined in 

§ 413.79(h)(1)(ii) by an IPF meeting the 

requirements of § 412.404(b) for the 

purposes of accounting for indirect 

teaching costs. 

* * * * * 

Displaced resident means a displaced 

resident as defined in § 413.79(h)(1)(iii) 

for the purposes of accounting for 

indirect teaching costs. 

* * * * * 

■ 3. Section 412.424 is amended by 

revising paragraph (d)(1)(iii)(F) to read 

as follows: 

§ 412.424 Methodology for calculating the 

Federal per diem payment system. 

* * * * * 

(d) * * * 

(1) * * * 

(iii) * * * 

(F) Closure of an IPF or IPF residency 

training program—(1) Closure of an IPF. 

For cost reporting periods beginning on 

or after July 1, 2011, an IPF may receive 

a temporary adjustment to its FTE cap 

to reflect displaced residents added 

because of another IPF’s closure if the 

IPF meets the following criteria: 

(i) The IPF is training additional 

displaced residents from an IPF that 

closed on or after July 1, 2011. 

(ii) No later than 60 days after the IPF 

begins to train the displaced residents, 

the IPF submits a request to its Medicare 

contractor for a temporary adjustment to 

its cap, documents that the IPF is 

eligible for this temporary adjustment 

by identifying the displaced residents 

who have come from the closed IPF and 

have caused the IPF to exceed its cap, 

and specifies the length of time the 

adjustment is needed. 

(2) Closure of an IPF’s residency 

training program. If an IPF that closes 

its residency training program on or 

after July 1, 2011, agrees to temporarily 

reduce its FTE cap according to the 

criteria specified in paragraph 

(d)(1)(iii)(F)(2)(ii) of this section, 

another IPF(s) may receive a temporary 

adjustment to its FTE cap to reflect 

displaced residents added because of 

the closure of the residency training 

program if the criteria specified in 

paragraph (d)(1)(iii)(F)(2)(i) of this 

section are met. 

(i) Receiving IPF(s). For cost reporting 

periods beginning on or after July 1, 

2011, an IPF may receive a temporary 

adjustment to its FTE cap to reflect 

displaced residents added because of 

the closure of another IPF’s residency 

training program if the IPF is training 

additional displaced residents from the 

residency training program of an IPF 

that closed a program; and if no later 

than 60 days after the IPF begins to train 

the displaced residents, the IPF submits 

to its Medicare Contractor a request for 

a temporary adjustment to its FTE cap, 

documents that it is eligible for this 

temporary adjustment by identifying the 

displaced residents who have come 

from another IPF’s closed program and 

have caused the IPF to exceed its cap, 

specifies the length of time the 

adjustment is needed, and submits to its 

Medicare contractor a copy of the FTE 

reduction statement by the hospital that 

closed its program, as specified in 

paragraph (d)(1)(iii)(F)(2)(ii) of this 

section. 

(ii) IPF that closed its program. An 

IPF that agrees to train displaced 

residents who have been displaced by 

the closure of another IPF’s program 

may receive a temporary FTE cap 

adjustment only if the hospital with the 

closed program temporarily reduces its 

FTE cap based on the FTE of displaced 

residents in each program year training 

in the program at the time of the 

program’s closure. This yearly reduction 

in the FTE cap will be determined based 

on the number of those displaced 

residents who would have been training 

in the program during that year had the 

program not closed. No later than 60 

days after the displaced residents who 

were in the closed program begin 

training at another hospital, the hospital 

with the closed program must submit to 

its Medicare contractor a statement 

signed and dated by its representative 

that specifies that it agrees to the 

temporary reduction in its FTE cap to 

allow the IPF training the displaced 

residents to obtain a temporary 

adjustment to its cap; identifies the 

displaced residents who were in 

training at the time of the program’s 

closure; identifies the IPFs to which the 

displaced residents are transferring once 

the program closes; and specifies the 

reduction for the applicable program 

years. 

* * * * * 

■ 4. Section 412.434 is amended by 

revising paragraph (b)(3) to read as 

follows: 

§ 412.434 Reconsideration and appeals 

procedures of Inpatient Psychiatric 

Facilities Quality Reporting (IPFQR) 

Program decisions 

* * * * * 

(b) * * * 

(3) Contact information for the 

inpatient psychiatric facility’s chief 

executive officer and QualityNet 

security official, including each 

individual’s name, email address, 

telephone number, and physical mailing 

address; 

* * * * * 


lotter on DSK11XQN23PROD with RULES5
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42679 

Dated: July 27, 2021. 

Xavier Becerra, 

Secretary, Department of Health and Human 

Services. 

[FR Doc. 2021–16336 Filed 7–29–21; 4:15 pm] 

BILLING CODE 4120–01–P 


lotter on DSK11XQN23PROD with RULES5