42424 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 Parts 411, 413, 483 and 489 

[CMS–1746–F] 

RIN 0938–AU36 

Medicare Program; Prospective 

Payment System and Consolidated 

Billing for Skilled Nursing Facilities; 

Updates to the Quality Reporting 

Program and Value-Based Purchasing 

Program for Federal Fiscal Year 2022; 

and Technical Correction to LongTerm Care Facilities Physical 

Environment Requirements 

AGENCY: Centers for Medicare & 

Medicaid Services (CMS), HHS. 

ACTION: Final rule. 

SUMMARY: This final rule updates the 

payment rates used under the 

prospective payment system (PPS) for 

skilled nursing facilities (SNFs) for 

fiscal year (FY) 2022. In addition, the 

final rule includes a forecast error 

adjustment for FY 2022, updates the 

diagnosis code mappings used under 

the Patient Driven Payment Model 

(PDPM), rebases and revises the SNF 

market basket, implements a recentlyenacted SNF consolidated billing 

exclusion along with the required 

proportional reduction in the SNF PPS 

base rates, and includes a discussion of 

a PDPM parity adjustment. In addition, 

the final rule includes updates for the 

SNF Quality Reporting Program (QRP) 

and the SNF Value-Based Purchasing 

(VBP) Program, including a policy to 

suppress the use of the SNF readmission 

measure for scoring and payment 

adjustment purposes in the FY 2022 

SNF VBP Program because we have 

determined that circumstances caused 

by the public health emergency for 

COVID–19 have significantly affected 

the validity and reliability of the 

measure and resulting performance 

scores. We are also finalizing a technical 

correction to the physical environment 

requirements that Long-Term Care 

facilities must meet in order to 

participate in the Medicare and 

Medicaid programs. 

DATES: These regulations are effective 

on October 1, 2021. 

FOR FURTHER INFORMATION CONTACT: 

Penny Gershman, (410) 786–6643, for 

information related to SNF PPS clinical 

issues. 

Anthony Hodge, (410) 786–6645, for 

information related to consolidated 

billing, and payment for SNF-level 

swing-bed services. 

John Kane, (410) 786–0557, for 

information related to the development 

of the payment rates and case-mix 

indexes, and general information. 

Kia Burwell, (410) 786–7816, for 

information related to the wage index. 

Heidi Magladry, (410) 786–6034, for 

information related to the skilled 

nursing facility quality reporting 

program. 

Lang Le, (410) 786–5693, for 

information related to the skilled 

nursing facility value-based purchasing 

program. 

Kristin Shifflett, (410) 786–4133, for 

information related to the long-term care 

conditions of participation. 

SUPPLEMENTARY INFORMATION: 

Availability of Certain Tables 

Exclusively Through the Internet on the 

CMS Website 

As discussed in the FY 2014 SNF PPS 

final rule (78 FR 47936), tables setting 

forth the Wage Index for Urban Areas 

Based on CBSA Labor Market Areas and 

the Wage Index Based on CBSA Labor 

Market Areas for Rural Areas are no 

longer published in the FEDERAL

REGISTER. Instead, these tables are 

available exclusively through the 

internet on the CMS website. The wage 

index tables for this final rule can be 

accessed on the SNF PPS Wage Index 

home page, at http://www.cms.gov/ 

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

Readers who experience any problems 

accessing any of these online SNF PPS 

wage index tables should contact Kia 

Burwell at (410) 786–7816. 

To assist readers in referencing 

sections contained in this document, we 

are providing the following Table of 

Contents. 

Table of Contents 

I. Executive Summary 

A. Purpose 

B. Summary of Major Provisions 

C. Summary of Cost and Benefits 

D. Advancing Health Information Exchange 

II. Background on SNF PPS 

A. Statutory Basis and Scope 

B. Initial Transition for the SNF PPS 

C. Required Annual Rate Updates 

III. Analysis and Responses to Public 

Comments on the FY 2022 SNF PPS 

Proposed Rule 

A. General Comments on the FY 2022 SNF 

PPS Proposed Rule 

IV. SNF PPS Rate Setting Methodology and 

FY 2022 Update 

A. Federal Base Rates 

B. SNF Market Basket Update 

C. Case-Mix Adjustment 

D. Wage Index Adjustment 

E. SNF Value-Based Purchasing Program 

F. Adjusted Rate Computation Example 

V. Additional Aspects of the SNF PPS 

A. SNF Level of Care—Administrative 

Presumption 

B. Consolidated Billing 

C. Payment for SNF-Level Swing-Bed 

Services 

D. Revisions to the Regulation Text 

VI. Other SNF PPS Issues 

A. Changes to SNF PPS Wage Index 

B. Technical Updates to PDPM ICD–10 

Mappings 

C. Recalibrating the PDPM Parity 

Adjustment 

VII. Skilled Nursing Facility (SNF) Quality 

Reporting Program (QRP) 

VIII. Skilled Nursing Facility Value-Based 

Purchasing Program (SNF VBP) 

IX. Long-Term Care Facilities: Physical 

Environment Requirements 

X. Collection of Information Requirements 

XI. Economic Analyses 

A. Regulatory Impact Analysis 

B. Regulatory Flexibility Act Analysis 

C. Unfunded Mandates Reform Act 

Analysis 

D. Federalism Analysis 

E. Reducing Regulation and Controlling 

Regulatory Costs 

F. Congressional Review Act 

G. Regulatory Review Costs 

I. Executive Summary 

A. Purpose 

This final rule updates the SNF 

prospective payment rates for fiscal year 

(FY) 2022 as required under section 

1888(e)(4)(E) of the Social Security Act 

(the Act). It also responds to section 

1888(e)(4)(H) of the Act, which requires 

the Secretary to provide for publication 

of certain specified information relating 

to the payment update (see section II.C. 

of this final rule) in the Federal 

Register, before the August 1 that 

precedes the start of each FY. As 

discussed in section VI.A. of this final 

rule, it will also rebase and revise the 

SNF market basket index, including 

updating the base year from 2014 to 

2018. As discussed in section V.D. of 

this final rule, it also makes revisions in 

the regulation text to exclude from SNF 

consolidated billing certain blood 

clotting factors and items and services 

related to the furnishing of such factors 

effective for items and services 

furnished on or after October 1, 2021, as 

required by the Consolidated 

Appropriations Act, 2021 (Pub. L. 116– 

260, enacted December 27, 2020), as 

well as certain other conforming 

revisions. In addition, as required under 

section 1888(e)(4)(G)(iii) of the Act, as 

added by section 103(b) of the BBRA 

1999, we provide for a proportional 

reduction in the Part A SNF PPS base 

rates to account for this exclusion, as 

described in section IV.B.6. of this final 

rule. We also make changes to the code 

mappings used under the SNF PPS for 

classifying patients into case-mix 


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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42425 

groups. Additionally, this final rule 

includes a forecast error adjustment for 

FY 2022. This final rule also includes a 

discussion of a PDPM parity adjustment. 

Finally, this final rule also updates 

requirements for the Skilled Nursing 

Facility Quality Reporting Program 

(SNF QRP) and the Skilled Nursing 

Facility Value-Based Purchasing 

Program (SNF VBP), including a policy 

to suppress the use of the SNF 

readmission measure for scoring and 

payment adjustment purposes in the FY 

2022 SNF VBP Program because we 

have determined that circumstances 

caused by the public health emergency 

for COVID–19 have significantly 

affected the validity and reliability of 

the measure and resulting performance 

scores. 

B. Summary of Major Provisions 

In accordance with sections 

1888(e)(4)(E)(ii)(IV) and (e)(5) of the Act, 

the Federal rates in this final rule reflect 

an update to the rates that we published 

in the SNF PPS final rule for FY 2021 

(85 FR 47594, August 5, 2020). We are 

also rebasing and revising the SNF 

market basket index, including updating 

the base year from 2014 to 2018. This 

final rule includes revisions to the 

regulation text to exclude from SNF 

consolidated billing certain blood 

clotting factors and items and services 

related to the furnishing of such factors 

effective for items and services 

furnished on or after October 1, 2021, as 

required by the Consolidated 

Appropriations Act, 2021, as well as 

certain conforming revisions. We are 

also making a required reduction in the 

SNF PPS base rates to account for this 

new exclusion. This final rule includes 

revisions to the International 

Classification of Diseases, Version 10 

(ICD–10) code mappings used under 

PDPM to classify patients into case-mix 

groups. Additionally, this final rule 

includes a forecast error adjustment for 

FY 2022. This final rule also includes a 

discussion of a PDPM parity adjustment, 

used to implement PDPM in a budget 

neutral manner. 

This final rule updates requirements 

for the SNF QRP, including the 

adoption of two new measures 

beginning with the FY 2023 SNF QRP: 

The SNF Healthcare Associated 

Infections (HAI) Requiring 

Hospitalization measure; and the 

COVID–19 Vaccination Coverage among 

Healthcare Personnel (HCP) measure. 

The COVID–19 Vaccination Coverage 

among HCP measure requires that SNFs 

use the Centers for Disease Control and 

Prevention (CDC)/National Healthcare 

Safety Network (NHSN) to submit data 

on the measure. We are also finalizing 

our proposal to modify the denominator 

for the Transfer of Health Information to 

the Patient—Post Acute Care (PAC) 

measure. Finally, we are finalizing our 

proposal to revise the number of 

quarters used for publicly reporting 

certain SNF QRP measures due to the 

public health emergency (PHE). 

Additionally, we are finalizing several 

updates for the SNF VBP Program 

including a policy to suppress the 

Skilled Nursing Facility 30-Day AllCause Readmission Measure (SNFRM) 

for the FY 2022 SNF VBP Program Year 

for scoring, adjusting and codifying the 

policy at § 413.338(g). We are also 

updating the Phase One Review and 

Corrections policy to implement a 

claims ‘‘snapshot’’ policy which aligns 

the review and corrections policy for the 

SNF VBP Program with the review and 

corrections policy we use in other 

value-based purchasing programs and 

codifying the policy at § 413.338(e)(1) of 

our regulations. We are also making a 

technical update to the instructions for 

a SNF to request an extraordinary 

circumstances exception and codifying 

that update at § 413.338(d)(4)(ii) of our 

regulations. In addition, we are 

finalizing a technical correction to the 

physical environment requirements for 

LTC facilities by revising § 483.90(d)(1) 

and adding § 483.90(d)(3). 

C. Summary of Cost and Benefits 

D. Advancing Health Information 

Exchange 

The Department of Health and Human 

Services (HHS) has a number of 

initiatives designed to encourage and 

support the adoption of interoperable 

health information technology and to 

promote nationwide health information 

exchange to improve health care and 

patient access to their health 

information. 

To further interoperability in postacute care settings, CMS and the Office 

of the National Coordinator for Health 

Information Technology (ONC) 

participate in the Post-Acute Care 

Interoperability Workgroup (PACIO) 

(https://pacioproject.org/) to facilitate 

collaboration with industry stakeholders 

to develop FHIR standards. These 

standards could support the exchange 

and reuse of patient assessment data 

derived from the minimum data set 

(MDS), inpatient rehabilitation facility 

patient assessment instrument (IRF– 

PAI), long term care hospital continuity 

assessment record and evaluation 

(LCDS), outcome and assessment 

information set (OASIS), and other 

sources. The PACIO Project has focused 

on FHIR implementation guides for 

functional status, cognitive status and 

new use cases on advance directives 

and speech, and language pathology. We 

encourage post-acute care (PAC) 

provider and health information 

technology (IT) vendor participation as 

these efforts advance. 

The CMS Data Element Library (DEL) 

continues to be updated and serves as 

the authoritative resource for PAC 

assessment data elements and their 

associated mappings to health IT 

standards such as Logical Observation 

Identifiers Names and Codes (LOINC) 

and Systematized Nomenclature of 

Medicine Clinical Terms (SNOMED). 

The DEL furthers CMS’ goal of data 

standardization and interoperability. 

When combined with digital 

information systems that capture and 

maintain these coded elements, their 

standardized clinical content can reduce 


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TABLE 1: Cost and Benefits 

Provision Description Total Transfers/Costs 

FY 2022 SNF PPS payment rate The overall economic impact of this final rule is an estimated increase of 

update. $410 million in ae:f!fegate payments to SNFs during FY 2022. 

FY 2022 SNF QRP changes. The overall economic impact of this fmal rule is an estimated increase in 

cost to SNFs of $6.63 million. 

FY 2022 SNF VBP changes. The overall economic impact of the SNF VBP Program is an estimated 

reduction of$191.64 million in aggregate payments to SNFs during FY 

2022. 
42426 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

1ONC, Draft 2 Trusted Exchange Framework and 

Common Agreement, https://www.healthit.gov/ 

sites/default/files/page/2019-04/FINAL

TEFCAQTF41719508version.pdf. 

provider burden by supporting the 

exchange of standardized healthcare 

data; supporting provider exchange of 

electronic health information for care 

coordination, person-centered care; and 

supporting real-time, data driven, 

clinical decision making. Standards in 

the Data Element Library (https://

del.cms.gov/DELWeb/pubHome) can be 

referenced on the CMS website and in 

the ONC Interoperability Standards 

Advisory (ISA). The 2021 ISA is 

available at https://www.healthit.gov/ 

isa. 

The 21st Century Cures Act (Cures 

Act) (Pub. L. 114–255, enacted 

December 13, 2016) requires HHS to 

take new steps to enable the electronic 

sharing of health information ensuring 

interoperability for providers and 

settings across the care continuum. The 

Cures Act includes a trusted exchange 

framework and common agreement 

(TEFCA) provision 1 that will enable the 

nationwide exchange of electronic 

health information across health 

information networks and provide an 

important way to enable bi-directional 

health information exchange in the 

future. For more information on current 

developments related to TEFCA, we 

refer readers to https://

www.healthit.gov/topic/interoperability/ 

trusted-exchange-framework-andcommon-agreement and https://

rce.sequoiaproject.org/. 

The ONC final rule entitled ‘‘21st 

Century Cures Act: Interoperability, 

Information Blocking, and the ONC 

Health IT Certification Program’’ (85 FR 

25642) published in the May 1, 2020, 

Federal Register (hereinafter referred to 

as ‘‘ONC Cures Act Final Rule’’) 

established policies related to 

information blocking as authorized 

under section 4004 of the 21st Century 

Cures Act. Information blocking is 

generally defined as a practice by a 

health IT developer of certified health 

IT, health information network, health 

information exchange, or health care 

provider that, except as required by law 

or specified by the HHS Secretary as a 

reasonable and necessary activity, is 

likely to interfere with access, exchange, 

or use of electronic health information. 

The definition of information blocking 

includes a knowledge standard, which 

is different for health care providers 

than for health IT developers of certified 

health IT and health information 

networks or health information 

exchanges. A healthcare provider must 

know that the practice is unreasonable, 

as well as likely to interfere with access, 

exchange, or use of electronic health 

information. To deter information 

blocking, health IT developers of 

certified health IT, health information 

networks and health information 

exchanges whom the HHS Inspector 

General determines, following an 

investigation, have committed 

information blocking, are subject to civil 

monetary penalties of up to $1 million 

per violation. Appropriate disincentives 

for health care providers are expected to 

be established by the Secretary through 

future rulemaking. Stakeholders can 

learn more about information blocking 

at https://www.healthit.gov/curesrule/ 

final-rule-policy/information-blocking. 

ONC has posted information resources 

including fact sheets (https://

www.healthit.gov/curesrule/resources/ 

fact-sheets), frequently asked questions 

(https://www.healthit.gov/curesrule/ 

resources/information-blocking-faqs), 

and recorded webinars (https://

www.healthit.gov/curesrule/resources/ 

webinars). 

We invite providers to learn more 

about these important developments 

and how they are likely to affect SNFs. 

II. Background on SNF PPS 

A. Statutory Basis and Scope 

As amended by section 4432 of the 

Balanced Budget Act of 1997 (BBA 

1997) (Pub. L. 105–33, enacted August 

5, 1997), section 1888(e) of the Act 

provides for the implementation of a 

PPS for SNFs. This methodology uses 

prospective, case-mix adjusted per diem 

payment rates applicable to all covered 

SNF services defined in section 

1888(e)(2)(A) of the Act. The SNF PPS 

is effective for cost reporting periods 

beginning on or after July 1, 1998, and 

covers all costs of furnishing covered 

SNF services (routine, ancillary, and 

capital-related costs) other than costs 

associated with approved educational 

activities and bad debts. Under section 

1888(e)(2)(A)(i) of the Act, covered SNF 

services include post-hospital extended 

care services for which benefits are 

provided under Part A, as well as those 

items and services (other than a small 

number of excluded services, such as 

physicians’ services) for which payment 

may otherwise be made under Part B 

and which are furnished to Medicare 

beneficiaries who are residents in a SNF 

during a covered Part A stay. A 

comprehensive discussion of these 

provisions appears in the May 12, 1998 

interim final rule (63 FR 26252). In 

addition, a detailed discussion of the 

legislative history of the SNF PPS is 

available online at https://

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

Downloads/Legislative_History_2018- 

10-01.pdf. 

Section 215(a) of the Protecting 

Access to Medicare Act of 2014 (PAMA) 

(Pub. L. 113–93, enacted April 1, 2014) 

added section 1888(g) to the Act 

requiring the Secretary to specify an allcause all-condition hospital readmission 

measure and an all-condition riskadjusted potentially preventable 

hospital readmission measure for the 

SNF setting. Additionally, section 

215(b) of PAMA added section 1888(h) 

to the Act requiring the Secretary to 

implement a VBP program for SNFs. 

Finally, section 2(c)(4) of the IMPACT 

Act amended section 1888(e)(6) of the 

Act, which requires the Secretary to 

implement a QRP for SNFs under which 

SNFs report data on measures and 

resident assessment data. 

B. Initial Transition for the SNF PPS 

Under sections 1888(e)(1)(A) and 

(e)(11) of the Act, the SNF PPS included 

an initial, three-phase transition that 

blended a facility-specific rate 

(reflecting the individual facility’s 

historical cost experience) with the 

Federal case-mix adjusted rate. The 

transition extended through the 

facility’s first 3 cost reporting periods 

under the PPS, up to and including the 

one that began in FY 2001. Thus, the 

SNF PPS is no longer operating under 

the transition, as all facilities have been 

paid at the full Federal rate effective 

with cost reporting periods beginning in 

FY 2002. As we now base payments for 

SNFs entirely on the adjusted Federal 

per diem rates, we no longer include 

adjustment factors under the transition 

related to facility-specific rates for the 

upcoming FY. 

C. Required Annual Rate Updates 

Section 1888(e)(4)(E) of the Act 

requires the SNF PPS payment rates to 

be updated annually. The most recent 

annual update occurred in a final rule 

that set forth updates to the SNF PPS 

payment rates for FY 2021 (85 FR 

47594, August 5, 2020). 

Section 1888(e)(4)(H) of the Act 

specifies that we provide for publication 

annually in the Federal Register the 

following: 

• The unadjusted Federal per diem 

rates to be applied to days of covered 

SNF services furnished during the 

upcoming FY. 

• The case-mix classification system 

to be applied for these services during 

the upcoming FY. 

• The factors to be applied in making 

the area wage adjustment for these 

services. 


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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42427 

Along with other revisions discussed 

later in this preamble, this final rule 

provides the required annual updates to 

the per diem payment rates for SNFs for 

FY 2022. 

III. Analysis and Responses to Public 

Comments on the FY 2022 SNF PPS 

Proposed Rule 

In response to the publication of the 

FY 2022 SNF PPS proposed rule, we 

received 338 public comments from 

individuals, providers, corporations, 

government agencies, private citizens, 

trade associations, and major 

organizations. The following are brief 

summaries of each proposed provision, 

a summary of the public comments that 

we received related to that proposal, 

and our responses to the comments. 

A. General Comments on the FY 2022 

SNF PPS Proposed Rule 

In addition to the comments we 

received on specific proposals 

contained within the proposed rule 

(which we address later in this final 

rule), commenters also submitted the 

following, more general, observations on 

the SNF PPS and SNF care generally. A 

discussion of these comments, along 

with our responses, appears below. 

Comment: Commenters submitted 

numerous comments and 

recommendations that are outside the 

scope of the proposed rule addressing a 

number of different policies, including 

the Coronavirus disease 2019 (COVID– 

19) pandemic. This included comments 

on the flexibilities provided to SNFs 

during the PHE, specifically through the 

waivers issued under sections 1135 and 

1812(f) of the Act. Commenters also 

expressed concerns about the 

substantial additional costs due to the 

PHE that would be permanent due to 

changes in patient care, infection 

control staff and equipment, personal 

protective equipment (PPE), reporting 

requirements, increased wages, 

increased food prices, and other 

necessary costs. Some commenters who 

received CARES Act Provider Relief 

funds indicated that those funds were 

not enough to cover these costs. 

Additionally, a few commenters from 

rural areas stated that their facilities 

were heavily impacted from the 

additional costs, particularly the need to 

raise wages, and that this could affect 

patients’ access to care. 

Response: We greatly appreciate these 

comments and suggestions for revisions 

to policies under the SNF PPS. 

However, because these comments are 

outside the scope of the current 

rulemaking, we are not addressing them 

in this final rule. We may take them 

under consideration in future 

rulemaking. 

IV. SNF PPS Rate Setting Methodology 

and FY 2022 Update 

A. Federal Base Rates 

Under section 1888(e)(4) of the Act, 

the SNF PPS uses per diem Federal 

payment rates based on mean SNF costs 

in a base year (FY 1995) updated for 

inflation to the first effective period of 

the PPS. We developed the Federal 

payment rates using allowable costs 

from hospital-based and freestanding 

SNF cost reports for reporting periods 

beginning in FY 1995. The data used in 

developing the Federal rates also 

incorporated a Part B add-on, which is 

an estimate of the amounts that, prior to 

the SNF PPS, would be payable under 

Part B for covered SNF services 

furnished to individuals during the 

course of a covered Part A stay in a SNF. 

In developing the rates for the initial 

period, we updated costs to the first 

effective year of the PPS (the 15-month 

period beginning July 1, 1998) using a 

SNF market basket index, and then 

standardized for geographic variations 

in wages and for the costs of facility 

differences in case mix. In compiling 

the database used to compute the 

Federal payment rates, we excluded 

those providers that received new 

provider exemptions from the routine 

cost limits, as well as costs related to 

payments for exceptions to the routine 

cost limits. Using the formula that the 

BBA 1997 prescribed, we set the Federal 

rates at a level equal to the weighted 

mean of freestanding costs plus 50 

percent of the difference between the 

freestanding mean and weighted mean 

of all SNF costs (hospital-based and 

freestanding) combined. We computed 

and applied separately the payment 

rates for facilities located in urban and 

rural areas, and adjusted the portion of 

the Federal rate attributable to wagerelated costs by a wage index to reflect 

geographic variations in wages. 

B. SNF Market Basket Update 

1. SNF Market Basket Index 

Section 1888(e)(5)(A) of the Act 

requires us to establish a SNF market 

basket index that reflects changes over 

time in the prices of an appropriate mix 

of goods and services included in 

covered SNF services. Accordingly, we 

have developed a SNF market basket 

index that encompasses the most 

commonly used cost categories for SNF 

routine services, ancillary services, and 

capital-related expenses. In the SNF PPS 

final rule for FY 2018 (82 FR 36548 

through 36566), we rebased and revised 

the market basket index, which 

included updating the base year from 

FY 2010 to 2014. In the proposed rule, 

we proposed to rebase and revise the 

market basket index and update the base 

year from 2014 to 2018. See section 

VI.A. of this final rule for more 

information. 

The SNF market basket index is used 

to compute the market basket 

percentage change that is used to update 

the SNF Federal rates on an annual 

basis, as required by section 

1888(e)(4)(E)(ii)(IV) of the Act. This 

market basket percentage update is 

adjusted by a forecast error correction, 

if applicable, and then further adjusted 

by the application of a productivity 

adjustment as required by section 

1888(e)(5)(B)(ii) of the Act and 

described in section IV.B.2.d. of this 

final rule. 

We proposed a FY 2022 SNF market 

basket percentage of 2.3 percent based 

on IGI’s fourth quarter 2020 forecast of 

the proposed 2018-based SNF market 

basket (before application of the forecast 

error adjustment and productivity 

adjustment). We also proposed that if 

more recent data subsequently become 

available (for example, a more recent 

estimate of the market basket and/or the 

productivity adjustment), we would use 

such data, if appropriate, to determine 

the FY 2022 SNF market basket 

percentage change, labor-related share 

relative importance, forecast error 

adjustment, or productivity adjustment 

in the SNF PPS final rule. 

Since the proposed rule, we have 

updated the FY 2022 market basket 

percentage increase based on IGI’s 

second quarter 2021 forecast with 

historical data through the first quarter 

of 2021. The FY 2022 growth rate of the 

2018-based SNF market basket is 

estimated to be 2.7 percent. 

In section IV.B.2.e. of this final rule, 

we discuss the 2 percent reduction 

applied to the market basket update for 

those SNFs that fail to submit measures 

data as required by section 1888(e)(6)(A) 

of the Act. 

2. Use of the SNF Market Basket 

Percentage 

Section 1888(e)(5)(B) of the Act 

defines the SNF market basket 

percentage as the percentage change in 

the SNF market basket index from the 

midpoint of the previous FY to the 

midpoint of the current FY. For the 

Federal rates set forth in this final rule, 

we use the percentage change in the 

SNF market basket index to compute the 

update factor for FY 2022. This factor is 

based on the FY 2022 percentage 

increase in the 2018-based SNF market 

basket index reflecting routine, 

ancillary, and capital-related expenses. 


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42428 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

As stated previously, in the proposed 

rule, the SNF market basket percentage 

update was estimated to be 2.3 percent 

for FY 2022 based on IGI’s fourth 

quarter 2020 forecast. For this final rule, 

based on IGI’s second quarter 2021 

forecast with historical data through the 

first quarter of 2021, the FY 2022 growth 

rate of the 2018-based SNF market 

basket is estimated to be 2.7 percent. 

A discussion of the comments 

received on applying the FY 2022 SNF 

market basket percentage increase to the 

SNF PPS rates, along with our 

responses, may be found below. 

Comment: Several commenters stated 

their support for the proposed FY 2022 

payment update of 1.3 percent reflecting 

the proposed market basket update, the 

productivity adjustment, and the 

forecast error adjustment. A few 

commenters, while noting appreciation 

for the 1.3 percent update, also noted 

that it is very low in comparison to the 

increased costs they are facing as a 

result of the COVID–19 pandemic and 

that many facilities are already 

operating on thin margins. 

Response: The proposed FY 2022 SNF 

payment update of 1.3 percent reflected 

the forecast available at that time of the 

market basket update, productivity 

adjustment, and forecast error. As stated 

in the proposed rule, we proposed to 

use the most recent forecast of data 

available to determine the final FY 2022 

SNF payment update. The current 

estimate of final FY 2022 SNF payment 

update is 1.2 percent based on the IGI 

second quarter 2021 forecast of the 

2018-based SNF market basket update 

(2.7 percent), reduced by the 

productivity adjustment (0.7 percentage 

point), and the application of the FY 

2020 forecast error adjustment (¥0.8 

percentage point). For this final rule, we 

have incorporated the most recent 

historical data and forecasts provided by 

IHS Global Inc., including experience 

during the PHE, in order to capture the 

price and wage pressures facing SNFs in 

FY 2022. By incorporating the most 

recent estimates available of the market 

basket update and productivity 

adjustment, we believe these data reflect 

the best available projection of input 

price inflation faced by SNFs for FY 

2022, adjusted for economy-wide 

productivity, which is required by 

statute. 

Comment: The Medicare Payment 

Advisory Commission (MedPAC) 

commented that they recommend that 

the Congress eliminate the update to 

SNF payments for FY 2022. Moreover, 

MedPAC stated that the aggregate 

Medicare margin for freestanding SNFs 

in 2019 was 11.3 percent, the 20th 

consecutive year that this margin has 

exceeded 10 percent. MedPAC further 

stated that the projected margin for FY 

2022 indicated that while payments 

might need to be reduced to more 

closely align them with the cost to treat 

beneficiaries, they also understand that 

the lasting impacts of COVID–19 on 

SNFs are uncertain which is why they 

proceeded cautiously in recommending 

no update rather than reductions to 

payments. 

Response: We appreciate MedPAC’s 

recommendation on the SNF annual 

update factor and the uncertainty for 

SNFs posed by the PHE. However, we 

are required to update SNF PPS 

payments by the market basket update, 

as required by section 

1888(e)(4)(E)(ii)(IV) of the Act, and then 

further adjust the market basket update 

by the application of a productivity 

adjustment, as required by section 

1888(e)(5)(B)(ii) of the Act. This 

productivity-adjusted market basket 

percentage update is further adjusted by 

a forecast error correction, if applicable. 

After considering the comments 

received on the FY 2022 SNF market 

basket update factor, we are finalizing 

the update factor of 2.7 percent to the 

SNF PPS base rates for FY 2022 (prior 

to the application of the forecast error 

adjustment and productivity 

adjustment, which are discussed below). 

3. Forecast Error Adjustment 

As discussed in the June 10, 2003 

supplemental proposed rule (68 FR 

34768) and finalized in the August 4, 

2003 final rule (68 FR 46057 through 

46059), § 413.337(d)(2) provides for an 

adjustment to account for market basket 

forecast error. The initial adjustment for 

market basket forecast error applied to 

the update of the FY 2003 rate for FY 

2004, and took into account the 

cumulative forecast error for the period 

from FY 2000 through FY 2002, 

resulting in an increase of 3.26 percent 

to the FY 2004 update. Subsequent 

adjustments in succeeding FYs take into 

account the forecast error from the most 

recently available FY for which there is 

final data, and apply the difference 

between the forecasted and actual 

change in the market basket when the 

difference exceeds a specified threshold. 

We originally used a 0.25 percentage 

point threshold for this purpose; 

however, for the reasons specified in the 

FY 2008 SNF PPS final rule (72 FR 

43425), we adopted a 0.5 percentage 

point threshold effective for FY 2008 

and subsequent FYs. As we stated in the 

final rule for FY 2004 that first issued 

the market basket forecast error 

adjustment (68 FR 46058), the 

adjustment will reflect both upward and 

downward adjustments, as appropriate. 

For FY 2020 (the most recently 

available FY for which there is final 

data), the forecasted or estimated 

increase in the SNF market basket index 

was 2.8 percent, and the actual increase 

for FY 2020 is 2.0 percent, resulting in 

the actual increase being 0.8 percentage 

point lower than the estimated increase. 

Accordingly, as the difference between 

the estimated and actual amount of 

change in the market basket index 

exceeds the 0.5 percentage point 

threshold, under the policy previously 

described (comparing the forecasted and 

actual increase in the market basket), 

the FY 2022 market basket percentage 

change of 2.7 percent, based on the IGI 

second quarter 2021 forecast, would be 

adjusted downward to account for the 

forecast error correction of 0.8 

percentage point, resulting in a SNF 

market basket percentage change of 1.2 

percent after reducing the market basket 

update by the productivity adjustment 

of 0.7 percentage point, discussed 

below. 

In the FY 2022 SNF PPS proposed 

rule, we noted that we may consider 

modifying this forecast error 

methodology in future rulemaking. We 

invited comments and feedback on this 

issue, in particular on the possibility of, 

in future rulemaking, either eliminating 

the forecast error adjustment, or raising 

the threshold for the forecast error from 

0.5 percent to 1.0 percent. 

Table 2 shows the forecasted and 

actual market basket increases for FY 

2020. 


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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42429 

The following is a summary of the 

public comments received on the 

potential revisions to the forecast error 

adjustment and our responses: 

Comment: Several commenters 

provided feedback on potentially 

modifying the SNF forecast error 

threshold in future rulemaking. Some 

commenters requested that the forecast 

error threshold remain the same at 0.5 

percentage point. Other commenters 

requested that the forecast error 

threshold be increased to 1.0 percentage 

point in order to provide greater 

stability and certainty for year-to-year 

payments, while others requested that it 

be eliminated. One commenter 

recommended retaining the forecast 

error adjustment for the next three fiscal 

years at 0.5 percentage point and to then 

move to an alternative approach that 

would use a cumulative rolling 

projected forecast error calculation 

before triggering the forecast error 

threshold. 

Response: We appreciate the 

commenters’ responses and viewpoints 

on the forecast error threshold and will 

take them into consideration for future 

rulemaking. 

Comment: Some commenters further 

stated that while they generally support 

the forecast error concept for the SNF 

PPS, given the scale of the COVID–19 

disruption that occurred in FY 2020 and 

the associated atypical claims, they have 

concerns about the reliability and 

timing of the proposed 0.8 percentage 

point forecast error adjustment. 

Commenters stated that they believe 

CMS did not provide transparency in 

what is driving the variance between the 

estimated and actual 2020 market basket 

update and, therefore, they did not have 

an opportunity to comment on the data 

used to explain the variance. They 

stated that the industry experience in 

2020 was that labor costs in particular 

were much higher than expected. A few 

commenters specifically requested that 

CMS eliminate the forecast error 

adjustment for FY 2022. 

Response: The PHE presented many 

challenges to SNFs and as more 

complete data covering the full impact 

of the PHE become available we plan to 

monitor the information as it pertains to 

future rate updates and forecast error 

adjustments. 

Pertaining to the forecast error, CMS 

publishes the forecasts of the market 

baskets (including SNF) on the CMS 

website (https://www.cms.gov/ResearchStatistics-Data-and-Systems/StatisticsTrends-and-Reports/ 

MedicareProgramRatesStats/ 

MarketBasketData) on a quarterly basis. 

Additionally, as stated on the CMS 

website, providers can also email 

DNHS@cms.hhs.gov for further 

information on the market baskets. For 

the FY 2020 SNF market basket forecast 

error, this quarterly information was 

indicating that the error was likely to 

exceed the threshold of 0.5 percentage 

point. The final FY 2020 forecast error 

was only recently able to be computed 

using historical data through the third 

quarter of 2020, and this information 

was provided in the proposed rule. In 

response to commenters, we are 

providing a detailed breakdown of the 

contribution of the major market basket 

categories to the 0.8-percentage point 

forecast error: 0.4 percentage point is 

due to lower compensation price 

growth, 0.2 percentage point is due to 

lower Fuel, Oil, and Gas prices, and 0.2 

percentage point is due to lower 

pharmaceutical prices. As stated in 

section VI.A. of this final rule, the SNF 

market basket is a Laspeyres-type price 

index that measures the prices 

associated with providing skilled 

nursing care services to Medicare 

beneficiaries. Cost growth is a function 

of price (such as the growth in average 

hourly wages) and quantity (such as 

increases in labor hours). Any changes 

in the quantity or mix of goods and 

services (that is, intensity) purchased 

over time relative to a base period are 

not measured annually, these are 

reflected when the market basket is 

rebased (such as our proposal to rebase 

the SNF market basket to 2018). 

Commenters interested in the detailed 

2014-based SNF market basket 

methodology and its underlying public 

data sources may refer to the FY 2018 

SNF PPS final rule (82 FR 36548 

through 36565). 

After consideration of the comments 

discussed above, we are finalizing the 

application of the proposed forecast 

error adjustment without modification. 

As stated above, based on IGI’s second 

quarter 2021 forecast with historical 

data through the first quarter of 2021, 

the updated FY 2022 growth rate of the 

2018-based SNF market basket is 

estimated to be 2.7 percent. Applying 

the forecast error adjustment for FY 

2022 results in an adjusted FY 2022 

market basket update factor of 1.9 

percent, which is then further reduced 

by the productivity adjustment 

discussed below. 

4. Productivity Adjustment 

Section 1888(e)(5)(B)(ii) of the Act, as 

added by section 3401(b) of the Patient 

Protection and Affordable Care Act 

(Affordable Care Act) (Pub. L. 111–148, 

enacted March 23, 2010) requires that, 

in FY 2012 and in subsequent FYs, the 

market basket percentage under the SNF 

payment system (as described in section 

1888(e)(5)(B)(i) of the Act) is to be 

reduced annually 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, in turn, 

defines the productivity adjustment to 

be equal to the 10-year moving average 

of changes in annual economy-wide, 

private nonfarm business multifactor 

productivity (MFP) (as projected by the 

Secretary for the 10-year period ending 

with the applicable FY, year, costreporting period, or other annual 

period). The U.S. Department of Labor’s 

Bureau of Labor Statistics (BLS) 

publishes the official measure of private 

nonfarm business MFP. We refer readers 

to the BLS website at http://

www.bls.gov/mfp for the BLS historical 

published MFP data. 

A complete description of the MFP 

projection methodology is available on 

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

Research-Statistics-Data-and-Systems/ 

Statistics-Trends-and-Reports/ 

MedicareProgramRatesStats/ 

MarketBasketResearch.html. We note 

that, effective with FY 2022 and 

forward, we are changing the name of 

this adjustment to refer to it as the 


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TABLE 2: Difference Between the Actual and Forecasted Market Basket Increases for FY 2020 

Index Forecasted Actual FY 2020 FY 2020 Difference FY 2020 Increase* Increase** 

SNF 2.8 2.0 -0.8 

*Published in Federal Register; based on second quarter 2019 IGI forecast (2014-based index). 

**Based on the fourth quarter 2020 IGI forecast (2014-based index). 
42430 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

‘‘productivity adjustment,’’ rather than 

the ‘‘MFP adjustment.’’ This change in 

terminology results in a title more 

consistent with the statutory language 

described in section 1886(b)(3)(B)(xi)(II) 

of the Act. 

a. Incorporating the Productivity 

Adjustment Into the Market Basket 

Update 

Per section 1888(e)(5)(A) of the Act, 

the Secretary shall establish a SNF 

market basket index that reflects 

changes over time in the prices of an 

appropriate mix of goods and services 

included in covered SNF services. 

Section 1888(e)(5)(B)(ii) of the Act, 

added by section 3401(b) of the 

Affordable Care Act, requires that for FY 

2012 and each subsequent FY, after 

determining the market basket 

percentage described in section 

1888(e)(5)(B)(i) of the Act, the Secretary 

shall reduce such percentage by the 

productivity adjustment described in 

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

Section 1888(e)(5)(B)(ii) of the Act 

further states that the reduction of the 

market basket percentage by the 

productivity adjustment may result in 

the market basket percentage being less 

than zero for a FY, and may result in 

payment rates under section 1888(e) of 

the Act being less than such payment 

rates for the preceding fiscal year. Thus, 

if the application of the productivity 

adjustment to the market basket 

percentage calculated under section 

1888(e)(5)(B)(i) of the Act results in a 

productivity-adjusted market basket 

percentage that is less than zero, then 

the annual update to the unadjusted 

Federal per diem rates under section 

1888(e)(4)(E)(ii) of the Act would be 

negative, and such rates would decrease 

relative to the prior FY. 

Based on the data available for the FY 

2022 SNF PPS proposed rule, the 

estimated 10-year moving average of 

changes in MFP for the period ending 

September 30, 2022 was 0.2 percentage 

point. However, for this final rule, based 

on IGI’s second quarter 2021 forecast, 

the estimated 10-year moving average of 

changes in MFP for the period ending 

September 30, 2022 is 0.7 percentage 

point. 

Consistent with section 

1888(e)(5)(B)(i) of the Act and 

§ 413.337(d)(2), as discussed previously, 

the market basket percentage for FY 

2022 for the SNF PPS is based on IGI’s 

second quarter 2021 forecast of the SNF 

market basket percentage, which is 

estimated to be 2.7 percent. This market 

basket percentage is then lowered by 0.8 

percentage point, due to application of 

the forecast error adjustment discussed 

above. Finally, as discussed above, we 

are applying a 0.7 percentage point 

productivity adjustment to the FY 2022 

SNF market basket percentage. The 

resulting productivity-adjusted FY 2022 

SNF market basket update is, therefore, 

equal to 1.2 percent, or 2.7 percent less 

0.8 percentage point to account for 

forecast error and less 0.7 percentage 

point to account for the productivity 

adjustment. 

5. Market Basket Update Factor for FY 

2022 

Sections 1888(e)(4)(E)(ii)(IV) and 

(e)(5)(i) of the Act require that the 

update factor used to establish the FY 

2022 unadjusted Federal rates be at a 

level equal to the market basket index 

percentage change. Accordingly, we 

determined the total growth from the 

average market basket level for the 

period of October 1, 2020 through 

September 30, 2021 to the average 

market basket level for the period of 

October 1, 2021 through September 30, 

2022. This process yields a percentage 

change in the 2018-based SNF market 

basket of 2.7 percent. 

As further explained in section 

IV.B.2.c. of this final rule, as applicable, 

we adjust the market basket percentage 

change by the forecast error from the 

most recently available FY for which 

there is final data and apply this 

adjustment whenever the difference 

between the forecasted and actual 

percentage change in the market basket 

exceeds a 0.5 percentage point threshold 

in absolute terms. Since the forecasted 

FY 2020 SNF market basket percentage 

change exceeded the actual FY 2020 

SNF market basket percentage change 

(FY 2020 is the most recently available 

FY for which there is historical data) by 

more than the 0.5 percentage point 

threshold, we proposed to adjust the FY 

2022 market basket percentage change 

downward by the forecast error 

correction. Applying the ¥0.8 

percentage point forecast error 

correction results in an adjusted FY 

2022 SNF market basket percentage 

change of 1.9 percent (2.7 percent 

market basket update less 0.8 percentage 

point forecast error adjustment). 

Section 1888(e)(5)(B)(ii) of the Act 

requires us to reduce the market basket 

percentage change by the productivity 

adjustment (10-year moving average of 

changes in MFP for the period ending 

September 30, 2022) which is estimated 

to be 0.7 percentage point, as described 

in section IV.B.2.d. of this final rule. 

Thus, we apply a net SNF market basket 

update factor of 1.2 percent in our 

determination of the FY 2022 SNF PPS 

unadjusted Federal per diem rates, 

which reflects a market basket increase 

factor of 2.7 percent, less the 0.8 percent 

forecast error correction and less the 0.7 

percentage point productivity 

adjustment. 

In the proposed rule, we noted that if 

more recent data become available (for 

example, a more recent estimate of the 

SNF market basket and/or MFP), we 

would use such data, if appropriate, to 

determine the FY 2022 SNF market 

basket percentage change, labor-related 

share relative importance, forecast error 

adjustment, or productivity adjustment 

in the FY 2022 SNF PPS final rule. 

Since more recent data did become 

available since the proposed rule, as 

outlined above, we have updated the 

various adjustment factors described 

through this section accordingly. 

We also noted that section 

1888(e)(6)(A)(i) of the Act provides that, 

beginning with FY 2018, SNFs that fail 

to submit data, as applicable, in 

accordance with sections 

1888(e)(6)(B)(i)(II) and (III) of the Act for 

a fiscal year will receive a 2.0 

percentage point reduction to their 

market basket update for the fiscal year 

involved, after application of section 

1888(e)(5)(B)(ii) of the Act (the 

productivity adjustment) and section 

1888(e)(5)(B)(iii) of the Act (the 1 

percent market basket increase for FY 

2018). In addition, section 

1888(e)(6)(A)(ii) of the Act states that 

application of the 2.0 percentage point 

reduction (after application of section 

1888(e)(5)(B)(ii) and (iii) of the Act) may 

result in the market basket index 

percentage change being less than zero 

for a fiscal year, and may result in 

payment rates for a fiscal year being less 

than such payment rates for the 

preceding fiscal year. Section 

1888(e)(6)(A)(iii) of the Act further 

specifies that the 2.0 percentage point 

reduction is applied in a noncumulative 

manner, so that any reduction made 

under section 1888(e)(6)(A)(i) of the Act 

applies only to the fiscal year involved, 

and that the reduction cannot be taken 

into account in computing the payment 

amount for a subsequent fiscal year. 

6. Unadjusted Federal Per Diem Rates 

for FY 2022 

As discussed in the FY 2019 SNF PPS 

final rule (83 FR 39162), in FY 2020 we 

implemented a new case-mix 

classification system to classify SNF 

patients under the SNF PPS, the PDPM. 

As discussed in section V.B.1. of that 

final rule (83 FR 39189), under PDPM, 

the unadjusted Federal per diem rates 

are divided into six components, five of 

which are case-mix adjusted 

components (Physical Therapy (PT), 

Occupational Therapy (OT), SpeechLanguage Pathology (SLP), Nursing, and 

Non-Therapy Ancillaries (NTA)), and 


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one of which is a non-case-mix 

component, as existed under the 

previous RUG–IV model. We proposed 

to use the SNF market basket, adjusted 

as described previously, to adjust each 

per diem component of the Federal rates 

forward to reflect the change in the 

average prices for FY 2022 from the 

average prices for FY 2021. We 

proposed to further adjust the rates by 

a wage index budget neutrality factor, 

described later in this section. Further, 

in the past, we used the revised OMB 

delineations adopted in the FY 2015 

SNF PPS final rule (79 FR 45632, 

45634), with updates as reflected in 

OMB Bulletin Nos. 15–01 and 17–01, to 

identify a facility’s urban or rural status 

for the purpose of determining which 

set of rate tables would apply to the 

facility. As discussed in the FY 2021 

SNF PPS proposed and final rules, we 

adopted the revised OMB delineations 

identified in OMB Bulletin No. 18–04 

(available at https://

www.whitehouse.gov/wp-content/ 

uploads/2018/09/Bulletin-18-04.pdf) to 

identify a facility’s urban or rural status 

effective beginning with FY 2021. 

For FY 2022, we note there is an 

additional adjustment to the unadjusted 

per diem base rates. Specifically, section 

134 in Division CC of the Consolidated 

Appropriations Act, 2021 included a 

provision amending section 

1888(e)(2)(A)(iii) of the Act so as to add 

‘‘blood clotting factors indicated for the 

treatment of patients with hemophilia 

and other bleeding disorders . . . and 

items and services related to the 

furnishing of such factors under section 

1842(o)(5)(C)’’ to the list of items and 

services excludable from the Part A SNF 

PPS per diem payment, effective for 

items and services furnished on or after 

October 1, 2021. We discuss this 

provision further in section V.B. of this 

final rule. 

Section 1888(e)(4)(G)(iii) of the Act 

further requires that the Secretary 

‘‘provide for an appropriate 

proportional reduction in payments so 

that . . . the aggregate amount of such 

reductions is equal to the aggregate 

increase in payments attributable to the 

exclusion’’ of the services from the Part 

A PPS per diem rates under section 

1888(e)(2)(A)(iii) of the Act. 

In the FY 2001 rulemaking cycle (65 

FR 19202 and 46792), we established a 

methodology for computing such offsets 

in response to similar targeted 

consolidated billing exclusions added to 

section 1888(e)(2)(A)(iii) Act by section 

103 of BBRA 1999. This methodology 

resulted in a reduction of 5 cents ($0.05) 

in the unadjusted urban and rural rates, 

using the identical data as used to 

establish the Part B add-on for a sample 

of approximately 1,500 SNFs from the 

1995 base period. However, because this 

methodology relied on data from 1995, 

we proposed a new methodology based 

on updated data (as discussed below) to 

apply the offsets required for the 

exclusion of the blood clotting factors 

and items and services related to the 

furnishing of such factors under section 

1842(o)(5)(C) of the Act (referred to 

collectively as the blood clotting factor 

exclusion), as specified under the 

Consolidated Appropriations Act, 2021. 

As we noted in the proposed rule, we 

believe the use of the updated data will 

more accurately capture the actual cost 

of these factors, as using updated 

utilization data would reflect new types 

of blood clotting factors introduced in 

recent years and changes in utilization 

patterns of blood clotting factors since 

1995. 

The methodology for calculating the 

blood clotting factor exclusion offset as 

set forth in the proposed rule consists of 

five steps. In the first step, we begin 

with the total number of SNF utilization 

days for beneficiaries who have any 

amount of blood clotting factor (BCF) 

use in FY 2020. While we recognize the 

potential effects of the PHE for COVID– 

19 on SNF utilization during 2020, we 

believe we should use FY 2020 data 

because it is the most recent data 

available, and thus would best reflect 

the latest types of blood clotting factors 

and the most recent changes in 

utilization patterns; also, the FY 2020 

data is the only data available that 

reflects utilization under the PDPM 

model rather than the RUG–IV model. 

However, in light of the potential 

impact of the PHE for COVID–19 on 

SNF utilization, particularly as it relates 

to those patients admitted with COVID– 

19 or whose stays utilized a PHE-related 

waiver (for example, the waiver which 

removes the requirement for a three-day 

prior inpatient hospital stay in order to 

receive SNF Part A coverage), we 

believe it is appropriate to use a subset 

of the full FY 2020 SNF population 

which excludes patients diagnosed with 

COVID–19 and those stays which 

utilized a PHE-related waiver. We 

discuss this concept in more detail in 

relation to the recalibration of the PDPM 

parity adjustment, discussed in section 

VI.C. of this final rule. As further 

explained below, we would note that 

using this subset population has very 

little impact on the result of the 

methodology described below. 

Throughout the discussion below, the 

term ‘‘SNF beneficiary’’ refers to 

beneficiaries in the FY 2020 subset 

population described above. 

Since BCF use has historically been 

subject to SNF consolidated billing and 

its usage cannot be observed on billed 

SNF claims, this methodology resorts to 

claims from other settings to 

approximate BCF utilization in SNFs. 

Specifically, BCF use as well as items 

and services related to the furnishing of 

such factors under section 1842(o)(5)(C) 

of the Act are identified by checking if 

any of the Healthcare Common 

Procedure Coding System (HCPCS) 

codes listed in the Act, including J7170, 

J7175, J7177–J7183, J7185–J7190, J7192– 

J7195, J7198–J7203, J7205, and J7207– 

J7211, are recorded on outpatient 

claims, which are claims submitted by 

institutional outpatient providers (such 

as a hospital outpatient department), or 

carrier claims, which are fee-for-service 

claims submitted by professional 

practitioners, such as physicians, 

physician assistants, clinical social 

workers, and nurse practitioners, and by 

some organizational providers, such as 

free-standing facilities. A SNF 

beneficiary with any BCF use is defined 

as a SNF beneficiary with at least one 

matched outpatient or carrier claim for 

blood clotting factors in FY 2020. To 

calculate the number of SNF utilization 

days for beneficiaries who have any 

amount of BCF use in FY 2020, we sum 

up the corresponding SNF utilization 

days of SNF beneficiaries with BCF use 

in FY 2020 (84 beneficiaries), which is 

3,317 total utilization days. 

In the second step, we estimate the 

BCF payment per day per SNF 

beneficiary with any BCF use in FY 

2020, which would include payment for 

the BCFs and items and services related 

to the furnishing of such factors under 

section 1842(o)(5)(C) of the Act. There 

are no direct payment data to track BCF 

use in SNFs since BCF use currently is 

bundled within the Part A per diem 

payment. Therefore, we rely on payment 

in outpatient and carrier claims as a 

proxy for this step. Instead of 

calculating BCF payment per day for 

SNF beneficiaries in a SNF stay, we 

estimate the BCF payment per day for 

SNF beneficiaries outside of their SNF 

and inpatient stays, under the 

assumption that BCF payment per day 

for SNF beneficiaries is similar during 

and outside of SNF stays. Outpatient or 

carrier claims for BCF use that overlap 

with a SNF stay or an inpatient stay of 

a SNF beneficiary are excluded to 

ensure that BCF-related payment is fully 

captured in Part B claims instead of 

partially paid through Part A. 

Overlapping claims are identified when 

the outpatient claim ‘‘From’’ date or the 

carrier claim expense date fall within a 

SNF or inpatient stay’s admission and 

discharge date window. The total BCF 

payment for SNF beneficiaries’ BCF use 


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42432 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

observed through Part B claims in FY 

2020 was $4,843,551. Next, to determine 

the corresponding utilizations days for 

SNF beneficiaries’ BCF use, we need to 

carve out their utilization days in a SNF 

or inpatient setting for these target 

beneficiaries. We first determine the 

total SNF and inpatient utilization days 

for these beneficiaries in FY 2020, 

which totals 5,408. Next, we determine 

the total days that the beneficiaries with 

BCF use were not in a SNF or inpatient 

stay, which is 365 (for days in the year) 

multiplied by the number of SNF 

beneficiaries with BCF use (84), less the 

total SNF and inpatient utilization days 

for these beneficiaries (5,408), which is 

20,142. Finally, we estimated the BCF 

payment per day, which is the total BCF 

payment observed in outpatient and 

carrier claims ($4,843,551) divided by 

the total days the beneficiaries were not 

in a SNF or inpatient setting (20,142). 

Thus, we calculate the BCF payment per 

day per SNF beneficiary to be $240. 

In the third step, we calculate the 

percentage of SNF payment associated 

with BCF usage. We multiply the 

estimated BCF payment per day ($240 

as determined in step 2) by the total 

SNF utilization days for SNF 

beneficiaries with BCF use in FY 2020 

(3,317 as determined in step 1). This 

yields an estimated BCF payment for 

SNF beneficiaries in the study 

population of $797,640. Next, we divide 

this by the total SNF payment for the 

study population during FY 2020 

($22,636,345,868) to yield the 

percentage of SNF payment associated 

with BCF use, which we estimate to be 

0.00352 percent. 

In the fourth step, we calculate the 

urban and rural base rate reductions, by 

multiplying the proposed FY 2022 

urban/rural base rates by the percentage 

of SNF payment associated with clotting 

factor use determined in step 3 (0.00352 

percent). In the case of the proposed 

urban base rate of $434.95, this yields 

an urban base rate deduction of $0.02, 

which we would apply as a $0.01 

reduction to the proposed FY 2022 NTA 

base rate and a $0.01 reduction to the 

proposed FY 2022 nursing base rate. In 

the case of the proposed rural base rate 

of $450.37, this yields a rural base rate 

deduction of $0.02, which we would 

apply as a $0.01 reduction to the 

proposed FY 2022 NTA base rates and 

a $0.01 reduction to the proposed FY 

2022 nursing base rate. We would apply 

the reduction to the NTA and nursing 

base rates because BCF is a type of NTA 

and nursing resources are required to 

furnish this medication. 

In step five, for purposes of impact 

analysis, we calculate the budget impact 

of the base rate reductions to be 

$782,785. We estimate the budget 

impact by multiplying the total FY2022 

SNF baseline ($34,211,000,000) by the 

percentage of SNF payment for clotting 

factor (0.00352 percent). This results in 

a total reduction in SNF spending of 

$1.2 million. To compare the result of 

this methodology to that which would 

have resulted from using the full FY 

2020 SNF population, we note that if we 

had used the full FY 2020 SNF 

population, the resultant impact would 

be a reduction in SNF spending of $1.5 

million, which represents 0.004551 

percent of total payments made under 

the SNF PPS. Given that these figures 

are so close as to result in the same two 

cent reduction in the FY 2022 SNF PPS 

unadjusted per diem rates, and given 

the reasons for using the subset 

population discussed in section VI.C. of 

this final rule, we believe it is 

appropriate to use this subset 

population as the basis for the 

calculations described throughout this 

section. 

We apply these rate reductions to the 

NTA and nursing components of the 

unadjusted Federal urban and rural per 

diem rate as shown in Tables 4 and 5. 

Table 3 displays the methodology and 

figures used to calculate these rate 

reductions. 

BILLING CODE 4120–01–P 


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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42433 

The comments we received on the 

proposed methodology to adjust the 

SNF PPS base rates in response to the 

recent blood clotting factor exclusion, 

along with our responses, appear below. 

Comment: Several commenters noted 

support for the proposed methodology 

for adjusting the base rates to remove 

the costs associated with Blood Clotting 

Factor (BCF)-related services from the 

Part A consolidated billing per diem 

payment that resulted in a proposed 

0.00352 percent adjustment. A 

commenter noted that this methodology 

is preferable to the alternative 

methodology that would result in a 

0.004551 percent adjustment. 

Response: We thank the commenters 

for their support. Accordingly, we are 

finalizing, as proposed, the 

methodology for reducing the base rates 

to remove the costs associated with 

Blood Clotting Factor (BCF)-related 

services. 

Tables 4 and 5 reflect the updated 

unadjusted Federal rates for FY 2022, 

prior to adjustment for case-mix. The 

rates in Tables 4 and 5 include the 

reductions calculated in Table 3 for 

blood clotting factor use. 

BILLING CODE 4120–01–C 


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TABLE 3: Estimation of Blood Clotting Factor on Base Rate Reduction 

FY2020 Total Part B Clotting Factor Payment for Benes with Any BCF 

Use Outside of SNF or In atient Sta 

FY2020 Total SNF and In atient Util Da s for Benes with An BCF Use 

FY2020 Total Days Not in SNF or Inpatient Stay for Benes with Any 

BCFUse 

FY2022 Urban Base Rate 

FY2022 Urban Base Rate Reduction for Clottin Factor Use 

FY2022 Rural Base Rate 

FY2022 SNF Baseline 

$4,843,551 

5,408 

20,142 

$434.95 

$34,211,000,000 

$782,785 

TABLE 4: FY 2022 Unadjusted Federal Rate Per Diem-URBAN 

Rate Component PT OT SLP Nursing NTA Non-Case-Mix 

Per Diem Amount $62.82 $58.48 $23.45 $109.51 $82.62 $98.07 

TABLE 5: FY 2022 Unadjusted Federal Rate Per Diem-RURAL 

Rate Component PT OT SLP Nursing NTA Non-Case-Mix 

Per Diem Amount $71.61 $65.77 $29.55 $104.63 $78.93 $99.88 
42434 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

C. Case-Mix Adjustment 

Under section 1888(e)(4)(G)(i) of the 

Act, the Federal rate also incorporates 

an adjustment to account for facility 

case-mix, using a classification system 

that accounts for the relative resource 

utilization of different patient types. 

The statute specifies that the adjustment 

is to reflect both a resident classification 

system that the Secretary establishes to 

account for the relative resource use of 

different patient types, as well as 

resident assessment data and other data 

that the Secretary considers appropriate. 

In the FY 2019 final rule (83 FR 39162, 

August 8, 2018), we finalized a new 

case-mix classification model, the 

PDPM, which took effect beginning 

October 1, 2019. The previous RUG–IV 

model classified most patients into a 

therapy payment group and primarily 

used the volume of therapy services 

provided to the patient as the basis for 

payment classification, thus creating an 

incentive for SNFs to furnish therapy 

regardless of the individual patient’s 

unique characteristics, goals, or needs. 

PDPM eliminates this incentive and 

improves the overall accuracy and 

appropriateness of SNF payments by 

classifying patients into payment groups 

based on specific, data-driven patient 

characteristics, while simultaneously 

reducing the administrative burden on 

SNFs. 

As we noted in the FY 2021 SNF PPS 

final rule (85 FR 47600), we continue to 

monitor the impact of PDPM 

implementation on patient outcomes 

and program outlays. We hope to release 

information in the future that relates to 

these issues, though we provide some of 

this information in section VI.C. of this 

final rule. We also continue to monitor 

the impact of PDPM implementation as 

it relates to our intention to ensure that 

PDPM is implemented in a budget 

neutral manner, as discussed in the FY 

2020 SNF PPS final rule (84 FR 38734). 

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

discuss the methodology to recalibrate 

the PDPM parity adjustment as 

appropriate to ensure budget neutrality, 

as we did after the implementation of 

RUG–IV in FY 2011. 

The PDPM uses clinical data from the 

MDS to assign case-mix classifiers to 

each patient that are then used to 

calculate a per diem payment under the 

SNF PPS, consistent with the provisions 

of section 1888(e)(4)(G)(i) of the Act. As 

discussed in section V.A. of this final 

rule, the clinical orientation of the casemix classification system supports the 

SNF PPS’s use of an administrative 

presumption that considers a 

beneficiary’s initial case-mix 

classification to assist in making certain 

SNF level of care determinations. 

Further, because the MDS is used as a 

basis for payment, as well as a clinical 

assessment, we have provided extensive 

training on proper coding and the 

timeframes for MDS completion in our 

Resident Assessment Instrument (RAI) 

Manual. As we have stated in prior 

rules, for an MDS to be considered valid 

for use in determining payment, the 

MDS assessment should be completed 

in compliance with the instructions in 

the RAI Manual in effect at the time the 

assessment is completed. For payment 

and quality monitoring purposes, the 

RAI Manual consists of both the Manual 

instructions and the interpretive 

guidance and policy clarifications 

posted on the appropriate MDS website 

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

Quality-Initiatives-Patient-AssessmentInstruments/NursingHomeQualityInits/ 

MDS30RAIManual.html. 

Under section 1888(e)(4)(H) of the 

Act, each update of the payment rates 

must include the case-mix classification 

methodology applicable for the 

upcoming FY. The FY 2022 payment 

rates set forth in this final rule reflect 

the use of the PDPM case-mix 

classification system from October 1, 

2021, through September 30, 2022. The 

case-mix adjusted PDPM payment rates 

for FY 2022 are listed separately for 

urban and rural SNFs, in Tables 6 and 

7 with corresponding case-mix values. 

Given the differences between the 

previous RUG–IV model and PDPM in 

terms of patient classification and 

billing, it was important that the format 

of Tables 6 and 7 reflect these 

differences. More specifically, under 

both RUG–IV and PDPM, providers use 

a Health Insurance Prospective Payment 

System (HIPPS) code on a claim to bill 

for covered SNF services. Under RUG– 

IV, the HIPPS code included the threecharacter RUG–IV group into which the 

patient classified as well as a twocharacter assessment indicator code that 

represented the assessment used to 

generate this code. Under PDPM, while 

providers still use a HIPPS code, the 

characters in that code represent 

different things. For example, the first 

character represents the PT and OT 

group into which the patient classifies. 

If the patient is classified into the PT 

and OT group ‘‘TA’’, then the first 

character in the patient’s HIPPS code 

would be an A. Similarly, if the patient 

is classified into the SLP group ‘‘SB’’, 

then the second character in the 

patient’s HIPPS code would be a B. The 

third character represents the Nursing 

group into which the patient classifies. 

The fourth character represents the NTA 

group into which the patient classifies. 

Finally, the fifth character represents 

the assessment used to generate the 

HIPPS code. 

Tables 6 and 7 reflect the PDPM’s 

structure. Accordingly, Column 1 of 

Tables 6 and 7 represents the character 

in the HIPPS code associated with a 

given PDPM component. Columns 2 and 

3 provide the case-mix index and 

associated case-mix adjusted component 

rate, respectively, for the relevant PT 

group. Columns 4 and 5 provide the 

case-mix index and associated case-mix 

adjusted component rate, respectively, 

for the relevant OT group. Columns 6 

and 7 provide the case-mix index and 

associated case-mix adjusted component 

rate, respectively, for the relevant SLP 

group. Column 8 provides the nursing 

case-mix group (CMG) that is connected 

with a given PDPM HIPPS character. For 

example, if the patient qualified for the 

nursing group CBC1, then the third 

character in the patient’s HIPPS code 

would be a ‘‘P.’’ Columns 9 and 10 

provide the case-mix index and 

associated case-mix adjusted component 

rate, respectively, for the relevant 

nursing group. Finally, columns 11 and 

12 provide the case-mix index and 

associated case-mix adjusted component 

rate, respectively, for the relevant NTA 

group. 

Tables 6 and 7 do not reflect 

adjustments which may be made to the 

SNF PPS rates as a result of the SNF 

VBP Program, discussed in section IV.D. 

of this final rule, or other adjustments, 

such as the variable per diem 

adjustment. Further, in the past, we 

used the revised OMB delineations 

adopted in the FY 2015 SNF PPS final 

rule (79 FR 45632, 45634), with updates 

as reflected in OMB Bulletin Nos, 15– 

01 and 17–01, to identify a facility’s 

urban or rural status for the purpose of 

determining which set of rate tables 

would apply to the facility. As 

discussed in the FY 2021 SNF PPS final 

rule (85 FR 47594), we adopted the 

revised OMB delineations identified in 

OMB Bulletin No. 18–04 (available at 

https://www.whitehouse.gov/wpcontent/uploads/2018/09/Bulletin-18- 

04.pdf) to identify a facility’s urban or 

rural status effective beginning with FY 

2021. 


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TABLE 6: PDPM Case-Mix Adjusted Federal Rates and Associated Indexes-URBAN 

PDPM PT PT OT OT SLP SLP Nursing Nursing Nursing NTA NTA 

Group CMI Rate CMI Rate CMI Rate CMG CMI Rate CMI Rate 

A 1.53 $96.11 1.49 $87.14 0.68 $15.95 ES3 4.06 $444.61 3.24 $267.69 

B 1.70 $106.79 1.63 $95.32 1.82 $42.68 ES2 3.07 $336.20 2.53 $209.03 

C 1.88 $118.10 1.69 $98.83 2.67 $62.61 ESl 2.93 $320.86 1.84 $152.02 

D 1.92 $120.61 1.53 $89.47 1.46 $34.24 HDE2 2.40 $262.82 1.33 $109.88 

E 1.42 $89.20 1.41 $82.46 2.34 $54.87 HDEl 1.99 $217.92 0.96 $79.32 

F 1.61 $101.14 1.60 $93.57 2.98 $69.88 HBC2 2.24 $245.30 0.72 $59.49 

G 1.67 $104.91 1.64 $95.91 2.04 $47.84 HBCl 1.86 $203.69 - -

H 1.16 $72.87 1.15 $67.25 2.86 $67.07 LDE2 2.08 $227.78 - -

I 1.13 $70.99 1.18 $69.01 3.53 $82.78 LDEl 1.73 $189.45 - -

J 1.42 $89.20 1.45 $84.80 2.99 $70.12 LBC2 1.72 $188.36 - -

K 1.52 $95.49 1.54 $90.06 3.7 $86.77 LBCl 1.43 $156.60 - -

L 1.09 $68.47 1.11 $64.91 4.21 $98.72 CDE2 1.87 $204.78 - -

M 1.27 $79.78 1.30 $76.02 - - CDEl 1.62 $177.41 - -

N 1.48 $92.97 1.50 $87.72 - - CBC2 1.55 $169.74 - -

0 1.55 $97.37 1.55 $90.64 - - CA2 1.09 $119.37 - - p 1.08 $67.85 1.09 $63.74 - - CBCl 1.34 $146.74 - -

Q - - - - - - CAI 0.94 $102.94 - -

R - - - - - - BAB2 1.04 $113.89 - -

s - - - - - - BABl 0.99 $108.41 - -

T - - - - - - PDE2 1.57 $171.93 - -

u - - - - - - PDEl 1.47 $160.98 - -

V - - - - - - PBC2 1.22 $133.60 - -

w - - - - - - PA2 0.71 $77.75 - -

X - - - - - - PBCl 1.13 $123.75 - - y - - - - - - PAI 0.66 $72.28 - -
42436 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

D. Wage Index Adjustment 

Section 1888(e)(4)(G)(ii) of the Act 

requires that we adjust the Federal rates 

to account for differences in area wage 

levels, using a wage index that the 

Secretary determines appropriate. Since 

the inception of the SNF PPS, we have 

used hospital inpatient wage data in 

developing a wage index to be applied 

to SNFs. We continue this practice for 

FY 2022, as we continue to believe that 

in the absence of SNF-specific wage 

data, using the hospital inpatient wage 

index data is appropriate and reasonable 

for the SNF PPS. As explained in the 

update notice for FY 2005 (69 FR 

45786), the SNF PPS does not use the 

hospital area wage index’s occupational 

mix adjustment, as this adjustment 

serves specifically to define the 

occupational categories more clearly in 

a hospital setting; moreover, the 

collection of the occupational wage data 

under the inpatient prospective 

payment system (IPPS) also excludes 

any wage data related to SNFs. 

Therefore, we believe that using the 

updated wage data exclusive of the 

occupational mix adjustment continues 

to be appropriate for SNF payments. As 

in previous years, we would continue to 

use the pre-reclassified IPPS hospital 

wage data, without applying the 

occupational mix, rural floor, or 

outmigration adjustment, as the basis for 

the SNF PPS wage index. For FY 2022, 

the updated wage data are for hospital 

cost reporting periods beginning on or 

after October 1, 2017 and before October 

1, 2018 (FY 2018 cost report data). 

We note that section 315 of the 

Medicare, Medicaid, and SCHIP 

Benefits Improvement and Protection 

Act of 2000 (BIPA) (Pub. L. 106–554, 

enacted December 21, 2000) authorized 

us to establish a geographic 

reclassification procedure that is 

specific to SNFs, but only after 

collecting the data necessary to establish 

a SNF PPS wage index that is based on 

wage data from nursing homes. 

However, to date, this has proven to be 

unfeasible due to the volatility of 

existing SNF wage data and the 

significant amount of resources that 

would be required to improve the 

quality of the data. More specifically, 

auditing all SNF cost reports, similar to 

the process used to audit inpatient 

hospital cost reports for purposes of the 

IPPS wage index, would place a burden 

on providers in terms of recordkeeping 

and completion of the cost report 

worksheet. In addition, adopting such 

an approach would require a significant 

commitment of resources by CMS and 

the Medicare Administrative 

Contractors, potentially far in excess of 

those required under the IPPS given that 

there are nearly five times as many 

SNFs as there are inpatient hospitals. 

Therefore, while we continue to believe 

that the development of such an audit 

process could improve SNF cost reports 

in such a manner as to permit us to 

establish a SNF-specific wage index, we 

do not believe this undertaking is 

feasible at this time. 

In the proposed rule, we proposed to 

continue using the same methodology 

discussed in the SNF PPS final rule for 

FY 2008 (72 FR 43423) to address those 

geographic areas in which there are no 

hospitals, and thus, no hospital wage 

index data on which to base the 

calculation of the FY 2022 SNF PPS 

wage index. For rural geographic areas 

that do not have hospitals and, 

therefore, lack hospital wage data on 

which to base an area wage adjustment, 

we proposed to continue using the 

average wage index from all contiguous 


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TABLE 7: PDPM Case-Mix Adjusted Federal Rates and Associated Indexes-RURAL 

PDPM PT PT OT OT SLP SLP Nursing Nursing Nursing NTA NTA 

Group CMI Rate CMI Rate CMI Rate CMG CMI Rate CMI Rate 

A 1.53 $109.56 1.49 $98.00 0.68 $20.09 ES3 4.06 $424.80 3.24 $255.73 

B 1.70 $121.74 1.63 $107.21 1.82 $53.78 ES2 3.07 $321.21 2.53 $199.69 

C 1.88 $134.63 1.69 $111.15 2.67 $78.90 ESI 2.93 $306.57 1.84 $145.23 

D 1.92 $137.49 1.53 $100.63 1.46 $43.14 HDE2 2.40 $251.11 1.33 $104.98 

E 1.42 $101.69 1.41 $92.74 2.34 $69.15 HDEI 1.99 $208.21 0.96 $75.77 

F 1.61 $115.29 1.60 $105.23 2.98 $88.06 HBC2 2.24 $234.37 0.72 $56.83 

G 1.67 $119.59 1.64 $107.86 2.04 $60.28 HBCI 1.86 $194.61 - -

H 1.16 $83.07 1.15 $75.64 2.86 $84.51 LDE2 2.08 $217.63 - -

I 1.13 $80.92 1.18 $77.61 3.53 $104.31 LDEI 1.73 $181.01 - -

J 1.42 $101.69 1.45 $95.37 2.99 $88.35 LBC2 1.72 $179.96 - -

K 1.52 $108.85 1.54 $101.29 3.7 $109.34 LBCI 1.43 $149.62 - -

L 1.09 $78.05 1.11 $73.00 4.21 $124.41 CDE2 1.87 $195.66 - -

M 1.27 $90.94 1.30 $85.50 - - CDEI 1.62 $169.50 - -

N 1.48 $105.98 1.50 $98.66 - - CBC2 1.55 $162.18 - -

0 1.55 $111.00 1.55 $101.94 - - CA2 1.09 $114.05 - - p 1.08 $77.34 1.09 $71.69 - - CBCI 1.34 $140.20 - -

Q - - - - - - CAI 0.94 $98.35 - -

R - - - - - - BAB2 1.04 $108.82 - -

s - - - - - - BABI 0.99 $103.58 - -

T - - - - - - PDE2 1.57 $164.27 - -

u - - - - - - PDEI 1.47 $153.81 - -

V - - - - - - PBC2 1.22 $127.65 - -

w - - - - - - PA2 0.71 $74.29 - -

X - - - - - - PBCI 1.13 $118.23 - - y - - - - - - PAI 0.66 $69.06 - -
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42437 

Core-Based Statistical Areas (CBSAs) as 

a reasonable proxy. For FY 2022, there 

are no rural geographic areas that do not 

have hospitals, and thus, this 

methodology will not be applied. For 

rural Puerto Rico, we proposed not to 

apply this methodology due to the 

distinct economic circumstances that 

exist there (for example, due to the close 

proximity to one another of almost all 

of Puerto Rico’s various urban and nonurban areas, this methodology would 

produce a wage index for rural Puerto 

Rico that is higher than that in half of 

its urban areas); instead, we would 

continue using the most recent wage 

index previously available for that area. 

For urban areas without specific 

hospital wage index data, we proposed 

that we would use the average wage 

indexes of all of the urban areas within 

the state to serve as a reasonable proxy 

for the wage index of that urban CBSA. 

For FY 2022, the only urban area 

without wage index data available is 

CBSA 25980, Hinesville-Fort Stewart, 

GA. 

The wage index applicable to FY 2022 

is set forth in Tables A and B available 

on the CMS website at http://

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

WageIndex.html. 

In the SNF PPS final rule for FY 2006 

(70 FR 45026, August 4, 2005), we 

adopted the changes discussed in 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 CBSA geographic designations, we 

provided for a 1-year transition in FY 

2006 with a blended wage index for all 

providers. For FY 2006, the wage index 

for each provider consisted of a blend of 

50 percent of the FY 2006 MSA-based 

wage index and 50 percent of the FY 

2006 CBSA-based wage index (both 

using FY 2002 hospital data). We 

referred to the blended wage index as 

the FY 2006 SNF PPS transition wage 

index. As discussed in the SNF PPS 

final rule for FY 2006 (70 FR 45041), 

after the expiration of this 1-year 

transition on September 30, 2006, we 

used the full CBSA-based wage index 

values. 

In the FY 2015 SNF PPS final rule (79 

FR 45644 through 45646), we finalized 

changes to the SNF PPS wage index 

based on the newest OMB delineations, 

as described in OMB Bulletin No. 13– 

01, beginning in FY 2015, including a 

1-year transition with a blended wage 

index for FY 2015. OMB Bulletin No. 

13–01 established revised delineations 

for Metropolitan Statistical Areas, 

Micropolitan Statistical Areas, and 

Combined Statistical Areas in the 

United States and Puerto Rico based on 

the 2010 Census, and provided guidance 

on the use of the delineations of these 

statistical areas using standards 

published in the June 28, 2010 Federal 

Register (75 FR 37246 through 37252). 

Subsequently, on July 15, 2015, OMB 

issued OMB Bulletin No. 15–01, which 

provided minor updates to and 

superseded OMB Bulletin No. 13–01 

that was issued on February 28, 2013. 

The attachment to OMB Bulletin No. 

15–01 provided detailed information on 

the update to statistical areas since 

February 28, 2013. The updates 

provided in OMB Bulletin No. 15–01 

were based on the application of the 

2010 Standards for Delineating 

Metropolitan and Micropolitan 

Statistical Areas to Census Bureau 

population estimates for July 1, 2012 

and July 1, 2013 and were adopted 

under the SNF PPS in the FY 2017 SNF 

PPS final rule (81 FR 51983, August 5, 

2016). In addition, on August 15, 2017, 

OMB issued Bulletin No. 17–01 which 

announced a new urban CBSA, Twin 

Falls, Idaho (CBSA 46300) which was 

adopted in the SNF PPS final rule for 

FY 2019 (83 FR 39173, August 8, 2018). 

As discussed in the FY 2021 SNF PPS 

final rule (85 FR 47594), we adopted the 

revised OMB delineations identified in 

OMB Bulletin No. 18–04 (available at 

https://www.whitehouse.gov/wpcontent/uploads/2018/09/Bulletin-18- 

04.pdf) beginning October 1, 2020, 

including a 1-year transition for FY 

2021 under which we applied a 5 

percent cap on any decrease in a 

hospital’s wage index compared to its 

wage index for the prior fiscal year (FY 

2020). The updated OMB delineations 

more accurately reflect the 

contemporary urban and rural nature of 

areas across the country, and the use of 

such delineations allows us to 

determine more accurately the 

appropriate wage index and rate tables 

to apply under the SNF PPS. 

As we previously stated in the FY 

2008 SNF PPS proposed and final rules 

(72 FR 25538 through 25539, and 72 FR 

43423), this and all subsequent SNF PPS 

rules and notices are considered to 

incorporate any updates and revisions 

set forth in the most recent OMB 

bulletin that applies to the hospital 

wage data used to determine the current 

SNF PPS wage index. We note that on 

March 6, 2020, OMB issued Bulletin No. 

20–01, which provided updates to and 

superseded OMB Bulletin No. 18–04 

that was issued on September 14, 2018. 

The attachments to OMB Bulletin No. 

20–01 provided detailed information on 

the updates (available on the web at 

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

01.pdf). In the FY 2021 SNF PPS final 

rule (85 FR 47611), we stated that we 

intended to propose any updates from 

OMB Bulletin No. 20–01 in the FY 2022 

SNF PPS proposed rule. After reviewing 

OMB Bulletin No. 20–01, we have 

determined that the changes in OMB 

Bulletin 20–01 encompassed 

delineation changes that do not impact 

the CBSA-based labor market area 

delineations adopted in FY 2021. 

Therefore, while we proposed to adopt 

the updates set forth in OMB Bulletin 

No. 20–01 consistent with our 

longstanding policy of adopting OMB 

delineation updates, we noted that 

specific wage index updates would not 

be necessary for FY 2022 as a result of 

adopting these OMB updates. 

The proposed wage index applicable 

to FY 2022 is set forth in Tables A and 

B and is available on the CMS website 

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

Medicare-Fee-for-Service-Payment/ 

SNFPPS/WageIndex.html. 

Once calculated, we would apply the 

wage index adjustment to the laborrelated portion of the Federal rate. Each 

year, we calculate a revised laborrelated share, based on the relative 

importance of labor-related cost 

categories (that is, those cost categories 

that are labor-intensive and vary with 

the local labor market) in the input price 

index. In the SNF PPS final rule for FY 

2018 (82 FR 36548 through 36566), we 

finalized a proposal to revise the laborrelated share to reflect the relative 

importance of the 2014-based SNF 

market basket cost weights for the 

following cost categories: Wages and 

Salaries; Employee Benefits; 

Professional Fees: Labor-Related; 

Administrative and Facilities Support 

Services; Installation, Maintenance, and 

Repair Services; All Other: LaborRelated Services; and a proportion of 

Capital-Related expenses. Effective 

beginning FY 2022, as discussed in 

section VI.A.4. of this final rule, for FY 

2022, we are rebasing and revising the 

labor-related share to reflect the relative 

importance of the 2018-based SNF 

market basket cost weights for the 

following cost categories: Wages and 

Salaries; Employee Benefits; 

Professional fees: Labor-related; 

Administrative and Facilities Support 

services; Installation, Maintenance, and 

Repair services; All Other: LaborRelated Services; and a proportion of 

Capital-Related expenses. The 

methodology for calculating the laborrelated portion for FY 2022 is discussed 

in section VI.A. of this final rule. 

We calculate the labor-related relative 

importance from the SNF market basket, 

and it approximates the labor-related 


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42438 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

portion of the total costs after taking 

into account historical and projected 

price changes between the base year and 

FY 2022. The price proxies that move 

the different cost categories in the 

market basket do not necessarily change 

at the same rate, and the relative 

importance captures these changes. 

Accordingly, the relative importance 

figure more closely reflects the cost 

share weights for FY 2022 than the base 

year weights from the SNF market 

basket. We calculate the labor-related 

relative importance for FY 2022 in four 

steps. First, we compute the FY 2022 

price index level for the total market 

basket and each cost category of the 

market basket. Second, we calculate a 

ratio for each cost category by dividing 

the FY 2022 price index level for that 

cost category by the total market basket 

price index level. Third, we determine 

the FY 2022 relative importance for 

each cost category by multiplying this 

ratio by the base year (2018) weight. 

Finally, we add the FY 2022 relative 

importance for each of the labor-related 

cost categories (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 Capital-Related expenses) to 

produce the FY 2022 labor-related 

relative importance. 

For the proposed rule, the laborrelated share for FY 2022 was based on 

IGI’s fourth quarter 2020 forecast of the 

proposed 2018-based SNF market basket 

with historical data through third 

quarter 2020. For this final rule, we 

based the labor-related share for FY 

2022 on IGI’s second quarter 2021 

forecast, with historical data through the 

first quarter 2021. Table 8 summarizes 

the labor-related share for FY 2022, 

based on IGI’s second quarter 2021 

forecast of the 2018-based SNF market 

basket with historical data through first 

quarter 2021, compared to the laborrelated share that was used for the FY 

2021 SNF PPS final rule. 

To calculate the labor portion of the 

case-mix adjusted per diem rate, we 

would multiply the total case-mix 

adjusted per diem rate, which is the 

sum of all five case-mix adjusted 

components into which a patient 

classifies, and the non-case-mix 

component rate, by the FY 2022 laborrelated share percentage provided in 

Table 8. The remaining portion of the 

rate would be the non-labor portion. 

Under the previous RUG–IV model, we 

included tables which provided the 

case-mix adjusted RUG–IV rates, by 

RUG–IV group, broken out by total rate, 

labor portion and non-labor portion, 

such as Table 9 of the FY 2019 SNF PPS 

final rule (83 FR 39175). However, as we 

discussed in the FY 2020 final rule (84 

FR 38738), under PDPM, as the total rate 

is calculated as a combination of six 

different component rates, five of which 

are case-mix adjusted, and given the 

sheer volume of possible combinations 

of these five case-mix adjusted 

components, it is not feasible to provide 

tables similar to those that existed in the 

prior rulemaking. 

Therefore, to aid stakeholders in 

understanding the effect of the wage 

index on the calculation of the SNF per 

diem rate, we have included a 

hypothetical rate calculation in Table 9. 

Section 1888(e)(4)(G)(ii) of the Act 

also requires that we apply this wage 

index in a manner that does not result 

in aggregate payments under the SNF 

PPS that are greater or less than would 

otherwise be made if the wage 

adjustment had not been made. For FY 

2022 (Federal rates effective October 1, 

2021), we apply an adjustment to fulfill 

the budget neutrality requirement. We 

meet this requirement by multiplying 

each of the components of the 

unadjusted Federal rates by a budget 

neutrality factor, equal to the ratio of the 

weighted average wage adjustment 

factor for FY 2021 to the weighted 

average wage adjustment factor for FY 

2022. For this calculation, we would use 

the same FY 2020 claims utilization 

data for both the numerator and 

denominator of this ratio. We define the 

wage adjustment factor used in this 

calculation as the labor portion of the 

rate component multiplied by the wage 

index plus the non-labor portion of the 

rate component. The proposed budget 

neutrality factor for FY 2022 as set forth 

in the proposed rule was 0.9999. 

In the proposed rule, we noted that if 

more recent data become available (for 

example, revised wage data), we would 

use such data, as appropriate, to 

determine the wage index budget 

neutrality factor in the SNF PPS final 

rule. Since the proposed rule, we have 

updated the weighted average wage 


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TABLE 8: Labor-Related Relative Importance, FY 2021 and FY 2022 

Relative importance, Relative importance, 

labor-related share, labor-related share, 

FY 2021 FY2022 

20:2 forecast1 21:2 forecast2 

Wages and salaries 51.1 51.4 

Employee benefits 9.9 9.5 

Professional fees: Labor-related 3.7 3.5 

Administrative & facilities 0.6 support services 0.5 

Installation, maintenance & 0.4 repair services 0.6 

All other: Labor-related services 2.6 2.0 

Capital-related (.391) 2.9 3.0 

Total 71.3 70.4 

1 Published in the Federal Register (85 FR 47605); based on the second quarter 2020 IHS Global Inc. forecast 

of the 2014-based SNF market basket, with historical data through first quarter 2020. 

2 Based on the second quarter 2021 IHS Global Inc. forecast of the 2018-based SNF market basket, with 

historical data through first quarter 2021. 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42439 

adjustment factor for FY 2022. Based on 

this updated information, the budget 

neutrality factor for FY 2022 is 1.0006. 

The following is a summary of the 

public comments received on the 

proposed revisions to the Wage Index 

Adjustment and our responses: 

Comment: Several commenters 

recommended that we consider creating 

a SNF-specific wage index utilizing the 

SNF cost report, as opposed to 

continuing to rely on hospital data as 

the basis for the SNF wage index. 

Commenters requested the SNF wage 

data analysis and access to needed 

hospital and SNF cost report wage data 

to conduct their own analysis towards 

assisting us in refining the current SNF 

wage index methodology. Additionally, 

one commenter requested to meet with 

CMS to discuss these ideas, while 

another commenter would like to 

provide more feedback. 

Response: We appreciate the 

commenter’s suggestion as to the 

development of a SNF specific wage 

index. However, to date, the 

development of a SNF-specific wage 

index has proven to be unfeasible due 

to the volatility of existing SNF wage 

data and the significant amount of 

resources that would be required to 

improve the quality of that data. We 

note that, consistent with the preceding 

discussion in this final rule as well as 

our previous responses to these 

recurring SNF-specific wage index 

comments (most recently published in 

the FY 2019 SNF PPS final rule (83 FR 

39172 through 39173)), developing such 

a wage index would require a resourceintensive audit process similar to that 

used for IPPS hospital data, to improve 

the quality of the SNF cost report data 

in order for it to be used as part of this 

analysis. We also discussed in the FY 

2019 SNF PPS why utilizing concepts 

such as trimming methods, BLS data, 

occupational mix, Payroll Based 

Journal, and rural floor are unfeasible or 

not applicable to SNF policy. We 

continue to believe that in the absence 

of the appropriate SNF-specific wage 

data, using the pre-reclassified, pre-rural 

floor hospital inpatient wage data 

(without the occupational mix 

adjustment) is appropriate and 

reasonable for the SNF PPS. 

Regarding the request for data, we 

will consider the comments and 

examine what data could be released 

that would assist stakeholders in 

understanding both the volatility of the 

SNF wage data and the issues with 

using this data to develop a SNFspecific wage index. As always, we 

encourage and welcome dialogue with 

stakeholders regarding this, or any 

other, issues related to SNF payments 

under Medicare. 

Comment: We received several 

comments that were outside the scope 

of the FY 2022 SNF PPS proposed rule. 

Specifically, commenters appreciated 

that, in the SNF PPS final rule for FY 

2021, CMS recognized the need for a 

transitional policy in the form of a 5 

percent cap on any decease in a SNF’s 

wage index in adopting the OMB 

delineations updated in OMB Bulletin 

18–04. However, these commenters also 

expressed that a 1-year cap is not 

sufficient to offset the enormous cuts 

scheduled for FY 2022, thus requesting 

an extension to the 5 percent cap 

transition. 

Response: We thank the commenters 

for bringing this issue to our attention. 

We note that at times when changes to 

the wage index occur, those changes 

may result in large and potentially 

unpredictable impacts on Medicare 

payments that impact providers. These 

changes may arise from changes to wage 

index areas due to updates related to 

decennial census data, changes to wage 

index areas due to updates related to 

revised OMB delineations. 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 are to use the most updated 

data and information available and 

provide that data and information, as 

well as any approaches to addressing 

these potential scenarios, through notice 

and comment rulemaking. 

After considering the comments 

received, for the reasons set forth in this 

final rule and in the FY 2022 SNF PPS 

proposed rule, we are finalizing our 

proposal to adopt the revised OMB 

delineations contained in OMB Bulletin 

18–04 as proposed, without 

modification. 

E. SNF Value-Based Purchasing 

Program 

Beginning with payment for services 

furnished on October 1, 2018, section 

1888(h) of the Act requires the Secretary 

to reduce the adjusted Federal per diem 

rate determined under section 

1888(e)(4)(G) of the Act otherwise 

applicable to a SNF for services 

furnished during a fiscal year by 2 

percent, and to adjust the resulting rate 

for a SNF by the value-based incentive 

payment amount earned by the SNF 

based on the SNF’s performance score 

for that fiscal year under the SNF VBP 

Program. To implement these 

requirements, we finalized in the FY 

2019 SNF PPS final rule the addition of 

§ 413.337(f) to our regulations (83 FR 

39178). 

Please see section VIII. of this final 

rule for a further discussion of our 

policies for the SNF VBP Program. 

F. Adjusted Rate Computation Example 

Tables 9, 10, and 11 provide examples 

generally illustrating payment 

calculations during FY 2022 under 

PDPM for a hypothetical 30-day SNF 

stay, involving the hypothetical SNF 

XYZ, located in Frederick, MD (Urban 

CBSA 23244), for a hypothetical patient 

who is classified into such groups that 

the patient’s HIPPS code is NHNC1. 

Table 9 shows the adjustments made to 

the Federal per diem rates (prior to 

application of any adjustments under 

the SNF VBP Program as discussed 

previously) to compute the provider’s 

case-mix adjusted per diem rate for FY 

2022, based on the patient’s PDPM 

classification, as well as how the 

variable per diem (VPD) adjustment 

factor affects calculation of the per diem 

rate for a given day of the stay. Table 10 

shows the adjustments made to the casemix adjusted per diem rate from Table 

9 to account for the provider’s wage 

index. The wage index used in this 

example is based on the FY 2022 SNF 

PPS wage index that appears in Table A 

available on the CMS website at http:// 

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

WageIndex.html. Finally, Table 11 

provides the case-mix and wage index 

adjusted per-diem rate for this patient 

for each day of the 30-day stay, as well 

as the total payment for this stay. Table 

11 also includes the VPD adjustment 

factors for each day of the patient’s stay, 

to clarify why the patient’s per diem 

rate changes for certain days of the stay. 

As illustrated in Table 9, SNF XYZ’s 

total PPS payment for this particular 

patient’s stay would equal $20,532.52. 


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TABLE 9: PDPM Case-Mix Adjusted Rate Computation Example 

Per Diem Rate Calculation 

Component Component Group Component Rate VPD Adjustment Factor VPD Adi. Rate 

PT N $92.97 1.00 $92.97 

OT N $87.72 1.00 $87.72 

SLP H $67.07 1.00 $67.07 

Nursine: N $169.74 1.00 $169.74 

NTA C $152.02 3.00 $456.06 

Non-Case-Mix - $98.07 - $98.07 

Total PDPM Case-Mix Ad_j. Per Diem $971.63 

TABLE 10: Wage Index Adjusted Rate Computation Example 

PDPM Waee Index Adiustment Calculation 

HIPPS PDPM Case-Mix Labor Wage Wage Index Non-Labor Total Case Mix 

and Wage Index Code Adjusted Per Diem Portion Index Adjusted Rate Portion Adj. Rate 

NHNCl $971.63 $684.03 0.9755 $667.27 $287.60 $954.87 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42441 

V. Additional Aspects of the SNF PPS 

A. SNF Level of Care—Administrative 

Presumption 

The establishment of the SNF PPS did 

not change Medicare’s fundamental 

requirements for SNF coverage. 

However, because the case-mix 

classification is based, in part, on the 

beneficiary’s need for skilled nursing 

care and therapy, we have attempted, 

where possible, to coordinate claims 

review procedures with the existing 

resident assessment process and casemix classification system discussed in 

section IV.C. of this final rule. This 

approach includes an administrative 

presumption that utilizes a beneficiary’s 

correct assignment, at the outset of the 

SNF stay, of one of the case-mix 

classifiers designated for this purpose to 

assist in making certain SNF level of 

care determinations. 

In accordance with § 413.345, we 

include in each update of the Federal 

payment rates in the Federal Register a 

discussion of the resident classification 

system that provides the basis for casemix adjustment. We also designate those 

specific classifiers under the case-mix 

classification system that represent the 

required SNF level of care, as provided 

in 42 CFR 409.30. This designation 

reflects an administrative presumption 

that those beneficiaries who are 

correctly assigned one of the designated 

case-mix classifiers on the initial 

Medicare assessment are automatically 

classified as meeting the SNF level of 

care definition up to and including the 

assessment reference date (ARD) for that 

assessment. 

A beneficiary who does not qualify for 

the presumption is not automatically 

classified as either meeting or not 

meeting the level of care definition, but 

instead receives an individual 

determination on this point using the 

existing administrative criteria. This 

presumption recognizes the strong 

likelihood that those beneficiaries who 

are correctly assigned one of the 

designated case-mix classifiers during 

the immediate post-hospital period 

would require a covered level of care, 

which would be less likely for other 

beneficiaries. 

In the July 30, 1999 final rule (64 FR 

41670), we indicated that we would 

announce any changes to the guidelines 

for Medicare level of care 

determinations related to modifications 

in the case-mix classification structure. 

The FY 2018 final rule (82 FR 36544) 

further specified that we would 

henceforth disseminate the standard 

description of the administrative 

presumption’s designated groups via the 

SNF PPS website at https://

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


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TABLE 11: Adjusted Rate Computation Example 

Day of Stay NTAVPD PT/OTVPD Case Mix and Wage Index 

Adjustment Factor Adjustment Factor Adjusted Per Diem Rate 

1 3.0 1.0 $954.87 

2 3.0 1.0 $954.87 

3 3.0 1.0 $954.87 

4 1.0 1.0 $656.08 

5 1.0 1.0 $656.08 

6 1.0 1.0 $656.08 

7 1.0 1.0 $656.08 

8 1.0 1.0 $656.08 

9 1.0 1.0 $656.08 

10 1.0 1.0 $656.08 

11 1.0 1.0 $656.08 

12 1.0 1.0 $656.08 

13 1.0 1.0 $656.08 

14 1.0 1.0 $656.08 

15 1.0 1.0 $656.08 

16 1.0 1.0 $656.08 

17 1.0 1.0 $656.08 

18 1.0 1.0 $656.08 

19 1.0 1.0 $656.08 

20 1.0 1.0 $656.08 

21 1.0 0.98 $652.52 

22 1.0 0.98 $652.52 

23 1.0 0.98 $652.52 

24 1.0 0.98 $652.52 

25 1.0 0.98 $652.52 

26 1.0 0.98 $652.52 

27 1.0 0.98 $652.52 

28 1.0 0.96 $648.97 

29 1.0 0.96 $648.97 

30 1.0 0.96 $648.97 

Total Payment $20,532.52 
42442 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

index.html (where such designations 

appear in the paragraph entitled ‘‘Case 

Mix Adjustment’’), and would publish 

such designations in rulemaking only to 

the extent that we actually intend to 

propose changes in them. Under that 

approach, the set of case-mix classifiers 

designated for this purpose under PDPM 

was finalized in the FY 2019 SNF PPS 

final rule (83 FR 39253) and is posted 

on the SNF PPS website (https://

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

index.html), in the paragraph entitled 

‘‘Case Mix Adjustment.’’ 

However, we note that this 

administrative presumption policy does 

not supersede the SNF’s responsibility 

to ensure that its decisions relating to 

level of care are appropriate and timely, 

including a review to confirm that any 

services prompting the assignment of 

one of the designated case-mix 

classifiers (which, in turn, serves to 

trigger the administrative presumption) 

are themselves medically necessary. As 

we explained in the FY 2000 SNF PPS 

final rule (64 FR 41667), the 

administrative presumption is itself 

rebuttable in those individual cases in 

which the services actually received by 

the resident do not meet the basic 

statutory criterion of being reasonable 

and necessary to diagnose or treat a 

beneficiary’s condition (according to 

section 1862(a)(1) of the Act). 

Accordingly, the presumption would 

not apply, for example, in those 

situations where the sole classifier that 

triggers the presumption is itself 

assigned through the receipt of services 

that are subsequently determined to be 

not reasonable and necessary. Moreover, 

we want to stress the importance of 

careful monitoring for changes in each 

patient’s condition to determine the 

continuing need for Part A SNF benefits 

after the ARD of the initial Medicare 

assessment. 

B. Consolidated Billing 

Sections 1842(b)(6)(E) and 1862(a)(18) 

of the Act (as added by section 4432(b) 

of the BBA 1997) require a SNF to 

submit consolidated Medicare bills to 

its Medicare Administrative Contractor 

(MAC) for almost all of the services that 

its residents receive during the course of 

a covered Part A stay. In addition, 

section 1862(a)(18) of the Act places the 

responsibility with the SNF for billing 

Medicare for physical therapy, 

occupational therapy, and speechlanguage pathology services that the 

resident receives during a noncovered 

stay. Section 1888(e)(2)(A) of the Act 

excludes a small list of services from the 

consolidated billing provision 

(primarily those services furnished by 

physicians and certain other types of 

practitioners), which remain separately 

billable under Part B when furnished to 

a SNF’s Part A resident. These excluded 

service categories are discussed in 

greater detail in section V.B.2. of the 

May 12, 1998 interim final rule (63 FR 

26295 through 26297). 

A detailed discussion of the 

legislative history of the consolidated 

billing provision is available on the SNF 

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

Medicare/Medicare-Fee-for-ServicePayment/SNFPPS/Downloads/ 

Legislative_History_2018-10-01.pdf. In 

particular, section 103 of the BBRA 

1999 amended section 1888(e)(2)(A)(iii) 

of the Act by further excluding a 

number of individual high-cost, low 

probability services, identified by 

HCPCS codes, within several broader 

categories (chemotherapy items, 

chemotherapy administration services, 

radioisotope services, and customized 

prosthetic devices) that otherwise 

remained subject to the provision. We 

discuss this BBRA 1999 amendment in 

greater detail in the SNF PPS proposed 

and final rules for FY 2001 (65 FR 19231 

through 19232, April 10, 2000, and 65 

FR 46790 through 46795, July 31, 2000), 

as well as in Program Memorandum 

AB–00–18 (Change Request #1070), 

issued March 2000, which is available 

online at www.cms.gov/transmittals/ 

downloads/ab001860.pdf. 

As explained in the FY 2001 proposed 

rule (65 FR 19232), the amendments 

enacted in section 103 of the BBRA 

1999 not only identified for exclusion 

from this provision a number of 

particular service codes within four 

specified categories (that is, 

chemotherapy items, chemotherapy 

administration services, radioisotope 

services, and customized prosthetic 

devices), but also gave the Secretary the 

authority to designate additional, 

individual services for exclusion within 

each of these four specified service 

categories. In the proposed rule for FY 

2001, we also noted that the BBRA 1999 

Conference report (H.R. Rep. No. 106– 

479 at 854 (1999) (Conf. Rep.)) 

characterizes the individual services 

that this legislation targets for exclusion 

as high-cost, low probability events that 

could have devastating financial 

impacts because their costs far exceed 

the payment SNFs receive under the 

PPS. According to the conferees, section 

103(a) of the BBRA 1999 is an attempt 

to exclude from the PPS certain services 

and costly items that are provided 

infrequently in SNFs. By contrast, the 

amendments enacted in section 103 of 

the BBRA 1999 do not designate for 

exclusion any of the remaining services 

within those four categories (thus, 

leaving all of those services subject to 

SNF consolidated billing), because they 

are relatively inexpensive and are 

furnished routinely in SNFs. 

As we further explained in the final 

rule for FY 2001 (65 FR 46790), and as 

is consistent with our longstanding 

policy, any additional service codes that 

we might designate for exclusion under 

our discretionary authority must meet 

the same statutory criteria used in 

identifying the original codes excluded 

from consolidated billing under section 

103(a) of the BBRA 1999: They must fall 

within one of the four service categories 

specified in the BBRA 1999; and they 

also must meet the same standards of 

high cost and low probability in the 

SNF setting, as discussed in the BBRA 

1999 Conference report. Accordingly, 

we characterized this statutory authority 

to identify additional service codes for 

exclusion as essentially affording the 

flexibility to revise the list of excluded 

codes in response to changes of major 

significance that may occur over time 

(for example, the development of new 

medical technologies or other advances 

in the state of medical practice) (65 FR 

46791). 

Effective with items and services 

furnished on or after October 1, 2021, 

section 134 in Division CC of the 

Consolidated Appropriations Act, 2021 

(Pub. L. 116–260) has established an 

additional category of excluded codes in 

section 1888(e)(2)(A)(iii)(VI) of the Act, 

for certain blood clotting factors for the 

treatment of patients with hemophilia 

and other bleeding disorders along with 

items and services related to the 

furnishing of such factors under section 

1842(o)(5)(C) of the Act. The specific 

factors, and items and services related to 

the furnishing of such factors, excluded 

under this provision are those 

identified, as of July 1, 2020, by HCPCS 

codes J7170, J7175, J7177–J7183, J7185– 

J7190, J7192–J7195, J7198–J7203, J7205, 

and J7207–J7211. Like the provisions 

enacted in the BBRA 1999, new section 

1888(e)(2)(A)(iii)(VI) of the Act gives the 

Secretary the authority to designate 

additional items and services for 

exclusion within the category of items 

and services described in that section. 

Section 1888(e)(4)(G)(iii) of the Act 

further requires that for any services 

that are unbundled from consolidated 

billing under section 1888(e)(2)(A)(iii) 

of the Act (and, thus, become qualified 

for separate payment under Part B), 

there must also be a corresponding 

proportional reduction made in 

aggregate SNF payments under Part A. 

Accordingly, using the methodology 

described in section III.B.6. of the 

proposed rule (see also section IV.B.6. of 

this final rule), we proposed to make a 


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proportional reduction of $0.02 in the 

unadjusted urban and rural rates to 

reflect these new exclusions, effective 

for items and services furnished on or 

after October 1, 2021. 

In the proposed rule, we specifically 

invited public comments identifying 

HCPCS codes in any of these five 

service categories (chemotherapy items, 

chemotherapy administration services, 

radioisotope services, customized 

prosthetic devices, and blood clotting 

factors) representing recent medical 

advances that might meet our criteria for 

exclusion from SNF consolidated 

billing. We noted that we may consider 

excluding a particular service if it meets 

our criteria for exclusion as specified 

previously. We requested that 

commenters identify in their comments 

the specific HCPCS code that is 

associated with the service in question, 

as well as their rationale for requesting 

that the identified HCPCS code(s) be 

excluded. 

We noted that the original BBRA 

amendment and the Consolidated 

Appropriations Act, 2021 identified a 

set of excluded items and services by 

means of specifying individual HCPCS 

codes within the designated categories 

that were in effect as of a particular date 

(in the case of the BBRA 1999, July 1, 

1999, and in the case of the 

Consolidated Appropriations Act, 2021, 

July 1, 2020), as subsequently modified 

by the Secretary. In addition, as noted 

above, the statute (section 

1888(e)(2)(A)(iii)(II) through (VI) of the 

Act) gives the Secretary authority to 

identify additional items and services 

for exclusion within the categories of 

items and services described in the 

statute, which are also designated by 

HCPCS code. Designating the excluded 

services in this manner makes it 

possible for us to utilize program 

issuances as the vehicle for 

accomplishing routine updates to the 

excluded codes to reflect any minor 

revisions that might subsequently occur 

in the coding system itself, such as the 

assignment of a different code number 

to a service already designated as 

excluded, or the creation of a new code 

for a type of service that falls within one 

of the established exclusion categories 

and meets our criteria for exclusion (for 

example, J7212, ‘‘factor viia 

(antihemophilic factor, recombinant)- 

jncw (sevenfact), 1 microgram’’, which 

became effective on January 1, 2021 and 

would fall in the blood clotting factor 

exclusion category). 

Accordingly, we noted that in the 

event that we identify through the 

current rulemaking cycle any new 

services that would actually represent a 

substantive change in the scope of the 

exclusions from SNF consolidated 

billing, we would identify these 

additional excluded services by means 

of the HCPCS codes that are in effect as 

of a specific date (in this case, October 

1, 2021). By making any new exclusions 

in this manner, we could similarly 

accomplish routine future updates of 

these additional codes through the 

issuance of program instructions. The 

latest list of excluded codes can be 

found on the SNF Consolidated Billing 

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

Medicare/Billing/SNF

ConsolidatedBilling. 

The following is a summary of the 

public comments received on the 

proposed revisions to Consolidated 

Billing and our responses: 

Comment: Several commenters noted 

support for the exclusion of blood 

clotting factors (BCFs) and related items 

and services from consolidated billing. 

Commenters stated that the exclusion of 

these services from consolidated billing 

will increase care to beneficiaries with 

BCF disorders. 

Response: We thank these 

commenters for their support. In 

accordance with this support and the 

legislative mandate to exclude BCFs 

from consolidated billing, we are 

finalizing the exclusion of BCFs as 

proposed. 

Comment: One commenter suggested 

the addition of two HCPCS codes to the 

list of BCF-related services that are 

excluded from consolidated billing: 

J7204 (effective as of 7/1/2020) and 

J7212 (effective as of 1/1/2021). The 

commenter stated that these two J Codes 

also represent treatments for people 

with hemophilia—J7204 is for 

hemophilia A and J7212 is for 

hemophilia A or B with inhibitors. 

Response: Upon review, we agree 

with the commenter and we have 

determined that HCPCS codes J7204 and 

J7212 should be excluded from 

consolidated billing. HCPCS code J7212 

was not created until January 1, 2021, 

after Division CC, section 134 of the 

Consolidated Appropriations Act of 

2001 (CAA) (Pub. L. 116–260, enacted 

on December 27, 2000) had been 

enacted, and the statutory exclusion 

designates codes that were identified as 

of July 1, 2020. HCPCS code J7204 was 

added on July 1, 2020; by contrast, the 

immediately adjacent codes of J7203 

and J7205 had already been added much 

earlier, in 2019 and 2016, respectively. 

Accordingly, HCPCS codes J7204 and 

J7212 were not included in the statutory 

code range provided in the 

aforementioned legislation. However, as 

we stated in the proposed rule, section 

1888(e)(2)(A)(iii) (VI) of the Act gives 

the Secretary authority to identify any 

additional blood clotting factors for 

exclusion. We further stated that we 

will utilize program issuances as the 

vehicle for making such routine updates 

to the list of excluded codes. In fact, we 

used J7212 as an example of a new code 

that we would designate through the 

issuance of program instructions. 

Accordingly, the new exclusions for 

HCPCS codes J7204 and J7212 will 

appear in a forthcoming consolidated 

billing update, with an effective date of 

October 1, 2021, the date that the 

statutory exclusion for BCFs takes effect. 

Comment: One commenter requested 

us to consider a particular 

chemotherapy drug, RIABNITM

(rituximab-arrx), HCPCS code Q5123, 

that the commenter recommended as 

meeting the criteria for exclusion from 

consolidated billing. The commenter 

stated the drug meets the ‘‘high-cost, 

low probability’’ criteria for exclusion, 

represents a change in medical 

technology, and already has its own 

HCPCS code. 

Response: We agree with the 

commenter and have determined that 

the drug described by HCPCS code 

Q5123 does qualify for exclusion. Its 

cost is comparable to other excluded 

chemotherapy drugs and it is rarely 

administered to SNF inpatients. Thus, it 

meets the ‘‘high-cost, low probability’’ 

standard in the SNF setting, as 

discussed in the BBRA 1999 Conf. 

Report. Furthermore, since it is a newly 

assigned code, the omission of this 

particular code from the original 

statutory code range would not indicate 

an intent for it to remain bundled. 

Accordingly, this new exclusion will 

appear in a forthcoming consolidated 

billing update. 

Comment: One commenter 

encouraged CMS to exclude 

erythropoietin (EPO) when given for 

non-dialysis use. The commenter stated 

that currently CMS excludes 

erythropoietin (EPO) when given for 

dialysis, but not for other uses. 

Response: We note that we have 

responded previously to comments 

regarding the use of EPO for nondialysis purposes, including in the FY 

2004 (68 FR 46059–62, August 4, 2003), 

FY 2006 (70 FR 45048–50, August 4, 

2005), and FY 2008 (72 FR 43430–32, 

August 3, 2007) final rules. As we have 

noted previously in this final rule and 

in previous responses to comments on 

this issue in the past, section 

1888(e)(2)(A)(iii) of the Act authorizes 

us to identify additional services for 

exclusion only within those particular 

service categories that it has designated 

for this purpose, and does not give us 

the authority to exclude other services 

which, though they may be related, fall 


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outside of the specified service 

categories themselves. Thus, while antiemetics, for example, are commonly 

administered in conjunction with 

chemotherapy, they are not themselves 

inherently chemotherapeutic in nature 

and, consequently, do not fall within 

the excluded chemotherapy category 

designated in the section 

1888(e)(2)(A)(iii)(II) of the Act. With 

regard to EPO, we additionally note that 

among the service categories that 

section 1888(e)(2)(A)(ii) of the Act 

already specifies as being excluded from 

SNF consolidated billing are items and 

services described in section 

1861(s)(2)(O) of the Act—that is, EPO 

that is furnished to dialysis patients 

competent to use the such drug without 

medical or other supervision, and does 

not provide for coverage in any other, 

non-dialysis situations, such as 

chemotherapy. This means the 

exclusion under the consolidated billing 

provision for EPO falls within this 

scope. 

Comment: One commenter reiterated 

the same set of comments that they had 

submitted in previous rulemaking 

cycles, noting the importance of 

continuing to exclude certain 

customized prosthetic devices from 

consolidated billing, and urging the 

exclusion of orthotics as well. The 

commenter also recommended the 

following four HCPCS codes for 

exclusion: L5000—Partial foot, shoe 

insert with longitudinal arch, toe filler; 

L5010—Partial foot, molded socket, 

ankle height, with toe filler; L5020— 

Partial foot, molded socket, tibial 

tubercle height, with toe filler; and 

L5987—All lower extremity prosthesis, 

shank foot system with vertical loading 

pylon. 

Response: We refer to the previous 

discussions in the FY 2018 SNF PPS 

final rule (82 FR 36547) and FY 2017 

SNF PPS final rule (81 FR 51986, 

August 5, 2016) regarding our decision 

not to adopt the recommendations for 

excluding orthotics as a class along with 

prosthetic codes L5010, L5020, and 

L5987. As we explained, it is our 

longstanding position that if a particular 

prosthetic code was already in existence 

as of the BBRA enactment date but was 

not designated in the BBRA for 

exclusion, this meant that it was 

intended to remain within the SNF PPS 

bundle. This would apply to all four of 

the prosthetic codes (L5000, L5010, 

L5020, and L5987) cited in the current 

comment. 

Comment: One commenter 

encouraged CMS to address whether 

monoclonal antibody infusions for 

treatment of COVID–19 will be excluded 

from consolidated billing after the end 

of the COVID–19 PHE, to continue 

efforts to combat the infection in 

facilities. 

Response: We appreciate the 

commenter’s concern. However, as 

previously described in this rule, 

section 1888(e)(2)(A) of the Act 

authorizes us to identify additional 

services for exclusion from the 

consolidated billing requirements only 

within those particular service 

categories that it has designated for this 

purpose, and does not give us the 

authority to exclude other services 

which fall outside of the specified 

service categories themselves. 

Monoclonal antibody infusions do not 

fall within one of the specified service 

categories. 

C. Payment for SNF-Level Swing-Bed 

Services 

Section 1883 of the Act permits 

certain small, rural hospitals to enter 

into a Medicare swing-bed agreement, 

under which the hospital can use its 

beds to provide either acute- or SNFlevel care, as needed. For critical access 

hospitals (CAHs), Part A pays on a 

reasonable cost basis for SNF-level 

services furnished under a swing-bed 

agreement. However, in accordance 

with section 1888(e)(7) of the Act, SNFlevel services furnished by non-CAH 

rural hospitals are paid under the SNF 

PPS, effective with cost reporting 

periods beginning on or after July 1, 

2002. As explained in the FY 2002 final 

rule (66 FR 39562), this effective date is 

consistent with the statutory provision 

to integrate swing-bed rural hospitals 

into the SNF PPS by the end of the 

transition period, June 30, 2002. 

Accordingly, all non-CAH swing-bed 

rural hospitals have now come under 

the SNF PPS. Therefore, all rates and 

wage indexes outlined in earlier 

sections of this final rule for the SNF 

PPS also apply to all non-CAH swingbed rural hospitals. As finalized in the 

FY 2010 SNF PPS final rule (74 FR 

40356 through 40357), effective October 

1, 2010, non-CAH swing-bed rural 

hospitals are required to complete an 

MDS 3.0 swing-bed assessment which is 

limited to the required demographic, 

payment, and quality items. As 

discussed in the FY 2019 SNF PPS final 

rule (83 FR 39235), revisions were made 

to the swing bed assessment to support 

implementation of PDPM, effective 

October 1, 2019. A discussion of the 

assessment schedule and the MDS 

effective beginning FY 2020 appears in 

the FY 2019 SNF PPS final rule (83 FR 

39229 through 39237). The latest 

changes in the MDS for swing-bed rural 

hospitals appear on the SNF PPS 

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

Medicare/Medicare-Fee-for-ServicePayment/SNFPPS/index.html. 

D. Revisions to the Regulation Text 

In the proposed rule, we proposed to 

make certain revisions in the regulation 

text itself. Specifically, we proposed to 

redesignate current 42 CFR 

411.15(p)(2)(xvii) and 489.20(s)(17) to 

§§ 411.15(p)(2)(xviii) and 489.20(s)(18), 

respectively, and to update the 

regulation text at §§ 411.15(p)(2)(xvii) 

and 489.20(s)(17) to reflect the recentlyenacted exclusion from SNF 

consolidated billing at section 

1888(e)(2)(A)(iii)(VI) of the Act effective 

for items and services furnished on or 

after October 1, 2021. Specifically, 

proposed revised §§ 411.15(p)(2)(xvii) 

and 489.20(s)(17) would reflect the 

exclusion of certain blood clotting 

factors for the treatment of patients with 

hemophilia and other bleeding 

disorders (identified by designated 

HCPCS codes in effect as of July 1, 2020, 

as subsequently modified by CMS), and 

items and services related to the 

furnishing of such factors, and would 

allow for the exclusion of any additional 

blood clotting factors identified by CMS 

and items and services related to the 

furnishing of such factors. In addition, 

we proposed to make conforming 

changes to the regulation text at 

§§ 411.15(p)(2)(xiii) through (xvi) and 

489.20(s)(13) through (16) to reflect the 

authority that has always existed for 

CMS to make updates to the list of 

excluded codes as provided in section 

1888(e)(2)(A)(iii)(II) through (V) of the 

Act, and as discussed in section IV.C. of 

the proposed rule. 

The following is a summary of the 

public comment received on the 

proposed revisions to the regulation text 

and our response: 

Comment: One commenter noted 

support for the regulation text revisions. 

Response: We thank the commenter 

for their support. We did not receive 

any other comments on the proposed 

revisions to the regulation text, and 

therefore, we are finalizing the revisions 

as proposed. 

VI. Other SNF PPS Issues 

A. Rebasing and Revising the SNF 

Market Basket 

Section 1888(e)(5)(A) of the Act 

requires the Secretary to establish a 

market basket index that reflects the 

changes over time in the prices of an 

appropriate mix of goods and services 

included in covered SNF services. 

Accordingly, we have developed a SNF 

market basket index that encompasses 

the most commonly used cost categories 

for SNF routine services, ancillary 


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services, and capital-related expenses. 

We use the SNF market basket index, 

adjusted in the manner described in 

section III.B. of this final rule, to update 

the SNF PPS per diem rates and to 

determine the labor-related share on an 

annual basis. 

The SNF market basket is a fixedweight, Laspeyres-type price index. A 

Laspeyres price index measures the 

change in price, over time, of the same 

mix of goods and services purchased in 

the base period. Any changes in the 

quantity or mix of goods and services 

(that is, intensity) purchased over time 

relative to a base period are not 

measured. 

The index itself is constructed in 

three steps. First, a base period is 

selected (the base period is 2018) and 

total base period expenditures are 

estimated for a set of mutually exclusive 

and exhaustive spending categories and 

the proportion of total costs that each 

category represents is calculated. These 

proportions are called cost or 

expenditure weights. Second, each 

expenditure category is matched to an 

appropriate price or wage variable, 

referred to as a price proxy. In nearly 

every instance, these price proxies are 

derived from publicly available 

statistical series that are published on a 

consistent schedule (preferably at least 

on a quarterly basis). Finally, the 

expenditure weight for each cost 

category is multiplied by the level of its 

respective price proxy. The sum of these 

products (that is, the expenditure 

weights multiplied by their price levels) 

for all cost categories yields the 

composite index level of the market 

basket in a given period. Repeating this 

step for other periods produces a series 

of market basket levels over time. 

Dividing an index level for a given 

period by an index level for an earlier 

period produces a rate of growth in the 

input price index over that timeframe. 

Effective for cost reporting periods 

beginning on or after July 1, 1998, we 

revised and rebased our 1977 routine 

costs input price index and adopted a 

total expenses SNF input price index 

using FY 1992 as the base year. In the 

FY 2002 SNF PPS final rule (66 FR 

39582), we rebased and revised the 

market basket to a base year of FY 1997. 

In the FY 2008 SNF PPS final rule (72 

FR 43425), we rebased and revised the 

market basket to a base year of FY 2004. 

In the FY 2014 SNF PPS final rule (78 

FR 47939), we revised and rebased the 

SNF market basket, which included 

updating the base year from FY 2004 to 

FY 2010. Lastly, in the FY 2018 SNF 

PPS final rule (82 FR 36548), we revised 

and rebased the SNF market basket, 

which included updating the base year 

from FY 2010 to FY 2014. In the FY 

2022 SNF PPS proposed rule (86 FR 

19969 through 19984) we proposed to 

rebase and revise the market basket 

updating the base year from 2014 to 

2018. Below is our methodology, as well 

as responses to comments. 

Effective for FY 2022 and subsequent 

fiscal years, we will rebase and revise 

the market basket to reflect 2018 

Medicare-allowable total cost data 

(routine, ancillary, and capital-related) 

from freestanding SNFs and to revise 

applicable cost categories and price 

proxies used to determine the market 

basket. Medicare-allowable costs are 

those costs that are eligible to be paid 

under the SNF PPS. For example, the 

SNF market basket excludes home 

health agency (HHA) costs as these costs 

would be paid under the HHA PPS, and 

therefore, these costs are not SNF PPS 

Medicare-allowable costs. We will 

maintain our policy of using data from 

freestanding SNFs, which represent 

about 93 percent of the total SNFs 

shown in Table 12. We believe using 

freestanding Medicare cost report (MCR) 

data, as opposed to the hospital-based 

SNF MCR data, for the cost weight 

calculation is most appropriate because 

of the complexity of hospital-based data 

and the representativeness of the 

freestanding data. Because hospitalbased SNF expenses are embedded in 

the hospital cost report, any attempt to 

incorporate data from hospital-based 

facilities requires more complex 

calculations and assumptions regarding 

the ancillary costs related to the 

hospital-based SNF unit. We believe the 

use of freestanding SNF cost report data 

is technically appropriate for reflecting 

the cost structures of SNFs serving 

Medicare beneficiaries. 

We will use 2018 as the base year as 

we believe that the 2018 MCRs 

represent the most recent, complete set 

of MCR data available to develop cost 

weights for SNFs at the time of 

rulemaking. We believe it is important 

to regularly rebase and revise the SNF 

market to reflect more recent data. 

Historically, the cost weights change 

minimally from year to year as they 

represent percent of total costs rather 

than cost levels; however, given the 

COVID–19 PHE, we will continue to 

monitor the upcoming MCR data to see 

if a more frequent rebasing schedule is 

necessary than our recent historical 

precedent of about every 4 years. The 

2018 Medicare cost reports are for cost 

reporting periods beginning on and after 

October 1, 2017 and before October 1, 

2018. While these dates appear to reflect 

fiscal year data, we note that a Medicare 

cost report that begins in this timeframe 

is generally classified as a ‘‘2018 cost 

report’’. For example, we found that of 

the available 2018 Medicare cost reports 

for SNFs, approximately 7 percent had 

an October 1, 2017 begin date, 

approximately 70 percent of the reports 

had a January 1, 2018 begin date, and 

approximately 12 percent had a July 1, 

2018 begin date. For this reason, we are 

defining the base year of the market 

basket as ‘‘2018-based’’ instead of ‘‘FY 

2018-based’’. 

Comment: Several commenters 

supported the rebasing and revising of 

the market basket, stating that a relevant 

market basket is a fundamental 

requirement for a well-functioning PPS. 

One commenter appreciated the 

proposed rebasing and revising of the 

SNF market basket as proposed and 

further stated that the use of the 2018 

data is more reflective of current costs 

of providing services compared to 2014 

data. Several commenters also 

supported CMS’ plans to monitor and 

revise and rebase more frequently. 

Response: We appreciate the 

commenters’ support of the rebasing 

and revising of the SNF market basket 

and note that we plan to review the 

2020 Medicare cost report data as soon 

as complete information is available to 

assess any impact of the PHE on the 

market basket relative cost shares. Any 

changes to the market basket would be 

proposed in rulemaking and will be 

subject to public comments. 

We proposed to develop cost category 

weights for the 2018-based SNF market 

basket in two stages. First, we proposed 

to derive eight major expenditures or 

cost weights from the 2018 MCR data 

(CMS Form 2540–10, OMB NO. 0938– 

0463) for freestanding SNFs: Wages and 

Salaries; Employee Benefits; Contract 

Labor; Pharmaceuticals; Professional 

Liability Insurance; Home Office/ 

Related Organization Contract Labor; 

Capital-related; and a residual ‘‘All 

Other’’. These are the same cost 

categories calculated using the 2014 

MCR data for the 2014-based SNF 

market basket. The residual ‘‘All Other’’ 

category would reflect all remaining 

costs that are not captured in the other 

seven cost categories. Second, we 

proposed to divide the residual ‘‘All 

Other’’ cost category into more detailed 

subcategories, using U.S. Department of 

Commerce Bureau of Economic 

Analysis’ (BEA) 2012 Benchmark InputOutput (I–O) ‘‘use table before 

redefinitions, purchaser’s value’’ for the 

Nursing and Community Care Facilities 

industry (NAICS 623A00) aged to 2018 

using applicable price proxy growth for 

each category of costs. Furthermore, we 

proposed to continue to use the same 

overall methodology as was used for the 

2014-based SNF market basket to 


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develop the capital related cost weights 

of the 2018-based SNF market basket. 

1. Development of Cost Categories and 

Weights 

a. Use of Medicare Cost Report Data To 

Develop Major Cost Weights 

In order to create a market basket that 

is representative of freestanding SNF 

providers serving Medicare patients and 

to help ensure accurate major cost 

weights (which is the percent of total 

Medicare-allowable costs, as defined 

below), we proposed to apply edits to 

remove reporting errors and outliers. 

Specifically, the SNF MCRs used to 

calculate the market basket cost weights 

exclude any providers that reported 

costs less than or equal to zero for the 

following categories: Total facility costs 

(Worksheet B, part 1, column 18, line 

100); total operating costs (Worksheet B, 

part 1, column 18, line 100 less 

Worksheet B, part 2, column 18, line 

100); Medicare general inpatient routine 

service costs (Worksheet D, part 1, 

column 1, line 1); and Medicare PPS 

payments (Worksheet E, part 3, column 

1, line 1). We also limited our sample 

to providers that had a MCR reporting 

period that was between 10 and 14 

months. The final sample used included 

roughly 13,500 MCRs (about 90 percent 

of the universe of SNF MCRs for 2018). 

The sample of providers is 

representative of the national universe 

of providers by region, by ownershiptype (proprietary, nonprofit, and 

government), and by urban/rural status. 

Additionally, for all of the major cost 

weights, except Home Office/Related 

Organization Contract Labor costs, the 

data are trimmed to remove outliers (a 

standard statistical process) by: (1) 

Requiring that major expenses (such as 

Wages and Salaries costs) and total 

Medicare-allowable costs are greater 

than zero; and (2) excluding the top and 

bottom 5 percent of the major cost 

weight (for example, Wages and Salaries 

costs as a percent of total Medicareallowable costs). We note that missing 

values are assumed to be zero, 

consistent with the methodology for 

how missing values are treated in the 

2014-based market basket methodology. 

For the Home Office/Related 

Organization Contract Labor cost 

weight, we proposed to first exclude 

providers whose Home Office/Related 

Organization Contract Labor costs are 

greater than Medicare-allowable total 

costs and then apply a trim that 

excludes those reporters with a Home 

Office/Related Organization Contract 

Labor cost weight above the 99th 

percentile. This allows providers with 

no Home Office/Related Organization 

Contract Labor costs to be included in 

the Home Office/Related Organization 

Contract Labor cost weight calculation . 

If we were to trim the top and bottom 

Home Office/Related Organization 

Contract Labor cost weight, we would 

exclude providers with a zero cost 

weight and the MCR data (Worksheet 

S–2 line 45) indicate that not all SNF 

providers have a home office. Providers 

without a home office would report 

administrative costs that might typically 

be associated with a home office in the 

Wages and Salaries and Employee 

Benefits cost weights, or in the residual 

‘‘All-Other’’ cost weight if they 

purchased these types of services from 

external contractors. We believe the 

trimming methodology that excludes 

those who report Home Office costs 

above the 99th percentile is appropriate 

as it removes extreme outliers while 

also allowing providers with zero Home 

Office/Related Organization Contract 

Labor costs to be included in the Home 

Office/Related Organization Contract 

Labor cost weight calculation. 

The trimming process is done 

individually for each cost category so 

that providers excluded from one cost 

weight calculation are not automatically 

excluded from another cost weight 

calculation. We note that these 

trimming methods are the same types of 

edits performed for the 2014-based SNF 

market basket, as well as other PPS 

market baskets (including but not 

limited to the IPPS market basket and 

HHA market basket). We believe this 

trimming process improves the accuracy 

of the data used to compute the major 

cost weights by removing possible data 

misreporting. 

The final weights of the 2018-based 

SNF market basket are based on 

weighted means. For example, the 

aggregate Wages and Salaries cost 

weight, after trimming, is equal to the 

sum of total Medicare-allowable wages 

and salaries of all providers divided by 

the sum of total Medicare-allowable 

costs for all providers in the sample. 

This methodology is consistent with the 

methodology used to calculate the 2014- 

based SNF market basket cost weights 

and other PPS market basket cost 

weights. We note that for each of the 

cost weights, we evaluated the 

distribution of providers and costs by 

region, by ownership-type, and by 

urban/rural status. For all of the cost 

weights, with the exception of the PLI 

(which is discussed in more detail 

later), the trimmed sample was 

nationally representative. 

For all of the cost weights, we use 

Medicare-allowable total costs as the 

denominator (for example, Wages and 

Salaries cost weight = Wages and 

Salaries costs divided by Medicareallowable total costs). Medicareallowable total costs were equal to total 

costs (after overhead allocation) from 

Worksheet B part I, column 18, for lines 

30, 40 through 49, 51, 52, and 71 plus 

estimated Medicaid drug costs, as 

defined below. We included estimated 

Medicaid drug costs in the pharmacy 

cost weight, as well as the denominator 

for total Medicare-allowable costs. This 

is the same methodology used for the 

2014-based SNF market basket. The 

inclusion of Medicaid drug costs was 

finalized in the FY 2008 SNF PPS final 

rule (72 FR 43425 through 43430), and 

for the same reasons set forth in that 

final rule, we proposed to continue to 

use this methodology in the 2018-based 

SNF market basket. 

We describe the detailed methodology 

for obtaining costs for each of the eight 

cost categories determined from the 

Medicare Cost Report below. The 

methodology used in the 2014-based 

SNF market basket can be found in the 

FY 2018 SNF PPS final rule (82 FR 

36548 through 36555). 

(1) Wages and Salaries: To derive 

Wages and Salaries costs for the 

Medicare-allowable cost centers, we 

proposed first to calculate total facility 

wages and salaries costs as reported on 

Worksheet S–3, part II, column 3, line 

1. We then proposed to remove the 

wages and salaries attributable to nonMedicare-allowable cost centers (that is, 

excluded areas), as well as a portion of 

overhead wages and salaries attributable 

to these excluded areas. Excluded area 

wages and salaries are equal to wages 

and salaries as reported on Worksheet 

S–3, part II, column 3, lines 3, 4, and 7 

through 11 plus nursing facility and 

non-reimbursable salaries from 

Worksheet A, column 1, lines 31, 32, 50, 

and 60 through 63. 

Overhead wages and salaries are 

attributable to the entire SNF facility; 

therefore, we proposed to include only 

the proportion attributable to the 

Medicare-allowable cost centers. We 

proposed to estimate the proportion of 

overhead wages and salaries attributable 

to the non-Medicare-allowable costs 

centers in two steps. First, we proposed 

to estimate the ratio of excluded area 

wages and salaries (as defined above) to 

non-overhead total facility wages and 

salaries (total facility wages and salaries 

(Worksheet S–3, part II, column 3, line 

1) less total overhead wages and salaries 

(Worksheet S–3, Part III, column 3, line 

14)). Next, we proposed to multiply 

total overhead wages and salaries by the 

ratio computed in step 1. We excluded 

providers whose excluded areas wages 

and salaries were greater than total 

facility wages and salaries and/or their 


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excluded area overhead wages and 

salaries were greater than total facility 

wages and salaries (about 50 providers). 

This is similar to the methodology used 

to derive Wages and Salaries costs in the 

2014-based SNF market basket. For the 

2014-based SNF market basket, we 

estimated the proportion of overhead 

wages and salaries that is attributable to 

the non-Medicare allowable costs 

centers (that is, excluded areas) by 

multiplying the ratio of excluded area 

wages and salaries (as defined above) to 

total wages and salaries as reported on 

Worksheet S–3, Part II, column 3, line 

1 by total overhead wages and salaries 

as reported on Worksheet S–3, Part III, 

column 3, line 14. 

(2) Employee Benefits: Medicareallowable employee benefits are equal to 

total facility benefits as reported on 

Worksheet S–3, part II, column 3, lines 

17 through 19 minus non-Medicareallowable (that is, excluded area) 

employee benefits and minus a portion 

of overhead benefits attributable to these 

excluded areas. Excluded area employee 

benefits are derived by multiplying total 

excluded area wages and salaries (as 

defined above in the ‘Wages and 

Salaries’ section) times the ratio of total 

facility benefits to total facility wages 

and salaries. This ratio of benefits to 

wages and salaries is defined as total 

facility benefit costs to total facility 

wages and salary costs (as reported on 

Worksheet S–3, part II, column 3, line 

1). Likewise, the portion of overhead 

benefits attributable to the excluded 

areas is derived by multiplying 

overhead wages and salaries attributable 

to the excluded areas (as defined in the 

‘Wages and Salaries’ section) times the 

ratio of total facility benefit costs to total 

facility wages and salary costs (as 

defined above). Similar to the Wages 

and Salaries cost weight, we excluded 

providers whose excluded areas benefits 

were greater than total facility benefits 

and/or their excluded area overhead 

benefits were greater than total facility 

benefits (zero providers were excluded 

because of this edit). This is similar to 

the methodology used to derive 

Employee Benefits costs in the 2014- 

based SNF market basket. 

(3) Contract Labor: We proposed to 

derive Medicare-allowable contract 

labor costs from Worksheet S–3, part II, 

column 3, line 14, which reflects costs 

for contracted direct patient care 

services (that is, nursing, therapeutic, 

rehabilitative, or diagnostic services 

furnished under contract rather than by 

employees and management contract 

services). This is the same methodology 

used to derive the Contract Labor costs 

in the 2014-based SNF market basket. 

(4) Pharmaceuticals: We proposed to 

calculate pharmaceuticals costs using 

the non-salary costs from the Pharmacy 

cost center (Worksheet B, part I, column 

0, line 11 less Worksheet A, column 1, 

line 11) and the Drugs Charged to 

Patients’ cost center (Worksheet B, part 

I, column 0, line 49 less Worksheet A, 

column 1, line 49). Since these drug 

costs were attributable to the entire SNF 

and not limited to Medicare-allowable 

services, we proposed to adjust the drug 

costs by the ratio of Medicare-allowable 

pharmacy total costs (Worksheet B, part 

I, column 11, for lines 30, 40 through 

49, 51, 52, and 71) to total pharmacy 

costs from Worksheet B, part I, column 

11, line 11. Worksheet B, part I allocates 

the general service cost centers, which 

are often referred to as ‘‘overhead costs’’ 

(in which pharmacy costs are included) 

to the Medicare-allowable and nonMedicare-allowable cost centers. This 

adjustment was made for those 

providers who reported Pharmacy cost 

center expenses. Otherwise, we 

assumed the non-salary Drugs Charged 

to Patients costs were Medicareallowable. Since drug costs for Medicare 

patients are included in the SNF PPS 

per diem rate, a provider with Medicare 

days should have also reported costs in 

the Drugs Charged to Patient cost center. 

We found a small number of providers 

(roughly 60) did not report Drugs 

Charged to Patients’ costs despite 

reporting Medicare days (an average of 

about 2,600 Medicare days per 

provider), and therefore, these providers 

were excluded from the 

Pharmaceuticals cost weight 

calculations. This is similar to the 

methodology used for the 2014-based 

SNF market basket. 

Second, as was done for the 2014- 

based SNF market basket, we proposed 

to continue to adjust the drug expenses 

reported on the MCR to include an 

estimate of total Medicaid drug costs, 

which are not represented in the 

Medicare-allowable drug cost weight. 

As stated previously in this section, the 

2018-based SNF market basket reflects 

total Medicare-allowable costs (that is, 

total costs for all payers for those 

services reimbursable under the SNF 

PPS). For the FY 2006-based SNF 

market basket (72 FR 43426), 

commenters noted that the total 

pharmaceutical costs reported on the 

MCR did not include pharmaceutical 

costs for dual-eligible Medicaid patients 

as these were directly reimbursed by 

Medicaid. Since all of the other cost 

category weights reflect expenses 

associated with treating Medicaid 

patients (including the compensation 

costs for dispensing these drugs), we 

made an adjustment to include these 

Medicaid drug expenses so the market 

basket cost weights would be calculated 

consistently. 

Similar to the 2014-based SNF market 

basket, we proposed to estimate 

Medicaid drug costs based on data 

representing dual-eligible Medicaid 

beneficiaries. Medicaid drug costs are 

estimated by multiplying Medicaid 

dual-eligible drug costs per day times 

the number of Medicaid days as 

reported in the Medicare-allowable 

skilled nursing cost center (Worksheet 

S–3, part I, column 5, line 1) in the SNF 

MCR. Medicaid dual-eligible drug costs 

per day (where the day represents an 

unduplicated drug supply day) were 

estimated using 2018 Part D claims for 

those dual-eligible beneficiaries who 

had a Medicare SNF stay during the 

year. The total drug costs per 

unduplicated day for 2018 of $24.48 

represented all drug costs (including the 

drug ingredient cost, the dispensing fee, 

vaccine administration fee and sales tax) 

incurred during the 2018 calendar year 

for those dual-eligible beneficiaries who 

had a SNF Medicare stay during that 

2018 calendar year. Therefore, they 

include drug costs incurred during a 

Medicaid SNF stay occurring in the 

2018 calendar year. By comparison, the 

2014-based SNF market basket also 

relied on data from the Part D claims, 

which yielded a dual-eligible Medicaid 

drug cost per day of $19.62 for 2014. 

We continue to believe that Medicaid 

dual-eligible beneficiaries are a 

reasonable proxy for the estimated drug 

costs per day incurred by Medicaid 

patients staying in a skilled nursing unit 

under a Medicaid stay. The skilled 

nursing unit is the Medicare-allowable 

unit in a SNF, which encompasses more 

skilled nursing and rehabilitative care 

compared to a nursing facility or longterm care unit. We believe that 

Medicaid patients receiving this skilled 

nursing care would on average have 

similar drug costs per day to dualeligible Medicare beneficiaries who 

have received Medicare skilled nursing 

care in the skilled nursing care unit 

during the year. We note that our 

previous analysis of the Part D claims 

data showed that Medicare beneficiaries 

with a SNF stay during the year have 

higher drug costs than Medicare 

patients without a SNF stay during the 

year. Also, in 2018, dual-eligible 

beneficiaries with a SNF stay during the 

year had drug costs per day of $24.48, 

which were approximately two times 

higher than the drug costs per day of 

$13.19 for nondual-eligible beneficiaries 

with a SNF Part A stay during the year. 

The Pharmaceuticals cost weight 

using only 2018 MCR data (without the 


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2https://www.aon.com/risk-services/thoughtleadership/report-2018-long-term-care.jsp. 

inclusion of the Medicaid dual-eligible 

drug costs) is 2.6 percent, compared to 

the proposed Pharmaceuticals cost 

weight (including the adjustment for 

Medicaid dual-eligible drug costs) of 7.5 

percent. The 2014-based SNF market 

basket had a Pharmaceuticals cost 

weight using only 2014 MCR data 

without the inclusion of the Medicaid 

dual-eligible drug costs of 2.9 percent 

and a total Pharmaceuticals cost weight 

of 7.3 percent. Therefore, the 0.2 

percentage point increase in the 

Pharmaceuticals cost weight is a result 

of a 0.5-percentage point increase in the 

Medicaid dual-eligible drug cost weight 

(reflecting the 25 percent increase in the 

Medicaid dual-eligible drug costs per 

day between 2014 and 2018) and a 0.3- 

percentage point decrease in the MCR 

drug cost weight. The decrease in the 

MCR drug cost weight was consistent, in 

aggregate, across urban and rural status 

SNFs as well as across for-profit, 

government, and nonprofit ownership 

type SNFs. 

(5) Professional Liability Insurance: 

We proposed to calculate the 

professional liability insurance (PLI) 

costs from Worksheet S–2 of the MCRs 

as the sum of premiums; paid losses; 

and self-insurance (Worksheet S–2, Part 

I, columns 1 through 3, line 41). This 

was the same methodology used to 

derive the Professional Liability costs 

for the 2014-based SNF market basket. 

About 60 percent of SNFs (about 

8,000) reported professional liability 

costs. After trimming, about 7,200 

(reflecting about 850,000 Skilled 

Nursing unit beds) were included in the 

calculation of the PLI cost weight for the 

2018-based SNF market basket. These 

providers treated roughly 870,000 

Medicare beneficiaries and had a 

Medicare length of stay (LOS) of 33 

days, a skilled nursing unit occupancy 

rate of 80 percent, and an average 

skilled nursing unit bed size of 125 

beds, which are all consistent with the 

national averages. We also verified that 

this sample of providers are 

representative of the national 

distribution of providers by ownershiptype and urban/rural status. We note 

that the sample of providers is less 

consistent with the national distribution 

of providers by region; however, we 

performed a sensitivity analysis where 

the PLI cost weight was reweighted 

based on the national regional 

distribution and the impacts were less 

than a 0.1 percentage point on the cost 

weight. 

We note that based on prior 

comments during the rebasing of the 

2014-based SNF market basket, we 

reviewed in detail the AON 2018 

Professional and General Liability 

Benchmark for Long Term Care 

Providers 2 that examines professional 

liability and general liability claim costs 

for long term care providers (including 

skilled nursing facility beds as well as 

independent living, assisted living, 

home health care, and rehabilitation 

facilities, representing about 186,000 

long term care beds). This study, 

although informative, was not 

appropriate for calculating a PLI cost 

weight as it represents more than just 

SNFs serving Medicare patients and 

captures claim losses as opposed to PLI 

costs (premiums, paid losses, and selfinsurance) incurred during a cost 

reporting year. We note that only 13 

percent of providers reported PLI paid 

losses or PLI self-insurance costs on the 

MCR while over 90 percent of providers 

reported PLI premiums indicating that 

the majority of losses incurred by 

Medicare participating SNFs will be 

covered by insurance premiums paid 

over time. Our comparison of the MCR 

data to the AON study for those select 

states’ data provided did show 

consistencies between the average state 

PLI costs per bed relative to the national 

average (as measured by the MCR) and 

AON’s loss per occupied bed relative to 

national values indicating that states 

with higher losses per occupied bed 

have higher PLI costs per total bed. 

We believe the MCR data continues to 

be the most appropriate data source to 

calculate the PLI cost weight for the 

2018-based SNF market basket as it is 

representative of SNFs serving Medicare 

beneficiaries and reflects PLI costs 

(premiums, paid losses, and selfinsurance) incurred during the 

provider’s cost reporting year. 

(6) Capital-Related: We proposed to 

derive the Medicare-allowable capitalrelated costs from Worksheet B, part II, 

column 18 for lines 30, 40 through 49, 

51, 52, and 71. This is the same 

methodology to derive capital-related 

costs used in the 2014-based SNF 

market basket. 

(7) Home Office/Related Organization 

Contract Labor Costs: We proposed to 

calculate Medicare-allowable Home 

Office/Related Organization Contract 

Labor costs to be equal to data reported 

on Worksheet S–3, part II, column 3, 

line 16. We note that for the 2014-based 

SNF market basket we also used 

Worksheet S–3, part II, column 3, line 

16 (Home office salaries & wage related 

costs) to determine these expenses; 

however, we referred to this category as 

Home Office Contract Labor Costs. The 

instructions for this data state ‘‘enter the 

salaries and wage related costs (as 

defined on lines 17 and 18 below) paid 

to personnel who are affiliated with a 

home office and/or related organization, 

who provide services to the SNF and/or 

NF, and whose salaries are not included 

on Worksheet A, column 1,’’ and 

therefore, we are referring to this cost 

category as Home Office/Related 

Organization Contract Labor costs. 

Furthermore, for this rebasing we no 

longer adjusted these expenses by the 

ratio of Medicare allowable operating 

costs to total facility operating costs as 

done for the 2014-based SNF market 

basket as the instructions indicate these 

expenses are for the SNF and NF units. 

About 7,000 providers (about 53 

percent) in 2018 reported having a home 

office (as reported on Worksheet S–2, 

part I, line 45); a lower share of 

providers than those in the 2014-based 

SNF market basket. As discussed in 

section VI.A.1. of this final rule, 

providers without a home office can 

incur these expenses directly by having 

their own staff, for which the costs 

would be included in the Wages and 

Salaries and Employee Benefits cost 

weights. Alternatively, providers 

without a home office could also 

purchase related services from external 

contractors for which these expenses 

would be captured in the residual ‘‘AllOther’’ cost weight. For this reason, 

unlike the other major cost weights 

described previously, we did not 

exclude providers that did not report 

Home Office/Related Organization 

Contract Labor costs. We note that this 

is similar to the methodology that was 

used for other PPS market baskets such 

as the 2017-based LTCH market basket 

(85 FR 58911). 

(8) All Other (residual): The ‘‘All 

Other’’ cost weight is a residual, 

calculated by subtracting the major cost 

weights (Wages and Salaries, Employee 

Benefits, Contract Labor, 

Pharmaceuticals, Professional Liability 

Insurance, Capital-Related, and Home 

Office/Related Organization Contract 

Labor) from 100. 

Table 12 shows the major cost 

categories and their respective cost 

weights as derived from the 2018 

Medicare cost reports. 


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3http://www.bea.gov/papers/pdf/IOmanual_

092906.pdf. 

Compared to the 2014-based SNF 

market basket, the Wages and Salaries 

cost weight and the Employee Benefits 

cost weight as calculated directly from 

the Medicare cost reports decreased by 

0.2 percentage point and 0.7 percentage 

point, respectively. The Contract Labor 

cost weight increased 0.7 percentage 

point and so in aggregate, the 

Compensation cost weight decreased 0.2 

percentage point. 

As we did for the 2014-based SNF 

market basket (82 FR 36555), we 

proposed to allocate contract labor costs 

to the Wages and Salaries and Employee 

Benefits cost weights based on their 

relative proportions under the 

assumption that contract labor costs are 

comprised of both wages and salaries 

and employee benefits. The contract 

labor allocation proportion for wages 

and salaries is equal to the Wages and 

Salaries cost weight as a percent of the 

sum of the Wages and Salaries cost 

weight and the Employee Benefits cost 

weight. Using the 2018 Medicare cost 

report data, this percentage is 84 percent 

(1 percentage point higher than the 

percent in the 2014-based SNF market 

basket); therefore, we proposed to 

allocate approximately 84 percent of the 

Contract Labor cost weight to the Wages 

and Salaries cost weight and 16 percent 

to the Employee Benefits cost weight. 

Table 13 shows the Wages and 

Salaries and Employee Benefits cost 

weights after contract labor allocation 

for the 2018-based SNF market basket 

and the 2014-based SNF market basket. 

b. Derivation of the Detailed Operating 

Cost Weights 

To further divide the ‘‘All Other’’ 

residual cost weight estimated from the 

2018 Medicare cost report data into 

more detailed cost categories, we 

proposed to use the 2012 Benchmark I– 

O ‘‘Use Tables/Before Redefinitions/ 

Purchaser Value’’ for Nursing and 

Community Care Facilities industry 

(NAICS 623A00), published by the 

Census Bureau’s, Bureau of Economic 

Analysis (BEA). These data are publicly 

available at http://www.bea.gov/ 

industry/io_annual.htm. The BEA 

Benchmark I–O data are generally 

scheduled for publication every 5 years 

with 2012 being the most recent year for 

which data is available. The 2012 

Benchmark I–O data are derived from 

the 2012 Economic Census and are the 

building blocks for BEA’s economic 

accounts; therefore, they represent the 

most comprehensive and complete set 

of data on the economic processes or 

mechanisms by which output is 

produced and distributed.3 BEA also 

produces Annual I–O estimates. 

However, while based on a similar 

methodology, these estimates are less 

comprehensive and provide less detail 

than benchmark data. Additionally, the 

annual I–O data are subject to revision 

once benchmark data become available. 

For these reasons, we proposed to 

inflate the 2012 Benchmark I–O data 

aged forward to 2018 by applying the 

annual price changes from the 

respective price proxies to the 

appropriate market basket cost 

categories that are obtained from the 

2012 Benchmark I–O data. Next, the 

relative shares of the cost shares that 

each cost category represents to the total 

residual I–O costs are calculated. These 

resulting 2018 cost shares of the I–O 

data are applied to the ‘‘All Other’’ 

residual cost weight to obtain detailed 

cost weights for the residual costs for 

the 2018-based SNF market basket. For 

example, the cost for Food: Direct 

Purchases represents 11.3 percent of the 

sum of the ‘‘All Other’’ 2012 Benchmark 

I–O Expenditures inflated to 2018. 

Therefore, the Food: Direct Purchases 

cost weight is 2.5 percent of the 2018- 

based SNF market basket (11.3 percent 

× 22.3 percent = 2.5 percent). For the 

2014-based SNF market basket (82 FR 

36553), we used a similar methodology 

utilizing the 2007 Benchmark I–O data 

(aged to 2014). 

Using this methodology, we proposed 

to derive 19 detailed SNF market basket 

cost category weights from the 2018- 

based SNF market basket ‘‘All Other’’ 

residual cost weight (22.3 percent). 

These categories are: (1) Fuel: Oil and 

Gas; (2) Electricity and Other Non-Fuel 

Utilities; (3) Food: Direct Purchases; (4) 

Food: Contract Services; (5) Chemicals; 

(6) Medical Instruments and Supplies; 

(7) Rubber and Plastics; (8) Paper and 

Printing Products; (9) Apparel; (10) 

Machinery and Equipment; (11) 

Miscellaneous Products; (12) 


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TABLE 12: Major Cost Categories Derived from the SNF Medicare Cost Reports* 

Ma_jor Cost Categories 2018-based 2014-Based 

Wages and Salaries 44.1 44.3 

Employee Benefits 8.6 9.3 

Contract Labor 7.5 6.8 

Pharmaceuticals 7.5 7.3 

Professional Liability Insurance 1.1 1.1 

Capital-related 8.2 7.9 

Home Office/Related Organization Contract Labor 0.7 0.7 

All other (residual) 22.3 22.6 

*Total may not sum to 100 due to rounding. 

TABLE 13: Wages and Salaries and Employee Benefits Cost Weights After Contract 

Labor Allocation 

Major Cost Categories 2018-based Market Basket 2014-Based Market Basket 

Wages and Salaries 50.4 50.0 

Employee Benefits 9.9 10.5 
42450 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

Professional Fees: Labor-Related; (13) 

Administrative and Facilities Support 

Services; (14) Installation, Maintenance, 

and Repair Services; (15) All Other: 

Labor-Related Services; (16) 

Professional Fees: Nonlabor-Related; 

(17) Financial Services; (18) Telephone 

Services; and (19) All Other: NonlaborRelated Services. The 2014-based SNF 

market basket had separate cost 

categories for Postage services and 

Water and Sewerage. Due to the small 

weights (less than 0.1 percentage point), 

we proposed that Postage costs be 

included in the All Other: Non-laborRelated Services and Water and 

Sewerage costs be included in the 

Electricity and Other Non-Fuel Utilities 

category. We note that the machinery 

and equipment expenses are for 

equipment that is paid for in a given 

year and not depreciated over the asset’s 

useful life. Depreciation expenses for 

moveable equipment are accounted for 

in the capital component of the 2018- 

based SNF market basket (described in 

section IV.A.1.c. of this final rule). 

c. Derivation of the Detailed Capital 

Cost Weights 

Similar to the 2014-based SNF market 

basket, we further divided the Capitalrelated cost weight into: Depreciation, 

Interest, Lease and Other Capital-related 

cost weights. 

We calculated the depreciation cost 

weight (that is, depreciation costs 

excluding leasing costs) using 

depreciation costs from Worksheet S–2, 

column 1, lines 20 and 21. Since the 

depreciation costs reflect the entire SNF 

facility (Medicare and non-Medicareallowable units), we used total facility 

capital costs (Worksheet B, Part I, 

Column 18, line 100) as the 

denominator. This methodology 

assumes that the depreciation of an 

asset is the same regardless of whether 

the asset was used for Medicare or nonMedicare patients. This methodology 

yielded depreciation costs as a percent 

of capital costs of 25.3 percent for 2018. 

We then apply this percentage to the 

2018-based SNF market basket 

Medicare-allowable Capital-related cost 

weight of 8.2 percent, yielding a 

Medicare-allowable depreciation cost 

weight (excluding leasing expenses, 

which is described in more detail 

below) of 2.1 percent. To further 

disaggregate the Medicare-allowable 

depreciation cost weight into fixed and 

moveable depreciation, we proposed to 

use the 2018 SNF MCR data for end-ofthe-year capital asset balances as 

reported on Worksheet A–7. The 2018 

SNF MCR data showed a fixed/ 

moveable split of 86/14. The 2014-based 

SNF market basket, which utilized the 

same data from the 2014 MCRs, had a 

fixed/moveable split of 83/17. 

We also derived the interest expense 

share of capital-related expenses from 

2018 SNF MCR data, specifically from 

Worksheet A, column 2, line 81. Similar 

to the depreciation cost weight, we 

calculated the interest cost weight using 

total facility capital costs. This 

methodology yielded interest costs as a 

percent of capital costs of 22.8 percent 

for 2018. We then apply this percentage 

to the 2018-based SNF market basket 

Medicare-allowable Capital-related cost 

weight of 8.2 percent, yielding a 

Medicare-allowable interest cost weight 

(excluding leasing expenses) of 1.9 

percent. As done with the last rebasing 

(82 FR 36556), we proposed to 

determine the split of interest expense 

between for-profit and not-for-profit 

facilities based on the distribution of 

long-term debt outstanding by type of 

SNF (for-profit or not-for-profit/ 

government) from the 2018 SNF MCR 

data. We estimated the split between 

for-profit and not-for-profit interest 

expense to be 25/75 percent compared 

to the 2014-based SNF market basket 

with 27/73 percent. 

Because the detailed data were not 

available in the MCRs, we used the most 

recent 2017 Census Bureau Service 

Annual Survey (SAS) data to derive the 

capital-related expenses attributable to 

leasing and other capital-related 

expenses. The 2014-based SNF market 

basket used the 2014 SAS data. We note 

that we proposed to use the 2017 SAS 

data because the Census Bureau no 

longer publishes these detailed capitalrelated expenses effective for 2018. 

Based on the 2017 SAS data, we 

determined that leasing expenses are 62 

percent of total leasing and capitalrelated expenses costs. In the 2014- 

based SNF market basket, leasing costs 

represent 63 percent of total leasing and 

capital-related expenses costs. We then 

apply this percentage to the 2018-based 

SNF market basket residual Medicareallowable capital costs of 4.2 percent 

derived from subtracting the Medicareallowable depreciation cost weight and 

Medicare-allowable interest cost weight 

from the 2018-based SNF market basket 

of total Medicare-allowable capital cost 

weight (8.2 percent¥2.1 percent¥1.9 

percent = 4.2 percent). This produces 

the 2018-based SNF Medicare-allowable 

leasing cost weight of 2.6 percent and 

all-other capital-related cost weight of 

1.6 percent. 

Lease expenses are not broken out as 

a separate cost category in the SNF 

market basket, but are distributed 

among the cost categories of 

depreciation, interest, and other capitalrelated expenses, reflecting the 

assumption that the underlying cost 

structure and price movement of leasing 

expenses is similar to capital costs in 

general. As was done with past SNF 

market baskets and other PPS market 

baskets, we assumed 10 percent of lease 

expenses are overhead and assigned 

them to the other capital-related 

expenses cost category. This is based on 

the assumption that leasing expenses 

include not only depreciation, interest, 

and other capital-related costs but also 

additional costs paid to the lessor. We 

distributed the remaining lease 

expenses to the three cost categories 

based on the proportion of depreciation, 

interest, and other capital-related 

expenses to total capital costs, 

excluding lease expenses. 

Table 14 shows the capital-related 

expense distribution (including 

expenses from leases) in the 2018-based 

SNF market basket and the 2014-based 

SNF market basket. 


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Table 15 presents the 2018-based SNF 

market basket and the 2014-based SNF 

market basket. 

BILLING CODE 4120–01–P 


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TABLE 14: Comparison of the Capital-related Expense Distribution of the 2018-based 

SNF Market Basket and the 2014-based SNF Market Basket 

Cost Category 2018-based SNF Market Basket 2014-based SNF Market Basket 

Capital-related Expenses 8.2 7.9 

Total Depreciation 3.0 2.9 

Total Interest 2.7 3.0 

Other Capital-related Expenses 2.6 2.0 

Note: The cost weights are calculated using three decimal places. For presentational purposes, we are displaying 

one decimal, and therefore, the detail capital cost weights may not add to the total capital-related expenses cost 

weight due to rounding. 
42452 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

BILLING CODE 4120–01–C 2. Price Proxies Used To Measure 

Operating Cost Category Growth 

After developing the 27 cost weights 

for the 2018-based SNF market basket, 

we selected the most appropriate wage 

and price proxies currently available to 

represent the rate of change for each 

expenditure category. With four 


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TABLE 15: 2018-based SNF Market Basket and 2014-based SNF Market Basket 

Cost Category 2018-based SNF Market Basket 2014-based SNF Market Basket 

Total 100.0 100.0 

Compensation 60.2 60.4 

Wages and Salaries 1 50.4 50.0 

Employee Benefits 1 9.9 10.5 

Utilities 1.5 2.6 

Electricity and Other Non-Fuel Utilities 1.0 1.4 

Fuel: Oil and Gas 0.4 1.3 

Professional Liability Insurance 1.1 1.1 

All Other 29.0 27.9 

Other Products 17.6 14.3 

Pharmaceuticals 7.5 7.3 

Food: Direct Purchase 2.5 3.1 

Food: Contract Purchase 4.3 0.7 

Chemicals 0.2 0.2 

Medical Instruments and Supplies 0.6 0.6 

Rubber and Plastics 0.7 0.8 

Paper and Printing Products 0.5 0.8 

Annarel 0.5 0.3 

Machinery and Equipment 0.5 0.3 

Miscellaneous Products 0.3 0.3 

All Other Services 11.5 13.6 

Labor-Related Services 6.4 7.4 

Professional Fees: Labor-related 3.5 3.8 

Installation, Maintenance, and Repair 0.6 0.6 

Services 

Administrative and Facilities Support 0.4 0.5 

All Other: Labor-Related Services 1.9 2.5 

Non Labor-Related Services 5.1 6.2 

Professional Fees: Nonlabor-Related 2.0 1.8 

Financial Services 1.3 2.0 

Telephone Services 0.3 0.5 

All Other: Nonlabor-Related Services3 1.5 2.0 

Capital-Related Expenses 8.2 7.9 

Total Depreciation 3.0 2.9 

Building and Fixed Equipment 2.5 2.5 

Movable Equipment 0.4 0.4 

Total Interest 2.7 3.0 

For-Profit SNFs 0.7 0.8 

Government and Nonprofit SNFs 2.0 2.1 

Other Capital-Related Expenses 2.6 2.0 

Note: The cost weights are calculated using three decimal places. For presentational purposes, we are displaying one 

decimal, and therefore, the detailed cost weights may not add to the aggregate cost weights or to 100.0 due to rounding. 

1. Contract labor is distributed to wages and salaries and employee benefits based on the share of total compensation that 

each category represents. 

2. Water and Sewerage costs are included in the Electricity and Other Non-Fuel Utilities cost category in the 2018-based 

SNF market basket. 

3. Postage costs are included in the All Other Non-labor-related cost category in the 2018-based SNF market basket. 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42453 

exceptions (three for the capital-related 

expenses cost categories and one for 

PLI), we base the wage and price proxies 

on Bureau of Labor Statistics (BLS) data, 

and group them into one of the 

following BLS categories: 

• Employment Cost Indexes. 

Employment Cost Indexes (ECIs) 

measure the rate of change in 

employment wage rates and employer 

costs for employee benefits per hour 

worked. These indexes are fixed-weight 

indexes and strictly measure the change 

in wage rates and employee benefits per 

hour. ECIs are superior to Average 

Hourly Earnings (AHE) as price proxies 

for input price indexes because they are 

not affected by shifts in occupation or 

industry mix, and because they measure 

pure price change and are available by 

both occupational group and by 

industry. The industry ECIs are based 

on the 2012 NAICS and the 

occupational ECIs are based on the 2000 

and 2010 Standard Occupational 

Classification System (SOC). 

• Producer Price Indexes. Producer 

Price Indexes (PPIs) measure the average 

change over time in the selling prices 

received by domestic producers for their 

output. The prices included in the PPI 

are from the first commercial 

transaction for many products and some 

services (https://www.bls.gov/ppi/). 

• Consumer Price Indexes. Consumer 

Price Indexes (CPIs) measure the 

average change over time in the prices 

paid by urban consumers for a market 

basket of consumer goods and services 

(https://www.bls.gov/cpi/). CPIs are only 

used when the purchases are similar to 

those of retail consumers rather than 

purchases at the producer level, or if no 

appropriate PPIs are available. 

We evaluated the price proxies using 

the criteria of reliability, timeliness, 

availability, and relevance. Reliability 

indicates that the index is based on 

valid statistical methods and has low 

sampling variability. Widely accepted 

statistical methods ensure that the data 

were collected and aggregated in a way 

that can be replicated. Low sampling 

variability is desirable because it 

indicates that the sample reflects the 

typical members of the population. 

(Sampling variability is variation that 

occurs by chance because only a sample 

was surveyed rather than the entire 

population.) Timeliness implies that the 

proxy is published regularly, preferably 

at least once a quarter. The market 

baskets are updated quarterly, and 

therefore, it is important for the 

underlying price proxies to be up-todate, reflecting the most recent data 

available. We believe that using proxies 

that are published regularly (at least 

quarterly, whenever possible) helps to 

ensure that we are using the most recent 

data available to update the market 

basket. We strive to use publications 

that are disseminated frequently, 

because we believe that this is an 

optimal way to stay abreast of the most 

current data available. Availability 

means that the proxy is publicly 

available. We prefer that our proxies are 

publicly available because this will help 

ensure that our market basket updates 

are as transparent to the public as 

possible. In addition, this enables the 

public to be able to obtain the price 

proxy data on a regular basis. Finally, 

relevance means that the proxy is 

applicable and representative of the cost 

category weight to which it is applied. 

The CPIs, PPIs, and ECIs that we have 

proposed meet these criteria. Therefore, 

we believe that they continue to be the 

best measure of price changes for the 

cost categories to which they would be 

applied. 

Table 20 lists all price proxies for the 

2018-based SNF market basket. Below is 

a detailed explanation of the price 

proxies used for each operating cost 

category. 

• Wages and Salaries: We proposed to 

use the ECI for Wages and Salaries for 

Private Industry Workers in Nursing 

Care Facilities (NAICS 6231; BLS series 

code CIU2026231000000I) to measure 

price growth of this category. NAICS 

623 includes facilities that provide a 

mix of health and social services, with 

many of the health services being 

largely some level of nursing services. 

Within NAICS 623 is NAICS 6231, 

which includes nursing care facilities 

primarily engaged in providing 

inpatient nursing and rehabilitative 

services. These facilities, which are 

most comparable to Medicare-certified 

SNFs, provide skilled nursing and 

continuous personal care services for an 

extended period of time, and therefore, 

have a permanent core staff of registered 

or licensed practical nurses. This is the 

same index used in the 2014-based SNF 

market basket. 

• Employee Benefits: We proposed to 

use the ECI for Benefits for Nursing Care 

Facilities (NAICS 6231) to measure 

price growth of this category. The ECI 

for Benefits for Nursing Care Facilities 

is calculated using BLS’s total 

compensation (BLS series ID 

CIU2016231000000I) for nursing care 

facilities series and the relative 

importance of wages and salaries within 

total compensation. We believe this 

constructed ECI series is technically 

appropriate for the reason stated above 

in the Wages and Salaries price proxy 

section. This is the same index used in 

the 2014-based SNF market basket. 

• Electricity and Other Non-Fuel 

Utilities: We proposed to use the PPI 

Commodity for Commercial Electric 

Power (BLS series code WPU0542) to 

measure the price growth of this cost 

category as Electricity costs account for 

93 percent of these expenses. This is the 

same index used for the Electricity cost 

category in the 2014-based SNF market 

basket. As previously noted, we 

proposed to include Water and 

Sewerage costs within the Electricity 

and Other Non-Fuel Utilities cost 

category, and to no longer use the CPI 

All Urban for Water and Sewerage 

Maintenance as we did for the 2014- 

based SNF market basket, due to the 

small size of this estimated cost weight 

(less than 0.1 percent). 

Comment: One commenter noted that 

CMS is proposing to include water and 

sewerage costs in the Electricity and 

Other Non-Fuel utilities cost weight and 

to no longer use the CPI All Urban for 

Water and Sewerage Maintenance. They 

expressed concern stating that many 

SNFs have invested in waste-water 

monitoring systems as a result of 

COVID–19. 

Response: We recognize the 

commenter’s concern but as stated 

above, the most recent year of 

Benchmark I–O data we have available 

to derive the detailed cost weights for 

the SNF market basket is 2012, with the 

data generally scheduled for publication 

every 5 years. Based on these data, the 

cost weight associated with Water and 

Sewerage costs is less than 0.1 percent, 

and therefore, we do not believe a 

separate cost category is appropriate. 

We will continue to monitor new data 

for SNFs as it becomes available, 

including any new Benchmark I–O data, 

and will propose a rebasing or revising 

of the SNF market basket cost weights 

as appropriate. 

• Fuel: Oil and Gas: We proposed to 

change the proxy used for the Fuel: Oil 

and Gas cost category. Our analysis of 

the Bureau of Economic Analysis’ 2012 

Benchmark I–O data for Nursing and 

Community Care Facilities shows 

approximately 96 percent of SNF Fuel: 

Oil and Gas expenses are for Petroleum 

Refineries (NAICS 324110), Natural gas 

(NAICS 221200), and Other Petroleum 

and Coal Products Manufacturing 

(NAICS 324190). We proposed to create 

a blended index based on those three 

NAICS chemical expenses listed above 

that account for 96 percent of SNF 

chemical expenses. We proposed to 

create this blend based on each NAICS’ 

expenses as a share of their sum. 

Therefore, we proposed a blended proxy 

of 61 percent of the PPI Industry for 

Petroleum Refineries (BLS series code 

PCU32411–32411), 7 percent of the PPI 


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Commodity for Natural Gas (BLS series 

code WPU0531), and 32 percent of the 

PPI for Other Petroleum and Coal 

Products manufacturing (BLS series 

code PCU32419–32419). 

The 2014-based SNF market basket 

also used a blended chemical proxy that 

was based on 2007 Benchmark I–O data. 

We believe our proposed Fuel: Oil and 

Gas blended index for the 2018-based 

SNF market basket is technically 

appropriate as it reflects more recent 

data on SNFs purchasing patterns. Table 

16 provides the weights for the 2018- 

based blended chemical index and the 

2014-based blended chemical index. 

• Professional Liability Insurance: We 

proposed to use the CMS Hospital 

Professional Liability Insurance Index to 

measure price growth of this category. 

We were unable to find a reliable data 

source that collects SNF-specific PLI 

data. Therefore, we proposed to use the 

CMS Hospital Professional Liability 

Index, which tracks price changes for 

commercial insurance premiums for a 

fixed level of coverage, holding nonprice factors constant (such as a change 

in the level of coverage). This is the 

same index used in the 2014-based SNF 

market basket. We believe this is an 

appropriate proxy to measure the price 

growth associated of SNF PLI as it 

captures the price inflation associated 

with other medical institutions that 

serve Medicare patients. 

• Pharmaceuticals: We proposed to 

use the PPI Commodity for 

Pharmaceuticals for Human Use, 

Prescription (BLS series code 

WPUSI07003) to measure the price 

growth of this cost category. This is the 

same index used in the 2014-based SNF 

market basket. 

• Food: Wholesale Purchases: We 

proposed to use the PPI Commodity for 

Processed Foods and Feeds (BLS series 

code WPU02) to measure the price 

growth of this cost category. This is the 

same index used in the 2014-based SNF 

market basket. 

• Food: Retail Purchase: We proposed 

to use the CPI All Urban for Food Away 

From Home (All Urban Consumers) 

(BLS series code CUUR0000SEFV) to 

measure the price growth of this cost 

category. This is the same index used in 

the 2014-based SNF market basket. 

• Chemicals: For measuring price 

change in the Chemicals cost category, 

we proposed to use a blended PPI 

composed of the Industry PPIs for Other 

Basic Organic Chemical Manufacturing 

(NAICS 325190) (BLS series code 

PCU32519–32519), Soap and Cleaning 

Compound Manufacturing (NAICS 

325610) (BLS series code PCU32561– 

32561), and Other Miscellaneous 

Chemical Product Manufacturing 

(NAICS 325998) (BLS series code 

PCU325998325998). 

Using the 2012 Benchmark I–O data, 

we found that these three NAICS 

industries accounted for approximately 

96 percent of SNF chemical expenses. 

The remaining 4 percent of SNF 

chemical expenses are for three other 

incidental NAICS chemicals industries 

such as Paint and Coating 

Manufacturing. We proposed to create a 

blended index based on those three 

NAICS chemical expenses listed above 

that account for 96 percent of SNF 

chemical expenses. We proposed to 

create this blend based on each NAICS’ 

expenses as a share of their sum. These 

expenses as a share of their sum are 

listed in Table 17. 

The 2014-based SNF market basket 

also used a blended chemical proxy that 

was based on 2007 Benchmark I–O data. 

We believe our proposed chemical 

blended index for the 2018-based SNF 

market basket is technically appropriate 

as it reflects more recent data on SNFs 

purchasing patterns. Table 17 provides 

the weights for the 2018-based blended 

chemical index and the 2014-based 

blended chemical index. 

• Medical Instruments and Supplies: 

We proposed to change the proxy used 

for the Medical Instruments and 

Supplies cost weight. The 2012 

Benchmark I–O data shows 46 percent 

of medical instruments and supply costs 

are for Surgical and medical instrument 

manufacturing costs (NAICS 339112) 

and 54 percent are for Surgical 

appliance and supplies manufacturing 

costs (NAICS 339113). To proxy the 

price changes associated with NAICS 

339112, we proposed using the PPI— 

Commodity—Surgical and medical 

instruments (BLS series code 

WPU1562). This the same price proxy 

we used in the 2014-based SNF market 

basket. To proxy the price changes 

associated with NAICS 339113, we 

proposed to use 50 percent for the PPI— 

Commodity—Medical and surgical 


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TABLE 16: Fuel: Oil and Gas Blended Index Weights 

2018-based 2014-based 

NAICS Price Proxv Index Index 

221200 PPI Commodity for Natural Gas 7% 35% 

324110 PPI Industry for Petroleum Refineries 61% 65% 

324190 PPI for Other Petroleum and Coal Products manufacturing 32% n/a 

Total 100% 100% 

TABLE 17: Chemical Blended Index Weights 

NAICS Price Proxy 2018-based 2014-based 

Index Index 

325190 PPI for Other Basic Organic Chemical Manufacturing 34% 22% 

325610 PPI for Soap and Cleaning Compound Manufacturing 21% 37% 

325998 PPI for Other Miscellaneous Chemical Product Manufacturing 45% 41% 

Total 100% 100% 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42455 

appliances and supplies (BLS series 

code WPU1563) and 50 percent for the 

PPI Commodity data for Miscellaneous 

products-Personal safety equipment and 

clothing (BLS series code WPU1571). 

The latter price proxy would reflect 

personal protective equipment 

including but not limited to face shields 

and protective clothing. The 2012 

Benchmark I–O data does not provide 

specific expenses for personal protective 

equipment (which would be reflected in 

the NAICS 339113 expenses); however, 

we recognize that this category reflects 

costs faced by SNFs. In absence of any 

specific cost data on personal protective 

equipment, we proposed to include the 

PPI Commodity data for Miscellaneous 

products-Personal safety equipment and 

clothing (BLS series code WPU1571) in 

the blended proxy for Medical 

Instruments and Supplies cost category 

with a weight of 27 percent (that is, 50 

percent of the NAICS 339113 expenses 

as a percent of the sum of NAICS 

339113 and NAICS 339112 expenses 

from the I–O). 

The 2014-based SNF market basket 

used a blend composed of 60 percent of 

the PPI Commodity for Medical and 

Surgical Appliances and Supplies (BLS 

series code WPU1563) and 40 percent of 

the PPI Commodity for Surgical and 

Medical Instruments (BLS series code 

WPU1562). Table 18 provides the 

proposed Medical Instruments and 

Supplies cost weight blended price 

proxy. 

Comment: One commenter 

appreciated CMS’ proposal to modify 

the Medical Instruments and Supplies 

proxy to reflect personal protective 

equipment. 

Response: We appreciate the 

commenter’s support and recognize the 

need to reflect the prices of medical 

instruments and supplies purchased by 

SNFs. 

• Rubber and Plastics: We proposed 

to use the PPI Commodity for Rubber 

and Plastic Products (BLS series code 

WPU07) to measure price growth of this 

cost category. This is the same index 

used in the 2014-based SNF market 

basket. 

• Paper and Printing Products: We 

proposed to use the PPI Commodity for 

Converted Paper and Paperboard 

Products (BLS series code WPU0915) to 

measure the price growth of this cost 

category. This is the same index used in 

the 2014-based SNF market basket. 

• Apparel: We proposed to use the 

PPI Commodity for Apparel (BLS series 

code WPU0381) to measure the price 

growth of this cost category. This is the 

same index used in the 2014-based SNF 

market basket. 

• Machinery and Equipment: We 

proposed to use the PPI Commodity for 

Machinery and Equipment (BLS series 

code WPU11) to measure the price 

growth of this cost category. This is the 

same index used in the 2014-based SNF 

market basket. 

• Miscellaneous Products: For 

measuring price change in the 

Miscellaneous Products cost category, 

we proposed to use the PPI Commodity 

for Finished Goods less Food and 

Energy (BLS series code WPUFD4131). 

Both food and energy are already 

adequately represented in separate cost 

categories and should not also be 

reflected in this cost category. This is 

the same index used in the 2014-based 

SNF market basket. 

• Professional Fees: Labor-Related: 

We proposed to use the ECI for Total 

Compensation for Private Industry 

Workers in Professional and Related 

(BLS series code CIU2010000120000I) to 

measure the price growth of this 

category. This is the same index used in 

the 2014-based SNF market basket. 

• Administrative and Facilities 

Support Services: We proposed to use 

the ECI for Total Compensation for 

Private Industry Workers in Office and 

Administrative Support (BLS series 

code CIU2010000220000I) to measure 

the price growth of this category. This 

is the same index used in the 2014- 

based SNF market basket. 

• Installation, Maintenance and 

Repair Services: We proposed to use the 

ECI for Total Compensation for All 

Civilian Workers in Installation, 

Maintenance, and Repair (BLS series 

code CIU1010000430000I) to measure 

the price growth of this new cost 

category. This is the same index used in 

the 2014-based SNF market basket. 

• All Other: Labor-Related Services: 

We proposed to use the ECI for Total 

Compensation for Private Industry 

Workers in Service Occupations (BLS 

series code CIU2010000300000I) to 

measure the price growth of this cost 

category. This is the same index used in 

the 2014-based SNF market basket. 

• Professional Fees: NonLaborRelated: We proposed to use the ECI for 

Total Compensation for Private Industry 

Workers in Professional and Related 

(BLS series code CIU2010000120000I) to 

measure the price growth of this 

category. This is the same index used in 

the 2014-based SNF market basket. 

• Financial Services: We proposed to 

use the ECI for Total Compensation for 

Private Industry Workers in Financial 

Activities (BLS series code 

CIU201520A000000I) to measure the 

price growth of this cost category. This 

is the same index used in the 2014- 

based SNF market basket. 

• Telephone Services: We proposed 

to use the CPI All Urban for Telephone 

Services (BLS series code 

CUUR0000SEED) to measure the price 

growth of this cost category. This is the 

same index used in the 2014-based SNF 

market basket. 

• All Other: NonLabor-Related 

Services: We proposed to use the CPI 

All Urban for All Items Less Food and 

Energy (BLS series code 

CUUR0000SA0L1E) to measure the 

price growth of this cost category. This 

is the same index used in the 2014- 

based SNF market basket. As previously 

noted, we proposed to include Postage 

costs within the All Other: NonLaborRelated Services cost category, and to no 


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TABLE 18: Medical Instruments and Supplies Blended Index Weights 

NAICS Price Proxy 2018-based 2014-based 

Index Index 

339112 PPI - Commodity - Surgical and medical instruments (WUII 562) 46% 40% 

PPI - Commodity - Medical and surgical appliances and supplies 

339113 (WPU1563) 27% 60% 

PPI Commodity data for Miscellaneous products-Personal safety 

equipment and clothing (WPU1571) 27% n/a 

Total 100% 100% 
42456 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

longer use the CPI All Urban for Postage 

as we did for the 2014-based SNF 

market basket, due to the small size of 

this estimated cost weight (less than 0.1 

percent). 

3. Price Proxies Used To Measure 

Capital Cost Category Growth 

We proposed to apply the same 

capital price proxies as were used in the 

2014-based SNF market basket, with the 

exception of the For-profit interest cost 

category, and below is a detailed 

explanation of the price proxies used for 

each capital cost category. We also 

proposed to continue to vintage weight 

the capital price proxies for 

Depreciation and Interest to capture the 

long-term consumption of capital. This 

vintage weighting method is the same 

method that was used for the 2014- 

based SNF market basket and is 

described below. 

• Depreciation—Building and Fixed 

Equipment: We proposed to use the 

BEA Chained Price Index for Private 

Fixed Investment in Structures, 

Nonresidential, Hospitals and Special 

Care (BEA Table 5.4.4. Price Indexes for 

Private Fixed Investment in Structures 

by Type). This BEA index is intended to 

capture prices for construction of 

facilities such as hospitals, nursing 

homes, hospices, and rehabilitation 

centers. This is the same index used in 

the 2014-based SNF market basket. 

• Depreciation—Movable Equipment: 

We proposed to use the PPI Commodity 

for Machinery and Equipment (BLS 

series code WPU11). This price index 

reflects price inflation associated with a 

variety of machinery and equipment 

that would be utilized by SNFs, 

including but not limited to medical 

equipment, communication equipment, 

and computers. This is the same index 

used in the 2014-based SNF market 

basket. 

• Nonprofit Interest: We proposed to 

use the average yield on Municipal 

Bonds (Bond Buyer 20-bond index). 

This is the same index used in the 2014- 

based SNF market basket. 

• For-Profit Interest: For the ForProfit Interest cost category, we 

proposed to use the iBoxx AAA 

Corporate Bond Yield index instead of 

the Moody’s AAA Corporate Bond Yield 

index that was used for the 2014-based 

SNF market basket. Effective for 

December 2020, the Moody’s AAA 

Corporate Bond series is no longer 

available for use under license to IGI, 

the nationally-recognized economic and 

financial forecasting firm with whom 

we contract to forecast the components 

of the market baskets and MFP. 

Therefore, we proposed to replace the 

price proxy for the For-Profit interest 

cost category. We compared the iBoxx 

AAA Corporate Bond Yield index with 

the Moody’s AAA Corporate Bond Yield 

index and found that the average growth 

rates in the two series were similar. 

Over the historical time period of FY 

2000 to FY 2020, the 4-quarter percent 

change moving average growth in the 

iBoxx series was approximately 0.1 

percentage point higher, on average, 

than the Moody’s AAA corporate Bond 

Yield index. 

• Other Capital: Since this category 

includes fees for insurances, taxes, and 

other capital-related costs, we proposed 

to use the CPI for Rent of Primary 

Residence (BLS series code 

CUUS0000SEHA), which would reflect 

the price growth of these costs. This is 

the same index used in the 2014-based 

SNF market basket. 

We believe that these price proxies 

are the most appropriate proxies for 

SNF capital costs that meet our 

selection criteria of relevance, 

timeliness, availability, and reliability. 

As stated above, we proposed to 

continue to vintage weight the capital 

price proxies for Depreciation and 

Interest to capture the long-term 

consumption of capital. To capture the 

long-term nature, the price proxies are 

vintage-weighted; and the vintage 

weights are calculated using a two-step 

process. First, we determine the 

expected useful life of capital and debt 

instruments held by SNFs. Second, we 

identify the proportion of expenditures 

within a cost category that is 

attributable to each individual year over 

the useful life of the relevant capital 

assets, or the vintage weights. 

We rely on Bureau of Economic 

Analysis (BEA) fixed asset data to derive 

the useful lives of both fixed and 

movable capital, which is the same data 

source used to derive the useful lives for 

the 2014-based SNF market basket. The 

specifics of the data sources used are 

explained below. 

a. Calculating Useful Lives for Moveable 

and Fixed Assets 

Estimates of useful lives for movable 

and fixed assets for the 2018-based SNF 

market basket are 9 and 26 years, 

respectively. These estimates are based 

on three data sources from the BEA: (1) 

Current-cost average age; (2) historicalcost average age; and (3) industryspecific current cost net stocks of assets. 

BEA current-cost and historical-cost 

average age data by asset type are not 

available by industry but are published 

at the aggregate level for all industries. 

The BEA does publish current-cost net 

capital stocks at the detailed asset level 

for specific industries. There are 64 

detailed movable assets (including 

intellectual property) and there are 32 

detailed fixed assets in the BEA 

estimates. Since we seek aggregate 

useful life estimates applicable to SNFs, 

we developed a methodology to 

approximate movable and fixed asset 

ages for nursing and residential care 

services (NAICS 623) using the 

published BEA data. For the 2018 SNF 

market basket, we use the current-cost 

average age for each asset type from the 

BEA fixed assets Table 2.9 for all assets 

and weight them using current-cost net 

stock levels for each of these asset types 

in the nursing and residential care 

services industry, NAICS 6230. (For 

example, nonelectro medical equipment 

current-cost net stock (accounting for 

about 35 percent of total moveable 

equipment current-cost net stock in 

2018) is multiplied by an average age of 

4.7 years. Current-cost net stock levels 

are available for download from the 

BEA website at https://apps.bea.gov/ 

iTable/index_FA.cfm. We then aggregate 

the ‘‘weighted’’ current-cost net stock 

levels (average age multiplied by 

current-cost net stock) into moveable 

and fixed assets for NAICS 6230. We 

then adjust the average ages for 

moveable and fixed assets by the ratio 

of historical-cost average age (Table 

2.10) to current-cost average age (Table 

2.9). 

This produces historical cost average 

age data for movable (equipment and 

intellectual property) and fixed 

(structures) assets specific to NAICS 

6230 of 4.7 and 13.1 years for 2018, 

respectively. The average age reflects 

the average age of an asset at a given 

point in time, whereas we want to 

estimate a useful life of the asset, which 

would reflect the average over all 

periods an asset is used. To do this, we 

multiply each of the average age 

estimates by two to convert to average 

useful lives with the assumption that 

the average age is normally distributed 

(about half of the assets are below the 

average at a given point in time, and 

half above the average at a given point 

in time). This produces estimates of 

likely useful lives of 9.49 and 26.19 

years for movable and fixed assets, 

which we round to 9 and 26 years, 

respectively. We proposed an interest 

vintage weight time span of 24 years, 

obtained by weighting the fixed and 

movable vintage weights (26 years and 

9 years, respectively) by the fixed and 

movable split (86 percent and 14 

percent, respectively). This is the same 

methodology used for the 2014-based 

SNF market basket, which had useful 

lives of 23 years and 10 years for fixed 

and moveable assets, respectively. We 

estimate that the impact of revising the 


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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42457 

useful lives had a minor impact on the 

average historical growth rate of the 

2018-based SNF market basket total 

aggregate capital cost price proxy. Over 

the FY 2016 to FY 2020 time period, the 

percent change moving average in the 

total aggregate capital cost price proxy 

was about 0.06 percentage point higher, 

on average, based on the 2018-based 

SNF market basket compared to the 

2014-based SNF market basket. 

b. Constructing Vintage Weights 

Given the expected useful life of 

capital (fixed and moveable assets) and 

debt instruments, we must determine 

the proportion of capital expenditures 

attributable to each year of the expected 

useful life for each of the three asset 

types: Building and fixed equipment, 

moveable equipment, and interest. 

These proportions represent the vintage 

weights. We were not able to find a 

historical time series of capital 

expenditures by SNFs. Therefore, we 

approximated the capital expenditure 

patterns of SNFs over time, using 

alternative SNF data sources. For 

building and fixed equipment, we used 

the stock of beds in nursing homes from 

the National Nursing Home Survey 

(NNHS) conducted by the National 

Center for Health Statistics (NCHS) for 

1962 through 1999. For 2000 through 

2010, we extrapolated the 1999 bed data 

forward using a 5-year moving average 

of growth in the number of beds from 

the SNF MCR data. For 2011 to 2014, we 

extrapolate the 2010 bed data forward 

using the average growth in the number 

of beds over the 2011 to 2014 time 

period. For 2015 to 2018, we proposed 

to extrapolate the 2014 bed data forward 

using the average growth in the number 

of beds over the 2015 to 2018 time 

period. We then used the change in the 

stock of beds each year to approximate 

building and fixed equipment purchases 

for that year. This procedure assumes 

that bed growth reflects the growth in 

capital-related costs in SNFs for 

building and fixed equipment. We 

believe that this assumption is 

reasonable because the number of beds 

reflects the size of a SNF, and as a SNF 

adds beds, it also likely adds fixed 

capital. 

As was done for the 2014-based SNF 

market basket (as well as prior market 

baskets), we proposed to estimate 

moveable equipment purchases based 

on the ratio of ancillary costs to routine 

costs. The time series of the ratio of 

ancillary costs to routine costs for SNFs 

measures changes in intensity in SNF 

services, which are assumed to be 

associated with movable equipment 

purchase patterns. The assumption here 

is that as ancillary costs increase 

compared to routine costs, the SNF 

caseload becomes more complex and 

would require more movable 

equipment. The lack of movable 

equipment purchase data for SNFs over 

time required us to use alternative SNF 

data sources. A more detailed 

discussion of this methodology was 

published in the FY 2008 SNF final rule 

(72 FR 43428). We believe the resulting 

two time series, determined from beds 

and the ratio of ancillary to routine 

costs, reflect real capital purchases of 

building and fixed equipment and 

movable equipment over time. 

To obtain nominal purchases, which 

are used to determine the vintage 

weights for interest, we converted the 

two real capital purchase series from 

1963 through 2018 determined above to 

nominal capital purchase series using 

their respective price proxies (the BEA 

Chained Price Index for Nonresidential 

Construction for Hospitals & Special 

Care Facilities and the PPI for 

Machinery and Equipment). We then 

combined the two nominal series into 

one nominal capital purchase series for 

1963 through 2018. Nominal capital 

purchases are needed for interest 

vintage weights to capture the value of 

debt instruments. 

Once we created these capital 

purchase time series for 1963 through 

2018, we averaged different periods to 

obtain an average capital purchase 

pattern over time: (1) For building and 

fixed equipment, we averaged 31, 26- 

year periods; (2) for movable equipment, 

we averaged 48, 9-year periods; and (3) 

for interest, we averaged 33, 24-year 

periods. We calculate the vintage weight 

for a given year by dividing the capital 

purchase amount in any given year by 

the total amount of purchases during the 

expected useful life of the equipment or 

debt instrument. To provide greater 

transparency, we posted on the CMS 

market basket website at http://

www.cms.gov/Research-Statistics-Dataand-Systems/Statistics-Trends-andReports/MedicareProgramRatesStats/ 

MarketBasketResearch.html, an 

illustrative spreadsheet that contains an 

example of how the vintage-weighted 

price indexes are calculated. 

The vintage weights for the 2018- 

based SNF market basket and the 2014- 

based SNF market basket are presented 

in Table 19. 

BILLING CODE 4120–01–P 


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42458 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

BILLING CODE 4120–01–C 

Comment: Many commenters stated 

that COVID–19 has required SNFs to 

make significant changes in operations 

resulting in much higher operating costs 

as a result of increased labor, PPE, 

janitorial, and capital costs. They stated 

the new cost levels were permanent and 

noted that the 2018 data used to rebase 

the market basket would not reflect 

these cost levels. They recommended 

CMS account for these increased costs 

in the market basket. 

Several commenters requested that 

CMS explore the temporary use of more 

heavily-weighted market basket 

elements to account for COVID–19 

influenced cost increases, especially for 

both in-house and contract labor costs 

and capital costs. To account for the 

change in labor costs, some commenters 

recommended that CMS make an 

adjustment to the labor–related price 

proxy to account for the increase in 

wages and salaries and contract labor 

costs. One commenter recommended 

that CMS use the Payroll-Based Journal 

(PBJ) data and examine the wage rate 

differential between Agency and 

Employed Nurses/Aides using the labor 

data reported on Schedule S–3 Part V of 

the SNF Medicare cost reports. The 

commenter recommended that the 

greater proportion of Agency staff in the 

PBJ data when combined with the price 

differential between Employed vs 

Agency staff would result in an increase 

in the price proxy for labor (with labor 

being roughly 70 percent of costs). 

One commenter listed testing of staff 

as one of the largest unbudgeted and 

unreimbursed costs for nursing homes. 

They stated that staff testing costs vary 

widely based on the size of the facility, 

types of tests used, and laboratory 

charges and on average have cost about 

100 per week per staff member tested. 

Some commenters stated that some PPE 

allotments were provided by state and 

local governments; however, the 

amounts were inconsequential in 

comparison with the needs. Some 

commenters further requested that CMS 

consider additional under-detected 

costs due to room-sharing by more than 

one COVID–19 positive patient which 

was required by space constraints and/ 

or isolation room shortages. 

One commenter also recommended 

CMS inflate the capital costs noting that 

SNFs have incurred increased costs to 

reduce the spread of COVID–19 by 

investing in fresh air intake systems, air 

purification systems, and new heating 

ventilation and air conditions systems. 

They also cited additional costs 


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TABLE 19: 2018-Based Vintage Weights and 2014-Based Vintage Weights 

Building and Fixed Movable Equipment Interest 

Yearl Equi1>ment 

2018-based 2014-Based 2018-based 2014-Based 2018-based 2014-Based 

26 years 23 years 9 years 10 years 24 years 21 years 

I 0.049 0.056 0.135 0.085 0.027 0.032 

2 0.050 0.055 0.140 0.087 0.028 0.033 

3 0.049 0.054 0.128 0.091 0.029 0.034 

4 0.047 0.052 0.112 0.097 0.031 0.036 

5 0.045 0.049 0.119 0.099 0.032 0.037 

6 0.043 0.046 0.111 0.102 0.034 0.039 

7 0.041 0.044 0.084 0.108 0.036 0.041 

8 0.040 0.043 0.080 0.109 0.037 0.043 

9 0.037 0.040 0.091 0.1IO 0.038 0.044 

IO 0.035 0.038 0.112 0.040 0.045 

II 0.036 0.038 0.043 0.048 

12 0.036 0.039 0.047 0.052 

13 0.036 0.039 0.049 0.056 

14 0.036 0.039 0.051 0.058 

15 0.035 0.039 0.050 0.060 

16 0.036 0.039 0.048 0.059 

17 0.036 0.040 0.048 0.057 

18 0.038 0.041 0.048 0.057 

19 0.037 0.043 0.048 0.056 

20 0.036 0.042 0.048 0.056 

21 0.035 0.042 0.047 0.057 

22 0.035 0.042 0.047 

23 0.035 0.042 0.047 

24 0.033 0.049 

25 0.032 

26 0.032 

Total 1.000 1.000 1.000 1.000 1.000 1.000 

Note: The vintage weights are calculated using thirteen decimals. For presentation purposes, we are displaying 

three decimals and therefore, the detail vintage weights may not add to 1.000 due to rounding. 

1 Year 1 represents the vintage weight applied to the farthest year while the vintage weight for year 26, for example, 

would apply to the most recent year. 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42459 

incurred in 2020 to invest in improved 

wireless technology and ultraviolet 

light. One commenter suggested that the 

capital costs should also reflect the 

increased costs of replacing and/or 

updating older facilities and the 

construction of larger facilities which 

would better position nursing facilities 

for any future pandemic situations. 

Response: We appreciate the 

commenter’s concern regarding the 

impact of COVID–19 on SNF costs. We 

reiterate that the SNF market basket is 

a fixed-weight, Laspeyres-type price 

index that measures the change in price, 

over time, of the same mix of goods and 

services purchased in the base period. 

Any changes in the quantity or mix of 

goods and services (that is, intensity) 

purchased over time relative to a base 

period are not reflected. Changes in 

costs are taken into consideration and 

reflected when the market basket is 

rebased and the cost weights are revised 

to reflect the most recent cost structure. 

CMS proposed to rebase and revise the 

SNF market basket for FY 2022 since it 

has been 4 years since the last rebasing. 

The SNF market basket cost weights rely 

on the data reported on the Medicare 

cost reports, which provide the most 

comprehensive expense data available 

for the universe of SNFs. We proposed 

to use the data reported for 2018 

because it is the most recent year of 

complete data available at the time of 

performing the analysis for the proposed 

SNF rule. 

We understand that the COVID–19 

pandemic has resulted in unanticipated 

challenges to SNF providers and all 

other healthcare provider settings. We 

note that the market basket updates 

account for the expected changes in the 

input prices, including labor, medical 

supplies, other products (including 

PPE), and capital. The price proxies take 

into account the changes in the 

expected prices of these good and 

services. The rates are set prospectively 

which requires forecasting the expected 

inflation pressures. The FY 2022 SNF 

payment update is based on the most 

recent forecast of expected price 

pressures that SNF providers will face 

in FY 2022. Additionally, the SNF 

payment update formula includes a 

forecast error adjustment if the 

difference between the historical SNF 

market basket growth and projected SNF 

market basket growth exceeds the 

forecast error threshold (in absolute 

terms). As discussed in section IV.B.3 of 

this final rule, the forecast error for FY 

2020 is ¥0.8 percentage point 

indicating the SNF market basket 

update factor was higher than the actual 

SNF market basket growth. The same 

analysis will be considered for FY 2021 

once historical data is available. 

We also note that while the overall 

operating expenses may have been 

impacted for providers in 2020, the 

market basket cost share weights are 

based on the relative shares of expenses 

by category. CMS would need to have a 

dataset that would provide expenditure 

levels for all categories of expenses to 

determine the relative shares of each 

cost category and there is not a 

comprehensive set of 2020 cost data for 

SNF providers available at this time. It 

would be inappropriate to only make 

adjustments to select costs as suggested 

by the commenters. As stated 

previously, we plan to review the 2020 

Medicare cost report data as soon as 

complete information is available to 

ensure the market basket relative cost 

shares are still appropriate. 

Finally, we respectfully disagree that 

the capital cost weight in the market 

basket should reflect future costs of 

replacing and/or updating older 

facilities and the construction of larger 

facilities in order to better position 

nursing facilities for any future 

pandemic situations. The market basket 

cost weights are based on actual 

expenses that SNF facilities incur and 

reported on the Medicare cost reports. 

After consideration of public 

comments, we are finalizing the 2018- 

based SNF market basket as proposed. 

Table 20 shows all the price proxies for 

the finalized 2018-based SNF market 

basket. 

BILLING CODE 4120–01–P 


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42460 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 


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TABLE 20: Price Proxies for the 2018-based SNF Market Basket 

Cost Category Weight Price proxy 

Total 100.0 

Compensation 60.2 

Wages and Salaries 1 50.4 ECT for Wages and Salaries for Private Industry Workers in 

Nursing Care Facilities 

Employee Benefits1 9.9 ECI for Total Benefits for Private Industry Workers in 

Nursing Care Facilities 

Utilities 1.5 

Electricity and Other Non-Fuel Utilities 1.0 PPI Commodity for Commercial Electric Power 

Fuel: Oil and Gas 0.4 Blend of Fuel PP ls 

Professional Liability Insurance 1.1 CMS Professional Liability Insurance Premium Index 

All Other 29.0 

Other Products 17.6 

Pharmaceuticals 7.5 PPI Commodity for Pharmaceuticals for Human Use, 

Prescription 

Food: Direct Purchase 2.5 PPT Commodity for Processed Foods and Feeds 

Food: Contract Purchase 4.3 CPI for Food A wav From Home (All Urban Consumers) 

Chemicals 0.2 Blend of Chemical PPTs 

Medical Instruments and Supplies 0.6 Blend of Medical Instruments and Supplies PPis 

Rubber and Plastics 0.7 PPI Commodity for Rubber and Plastic Products 

Paper and Printing Products 0.5 PPI Commodity for Converted Paper and Paperboard 

Products 

Aonarel 0.5 PPI Commodity for Apparel 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42461 

BILLING CODE 4120–01–C 

4. Labor-Related Share 

We define the labor-related share 

(LRS) as those expenses that are laborintensive and vary with, or are 

influenced by, the local labor market. 

Each year, we calculate a revised laborrelated share based on the relative 

importance of labor-related cost 

categories in the input price index. 

Effective for FY 2022, we proposed to 

revise and update the labor-related 

share to reflect the relative importance 

of the 2018-based SNF market basket 

cost categories that we believe are laborintensive and vary with, or are 

influenced by, the local labor market. 

For the 2018-based SNF market basket 

these are: (1) Wages and Salaries 

(including allocated contract labor costs 

as described above); (2) Employee 

Benefits (including allocated contract 

labor costs as described above); (3) 

Professional fees: Labor-related; (4) 

Administrative and Facilities Support 

Services; (5) Installation, Maintenance, 

and Repair Services; (6) All Other: 

Labor-Related Services; and (7) a 

proportion of capital-related expenses. 

We proposed to continue to include a 

proportion of capital-related expenses 

because a portion of these expenses are 

deemed to be labor-intensive and vary 

with, or are influenced by, the local 

labor market. For example, a proportion 

of construction costs for a medical 

building would be attributable to local 

construction workers’ compensation 

expenses. 

Consistent with previous SNF market 

basket revisions and rebasings, the All 

Other: Labor-related services cost 

category is mostly comprised of 

building maintenance and security 

services (including, but not limited to, 

landscaping services, janitorial services, 

waste management services services) 

and dry cleaning and laundry services. 

Because these services tend to be laborintensive and are mostly performed at 

the SNF facility or in the local area (and 

therefore, unlikely to be purchased in 

the national market), we believe that 

they meet our definition of labor-related 

services. 

These are the same cost categories we 

have included in the LRS for the 2014- 

based SNF market basket rebasing (82 

FR 36563), as well as the same 

categories included in the LRS for the 

2016-based IRF market basket (84 FR 

39087), 2016-based IPF market basket 


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Cost Category Weight Price proxy 

Machinery and Equipment 0.5 PPI Commoditv for Machinery and Equipment 

Miscellaneous Products 0.3 PPI Commodity for Finished Goods Less Food and Energy 

All Other Services 11.5 

Labor-Related Services 6.4 

Professional Fees: Labor-related 3.5 ECI for Total Compensation for Private Industry Workers in 

Professional and Related 

Installation, Maintenance, and Repair Services 0.6 ECI for Total Compensation for All Civilian workers in 

Installation, Maintenance, and Repair 

Administrative and Facilities Support 0.4 ECI for Total Compensation for Private Industry Workers in 

Office and Administrative Support 

All Other: Labor-Related Services 1.9 ECI for Total Compensation for Private Industry Workers in 

Service Occupations 

Non Labor-Related Services 5.1 

Professional Fees: Nonlabor-Related 2.0 ECI for Total Compensation for Private Industry Workers in 

Professional and Related 

Financial Services 1.3 ECI for Total Compensation for Private Industry Workers in 

Financial Activities 

Telephone Services 0.3 CPI for Telephone Services 

All Other: Nonlabor-Related Services 1.5 CPI for All Items Less Food and Energy 

Capital-Related Expenses 8.2 

Total Depreciation 3.0 

BEA's Chained Price Index for Private Fixed Investment in 

Building and Fixed Equipment 2.5 Structures, Nonresidential, Hospitals and Special Care -

vintage wei!!hted 26 years 

Movable Equipment 0.4 PPI Commodity for Machinery and Equipment - vintage 

wei!!hted 9 years 

Total Interest 2.7 

For-Profit SNFs 0.7 iBoxx - Average yield on Aaa bond - vintage weighted 24 

vears 

Government and Nonprofit SNFs 2.0 Bond Buyer - Average yield on Domestic Municipal Bonds -

vintage wei!!hted 24 vears 

Other Capital-Related Expenses 2.6 CPI for Rent of Primarv Residence 

Note: The cost weights are calculated using three decimal places. For presentation purposes, we are displaying one 

decimal, and therefore, the detailed cost weights may not add to the aggregate cost weights or to 100. 0 due to 

rounding. 

1 Contract labor is distributed to wages and salaries and employee benefits based on the share of total compensation 

that each category represents. 
42462 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

(84 FR 38445), and 2017-based LTCH 

market basket (85 FR 58910). 

As discussed in the FY 2018 SNF PPS 

proposed rule (82 FR 21040), in an effort 

to determine more accurately the share 

of nonmedical professional fees 

(included in the 2018-based SNF market 

basket Professional Fees cost categories) 

that should be included in the laborrelated share, we surveyed SNFs 

regarding the proportion of those fees 

that are attributable to local firms and 

the proportion that are purchased from 

national firms. Based on these weighted 

results, we determined that SNFs 

purchase, on average, the following 

portions of contracted professional 

services inside their local labor market: 

• 78 percent of legal services. 

• 86 percent of accounting and 

auditing services. 

• 89 percent of architectural, 

engineering services. 

• 87 percent of management 

consulting services. 

Together, these four categories 

represent 3.5 percentage points of the 

total costs for the 2018-based SNF 

market basket. We applied the 

percentages from this special survey to 

their respective SNF market basket 

weights to separate them into laborrelated and nonlabor-related costs. As a 

result, we are designating 2.9 of the 3.5 

percentage points total to the laborrelated share, with the remaining 0.6 

percentage point categorized as 

nonlabor-related. 

In addition to the professional 

services as previously listed, for the 

2018-based SNF market basket, we 

proposed to allocate a proportion of the 

Home Office/Related Organization 

Contract Labor cost weight, calculated 

using the Medicare cost reports as 

previously stated, into the Professional 

Fees: Labor-related and Professional 

Fees: Nonlabor-related cost categories. 

We proposed to classify these expenses 

as labor-related and nonlabor-related as 

many facilities are not located in the 

same geographic area as their home 

office, and therefore, do not meet our 

definition for the labor-related share 

that requires the services to be 

purchased in the local labor market. 

Similar to the 2014-based SNF market 

basket, we proposed for the 2018-based 

SNF market basket to use the Medicare 

cost reports for SNFs to determine the 

home office labor-related percentages. 

The Medicare cost report requires a SNF 

to report information regarding its home 

office provider. Using information on 

the Medicare cost report, we compared 

the location of the SNF with the 

location of the SNF’s home office. We 

proposed to classify a SNF with a home 

office located in their respective labor 

market if the SNF and its home office 

are located in the same Metropolitan 

Statistical Area (MSA). Then we 

determine the proportion of the Home 

Office/Related Organization Contract 

Labor cost weight that should be 

allocated to the labor-related share 

based on the percent of total Home 

Office/Related Organization Contract 

Labor costs for those SNFs that had 

home offices located in their respective 

local labor markets of total Home Office/ 

Related Organization Contract Labor 

costs for SNFs with a home office. We 

determined a SNF’s and its home 

office’s MSA using their zip code 

information from the Medicare cost 

report. Using this methodology, we 

determined that 21 percent of SNFs’ 

Home Office/Related Organization 

Contract Labor costs were for home 

offices located in their respective local 

labor markets. Therefore, we proposed 

to allocate 21 percent of the Home 

Office/Related Organization Contract 

Labor cost weight (0.14 percentage point 

= 0.69 percent × 21 percent) to the 

Professional Fees: Labor-related cost 

weight and 79 percent of the Home 

Office/Related Organization Contract 

Labor cost weight to the Professional 

Fees: Nonlabor-related cost weight (0.55 

percentage point = 0.69 percent × 79 

percent). The 2014-based SNF market 

basket used a similar methodology for 

allocating the Home Office/Related 

Organization Contract Labor cost weight 

to the labor-related share. 

In summary, based on the two 

allocations mentioned earlier, we 

proposed to apportion 3.0 percentage 

points of the Professional Fees (2.9 

percentage points) and Home Office/ 

Related Organization Contract Labor 

(0.1 percentage point) cost weights into 

the Professional Fees: Labor-Related 

cost category. This amount was added to 

the portion of professional fees that we 

already identified as labor-related using 

the I–O data such as contracted 

advertising and marketing costs 

(approximately 0.45 percentage point of 

total costs) resulting in a Professional 

Fees: Labor-Related cost weight of 3.5 

percent. 

Based on IHS Global Inc. 2020q4 

forecast with historical data thrugh 

2020q3, we proposed a FY 2022 laborrelated share of 70.1 percent (86 FR 

19965). 

Comment: A few commenters 

appreciated the reduction of the laborrelated share from 71.3 percent to 70.1 

percent for FY 2022. 

Response: We appreciate the 

commenters’ support. We believe that 

updating the labor-related share to 

reflect the more recent data of the 2018- 

based SNF market basket is appropriate 

to ensuring accurate payments to SNF 

providers. 

Comment: One commenter urged 

CMS to reverse the decrease in the 

labor-related share from 71.3 percent to 

70.1 percent in FY 2022. The 

commenter stated that a lower labor 

share does not reflect the experiences of 

SNFs during the PHE. They stated that 

SNFs face difficulty hiring and 

maintaining staff and to keep pace with 

labor shortages and also claim that 

average salary costs have increased over 

2020. 

Response: We disagree with the 

commenter’s request to not finalize our 

proposal to determine the labor-related 

share for FY 2022 based on the 

proposed 2018-based SNF market 

basket. We believe that updating the 

labor share to reflect more recent cost 

data of the 2018-based SNF market 

basket is a technical improvement in 

determining the labor-related share. We 

also note that the SNF labor-related 

share is based on the relative 

importance of the labor-related 

categories and therefore, accounts for 

both a change to the base year weights 

(accounting for total spending) but also 

accounts for price changes from the base 

year to the FY 2022 payment period. 

Therefore, we believe that the LRS 

based on the 2018-based market basket 

is a technical improvement. As stated in 

the FY 2022 SNF PPS proposed rule (86 

FR 19959), if more recent data became 

available (for example, a more recent 

estimate of the SNF market basket and/ 

or productivity), we would use such 

data, if appropriate, to determine the FY 

2022 SNF market basket percentage 

change, labor-related share relative 

importance, forecast error adjustment, 

or productivity adjustment in the FY 

2022 SNF PPS final rule. Based on IGI’s 

2021q2 forecast (with historical data 

through 2021q1), the labor-related share 

of the finalized 2018-based SNF market 

basket is 70.4 percent. 

Table 21 compares the FY 2022 laborrelated share based on the 2018-based 

SNF market basket relative importance 

and the FY 2021 labor-related share 

based on the 2014-based SNF market 

basket relative importance as finalized 

in the FY 2021 SNF final rule (85 FR 

47605). 


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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42463 

The FY 2022 SNF labor-related share 

is 0.9 percentage point lower than the 

FY 2021 SNF labor-related share (based 

on the 2014-based SNF market basket). 

The major reason for the lower laborrelated share is due to the incorporation 

of the 2012 Benchmark I–O data, 

primarily stemming from a decrease in 

the All Other: Labor-related services and 

Professional Fees: Labor-related services 

cost weights, and a decrease in the 

Compensation cost weight as a result of 

incorporating the 2018 MCR data. 

5. Market Basket Estimate for the FY 

2022 SNF PPS Update 

As discussed previously, beginning 

with the FY 2022 SNF PPS update, we 

are adopting the 2018-based SNF market 

basket as the appropriate market basket 

of goods and services for the SNF PPS. 

Consistent with historical practice, we 

estimate the market basket update for 

the SNF PPS based on IHS Global Inc.’s 

(IGI) forecast. IGI is a nationally 

recognized economic and financial 

forecasting firm that contracts with CMS 

to forecast the components of the market 

baskets and multifactor productivity 

(MFP). Based on IGI’s second quarter 

2021 forecast with historical data 

through the first quarter of 2021, the 

most recent estimate of the 2018-based 

SNF market basket update for FY 2022 

is 2.7 percent—which is the same 

update as the FY 2022 percent change 

of the 2014-based SNF market basket. 

Table 22 compares the 2018-based 

SNF market basket and the 2014-based 

SNF market basket percent changes. For 

the historical period between FY 2017 

and FY 2020, there is no difference in 

the average growth rates between the 

two market baskets. For the forecasted 

period between FY 2021 and FY 2023, 

the average difference in the growth 

rates between the two market baskets is 

¥0.1 percentage point. 


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TABLE 21: FY 2021 and FY 2022 SNF Labor-Related Share 

Relative importance, Relative importance, 

labor-related share, labor-related share, 

FY 2021 FY2022 

20:2 forecast 1 21:2 forecast 2 

Wages and salaries 3 51.1 51.4 

Employee benefits* 9.9 9.5 

Professional fees: Labor-related 3.7 3.5 

Administrative & facilities sunnort services 0.5 0.6 

Installation, maintenance & repair services 0.6 0.4 

All other: Labor-related services 2.6 2.0 

Capital-related (0.391) 2.9 3.0 

Total 71.3 70.4 

1 Published in the Federal Register (85 FR 47605); based on the second quarter 2020 IHS Global Inc. forecast of the 

2014-based SNF market basket, with historical data through first quarter 2020. 

2 Based on the second quarter 2021 IHS Global Inc. forecast of the 2018-based SNF market basket, with historical 

data through first quarter 2021. 

3 The Wages and Salaries and Employee Benefits cost weight reflect contract labor costs as described above. 

TABLE 22: 2018-based SNF Market Basket and 2014-based SNF Market Basket, 

Percent Changes: 2017-2023 

Fiscal Year (FY) 2018-based SNF Market Basket 2014-based SNF Market Basket 

Historical data: 

FY 2017 2.5 2.7 

FY 2018 2.6 2.6 

FY 2019 2.4 2.3 

FY 2020 2.1 2.0 

Average FY 2017-2020 2.4 2.4 

Forecast: 

FY2021 3.1 3.2 

FY2022 2.7 2.7 

FY2023 2.7 2.7 

Average FY 2021-2023 2.8 2.9 

Source: IHS Global, Inc. 2nd quarter 2021 forecast with historical data through 1st quarter 2021. 
42464 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

B. Technical Updates to PDPM ICD–10 

Mappings 

In the FY 2019 SNF PPS final rule (83 

FR 39162), we finalized the 

implementation of the Patient Driven 

Payment Model (PDPM), effective 

October 1, 2019. The PDPM utilizes 

International Classification of Diseases, 

Version 10 (ICD–10) codes in several 

ways, including to assign patients to 

clinical categories used for 

categorization under several PDPM 

components, specifically the PT, OT, 

SLP and NTA components. The ICD–10 

code mappings and lists used under 

PDPM are available on the PDPM 

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

Medicare/MedicareFee-for-ServicePayment/SNFPPS/PDPM. 

Each year, the ICD–10 Coordination 

and Maintenance Committee, a Federal 

interdepartmental committee that is 

chaired by representatives from the 

National Center for Health Statistics 

(NCHS) and by representatives from 

CMS, meets biannually and publishes 

updates to the ICD–10 medical code 

data sets in June of each year. These 

changes become effective October 1 of 

the year in which these updates are 

issued by the committee. The ICD–10 

Coordination and Maintenance 

Committee also has the ability to make 

changes to the ICD–10 medical code 

data sets effective on April 1. 

In the FY 2020 SNF PPS final rule (84 

FR 38750), we outlined the process by 

which we maintain and update the ICD– 

10 code mappings and lists associated 

with the PDPM, as well as the SNF 

GROUPER software and other such 

products related to patient classification 

and billing, so as to ensure that they 

reflect the most up to date codes 

possible. Beginning with the updates for 

FY 2020, we apply nonsubstantive 

changes to the ICD–10 codes included 

on the PDPM code mappings and lists 

through a subregulatory process 

consisting of posting updated code 

mappings and lists on the PDPM 

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

Medicare/Medicare-Fee-forServicePayment/SNFPPS/PDPM. Such 

nonsubstantive changes are limited to 

those specific changes that are necessary 

to maintain consistency with the most 

current ICD–10 medical code data set. 

On the other hand, substantive changes, 

or those that go beyond the intention of 

maintaining consistency with the most 

current ICD–10 medical code data set, 

will be proposed through notice and 

comment rulemaking. For instance, 

changes to the assignment of a code to 

a comorbidity list or other changes that 

amount to changes in policy are 

considered substantive changes for 

which we would undergo notice and 

comment rulemaking. 

This year’s proposed rule (86 FR 

19984–19985) proposed several changes 

to the PDPM ICD–10 code mappings and 

lists. We proposed the following 

changes: 

On October 1, 2020 two ICD–10 codes 

representing types of sickle-cell disease; 

D57.42 ‘‘Sickle-cell thalassemia beta 

zero without crisis’’ and D57.44 ‘‘Sicklecell thalassemia beta plus without 

crisis’’ took effect and were clinically 

mapped to the category of ‘‘Medical 

Management’’. However, there are more 

specific codes to indicate why a patient 

with sickle-cell disease would require 

SNF care, and if the patient is not in 

crisis, this most likely indicates that 

SNF care is not required. For this 

reason, we proposed to change the 

assignment of D57.42 and D57.44 to 

‘‘Return to Provider’’. 

On October 1, 2020, three new ICD– 

10 codes representing types of 

esophageal conditions; K20.81 ‘‘Other 

esophagitis with bleeding’’, K20.91, 

‘‘Esophagitis, unspecified with bleeding, 

and K21.01 ‘‘Gastro-esophageal reflux 

disease with esophagitis, with bleeding’’ 

took effect and were clinically mapped 

to ‘‘Return to Provider’’. Upon review of 

these codes, we recognize that these 

codes represent these esophageal 

conditions with more specificity than 

originally considered because of the 

bleeding that is part of the conditions 

and that they would more likely be 

found in SNF patients. Therefore, we 

proposed to change the assignment of 

K20.81, K20.91, and K21.01 to ‘‘Medical 

Management’’ in order to promote more 

accurate clinical category assignment. 

In December 2020, the CDC 

announced several additions to the ICD– 

10 Classification related to COVID–19 

that became effective on January 1, 

2021. One such code, M35.81 

‘‘Multisystem inflammatory syndrome’’, 

was assigned to ‘‘Non-Surgical 

Orthopedic/Musculoskeletal’’. However, 

Multisystem inflammatory syndrome 

can involve more than the 

musculoskeletal system. It can also 

involve the gastrointestinal tract, heart, 

central nervous system, and kidneys. 

For this reason, we proposed to change 

the assignment of M35.81 to ‘‘Medical 

Management’’ in order to promote more 

accurate clinical category assignment. 

On October 1, 2020, three new ICD– 

10 codes representing types of neonatal 

cerebral infarction were classified as 

‘‘Return to Provider.’’ These codes were 

P91.821 ‘‘Neonatal cerebral infarction, 

right side of brain,’’ P91.822, ‘‘Neonatal 

cerebral infarction, left side of brain,’’ 

and P91.823, ‘‘Neonatal cerebral 

infarction, bilateral.’’ While a neonate is 

unlikely to be a Medicare beneficiary, 

this diagnosis could continue to be used 

later in life hence placing those with 

this condition in the acute neurologic 

category. Therefore, we proposed to 

change the assignment of P91.821, 

P91.822, and P91.823 to ‘‘Acute 

Neurologic’’ in order to promote more 

accurate clinical category assignment. 

On April 1, 2020, U07.0, ‘‘Vapingrelated disorder,’’ took effect and was 

classified as a ‘‘Return to Provider’’ code 

because at the time, ‘‘Vaping-related 

disorder’’ was not considered a code 

that would be a primary diagnosis 

during a SNF stay. However, upon 

further review, we believe that many 

patients who exhibit this diagnosis 

require steroids, empiric antibiotics and 

oxygen for care which could carry over 

to the post-acute setting. For this reason, 

we proposed to change the assignment 

of U07.0 to ‘‘Pulmonary’’ classification 

in order to promote more accurate 

clinical category assignment. 

In the FY 2021 proposed rule (85 FR 

20939), we sought comments on 

additional substantive and 

nonsubstantive changes that 

commenters believed were necessary. 

We received three comments suggesting 

several changes to the ICD–10 to clinical 

category mappings. One of those 

changes was substantive, requiring 

notice and comment rulemaking. The 

commenter suggested that the FY 2020 

ICD–10 to clinical category mapping of 

G93.1 ‘‘Anoxic brain damage, not 

elsewhere classified’’ be changed to 

‘‘Acute Neurologic’’ from ‘‘Return to 

Provider,’’ which we would consider a 

substantive change. Codes that result in 

‘‘Return to Provider’’ are codes that 

cannot be used in I0020B of the MDS 

because item I0020B is used to establish 

the primary medical condition that a 

patient presents with during a SNF stay. 

Although some codes are considered 

‘‘Return to Provider’’ for payment 

purposes, they are still used to support 

the care and services used for secondary 

and co-morbidity diagnoses. The ICD– 

10 code, G93.1 was initially clinically 

mapped to ‘‘Return to provider’’ because 

‘‘Anoxic brain damage, not elsewhere 

classified’’ was non-specific and did not 

fully describe a patient’s deficits and 

may not have been an acute condition. 

However, upon further review, our 

clinicians determined that although this 

may not be an acute condition, ‘‘Anoxic 

brain damage, not elsewhere classified’’ 

would still likely result in a need for 

SNF care and is similar to conditions 

such as ‘‘Compression of the brain’’, 

‘‘Cerebral edema’’, and 

‘‘encephalopathy’’, which are mapped 

into the ‘‘Acute Neurologic’’ category. 

Therefore, we proposed to change the 


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assignment of G93.1 ‘‘Anoxic brain 

damage, not elsewhere classified’’ to 

‘‘Acute Neurologic’’. 

We invited comments on the 

proposed substantive changes to the 

ICD–10 code mappings discussed 

previously, as well as comments on 

additional substantive and nonsubstantive changes that commenters 

believe are necessary. 

The following is a summary of the 

public comments received on the 

proposed revisions to the Technical 

Updates to PDPM ICD–10 Mappings and 

our responses: 

Comment: Several commenters stated 

that they support the overall effort to 

improve accuracy and clarity within 

PDPM. One commenter specifically 

notd their appreciation for the change to 

the PDPM mapping for G93.1 ‘‘Anoxic 

brain damage, not elsewhere classified’’ 

from ‘‘Return to provider’’ to ‘‘Acute 

neurologic’’. Commenters explained that 

they treat many patients with this ICD– 

10 diagnosis and the proposed change 

would better compensate for these 

services. Another commenter supported 

the proposed change to the PDPM 

mapping for K20.81 ‘‘Other esophagitis 

with bleeding’’, K20.91, ‘‘Esophagitis, 

unspecified with bleeding, and K21.01 

‘‘Gastro-esophageal reflux disease with 

esophagitis, with bleeding’’ from 

‘‘Return to provider’’ to ‘‘Medical 

management’’. 

Response: We appreciate the positive 

comments we received that supported 

our efforts to more accurately map 

several diagnoses under PDPM. We 

agree with the comments regarding the 

remapping of G93.1 to ‘‘Acute 

neurologic’’ and K20.81 ‘‘Other 

esophagitis with bleeding’’, K20.91, 

‘‘Esophagitis, unspecified with bleeding, 

and K21.01 ‘‘Gastro-esophageal reflux 

disease with esophagitis, with bleeding’’ 

to ‘‘Medical management’ as well as the 

proposal to remap M35.81 ‘‘Multisystem 

inflammatory syndrome;’’ P91.821 

‘‘Neonatal cerebral infarction, right side 

of brain;’’ P91.822 ‘‘Neonatal infarction, 

left side of brain;’’ P91.823 ‘‘Neonatal 

cerebral infarction, bilateral;’’ U07.0 

‘‘Vaping-related disorder;’’ and G93.1 

‘‘Anoxic brain damage, not elsewhere 

classified.’’ Like the commenters, we 

believe that remapping will allow for 

more accurate payment for these 

diagnoses. 

Comment: One commenter did not 

support the proposal to change mapping 

of D57.42 ‘‘Sickle-cell thalassemia beta 

zero without crisis’’ and D57.44 ‘‘Sicklecell thalassemia beta plus without 

crisis’’ from Medical Management to 

Return to Provider. They stated an 

understanding that in some cases, there 

may be a more specific ICD–10 code that 

may be available, if supported by the 

physician. However, they stated that 

residents who have been diagnosed with 

only D57.42 or D57.44 and not a further 

specified code may still require a skilled 

level of care in the SNF for this 

condition. They stated that since a 

particular diagnosis, in and of itself, 

cannot meet the criteria of a skilled 

level of care, they stated it would be 

appropriate to continue to map D57.42 

and D57.44 to the Medical Management 

clinical category. 

Response: As the commenter 

explained, a diagnosis, in and of itself, 

may not meet the criteria of a skilled 

level of care. We agree with that notion. 

Therefore, we continue to believe that 

the diagnosis codes of only D57.42 or 

D57.44 do not provide enough specific 

information to be the primary diagnosis 

used for payment. If there is a symptom 

or condition that is a result of this 

diagnosis, that symptom or condition 

should be coded on the MDS and would 

be able to be mapped for PDPM 

payment. We would note that there is 

no limitation on which ICD–10 

diagnoses a provider can include on the 

MDS 3.0. However, there are specific 

diagnoses which are more appropriate 

for PDPM mapping and are used for 

payment as the primary diagnosis under 

PDPM. 

Comment: One commenter suggested 

additional changes to the ICD–10 code 

mappings and comorbidity lists that 

were outside the scope of this 

rulemaking. As mentioned previously, 

this commenter stated their support for 

changing K20.81, K20.91, and K21.01 

from the ‘‘Return to Provider’’ mapping 

to ‘‘Medical Management.’’ This 

commenter also requested that we also 

consider remapping the following 

similar diagnosis codes that frequently 

require SNF skilled care, from Return to 

Provider to Medical Management: 

K22.11 ‘‘Ulcer of esophagus with 

bleeding’’, K25.0 ‘‘Acute gastric ulcer 

with hemorrhage’’, K25.1’’Acute gastric 

ulcer with perforation’’, K25.2 ‘‘Acute 

gastric ulcer with both hemorrhage and 

perforation’’, K26.0 ‘‘Acute duodenal 

ulcer with hemorrhage’’, K26.1 ‘‘Acute 

duodenal ulcer with perforation’’, K26.2 

‘‘Acute duodenal ulcer with both 

hemmhorage and perforation’’, K27.0 

‘‘Acute peptic ulcer, site unspecified 

with hemorrhage’’, K27.1 ‘‘Acute peptic 

ulcer, site unspecified with 

perforation’’, K27.2 ‘‘Acute peptic ulcer, 

site unspecified with both hemorrhage 

and perforation’’, K28.0 ‘‘Acute 

gastrojejunal ulcer with hemorrhage’’, 

K28.1 ‘‘Acute gastrojejunal ulcer with 

perforation’’, K28.2 ‘‘Acute gastrojejunal 

ulcer with both hemorrhage and 

perforation’’, and K29.01 ‘‘Acute 

gastritis with bleeding.’’ 

They also requested that we consider 

remapping M62.81 ‘‘Muscle weakness 

(generalized)’’ from Return to Provider 

to Non-orthopedic Surgery with the 

rationale that frail elderly beneficiaries 

are often admitted to the SNF following 

hospitalization for a significant 

infection (for example, pneumonia, 

COVID–19, urinary tract infection, other 

respiratory infection). This commenter 

explained that there is currently no 

sequela or late-effects ICD–10 code 

available when such beneficiaries 

require skilled nursing and therapy due 

to the late effects of the resolved 

infection. The active infection may no 

longer exist, but muscle weakness is 

often the primary diagnosis the 

physician identifies as requiring skilled 

care for these frail elderly beneficiaries. 

Additionally, this commenter asked that 

we consider remapping R62.7 ‘‘Adult 

failure to thrive’’ from Return to 

Provider to Medical Management. 

According to this commenter, 

physicians often diagnose adult failure 

to thrive when a resident has been 

unable to have oral intake sufficient for 

survival. Typically, this diagnosis is 

appended when the physician has 

determined that a feeding tube should 

be considered to provide sufficient 

intake for survival. According to the 

commenter, it would then appropriately 

become the primary diagnosis for a 

skilled stay. 

Response: We note that the changes 

suggested by the commenter are outside 

the scope of this rulemaking, and will 

not be addressed in this rule. We will 

further consider the suggested changes 

to the ICD–10 code mappings and 

comorbidity lists and may implement 

them in the future as appropriate. To the 

extent that such changes are nonsubstantive, we may issue them in a 

future subregulatory update if 

appropriate; however, if such changes 

are substantive changes, in accordance 

with the update process established in 

the FY 2020 SNF PPS final rule, such 

changes must undergo full notice and 

comment rulemaking, and thus may be 

included in future rulemaking. See the 

discussion of the update process for the 

ICD–10 code mappings and lists in the 

FY 2020 SNF PPS final rule (84 FR 

38750) for more information. 

After considering public comments, 

we are finalizing the revisions as 

proposed. 


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C. Recalibrating the PDPM Parity 

Adjustment 

1. Background 

On October 1, 2019, we implemented 

the Patient Driven Payment Model 

(PDPM) under the SNF PPS, a new casemix classification model that replaced 

the prior case-mix classification model, 

the Resource Utilization Groups, 

Version IV (RUG–IV). As discussed in 

the FY 2019 SNF PPS final rule (83 FR 

39256), as with prior system transitions, 

we proposed and finalized 

implementing PDPM in a budget neutral 

manner. This means that the transition 

to PDPM, along with the related policies 

finalized in the FY 2019 SNF PPS final 

rule, were not intended to result in an 

increase or decrease in the aggregate 

amount of Medicare payment to SNFs. 

We believe ensuring parity is integral to 

the process of providing ‘‘for an 

appropriate adjustment to account for 

case mix’’ that is based on appropriate 

data in accordance with section 

1888(e)(4)(G)(i) of the Act. Section V.I. 

of the FY 2019 SNF PPS final rule (83 

FR 39255 through 39256) discusses the 

methodology that we used to implement 

PDPM in a budget neutral manner. 

Specifically, we multiplied each of the 

PDPM case-mix indexes (CMI) by an 

adjustment factor that was calculated by 

comparing total payments under RUG– 

IV, using FY 2017 claims and 

assessment data (the most recent final 

claims data available at the time), and 

what we expected total payments would 

be under the then proposed PDPM 

based on that same FY 2017 claims and 

assessment data. In the FY 2020 SNF 

PPS final rule (84 FR 38734 through 

38735), we finalized an updated 

standardization multiplier and parity 

adjustment based on FY 2018 claims 

and assessment data. Through this 

comparison, and as discussed in the FY 

2020 SNF PPS final rule, this analysis 

resulted in an adjustment factor of 1.46, 

by which all the PDPM CMIs were 

multiplied so that total estimated 

payments under PDPM would be equal 

to total actual payments under RUG–IV, 

assuming no changes in the population, 

provider behavior, and coding. By 

multiplying each CMI by 1.46, the CMIs 

were inflated by 46 percent in order to 

achieve budget neutrality. 

A similar type of adjustment was used 

when we transitioned from RUG–III to 

RUG–IV in FY 2011. However, as 

discussed in the FY 2012 SNF PPS final 

rule (76 FR 48492 through 48500), we 

observed that once actual RUG–IV 

utilization data became available, the 

actual RUG–IV utilization patterns 

differed significantly from those we had 

projected using the historical data that 

grounded the RUG–IV parity 

adjustment. As a result, in the FY 2012 

SNF PPS final rule, we used actual FY 

2011 RUG–IV utilization data to 

recalibrate the RUG–IV parity 

adjustment. Based on the use of FY 2011 

RUG–IV utilization data, we decreased 

the RUG–IV parity adjustment applied 

to the nursing CMIs for all RUG–IV 

therapy groups from an adjustment 

factor of 61 percent to an adjustment 

factor of 19.84 percent (while 

maintaining the original 61 percent total 

nursing CMI increase for all non-therapy 

RUG–IV groups). As a result of this 

recalibration, FY 2012 SNF PPS rates 

were reduced by 12.5 percent, or $4.47 

billion, in order to achieve budget 

neutrality under RUG–IV prospectively. 

Since PDPM implementation, we have 

closely monitored PDPM utilization 

data to ascertain, among other things, if 

the PDPM parity adjustment provided 

for a budget neutral transition to this 

new case-mix classification model. 

Similar to what occurred in FY 2011 

with RUG–IV implementation, we have 

observed significant differences between 

expected SNF PPS payments and casemix utilization, based on historical data, 

and the actual SNF PPS payments and 

case-mix utilization under PDPM, based 

on FY 2020 data. As a result, it would 

appear that rather than simply achieving 

parity, the FY 2020 parity adjustment 

may have inadvertently triggered a 

significant increase in overall payment 

levels under the SNF PPS. We believed 

that, based on the data from this initial 

phase of PDPM, a recalibration of the 

PDPM parity adjustment may be 

warranted to ensure that the adjustment 

serves its intended purpose to make the 

transition between RUG–IV and PDPM 

budget neutral. 

However, we also acknowledged in 

the proposed rule that the pandemicrelated PHE for COVID–19, which began 

during the first year of PDPM and has 

continued into at least part of FY 2021, 

has had a likely impact on SNF PPS 

utilization data. Further, following the 

methodology utilized in calculating the 

initial parity adjustment, we typically 

would use claims and assessment data 

for a given year to classify patients 

under both the current system and the 

prior system to compare aggregate 

payments and determine an appropriate 

adjustment factor to achieve parity. 

When we performed a similar 

recalibration of the RUG–IV parity 

adjustment, for example, we used data 

from FY 2011, the first year of RUG–IV 

implementation, as the basis for 

recalibrating the RUG–IV parity 

adjustment. However, in addition to the 

aforementioned potential issues with 

the FY 2020 SNF utilization data arising 

from the PHE for COVID–19, we were 

concerned that given the significant 

differences in both patient assessment 

requirements and payment incentives 

between RUG–IV and PDPM, using the 

same methodology we have used in the 

past to calculate a recalibrated PDPM 

parity adjustment could lead to a 

potentially inaccurate recalibration. 

As described in the FY 2022 SNF 

proposed rule, we presented some of the 

results of our PDPM data monitoring 

efforts and a potential recalibration 

methodology intended to address the 

issues presented above. First, it was 

important to provide transparency on 

the observed impacts of PDPM 

implementation, as we believed there 

have been significant changes observed 

in SNF utilization that are tied strictly 

to PDPM and not the PHE for COVID– 

19. Second, we wished to make clear 

why we believed that the typical 

methodology for recalibrating the parity 

adjustment may not provide an accurate 

recalibration under PDPM. Finally, we 

viewed this as an opportunity to seek 

comment on a path forward for 

recalibrating the PDPM parity 

adjustment to ensure that PDPM is 

implemented in a budget neutral 

manner, as intended. 

2. FY 2020 Changes in SNF Case-Mix 

Utilization 

FY 2020 was a year of significant 

change under the SNF PPS. In addition 

to implementing PDPM, a national PHE 

for COVID–19 was declared. With the 

announcement of the PHE for COVID– 

19, we also announced a number of 

waivers that impacted SNF operations 

and the population of Medicare 

beneficiaries who were able to access 

the Part A SNF benefit. Most notably, 

under authority granted us by section 

1812(f) of the Act, we issued a waiver 

of section 1861(i) of the Act, specifically 

the requirement that in order for a SNF 

stay to be covered by Medicare, a 

beneficiary must have a prior inpatient 

hospital stay of not less than 3 

consecutive days before being admitted 

to the Part A SNF stay. Additionally, 

this waiver also allowed certain 

beneficiaries renewed SNF coverage 

without first having to start a new 

benefit period. The section 1812(f) 

waiver, particularly the component that 

permits beneficiaries to access the Part 

A SNF benefit without a prior 

hospitalization, allowed beneficiaries 

who would not typically be able to 

access the Part A SNF benefit to receive 

a Part A covered SNF stay (for example, 

long term care nursing home patients 

without any prior hospitalization). A 

key aspect of our suggested potential 

methodology for recalibrating the PDPM 


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parity adjustment involved parsing out 

the impact of these waivers and the 

different population of beneficiaries that 

had access to the SNF benefit as result 

of these waivers from the population of 

beneficiaries that would have been 

admitted to SNFs subsequent to PDPM 

implementation without these waivers, 

as well as differences in the type of care 

these patients received. 

We noted that while the PHE for 

COVID–19 clearly had impacts on 

nursing home care protocols and many 

other aspects of SNF operations, the 

relevant issue for pursuing a 

recalibration of the PDPM parity 

adjustment is whether or not these 

changes caused the SNF case-mix 

distribution to be distinctly different 

from what it would have been were it 

not for the PHE for COVID–19. In other 

words, while different people were able 

to access the Part A SNF benefit than 

would typically be able to do so, the 

issue was whether or not the relative 

percentage of beneficiaries in each 

PDPM group was different than what 

those percentages would have been 

were it not for the PHE for COVID–19 

and related waivers. We solicited 

comments on whether and how 

stakeholders believed that the PHE for 

COVID–19 impacted the distribution of 

patient case-mix. 

In the proposed rule, we 

acknowledged the impact of COVID–19 

on SNF utilization data by removing 

those using a PHE-related waiver and 

those with a COVID–19 diagnosis from 

our data set. In FY 2020, only 

approximately 9.8 percent of SNF stays 

included a COVID–19 ICD–10 diagnosis 

code either as a primary or secondary 

diagnosis, while 15.6 percent of SNF 

stays utilized a section 1812(f) waiver 

(with the majority of these cases using 

the prior hospitalization waiver), as 

identified by the presence of a ‘‘DR’’ 

condition code on the SNF claim. As 

compared to prior years, when 

approximately 98 percent of SNF 

beneficiaries had a qualifying prior 

hospital stay, approximately 87 percent 

of SNF beneficiaries had a qualifying 

prior hospitalization in FY 2020. These 

general statistics are important, as they 

highlight that while the PHE for 

COVID–19 certainly impacted many 

aspects of nursing home operations, the 

overwhelming majority of SNF 

beneficiaries entered into Part A SNF 

stays in FY 2020 as they would have in 

any other year; that is, without using a 

PHE-related waiver, with a prior 

hospitalization, and without a COVID– 

19 diagnosis. 

Our data analysis found that even 

after removing those using a PHErelated waiver and those with a COVID– 

19 diagnosis from our data set, the 

observed inadvertent increase in SNF 

payments since PDPM was 

implemented was approximately the 

same. This finding suggests that the 

significant changes observed in SNF 

utilization are tied strictly to PDPM and 

not the PHE for COVID–19, as the 

‘‘new’’ population of SNF beneficiaries 

(that is, COVID–19 patients and those 

using a section 1812(f) waiver) did not 

appear to be the cause of the increase in 

SNF payments after implementation of 

PDPM. 

Moreover, we presented evidence that 

PDPM alone impacted certain aspects of 

SNF patient classification and care 

provision. For example, through FY 

2019, SNF patients received an average 

of approximately 91 therapy minutes 

per day. Beginning concurrently with 

PDPM implementation (and well before 

the onset of the pandemic), the average 

number of therapy minutes SNF 

patients received per day dropped to 

approximately 62 minutes, a decrease of 

over 30 percent. Similarly, we also 

observed an increase in nonindividualized modes of therapy 

provision beginning with PDPM 

implementation. While the percentage 

of SNF stays that included concurrent or 

group therapy was approximately 1 

percent for each of these therapy modes 

prior to FY 2020, these numbers rose to 

approximately 32 percent and 29 

percent, respectively, concurrent with 

PDPM implementation. Notably, when 

the PHE for COVID–19 was declared in 

April 2020, these numbers then dropped 

to 8 percent and 4 percent, respectively, 

highlighting an impact of the PHE for 

COVID–19 on SNF care provision and 

utilization. 

We also noted that while the increases 

in concurrent and group therapy 

utilization were anticipated prior to 

PDPM implementation based on 

comments on the FY 2019 and FY 2020 

SNF PPS proposed rules, we maintain 

the belief that the unique characteristics 

and goals of each SNF patient should 

drive patient care decisions and we did 

not identify any significant changes in 

health outcomes for SNF patients due to 

PDPM implementation. For example, we 

observed no significant changes in the 

percentage of stays with falls with major 

injury, the percentage of stays ending 

with Stage 2–4 or unstageable pressure 

ulcers or deep tissue injury, the 

percentage of stays readmitted to an 

inpatient hospital setting within 30 days 

of SNF discharge, or other similar 

metrics. As we stated in the FY 2020 

SNF PPS final rule (84 FR 38748), we 

believe that financial motives should 

not override the clinical judgment of a 

therapist or therapy assistant to provide 

less than appropriate therapy, and we 

will continue to monitor these and other 

metrics to identify any adverse trends 

accompanying the implementation of 

PDPM. 

These changes in therapy provision 

highlight the reasons we believed that 

the typical methodology for 

recalibrating a parity adjustment would 

not be appropriate in the context of 

PDPM and may lead to an 

overcorrection. As discussed previously 

in this final rule and in the FY 2012 

SNF PPS final rule (76 FR 26371), we 

would typically utilize claims and 

assessment data from a given period 

under the new payment system, classify 

patients under both the current and 

prior payment model using this same set 

of data, compare aggregate payments 

under each payment model, and 

calculate an appropriate adjustment 

factor to achieve budget neutrality. 

However, given the significant changes 

in therapy provision since PDPM 

implementation, we found that using FY 

2020 patient assessment data collected 

under PDPM would lead to a significant 

underestimation of RUG–IV case mix for 

purposes of determining what aggregate 

payments would have been under RUG– 

IV for the same period. 

We invited comments on the 

information presented above, as well as 

on the potential impact of using the 

reported FY 2020 patient assessment 

data from the MDS to reclassify SNF 

beneficiaries under RUG–IV, consistent 

with the same type of recalibration 

methodology we have used for prior 

system transitions. 

3. Methodology for Recalibrating the 

PDPM Parity Adjustment 

In this section, we discuss the 

methodology we considered in the FY 

2022 proposed rule for recalibrating the 

PDPM parity adjustment. Table 23 

provides the expected and actual 

average PDPM CMI expected for each of 

the PDPM rate components based on 

data from FY 2019 and FY 2020. First, 

we calculated the expected average CMI 

for each component by summing the 

expected PDPM CMI for each day of 

service in FY 2019 and then dividing by 

the total number of days of service in FY 

2019. Next, we provided two separate 

calculations for the actual average 

PDPM CMI, both for the full SNF 

population and for the SNF population 

after exclusions due to COVID 

(henceforth referred to as the ‘‘subset 

population’’), by summing the CMI for 

each day of service in FY 2020 and then 

divided this by the total number of days 

of service in FY 2020. As discussed 

above, we excluded SNF stays where 

the patient was diagnosed with COVID– 


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19 or the stay utilized a PHE for COVID– 

19 related waiver, as identified by the 

presence of a ‘‘DR’’ condition code on 

the associated SNF claim. 

The results presented in Table 23 

show that the average CMI for both the 

full and subset FY 2020 populations 

was slightly lower than expected for the 

PT and OT rate components, and much 

higher than expected for the SLP, 

Nursing, and NTA components. We 

believed that the significant increases of 

22.6 percent, 16.8 percent, and 5.6 

percent in average case-mix, 

respectively, for the full FY 2020 SNF 

population was primarily responsible 

for the inadvertent increase in spending 

under PDPM. Further, given that we 

observed similar increases in the 

average CMI for these components in 

the subset FY 2020 SNF population, we 

believed that these increases in average 

case-mix for these components were the 

result of PDPM and not the PHE for 

COVID–19. We invited comments on 

this approach and the extent to which 

commenters believed that the PHE for 

COVID–19 may have impacted the 

PDPM case-mix distribution in ways not 

captured in Table 23 or in the 

discussion provided here. 

Historically, our basic methodology 

for recalibrating the parity adjustment 

has been to compare total payments 

under the new case-mix model with 

what total payments would have been 

under the prior case-mix model, were 

the new model not implemented. In the 

context of the PDPM, this meant 

comparing total FY 2020 payments 

under PDPM to what FY 2020 payments 

would have been under RUG–IV if 

PDPM were not implemented. In order 

to calculate expected total payments 

under RUG–IV, we used the percentage 

of stays in each RUG–IV group in FY 

2019 and multiplied these percentages 

by the total number of FY 2020 days of 

service. We then multiplied the number 

of days for each RUG–IV group by the 

RUG–IV per diem rate, which we 

obtained by inflating the FY 2019 SNF 

PPS RUG–IV rates by the FY 2020 

market basket update factor. The total 

payments under RUG–IV also accounted 

for the AIDS add-on under RUG–IV and 

a provider’s FY 2020 urban or rural 

status. In order to calculate the actual 

total payments under PDPM, we used 

data reported on FY 2020 claims. 

Specifically, we used the Health 

Insurance Prospective Payment System 

(HIPPS) code on the SNF claim to 

identify the patient’s case-mix 

assignment and associated CMIs, 

utilization days on the claim to 

calculate stay payments and the variable 

per diem adjustment, the presence of an 

HIV diagnosis on the claim to account 

for the PDPM AIDS add-on, and a 

provider’s urban or rural status. As with 

the analysis for Table 23, we calculated 

total payments both for the full and 

subset FY 2020 SNF populations. 

We believed that this methodology 

provided a more accurate representation 

of what RUG–IV payments would have 

been in FY 2020, were it not for the 

change in payment incentives and care 

provision precipitated by PDPM 

implementation, than using data 

reported under PDPM to reclassify these 

patients under RUG–IV. In particular, 

given the reduction in therapy 

utilization under PDPM as compared to 

RUG–IV, using the therapy utilization 

data reported under PDPM to reclassify 

SNF patients back into RUG–IV groups 

would produce a case-mix distribution 

that would be significantly different 

from the RUG–IV case-mix distribution 

we would have expected were it not for 

PDPM implementation. Since the 

reduction in therapy would lead to a 

reduction in the RUG–IV case-mix 

assignments (for example, Ultra-High 

and Very-High Rehabilitation 

assignments are not nearly as prevalent 

using PDPM-reported data as they are 

using data that existed prior to PDPM), 

this would lead to an underestimation 

of what RUG–IV payments would have 

been in FY 2020. This, in turn, would 

lead to an overcorrection in 

recalibrating the parity adjustment due 

to the low estimated total RUG–IV 

payments. Additionally, given the 

significant changes in the patient 

assessment schedule, specifically the 

removal of the Change of Therapy Other 

Medicare Required Assessment, we 

cannot know if the patient would 

continue to remain classified in the 

RUG–IV group into which the patient 

classified on the 5-day assessment 

beyond that assessment window. In 

other words, without having an interim 

assessment between the 5-day 

assessment and the patient’s discharge 

from the facility, we would be unable to 

determine if the RUG–IV group into 

which the patient classified on the 5- 

day assessment changed during the stay, 

or if the patient continued to receive an 

amount of therapy services consistent 

with the initial RUG–IV classification. 

As a result, using reported data under 

PDPM could lead to a reclassification of 

patients under RUG–IV that is not 

consistent with how patients would 

have been classified under RUG–IV if 

PDPM had not been implemented. As 

such, we believed that using the FY 

2019 RUG–IV case-mix distribution as a 

proxy for what the RUG–IV case-mix 

distribution would have been in FY 

2020 were it not for PDPM 

implementation provides a more 

accurate calculation of what total RUG– 

IV payments would have been during 

FY 2020 absent PDPM implementation. 

Our analysis identified a 5.3 percent 

increase in aggregate spending under 

PDPM as compared to expected total 

payments under RUG–IV for FY 2020 


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TABLE 23: Average Case-Mix Index, Expected and Actual, by Component 

Expected CMI (FY ActualCMI ActualCMI 

(FY 2020 without DR 2019 Estimate) (FY 2020) orCOVID) 

PT 1.53 1.50 1.52 

OT 1.52 1.51 1.52 

SLP 1.39 1.71 1.67 

Nursing 1.43 1.67 1.62 

NTA 1.14 1.20 1.21 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42469 

when considering the full SNF 

population, and a 5 percent increase in 

aggregate spending under PDPM for FY 

2020 when considering the subset 

population. Although these results are 

similar, in light of the potential 

differences in the PDPM case-mix 

distribution that may have been 

precipitated by the admission of 

patients diagnosed with COVID–19 and 

patients whose stays utilized a PHErelated waiver, we believe it would be 

more appropriate to pursue a 

recalibration using the subset 

population. Since the initial increase to 

the PDPM CMIs to achieve budget 

neutrality applied equally across all 

case-mix adjusted components, we 

believed it would be appropriate, in the 

event an adjustment is made, to adjust 

the CMIs across all such components in 

equal measure. Using the methodology 

described above, the resultant PDPM 

parity adjustment factor would be 

lowered from 46 percent to 37 percent 

for each of the PDPM case-mix adjusted 

components. If we applied this 

methodology for FY 2022, we estimated 

a reduction in SNF spending of 5 

percent, or approximately $1.7 billion. 

Based on the above discussion and 

analysis, we described a potential path 

towards a recalibration of the PDPM 

parity adjustment. We invited 

comments on our methodology, 

particularly on the use of the FY 2019 

RUG–IV case-mix distribution to 

calculate expected FY 2020 SNF 

payments and on using the subset FY 

2020 SNF population. 

As we noted in the FY 2012 SNF PPS 

final rule (76 FR 48493), we believe it 

is imperative that we act in a wellconsidered but expedient manner once 

excess payments are identified, as we 

did in FY 2012. However, despite the 

importance of ensuring that PDPM is 

budget neutral going forward, we 

acknowledged that applying such a 

significant reduction in payments in a 

single year without time to prepare for 

the reduction in revenue could create a 

financial burden for providers. We 

therefore considered two potential 

mitigation strategies to ease the 

transition to prospective budget 

neutrality in the event an adjustment is 

finalized: Delayed implementation and 

phased implementation. 

With regard to a delayed 

implementation strategy, this would 

mean that we would implement the 

reduction in payment, or some portion 

of the reduction in payment if combined 

with a phased implementation approach 

described below, in a later year than the 

year in which the reduction is finalized. 

For example, considering the 5 percent 

reduction discussed above, if this 

reduction was finalized in FY 2022 with 

a 1 year delayed implementation, this 

would mean that the full 5 percent 

reduction would be prospectively 

applied to the PDPM CMIs in FY 2023. 

If the reduction was finalized in FY 

2022 with a 2 year delayed 

implementation, then the full 5 percent 

reduction in the PDPM CMIs would be 

applied prospectively beginning in FY 

2024. This type of strategy on its own 

does not serve to mitigate the overall 

amount of the reduction in a single year, 

but rather serves to provide facilities 

with time to prepare for the impending 

reduction in payments. We solicited 

comments on whether stakeholders 

believe that, in the event we finalize the 

parity adjustment recalibration, we 

should finalize this recalibration with a 

delayed implementation. Additionally, 

to the extent that stakeholders believe 

that a delayed implementation would be 

warranted, we solicited comments on 

the appropriate length of the delay. 

With regard to a phased 

implementation strategy, this would 

mean that the amount of the reduction 

would be spread out over some number 

of years. Such an approach helps to 

mitigate the impact of the reduction in 

payments by applying only a portion of 

the reduction in a given year. For 

example, if we were to use a 2-year 

phased implementation approach to the 

5 percent reduction discussed above, 

this would mean that the PDPM CMIs 

would be reduced by 2.5 percent in the 

first year of implementation and then 

reduced by the remaining 2.5 percent in 

the second and final year of 

implementation. So, for example, if this 

adjustment was finalized for FY 2022, 

then the PDPM CMIs would be reduced 

by 2.5 percent in FY 2022 and then 

reduced by an additional 2.5 percent in 

FY 2023. We note that the number of 

years for a phased implementation 

approach could be as little as 2 years but 

as long as necessary to appropriately 

mitigate the yearly impact of the 

reduction. For example, we could 

implement a 5-year phased approach for 

this reduction, which would apply a 

one percent reduction to the PDPM 

CMIs each year for 5 years. We solicited 

comments on the need for a phased 

implementation approach to 

recalibrating the PDPM parity 

adjustment, as well as on the 

appropriate length of such an approach. 

We could also use a combination of 

both mitigation strategies. For example, 

we could finalize a 2 year phased 

approach with a 1 year delayed 

implementation. Using FY 2022 as the 

hypothetical year in which such an 

approach could be finalized, this would 

mean that there would be no reduction 

to the PDPM CMIs in FY 2022, a 2.5 

percent reduction to the PDPM CMIs in 

FY 2023, and then a 2.5 percent 

reduction in the PDPM CMIs in FY 

2024. We solicited comments on the 

possibility of combining these 

approaches and what stakeholders 

believe would be appropriate to mitigate 

the impact of the reduction in SNF PPS 

payments. 

We noted that for any of these 

options, the adjustment would be 

applied prospectively, and the case mix 

indexes would not be adjusted to 

account for deviations from budget 

neutrality in years before the payment 

adjustments are implemented. 

We invited comments on the 

methodology described above for 

recalibrating the PDPM parity 

adjustment and the strategies described 

above for mitigating the impact of 

implementing such an adjustment, in 

the event we finalize a recalibration. 

Comment: The majority of 

commenters strongly objected to our 

methodology and the possibility of 

finalizing the recalibration in FY 2022 

during the COVID–19 PHE. We received 

comments about this issue both from 

individual commenters and multiple 

letter writing campaigns. Commenters 

suggested that FY 2020 data was not 

representative because PDPM was only 

in place for 5 months, from October 

2019 to February 2020, prior to the 

beginning of the PHE. They outlined 

several ways that the PHE affected FY 

2020 data in ways not accounted for by 

our subset population methodology, 

which excluded patients with a COVID– 

19 diagnosis or who utilized a PHErelated disaster waiver. Their critiques 

of our methodology fall into two 

categories: That we did not fully 

account for the acuity of patients with 

COVID–19 and that we did not fully 

account for the overall effect of the PHE 

across all patients. 

First, commenters were concerned 

that our analysis did not account for the 

impact of COVID–19 on overall patient 

case-mix and acuity. Some commenters 

suggested that we may have missed 

COVID–19 cases from the early months 

of the PHE because there was no 

COVID–19 specific diagnosis code 

available before April 2020 and because 

providers were unaware of or confused 

about waiver utilization. Additionally, 

the well-documented shortage of 

COVID–19 testing led to SNFs being 

unable to confirm and report COVID–19 

cases despite higher than average 

caseloads in upper respiratory 

infections and associated increases in 

patient acuity. In light of this, one 

commenter suggested that we analyze 

the FY 2020 data for a higher-thanVerDate Sep<11>2014 20:18 Aug 03, 2021 Jkt 253001 PO 00000 Frm 00047 Fmt 4701 Sfmt 4700 E:\FR\FM\04AUR3.SGM 04AUR3

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expected burden of upper respiratory 

infection cases and exclude these sicker 

patients from the parity adjustment 

analysis. Finally, commenters were 

concerned that PDPM did not fully 

capture clinically appropriate sequelae 

or adequately reimburse intensive 

nursing care provided to COVID–19 

patients who were cohorted together 

instead of in a single room. 

Second, commenters stated that the 

PHE raised the clinical complexity of all 

residents regardless of COVID–19 illness 

or diagnosis, therefore skewing the casemix data for FY 2020. Because many 

providers chose to halt elective 

surgeries during a portion of the PHE, 

the residents admitted were the most 

acute who could not be cared for at 

home. Limitations regarding visitation 

led to higher levels of mood distress, 

cognitive decline, mobility decline, 

change in appetite, weight loss requiring 

diet modifications, and compromised 

skin integrity. Occupancy dropped 

significantly compared to pre-pandemic 

levels (many commenters reported an 

approximate 20 percent decrease) and 

commenters believe it could take up to 

2 or 3 years to return to a pre-pandemic 

level census. One commenter expressed 

concern with the accuracy of the CMIs 

due to having a smaller sample size due 

to excluding COVID cases, stating that 

these factors would have impacted 

average CMI calculations and would not 

be representative of an average SNF 

yearly census. 

Overall, the majority of commenters 

agreed that it was difficult to assess true 

PDPM case-mix distribution due to only 

a very short period before the PHE, and 

therefore believed that a longer time 

period of data outside of a PHE 

environment is necessary to determine 

whether a parity adjustment is required. 

They urged CMS to take more time for 

deliberation and utilize a period of data 

outside of a PHE environment, defined 

by one commenter as beginning 90 days 

after the end of the PHE and continuing 

for one year thereafter. 

Some commenters supported the 

analytic approach we described in the 

proposed rule and concurred with the 

need for a parity adjustment. While 

MedPAC recommended proceeding 

cautiously and making no update for FY 

2022, they found our data analysis 

approach to be reasonable and urged 

CMS to keep an account of 

overpayments that would have been 

made in establishing future updates. 

Several commenters indicated that they 

would support a future parity 

adjustment, if warranted, if CMS 

combines delayed implementation with 

a phased-in approach. One commenter 

recommended proceeding with the 

parity adjustment for FY 2022 due 

primarily to behavioral changes 

exhibited by SNFs at the outset of 

PDPM, such as the reduction in therapy 

services provided to SNF patients. 

Response: We thank the commenters 

for their feedback. In light of these 

comments, as well as the importance of 

addressing any existing overpayments 

under the SNF PPS, we intend to utilize 

these comments to refine the data we 

have collected in developing a proposed 

methodology that will be included in 

the FY 2023 SNF PPS Proposed Rule. 

Comment: Several commenters made 

suggestions for revisions to our 

methodology and opposed the 

possibility of finalizing the recalibration 

in FY 2022 for reasons unrelated to the 

COVID–19 PHE. Some commenters 

pointed out that our analysis did not 

account for the effect of CMS’ 

instruction to assess all patients anew in 

October 2019 using the PDPM MDS 

assessment, which would likely have 

elevated NTA scores due to restarting 

the stay at the highest payment level, 

even though some patients assessed may 

have been in the middle or end of their 

Medicare Part A coverage. One 

commenter supported our methodology, 

stating that it would be inappropriate to 

attempt to reclassify the data set 

associated with the FY 2020 SNF 

population using the RUG–IV model, 

given the significant differences 

between the two and the changes 

implemented to the patient assessment 

schedule. 

Some commenters suggested that 

budget neutrality may not be an 

attainable goal because less attention 

was paid to diagnosis coding under 

RUG–IV. One commenter stated that the 

exact opposite occurred of the 

assumption stated in the proposed rule 

regarding no changes in the population, 

provider behavior, and coding, as PDPM 

represented a significant change in how 

nursing homes should manage and 

document care for Medicare Part A 

residents. The same commenter stated 

that by transitioning to a system where 

therapy minutes primarily drove 

reimbursement to a system where a 

more holistic coding approach 

established payment, one would expect 

more accurate coding. This change is 

better for patient care and does not 

indicate that conditions such as 

depression and swallowing difficulties 

were not treated prior to PDPM, but 

rather indicates providers are 

demonstrating more accurate 

documentation to support the care 

already being given for these conditions. 

Response: We thank the commenters 

for their feedback and will take these 

recommendations into consideration for 

the FY 2023 SNF PPS proposed rule. 

However, we remind commenters that 

the methodology used to identify the 

magnitude of the adjustment necessary 

to achieve parity does not rely on the 

actual dollar amounts paid under 

PDPM, but rather a comparison between 

expected SNF PPS payments, based on 

historical case-mix utilization data 

under RUG–IV, to SNF PPS payments 

based on actual case-mix utilization 

data collected after PDPM 

implementation. 

Comment: Some commenters stated 

that expenditures for their facilities did 

not support a 5 percent potential parity 

adjustment. One commenter calculated 

a 4.5 percent increase, inclusive of the 

2.8 percent market basket increase, in 

overall payment under PDPM as 

compared to the RUG–IV. Another 

commenter stated that the PDPM budget 

neutrality adjustment did not take into 

account the 2 percent reduction (60 

percent of which would be available to 

be earned back as a value-based 

incentive payment) to be put in the 

Medicare trust fund from the SNF VBP 

program. 

Response: We appreciate these 

comments. As described in the 

proposed rule, our methodology 

included the subset population of SNF 

beneficiaries without a COVID–19 

diagnosis or a PHE-related disaster 

waiver, across all facilities. We 

understand that there may be variation 

between facilities, though the parity 

adjustment is calculated and applied at 

a systemic level to all facilities paid 

under the SNF PPS. We emphasize that 

budget neutrality refers only to the 

transition between case-mix 

classification models (in this case, from 

RUG–IV to PDPM) and is not intended 

to include unrelated SNF policies such 

as the market basket increase or the SNF 

VBP program. 

Comment: One commenter supported 

delaying the PDPM parity adjustment 

due to the proposed substantive changes 

to the ICD–10 diagnosis code mapping, 

stating that these changes may have a 

significant impact on the accuracy of 

patient classification and on payment 

amounts if finalized. 

Response: We thank the commenter 

for this feedback and will take this 

recommendation into consideration for 

the FY 2023 SNF PPS proposed rule. 

Comment: The majority of 

commenters supported combining both 

mitigation strategies of delayed 

implementation of 2 years and a gradual 

phase-in of no more than 1 percent per 

year. MedPAC supported delayed 

implementation, but did not believe a 

phased-in approach is warranted given 


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the high level of aggregate payment to 

SNFs. 

Response: We thank the commenters 

for their feedback and will take these 

recommendations into consideration for 

the FY 2023 SNF PPS proposed rule. 

Comment: Some commenters made 

recommendations to revise the 

methodology for applying the 

recalibrated parity adjustment factor, 

after it is recalculated in light of the 

comments on the proposed rule. Several 

commenters disagreed with adjusting 

the CMIs across all case-mix adjusted 

components in equal measure, 

suggesting that this approach would 

harm patient care by further reducing 

therapy minutes. Instead, the 

commenters recommended adjusting 

only the CMIs for those PDPM 

components that drive the unintended 

increase observed under PDPM. 

According to data provided in the 

proposed rule, these would be the SLP, 

Nursing, and NTA components, not the 

PT or OT components. One commenter 

further recommended that the bottom 

four PDPM SLP groups (A, B, C, and D) 

remain unadjusted as those 

reimbursement levels are already very 

low. Several other commenters 

disagreed with adjusting the CMIs 

across all SNFs, instead suggesting that 

CMS should develop indicators to 

identify and impose financial penalties 

on the specific facilities driving the 

increase. 

Response: We thank the commenters 

for their feedback and will take these 

recommendations into consideration for 

the FY 2023 SNF PPS proposed rule. 

We thank the commenters for their 

feedback and will take these suggestions 

and recommendations into 

consideration as we consider the best 

path forward to ensure budget neutrality 

in the FY 2023 SNF PPS proposed rule. 

As stated earlier in this section, we 

believe it is imperative that we act in a 

well-considered but expedient manner 

once excess payments are identified. 

Additionally, as stated earlier in this 

section, our analysis of FY 2020 data 

found that even after removing 

beneficiaries using a PHE-related waiver 

or with a COVID–19 diagnosis from our 

data set, the observed inadvertent 

increase in SNF payments since PDPM 

was implemented was approximately 

the same. We will continue to monitor 

all available data and take that into 

consideration, in combination with the 

feedback and recommendations 

received, for developing the FY 2023 

SNF PPS proposed rule. 

VII. Skilled Nursing Facility (SNF) 

Quality Reporting Program (QRP) 

A. Background and Statutory Authority 

The Skilled Nursing Facility Quality 

Reporting Program (SNF QRP) is 

authorized by section 1888(e)(6) of the 

Act, and it applies to freestanding SNFs, 

SNFs affiliated with acute care facilities, 

and all non-CAH swing-bed rural 

hospitals. Section 1888(e)(6)(A)(i) of the 

Act requires the Secretary to reduce by 

2 percentage points the annual market 

basket percentage update described in 

section 1888(e)(5)(B)(i) of the Act 

applicable to a SNF for a fiscal year, 

after application of section 

1888(e)(5)(B)(ii) of the Act (the 

productivity adjustment) and section 

1888(e)(5)(B)(iii) of the Act, in the case 

of a SNF that does not submit data in 

accordance with sections 

1888(e)(6)(B)(i)(II) and (III) of the Act for 

that fiscal year. For more information on 

the requirements we have adopted for 

the SNF QRP, we refer readers to the FY 

2016 SNF PPS final rule (80 FR 46427 

through 46429), FY 2017 SNF PPS final 

rule (81 FR 52009 through 52010), FY 

2018 SNF PPS final rule (82 FR 36566 

through 36605), FY 2019 SNF PPS final 

rule (83 FR 39162 through 39272), and 

FY 2020 SNF PPS final rule (84 FR 

38728 through 38820). 

B. General Considerations Used for the 

Selection of Measures for the SNF QRP 

For a detailed discussion of the 

considerations we use for the selection 

of SNF QRP quality, resource use, or 

other measures, we refer readers to the 

FY 2016 SNF PPS final rule (80 FR 

46429 through 46431). 

1. Quality Measures Currently Adopted 

for the FY 2022 SNF QRP 

The SNF QRP currently has 13 

measures for the FY 2022 SNF QRP, 

which are outlined in Table 24. For a 

discussion of the factors used to 

evaluate whether a measure should be 

removed from the SNF QRP, we refer 

readers to 42 CFR 413.360(b)(3). 

BILLING CODE 4120–01–P 


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4The measure steward changed the name of the 

measure from SARS–CoV–2 Vaccination Coverage 

among Healthcare Personnel to COVID–19 

Vaccination Coverage among Healthcare Personnel. 

There were no changes to the measure itself, other 

than the name change. 

BILLING CODE 4120–01–C 

C. SNF QRP Quality Measure Proposals 

Beginning With the FY 2023 SNF QRP 

Section 1899B(h)(1) of the Act permits 

the Secretary to remove, suspend, or 

add quality measures or resource use or 

other measures described in sections 

1899B(c)(1) and (d)(1) of the Act, 

respectively, so long as the Secretary 

publishes in the Federal Register (with 

a notice and comment period) a 

justification for such removal, 

suspension or addition. Section 

1899B(a)(1)(B) of the Act requires that 

all of the data that must be reported in 

accordance with section 1899B(a)(1)(A) 

of the Act (including resource use or 

other measure data under section 

1899B(d)(1)) be standardized and 

interoperable to allow for the exchange 

of the information among post-acute 

care (PAC) providers and other 

providers and the use by such providers 

of such data to enable access to 

longitudinal information and to 

facilitate coordinated care. 

We proposed to adopt two new 

measures for the SNF QRP beginning 

with the FY 2023 SNF QRP: The SNF 

Healthcare-Associated Infections 

Requiring Hospitalization measure (SNF 

HAI) and the COVID–19 Vaccination 

Coverage among Healthcare Personnel 

(HCP) 4 measure as an ‘‘other measure’’ 

under section 1899B(d)(1) of the Act. 

The SNF HAI measure is an outcome 

measure. The data used to report the 

SNF HAI measure are standardized and 

interoperable and would allow 

providers to exchange this data and 

compare outcomes across the care 

continuum and PAC settings. Clinical 

data captured in every clinical setting 

informs a resident’s current medical 

care plan, facilitates coordinated care, 

and improves Medicare beneficiary 

outcomes. We plan to develop HAI 

measures in other PAC settings, such as 

the Inpatient Rehabilitation Facility 

(IRF) Quality Reporting Program and the 

Long-Term Care Hospital (LTCH) 

Quality Reporting Program. The 

proposed measure supports the CMS 

Meaningful Measures Initiative through 

the Making Care Safer by Reducing 

Harm Caused in the Delivery of Care 

domain. We have previously solicited 

feedback on the SNF HAI measure as a 

future measure for the SNF QRP and 

received several comments of support as 

well as a few comments recommending 

suggestions (84 FR 38765). The measure 

is described in more detail below. 

We proposed the COVID–19 

Vaccination Coverage among HCP 

measure as an ‘‘other’’ measure under 

section 1899B(d)(1) of the Act beginning 

with the FY 2023 SNF QRP. In 

accordance with section 1899B(a)(1)(B) 

of the Act, the data used to calculate 

this measure are standardized and 

interoperable. The proposed measure 

supports the Meaningful Measures 

domain of Promote Effective Prevention 


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TABLE 24: Quality Measures Currently Adopted for the FY 2022 SNF QRP 

Application of Functional 

Assessment/Care Plan 

Change in Mobility Score 

Discharge Mobility Score 

Change in Self-Care Score 

Discharge Self-Care Score 

DRR 

DTC 

PPR 

Application of Percent of Residents Experiencing One or More Falls with Major 

1n· Lon Sta QF #0674 . 

Application of Percent of Long-Term Care Hospital (L TCH) Patients with an 

Admission and Discharge Functional Assessment and a Care Plan That Addresses 

Function F #2631 . 

Application ofIRF Functional Outcome Measure: Change in Mobility Score for 

Medical Rehabilitation Patients F #2634 . 

Application ofIRF Functional Outcome Measure: Discharge Mobility Score for 

Medical Rehabilitation Patients F #2636 . 

Application of the IRF Functional Outcome Measure: Change in Self-Care Score 

for Medical Rehabilitation Patients F #2633 . 

Application of IRF Functional Outcome Measure: Discharge Self-Care Score for 

Medical Rehabilitation Patients (NQF #2635). 

Drug Regimen Review Conducted With Follow-Up for Identified Issues-Post 

Acute Care (PAC) Skilled Nursing Facility (SNF) Quality Reporting Program 

RP. 

scharge to Community (DTC}-Post Acute Care (PAC) Skilled Nursing Facility 

F F #3481 . 

Potentially Preventable 30-Day Post-Discharge Readmission Measure for Skilled 

Nursing Facility (SNF) Quality Reporting Program (QRP). 

*In response to the public health emergency (PHE) for the Coronavirus Disease 2019 (COVID-19), CMS released an Interim 

Final Rule (85 FR 27595 through 27597) which delayed the compliance date for collection and reporting of the Transfer of 

Health Information measures for at least two full fiscal years after the end of the PHE. 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42473 

5CMS. (2006). Eliminating Serious Preventable, 

and Costly Medical Errors—Never Events. Retrieved 

from https://www.cms.gov/newsroom/fact-sheets/

eliminating-serious-preventable-and-costlymedical-errors-never-events. 

6Office of Inspector General. (2014). Adverse 

events in skilled nursing facilities: National 

incidence among Medicare beneficiaries. Retrieved 

from https://oig.hhs.gov/oei/reports/oei-06-11- 

00370.pdf. 

7Beganovic, M., & Laplante, K. (2018). 

Communicating with Facility Leadership; Metrics 

for Successful Antimicrobial Stewardship Programs 

(Asp) in Acute Care and Long-Term Care Facilities. 

Rhode Island medical journal (2013), 101(5) (2018), 

45–49. 

8Cooper, D., McFarland, M., Petrilli, F., & Shells, 

C. (2019). Reducing inappropriate antibiotics for 

urinary tract infections in long-term care: A 

replication study. Journal of Nursing Care Quality, 

34(1), 16–21. http://dx.doi.org/10.1097/NCQ.

0000000000000343. 

9Feldstein, D., Sloane, P.D., & Feltner, C. (2018). 

Antibiotic stewardship programs in nursing homes: 

A systematic review. Journal of the American 

Medical Directors Association, 19(2), 110–116. 

http://dx.doi.org/10.1016/j.jamda.2017.06.019. 

10Castle, N., Engberg, J.B., Wagner, L.M., & 

Handler, S. (2017). Resident and facility factors 

associated with the incidence of urinary tract 

infections identified in the Nursing Home 

Minimum Data Set. Journal of Applied Gerontology, 

36(2), 173–194. http://dx.doi.org/10.1177/ 

0733464815584666. 

11Crnich, C.J., Jump, R., Trautner, B., Sloane, 

P.D., & Mody, L. (2015). Optimizing antibiotic 

stewardship in nursing homes: A narrative review 

and recommendations for improvement. Drugs & 

Aging, 32(9), 699–716. http://dx.doi.org/10.1007/ 

s40266-015-0292-7. 

12 Dick, A.W., Bell, J.M., Stone, N.D., Chastain, 

A.M., Sorbero, M., & Stone, P.W. (2019). Nursing 

home adoption of the National Healthcare Safety 

Network Long-term Care Facility Component. 

American Journal of Infection Control, 47(1), 59–64. 

http://dx.doi.org/10.1016/j.ajic.2018.06.018. 

13Cooper, D., McFarland, M., Petrilli, F., & Shells, 

C. (2019). Reducing inappropriate antibiotics for 

urinary tract infections in long-term care: A 

replication study. Journal of Nursing Care Quality, 

34(1), 16–21. http://dx.doi.org/10.1097/NCQ.

0000000000000343. 

14 Gucwa, A.L., Dolar, V., Ye, C., & Epstein, S. 

(2016). Correlations between quality ratings of 

skilled nursing facilities and multidrug-resistant 

urinary tract infections. American Journal of 

Infection Control, 44(11), 1256–1260. http://

dx.doi.org/10.1016/j.ajic.2016.03.015. 

15Travers, J.L., Stone, P.W., Bjarnadottir, R.I., 

Pogorzelska-Maziarz, M., Castle, N.G., & Herzig, 

C.T. (2016). Factors associated with resident 

influenza vaccination in a national sample of 

nursing homes. American Journal of Infection 

Control, 44(9), 1055–1057. http://dx.doi.org/ 

10.1016/j.ajic.2016.01.019. 

16CMS. (2006). Eliminating Serious Preventable, 

and Costly Medical Errors—Never Events. Retrieved 

from https://www.cms.gov/newsroom/fact-sheets/

eliminating-serious-preventable-and-costlymedical-errors-never-events. 

17Centers for Disease Control and Prevention 

(2009). The Direct Medical Costs of HealthcareAssociated Infections in U.S. Hospitals and the 

Benefits of Prevention. Retrieved from https://

www.cdc.gov/hai/pdfs/hai/scott_costpaper.pdf. 

18Ouslander, J.G., Diaz, S., Hain, D., & Tappen, 

R. (2011). Frequency and diagnoses associated with 

7- and 30-day readmission of skilled nursing facility 

patients to a nonteaching community hospital. 

Journal of the American Medical Directors 

Association, 12(3), 195–203. http://dx.doi.org/ 

10.1016/j.jamda.2010.02.015. 

19Zimlichman, E., Henderson, D., Tamir, O., 

Franz, C., Song, P., Yamin, C.K., . . . Bates, D.W. 

(2013). Health care-associated infections: A metaanalysis of costs and financial impact on the US 

health care system. JAMA Internal Medicine, 

173(22), 2039–2046. Retrieved from https://

jamanetwork.com/journals/jamainternalmedicine/ 

fullarticle/1733452. 

20Montoya, A., & Mody, L. (2011). Common 

infections in nursing homes: A review of current 

issues and challenges. Aging Health, 7(6), 889–899. 

http://dx.doi.org/10.2217/ahe.11.80. 

21Office of Disease Prevention and Health 

Promotion. (2013). Long-term care facilities. In U.S. 

Department of Health and Human Services, 

National action plan to prevent health careassociated infections: Road map to elimination (pp. 

194–239). Retrieved from https://health.gov/ourwork/health-care-quality/health-care-associatedinfections/national-hai-action-plan. 

22Chidambaram, P., Neuman T., Garfield R. 

(2020). Racial and Ethnic Disparities in COVID–19 

Cases and Deaths in Nursing Homes. Retrieved from 

https://www.kff.org/coronavirus-covid-19/issuebrief/racial-and-ethnic-disparities-in-covid-19- 

cases-and-deaths-in-nursing-homes/. 

23Li Y., Cen X., Temkin-Greener R. (2020). Racial 

and Ethnic Disparities in COVID–19 Infections and 

Deaths Across U.S. Nursing Homes. Journal of the 

American Geriatrics Society, 68(11), 2454–2461. 

https://pubmed.ncbi.nlm.nih.gov/32955105/. 

24 Kimball, A., Hatfield, K.M., Arons, M., James, 

A., Taylor, J., Spicer, K., Bardossy, A.C., Oakley, 

L.P., Tanwar, S., Chisty, Z., Bell, J.M., Methner, M., 

Harney, J., Jacobs, J.R., Carlson, C.M., McLaughlin, 

H.P., Stone, N., Clark, S., Brostrom-Smith, C., Page, 

L.C., . . . CDC COVID–19 Investigation Team 

(2020). Asymptomatic and Presymptomatic SARS– 

CoV–2 Infections in Residents of a Long-Term Care 

Skilled Nursing Facility—King County, 

Washington, March 2020. MMWR. Morbidity and 

mortality weekly report, 69(13), 377–381. https://

doi.org/10.15585/mmwr.mm6913e1. 

25McMichael, T.M., Clark, S., Pogosjans, S., Kay, 

M., Lewis, J., Baer, A., Kawakami, V., Lukoff, M.D., 

Ferro, J., Brostrom-Smith, C., Riedo, F.X., Russell, 

D., Hiatt, B., Montgomery, P., Rao, A.K., Currie, 

D.W., Chow, E.J., Tobolowsky, F., Bardossy, A.C., 

Oakley, L.P., . . . Public Health—Seattle & King 

County, EvergreenHealth, and CDC COVID–19 

Continued 

and Treatment of Chronic Disease. We 

identified the measure concept as a 

priority in response to the current 

public health crisis. This process 

measure was developed with the 

Centers for Disease Control and 

Prevention (CDC) to track COVID–19 

vaccination coverage among HCP in the 

SNF setting. This measure is described 

in more detail below. 

In addition, we proposed to update 

the denominator for one measure, the 

Transfer of Health (TOH) Information to 

the Patient—Post-Acute Care (PAC) 

measure to exclude residents discharged 

home under the care of an organized 

home health service or hospice. 

1. Skilled Nursing Facility (SNF) 

Healthcare-Associated Infections (HAI) 

Requiring Hospitalization Quality 

Measure Beginning With the FY 2023 

SNF QRP 

a. Background 

Monitoring the occurrence of HAIs 

among SNF residents can provide 

valuable information about a SNF’s 

quality of care. Although HAIs are not 

considered ‘‘never events’’, or serious 

adverse errors in the provision of health 

care services that should never occur, 

most are preventable as they are often 

the result of poor processes and 

structures of care.5 Evidence suggests 

there is a wide variation in HAI rates 

among SNF providers. An analysis of 

FY 2018 SNF claims indicates a 

performance gap in HAI rates across 

SNFs. Among the 14,347 SNFs included 

in the sample for the analysis, riskadjusted measure scores ranged from a 

minimum of 2.19 percent to a maximum 

of 19.83 percent. Further, a 2014 report 

from the Office of the Inspector General 

(OIG) estimated that one in four adverse 

events among SNF residents are due to 

HAIs, and more than half of all HAIs are 

potentially preventable.6 Typically, 

HAIs result from inadequate patient 

management following a medical 

intervention, such as surgery or device 

implementation, or poor adherence to 

protocol and antibiotic stewardship 

guidelines.789 Several provider 

characteristics are also related to HAIs 

including staffing levels (for example, 

high turnover, low staff-to-resident 

ratios, etc.), facility structure 

characteristics (for example, national 

chain membership, high occupancy 

rates, etc.), and adoption or lack thereof 

of infection surveillance and prevention 

policies.10 11 12 13 14 15 Inadequate 

prevention and treatment of HAIs is 

likely to result in poor health care 

outcomes for residents and wasteful 

resource use. For example, HAIs are 

associated with longer lengths of stay, 

use of higher-intensity care (for 

example, critical care services and 

hospital readmissions), increased 

mortality, and high health care 

costs.16 17 18 19 Monitoring SNF HAI rates 

would provide information about each 

facility’s adeptness in infection 

prevention and management. 

Addressing HAIs in SNFs is 

particularly important as several factors 

place SNF residents at high risk for 

infection, including increased age, 

cognitive and functional decline, use of 

indwelling devices, frequent care 

transitions, and close contact with other 

resident and healthcare workers.20 21

Furthermore, in SNFs, COVID–19 has a 

disproportionate impact on racial and 

ethnic minorities as well as people 

living with disabilities.22 23 Emerging 

COVID–19 studies reveal higher patient 

spread due to poor infection control, 

staff rotations between multiple SNFs, 

and poor patient COVID–19 

screenings.24 25 An analysis comparing 


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42474 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

Investigation Team (2020). COVID–19 in a LongTerm Care Facility—King County, Washington, 

February 27–March 9, 2020. MMWR. Morbidity and 

mortality weekly report, 69(12), 339–342. https://

doi.org/10.15585/mmwr.mm6912e1. 

26The CMS COVID–19 Nursing Home Dataset 

used in this analysis was not limited to just the 

SNF, but applied to the entire nursing home. The 

study population of the analysis includes Medicarecertified nursing homes providing SNF care. 

27Office of Inspector General. (2014). Adverse 

events in skilled nursing facilities: National 

incidence among Medicare beneficiaries. Retrieved 

from https://oig.hhs.gov/oei/reports/oei-06-11- 

00370.pdf. 

28Beganovic, M., & Laplante, K. (2018). 

Communicating with Facility Leadership; Metrics 

for Successful Antimicrobial Stewardship Programs 

(Asp) in Acute Care and Long-Term Care Facilities. 

Rhode Island medical journal (2013), 101(5) (2018), 

45–49. 

29Crnich, C.J., Jump, R., Trautner, B., Sloane, 

P.D., & Mody, L. (2015). Optimizing antibiotic 

stewardship in nursing homes: A narrative review 

and recommendations for improvement. Drugs & 

Aging, 32(9), 699–716. http://dx.doi.org/10.1007/ 

s40266-015-0292-7. 

30Freeman-Jobson, J.H., Rogers, J.L., & WardSmith, P. (2016). Effect of an education presentation 

on the knowledge and awareness of urinary tract 

infection among non-licensed and licensed health 

care workers in long-term care facilities. Urologic 

Nursing, 36(2), 67–71. http://dx.doi.org/10.7257/ 

1053-816X.2016.36.2.67 Crnich, C.J., Jump, R., 

Trautner, B., Sloane, P.D., & Mody, L. (2015). 

Optimizing antibiotic stewardship in nursing 

homes: A narrative review and recommendations 

for improvement. Drugs & Aging, 32(9), 699–716. 

http://dx.doi.org/10.1007/s40266-015-0292-7. 

31Hutton, D.W., Krein, S.L., Saint, S., Graves, N., 

Kolli, A., Lynem, R., & Mody, L. (2018). Economic 

evaluation of a catheter-associated urinary tract 

infection prevention program in nursing homes. 

Journal of the American Geriatrics Society, 66(4), 

742–747. http://dx.doi.org/10.1111/jgs.15316. 

32Nguyen, H.Q., Tunney, M.M., & Hughes, C.M. 

(2019). Interventions to Improve Antimicrobial 

Stewardship for Older People in Care Homes: A 

Systematic Review. Drugs & aging, 36(4), 355–369. 

https://doi.org/10.1007/s40266-019-00637-0. 

33Sloane, P.D., Zimmerman, S., Ward, K., Kistler, 

C.E., Paone, D., Weber, D.J., Wretman, C.J., & 

Preisser, J.S. (2020). A 2-Year Pragmatic Trial of 

Antibiotic Stewardship in 27 Community Nursing 

Homes. Journal of the American Geriatrics Society, 

68(1), 46–54. https://doi.org/10.1111/jgs.16059. 

34Lee, M.H., Lee GA, Lee SH, Park YH (2019). 

Effectiveness and core components of infection 

prevention and control programmes in long-term 

care facilities: a systematic review. Retrieved from 

https://pubmed.ncbi.nlm.nih.gov/30794854/. 

SNF HAI rates using FY 2019 data with 

the currently reported rates of COVID– 

19 in SNFs found that nursing homes 

with higher HAI rates in FY 2019 also 

have a higher number of COVID–19 

cases.26 This analysis was presented to 

the PAC–LTC MAP Workgroup at the 

January 11th meeting (http://www.

qualityforum.org/WorkArea/linkit.aspx?

LinkIdentifier=id&ItemID=94559, slide 

134). We believe this finding supports a 

relationship not only between this 

measure and overall HAI prevention 

and control in SNFs, but also in 

predicting those SNFs more likely to 

have higher rates of infection in future 

pandemics. Several interventions may 

reduce HAI rates among SNFs, thus 

improving quality of care. These 

interventions include the adoption of 

infection surveillance and prevention 

policies, safety procedures, antibiotic 

stewardship, and staff education and 

training programs.27 28 29 30 31 32 33

Additionally, infection prevention and 

control programs with core components 

in education, monitoring, and feedback 

on infection rates from surveillance 

programs or feedback on infection 

control practices from audits have been 

found to be successful interventions for 

reducing HAIs.34 The effectiveness of 

these interventions suggests 

improvement of HAI rates among SNF 

residents is possible through modifying 

provider-led processes and 

interventions. 

The proposed SNF HAI measure uses 

Medicare fee-for-service (FFS) claims 

data to estimate the risk-standardized 

rate of HAIs that are acquired during 

SNF care and result in hospitalization. 

Unlike other HAI measures that target 

specific infections, this measure would 

target all HAIs serious enough to require 

admission to an acute care hospital. 

Given the current COVID–19 public 

health emergency, we believe this 

measure would promote patient safety 

and increase the transparency of quality 

of care in the SNF setting. This measure 

also compares SNFs to their peers to 

statistically separate those that perform 

better than or worse than each other in 

infection prevention and management. 

We believe peer comparison would 

encourage SNFs to improve the quality 

of care they deliver. 

b. Stakeholder and Technical Expert 

Panel (TEP) Input 

In our development and specification 

of this measure, we employed a 

transparent process in which we sought 

input from stakeholders and national 

experts and engaged in a process that 

allowed for pre-rulemaking input, in 

accordance with section 1890A of the 

Act. 

To meet this requirement, we 

provided the following opportunities for 

stakeholder input. Our measure 

development contractor for the SNF HAI 

measure convened a Technical Expert 

Panel (TEP) on May 9, 2019 to obtain 

expert input on the development of an 

HAI measure for use in the SNF QRP. 

The TEP consisted of stakeholders with 

a diverse range of expertise, including 

SNF and PAC subject matter knowledge, 

clinical and infectious disease expertise, 

patient and family perspectives, and 

measure development experience. The 

TEP supported the proposed measure 

concept and provided substantive input 

regarding the measure’s specifications. 

Recommendations provided by the TEP 

included refining the measure’s 

operational definition, exclusion 

criteria, and HAI ICD–10 diagnosis code 

list, among other considerations. All 

recommendations from the TEP were 

taken into consideration and applied 

appropriately where feasible. A 

summary of the TEP proceedings titled 

SNF HAI Final TEP Report is available 

on the SNF QRP Measures and 

Technical Information page at https://

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

Skilled-Nursing-Facility-QualityReporting-Program/SNF-QualityReporting-Program-Measures-andTechnical-Information. 

Following the TEP, our measure 

development contractor released draft 

quality measure specifications for 

public comment on the SNF HAI 

measure. Stakeholder feedback was 

solicited on the proposed measure by 

requesting comment on the CMS 

Measures Management System 

Blueprint site. The comment submission 

period was from September 14, 2020 to 

October 14, 2020. Comments on the 

measure varied. Many commenters 

supported the idea of adopting an HAI 

measure to improve prevention efforts; 

however, commenters also offered 

criticisms about the measure’s 

specifications and implementation. The 

summary report of the September 14 to 

October 14, 2020 public comment 

period titled SNF HAI Public Comment 

Summary Report is available on the SNF 

QRP Measures and Technical 

Information page at https://

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

Skilled-Nursing-Facility-QualityReporting-Program/SNF-QualityReporting-Program-Measures-andTechnical-Information. 

c. Measure Applications Partnership 

(MAP) Review 

Our pre-rulemaking process includes 

making publicly available a list of 

quality and efficiency measures, called 

the Measures under Consideration 

(MUC) List that the Secretary is 

considering adopting through the 

Federal rulemaking process for use in 

Medicare programs. This allows multistakeholder groups to provide 

recommendations to the Secretary on 

the measures included on the list. 

We included the SNF HAI measure 

under the SNF QRP Program in the 

publicly available ‘‘List of Measures 

under Consideration for December 21, 


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35National Quality Forum. List of Measures 

Under Consideration for December 21, 2020. 

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

measures-under-consideration-list-2020-report.pdf 

on January 12, 2021. 

2020’’ (MUC List).35 The National 

Quality Forum (NQF)-convened 

Measure Applications Partnership 

(MAP) Post-Acute Care/Long-Term Care 

(PAC–LTC) workgroup met virtually on 

January 11, 2021 and provided input on 

the proposed measure. The MAP offered 

conditional support of the SNF HAI 

measure for rulemaking contingent 

upon NQF endorsement, noting that the 

measure adds value to the SNF QRP by 

presenting one overall measurement of 

all HAIs acquired during SNF care that 

result in hospitalizations, information 

that is not currently available. The MAP 

recognized that the proposed measure is 

intended to reflect global infection 

control for a facility, and may encourage 

SNFs to access processes and perform 

interventions to reduce adverse events 

among SNF residents that are due to 

HAIs. The MAP Rural Health 

Workgroup also agreed that the SNF 

HAI measure is suitable for use with 

rural providers in the SNF QRP. The 

final MAP report is available at http:// 

www.qualityforum.org/Publications/ 

2021/03/MAP_2020-2021_

Considerations_for_Implementing_

Measures_Final_Report_-_Clinicians,_

Hospitals,_and_PAC-LTC.aspx. 

Additionally, measure testing was 

conducted on the SNF HAI measure. 

Split-half testing revealed the proposed 

measure’s moderate reliability. Validity 

testing of the measure showed good 

model discrimination as the HAI model 

can accurately predict HAI cases while 

controlling for differences in resident 

case-mix. The SNF HAI TEP also 

showed strong support for the face 

validity of the proposed measure. For 

measure testing details, refer to the 

document titled, Skilled Nursing 

Facility Healthcare-Associated 

Infections Requiring Hospitalization for 

the Skilled Nursing Facility Quality 

Reporting Program Technical Report 

available on the SNF QRP Measures and 

Technical Information page at https://

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

Skilled-Nursing-Facility-QualityReporting-Program/SNF-QualityReporting-Program-Measures-andTechnical-Information. This proposed 

measure is not currently NQF endorsed, 

but CMS plans to submit the measure 

for NQF endorsement in the future. 

d. Competing and Related Measures 

Section 1899B(e)(2)(A) of the Act 

requires that, absent an exception under 

section 1899B(e)(2)(B) of the Act, 

measures specified under section 1899B 

of the Act be endorsed by the entity 

with a contract under section 1890(a) of 

the Act, currently the National Quality 

Forum (NQF). 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, section 1899B(e)(2)(B) of 

the Act permits the Secretary to 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. 

The proposed SNF HAI measure is 

not NQF endorsed, so we considered 

whether there are other available 

measures that assess HAIs in SNFs. 

After review of the NQF’s consensusendorsed measures, we were unable to 

identify any NQF endorsed measures for 

SNFs focused on capturing several types 

of severe infections attributable to the 

SNF setting in one composite score. For 

example, although the measures Percent 

of Residents with a Urinary Tract 

Infection (Long-Stay) (NQF #0684), 

National Healthcare Safety Network 

(NHSN) Catheter-Associated Urinary 

Tract Infections (NQF #0138), NHSN 

Central Line-Associated Bloodstream 

Infections (NQF #0139), and NHSN 

Facility-Wide Inpatient Hospital-onset 

Clostridium Difficile Infection (NQF 

#1717) are NQF endorsed and all report 

on specific types of infections, they do 

not provide an overall HAI rate and are 

not specific to the SNF setting. 

Additionally, although the Skilled 

Nursing Facility 30-Day All-Cause 

Readmission measure (NQF #2510), the 

Potentially Preventable 30-Day PostDischarge Readmission measure for SNF 

QRP, and the Skilled Nursing Facility 

30-Day Potentially Preventable 

Readmission after Hospital Discharge 

measure (SNFPPR) are all specific to the 

SNF setting, they are not solely focused 

on infections. We intend to submit this 

proposed measure to the NQF for 

consideration of endorsement when 

feasible. 

Therefore, after consideration of other 

available measures, we find that the 

exception under section 1899B(e)(2)(B) 

of the Act applies and are proposing the 

measure, Skilled Nursing Facility (SNF) 

Healthcare-Associated Infections (HAI) 

Requiring Hospitalization measure 

beginning with the FY 2023 SNF QRP. 

e. Quality Measure Calculation 

The proposed measure estimates the 

risk-standardized rate of HAIs that are 

acquired during SNF care and result in 

hospitalization using 1 year of Medicare 

FFS claims data. 

Both the proposed measure numerator 

and denominator are risk-adjusted. The 

measure’s adjusted numerator is the 

estimated number of SNF stays 

predicted to have an HAI that results in 

hospitalization. The estimate starts with 

the observed count of the measure 

outcome, which is then risk-adjusted for 

resident characteristics and a statistical 

estimate of the SNF effect beyond 

resident case mix. The term ‘‘SNF 

effect’’ represents provider-specific 

behaviors that result in facilities’ HAI 

rates. These behaviors may include 

adherence to evidence-based infection 

control policies and procedures. The 

adjusted denominator is the expected 

number of SNF stays with the measure 

outcome. The adjusted denominator is 

calculated by risk-adjusting the total 

eligible SNF stays for resident 

characteristics excluding the SNF effect. 

The proposed measure is calculated 

using a standardized risk ratio (SRR) in 

which the predicted number of HAIs for 

SNF stays per provider is divided by the 

expected number of HAIs. For each 

SNF, a risk-adjusted rate of HAIs that 

are acquired during SNF care and result 

in hospitalization is calculated by 

multiplying the SRR by the overall 

national observed rate of HAIs for all 

SNF stays. The measure is risk-adjusted 

for age and gender characteristics, 

original reason for Medicare 

Entitlement, principal diagnosis during 

the prior proximal inpatient (IP) stay, 

types of surgery or procedure from the 

prior proximal IP stay, length of stay 

and ICU/CCU utilization from the prior 

proximal IP stay, dialysis treatment 

from the prior proximal IP stay, and 

HCC comorbidities and number of prior 

IP stays within 1 year preceding the 

SNF stay. For technical information 

about this proposed measure, including 

information about the measure 

calculation, risk adjustment, and 

exclusions, refer to the document titled, 

Skilled Nursing Facility HealthcareAssociated Infections Requiring 

Hospitalization for the Skilled Nursing 

Facility Quality Reporting Program 

Technical Report available on the SNF 

QRP Measures and Technical 

Information page at https://

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

Skilled-Nursing-Facility-QualityReporting-Program/SNF-QualityReporting-Program-Measures-andTechnical-Information. If this measure 

is finalized, we intend to publicly report 

this measure using four quarters of 

claims data. We refer readers to section 

VII.H.2. of this proposed rule for 

information regarding public reporting. 


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36Acumen LLC & CMS. (2021). Skilled Nursing 

Facility Healthcare-Associated Infections Requiring 

Hospitalization for the Skilled Nursing Facility 

Quality Reporting Program: Technical Report. 

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

Quality-Initiatives-Patient-Assessment-Instruments/ 

NursingHomeQualityInits/Skilled-Nursing-FacilityQuality-Reporting-Program/SNF-Quality-ReportingProgram-Measures-and-Technical-Information. 

37Office of Inspector General. (2014). Adverse 

Events in Skilled Nursing Facilities: National 

Incidence Among Medicare Beneficiaries. Retrieved 

from https://oig.hhs.gov/oei/reports/oei-06-11- 

00370.pdf. 

38CMS. (2006). Eliminating Serious, Preventable, 

and Costly Medical Errors—Never Events. Retrieved 

from https://www.cms.gov/newsroom/fact-sheets/ 

eliminating-serious-preventable-and-costlymedical-errors-never-events. 

39Office of Inspector General. (2014). Adverse 

events in skilled nursing facilities: National 

incidence among Medicare beneficiaries. Retrieved 

from https://oig.hhs.gov/oei/reports/oei-06-11- 

00370.pdf. 

40Levitt, A.T., Freeman, C., Schwartz, C.R., 

McMullen, T., Felder, S., Harper, R., Van, C.D., Li, 

Q., Chong, N., Hughes, K., Daras, L.C., Ingber, M., 

We invited public comment on our 

proposal to adopt the quality measure, 

the Skilled Nursing Facility (SNF) 

Healthcare-Associated Infections (HAIs) 

Requiring Hospitalization measure (SNF 

HAI measure), beginning with the FY 

2023 SNF QRP. 

The following is a summary of the 

public comments received on our 

proposal to adopt the quality measure, 

Skilled Nursing Facility (SNF) 

Healthcare-Associated Infections (HAIs) 

Requiring Hospitalization measure (SNF 

HAI measure), beginning with the FY 

2023 SNF QRP and our responses: 

Comment: Several commenters 

supported adoption of the SNF HAI 

measure beginning with the FY 2023 

SNF QRP. The Medicare Payment 

Advisory Commission (MedPAC) 

supported the adoption of the measure, 

stating that Medicare quality programs 

should include population-based 

outcome measures and the rate of 

infections acquired during a SNF stay 

that are severe enough to require 

hospitalization is an outcome of 

importance to beneficiaries and the 

Medicare program. Additionally, 

commenters noted that HAIs are 

potentially preventable and signal 

actionable gaps in care quality. 

Commenters agree that the measure is 

actionable in reducing HAI incidence, 

and does not add burden to providers 

through its use of Medicare FFS claims. 

One commenter supported 

interoperability of the measure in its 

future expansion to other post-acute 

care settings, such as IRFs and LTCHs. 

Another commenter supported the SNF 

HAI measure, recognizing emerging 

evidence that associates high SNF HAI 

rates with higher patient COVID–19 

spread. Additional commenters 

supported the overall concept of the 

SNF HAI measure, recognizing the 

effectiveness of the measure to prevent 

and control the spread of infections and 

improve transparency among providers. 

Response: We thank commenters for 

their support of the SNF HAI measure. 

We agree that there is a critical need to 

reduce HAIs in SNFs and that 

monitoring SNF HAI rates provides 

valuable information on a SNF’s quality 

of care. We believe this proposed 

quality measure will address the lack of 

HAI data in SNFs, increase 

transparency, and help reduce rates of 

HAIs. 

Comment: One commenter disagreed 

with the assertion that there is a 

performance gap regarding HAIs in 

SNFs. The commenter noted that there 

is an inability to define the magnitude 

of the issue which makes it difficult to 

identify benchmarks and goals. 

Response: Our analysis of FY 2019 

data demonstrated that there is a 

performance gap in HAI rates across 

SNFs. Among the 14,102 SNFs included 

in the sample for the analysis, riskadjusted measure scores ranged from a 

minimum of 2.36 percent to a maximum 

of 17.62 percent.36 Further, a 2014 

report from the Office of the Inspector 

General (OIG) estimated that one in four 

adverse events among SNF residents are 

due to HAIs.37 Although most HAIs are 

not considered ‘‘never-events,’’ most are 

preventable and result from inadequate 

care processes and structures.38

Including the SNF HAI measure in the 

SNF QRP would provide SNFs 

information to help them improve their 

infection control and prevention 

strategies, as they will learn about their 

own facility’s HAI rate compared to 

their peer SNFs and the national 

average. Including the SNF HAI 

measure in the SNF QRP would also 

help patients choose which SNF they 

would like to receive care from. 

Comment: A commenter supported 

the SNF HAI measure’s focus on 

infection prevention in the nursing 

facility, but was concerned that FY 2019 

data would be used as a benchmark for 

HAI performance and that FY 2019 data 

do not take into account changes in 

infection prevention requirements like 

those at 42 CFR 483.80(b), which 

requires the facility to designate one or 

more individual(s) as the infection 

preventionist(s) responsible for the 

facility’s infection prevention and 

control program. 

Response: We would like to clarify 

that FY 2019 data are not being used as 

a benchmark for HAI performance. This 

measure compares facilities’ HAI rates 

to their peers (that is, all other SNFs in 

the United States), and to the national 

average. Therefore, the benchmark of 

this measure’s performance is the 

national average of the reporting period, 

not specifically FY 2019. With regard to 

the infection preventionist role, we note 

that under § 483.80, facilities have been 

required to establish an infection 

prevention and control program since 

late 2016 prior to the infection 

preventionist role requirement effective 

late 2019. 

Comment: Several commenters 

recommended that CMS postpone 

implementation of the measure until it 

receives NQF endorsement. These 

comments advocated for use of NQFendorsed measures, indicating that the 

NQF process includes a robust measure 

review with routine measure 

maintenance to reflect changes in 

performance. 

Response: We direct readers to section 

VII.C.1.d. of this final rule, where we 

discuss this topic in detail. Despite the 

current absence of NQF endorsement, 

we still believe it is critical to adopt the 

SNF HAI measure into the FY 2023 SNF 

QRP as one in four adverse events 

among SNF residents are due to HAIs, 

and approximately more than half of all 

HAIs are potentially preventable.39

Identifying several types of severe HAIs 

attributable to the SNF setting in one 

composite score provides actionable 

information to providers that may hold 

them accountable, encourage them to 

improve the quality of care they deliver, 

and improve transparency. Although the 

SNF HAI measure is not currently 

endorsed by the NQF, we agree that 

there is value in obtaining measure 

endorsement and plan to submit the 

measure for NQF endorsement in the 

future. 

Comment: Several commenters 

opposed the use of Medicare FFS claims 

for the SNF HAI measure. Many 

commenters do not believe that claimsbased measures are appropriate for 

measuring HAIs, and would instead 

support the use of NHSN chartabstracted surveillance data. 

Commenters emphasized the scientific 

process that ensures integrity and 

accuracy of NHSN data while 

questioning the reliability of claims 

data. Another commenter suggested 

using NHSN data in conjunction with 

claims data, noting the benefits of using 

standardized, validated NHSN 

definitions. 

Response: As mentioned in the SNF 

HAI Final TEP Summary Report, some 

TEP members voiced concerns about the 

accuracy of using inpatient claims to 

accurately capture infections acquired 

in a SNF.40 The TEP discussed 


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Smith, L., & Erim, D. (2019). Final Technical Expert 

Panel Summary Report: Development of a 

Healthcare-Associated Infections Quality Measure 

for the Skilled Nursing Facility Quality Reporting 

Program. Retrieved from https://www.cms.gov/ 

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

SNF-HAI-Final-TEP-Report-7-15-19_508C.pdf. 

41Cafardi, S.G., Snow, C.L., Holtzman, L., Waters, 

H., McCall, N.T., Halpern, M., Newman, L., Langer, 

J., Eng, T., & Guzman, C.R. (2012). Accuracy of 

Coding in the Hospital-Acquired ConditionsPresent on Admission Program Final Report. 

Retrieved from https://www.cms.gov/medicare/ 

medicare-fee-for-service-payment/hospitalacqcond/ 

downloads/accuracy-of-coding-final-report.pdf. 

42He, F., Daras, L.C., Renaud, J., Ingber, M., 

Evans, R., & Levitt, A. (2019, June 3). Reviewing 

Medical Records to Assess the Reliability of Using 

Diagnosis Codes in Medicare Claims to Identify 

Potentially Preventable Readmissions. Retrieved 

from https://academyhealth.confex.com/ 

academyhealth/2019arm/meetingapp.cgi/Paper/ 

31496. 

43Levitt, A.T., Freeman, C., Schwartz, C.R., 

McMullen, T., Felder, S., Harper, R., Van, C.D., Li, 

Q., Chong, N., Hughes, K., Daras, L.C., Ingber, M., 

Smith, L., & Erim, D. (2019). Final Technical Expert 

Panel Summary Report: Development of a 

Healthcare-Associated Infections Quality Measure 

for the Skilled Nursing Facility Quality Reporting 

Program. Retrieved from https://www.cms.gov/ 

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

SNF-HAI-Final-TEP-Report-7-15-19_508C.pdf. 

alternative data sources, including the 

use of NHSN data, but ultimately 

decided against it as it would increase 

provider burden. The TEP ultimately 

agreed that claims data are high quality 

and would strengthen the SNF QRP 

measure portfolio without increasing 

provider burden. Additionally, other 

claims-based measures have been 

deemed reliable through NQF 

endorsement, such as the Skilled 

Nursing Facility 30-Day All-Cause 

Readmission measure (SNFRM) (NQF 

#2510). 

Comment: Many commenters opposed 

the use of Medicare claims due to 

concerns that its data delay would not 

allow for timely improvement of the 

HAI rate. 

Response: We have worked to 

streamline our public reporting 

processes, and to narrow the gap 

between the submission of claims data 

and the public display of that data. To 

ensure that we give ample time for 

providers to submit their claims data, 

we have established a 90-day run-out 

period following the end of a calendar 

year or fiscal year. Beyond that, there 

are specific administrative and review/ 

quality assurance processes that must 

take place in a sequential order for CMS 

to ensure we are displaying accurate 

data. We have narrowed this gap 

between claims submission and public 

display to the extent feasible at this 

time. 

Comment: Commenters expressed 

concern over the measure’s dependence 

on the diagnosis of patients by medical 

practitioners who are outside of the 

influence of the SNF. These commenters 

are concerned that because the measure 

outcome is calculated based on hospital 

information, not SNF information, it 

reflects the coding practices of hospitals 

rather than actual quality of care at 

SNFs. Commenters also expressed 

concerns about differences in hospital 

surveillance that may result in an 

inaccurate SNF HAI rate. 

Response: We use inpatient claims for 

the SNF HAI measure because the 

measure’s main outcome is HAIs that 

require hospitalization. In response to 

the commenters’ assertion that inpatient 

claims are unreliable, a medical record 

review on the accuracy of hospital 

coding of Hospital Acquired Conditions 

(HACs) and Present on Admission 

(POA) conditions did not find patterns 

of widespread underreporting of HACs 

or overreporting of POA status.41

Rather, the study found that only 3 

percent of HAC cases were 

underreported and 91 percent of all 

cases coded POA were coded 

accurately. Another medical record 

review conducted by us assessed the 

accuracy of the principal diagnosis 

coded on a Medicare claim to identify 

whether a patient was admitted for a 

diagnosis included in our list of 

potentially preventable readmission 

(PPR) diagnoses.42 The study analyzed 

inpatient discharges from October 2015 

through September 2017 and found high 

agreement between principal diagnoses 

in Medicare claims and corresponding 

medical records. Specifically, the 

agreement rate between principal 

diagnoses in Medicare claims and 

information in the corresponding 

medical records ranged from 83 percent 

to 94 percent by study hospital. 

Additionally, 91 percent to 97 percent 

of principal diagnoses from the 

corresponding medical records were 

included in CMS’ list of PPR diagnoses. 

Therefore, we disagree with 

commenters’ concerns about the 

accuracy of inpatient claims data. 

In addition, several other SNF QRP 

measures rely on data from other 

settings such as Skilled Nursing Facility 

30-Day Potentially Preventable 

Readmission after Hospital Discharge 

(SNFPPR), Skilled Nursing Facility 30- 

Day All-Cause Readmission (SNFRM) 

(NQF #2510), and Potentially 

Preventable 30-Day Post-Discharge 

Readmission Measure for Skilled 

Nursing Facility Quality Reporting. 

Comment: Several commenters 

disagreed with the measure’s restriction 

to only include HAIs that require 

inpatient hospitalization and to exclude 

emergency room visits and observation 

stays. These commenters believe that 

limiting HAIs to only those that require 

hospitalization will undercount 

preventable HAIs and lead to negative 

outcomes for residents. 

Response: We acknowledge that 

detecting all HAIs in the measure’s 

definition would increase the amount of 

infection data provided to SNFs and 

empower quality improvement. 

However, we decided to propose only 

including HAIs requiring 

hospitalization in our measure 

definition in response to suggestions by 

the TEP.43 One TEP member noted that 

SNFs could risk information overload if 

we include every possible HAI in the 

SNF HAI rate. 

TEP members ultimately 

recommended that it would be more 

valuable for SNFs to have a 

concentrated list of severe infections to 

target quality improvement in the 

biggest impact areas. Avoiding 

information overload will help to make 

the measure more actionable, as SNFs 

may be able to target the focus of their 

infection and prevention control 

programs on their residents’ most severe 

infections. The TEP also recommended 

excluding observation stays and 

emergency department visits out of 

concern that these stays are not long 

enough to acquire all the lab results 

needed for accurate diagnosis of 

infections. 

Overall, TEP members believed that 

diagnoses of SNF residents transferred 

and hospitalized would be more likely 

to be based on the whole history and 

comprehensive test results and thus 

more likely to represent true infections. 

Comment: Some commenters opposed 

the adoption of a composite score, with 

concern that the measure is not 

infection-specific and would not allow 

for timely facility-level targeted 

interventions. One commenter 

recommended to narrow the SNF HAI 

measure to specific infections such as 

central line-associated bloodstream 

infections (CLASBI) or catheterassociated urinary tract infections 

(CAUTI). This commenter noted that 

focusing on a couple of infections could 

make it easier to isolate performance 

issues and focus on improving those 

outcomes. 

Response: The SNF HAI composite 

score is intended to provide a summary 

of overall performance in HAI 

prevention and control. Rather than 

focusing on interventions targeting a 

single infection, the goal of this measure 

is for SNFs to focus on foundational 

safety interventions, such as rates of 

hand washing, vaccinations, and 


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44Levitt, A.T., Freeman, C., Schwartz, C.R., 

McMullen, T., Felder, S., Harper, R., Van, C.D., Li, 

Q., Chong, N., Hughes, K., Daras, L.C., Ingber, M., 

Smith, L., & Erim, D. (2019). Final Technical Expert 

Panel Summary Report: Development of a 

Healthcare-Associated Infections Quality Measure 

for the Skilled Nursing Facility Quality Reporting 

Program. Retrieved from https://www.cms.gov/ 

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

SNF-HAI-Final-TEP-Report-7-15-19_508C.pdf. 

antibiotic stewardship programs that 

will reduce all instances of infection. 

We believe that reporting a composite, 

facility-level score is valuable because it 

informs SNFs of their overall HAI rates 

and allows them to compare these rates 

to their peers. This will enable SNFs to 

track their own performance and 

improve their quality of care through 

infection prevention and control 

programs. However, we recognize the 

benefits of measuring infection-specific 

data and will consider developing 

infection-specific HAI measures in the 

future. 

Comment: One commenter urged that 

the SNF HAI measure should include 

mitigation approaches to prevent 

misattribution of a HAI to a SNF. This 

commenter also recommended that the 

measure implement infection-specific 

incubation periods and states that the 

COVID–19 pandemic has exposed the 

importance of infection-specific 

incubation periods. COVID–19 

infections can occur before the onset of 

symptoms or a positive infection test 

result is observed, and in many cases, 

residents may have been exposed to 

COVID–19 prior to SNF admission. 

Response: We acknowledge the 

difficulties of assigning attribution in 

the SNF setting since HAIs often have 

risk factors that are outside of the SNF’s 

control. Although most are preventable, 

HAIs are not considered to be ‘‘neverevents’’ and we acknowledge that 

residents may contract infections 

outside of the SNF. However, we note 

that it is the responsibility of the SNF 

to implement infection prevention 

protocols and to best manage infections 

when they occur. Further, to help 

prevention misattribution, the measure 

excludes certain community-acquired 

infections, implements an incubation 

window, and applies the Centers for 

Disease Control (CDC) and Prevention’s 

National Healthcare Safety Network 

(NHSN) Repeat Infection Timeframe 

(RIT) to exclude preexisting infections 

that were acquired from the prior 

inpatient stay. Predating the COVID–19 

pandemic, we obtained clinical input 

from TEP panelists on the SNF HAI 

measure about the time window to 

identify HAIs attributable to the SNF.44

The TEP agreed that the same time 

window should be applied to all 

infections. Although the selected 

incubation window may not hold true 

for all infections, TEP members noted it 

was a reasonable average. 

Since COVID–19 was not discussed 

during TEP proceedings, we will 

consider working with the CDC to 

determine whether or not this 

reasonable average approach is still 

appropriate or if we should consider 

establishing an infection-specific 

incubation window to account for 

COVID–19 in the future. 

Comment: Several commenters did 

not find the measure actionable, citing 

that they would only have access to 

facility-level data rather than patientlevel information. Commenters 

requested patient-level data in 

confidential feedback reports be 

available through the Certification and 

Survey Provider Enhanced Reports 

(CASPER) system, noting its importance 

in improving provider transparency and 

actionability. Additionally, commenters 

expressed the importance of providing 

facilities with infection-specific data to 

help reduce future infection prevalence. 

Response: We disagree with the 

commenters that the use of facility-level 

data for the measure makes it less 

actionable. One of the benefits of a 

facility-level, composite indicator is its 

simplicity. A single score, 

representative of an entire facility, is 

easier to interpret, easier to use as a 

benchmark for tracking performance, 

and easier to use for comparisons among 

peers. The measure is not intended to 

stand alone; rather, it can be used in 

conjunction with other surveillance 

activities to plan for quality 

improvement. While an overall facility 

HAI rate may not provide information 

for targeting HAI prevention efforts to 

specific infection types, we believe that 

aggregate HAI prevalence data still 

provides actionable feedback to SNFs. 

The prevention of HAIs is not specific 

to an individual type of infection that 

can be presented in patient-level 

feedback reports. Rather, infection 

prevention and control efforts should 

address multiple infection types and 

SNFs should already be implementing 

infection control practices that include 

various approaches such as vaccination, 

isolation, hand washing, antibiotic 

stewardship programs, surveillance, 

sanitation, and staff training. Therefore, 

a facility-level HAI score is a reflection 

of quality of care as it measures a SNF’s 

adeptness in infection prevention and 

management. 

Comment: We received several 

comments about risk adjustment of the 

SNF HAI measure. One commenter 

disagreed that the SNF HAI measure 

should be risk-adjusted, especially for 

factors that are under facility control. 

This commenter believes that risk 

adjustment masks poor outcomes for 

residents that result directly from poor 

quality of care because risk adjustment 

excuses facilities from properly caring 

for high-risk patients. 

Response: We share the commenters’ 

concern that inclusion of certain 

covariates could mask adverse 

outcomes. However, lack of risk 

adjustment would disadvantage SNFs 

that specialize in treating high-risk 

populations in terms of HAI 

performance. In order to prevent 

provider manipulation, we focused on 

selecting factors that are not under the 

control of SNFs, such as patient 

characteristics rather than service 

provision. We would like to emphasize 

that the goal of this risk-adjusted 

measure is to identify SNFs that have 

notably higher rates of HAIs acquired 

during SNF care, when compared to the 

national average HAI rate. The purpose 

of risk adjustment is to account for risk 

factor differences across SNFs, when 

comparing quality of care among them. 

In other words, risk adjustment ‘‘levels 

the playing field’’ and allows for fairer 

quality-of-care comparisons across SNFs 

by controlling for differences in resident 

case-mix. Risk adjustment is 

particularly important for outcome 

measures because resident outcomes 

may be affected by factors such as age, 

gender, and health status that go beyond 

the quality of care delivered by SNFs. 

Comment: A few commenters 

supported risk adjustment but 

considered the proposed risk 

adjustment approach as inadequate and 

missing patient-level and provider-level 

factors. One commenter specifically 

asked that the measure be risk adjusted 

to account for high rates of patients with 

spinal cord injuries. 

Response: The risk adjustment model 

accounts for several patient-level factors 

such as age, sex, original reason for 

Medicare Entitlement, 283 principal 

diagnoses Clinical Classification 

Software (CCS) categories, 79 

Hierarchical Condition Categories (HCC) 

comorbidities, 10 surgical procedure 

CCS categories from the prior proximal 

stay, length of stay, and intensive care 

unit (ICU)/critical care unit (CCU) 

utilization from the prior proximal stay. 

We would like to clarify that spinal cord 

injuries are included in the risk 

adjustment model as CCS 227 spinal 

cord injury and HCC72 spinal cord 

disorders/injuries. 

Comment: One commenter was 

concerned about the lack of adjustment 

for social risk factors. 

Response: Risk adjustment includes 

age and sex but we acknowledge that 


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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42479 

45National Quality Forum (NQF). (2021). Social 

Risk Trial Final Report: Draft Report—Version 2. 

Retrieved from https://www.qualityforum.org/ 

WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=

95208. 

46Acumen LLC & CMS. (2021). Skilled Nursing 

Facility Healthcare-Associated Infections Requiring 

Hospitalization for the Skilled Nursing Facility 

Quality Reporting Program: Technical Report. 

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

Quality-Initiatives-Patient-Assessment-Instruments/ 

NursingHomeQualityInits/Skilled-Nursing-FacilityQuality-Reporting-Program/SNF-Quality-ReportingProgram-Measures-and-Technical-Information. 

47Acumen LLC & CMS. (2021). Skilled Nursing 

Facility Healthcare-Associated Infections Requiring 

Hospitalization for the Skilled Nursing Facility 

Quality Reporting Program: Technical Report. 

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

Quality-Initiatives-Patient-Assessment-Instruments/ 

NursingHomeQualityInits/Skilled-Nursing-FacilityQuality-Reporting-Program/SNF-Quality-ReportingProgram-Measures-and-Technical-Information. 

48National Quality Forum (NQF). (2021). 

Measure Applications Partnership 2020–2021 

Considerations for Implementing Measures in 

Federal Programs: Clinician, Hospital & PAC/LTC. 

Retrieved from http://www.qualityforum.org/ 

Publications/2021/03/MAP_2020-2021_

Considerations_for_Implementing_Measures_Final_

Report_-_Clinicians,_Hospitals,_and_PACLTC.aspx. 

the measure does not address social risk 

factors, such as income nor race/ 

ethnicity. During the development of 

the SNF HAI measure, the NQF was 

conducting a Social Risk Trial to 

investigate social risk factors’ 

association with outcome measures. 

Past NQF guidelines stated that social 

risk factors should not be included as 

adjustment variables. After the 2021 

conclusion of the trial, the NQF 

acknowledged that adjusting for social 

risk factors can obscure disparities and 

the Disparities Standing Committee 

recommended that each performance 

measure be assessed individually to 

determine appropriateness of 

adjustment for social risk factors.45 It is 

unclear if the benefits of adjusting for 

other social risk factors in the SNF HAI 

measure outweigh the potential 

consequences of masking social 

disparities. Therefore, we proposed to 

exclude social risk factors for now, but 

will continue to evaluate this issue by 

monitoring disparities and social risk 

factors as part of our routine measure 

monitoring work. 

Comment: One commenter believes 

that risk adjustment is inappropriately 

applied at the patient level and hospital 

level due to the use of inpatient claims, 

rather than at the SNF level. 

Response: SNF HAI risk adjustment is 

not implemented at the patient level nor 

at the hospital level. While the measure 

uses inpatient claims to identify HAIs 

acquired during a SNF stay, the unit of 

analysis for the risk adjustment is at the 

SNF stay level. The risk adjustment 

model applies a SNF provider-specific 

intercept via a hierarchical modeling 

approach. For more information about 

our risk adjustment approach, we refer 

to the SNF HAI Technical Report.46

Comment: One commenter advocated 

for CMS to be transparent about the 

measure’s calculations, noting that 

providers should be able to calculate 

their own HAI rate for measure 

validation, if necessary. 

Response: While we intend to make as 

much information related to SNF HAI 

performance as possible available to 

SNFs through confidential feedback 

reports under section 1899B(f) of the 

Act, we understand that claims-based 

quality measurement is difficult for 

SNFs to replicate for validation 

purposes. It would require familiarity 

with a number of data sources that are 

used to develop the risk-adjustment 

model for SNF HAI in order to account 

for variation across SNFs in case-mix 

and patient characteristics predictive of 

HAIs requiring hospitalization 

(including the Medicare Enrollment 

Database [EDB], Agency for Healthcare 

Research & Quality [AHRQ] Clinical 

Classification Software [CCS] groupings 

of ICD–10 codes, and CMS’s HCC 

mappings of ICD–10 codes). We view 

this as a necessary compromise to 

minimize reporting burden on 

participating SNFs by using claims data 

while ensuring we obtain timely data for 

quality improvement. We refer readers 

to the SNF HAI Technical Report for 

more information regarding the 

measure’s specifications and formulas 

used for rate calculations.47

Comment: One commenter did not 

support the measure because its testing 

results demonstrated moderate 

reliability. 

Response: We used FY 2018 and 2019 

data to conduct split-half reliability 

analyses to assess the internal 

consistency of the measure. Although 

our results showed moderate measure 

reliability, the MAP offered conditional 

support of the measure contingent upon 

NQF endorsement based on the above 

reliability results as well as other testing 

results.48 Additional measure testing 

results revealed high reportability and 

usability, high variability, strong face 

validity, and good model 

discrimination.43 We plan to submit the 

measure for NQF endorsement in the 

future. 

Comment: Some commenters 

highlighted their concerns regarding 

SNF HAI and COVID–19, noting the 

challenges they faced during the PHE, 

and how these challenges may impact 

their SNF HAI measure rates. 

Response: We acknowledge the 

severity of the pandemic and its 

detrimental impact on SNFs. As 

included in section VII.H.3. of this final 

rule, we proposed that no data reflecting 

services provided in FY 2020 would be 

publicly reported, as this measure 

would only be publicly reported using 

FY 2019 and FY 2021 data. We 

recognize that quality data collection 

and reporting for services furnished 

during the PHE may not be reflective of 

their true level of performance during 

this time of emergency. At the same 

time, COVID–19 has heightened the 

importance of infection prevention and 

control programs and the need for HAI 

data. 

Comment: One commenter linked the 

SNF HAI measure to health equity 

through the use of Medicare claims, 

noting that the measure should report 

demographic information such as race 

and ethnicity to shed light on potential 

health care disparities among SNF 

residents. 

Response: We plan to track sex, age, 

race, ethnicity, and Medicare/Medicaid 

dual-eligibility status as part of CMS’ 

routine monitoring and evaluation of 

the SNF HAI measure. This information 

will not be displayed on Care Compare 

as part of SNF HAI measure reporting, 

but we will take this request into 

consideration in our future efforts to 

promote health equity. 

Comment: Some commenters urged 

CMS to provide resources, support, and 

trainings for quality improvement and 

infection prevention among SNFs. 

Commenters encourage CMS to work 

with stakeholders to consider the labor 

required to measure and prevent HAIs 

in SNFs under the critical shortage of 

healthcare personnel, and recommend 

for CMS to implement a requirement for 

SNFs to hire at least one person trained 

in infection control to be available at the 

facility, with their hours predicated on 

the number of beds. 

Response: We would like to 

emphasize that SNFs should already be 

maintaining infection control programs 

in order to meet the quality 

requirements for certification in the 

Medicare program as outlined in the 

long-term care facility Requirements of 

Participation (RoPs). These regulations 

at § 483.80 require facilities to establish 

and maintain an infection prevention 

and control program, including 

designating one or more individual(s) as 

the infection preventionist who works at 

least part time at the facility and who is 

responsible for the facility’s infection 

prevention and control program. 

Comment: Other commenters urge 

CMS to train SNFs on best practices for 

reducing HAIs. 

Response: We have made several 

resources available such as free online 


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42480 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

49U.S. Dept. of Health and Human Services, 

Office of the Assistant Secretary for Preparedness 

and Response. (2020). Determination that a Public 

Health Emergency Exists. Retrieved from https://

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

Pages/2019-nCoV.aspx. 

50Centers for Disease Control and Prevention. 

(2020). Your Health: Symptoms of Coronavirus. 

Retrieved from https://www.cdc.gov/coronavirus/ 

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

51Centers for Disease Control and Prevention 

(2021). Health Equity Considerations and Racial 

and Ethnic Minority Groups. Available at https://

www.cdc.gov/coronavirus/2019-ncov/community/ 

health-equity/race-ethnicity.html. 

52Centers for Disease Control and Prevention. 

(2020). Your Health: Symptoms of Coronavirus. 

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

ncov/symptoms-testing/symptoms.html. 

53Centers for Disease Control and Prevention. 

(2020). CDC COVID Data Tracker. Available at 

https://covid.cdc.gov/covid-data-tracker/#cases_

casesper100klast7days. 

54 Ibid. 

55Associated 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-cases-74a1f0dc3634917

a5dc13408455cd895. 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-fullare-us-intensive-care-units-new-data-paints-analarming-picture.html. 

56NPR. U.S. Hits 100,000 COVID–19 

Hospitalizations, Breaks Daily Death Record. Dec. 2, 

2020. Accessed on December 17, 2020 at https://

www.npr.org/sections/coronavirus-live-updates/ 

2020/12/02/941902471/u-s-hits-100-000-covid-19- 

hospitalizations-breaks-daily-death-record; The 

Wall Street Journal. Coronavirus Live Updates: U.S. 

Hospitalizations, Newly Reported Cases, Deaths 

Edge Downward. Accessed on January 11 at https:// 

www.wsj.com/livecoverage/covid-2021-01-11. 

57Centers for Disease Control and Prevention. 

(2021). COVID–19. Your Health. Frequently Asked 

Questions. Accessed on January 11, 2021 at https:// 

www.cdc.gov/coronavirus/2019-ncov/faq.html. 

58Centers for Disease Control and Prevention 

(2021). COVID–19. Your Health. Frequently Asked 

Questions. Accessed on January 11, 2021 at https:// 

www.cdc.gov/coronavirus/2019-ncov/faq.html. 

59Centers for Disease Control and Prevention 

(2021). COVID–19. Your Health. Frequently Asked 

Questions. Accessed on January 11, 2021 at https:// 

www.cdc.gov/coronavirus/2019-ncov/faq.html. 

60Centers for Disease Control and Prevention. 

(2020). Clinical Questions about COVID–19: 

Questions and Answers. Accessed on December 2, 

2020 at https://www.cdc.gov/coronavirus/2019- 

ncov/hcp/faq.html. 

61Centers 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. 

62Centers 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 

December 2 at https://www.cdc.gov/coronavirus/ 

2019-ncov/hcp/guidance-risk-assesment-hcp.html. 

63 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. 

64Centers for Disease Control and Prevention. 

(2020). COVID–19 Vaccination Program Interim 

Playbook for Jurisdiction Operations. Accessed on 

December 18 at https://www.cdc.gov/vaccines/imzmanagers/downloads/COVID-19-VaccinationProgram-Interim_Playbook.pdf. 

65U.S. Food and Drug Administration. (2021). 

Pfizer-BioNTech COVID–19 Vaccine. Available at 

https://www.fda.gov/emergency-preparedness-andresponse/coronavirus-disease-2019-covid-19/pfizerbiontech-covid-19-vaccine. U.S. Food and Drug 

Administration. (2021). Pfizer-BioNTech COVID–19 

Vaccine EUA Letter of Authorization. Available at 

https://www.fda.gov/media/150386/download. 

training modules in partnership with 

the CDC and Quality Improvement 

Organizations (QIOs). The QIO program 

aims to increase patient safety and care 

coordination, and improve clinical 

quality by, among other things, working 

with providers, other stakeholders, and 

Medicare beneficiaries on initiatives to 

improve the quality of health care for 

Medicare beneficiaries. Several of these 

resources can be found on the following 

web pages as provided by the CDC: 

https://www.cdc.gov/longtermcare/ 

prevention/index.html and https://

www.cdc.gov/longtermcare/ 

training.html. Additionally, the CMS 

Office of Minority Health (OMH) offers 

a Disparity Impact Statement as an 

intervention to address HAI-related 

disparities. This tool may be used to 

provide health equity technical 

assistance and reduce HAIs among 

vulnerable populations. The Disparity 

Impact Statement tool can be viewed at 

https://www.cms.gov/About-CMS/ 

Agency-Information/OMH/Downloads/ 

Disparities-Impact-Statement-508- 

rev102018.pdf. 

After careful consideration of the 

public comments we received, we are 

finalizing our proposal to adopt the SNF 

HAI measure as a Medicare FFS claimsbased measure beginning with the FY 

2023 payment determination and 

subsequent years as proposed. 

2. COVID–19 Vaccination Coverage 

Among Healthcare Personnel (HCP) 

Measure Beginning With the FY 2023 

SNF QRP 

a. Background 

On January 31, 2020, the Secretary of 

the U.S. Department of Health and 

Human Services (HHS) declared a 

public health emergency (PHE) for the 

United States in response to the global 

outbreak of SARS-CoV–2, a novel (new) 

coronavirus that causes a disease named 

‘‘coronavirus disease 2019’’ (COVID– 

19).49 COVID–19 is a contagious 

respiratory infection 50 that can cause 

serious illness and death. Older 

individuals, racial and ethnic 

minorities, and those with underlying 

medical conditions are considered to be 

at higher risk for more serious 

complications from COVID–19.51 52 As 

stated in the proposed rule, as of April 

4, 2021, the U.S. reported over 30 

million cases of COVID–19 and over 

553,000 COVID–19 deaths.53 As of July 

21, 2021, the U.S. has reported over 34 

million cases of COVID–19 and over 

607,000 COVID–19 deaths.54

Hospitals and health systems saw 

significant surges of COVID–19 patients 

as community infection levels 

increased.55 In December 2020 and 

January 2021, media outlets reported 

that more than 100,000 Americans were 

in the hospital with COVID–19.56

Evidence indicates that COVID–19 

primarily spreads when individuals are 

in close contact with one another.57 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.58 Experts believe that 

COVID–19 spreads less commonly 

through contact with a contaminated 

surface.59 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.60 Subsequent 

to the publication of the proposed rule, 

the CDC has 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.61 Personal protective 

equipment (PPE) and other infectioncontrol precautions can reduce the 

likelihood of transmission in health care 

settings, but COVID–19 can still spread 

between healthcare personnel (HCP) 

and patients given the close contact that 

may occur during the provision of 

care.62 The CDC has emphasized that 

health care settings, including long-term 

care settings, can be high-risk places for 

COVID–19 exposure and transmission.63

Vaccination is a critical part of the 

nation’s strategy to effectively counter 

the spread of COVID–19 and ultimately 

help restore societal functioning.64 On 

December 11, 2020, the Food and Drug 

Administration (FDA) issued the first 

Emergency Use Authorization (EUA) for 

a COVID–19 vaccine in the U.S.65

Subsequently the FDA issued EUAs for 

additional COVID–19 vaccines. In 

issuing these EUAs, the FDA 

determined that it was reasonable to 

conclude that the known and potential 

benefits of each vaccine, when used as 


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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42481 

66 Ibid. 

67U.S. Food and Drug Administration. (2021). 

ModernaTX, Inc. COVID–19 Vaccine EUA Letter of 

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

media/144636/download. 

68U.S. Food and Drug Administration (2021). 

Janssen Biotech, Inc. COVID–19 Vaccine EUA Letter 

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

media/146303/download. 

69The White House. Remarks by President Biden 

on the COVID–19 Response and the State of 

Vaccinations. March 29, 2021. Accessed at https:// 

www.whitehouse.gov/briefing-room/speechesremarks/2021/03/29/remarks-by-president-bidenon-the-covid-19-response-and-the-state-ofvaccinations/. 

70Health 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. 

71 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. 

72 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/. 

73Associated 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. 

74Press Briefing by White House COVID–19 

Response Team and Public Health Officials | The 

White House. 

75Centers for Disease Control and Prevention. 

Weekly COVID–19 Vaccination Data Reporting. 

Accessed at https://www.cdc.gov/nhsn/ltc/weeklycovid-vac/index.html. 

76Centers for Medicare & Medicaid Services. Prerulemaking. Accessed at https://www.cms.gov/ 

Medicare/Quality-Initiatives-Patient-AssessmentInstruments/QualityMeasures/Pre-Rulemaking. 

77National Quality Forum. List of Measures 

Under Consideration for December 21, 2020. 

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

measures-under-consideration-list-2020-report.pdf 

on January 12, 2021. 

authorized to prevent COVID–19, 

outweighed its known and potential 

risks.66 67 68

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.69 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 

healthcare personnel (HCP), and 

individuals at highest risk for 

developing severe illness from COVID– 

19.70 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.71 Research 

suggests most states followed this 

recommendation,72 and HCP began 

receiving the vaccine in mid-December 

of 2020.73 Subsequent to the publication 

of the SNF PPS proposed rule, on April 

8, 2021, the White House confirmed that 

there was sufficient vaccine supply for 

all Americans.74

HCP are at risk of carrying COVID–19 

infection to patients, experiencing 

illness or death as a result of COVID– 

19 themselves, and transmitting it to 

their families, friends, and the general 

public. We believe it is important to 

require that SNFs report HCP 

vaccination in order to assess whether 

they are taking steps to limit the spread 

of COVID–19 among their HCP, reduce 

the risk of transmission of COVID–19 

within their facilities, and to help 

sustain the ability of SNFs to continue 

serving their communities throughout 

the PHE and beyond. Currently, as 

required under the May 8, 2020 interim 

final rule with comment period (85 FR 

27601–27602), SNFs are required to 

submit COVID–19 data through the 

CDC’s NHSN Long-term Care Facility 

COVID–19 Module of the NHSN. 

Examples of data reported in the 

module include: Suspected and 

confirmed COVID–19 infections among 

residents and staff, including residents 

previously treated for COVID–19; total 

deaths and COVID–19 deaths among 

residents and staff; personal protective 

equipment and hand hygiene supplies 

in the facility; ventilator capacity and 

supplies available in the facility; 

resident beds and census; access to 

COVID–19 testing while the resident is 

in the facility; and staffing shortages. 

Although HCP and resident COVID–19 

vaccination data reporting modules are 

currently available through the NHSN, 

the reporting of this data is voluntary.75

Subsequent to the publication of the 

SNF PPS proposed rule, an interim final 

rule with comment period (IRC) 

published on May 13, 2021 entitled 

‘‘Medicare and Medicaid Programs; 

COVID–19 Vaccine Requirements for 

Long-Term Care (LTC) Facilities and 

Intermediate Care Facilities for 

Individuals with Intellectual Disabilities 

(ICFs-IID) Residents, Clients, and Staff’’ 

(86 FR 26315–26316) (hereafter referred 

to as the May 2021 IFC), SNFs are 

required to report to the CDC’s NHSN, 

on a weekly basis, the COVID–19 

vaccination status of all residents and 

staff. 

We also believe that publishing 

facility-level COVID–19 HCP 

vaccination rates on Care Compare 

would be helpful to many patients, 

including those who are at high-risk for 

developing serious complications from 

COVID–19, as they choose facilities 

from which to seek treatment. Under 

CMS’ Meaningful Measures Framework, 

the COVID–19 Vaccination Coverage 

among Healthcare Personnel measure 

addresses the quality priority of 

‘‘Promote Effective Prevention & 

Treatment of Chronic Disease’’ through 

the Meaningful Measures Area of 

‘‘Preventive Care.’’ 

Therefore, we proposed a new 

measure, COVID–19 Vaccination 

Coverage among HCP to assess the 

proportion of a SNF’s healthcare 

workforce that has been vaccinated 

against COVID–19. 

b. Stakeholder Input 

In the development and specification 

of the measure, a transparent process 

was employed to seek input from 

stakeholders and national experts and 

engage in a process that allows for prerulemaking input on each measure, 

under section 1890A of the Act.76 To 

meet this requirement, the following 

opportunity was provided for 

stakeholder input. 

The pre-rulemaking process includes 

making publicly available a list of 

quality and efficiency measures, called 

the Measures Under Consideration 

(MUC) List that the Secretary is 

considering adopting, through Federal 

rulemaking process, for use in Medicare 

program(s). This allows multistakeholder groups to provide 

recommendations to the Secretary on 

the measures included on the list. The 

COVID–19 Vaccination Coverage among 

HCP measure was included on the 

publicly available ‘‘List of Measures 

under Consideration for December 21, 

2020’’ (MUC List).77 Five comments 

were received from industry 

stakeholders during the pre-rulemaking 

process on the COVID–19 Vaccination 

Coverage among HCP measure, and 

support was mixed. Commenters 

generally supported the concept of the 

measure. However, there was concern 

about the availability of the vaccine and 


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78Measure Applications Partnership. MAP 

Preliminary Recommendations 2020–2021. 

Accessed on February 3, 2021 at https://www.

qualityforum.org/WorkArea/linkit.aspx?

LinkIdentifier=id&ItemID=94650. 

79 Ibid. 

80 Ibid. 

81 Ibid. 

82The Influenza Vaccination Coverage among 

Healthcare Personnel (NQF #0431) measure which 

is NQF endorsed and was adopted in the IRF QRP 

in the FY 2014 IRF PPS Final Rule (78 FR 47905 

through 47906), and in the LTCH QRP in the FY 

2013 IPPS/LTCH PPS Final Rule (77 FR 53630 

through 53631). 

83Centers for Disease Control and Preventions. 

Morbidity and Mortality Weekly Report. March 29, 

2021. Available at https://www.cdc.gov/mmwr/ 

volumes/70/wr/mm7013e3.htm?s_cid=mm7013e3_

w. 

84National Quality Forum. Key Points for 

Evaluating Scientific Acceptability. Revised January 

3, 2020. https://www.qualityforum.org/Measuring_

Performance/Scientific_Methods_Panel/Docs/

Evaluation_Guidance.

aspx#:∼:text=NQF%20is%20not%

20prescriptive%20about,reliability

%20or%20validity%

20testing%20results.&text=Reliability%20

and%20validity%20must%20be,source%20

and%20level%20of%20analysis). 

85 Ibid. 

measure definition for HCP, and some 

commenters encouraged CMS to 

continue to update the measure as new 

evidence comes in. 

c. Measure Applications Partnership 

(MAP) Review 

When the Measure Applications 

Partnership (MAP) PAC–LTC 

Workgroup convened on January 11, 

2021, it reviewed the MUC List and the 

COVID–19 Vaccination Coverage among 

HCP 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 SNF QRP measure set by 

providing transparency about an 

important COVID–19 intervention to 

help limit COVID–19 infections.78 The 

MAP also stated that collecting 

information on COVID–19 vaccination 

coverage among healthcare personnel 

and providing feedback to facilities 

would allow facilities to benchmark 

coverage rates and improve coverage in 

their facility, and that reducing rates of 

COVID–19 in healthcare personnel may 

reduce transmission among patients and 

reduce instances of staff shortages due 

to illness.79

In its preliminary recommendations, 

the MAP PAC–LTC Workgroup did not 

support this measure for rulemaking, 

subject to potential for mitigation.80 To 

mitigate its concerns, the MAP believed 

that the measure needed welldocumented evidence, finalized 

specifications, testing, and NQF 

endorsement prior to implementation.81

Subsequently, the MAP Coordinating 

Committee met on January 25, 2021, and 

reviewed the COVID–19 Vaccination 

Coverage among Healthcare Personnel 

measure. In the 2020–2021 MAP Final 

Recommendations, the MAP offered 

conditional support for rulemaking 

contingent on CMS bringing the 

measure back to the MAP once the 

specifications are further clarified. The 

final MAP report is available at http:// 

www.qualityforum.org/Publications/ 

2021/03/MAP_2020- 

2021_Considerations_for_Implementing

_Measures_Final_Report_-_Clinicians,

_Hospitals,_and_PAC-LTC.aspx. 

In response to the MAP request for 

CMS to bring the measure back once the 

specifications were further clarified, 

CMS met with the MAP Coordinating 

Committee on March 15, 2021. First, 

CMS and CDC clarified the alignment of 

the COVID–19 Vaccination Coverage 

among HCP with the Influenza 

Vaccination Coverage among HCP (NQF 

#0431), an NQF-endorsed measure since 

2012. The COVID–19 Vaccination 

Coverage among HCP measure is 

calculated using the same approach as 

the Influenza Vaccination Coverage 

among HCP measure.82 The approach to 

identifying HCPs eligible for the 

COVID–19 vaccination is analogous to 

those used in the NQF endorsed flu 

measure which underwent rigorous 

review from technical experts about the 

validity of that approach and for which 

ultimately received NQF endorsement. 

More recently, prospective cohorts of 

health care personnel, first responders, 

and other essential and frontline 

workers over 13 weeks in eight U.S. 

locations confirmed that authorized 

COVID–19 vaccines are highly effective 

in real-world conditions. Vaccine 

effectiveness of full immunization with 

two doses of vaccines was 90 percent.83

Additionally, to support the 

measure’s data element validity, CDC 

conducted testing of the COVID–19 

vaccination numerator using data 

collected through the NHSN and 

independently reported through the 

Federal Pharmacy Partnership for Longterm Care Program for delivering 

vaccines to long-term care facilities. 

These are two completely independent 

data collection systems. In initial 

analyses of the first month of 

vaccination, the number of HCP 

vaccinated in approximately 1,200 

facilities which had data from both 

systems, the number of HCP vaccinated 

was highly correlated between these two 

systems with a correlation coefficient of 

nearly 90 percent in the second two 

weeks of reporting. Of note, assessment 

of data element reliability may not be 

required by NQF if data element validity 

is demonstrated.84 To assess the validity 

of new performance measure score (in 

this case, percentage of COVID–19 

vaccination coverage), NQF allows 

assessment by face validity (that is, 

subjective determination by experts that 

the measure appears to reflect quality of 

care, done through a systematic and 

transparent process),85 and the MAP 

concurred with the face validity of the 

COVID–19 Vaccination Coverage among 

HCP measure. Materials from the March 

15, 2021 MAP Coordinating Committee 

meeting are on the NQF website at 

https://www.qualityforum.org/ 

ProjectMaterials.aspx?projectID=75367. 

This measure is not NQF endorsed, 

but the CDC, in collaboration with CMS, 

plans to submit the measure for NQF 

endorsement in the future. 

d. Competing and Related Measures 

Section 1899B(e)(2)(A) of the Act 

requires that absent an exception under 

section 1899B(e)(2)(B) of the Act, each 

measure specified by the Secretary be 

endorsed by the entity with a contract 

under section 1890(a) of the Act, 

currently the National Quality Forum 

(NQF). 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, section 1899B(e)(2)(B) of the 

Act permits the Secretary to specify a 

measure that is not so endorsed, as long 

as due consideration is given to the 

measures that have been endorsed or 

adopted by a consensus organization 

identified by the Secretary. The 

proposed COVID–19 Vaccination 

Coverage among HCP measure is not 

currently NQF endorsed and has not 

been submitted to the NQF for 

consideration, so we considered 

whether there are other available 

measures that assess COVID–19 

vaccinations among HCP. After review 

of the NQF’s consensus-endorsed 

measures, we were unable to identify 

any NQF endorsed measures for SNFs 

focused on capturing COVID–19 

vaccination coverage of HCP, and we 

found no other feasible and practical 

measure on the topic of COVID–19 

vaccination coverage among HCP. The 

only other vaccination coverage of HCP 

measure found was the Influenza 

Vaccination Coverage among Healthcare 

Personnel (NQF #0431) measure which 

is NQF endorsed and was adopted in 

the IRF QRP in the FY 2014 IRF PPS 

final rule (78 FR 47905 through 47906), 

and in the LTCH QRP in the FY 2013 

IPPS/LTCH PPS final rule (77 FR 53630 

through 53631). 


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86Centers for Disease Control and Prevention. 

Interim Clinical Considerations for Use of COVID– 

19 Vaccines Currently Authorized in the United 

Sates. Contraindications found in Appendix B: 

Triage of people presenting for the vaccination. 

Accessed at https://www.cdc.gov/vaccines/covid19/info-by-product/clinical-considerations.html. 

87Centers 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. 

88Chen MK, Chevalier JA, Long EF. Nursing 

home staff networks and COVID–19. Proceedings of 

the National Academy of Sciences of the United 

States of America (PNAS). Available at https://

www.pnas.org/content/118/1/e2015455118. 

Accessed June 29, 2021. 

89Centers for Disease Control and Prevention. 

(2020). COVID–19 Vaccination Program Interim 

Playbook for Jurisdiction Operations. Retrieved 

from https://www.cdc.gov/vaccines/imzmanagers/ 

downloads/COVID-19. 

Given the novel nature of the SARS– 

CoV–2 virus, and the significant and 

immediate risk it poses in SNFs, we 

believe it was necessary to propose the 

measure as soon as possible. Therefore, 

after consideration of other available 

measures that assess COVID–19 

vaccination rates among HCP, we 

believe the exception under section 

1899B(e)(2)(B) of the Act applies. This 

proposed measure has the potential to 

generate actionable data on vaccination 

rates that can be used to target quality 

improvement among SNF providers. 

e. Quality Measure Calculation 

The COVID–19 Vaccination Coverage 

among Healthcare Personnel (HCP) 

measure is a process measure developed 

by the CDC to track COVID–19 

vaccination coverage among HCP in 

facilities such as SNFs. Since this 

proposed measure is a process measure, 

rather than an outcome measure, it does 

not require risk-adjustment. 

The denominator would be the 

number of HCP eligible to work in the 

facility for at least one day during the 

reporting period, excluding persons 

with contraindications to COVID–19 

vaccination that are described by the 

CDC.86 While the SNF QRP applies to 

freestanding SNFs, SNFs affiliated with 

acute care facilities, and all non-CAH 

swing-bed rural hospitals, we believe it 

is necessary to include all HCP within 

the facility in the measure denominator 

because all HCP would have access to 

and may interact with SNF residents. 

The numerator would be the 

cumulative number of HCP eligible to 

work in the facility for at least one day 

during the reporting period and who 

received a complete vaccination course 

against SARS–CoV–2. A complete 

vaccination course may require one or 

more doses depending on the specific 

vaccine used. The finalized measure 

specifications are on the CDC website at 

https://www.cdc.gov/nhsn/nqf/ 

index.html. 

We proposed that SNFs would submit 

data for the measure through the CDC/ 

NHSN data collection and submission 

framework.87 SNFs would use the 

COVID–19 vaccination data reporting 

module in the NHSN Healthcare 

Personnel Safety (HPS) Component to 

report the number of HCP eligible who 

have worked at the facility that week 

(denominator) and the number of those 

HCP who have received a completed 

COVID–19 vaccination course 

(numerator). SNFs would submit 

COVID–19 vaccination data for at least 

1 week each month. If SNFs submit 

more than 1 week of data in a month, 

the most recent week’s data would be 

used for measure calculation purposes. 

Each quarter, the CDC would calculate 

a summary measure of COVID–19 

vaccination coverage from the 3 

monthly modules of data reported for 

the quarter. This quarterly rate would be 

publicly reported on the Care Compare 

website. Subsequent to the first refresh, 

one additional quarter of data would be 

added to the measure calculation during 

each advancing refresh, until the point 

four full quarters of data is reached. 

Thereafter, the measure would be 

reported using four rolling quarters of 

data on Care Compare. 

For purposes of submitting data to 

CMS for the FY 2023 SNF QRP, SNFs 

would be required to submit data for the 

period October 1, 2021 through 

December 31, 2021. Following the 

initial data submission quarter for the 

FY 2023 SNF QRP, subsequent 

compliance for the SNF QRP would be 

based on four quarters of such data 

submission. For more information on 

the measure’s proposed public reporting 

period, we refer readers to section 

VII.H.3. of this final rule. 

We invited public comment on our 

proposal to add a new measure, COVID– 

19 Vaccination Coverage among 

Healthcare Personnel (HCP), to the SNF 

QRP beginning with the FY 2023 SNF 

QRP. 

The following is a summary of the 

public comments received on our 

proposal to add a new measure, COVID– 

19 Vaccination Coverage among 

Healthcare Personnel (HCP), to the SNF 

QRP beginning with the FY 2023 SNF 

QRP and our responses: 

Comment: A number of organizations, 

including provider associations and 

patient advocacy groups, support the 

proposal to adopt the COVID–19 

Vaccination Coverage among HCP 

measure for the SNF QRP. Commenters 

agree that the measure would help 

assess the degree to which SNFs are 

taking steps to limit the spread of 

COVID–19 and reduce the risk of 

transmission within their facilities. 

Commenters pointed out that public 

reporting of COVID–19 vaccination 

among HCP on Care Compare would 

provide consumers with important 

information with which to make 

informed decisions about the safety of a 

SNF. Commenters also believe the 

information would provide greater 

transparency to Federal officials and 

other stakeholders seeking to effectively 

target vaccine hesitancy, as well as 

provide resources related to the COVID– 

19 vaccines. 

Response: We thank the commenters 

for their support and agree that the 

COVID–19 Vaccination among HCP 

measure will help assess the degree to 

which SNFs are taking steps to limit the 

spread of COVID–19 and assess the risk 

of transmission within their facilities. 

This is consistent with information 

published by the CDC and others, which 

has emphasized that healthcare settings, 

including SNFs, can be high-risk places 

for COVID–19 exposure and 

transmission, and notes that COVID–19 

can spread among HCP and residents 

given the close contact that may occur 

during the provision of care.88

Vaccination is a critical part of the 

nation’s strategy to effectively counter 

the spread of COVID–19 and ultimately 

help restore societal functioning.89 We 

also agree with commenters that public 

reporting of COVID–19 Vaccination 

Coverage among HCP on Care Compare 

would provide consumers with 

important information with which to 

make informed decisions about the 

safety of a SNF. 

Comment: One commenter cautioned 

against using the data in a way that 

adversely impacts the nursing home 

workforce, including SNF HCP, but 

believes the reporting will assist CMS to 

provide targeted support and education 

to providers. 

Response: The SNF QRP helps inform 

health care consumers about the quality 

of healthcare SNFs provide to their 

residents. The measure does not impose 

additional requirements on the HCP 

workforce. We agree with the 

commenter that public reporting of the 

COVID–19 Vaccination Coverage among 

HCP measure on Care Compare would 

provide consumers with important 

information with which to make 

informed decisions about the safety of a 

SNF. 

Comment: Another commenter urged 

CMS to require provider reporting of 

other activities related to vaccination, 

such as whether paid leave is provided 

for HCP to take off from work and 

recover from any side effects 


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90CBS News. More Than 20 States Not Ordering 

All Available Doses as COVID–19 Vaccinations 

Slow. Retrieved from https://www.cbsnews.com/ 

news/covid-19-vaccine-doses-states/. 

91 Good Rx. From Shortage to Surplus: A Growing 

Number of U.S. Counties Have Vacant COVID–19 

Vaccine Appointments. Retrieved from https://

www.goodrx.com/blog/covid-19-vaccine-surplusvacant-appointments/. 

experienced after taking the vaccine, 

believing this would make it easier for 

HCP to obtain vaccination. 

Response: We appreciate the 

commenters’ suggestions to collect 

additional information related to 

vaccinations, however CMS does not 

presently have the statutory authority to 

collect information related to paid leave 

or the side effects experienced after 

taking the vaccine. 

Comment: A few commenters 

recommended the measure should 

include all personnel in the facility, 

such as social services, dietary, and 

housekeeping, not just personnel who 

have direct contact with residents. 

Response: We proposed to include all 

HCP within the facility, such as social 

services, dietary and housekeeping, and 

refer readers to section VI.C.2.e. of the 

FY 2022 SNF proposed rule and to the 

Instructions for Completion of the 

Weekly Healthcare Personnel COVID–19 

Vaccination Cumulative Summary for 

Long-Term Care Facilities (57.219, REV 

3) at https://www.cdc.gov/nhsn/forms/ 

instr/57.219-toi-508.pdf which details 

all HCP included in the measure. 

Comment: One commenter stated the 

COVID–19 Vaccination Coverage among 

HCP is superfluous given the fact that 

CMS also proposed the SNF HAI 

measure which they believe to be a 

better indicator of a SNF’s overall 

infection prevention practices. 

Response: We disagree with the 

commenter’s statement that the COVID– 

19 Vaccination Coverage among HCP 

measure is superfluous since the 

measure and the SNF HAI measure each 

assess distinct aspects of infection 

prevention. The COVID–19 Vaccination 

among HCP measure assesses the 

percentage of HCP in the facility who 

have received a complete vaccination 

course for SARS–CoV–2. The SNF HAI 

measure assesses the percentage of 

healthcare acquired infections that 

result in a hospitalization. While it is 

true that the SNF HAI measure may 

capture a subset of the COVID–19 cases 

that result in hospitalization, we believe 

both measures are distinct and 

necessary to assess SNFs’ practices to 

mitigate hospitalizations for infections. 

Additionally, we believe it is important 

for patients and caregivers to have the 

COVID–19 Vaccination Coverage among 

HCP measure data to help them more 

directly assess how a SNF is mitigating 

the risk of COVID–19 transmission. 

Comment: One commenter was 

encouraged by the CDC’s measure 

validity testing following the MUC 

formal comment period earlier this year 

and the measure specifications 

subsequently delineated by the CDC in 

March 2021. Given the measure’s 

potential to generate actionable data on 

vaccination rates, they think it is 

important for CMS, in collaboration 

with the CDC, to continue to hone the 

measure as it is submitted for NQF 

endorsement in the future. 

Response: We thank the commenter 

for their support and we will continue 

to collaborate with the CDC. The CDC, 

in collaboration with CMS, are planning 

to submit the measure for consideration 

in the NQF Fall 2021 measure cycle. 

A number of commenters wrote in 

support of the measure’s concept and 

the need to encourage widespread 

vaccination among HCP. However, there 

were also several concerns with the 

measure, including burden, lack of 

access to the vaccine, concerns of staff 

intimidation if they elect not to receive 

the vaccine, the fact that it is unknown 

whether a booster vaccination will be 

necessary, and concern that the 

vaccinations have not received full FDA 

approval. We address each of these 

comments separately below: 

Comment: A couple of commenters 

spoke to the fact that COVID–19 

vaccination administration has been 

fragmented and challenging and were 

concerned whether vaccine supply 

would remain sufficient across the 

nation to ensure all HCP could receive 

it. 

Response: As part of its national 

strategy to address COVID–19, the 

current administration stated that it 

would work with states and the private 

sector to execute an aggressive 

vaccination strategy. The goal of the 

U.S. government is to ensure that every 

American who wants to receive a 

COVID–19 vaccine can receive one. 

While we acknowledge that vaccine 

supply was initially limited, more than 

20 states are no longer ordering all the 

vaccine doses allocated to them due to 

decline in demand,90 and more than 

1,000 counties are reporting a surplus of 

vaccine appointments.91 We understand 

that vaccine availability may vary based 

on location, and vaccination and 

medical staff authorized to administer 

the vaccination may not be readily 

available in all areas. Supply 

distribution is the responsibility of each 

state, and SNFs should continue to 

consult state and local health 

departments to understand the range of 

options for how vaccine provision can 

be made available to HCP. 

Comment: A couple of commenters 

expressed concern over the potential for 

inequality among SNFs because onedose vaccines are not equally available 

across the nation. They stated some 

SNFs would be at a disadvantage 

because of the 4-week waiting period 

between doses of the two-dose vaccines 

to reach complete vaccination status. 

Response: This measure provides 

information to patients about the extent 

to which HCP have completed a 

COVID–19 vaccination course during a 

defined period of time. Given this goal, 

geographic variation in vaccine 

availability, including the types of 

vaccines available, ultimately does not 

make the information captured by this 

measure any less valuable to 

stakeholders. 

Because we proposed to begin 

reporting the COVID–19 Vaccination 

Coverage among HCP measure using one 

quarter of data, there will be time during 

each quarter for persons receiving the 

two-dose vaccine to reach complete 

vaccination status. In the event that an 

HCP does not complete a vaccination 

course during a reporting period, they 

would still be captured when the 

measure is updated in the subsequent 

quarter, assuming the HCP remains 

eligible. 

Comment: One commenter noted that 

CMS proposed a COVID–19 Vaccination 

Coverage among HCP measure in the FY 

2022 Inpatient Prospective Payment 

System (IPPS) proposed rule and stated 

the numerator would be calculated 

based on HCP who received a 

completed vaccination course ‘‘since the 

vaccine was first available or on a 

repeated interval if revaccination is 

recommended.’’ The commenter 

requested CMS provide clarification 

how evolving vaccine recommendations 

will be accounted for in the COVID–19 

Vaccination Coverage among HCP 

measure proposed for the SNF QRP. 

Several other commenters questioned 

how vaccination boosters would factor 

into reporting requirements. 

Commenters stated it would be 

premature for CMS to adopt the measure 

because it is unknown how long the 

COVID–19 vaccination would be 

effective as well as whether and how 

often booster shots may be required. 

They noted that given the evolving 

nature of the COVID–19 virus, that 

information could change between the 

time a person receives a vaccine and the 

public reporting of the data. 

Commenters noted that these were 

important unanswered questions they 

thought would affect both the design 

and feasibility of any HCP vaccination 


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92Centers for Disease Control and Prevention. 

Vaccine Administration. Available at https://

www.cdc.gov/vaccines/covid-19/clinicalconsiderations/covid-19-vaccines-us.html. Accessed 

June 25, 2021. 

93Centers for Disease Control and Prevention. 

Covid-19 vaccines and new variants. Available at 

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

vaccines/effectiveness/work.html

#:∼:text=COVID%2D19%20vaccines%20and

%20new%20variants%20of%20the%

20virus&text=Current%20data%

20suggest%20that%20COVID,after%20they%20

are%20fully%20vaccinated. Accessed June 25, 

2021. 

measure and would likely result in a 

change to the measure definition. 

Several commenters suggested CMS 

wait until expectations are clarified 

about maintaining employees’ COVID– 

19 vaccinations. 

Response: The COVID–19 Vaccination 

Coverage among HCP measure is a 

measure of a completed COVID–19 

vaccination course (as proposed in 

section VI.C.2.e. of the FY 2022 SNF 

PPS proposed rule). A complete 

vaccination course may require one or 

more doses depending on the specific 

vaccine used. Currently, the need for 

COVID–19 booster doses has not been 

established, and no additional doses are 

currently recommended for HCP.92

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. 

Comment: We received several 

comments posing questions about the 

uncertainty the provider community, 

which we interpret to be SNFs, believe 

around the future of the COVID–19 

vaccination due to the prevalence of 

misinformation about COVID–19 and 

the vaccines. 

Response: We acknowledge that the 

science around the SARS–CoV–2 virus 

continues to evolve. We are still 

learning how effective the vaccines are 

against new variants of the virus that 

causes COVID–19, although current 

evidence suggests that the COVID–19 

vaccines authorized for use in the 

United States offer protection against 

most variants currently spreading in the 

United States.93 This is one of several 

reasons we proposed the COVID–19 

Vaccination Coverage among HCP 

measure. The CDC will continue to 

monitor the effectiveness of the COVID– 

19 vaccines. 

Comment: A number of commenters 

voiced concern that requiring SNFs to 

report this information for payment 

purposes could create incentives for 

SNF employers to coerce or intimidate 

HCP who decline the vaccine. They 

point out that vaccine hesitancy is a real 

challenge not only among the general 

public, but also among HCP. They note 

that some personnel have indicated a 

preference to wait until the vaccine 

receives full FDA approval before 

receiving it. These commenters 

expressed concern that adding the 

measure to the SNF QRP conflates the 

ability of a nursing home to overcome 

the independent, individual medical 

choices of its HCP with the ability of the 

nursing home to provide quality care to 

the residents living in the facility. Some 

commenters were concerned that 

healthcare workers who have not yet 

received the vaccine or who cannot for 

various reasons may be let go or have 

reduced hours based on an employer’s 

desire for higher reporting. They point 

to the challenges in finding healthcare 

workers to meet demand, and that 

requiring vaccines will only make it 

worse. For these reasons, they believe 

CMS should delay implementation and 

public reporting until FY 2023 or 

remove the measure entirely. 

Response: We appreciate that some 

HCP may have concerns about COVID– 

19 vaccinations, but the COVID–19 

Vaccination Coverage among HCP 

measure does not mandate or require 

SNF HCP to complete a COVID–19 

vaccination course in order to meet the 

measure’s data reporting requirements. 

The SNF QRP is a pay-for-reporting 

program and the number of HCP who 

have been vaccinated in a SNF does not 

impact SNF’s ability to successfully 

report the measure. Additionally, we 

believe it is important that the SNFs 

report COVID–19 Vaccination Coverage 

among HCP measure as soon as possible 

to assess the potential spread of COVID– 

19 among their HCP and assess the risk 

of transmission of COVID–19 within 

their facilities, and to help sustain the 

ability of SNFs to continue serving their 

communities throughout the PHE and 

beyond. 

Comment: A few commenters were 

concerned that if SNFs were found to 

have ‘‘missing data,’’ they would receive 

a monetary penalty or a reduction in 

reimbursement. 

Response: The SNF QRP is a pay-forreporting program and the measures 

under the SNF QRP are tools that 

measure or quantify healthcare 

processes, outcomes, patient 

perceptions, and organizational 

structure and/or systems that are 

associated with the ability to provide 

high-quality health care and/or that 

relate to one or more quality goals for 

health care. The rate of vaccination in 

a SNF is not tied to a SNF’s Medicare 

payment. 

To meet the reporting requirements 

for the COVID–19 Vaccination Coverage 

among HCP measure, we proposed that 

a SNF would have to report the 

cumulative number of HCP eligible to 

work in the SNF for at least one day 

during the reporting period and who 

received a complete vaccination course 

against SARS–CoV–2. SNFs would have 

to report data for the measure at least 

one week per month and could selfselect the week. For SNFs that report 

more than 1 week per month, the last 

week of the reporting month will be 

used. 

CMS’ contractor sends informational 

messages to SNFs that are not meeting 

Annual Payment Update (APU) 

thresholds on a quarterly basis ahead of 

each submission deadline. Information 

about how to sign up for these alerts can 

be found on the SNF QRP Help web 

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

Quality-Initiatives-Patient-AssessmentInstruments/NursingHomeQualityInits/ 

Skilled-Nursing-Facility-QualityReporting-Program/SNF-QualityReporting-Program-QRP-Help. 

Comment: A couple commenters 

expressed concern about unintended 

consequences and legal risks to their 

organization if HCP experience an 

adverse event related to vaccination, 

and therefore oppose adoption of the 

COVID–19 Vaccination Coverage among 

HCP measure into the SNF QRP. 

Response: It is unclear what 

unintended consequences and legal 

risks the commenters are referring to. 

The SNF QRP is a pay-for-reporting 

program, and SNFs are assessed under 

the program based on whether they have 

met the SNF QRP’s reporting 

requirements. The COVID–19 

Vaccination Coverage among HCP 

measure does not require HCP to be 

vaccinated in order for SNFs to 

successfully report the measure under 

the SNF QRP. 

Comment: One commenter raised 

concern about the possibility of a 

double jeopardy that would arise from 

the interplay of a SNF QRP measure on 

COVID–19 vaccination and the 

requirements of the interim final rule 

with comment period (the May 2021 

IFC). They note that under the May 2021 

IFC, a nursing home can be cited and 

receive a civil monetary penalty (CMP) 

for failure to report COVID–19 

vaccination data for a given week, while 

under the SNF QRP, a SNF may incur 

a rate reduction for a full calendar year 

if it fails to meet the reporting 

requirements. Several other commenters 

echoed the same concerns. 

Response: It is unclear what the 

commenter means by the term ‘‘double 

jeopardy’’, but we interpret it to mean 

that the commenter is concerned about 

being penalized twice for the same data 


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94U.S. Equal Employment Opportunity 

Commission. What You Should Know About 

COVID–19 and the ADA, the Rehabilitation Act, 

and Other EEO Laws. Available at https://

www.eeoc.gov/wysk/what-you-should-know-aboutcovid-19-and-ada-rehabilitation-act-and-other-eeolaws. Accessed June 25, 2021. 

submission requirements. We disagree 

with the commenter, as the LTC facility 

requirements of participation at 

(requirements) at § 483.80(g) and the 

SNF QRP are two separate requirements. 

The LTC facility requirements require 

nursing homes to report weekly on the 

COVID–19 vaccination status of all 

residents and staff as well as COVID–19 

therapeutic treatment administered to 

residents. As discussed in section 

VIII.C.2.e of this final rule, we proposed 

that SNFs would report the number of 

eligible HCP who have worked at the 

facility during 1 week of each month 

and the number of those HCP who have 

received a completed COVID–19 

vaccination course. Each system has its 

own methods of validation and carry 

separate penalties. We proposed the 

COVID–19 Vaccination Coverage among 

HCP measure under the SNF QRP. 

Comment: One commenter stated they 

did not support the adoption of the 

COVID–19 Vaccination Coverage among 

HCP measure into the SNF QRP because 

they believe it conflicts with the May 

2021 IFC that specifies a similar 

measure using similar data sources. 

Response: As described above, the 

regulations at § 483.80(g) finalized in 

the May 2021 IFC are for the LTC 

facilities’ requirements, and are separate 

from the SNF QRP. The purpose of the 

proposed COVID–19 Vaccination 

Coverage among HCP measure is 

different from the vaccination 

information reporting requirement in 

the May 2021 IFC. The proposed SNF 

QRP COVID–19 Vaccination Coverage 

among HCP measure will allow for the 

collection of this data under the SNF 

QRP and subsequent public reporting of 

facility-level HCP vaccination rates on 

Care Compare so that Medicare 

beneficiaries can make side-by-side 

facility comparisons to facilitate 

informed decision making in an 

accessible and user-friendly manner. 

The measure’s purpose is distinct from 

those laid out in the May 2021 IFC 

which are: To update the LTC facilities’ 

requirements to address the issues of 

resident and staff vaccination education 

and the reporting of COVID–19 

vaccinations and therapeutic treatments 

to the CDC; to ensure that all LTC 

facility residents and the staff that care 

for them are provided ongoing access to 

vaccination against COVID–19; to assist 

surveyors to determine individual 

facilities that may need to have focused 

infection control surveys; to monitor 

broader community uptake and to allow 

the CDC to identify and alert CMS to 

facilities that may need additional 

support in regards to vaccine 

administration and education. 

Comment: One commenter stated that 

since the May 2021 IFC was released, 

they have been reporting staff and 

resident vaccination rates weekly via 

NHSN’s Weekly HCP and Resident 

COVID–19 Vaccination Module. The 

proposal to add the COVID–19 

Vaccination Coverage among HCP 

measure to the SNF QRP uses the same 

reporting process but at a different 

frequency. This commenter 

recommended CMS align the reporting 

requirements at § 483.80(g) with the 

COVID–19 Vaccination Coverage among 

HCP measure reporting requirements or 

explain how to manage competing 

requirements in different rules. Another 

commenter was unclear which rule they 

should follow. Another commenter 

stated they support the requirement in 

this rule to report monthly but are 

concerned that once the PHE is lifted, it 

would be overly burdensome to ask 

providers to report every week. They 

requested that CMS respond and 

explain how to manage competing 

requirements in different rules. 

Response: The requirements finalized 

at § 483.80(g) are mandatory for 

participating in Medicare and are 

separate from the SNF QRP. Each of the 

requirements is met by reporting 

through the NHSN’s Weekly HCP 

COVID–19 Vaccination Module. We are 

clarifying that a SNF that submits four 

weeks of data to meet the requirements 

of participation at § 483.80(g) would 

also meet the data submission 

requirement for the COVID–19 

Vaccination Coverage among HCP for 

the SNF QRP. 

Comment: A number of commenters 

stated it is premature to begin tracking 

COVID–19 vaccinations because the 

COVID–19 vaccines are authorized 

through an EUA and do not have full 

FDA approval at this time. One 

commenter acknowledged that they 

were confident in the safety and efficacy 

of the three current vaccines but still 

finds it to be incongruous to adopt a 

measure into Federal Quality Reporting 

Programs that assess the use of a 

product that has not yet received full 

Federal approval. Several commenters 

stated the measure should not be 

adopted until full approval by FDA 

across all existing submitted vaccines 

under EUAs. Another commenter stated 

that until FDA approves the vaccines, 

they do not have control over the 

vaccination status of their employees. 

Response: The COVID–19 vaccines 

are authorized by the FDA for use 

through an Emergency Use 

Authorization (EUA). We refer readers 

to the FDA website for additional 

information related to FDA process for 

evaluating an EUA request at https://

www.fda.gov/vaccines-blood-biologics/ 

vaccines/emergency-use-authorizationvaccines-explained. The Equal 

Employment Opportunity Commission 

(EEOC) released updated and expanded 

technical assistance on May 28, 2021.94

Specifically the EEOC stated the Federal 

equal employment opportunity (EEO) 

laws do not prevent an employer from 

requiring all employees physically 

entering the workplace to be vaccinated 

for COVID–19, so long as the employer 

complies with the reasonable 

accommodation provisions of the 

Americans with Disabilities Act (ADA) 

and Title VII of the Civil Rights Act of 

1964 and other EEO considerations. In 

addition, FDA is closely monitoring the 

safety of the COVID–19 vaccines 

authorized for emergency use. We 

believe that due to the continued PHE 

and the ongoing risk of infection 

transmissions in the SNF population, 

the benefits of finalizing this measure in 

this year’s final rule are essential for 

patient safety. 

Comment: We received numerous 

comments requesting that CMS delay 

the adoption of the COVID–19 

Vaccination Coverage among HCP 

measure until it has received NQF 

endorsement. Commenters were 

concerned that since the measure has 

not been fully specified, tested, or 

endorsed by the NQF, then it may not 

be thoroughly tested and vetted, and 

may impact patients’ certainty that the 

data they rely on are reliable. Other 

commenters included language from the 

Post-Acute Care/Long-term Care 

Workgroup (Workgroup) of the 

Measures Application Partnership 

(MAP) meeting transcript to support 

their position. They all urged the 

agency, in addition to seeking NQF 

endorsement, to fully develop and test 

the measure for reliability and validity 

before implementing it in the SNF QRP. 

Response: Given the novel nature of 

the SARS–CoV–2 virus, and the 

significant and immediate health risk it 

poses in SNFs, we believe it is necessary 

to adopt this measure as soon as 

possible. Additionally, given the results 

from CDC’s preliminary validity testing 

of the data elements required for the 

measure numerator (described further in 

section VI.C.2.c. of the FY 2022 SNF 

PPS proposed rule), the alignment 

between the denominator of this 

measure and the denominator of the 

Influenza Vaccination among HCP 


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95Medicare COVID–19 Data Snapshot Overview. 

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

medicare-covid-19-data-snapshot-fact-sheet.pdf. 

Accessed July 12, 2021. 

measure (NQF#0431), and the MAP’s 

determination that the measure has face 

validity, CMS proposes the COVID–19 

Vaccination Coverage among HCP 

measure beginning with the FY 2023 

SNF QRP. As noted previously, the 

CDC, in collaboration with CMS, are 

planning to submit the measure for 

consideration in the NQF Fall 2021 

measure cycle. 

Comment: A commenter stated they 

did not believe CMS had the statutory 

authority to add the COVID–19 

Vaccination Coverage among HCP 

measure to the SNF QRP. The 

commenter went on to state that section 

1899B(a)(1)(B) of the IMPACT Act is 

intended to support interoperable 

patient care measures to compare 

outcomes across post-acute provider 

settings. They do not believe the 

proposed staff vaccination measure is a 

patient care measure. 

Response: We believe the commenter 

is referring to section 1899B(a)(1)(B) of 

the Act. We disagree with the 

commenter that we lack the statutory 

authority to propose this measure. 

Section 1899B(d)(1) of the Act requires 

the Secretary to specify resource use 

and other measures. Section 

1899B(a)(1)(B) requires, in part, that 

data on resource use and other measures 

under section 1899B(d)(1) of the Act 

facilitate coordinated care and improve 

Medicare beneficiary outcomes. 

Remaining COVID–19 free while 

receiving SNF care is critically 

important for Medicare beneficiaries, 

and thus a measure that increases the 

likelihood of this outcome would be 

considered a patient care measure. As 

illustrated in Medicare claims and 

encounter data,95 the number of 

Medicare beneficiaries hospitalized 

with COVID–19 in the last week of 

December 2020 was over 50,000, and 

the number of COVID–19 cases 

exceeded 4.3 million as of April 24, 

2021. We believe that the toll the COVID 

pandemic has taken on Medicare 

beneficiaries demonstrates the need for 

increased action to mitigate the effects 

of the ongoing pandemic. 

Section 1899B(a)(1)(B) of the Act also 

requires, in part, that data on resource 

use and other measures under section 

1899B(d)(1) of the Act be standardized 

and interoperable so as to allow for the 

exchange of such data among PAC 

providers, including SNFs. We have 

proposed the COVID–19 Vaccination 

Coverage among HCP measure under the 

IRF QRP in the FY 2022 IRF PPS 

proposed rule (86 FR 19105 through 

19108), and the LTCH QRP under the 

FY 2022 IPPS/LTCH PPS proposed rule 

(86 FR 25610 through 25613) consistent 

with these requirements. Further, this 

measure would facilitate patient care 

and care coordination during the 

discharge planning process. A 

discharging hospital or facility, in 

collaboration with the patient and 

family, could use this measure to 

coordinate care and ensure patient 

preferences are considered in the 

discharge plan. Patients at high risk for 

negative outcomes due to COVID–19 

(perhaps due to underlying conditions) 

can use healthcare provider vaccination 

rates when they are selecting a SNF for 

next-level care. 

Comment: A commenter noted that 

CMS, to date, has restricted all measures 

developed under section 1899B(a)(1)(B) 

of the Act to include only Medicare 

beneficiaries accessing their post-acute 

care benefit to align with the other postacute care settings. They recommended 

not finalizing the COVID–19 

Vaccination Coverage among HCP 

measure because it is not restricted to 

staff providing care to post-acute care 

residents and would be nearly 

impossible to collect. 

Response: To date, we have 

developed measures under section 

1899B of the Act to include only 

Medicare beneficiaries accessing their 

post-acute care benefit. We proposed the 

measure as specified by the CDC, which 

includes all of the staff within the 

facility because all staff within the 

facility place patients receiving postacute care (including SNF residents) at 

risk for getting COVID–19. This is true 

whether or not they are providing direct 

care to post-acute care patients. 

In regard to the comment about the 

near impossibility of collecting 

information exclusively among staff 

providing care to post-acute care 

residents, we agree. This is one of the 

reasons why the measure is specified to 

capture the information on all 

healthcare staff in the SNF, including 

personnel, such as dietary staff, 

administrators, or social workers. While 

it may be easy to identify SNF direct 

care staff who provide care to SNF 

residents, it would be nearly impossible 

to ensure other personnel, such as 

dietary staff, administrators, or social 

workers, interact exclusively with SNF 

patients. 

Comment: We heard from several 

commenters who found the COVID–19 

Vaccination Coverage measure among 

HCP was not aligned with the Influenza 

Vaccination Coverage among HCP (NQF 

#0431) measure as CMS stated in the 

proposed rule. They pointed out that 

circumstances around the use of the 

COVID–19 vaccine are not entirely 

comparable to those of the influenza 

vaccine. 

Response: We agree that there are key 

differences between the Influenza 

Vaccination among HCP measure and 

the COVID–19 Vaccination Coverage 

among HCP measure. We acknowledge 

that even though the CDC modeled the 

COVID–19 Vaccination Coverage among 

HCP measure after the Influenza 

Vaccination among HCP measure, FDAapproved influenza vaccines and the 

authorized COVID–19 vaccines differ in 

multiple ways. The reporting 

requirements for the numerator of the 

COVID–19 Vaccination Coverage among 

HCP measure that one commenter listed 

are due to the fact that some COVID–19 

vaccines require two doses to reach full 

vaccination status, while some COVID– 

19 vaccines require only one dose. The 

measures are aligned with respect to the 

reporting mechanism used to report data 

(the NHSN) and key components of the 

measure specifications (for example, the 

definition of the denominator), but the 

measures allow for important 

differences to reflect the reality that the 

circumstances around vaccine 

administration (that the commenter 

points out) are not identical. 

Comment: Several commenters 

pointed to the fact that SNFs have many 

questions about the specifics of the 

COVID–19 Vaccination Coverage among 

HCP measure such as what the longterm plans for using the measure in the 

SNF QRP are. Another commenter 

thought the measure seemed 

unnecessary based on the current 

vaccination push and the fact that due 

to the Federal Vaccination Schedule, 

healthcare workers would already have 

received the vaccination. This 

commenter did not believe it addressed 

many of the unknowns still ahead 

regarding the virus. 

Response: We interpret the 

commenter’s reference to the ‘‘Federal 

Vaccination Schedule’’ to be referring to 

the eligibility criteria during the initial 

rollout of the COVID–19 vaccine. When 

the U.S. supply of COVID–19 vaccine 

was limited, CDC provided 

recommendations to Federal, state, and 

local governments about who should be 

vaccinated first. While CDC made 

recommendations for who should be 

offered the COVID–19 vaccines first, 

each state had its own plan. CMS 

acknowledges that healthcare workers 

were given priority in receiving the 

vaccine, but as reported by Medscape 


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42488 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

96Medscape. Disturbing Number of Hospital 

Workers Still Unvaccinated. Available at https://

www.medscape.com/viewarticle/953871. Accessed 

July 13, 2021. 

97Pfizer-BioNtech COVID–19 vaccine. Available 

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

pfizer-biontech-covid-19-vaccine. 

98Moderna COVID–19 vaccine. Available at 

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

moderna-covid-19-vaccine. 

99 Janssen COVID–19 vaccine. Available at 

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

janssen-covid-19-vaccine. 

Medical News on June 28, 2021,96

Federal data show that one in four 

hospital workers across the United 

States are still unvaccinated, and only 

one in every three hospital workers are 

vaccinated in the nation’s 50 largest 

health systems. We believe it is critical 

to measure staff vaccination rates among 

SNFs even as vaccinations become more 

common, especially in light of the 

vaccine hesitancy other comments have 

pointed out. 

In response to the comment asking 

about the long-term plans for using the 

measure, as described in sections 

VII.C.2.e and VII.H.3. of this final rule, 

we proposed to adopt the COVID–19 

Vaccination Coverage among HCP 

measure into the SNF QRP and publicly 

report on SNF performance. Once a 

measure is adopted under the SNF QRP, 

the measure will remain in effect until 

CMS proposes that it be removed, 

suspended, or replaced. We refer 

readers to the FY 2016 SNF PPS final 

rule (80 FR 46431 through 46432) for 

details on this policy. 

Comment: A commenter questioned 

whether the COVID–19 Vaccination 

among HCP measure aligned with the 

Merit-based Incentive Payment System 

(MIPS) measure that was reviewed by 

the MAP and assesses patients who 

received at least one dose (in addition 

to a complete course). 

Response: We understand the 

commenter to be questioning whether 

this measure is similar to the measure 

considered for another quality reporting 

program, the Merit-based Incentive 

Payment System (MIPS) for clinicians. If 

so, MUC—0045, the SARS–Co–V–2 

Vaccination by Clinician measure 

differs from the COVID–19 Vaccination 

Coverage among HCP measure. Most 

notably, the SARS–CoV–2 Vaccination 

by Clinician measure assesses the 

proportion of patients who received at 

least one SARS–CoV–2 vaccination 

while the COVID–19 Vaccination 

Coverage among HCP measure assesses 

the proportion of HCP who complete a 

SARS–CoV–2 vaccination course. 

Comment: Commenters pointed out 

that the Influenza Vaccination Coverage 

among HCP (NQF #0431) measure 

utilizes providers working in the facility 

for the denominator whereas the 

proposed COVID–19 metric utilizes 

providers eligible to work in the facility. 

Several commenters requested that CMS 

revise the COVID–19 Vaccination 

Coverage among HCP measure 

denominator to include eligible 

providers who have worked at the 

facility during the period being 

measured, similar to the influenza 

measure. The commenters believe this 

would be important due to differences 

across states as to whom would be 

considered ‘‘eligible’’ to work due to 

laws such as the Family Medical Leave 

Act (FMLA) and state-level laws 

associated with defining employee 

status. 

Response: As described in section 

VII.G.3. of this final rule, we proposed 

the COVID–19 Vaccination Coverage 

among HCP measure to include HCP 

who work regularly in the SNF, and to 

require SNFs to use the specifications 

and data collection tools for the 

proposed COVID–19 Vaccination 

Coverage among HCP as required by 

CDC as of the time that the data are 

submitted. Subsequent to the 

publication of the FY 2022 SNF PPS 

proposed rule on April 8, 2021, the CDC 

released the Instructions for Completion 

of the Weekly Healthcare Personnel 

COVID–19 Vaccination Cumulative 

Summary for Long-Term Care Facilities 

(57.219, REV3) which are available at 

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

57.219-toi-508.pdf . The document 

defines HCP eligible to have worked to 

include those scheduled to work in the 

facility at least one day every week. The 

document instructs SNFs to count any 

HCP working part of a day, as well as 

those that may be on temporary leave 

during the week of data collection. 

Temporary leave was further defined as 

less than or equal to 2 weeks in 

duration. Because the measurement 

period covered by the Influenza 

Vaccination Coverage among HCP (NQF 

#0431) measure is quite long (the entire 

6 month influenza season), such 

absences do not impact the Influenza 

Vaccination Coverage among HCP (NQF 

#0431) measure denominator. However, 

in order to provide more timely 

measurement of COVID–19 vaccination 

coverage while also reducing the burden 

of data collection for SNFs, we proposed 

the measurement period of the COVID– 

19 Vaccination among HCP measure to 

be only one week, considerably shorter 

than the time period covered by the 

Influenza Vaccination Coverage among 

HCP (NQF #0431) measure, and a 

number of regularly working HCP who 

would be counted within the 6-month 

period of the Influenza Vaccination 

Coverage Measure may be absent during 

this shortened period. Therefore, HCP 

who regularly work in the SNF, but may 

be temporarily absent for up to 2 weeks, 

are still to be included in the COVID– 

19 Vaccination Coverage among HCP 

measure as these regular workers will be 

working during other weeks of the 

reporting month. While differences may 

exist across states in employment 

eligibility definitions, the CDC 

definition for purposes of this measure 

includes HCP eligible to have worked 

and scheduled to work in the facility at 

least one day during the week of data 

collection. This approach provides a 

consistent definition of eligibility which 

is necessary for national and regional 

data analyses. 

Comment: One commenter provided 

several recommendations for revising 

the denominator of the COVID–19 

Vaccination Coverage among HCP 

measure. They stated there are several 

contraindications or exclusions that go 

beyond allergies to the ingredients of 

the vaccine, and therefore these persons 

should be excluded from the 

denominator as well. They specifically 

point to individuals who have been 

vaccinated within the last 2 weeks and 

individuals who have received 

monoclonal antibody or another 

COVID–19 therapy and individuals with 

an active COVID–19 infection as 

persons who should be excluded from 

the measure. They also urged CMS to 

ensure that the regulatory language has 

the flexibility to accommodate these and 

any future changes. 

Response: We thank the commenter 

for the recommendations. The CDC 

website describes a number of clinical 

considerations for the use of COVID–19 

vaccines on its website at https://

www.cdc.gov/vaccines/covid-19/ 

downloads/summary-interim-clinicalconsiderations.pdf. These 

considerations are separate from the 

contraindications to the vaccines. 

Contraindications to the vaccines can be 

found in the FDA Fact Sheets for the 

authorized COVID–19 vaccines, which 

are accessible through the FDA web 

pages for those vaccines.97 98 99

Therefore, we disagree with the 

commenter and do not believe the 

definition of the denominator needs to 

be changed. 

Comment: One commenter stated that 

if CMS proceeded with finalizing the 

measure, they strongly encourage the 

agency to consider including all HCP in 

the denominator, at least for an initial 

reporting period and to allow for 


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100CMS. Interim Final Rule—COVID–19 Vaccine 

Immunization Requirements for Residents and 

Staff. Retrieved from https://www.cms.gov/files/ 

document/qso-21-19-nh.pdf. 

101NHSN. Instructions for Completion of the 

Weekly Healthcare Personnel COVID–19 

Vaccination Cumulative Summary for Long-Term 

Care Facilities (57.219, REV 3). Retrieved from 

https://www.cdc.gov/nhsn/forms/instr/57.219-toi508.pdf. 

consistent cross-provider reporting and 

accurate measurement and comparisons. 

They also stated CMS should include a 

clear explanation in public reporting 

that the measure includes HCP with 

contraindications. 

Response: We interpret the 

commenter to be stating that the 

denominator should include HCP with 

and without contraindications to the 

vaccination. We believe that excluding 

HCP with contraindications from the 

measure strikes an appropriate balance 

between obtaining accurate estimates of 

vaccine rates among HCP within SNFs 

and not holding a SNF accountable for 

HCP with a COVID–19 vaccination 

contraindication, as the number of HCP 

with contraindications or exclusions 

from vaccination is expected to be low. 

Comment: One commenter raised a 

question about guidance to state survey 

agencies found in QSO–21–19–NH.100

In it, they pointed out a discrepancy in 

how CMS defined ‘‘staff’’ for COVID–19 

vaccination reporting and the definition 

provided for HCP under the proposed 

quality measure. They are concerned 

about the confusion it will cause 

providers. 

Response: We interpret the 

commenter’s point to be about the 

definitions for purposes of reporting 

data to the NHSN to meet the LTC 

facility requirements at § 483.80(g) and 

the requirements for the SNF QRP. Our 

May 11, 2021 guidance, QSO–21–19– 

NH, defines ‘‘staff’’ to mean individuals 

who work in the facility on a regular 

(that is, at least once a week) basis, 

including individuals who may not be 

physically in the LTC facility for a 

period of time due to illness, disability, 

or scheduled time off, but who are 

expected to return to work. This also 

includes individuals under contract or 

arrangement, including hospice and 

dialysis staff, physical therapists, 

occupational therapists, mental health 

professionals, or volunteers, who are in 

the facility on a regular basis, as the 

vaccine is available. The instructions for 

completing the NHSN Weekly 

Healthcare Personnel COVID–19 

Vaccination Cumulative Summary for 

Long-Term Care Facilities 101 defines 

‘‘Number of HCP that were eligible to 

have worked at this facility for at least 

1 day during the week of data 

collection’’ to include employees, 

contractors, or students, trainees, and 

volunteers who are scheduled to work 

in the facility at least one day every 

week. Working any part of a day is 

considered as working 1 day. HCP are 

to be included even if they are on 

temporary leave during the week of data 

collection. Temporary leave is defined 

as less than or equal to 2 weeks in 

duration. Examples of temporary leave 

may include sick leave or vacation. In 

instances where temporary leave 

extends past 2 weeks, the healthcare 

worker should not be included in 

question #1 for the current week of data 

collection. We believe the NHSN 

instructions to be a clarification of the 

QSO–21–19–NH memo, provided to 

facilitate completion of the module in a 

consistent manner. 

Comment: One commenter had 

questions on what ‘‘fully vaccinated’’ 

meant. 

Response: The term ‘‘fully 

vaccinated’’ is not used in the proposed 

COVID–19 Vaccination Coverage among 

HCP measure. We proposed the 

numerator for the COVID–19 

Vaccination Coverage among HCP 

measure to include a complete 

vaccination course as defined in section 

VI.C.2.e. of the FY 2022 SNF PPS 

proposed rule. We refer the commenter 

to the CDC’s website where the term 

‘‘fully vaccinated’’ is defined at https:// 

www.cdc.gov/coronavirus/2019-ncov/ 

vaccines/fully-vaccinated.html. 

After careful consideration of the 

public comments we received, we are 

finalizing our proposal to adopt the 

COVID–19 Vaccination Coverage among 

Healthcare Personnel (HCP) measure 

beginning with the FY 2023 SNF QRP 

as proposed. 

3. Update to the Transfer of Health 

(TOH) Information to the Patient—PostAcute Care (PAC) Measure Beginning 

With the FY 2023 SNF QRP 

We proposed to update the Transfer of 

Health Information to the Patient—PostAcute Care (PAC) measure denominator 

to exclude residents discharged home 

under the care of an organized home 

health service or hospice. This measure 

assesses for and reports on the timely 

transfer of health information, 

specifically transfer of a medication list. 

We adopted this measure in the FY 2020 

SNF PPS final rule (84 FR 38761 

through 38764) beginning with the FY 

2022 SNF QRP. It is a process measure 

that evaluates for the transfer of 

information when a resident is 

discharged from his or her current PAC 

setting to a private home/apartment, 

board and care home, assisted living, 

group home, transitional living, or home 

under the care of an organized home 

health service organization or hospice. 

This measure, adopted under section 

1899B(c)(1)(E) of the Act, was 

developed to be a standardized measure 

for the IRF QRP, LTCH QRP, SNF QRP, 

and Home Health (HH) QRP. The 

measure is calculated by one 

standardized data element that asks, ‘‘At 

the time of discharge, did the facility 

provide the resident’s current 

reconciled medication list to the 

resident, family, and/or caregiver?’’ The 

discharge location is captured by items 

on the Minimum Data Set (MDS). 

Specifically, we proposed to update 

the measure denominator. Currently, the 

measure denominators for both the 

TOH-Patient and the TOH-Provider 

measure assess the number of residents 

discharged home under the care of an 

organized home health service 

organization or hospice. In order to 

align the measure with the IRF QRP, 

LTCH QRP and HH QRP and avoid 

counting the resident in both TOH 

measures in the SNF QRP, we proposed 

to remove this location from the 

definition of the denominator for the 

TOH-Patient measure. Therefore, we 

proposed to update the denominator for 

the TOH-Patient measure to only 

discharges to a private home/apartment, 

board and care home, assisted living, 

group home, or transitional living. For 

additional technical information 

regarding the TOH-Patient measure, we 

refer readers to the document titled 

‘‘Final Specifications for SNF QRP 

Quality Measures and Standardized 

Patient Assessment Data Elements’’ 

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

Medicare/Quality-Initiatives-PatientAssessment-Instruments/NursingHome

QualityInits/Downloads/FinalSpecifications-for-SNF-QRP-QualityMeasures-and-SPADEs.pdf. 

We invited public comment on our 

proposal to update the denominator of 

the Transfer of Health (TOH) 

Information to the Patient—Post-Acute 

Care (PAC) measure (TOH-Patient-PAC 

measure) beginning with the FY 2023 

SNF QRP. 

The following is a summary of the 

public comments received on our 

proposal to update the denominator of 

the TOH Information to the Patient— 

PAC measure beginning with the FY 

2023 SNF QRP and our responses: 

Comment: We received overwhelming 

support for our proposal to update the 

TOH-Patient-PAC measure’s 

denominator to remove the inclusion of 

‘‘home under care of an organized home 

health service organization or hospice.’’ 

Provider and trade associations agreed 

that the update will reduce denominator 

redundancy in the two TOH 


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Information—PAC measures. One 

commenter stated that the update will 

provide a refined measure that more 

accurately accounts for the SNF’s 

performance in this area. A few 

commenters also were appreciative of 

CMS’ review of measures to reduce 

unnecessary provider burden. 

Response: We appreciate the 

commenters’ support. 

Comment: A few commenters stated 

that it was premature to introduce this 

measure beginning with the FY 2023 

SNF QRP since the assessment data 

would not be available to calculate 

performance. Since the TOH-Patient 

measure requires the use of MDS item 

A2105—Discharge Status, an item that 

is currently not available on the 

assessment tool used by SNFs (the MDS 

V1.17.2) commenters did not believe the 

information could be collected. They 

noted that in the IFC published on May 

8, 2020 entitled ‘‘Medicare and 

Medicaid Programs, Basic Health 

Program, and Exchanges; Additional 

Policy and Regulatory Revisions in 

Response to the COVID–19 Public 

Health Emergency and Delay of Certain 

Reporting Requirements for the Skilled 

Nursing Facility Quality Reporting 

Program’’ (85 FR 27550), CMS delayed 

collection of MDS item A2105— 

Discharge Status until a particular point 

in time after the PHE has ended. 

Therefore, commenters requested that 

CMS consider reinstating the delay of 

this measure as originally stated in the 

May 8, 2020 IFC. 

Response: We acknowledge that the 

current version of the MDS, MDS 3.0 

v1.17.2, which SNFs use to submit data 

to meet the requirements of the SNF 

QRP, does not currently include the 

data elements needed to report the 

TOH-Patient-PAC measure which we 

finalized for data collection beginning 

October 1, 2020 (84 FR 38761 through 

38764). In the May 8, 2020 IFC (85 FR 

27550), we delayed data collection for 

certain SNF QRP items, including the 

MDS item A2105, until the October 1 

date that is at least two full fiscal years 

after the end of the PHE for COVID–19. 

However, because it is uncertain when 

the PHE will end, we proposed to make 

the measure denominator specification 

change effective FY 2023. Therefore, 

when the PHE ends, and the MDS item 

A2105—Discharge Status collection 

begins, the measure update would 

already be in place. 

Comment: One commenter opposed 

our proposal to update the denominator 

specifications for the TOH-Patient-PAC 

measure. The commenter was 

concerned that revising the denominator 

would remove the responsibility of the 

SNF to provide the medication list to 

the ‘‘patient, family, or caregiver’’ when 

the patient is transferred to home health 

or hospice providers. The commenter 

believes that the current medication list 

should be provided to the resident and 

family/caregivers regardless of the 

discharge location because family 

caregivers are often involved in assisting 

the person they are caring for with their 

medications. 

Response: The TOH-Patient-PAC data 

element under the TOH-Patient-PAC 

measure asks about the transfer of a 

reconciled medication list to the patient, 

family, and/or caregiver. While 

residents discharged home under the 

care of an organized home health 

service organization or hospice will no 

longer be included in the denominator 

of the TOH-Patient-PAC measure to 

reduce redundancy with the TOHProvider-PAC measure, we acknowledge 

the importance of family and/or 

caregivers and encourage care 

collaboration between the SNF and the 

family or caregiver when authorized by 

the patient. SNFs are required under 

§ 483.21(c)(2)(iii) to provide a resident 

at discharge with a discharge summary 

that includes, but is not limited to, 

reconciliation of all pre-discharge 

medications with the resident’s postdischarge medications (both prescribed 

and over-the-counter). We refer the 

commenter to the FY 2020 SNF PPS 

final rule (84 FR 38761 through 38764) 

for additional information about this 

process measure. 

Comment: One commenter requested 

clarity on the measure and the problem 

CMS is aiming to resolve. 

Response: We refer the reader to the 

FY 2020 SNF PPS proposed and final 

rules (84 FR 17638 through 17643 and 

84 FR 38761 through 38764, 

respectively) where the TOH-PatientPAC measure was proposed and 

finalized. For additional technical 

information regarding the TOH-PatientPAC measure, we refer readers to the 

document titled ‘‘Final Specifications 

for SNF QRP Quality Measures and 

Standardized Patient Assessment Data 

Elements’’ available at https://

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

Downloads/Final-Specifications-forSNF-QRP-Quality-Measures-andSPADEs.pdf. 

We refer the reader to section VI.C.3. 

of the FY 2022 SNF proposed rule 

where we described the issue this 

proposal addresses. Currently, the 

measure denominators for both the 

TOH-Patient and the TOH-Provider 

measure assess the number of residents 

discharged home under the care of an 

organized home health service 

organization or hospice. In order to 

align the measure with the IRF QRP, 

LTCH QRP and HH QRP and avoid 

counting the resident in both TOH 

measures in the SNF QRP, we proposed 

to remove this location from the 

definition of the denominator for the 

TOH-Patient measure. 

After careful consideration of the 

public comments we received, we are 

finalizing our proposal to update the 

denominator for the Transfer of Health 

(TOH) Information to the Patient–PostAcute Care (PAC) measure under 

section 1899B(c)(1)(E) of the Act 

beginning with the CY 2023 SNF QRP 

as proposed. 

D. SNF QRP Quality Measures Under 

Consideration for Future Years: Request 

for Information (RFI) 

We solicited input on the importance, 

relevance, appropriateness, and 

applicability of each of the measures 

and concepts under consideration listed 

in Table 25 for future years in the SNF 

QRP. 


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103https://www.cdc.gov/nhsn/ltc/weekly-covidvac/index.html. 

We received several comments on this 

RFI, which are summarized below: 

Comment: Most commenters 

supported the inclusion of all the 

proposed measures listed in Table 25. 

One commenter stated that all of the 

measures and measure concepts are 

important and relevant for assessing 

quality of care delivered to SNF 

patients. 

Many commenters supported the 

concept of frailty, and one commenter 

stated that frailty assessments provide a 

means of identifying older adults most 

vulnerable to adverse health outcomes. 

Commenters were generally 

supportive of the measure concept for 

shared decision-making process and 

pointed out it was important to ensuring 

care delivered in a SNF was in line with 

the person’s goals and values. Other 

commenters questioned how it could be 

captured in the SNF QRP. One 

commenter shared concerns about using 

shared decision-making as a quality 

measure, and recommended CMS only 

use claims-based quality measures. 

Several commenters supported the 

concept of patient reported outcomes 

(PROs) while others were uncertain 

what CMS intends with the term patient 

reported outcomes. One commenter 

stressed the importance of PROs since 

they determine outcomes based on 

information obtained directly from 

patients, and therefore provide greater 

insight into patients’ experience of the 

outcomes of care. Another commenter 

echoed that and stated that patients and 

caregivers are the best sources of 

information reflecting the totality of the 

patient experience. 

Several commenters were supportive 

of the inclusion of pain management 

quality measures because pain is a 

common occurrence with SNF residents 

and may be under recognized and 

undertreated. One commenter stated 

that the development of an appropriate 

pain assessment and pain management 

processes measure is a clinically 

challenging domain that requires much 

more attention. Another commenter 

agreed stating that it is an area to focus 

on since given the current opioid 

epidemic, appropriate pain management 

has become a delicate and challenging 

subject. 

Commenters were generally 

supportive of the concept of health 

equity in quality measurement. They 

agree that closing the health equity gap 

is essential to ensure optimal health 

services and outcomes to all Americans 

regardless of individual characteristics, 

and one commenter noted that health 

equity is a vital quality measure to 

ensure that long term care is equal for 

all residents. 

A couple of commenters encouraged 

CMS to remove topped out measures 

and low occurrence measures to ensure 

it remains relevant to quality and 

performance. Commenters also 

suggested other concepts for quality 

measurement in the SNF QRP such as: 

Nutritional status, cognitive status, and 

advance directives. 

Response: We appreciate the input 

provided by commenters. While we will 

not be responding to specific comments 

submitted in response to this RFI in this 

final rule, we intend to use this input to 

inform our future measure development 

efforts. 

E. Fast Healthcare Interoperability 

Resources (FHIR) in Support of Digital 

Quality Measurement in Quality 

Programs—RFI 

1. Solicitation of Comments 

We sought input on the following 

steps that would enable transformation 

of CMS’ quality measurement enterprise 

to be fully digital. 

• What EHR/IT systems do you use 

and do you participate in a health 

information exchange (HIE)? 

• How do you currently share 

information with other providers? 

• In what ways could we incentivize 

or reward innovative uses of health 

information technology (IT) that could 

reduce burden for post-acute care 

settings, including but not limited to 

SNFs? 

• What additional resources or tools 

would post-acute care settings, 

including but not limited to SNFs, and 

health IT vendors find helpful to 

support the testing, implementation, 

collection, and reporting of all measures 

using FHIR standards via secure APIs to 

reinforce the sharing of patient health 

information between care settings? 

• Would vendors, including those 

that service post-acute care settings, 

such as SNFs, be interested in or willing 

to participate in pilots or models of 

alternative approaches to quality 

measurement that would align 

standards for quality measure data 

collection across care settings to 

improve care coordination, such as 

sharing patient data via secure FHIR API 

as the basis for calculating and reporting 

digital measures? 

While we will not be responding to 

specific comments submitted in 

response to this RFI in this final rule, 

we appreciate all of the comments on 

and interest in this topic. We believe 

that this input is very valuable in the 

continuing development of our 

transition to digital quality 

measurement in CMS quality programs. 

We will continue to take all comments 

into account as we develop future 

regulatory proposals or future 

subregulatory policy guidance for our 

digital quality measurement efforts. 

F. Closing the Health Equity Gap in 

Post-Acute Care Quality Reporting 

Programs—RFI 

1. Solicitation of Public Comment 

Under authority of the IMPACT Act 

and section 1888(e)(6) of the Act, we 

solicited comment on the possibility of 

revising measure development, and the 

collection of other Standardized Patient 

Assessment Data Elements that address 

gaps in health equity in the SNF QRP. 

Any potential health equity data 

collection or measure reporting within a 

CMS program that might result from 

public comments received in response 

to this solicitation would be addressed 

through a separate notice-and-comment 

rulemaking in the future. 

Specifically, we invited public 

comment on the following: 

• Recommendations for quality 

measures, or measurement domains that 

address health equity, for use in the 

SNF QRP. 

• As finalized in the FY 2020 SNF 

PPS final rule (84 FR 38805 through 

38817), SNFs must report certain 

standardized patient assessment data 

elements on SDOH, including race, 

ethnicity, preferred language, interpreter 

services, health literacy, transportation 

and social isolation.102 We solicited 

guidance on any additional items, 

including standardized patient 

assessment data elements that could be 

used to assess health equity in the care 

of SNF residents, for use in the SNF 

QRP. 

• Recommendations for how CMS 

can promote health equity in outcomes 

among SNF residents. For example, we 

are interested in feedback regarding 

whether including facility-level quality 

measure results stratified by social risk 

factors and social determinants of health 

(for example, dual eligibility for 

Medicare and Medicaid, race) in 

confidential feedback reports could 

allow facilities to identify gaps in the 

quality of care they provide. (For 

example, methods similar or analogous 

to the CMS Disparity Methods 103 which 

provide hospital-level confidential 

results stratified by dual eligibility for 

condition-specific readmission 

measures, which are currently included 

in the Hospital Readmission Reduction 


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Program (see 84 FR 42496 through 

42500)). 

• Methods that commenters or their 

organizations use in employing data to 

reduce disparities and improve patient 

outcomes, including the source(s) of 

data used, as appropriate. 

• Given the importance of structured 

data and health IT standards for the 

capture, use, and exchange of relevant 

health data for improving health equity, 

the existing challenges providers’ 

encounter for effective capture, use, and 

exchange of health information, 

including data on race, ethnicity, and 

other social determinants of health, to 

support care delivery and decision 

making. 

While we will not be responding to 

specific comments submitted in 

response to this Health Equity RFI in 

this final rule, we appreciate all of the 

comments and interest in this topic. We 

will continue to take all concerns, 

comments, and suggestions into account 

as we continue work to address and 

develop policies on this important 

topic. It is our hope to provide 

additional stratified information to 

providers related to race and ethnicity if 

feasible. The provision of stratified 

measure results will allow PAC 

providers to understand how they are 

performing with respect to certain 

patient risk groups, to support these 

providers in their efforts to ensure 

equity for all of their patients and to 

identify opportunities for improvements 

in health outcomes. 

G. Form, Manner, and Timing of Data 

Submission Under the SNF QRP 

1. Background 

We refer readers to the regulatory text 

at 42 CFR 413.360(b) for information 

regarding the current policies for 

reporting SNF QRP data. 

2. Schedule for Data Submission of the 

SNF HAI Measure Beginning With the 

FY 2023 QRP 

The SNF HAI measure, which we 

discuss in section VII.C.1. of this final 

rule, is a Medicare FFS claims-based 

measure. Because claims-based 

measures can be calculated based on 

data that have already been submitted to 

the Medicare program for payment 

purposes, no additional information 

collection would be required from 

SNFs. We proposed to use 1 year of FY 

2019 claims data (October 1, 2018 

through September 30, 2019) for the FY 

2023 SNF QRP. We proposed to use FY 

2019 data to calculate this measure 

because it is the most recent fiscal year 

of data that has not been exempted due 

to the PHE. Beginning with the FY 2024 

SNF QRP, compliance with APU 

reporting requirements would use FY 

2021 claims data (October 1, 2020 

through September 30, 2021) and 

advance by one FY with each annual 

refresh. Due to the fact that Q1 and Q2 

2020 data were excepted by CMS related 

to the COVID–19 PHE, these quarters of 

data would not be used for purposes of 

the QRP. For information on public 

reporting of the SNF HAI measure, we 

refer you to Table 29 in section 

VII.H.4.c. of this final rule. 

We invited public comment on this 

proposal. 

The following is a summary of the 

public comments received on the 

proposed Schedule for Data Submission 

of the SNF HAI measure beginning with 

the FY 2023 QRP and our responses: 

Comment: One commenter was 

supportive of the measure’s schedule for 

data submission. 

Response: We thank this commenter 

for their support of the SNF HAI data 

submission schedule. 

Comment: Another commenter 

supported the collection of SNF HAI 

data, but does not want CMS to report 

it publicly until the PHE has expired. 

Response: We thank this commenter 

for their support. Any comments related 

to SNF HAI public reporting will be 

addressed in section VII.H.2. of this 

final rule. 

After careful consideration of the 

public comments we received, we are 

finalizing the proposed schedule for 

data submission of the SNF HAI 

measure beginning with the FY 2023 

SNF QRP as proposed. 

3. Method of Data Submission for 

COVID–19 Vaccination Coverage 

Among Healthcare Personnel (HCP) 

Measure 

As discussed in section VII.C.2 of this 

final rule, we proposed to require that 

SNFs submit data on the COVID–19 

Vaccination Coverage among HCP 

measure through the Centers for Disease 

Control and Prevention (CDC)/National 

Healthcare Safety Network (NHSN). The 

NHSN is a secure, internet-based 

surveillance system maintained by the 

CDC that can be utilized by all types of 

healthcare facilities in the United States, 

including acute care hospitals, longterm acute care hospitals, psychiatric 

hospitals, rehabilitation hospitals, 

outpatient dialysis centers, ambulatory 

surgery centers, and SNFs. The NHSN 

enables healthcare facilities to collect 

and use vaccination data, and 

information on other adverse events. 

NHSN collects data via a Web-based 

tool hosted by the CDC (http://

www.cdc.gov/). The NHSN is provided 

free of charge. We proposed for SNFs to 

submit the data needed to calculate the 

COVID–19 Vaccination Coverage among 

Healthcare Personnel measure using the 

NHSN’s standard data submission 

requirements. CDC/NHSN requirements 

include adherence to training 

requirements, use of CDC measure 

specifications, data element definitions, 

data submission requirements and 

instructions, data submission 

timeframes, as well as NHSN 

participation forms and indications to 

CDC allowing CMS to access data for 

this measure for the SNF quality 

reporting program purposes. Detailed 

requirements for NHSN participation, 

measure specifications, and data 

collection can be found at http://

www.cdc.gov/nhsn/. We proposed to 

require SNFs to use the specifications 

and data collection tools for the 

proposed COVID–19 Vaccination 

Coverage among Healthcare Personnel 

measure as required by CDC as of the 

time that the data are submitted. 

We invited public comment on this 

proposal. The following is a summary of 

the public comments received on the 

proposed Method of Data Submission 

for COVID–19 Vaccination Coverage 

among Healthcare Personnel measure 

and our responses: 

Comment: One commenter requested 

that CMS provide further information 

on how reporting to a system 

maintained by the CDC would be shared 

with CMS for purposes of determining 

SNF QRP reporting compliance. They 

questioned how the SNF QRP 

compliance rate would be calculated 

since the measure is not submitted 

through the MDS. Another commenter 

recommended the use of the COVID–19 

Module of the NHSN to report 

healthcare employee vaccination rates, 

rather than requiring a separate 

reporting process through the SNF QRP. 

Response: We interpret the 

commenter to be referring to the SNF 

QRP reporting requirements for the SNF 

Annual Payment Update (APU). As 

explained in section VII.G.3. of this final 

rule, the mechanism through which the 

data for calculating the COVID–19 

Vaccination Coverage among HCP 

measure would be the Weekly 

Healthcare Personnel COVID–19 

Vaccination Cumulative Summary for 

Long-Term Care Facilities Module 104 of 

the NHSN. There is no ‘‘separate’’ 

submission system. The NHSN collects 

the data submitted by SNFs, calculates 

the summary score, and transmits the 

information to CMS on a quarterly basis. 

CMS would use that information to 

determine whether a SNF has met the 


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105 Data Tracking Worksheet for COVID–19 

Vaccination among Healthcare Personnel at https:// 

www.cdc.gov/nhsn/hps/weekly-covid-vac/ 

index.html. 

SNF QRP reporting requirements for the 

COVID–19 Vaccination among HCP 

measure. 

Comment: One commenter raised 

concerns about implementing a measure 

based on NHSN data. They explained 

that SNFs have experienced problems in 

the past year using the NHSN for 

reporting COVID–19 related data 

because they were unaware that they 

had made errors. They stated there was 

no process in place for SNF providers to 

receive feedback on data submissions 

and correct any errors before the data 

was made public and assessed. Given 

the importance of identifying potential 

errors and making corrections, they are 

concerned SNFs will be unfairly 

penalized. 

Response: SNFs will have access to 

provider reports on their NHSN measure 

performance prior to the submission 

deadline. Additionally, CMS’ contractor 

sends informational messages to SNFs 

that are not meeting Annual Payment 

Update (APU) thresholds on a quarterly 

basis ahead of each submission 

deadline. Information about how to sign 

up for these alerts can be found on the 

SNF QRP Help web page at https://

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

Skilled-Nursing-Facility-QualityReporting-Program/SNF-QualityReporting-Program-QRP-Help. 

Comment: Several commenters 

expressed concerns about the 

administrative burden associated with 

reporting of the measure through NHSN 

and other systems. They pointed to 

other reporting systems being used 

around the country and stated that this 

would be duplicative reporting. Several 

commenters referenced the Department 

of Health and Human Services 

TeleTracking system, and various state 

agencies and databases. They stated that 

having to utilize these systems in 

addition to the NHSN and its reporting 

period utilizes additional resources and 

will require multiple tracking strategies 

to keep up. They urged CMS to use data 

from these systems without requiring 

additional data collection in the NHSN. 

Response: The TeleTracking system 

was one system that was used to manage 

the critical first months of the PHE for 

COVID–19, as it was critical that the 

Federal Government received data to 

facilitate planning, monitoring, and 

resource allocation during the COVID– 

19 Public Health Emergency (PHE). The 

TeleTracking system collects a number 

of data points, such as ventilators in the 

facility, ventilators in use, ICU beds 

available and ICU beds occupied. 

However, the TeleTracking system was 

not used for the SNF QRP. We proposed 

to use the NHSN COVID–19 Modules for 

tracking COVID–19 vaccination 

Coverage among HCP across all sites of 

service, including SNFs as most of the 

state Immunization Information Systems 

do not include the information needed 

to calculate the COVID–19 Vaccination 

Coverage among HCP. Additionally, the 

CDC has developed a Data Tracking 

Worksheet to assist SNFs collect 

information for the COVID–19 

Vaccination Coverage among HCP 

measure. After entering the COVID–19 

vaccination data for each HCP into the 

Tracking Worksheet and selecting a 

week, the data to be entered into the 

NHSN would automatically be 

calculated on the Reporting 

Summary.105

Comment: One commenter 

encouraged CMS to evaluate both 

methods of how data are submitted (that 

is, the TeleTracking system and the 

NHSN) and select just one standardized 

data reporting system and process. This 

commenter was in favor of using the 

NHSN to report the COVID–19 

Vaccination Coverage among HCP 

measure because all care settings are 

using it to report the Influenza 

Vaccination Coverage measure among 

HCP and discontinuing COVID–19 

vaccination reporting to the HHS 

tracking system. 

Response: We proposed using the 

NHSN COVID–19 Modules for tracking 

COVID–19 Vaccination Coverage among 

HCP across all sites of service, including 

SNFs because most of the state 

Immunization Information Systems do 

not include the information needed to 

calculate the COVID–19 Vaccination 

Coverage among HCP measure. 

Comment: A few commenters 

commented on CMS’s statement that the 

COVID–19 Vaccination Coverage among 

HCP measure was modeled after the 

Influenza Vaccination Coverage among 

HCP measure. They believe there are 

key differences between the two 

measures, such as how the vaccines are 

administered and data are collected. 

Another provider listed the different 

reporting requirements for the 

numerator for the COVID–19 

vaccination as compared to the 

influenza vaccination. 

Response: We acknowledge that there 

are implementation differences between 

the two measures, even though the CDC 

modeled the COVID–19 Vaccination 

Coverage among HCP measure after the 

Influenza Vaccination Coverage among 

HCP measure. It is true that the 

influenza vaccine and the COVID–19 

vaccine are not identical, and therefore 

the administration of these vaccines will 

not be identical. The key differences 

between the reporting requirements for 

the numerator of the COVID–19 

Vaccination Coverage among HCP 

measure that the one commenter listed 

out are due to the fact that 2 of the 3 

available COVID–19 vaccines require 2 

doses to reach full vaccination status, 

and the 3rd available COVID–19 vaccine 

requires only 1 dose. 

Comment: One commenter stated that 

the reporting burden for the COVID–19 

Vaccination Coverage among HCP 

measure would be high since certain 

health care settings, including SNFs, do 

not currently use the NHSN to report 

data for the SNF QRP. Adopting the 

measure would require adjustments in 

workflow for which CMS would need to 

provide significant technical support. 

Response: We disagree with the 

commenter, as SNFs are currently 

required to submit COVID–19 HCP 

vaccination data through the CDC’s 

NHSN Long-term Care Facility COVID– 

19 Module of the NHSN. We refer 

readers to § 483.80(g). Therefore we 

believe there will be no additional 

burden imposed with the adoption of 

the SNF QRP measure. 

Comment: One commenter attributed 

the burden of reporting to the fact that 

the commenter keeps employee health 

records separate from their electronic 

health records (EHRs) due to health 

privacy concerns. Other commenters 

attributed the burden of reporting to the 

fact that they cannot or have not 

routinely collected recorded 

information about medical 

contraindications or the reason for the 

employees’ declination in their 

employee health records. They stated 

that because the indications and 

contraindications for receiving the 

vaccine have changed frequently, and 

ongoing findings and studies will 

continue to do so, collecting this 

information will be even more difficult 

to track. One commenter stated it will 

be challenging for providers to obtain 

the full count of adult students/trainees 

and volunteers associated with the 

healthcare system, as these individuals 

are not always captured or identified as 

such in their HR databases. Therefore 

attempting to identify, collect, and 

extract data on employee vaccinations 

are inherently difficult and burdensome. 

Response: SNFs have experience 

tracking information and collecting data 

to inform their care approaches and 

business practices and have been 

collecting information related to 

COVID–19 infections and vaccinations. 

While SNFs will not have the burden of 


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106 Data Tracking Worksheet for COVID–19 

Vaccination among Healthcare Personnel at https:// 

www.cdc.gov/nhsn/hps/weekly-covid-vac/ 

index.html. 

registering and learning how to use the 

NHSN, we acknowledge there will be 

burden with collecting the required 

information. However, we believe it will 

be minimal because SNFs already have 

experience successfully reporting 

information using the NHSN reporting 

modules. We refer readers to section 

XI.A.5. of this final rule for an estimate 

of burden related to the COVID–19 

Vaccination Coverage among HCP 

measure. The data sources for the 

number of HCP who have received 

COVID–19 vaccines may include HCP 

health records and paper and/or 

electronic documentation of vaccination 

given at the healthcare facility, 

pharmacy, or elsewhere. Further, HCP 

receiving vaccination elsewhere may 

provide documentation of vaccination. 

Additionally, the CDC has provided a 

number of resources including a tool 

called the Data Tracking Worksheet for 

COVID–19 Vaccination among 

Healthcare Personnel to help SNFs log 

and track this information.106

We also understand the commenter to 

state that the contraindications and 

precautions for the COVID–19 vaccine 

are changing as more studies are 

released. We would like to clarify that 

the contraindications have not changed. 

There are additional considerations 

around timing of the vaccine and which 

vaccine might be more appropriate for 

persons with underlying medications 

that are more clearly understood now. A 

summary of interim clinical 

considerations can be found at https:// 

www.cdc.gov/vaccines/covid-19/ 

downloads/summary-interim-clinicalconsiderations.pdf. 

Comment: We received a comment in 

response to the proposed adoption of 

the COVID–19 Vaccination Coverage 

among HCP measure for the SNF QRP 

recommending CMS assess 

Immunization Information Systems 

(IIS). 

Response: We understand 

Immunization information systems (IIS) 

to be confidential, population-based, 

computerized databases that record 

immunization doses administered by 

participating providers to persons 

residing within a given geopolitical area 

but these systems are not standardized 

across all SNFs. The Department of HHS 

has an Immunization Information 

Systems Support Branch (IISSB), that 

facilitates the development, 

implementation, and acceptance of 

these systems, but they are overseen by 

the states and/or organizations who 

develop them. CMS proposed using the 

NHSN COVID–19 Modules for 

collecting data on the COVID–19 

Vaccination Coverage among HCP 

across all sites of service, including 

SNFs. 

After careful consideration of the 

public comments we received, we are 

finalizing the method of data 

submission for COVID–19 Vaccination 

Coverage among Healthcare Personnel 

measure as proposed. 

4. Schedule for Data Submission of the 

COVID–19 Vaccination Coverage 

Among Healthcare Personnel Measure 

Beginning With the FY 2023 SNF QRP 

As discussed in section VII.C.2. of this 

final rule, we proposed to adopt the 

COVID–19 Vaccination Coverage among 

HCP quality measure beginning with the 

FY 2023 SNF QRP. Given the timesensitive nature of this measure in light 

of the PHE, we proposed an initial data 

submission period from October 1, 2021 

through December 31, 2021. Starting in 

CY 2022, SNFs would be required to 

submit data for the entire calendar year 

beginning with the FY 2024 SNF QRP. 

SNFs would submit data for the 

measure through the CDC/NHSN webbased surveillance system. SNFs would 

use the COVID–19 vaccination data 

collection module in the NHSN Longterm Care (LTC) Component to report 

the cumulative number of HCP eligible 

to work in the healthcare facility for at 

least 1 day during the reporting period, 

excluding persons with 

contraindications to COVID–19 

vaccination (denominator) and the 

cumulative number of HCP eligible to 

work in the SNF for at least 1 day 

during the reporting period and who 

received a complete vaccination course 

against COVID–19 (numerator). SNFs 

would submit COVID–19 vaccination 

data through the NHSN for at least 1 

week each month and the CDC would 

report to CMS quarterly. We invited 

public comment on this proposal. The 

following is a summary of the public 

comments received on the proposed 

Schedule for Data Submission of the 

COVID–19 Vaccination Coverage among 

Healthcare Personnel Measure 

beginning with the FY 2023 SNF QRP 

and our responses: 

Comment: One commenter requested 

that CMS clarify when SNFs should 

submit vaccination data so the data 

reported will be consistent among all 

SNFs. 

Response: We proposed SNFs submit 

vaccination data 1 week out of every 

month, but with the option for SNFs to 

choose which week to report. 

Comment: We received several 

comments requesting that CMS consider 

easing the reporting frequency for the 

COVID–19 Vaccination Coverage among 

HCP measure. They stated that reporting 

vaccinations 1 week per month, rather 

than one time per quarter is 

burdensome. A couple of providers 

support quarterly reporting since the 

Influenza Vaccination among HCP 

measure uses quarterly reporting. 

Response: We want to clarify that the 

COVID–19 Vaccination Coverage among 

HCP measure is reported to the CDC 

through the NHSN at least 1 week per 

month. Each quarter the CDC averages 

the 3 weeks of data collected over the 

3 months and sends a quarterly average 

vaccination rate for each provider to 

CMS. We proposed a reporting schedule 

of 1 week per month to provide 

vaccination coverage data on a more 

timely basis than the Influenza 

Vaccination Coverage among HCP (NQF 

#0431), while also reducing the burden 

on SNFs that weekly reporting of this 

information would have been. 

Comment: A commenter stated that 

CMS did not explain the feedback 

reports and the timeline for feedback on 

the COVID–19 Vaccination Coverage 

among HCP measure as required by the 

IMPACT Act. 

Response: Historically, we have 

provided the following types of 

confidential provider feedback reports 

that give providers opportunity to 

review and correct data: (1) Review and 

Correct, which allows providers to 

review and correct their data for any 

given CY quarter, as early as one day 

following the end of the given quarter, 

but prior to the data submission 

deadline for that quarter, which falls 

approximately 4.5 months after the end 

of the quarter; and (2) Provider Preview 

Report, the purpose of which is to allow 

providers to preview their quality 

measure scores that will be publicly 

posted for the upcoming refresh of Care 

Compare, and also allows providers to 

request a formal review of the data 

contained within, should the provider 

disagree with the reported measure 

results. 

We also provide Quality Measure 

Reports (Facility and Patient-Level), the 

purpose of which is to allow providers 

to improve quality based on the most 

up-to-date data they have entered and/ 

or modified within our systems. This 

report type is not related to public 

reporting, and is produced solely for the 

benefit of quality improvement. Quality 

Measure Reports are not related to 

public reporting and do not observe the 

quarterly data submission deadlines of 

assessment-based data, and will 

continue to capture and include any and 

all data entered and/or modified beyond 

any data submission deadline. We 


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provide Quality Measure Reports in 

order to give providers, including SNFs, 

the most accurate picture of quality 

within their facility, allowing for the 

improvement of quality. While we have 

historically added new measures to the 

Quality Measure reports prior to public 

reporting, the Quality Measure reports 

are not related to public reporting. 

Because we believe it is in the best 

interest of Medicare beneficiaries that 

we publicly report the results of the 

COVID–19 Vaccination HCP measures 

as soon as is feasible, in this instance, 

we are not able to add this measure to 

the Quality Measure reports prior to 

public reporting. Instead, we plan to 

add this new measure to the Quality 

Measure reports in fall 2022, at the 

earliest, which will in no way affect a 

SNF’s ability to review and/or correct 

their data for this measure, nor will it 

affect a SNF’s ability to preview the 

COVID–19 Vaccination HCP data prior 

to the public posting of this data. 

The COVID–19 Vaccination HCP 

measure is stewarded by the CDC 

NHSN. To date, we have never added 

any of the CDC NHSN measures to the 

Review and Correct report, as the data 

for these measures are at the CDC. In 

lieu of this, the CDC makes accessible to 

PAC providers, including SNFs, reports 

that are similar to the Review and 

Correct reports that allow for real-time 

review of data submissions for all CDC 

NHSN measures adopted for use in the 

CMS PAC QRPs, including the SNF 

QRP. These reports are referred to as the 

‘‘CMS Reports’’ within the Analysis 

Reports page in the NHSN Application. 

Such a report exists for each CDC/NHSN 

measure within each of the PAC 

programs, and each report is intended to 

mimic the data that will be sent to CMS 

on their behalf. This report will exist to 

serve the same ‘‘review and correct’’ 

purposes for the COVID–19 Vaccination 

Coverage among HCP measure. The CDC 

publishes reference guides for each 

facility type (including SNF) and each 

NHSN measure, which explain how to 

run and interpret the reports. 

We will provide SNFs with a preview 

of SNF performance on the COVID–19 

Vaccination Coverage among HCP 

measure, available on the SNF Provider 

Preview Report, which will be issued 

approximately 3 months prior to 

displaying the measure on Care 

Compare. As always, SNFs will have a 

full 30 days to preview their data. 

Should a SNF disagree with their 

measure results, they can request a 

formal review of their data by CMS. 

Instruction for submitting such a request 

are available on the SNF Quality 

Reporting Public Reporting website at 

https://www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/NursingHomeQualityInits/ 

Skilled-Nursing-Facility-QualityReporting-Program/SNF-QualityReporting-Program-Public-Reporting. 

After careful consideration of the 

public comments we received, we are 

finalizing the schedule for data 

submission of the COVID–19 

Vaccination Coverage among Healthcare 

Personnel measure beginning with the 

FY 2023 SNF QRP as proposed. 

5. Consolidated Appropriations Act and 

the SNF QRP 

On December 27, 2020, Congress 

enacted the Consolidated 

Appropriations Act, 2021 (CAA) (Pub. 

L. 116–260). Section 111(a)(3) of 

Division CC of the CAA amends section 

1888 of the Act by adding a new 

paragraph (h)(12), which requires the 

Secretary to apply a process to validate 

the measures submitted under the SNF 

VBP and the measures and data 

submitted under the SNF QRP as 

appropriate, which may be similar to 

the process specified under the Hospital 

Inpatient Quality Reporting (IQR) 

Program for validating inpatient 

hospital measures. We plan to develop 

a process for validating the SNF QRP 

measures and data and implement this 

policy as soon as technically feasible. 

We will provide more details and seek 

public comment in future rulemaking. 

For more information on the SNF VBP 

please refer to section VIII. of this rule. 

H. Policies Regarding Public Display of 

Measure Data for the SNF QRP 

1. Background 

Section 1899B(g) of the Act requires 

the Secretary to establish procedures for 

making the SNF QRP data available to 

the public, including the performance of 

individual SNFs, after ensuring that 

SNFs have the opportunity to review 

their data prior to public display. SNF 

QRP measure data are currently 

displayed on the Nursing homes 

including rehab services website within 

Care Compare and the Provider Data 

Catalog. Both Care Compare and the 

Provider Data Catalog replaced Nursing 

Home Compare and Data.Medicare.gov, 

which were retired in December 2020. 

For a more detailed discussion about 

our policies regarding public display of 

SNF QRP measure data and procedures 

for the opportunity to review and 

correct data and information, we refer 

readers to the FY 2017 SNF PPS final 

rule (81 FR 52045 through 52048). 

2. Public Reporting of the Skilled 

Nursing Facility Healthcare-Associated 

Infections Requiring Hospitalization 

Measure Beginning With the FY 2023 

SNF QRP 

We proposed public reporting for the 

SNF HAI measure beginning with the 

April 2022 Care Compare refresh or as 

soon as technically feasible using data 

collected from discharges in FY 2019 

beginning October 1, 2018 through 

September 30, 2019. Provider preview 

reports would be distributed in January 

2022. A SNF’s HAI rates would be 

displayed based on 1 fiscal year of data. 

Since we cannot publicly report data 

from Q1 and Q2 of 2020 due to the PHE, 

we proposed to use data collected from 

discharges in FY 2021 (October 1, 2020 

through September 30, 2021) for public 

reporting of the SNF HAI measure in the 

October 2022 Care Compare refresh. 

Thereafter, the SNF HAI measure would 

be calculated using four quarters of FY 

data for the annual refresh on Care 

Compare. Claims-based measures are 

only refreshed on Care Compare 

annually. To ensure statistical reliability 

of the data, we proposed assigning SNFs 

with fewer than 25 eligible stays during 

a performance period to a separate 

category: ‘‘The number of resident stays 

is too small to report.’’ Eligible stays 

meet the measure’s denominator 

inclusion criteria, and we refer readers 

to the Skilled Nursing Facility 

Healthcare-Associated Infections 

Requiring Hospitalization for the Skilled 

Nursing Facility Quality Reporting 

Program Technical Report available at 

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

snf-hai-technical-report.pdf/ for more 

details. If a SNF had fewer than 25 

eligible stays, the SNF’s performance 

would not be publicly reported for the 

measure for that performance period. 

We refer readers to CMS’s SNF QRP 

Public Reporting web page for more 

information available at https://

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

Skilled-Nursing-Facility-QualityReporting-Program/SNF-QualityReporting-Program-Public-Reporting. 

We invited public comment on this 

proposal for the public display of the 

SNF HAI measure on Care Compare. 

The following is a summary of the 

public comments received on our 

proposal for the public display of the 

SNF HAI measure on Care Compare and 

our responses: 

Comment: Several commenters 

supported the proposed public reporting 

schedule. 

Response: We appreciate our 

commenters for their support in the 


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42496 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

107 Kimball, A., Hatfield, K.M., Arons, M., James, 

A., Taylor, J., Spicer, K., Bardossy, A.C., Oakley, 

L.P., Tanwar, S., Chisty, Z., Bell, J.M., Methner, M., 

Harney, J., Jacobs, J.R., Carlson, C.M., McLaughlin, 

H.P., Stone, N., Clark, S., Brostrom-Smith, C., Page, 

L.C., . . . CDC COVID–19 Investigation Team 

(2020). Asymptomatic and Presymptomatic SARS– 

CoV–2 Infections in Residents of a Long-Term Care 

Skilled Nursing Facility—King County, 

Washington, March 2020. MMWR. Morbidity and 

mortality weekly report, 69(13), 377–381. https://

doi.org/10.15585/mmwr.mm6913e1. 

108McMichael, T.M., Clark, S., Pogosjans, S., Kay, 

M., Lewis, J., Baer, A., Kawakami, V., Lukoff, M.D., 

Ferro, J., Brostrom-Smith, C., Riedo, F.X., Russell, 

D., Hiatt, B., Montgomery, P., Rao, A.K., Currie, 

D.W., Chow, E.J., Tobolowsky, F., Bardossy, A.C., 

Oakley, L.P., . . . Public Health—Seattle & King 

County, EvergreenHealth, and CDC COVID–19 

Investigation Team (2020). COVID–19 in a LongTerm Care Facility—King County, Washington, 

February 27–March 9, 2020. MMWR. Morbidity and 

mortality weekly report, 69(12), 339–342. https://

doi.org/10.15585/mmwr.mm6912e1. 

109Centers for Disease Control and Prevention. 

Science Brief: COVID–19 Vaccines and Vaccination. 

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

ncov/science/science-briefs/fully-vaccinatedpeople.html. 

public display schedule of the SNF HAI 

measure. 

Comment: A couple of commenters 

recommended delaying SNF HAI 

measure adoption due to concerns that 

FY 2021 will include COVID–19 data 

and therefore not be comparable to FY 

2019 non-COVID–19 data. Commenters 

suggested delaying public reporting 

until after the end of the PHE to avoid 

penalizing SNFs. 

Response: As long as SNFs report 

their HAI rates, which will occur at no 

additional burden since the measure is 

claims-based, they will satisfy the 

reporting requirements for the measure. 

To clarify, we do not intend to use FY 

2019 data as a benchmark for 

comparison against FY 2021 data. 

Instead, the measure identifies SNFs 

that have notably higher rates of HAIs 

that are acquired during SNF care and 

result in hospitalization, when 

compared to the performance of other 

SNFs in the United States in the same 

time period. COVID–19 has heightened 

the importance of infection prevention 

and control programs and the need to 

report HAI data. Evidence suggests that 

higher COVID–19 transmission in 

healthcare settings, including SNFs, is 

associated with poorer infection control, 

staff rotations between multiple SNFs, 

and inadequate patient COVID–19 

screenings.107 108 We will continue to 

evaluate the impact of the PHE and 

explore the impact of COVID–19 on 

quality reporting. 

Comment: One commenter opposed 

CMS excluding SNFs with fewer than 

25 admissions from public reporting of 

the SNF HAI measure. 

Response: Infection control in small 

SNFs is as essential as in larger SNFs. 

We proposed the minimum reporting 

threshold to ensure sufficient reliability 

and to mitigate the risk of exposing 

personally identifiable information (PII) 

and protected health information (PHI). 

This proposal of minimum threshold for 

public reporting is in alignment with 

the existing SNF QRP claims-based 

measures, specifically the Discharge to 

Community (DTC) and Potentially 

Preventable 30-Day Post-Discharge 

Readmission (PPR) measures. 

After careful consideration of the 

public comments we received, we are 

finalizing the proposal to publicly 

report the SNF HAI measure beginning 

with the April 2022 refresh as proposed. 

3. Public Reporting of the COVID–19 

Vaccination Coverage Among 

Healthcare Personnel (HCP) Measure 

Beginning With the FY 2023 SNF QRP 

We proposed to publicly report the 

COVID–19 Vaccination Coverage among 

Healthcare Personnel measure 

beginning with the October 2022 Care 

Compare refresh or as soon as 

technically feasible using data collected 

for Q4 2021 (October 1, 2021 through 

December 31, 2021). If finalized as 

proposed, a SNF’s HCP COVID–19 

vaccination coverage rate would be 

displayed based on one quarter of data. 

Provider preview reports would be 

distributed in July 2022. Thereafter, 

HCP COVID–19 vaccination coverage 

rates would be displayed based on one 

quarter of data updated quarterly. 

Subsequent to this, one additional 

quarter of data would be added to the 

measure calculation during each 

advancing refresh, until the point four 

full quarters of data is reached. 

Thereafter, the measure would be 

reported using four rolling quarters of 

data. 

We invited public comment on this 

proposal for the public display of the 

COVID–19 Vaccination Coverage among 

HCP measure on Care Compare. The 

following is a summary of the public 

comments received on our proposal for 

the public display of the COVID–19 

Vaccination Coverage among HCP 

measure on Care Compare and our 

responses: 

Comment: Several commenters 

supported the proposal to publicly 

report the COVID–19 Vaccination 

Coverage among HCP measure 

beginning with the October 2022 Care 

Compare refresh or as soon as 

technically feasible. The commenters 

stated that publishing facility-level data 

on HCP vaccination rates would also 

provide additional information about 

SNFs pandemic response and readiness 

efforts. 

Response: We thank the commenters 

for their support and agree that 

publishing facility-level data on HCP 

vaccination rates would also provide 

additional information about SNFs’ 

pandemic response and readiness 

efforts. 

Comment: One commenter suggested 

reporting the percentage of HCP that 

had received their dose, broken out by 

first and second dose, as well as the 

percentage of all facility staff that have 

received their dose, broken out by first 

and second dose. 

Response: We believe the value of the 

measure is in knowing the number of 

HCP who have completed their 

vaccination course as accumulating 

evidence indicates fully vaccinated 

people are able to participate in most 

activities with very low risk of acquiring 

or transmitting SARS–CoV–2.109

Comment: A commenter requested 

that CMS reconsider how the measure is 

calculated for public reporting. They 

supported the concept of reporting one 

quarter of data. They recommend that 

after the first refresh, rather than 

calculating a summary measure of the 

COVID–19 vaccination coverage from 

the 3 monthly modules of data reported 

for the quarter during each refresh and 

adding one additional quarter of data to 

the measure calculation during each 

advancing refresh, until the point that 

four full quarters of data is reached, to 

use an alternate approach. They 

recommend updating the information 

monthly with only the most recent data, 

such that the measure would be 

consumed as the most recent quarter of 

data refreshed quarterly. They caution 

that averaging over 12 months would 

result in the dilution of the most recent, 

and potentially more meaningful 

information, and may actually 

discourage higher provider vaccine 

uptake rates since it would be harder to 

change performance on this measure. 

Response: We agree with the 

commenters’ concern with regard to 

timely display of publicly reported data. 

We believe it is important to make the 

most up-to-date data available to 

beneficiaries, which will support them 

in making essential decisions about 

health care. We agree with these 

concerns, and find that it is appropriate 

to revise the public reporting policy for 

this measure to use quarterly reporting, 

as opposed to averaging over four 

rolling quarters, which allows the most 

recent quarter data to be displayed for 

the reasons outlined by the commenter. 

This revision would result in publishing 

information that is more up to date and 

would not affect the data collection 

schedule established for submitting data 

to NHSN for the COVID–19 vaccination 


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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42497 

110Centers for Disease Control and Prevention. 

Building Confidence in COVID–19 Vaccines. 

Available at https://www.cdc.gov/vaccines/covid19/vaccinate-with-confidence.html. 

111Centers for Disease Control and Prevention. 

Updated Healthcare Infection Prevention and 

Control Recommendations in Response to COVID– 

19 Vaccination. Available at https://www.cdc.gov/ 

coronavirus/2019-ncov/hcp/infection-control-aftervaccination.html. Accessed June 26, 2021. 

measure. This revision would simply 

update the way the measure’s data are 

displayed for the public reporting 

purposes. 

Comment: One commenter 

recommended that CMS either delay 

adoption of the measure for at least 1 

year (that is, until October 1, 2022), or 

adopt the measure for voluntary 

reporting for at least the first year so it 

would not appear as though the 

Administration supported mandatory 

vaccinations. 

Response: We believe that the 

unprecedented risks associated with the 

COVID–19 PHE warrant direct and 

prompt attention and, that it is 

important to begin publicly reporting 

this measure as proposed. However, as 

discussed in section VII.C.2.e. of this 

final rule, the COVID–19 Vaccination 

Coverage among HCP measure does not 

require SNF HCP to be vaccinated in 

order for SNFs to report the measure 

under the SNF QRP. 

Comment: One commenter stated that 

several state legislatures were 

considering laws to prohibit an 

employer from forcing employees to be 

vaccinated for COVID–19, while other 

states are considering legislation to 

specifically authorize employermandated vaccinations. The commenter 

is concerned that provider performance 

on the measure could vary significantly 

based on differing state laws. 

Response: We believe that the 

unprecedented risks associated with the 

PHE for COVID–19 warrant direct 

attention. Further, the COVID–19 

Vaccination Coverage among HCP 

measure does not require providers to 

adopt mandatory vaccination policies. 

To support a comprehensive vaccine 

administration strategy, we encourage 

SNFs to engage in the provision of 

appropriate and accessible education 

and vaccine-offering activities. Many 

SNFs across the country are educating 

staff, patients, and patient 

representatives, participating in vaccine 

distribution programs, and reporting 

vaccine administration. The CDC has a 

number of resources 110 available to 

providers to assist in building vaccine 

confidence. 

Consistent vaccination reporting by 

SNFs via the NHSN will help patients 

and their caregivers identify SNFs that 

have potential issues with vaccine 

confidence or slow uptake among staff. 

Implementation of COVID–19 vaccine 

education and vaccination programs in 

SNFs will help protect patients and 

staff, allowing for an expedited return to 

more normal routines, including timely 

preventive healthcare; family, caregiver, 

and community visitation; and group 

and individual activities.111

Comment: Several commenters 

questioned whether the COVID–19 

Vaccination Coverage among HCP 

measure’s information will be of value 

in 2023 and beyond given the time 

associated with data collection, 

submission, and validation. While they 

support the rights of consumers to 

access real-time meaningful data to help 

inform healthcare decision-making, they 

believe that the use of a single, dated 

measure is not a true reflection of the 

safety or quality of care delivered at the 

SNF. 

Response: We disagree with the 

commenter and believe the measure 

should be publicly reported. As far as 

the timeliness of the reporting, the SNF 

QRP public display policies, as finalized 

in the FY 2017 SNF PPS final rule (81 

FR 52041), allows 4.5 months after the 

end of the reporting quarter for SNFs to 

submit SNF QRP data. A number of 

administrative tasks must then occur in 

sequential order between the time SNF 

QRP data are submitted and are reported 

in Care Compare to ensure the validity 

of the data and to allow SNFs sufficient 

time to appeal any determinations of 

APU non-compliance. We have 

streamlined the process as much as 

possible, but must take these steps to 

ensure we are publishing accurate data. 

Additionally, the COVID–19 

Vaccination Coverage among HCP 

measure will be one of several measures 

on Care Compare that patients and 

caregivers can use to make informed 

healthcare decisions. As with all other 

measures, we will routinely monitor 

this measure’s performance, including 

assessing performance gaps across 

SNFs, and ensure the measure remains 

valid, reliable, and useful to consumers. 

Comment: One commenter stated that 

since the COVID–19 vaccination rates 

for both staff and residents are now 

posted on the nursing home site at 

data.cms.gov (as a result of the new 

reporting requirements at § 483.80(g)) 

that adding the COVID–19 Vaccination 

Coverage among HCP measure to the 

SNF QRP for the stated purpose of 

transparency appears to be duplicative, 

unnecessary, and potentially more 

confusing. One commenter urged the 

CDC and CMS to use the data collected 

as a result of the change made to LTC 

Requirements of Participation at 

§ 483.80(g) to publish on Care Compare 

since they believe it would provide a 

more accurate and comprehensive 

measure of HCP vaccination. Another 

commenter urged CMS to direct 

consumers to use the TeleTracking 

system to find vaccination rates. 

Response: We disagree with these 

comments. The Care Compare provides 

a user-friendly interface that patients 

and caregivers can use to make 

informed decisions about healthcare 

based on cost, quality of care, volume of 

services, and other data, while also 

giving them the option to compare SNFs 

using this information. The data found 

on data.cms.gov and in the 

TeleTracking system do not have these 

features. 

Comment: Another commenter 

questioned whether incorporating 2021 

vaccination rates for HCP into quality 

ratings on Medicare Compare in 2023 

would provide valuable information to 

SNF residents and their families. 

Response: We are interpreting the 

commenter’s question to be about the 

COVID–19 Vaccination Coverage among 

HCP measure and the timeline for 

reporting it on Care Compare. We 

proposed to report the inaugural 

COVID–19 Vaccination Coverage among 

HCP measure beginning with the 

October 2022 Care Compare refresh or 

as soon as technically feasible using 

data collected for Q4 2021 (October 1, 

2021 through December 31, 2021). If 

finalized as proposed, provider preview 

reports would be distributed in July 

2022. 

Comment: A commenter did not 

support the proposal to use a shortened 

reporting timeframe of October 2021– 

December 2021 to meet the APU 

reporting requirements for FY 2023. 

Response: We interpret the 

commenter to be referring to the SNF 

QRP reporting requirements to meet the 

compliance threshold for the FY 2023 

Annual Payment Update. Our proposal 

to use of one quarter of data for the 

initial year of quality reporting for a 

new measure is consistent with the 

approach finalized in the FY 2016 SNF 

PPS final rule (80 FR 46389 to 46777) 

for all new measures in their first year 

of data reporting. 

Comment: Commenters had differing 

opinions on whether the information 

obtained from the COVID–19 

Vaccination Coverage among HCP 

measure would be helpful to consumers. 

Some stated that it does little to guide 

patients and their caregivers in the 

discharge planning process or to 

distinguish SNFs from one another. 

Another commenter acknowledged the 

value of this information for public 


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42498 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

112Medicare COVID–19 Data Snapshot Overview. 

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

medicare-covid-19-data-snapshot-fact-sheet.pdf. 

Accessed July 12, 2021. 

113https://www.phe.gov/emergency/news/ 

healthactions/section1135/Pages/covid19- 

13March20.aspx. 

114https://www.cms.gov/files/document/ 

guidance-memo-exceptions-and-extensions-qualityreporting-and-value-based-purchasingprograms.pdf. 

115More information about the SNF QRP Public 

Reporting schedule can be found on the SNF QRP 

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

Medicare/Quality-Initiatives-Patient-AssessmentInstruments/NursingHomeQualityInits/SkilledNursing-Facility-Quality-Reporting-Program/SNFQuality-Reporting-Program-Public-Reporting. 

health and educational purposes, but 

still believes it would not be appropriate 

at this time to report publicly on 

MUC20–044 for the purposes of 

assessing SNF quality performance. 

Response: We interpret the 

commenter to be referring to the CMS 

2020 Measures Under Consideration 

(MUC) list and specifically the SARS– 

CoV–2 Vaccination Coverage among 

HCP measure (MUC20–044), whose 

name was subsequently changed to the 

COVID–19 Vaccination Coverage among 

HCP measure. This measure is 

important at this time because, as 

illustrated in Medicare claims and 

encounter data, the number of Medicare 

beneficiaries diagnosed with COVID–19 

exceeded 4.3 million as of April 24, 

2021.112 We believe that the toll the 

COVID–19 pandemic has taken on 

Medicare beneficiaries, including SNF 

residents, demonstrates the need for 

increased action to mitigate the effects 

of the ongoing pandemic. Additionally, 

public reporting of this measure will 

inform patients and families of more 

recent information on quality of care 

provided in SNFs so patients and 

caregivers are able to make informed 

choices about critical dimensions of 

quality. 

After careful consideration of the 

public comments we received, we are 

finalizing our proposal to publicly 

report the COVID–19 Vaccination 

Coverage among Healthcare Personnel 

(HCP) measure beginning with the 

October 2022 Care Compare refresh or 

as soon as technically feasible using 

data collected for Q4 2021 (October 1, 

2021 through December 31, 2021). 

However, based on public comment, we 

will not finalize our plan to add one 

additional quarter of data during each 

advancing refresh, until the point that 

four full quarters of data is reached and 

then report the measure using four 

rolling quarters of data. We will instead 

only report the most recent quarter of 

data. This revision would result in 

publishing more meaningful 

information that is up to date. 

4. Public Reporting of Quality Measures 

in the SNF QRP With Fewer Quarters 

Due to COVID–19 Public Health 

Emergency (PHE) Exemptions 

a. COVID–19 Public Health Emergency 

Temporary Exemptions 

Under the authority of section 319 of 

the Public Health Service Act, the 

Secretary of Health and Human Services 

declared a public health emergency 

(PHE) effective as of January 27, 2020. 

On March 13, 2020, subsequent to a 

presidential declaration of national 

emergency under the Stafford Act, the 

Secretary invoked section 1135(b) of the 

Act (42 U.S.C. 1320b–5) to waive or 

modify the requirements of titles XVIII, 

XIX, and XXI of the Act and regulations 

related to the PHE for COVID–19, 

effective as of March 1, 2020.113 On 

March 27, 2020, we sent a guidance 

memorandum under the subject title, 

‘‘Exceptions and Extensions for Quality 

Reporting Requirements for Acute Care 

Hospitals, PPS-Exempt Cancer 

Hospitals, Inpatient Psychiatric 

Facilities, Skilled Nursing Facilities, 

Home Health Agencies, Hospices, 

Inpatient Rehabilitation Facilities, LongTerm Care Hospitals, Ambulatory 

Surgical Centers, Renal Dialysis 

Facilities, and MIPS Eligible Clinicians 

Affected by COVID–19’’ to the Medicare 

Learning Network (MLN) Connects 

Newsletter and Other Program-Specific 

Listserv Recipients,114 hereafter referred 

to as the March 27, 2020 CMS Guidance 

Memo. In that memo we granted an 

exception to the SNF QRP reporting 

requirements from Q4 2019 (October 1, 

2019 through December 31, 2019), Q1 

2020 (January 1, 2020 through March 

31, 2020), and Q2 2020 (April 1, 2020 

through June 30, 2020). We also stated 

that we would not publicly report any 

SNF QRP data that might be greatly 

impacted by the exceptions from Q1 and 

Q2 of 2020. This exception impacted the 

schedule for public reporting that would 

have included those two quarters of 

data. 

SNF quality measures are publicly 

reported on Care Compare. Care 

Compare uses four quarters of data for 

MDS assessment-based measures and 

eight quarters for claims-based 

measures. Table 26 displays the original 

schedule for public reporting of SNF 

QRP measures.115


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During 2020, we conducted testing to 

inform decisions about publicly 

reporting data for those refreshes which 

include partially and/or fully exempt 

data (discussed below). The testing 

helped us develop a plan for posting 

data that are as up-to-date as possible 

and that also meet acceptable standards 

for public reporting. We believe that the 

plan allows us to provide consumers 

with helpful information on the quality 

of SNF care, while also making the 

necessary adjustments to accommodate 

the exemption provided SNFs. The 

following sections provide the results of 

our testing, and explain how we used 

the results to develop plans for 

accommodating exempt and partiallyexempt data in public reporting. 

b. Exempted Quarters 

In the March 27, 2020 Medicare 

Learning Network (MLN) Newsletter on 

Exceptions and Extensions for Quality 

Reporting Program (QRP) Requirements, 

we stated that we would not report any 

PAC quality data that might be greatly 

impacted by the exemptions granted for 

Quarter 1 and Quarter 2 of 2020. Given 

the timing of the PHE onset, we 

determined that we would not use SNF 

MDS assessments or SNF claims from 

Quarter 1 and Quarter 2 of 2020 for 

public reporting, but that we would 

assess the COVID–19 PHE impact on 

data from Quarter 4 2019. Before 

proceeding with the October 2020 

refresh, we conducted testing to ensure 

that, despite the voluntary nature of 

reporting for that quarter, public 

reporting would still meet our public 

reporting standards. We found the level 

of reporting, measured in the number of 

eligible stays and providers, and the 

reported outcomes, to be in line with 

levels and trends observed in FY 2018 

and FY 2019. We note that Quarter 4 

2019 ended before the onset of the 

COVID–19 pandemic in the United 

States. Thus, we proceeded with 

including these data in SNF QRP 

measure calculations for the October 

2020 refresh. 

c. Update on Data Freeze and Proposal 

for January 2022 Public Reporting 

Methodology for SNF Claims-Based and 

MDS Assessment-Based Measures 

In addition to the January 2021 

refresh, there are several other 

forthcoming refreshes for which the 

original public reporting schedules 

included exempted quarters of SNF QRP 

data. The impacted refreshes for MDS 

assessment and claims based measures 

are outlined in (Table 26). We 

determined that freezing the data 

displayed on the website with the 

October 2020 refresh values—that is, 

hold data constant after the October 

2020 refresh data on the website 

without subsequent update—would be 

the most straightforward, efficient, and 

equitable approach for SNFs. Thus, we 

decided that, for as many refreshes as 

necessary, we would hold data constant 

on the website with the October 2020 

data, and communicate this decision to 

the public. 

Because October 2020 refresh data 

will become increasingly out-of-date 

and thus less useful for consumers, we 

analyzed whether it would be possible 

to use fewer quarters of data for one or 

more refreshes and thus reduce the 

number of refreshes that continue to 

display October 2020 data. Using fewer 

quarters of more up-to-date data 

requires that (1) a sufficient percentage 

of SNFs would still likely have enough 

assessment data to report quality 

measures (reportability); and (2) fewer 

quarters would likely produce similar 

measure scores for providers, with 

similar reliability, and thus not unfairly 

represent the quality of care SNFs 

provide during the period reported in a 

given refresh (reliability). 


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TABLE 26: SNF Quarters in Care Compare Original Schedule for Refreshes Affected by 

COVID-19 PEH Exemptions - Assessment and Claims Based Measures 

Quarter Refresh SNF Quarters in Original Schedule for Care Compare 

January 2021 MDS: Q2 2019 - Ql 2020 (4 quarters) 

Claims: Q4 2017 -Q3 2019 (8 quarters) 

April 2021 MDS: Q3 2019 - Q2 2020 (4 quarters) 

Claims: 04 2017 -03 2019 (8 quarters) 

July 2021 MDS: Q4 2019 - Q3 2020 (4 quarters) 

Claims: Q4 2017 -Q3 2019 (8 quarters) 

October 2021 MDS: Ql 2020 - Q4 2020 (4 quarters) 

Claims: Q4 2018 -Q3 2020 (8 quarters) 

January 2022 MDS: Q2 2020 - QI 2021 (4 quarters) 

Claims: Q4 2018 -Q3 2020 (8 quarters) 

April 2022 MDS: Q3 2020 - Q2 2021 ( 4 quarters) 

Claims: Q4 2018 -Q3 2020 (8 quarters) 

July 2022 MDS: Q4 2020 - Q3 2021 (4 quarters) 

Claims: Q4 2018 -Q3 2020 (8 quarters) 

October 2022 MDS: Ql 2021 - Q4 2021 (4 quarters) 

Claims: 04 2019 - 03 2021 (8 quarters) 

January 2023 MDS: Q2 2021 - Q 1 2022 ( 4 quarters) 

Claims: 04 2019 -03 2021 (8 quarters) 

April 2023 MDS: Q3 2021 - Q2 2022 (4 quarters) 

Claims: 04 2019 - 03 2021 (8 quarters) 

July 2023 MDS: Q4 2021 - Q3 2022 (4 quarters) 

Claims: 04 2019 -03 2021 (8 quarters) 
42500 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

To assess these criteria, we conducted 

reportability and reliability analysis 

using 3 quarters of data in a refresh, 

instead of the standard 4 quarters of 

data for reporting assessment-based 

measures and using 6 quarters instead of 

8 for claims-based measures. 

Specifically, we used historical data to 

calculate MDS assessment based and 

SNF claims based quality measures 

under two scenarios: 

1. Standard Public Reporting (SPR) 

Base Scenario: We used four quarters of 

CY 2019 data as a proxy alternative for 

the exempted quarters in CY 2020 in 

order to compare results. For 

assessment-based measures, the quarters 

used in this scenario are Q1 through Q4 

2019. For claims-based measures, the 

quarters used in this scenario are Q1 

2018 through Q4 2019. 

2. COVID–19 Affected Reporting 

(CAR) Scenario: We calculated SNF 

QRP measures using 3 quarters (Q2 2019 

through Q4 2019) of SNF QRP data for 

assessment-based measures, and 6 

quarters (Q1 2018 through Q4 2018 and 

Q3 2019 through Q4 2019) for claimsbased measures. The CAR scenario uses 

the most recently available data to 

simulate the public health emergency 

reality where quarters 1 and 2 of a 

calendar year must be excluded from 

calculation. Quarterly trends in MDS 

assessment-based and claims based 

measures indicate that these measures 

do not exhibit substantial seasonal 

variation. 

To assess performance in these 

scenarios, we calculated the 

reportability as the percent of SNFs 

meeting the case minimum for public 

reporting (the public reporting 

threshold). To test the reliability of 

restricting the SNFs included in the SPR 

Base Scenario to those included in the 

CAR Scenario, we performed three tests 

on the set of SNFs included in both 

scenarios. First, we evaluated measure 

correlation using the Pearson and 

Spearman correlation coefficients, 

which assess the alignment of SNFs’ 

provider scores. Second, for each 

scenario, we conducted a split-half 

reliability analysis and estimated 

intraclass correlation (ICC) scores, 

where higher scores imply better 

internal reliability. Modest differences 

in ICC scores between both scenarios 

would suggest that using fewer quarters 

of data does not impact the internal 

reliability of the results. Third, we 

estimated reliability scores where a 

higher value indicates that measure 

scores are relatively consistent for 

patients admitted to the same SNF and 

variation in the measure reflects true 

differences across providers. To 

calculate the reliability results, we 

restricted the SNFs included in the SPR 

scenario to those included in the CAR 

scenario. 

Our testing indicated that the 

expected impact of using fewer quarters 

of data on reportability and reliability of 

MDS assessment-based and claims 

based measures is acceptable. 

We proposed to use the CAR scenario 

as the approach for the following 

affected refreshes for MDS assessmentbased measures, the affected refresh is 

the January 2022 refresh; for claimsbased measures, the affected refreshes 

occur from January 2022 through July 

2023. For the earlier four affected 

refreshes (January, April, July, and 

October 2021), we decided to hold 

constant the Care Compare website with 

October 2020 data. We communicated 

this decision in a Public Reporting Tip 

Sheet, which is located at https://

www.cms.gov/files/document/snfqrpcovid19prtipsheet-october2020.pdf. 

Our proposal of the CAR approach for 

the affected refreshes would allow us to 

begin displaying more recent data in 

January 2022, rather than continue 

displaying October 2020 data (Q1 2019 

through Q4 2019 for assessment-based 

measures, Q4 2017 through Q3 2019 for 

claims-based measures). We believe that 

resuming public reporting starting in 

January 2022 with fewer quarters of data 

can assist consumers by providing more 

recent quality data as well as more 

actionable data for SNF providers. Our 

testing results indicate we can achieve 

these positive impacts with acceptable 

changes in reportability and reliability. 

Table 27 summarizes the revised 

schedule (that is, frozen data) and the 

proposed schedule (that is, using fewer 

quarters in the affected refreshes) for 

assessment-based measures. Tables 28 

and 29 summarize the revised schedule 

(that is, frozen data) and the proposed 

schedule (that is, using fewer quarters in 

the affected refreshes) for claims-based 

measures. 

We invited public comment on the 

proposal to use the CAR scenario to 

publicly report SNF measures for the 

January 2022 through July 2023 

refreshes. 

BILLING CODE 4120–01–P 


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TABLE 27: Revised and Proposed Schedule for Refreshes Affected by COVID-19 PHE 

Exem tions for SNF MDS Assessment-based QMs 

Quarter Refresh 

October 2020 

January 2021 

April 2021 

July 2021 

October 2021 

January 2022 

April 2022 

MDS Assessment Quarters in 

Revised/Proposed Schedule for 

Care Compare (number of 

quarters) 

Q3 2020 -QI 2021 (3) 

Q3 2020 -Q2 2021 (4)* 

*Normal reporting resumes with 4 

uarters of data 

Note: The shaded cells represent data held constant due to PHE related to 

COVID-19. 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42501 

BILLING CODE 4120–01–C 

The following is a summary of the 

public comments received on the 

proposal to use the CAR scenario to 

publicly report SNF measures for the 

January 22 through July 2023 refreshes 

and our responses: 

Comment: We received two comments 

on the proposed COVID–19 Affected 

Reporting (CAR) scenario methodology. 

One commenter supported the proposal 

to report fewer quarters of data. Another 

commenter stated that the CAR scenario 

appeared to adequately ensure data 

reportability and reliability and 

requested that CMS continue to monitor 

modified Care Compare refreshes until 

normal reporting resumes to ensure the 

CAR approach produces valid and 

reliable results. 

Response: We thank the commenters 

for their support and will continue to 

monitor measures to identify any 

concerning trends as part of our routine 

monitoring activities to regularly assess 

measure performance, reliability, and 

reportability for all data submitted for 

the SNF QRP. 

Comment: Most commenters 

expressed their appreciation for the 

flexibility that CMS offered to SNF 

providers during the early months of the 

COVID–19 pandemic in granting an 

exception to the SNF QRP reporting 

requirements from Q1 2020 (January 1, 

2020 through March 31, 2020) and Q2 

2020 (April 1, 2020 through June 30, 

2020). However, a number of 

commenters raised concerns with CMS’ 

proposal to utilize fewer than the 

standard number of quarters for public 

reporting of quality measures on Care 

Compare, since it includes SNF QRP 

reporting from Q3 2020 (July 1, 2020 

through September 30, 2020) and Q4 

2020 (October 1, 2020 through 

December 31, 2020). Commenters 

pointed out that the COVID–19 

pandemic community infection rate 

surged repeatedly across different 

regions of the country, at different 

times, and did not begin to become 

under control until Q1 2021 after the 

first wave of COVID–19 vaccine was 

disseminated to SNF residents and staff. 

Instead, they urged CMS to exclude the 

entire calendar year 2020 data. 

Response: While we understand that 

there are concerns related to the use of 

Q3 and Q4 2020 data, we believe that 

the value of the information provided to 

users through public reporting 

outweighs these concerns. Additionally, 

we provided a 6-month exception to 


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TABLE 28: Revised and Proposed Schedule for Refreshes Affected by COVID-19 PHE 

Exemptions for SNF Claims-based QMs 

Quarter Refresh 

October 2022 

October 2023 

Claims-based Quarters in 

Revised/Proposed Schedule for Care 

Co rs 

Q4 2020 - Q3 2022 (8)* 

*Normal reporting resumes with 8 

uarters of data 

Note: The shaded cells represent data held constant due to PHE related to COVID-19. 

TABLE 29: Proposed Schedule for Refreshes Affected by COVID-19 PHE Exemptions for 

the SNF HAI Measure 

Quarter Refresh Claims-based Quarters in Proposed 

Schedule for Care Compare 

(number of quarters) 

April 2022 Q4 2018 -Q3 2019 (4) 

July 2022 Q4 2018 -Q3 2019 (4) 

October 2022 Q4 2020 - Q3 2021 (4) 

*Normal reporting resumes for 

claims-based measures refreshed 

annually 
42502 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

SNF QRP reporting requirements related 

to the PHE, and we believe that 

timeframe was sufficient for providers 

to adjust to the change in care patterns 

associated with the pandemic. We 

further believe that the public display of 

quality data is extremely important so 

patients and caregivers can continue to 

make informed healthcare choices. The 

continued need for access to provider 

quality data on Care Compare by CMS 

beneficiaries outweighs any potential 

provider impacts. 

As described above, we conducted 

testing to inform our decisions about 

publicly reporting data for refreshes 

using Q3 and Q4 2020. As discussed in 

section VI.H.4.c. of the FY 2021 SNF 

PPS proposed rule (86 FR 20004 

through 20005), the testing helped us 

develop a plan that we believe meets 

acceptable standards for public 

reporting. SNFs that believe they were 

disproportionately affected by the PHE 

may apply for an individual exception 

or extension related to the SNF QRP 

reporting requirements for Q3 and/or Q4 

2020. Instructions for requesting an 

extraordinary circumstances exemption 

(ECE) may be found on the SNF QRP 

Reconsideration and Exception and 

Extension web page at https://

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

Skilled-Nursing-Facility-QualityReporting-Program/SNF-QRReconsideration-and-Exception-andExtension. 

Comment: One commenter believes 

public reporting should be frozen until 

the first quarter after the end of the PHE. 

Since the proposed public reporting 

schedule would utilize data submitted 

while the country was still under a PHE, 

particularly during the proposed Q3 

2020 through Q1 2021 timeframes, they 

believe it may not reflect normal SNF 

performance and results both at the 

facility, and geographically. 

Response: We disagree with the 

commenter about freezing the data until 

after the first quarter of the end of the 

PHE. COVID–19 has caused us to take 

a number of actions to further protect 

SNF residents. Resuming public 

reporting will inform patients and 

families of more recent information on 

quality of care provided in SNFs. As we 

progress, we will analyze SNF QRP 

measures for any significant changes, 

and take any actions needed to continue 

the improvement and protection of 

patient health and safety. 

Comment: Several commenters 

believe that payments to their SNFs 

would be negatively impacted since 

their state Medicaid systems use quality 

measure data and the star ratings 

published on Care Compare to 

determine quality incentive payment 

rates to nursing facilities. They urged 

CMS not to penalize providers under 

the Five-Star rating system for measure 

performance ratings derived during Q3 

2020 through Q1 2021. 

Response: We acknowledge that other 

programs may utilize the SNF QRP for 

their own purposes. We proposed the 

COVID–19 Vaccination Coverage among 

HCP measure for the SNF QRP. 

Comments about state Medicaid 

programs and the Five-Star rating 

system are outside the scope of this final 

rule. 

Comment: One commenter stated that 

due to specific CDC and CMS mandated 

COVID–19 infection control 

requirements, specific MDS items used 

for some measures (that is, mobility and 

self-care) may have been directly and 

artificially impacted, which could 

further skew the results during this 

period. The inability to account for or 

risk-adjust the measures for the 

influence of a worldwide airborne viral 

pandemic was also given as justification 

for excluding additional quarters in 

2020. 

Response: We are uncertain what the 

commenter means in stating that some 

measures may have been artificially 

impacted. We acknowledge the efforts 

that SNFs have gone to keep their 

residents and staffs as safe as possible 

during the COVID–19 PHE. One of the 

reasons the SNF QRP reporting 

requirement waivers for reporting 

measure data was granted for Q4 2019 

through Q2 2020 was to enable SNFs to 

address their residents’ care, and to 

acclimate to care patterns associated 

with the PHE. However, CMS uses all 

SNF QRP data submitted to CMS for the 

purposes of public reporting. As stated 

previously, we routinely monitor 

measures to identify any concerning 

trends, and will continue to do so as 

part of our routine monitoring activities 

to regularly assess measure 

performance, reliability, and 

reportability for all data submitted for 

the SNF QRP. 

Comment: One commenter requested 

that CMS include a notation on Care 

Compare to explain the temporary 

adjustments made for the PHE and that 

consumers should consider additional 

information when selecting facilities 

such as survey results and in-person 

facility visits. 

Response: We will notify consumers 

of the use of fewer quarters of data 

reported on Care Compare when the 

website is refreshed. However, we do 

not believe that posting additional 

messaging alluding to how SNF measure 

scores may or may not be affected by the 

ongoing PHE would be helpful to 

consumers. Such messages would give 

the impression that the data posted on 

Care Compare are inaccurate or cannot 

be used when making informed 

healthcare decisions, which is not the 

case given the extensive testing CMS 

conducts. 

After careful consideration of the 

public comments, we are finalizing the 

revisions to use the CAR scenario to 

publicly report SNF measures for the 

January 2022 through July 2023 

refreshes as proposed. 

I. Miscellaneous Comments 

Comment: One commenter 

encouraged CMS to provide more 

infrastructure support for SNFs to adopt 

certified electronic technology to 

facilitate meaningful data exchange. 

They point out the importance of 

knowing whether the data have been 

received and acted upon, as well as the 

opportunity to understand just what 

parts of the data are most beneficial to 

the receiving provider. 

Response: This comment is out of 

scope and is not relevant to our 

proposal to update the TOH Information 

measure. 

VIII. Skilled Nursing Facility ValueBased Purchasing (SNF VBP) Program 

A. Statutory Background 

Section 215(b) of the Protecting 

Access to Medicare Act of 2014 (PAMA) 

(Pub. L. 113–93) authorized the SNF 

VBP Program (the ‘‘Program’’) by adding 

section 1888(h) to the Act. As a 

prerequisite to implementing the SNF 

VBP Program, in the FY 2016 SNF PPS 

final rule (80 FR 46409 through 46426), 

we adopted an all-cause, all-condition 

hospital readmission measure, as 

required by section 1888(g)(1) of the 

Act, and discussed other policies to 

implement the Program such as 

performance standards, the performance 

period and baseline period, and scoring. 

SNF VBP Program policies have been 

codified in our regulations at 42 CFR 

413.338. For additional background 

information on the SNF VBP Program, 

including an overview of the SNF VBP 

Report to Congress and a summary of 

the Program’s statutory requirements, 

we refer readers to the following prior 

final rules: 

• In the FY 2017 SNF PPS final rule 

(81 FR 51986 through 52009), we 

adopted an all-condition, risk-adjusted 

potentially preventable hospital 

readmission measure for SNFs, as 

required by section 1888(g)(2) of the 

Act, adopted policies on performance 

standards, performance scoring, and 

sought comment on an exchange 


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function methodology to translate SNF 

performance scores into value-based 

incentive payments, among other topics. 

• In the FY 2018 SNF PPS final rule 

(82 FR 36608 through 36623), we 

adopted additional policies for the 

Program, including an exchange 

function methodology for disbursing 

value-based incentive payments. 

• In the FY 2019 SNF PPS final rule 

(83 FR 39272 through 39282), we 

adopted more policies for the Program, 

including a scoring adjustment for lowvolume facilities. 

• In the FY 2020 SNF PPS final rule 

(84 FR 38820 through 38825), we 

adopted additional policies for the 

Program, including a change to our 

public reporting policy and an update to 

the deadline for the Phase One Review 

and Correction process. We also 

adopted a data suppression policy for 

low-volume SNFs. 

• In the FY 2021 SNF PPS final rule 

(85 FR 47624 through 47627), we 

amended regulatory text definitions at 

§ 413.338(a)(9) and (11) to reflect the 

definition of Performance Standards and 

the updated Skilled Nursing Facility 

Potentially Preventable Readmissions 

after Hospital Discharge measure name, 

respectively. We also updated the Phase 

One Review and Correction deadline 

and codified that update at 

§ 413.338(e)(1). Additionally, we 

codified the data suppression policy for 

low-volume SNFs at § 413.338(e)(3)(i), 

(ii), and (iii) and amended 

§ 413.338(e)(3) to reflect that SNF 

performance information will be 

publicly reported on the Nursing Home 

Compare website and/or successor 

website (84 FR 38823 through 38824) 

which since December 2020 is the 

Provider Data Catalogue website 

(https://data.cms.gov/provider-data/). 

The SNF VBP Program applies to 

freestanding SNFs, SNFs affiliated with 

acute care facilities, and all non-CAH 

swing-bed rural hospitals. Section 

1888(h)(1)(B) of the Act requires that the 

SNF VBP Program apply to payments 

for services furnished on or after 

October 1, 2018. We believe the 

implementation of the SNF VBP 

Program is an important step towards 

transforming how payment is made for 

care, moving increasingly towards 

rewarding better value, outcomes, and 

innovations instead of merely rewarding 

volume. 

B. SNF VBP Program Measures 

For background on the measures we 

have adopted for the SNF VBP Program, 

we refer readers to the FY 2016 SNF 

PPS final rule (80 FR 46419), where we 

finalized the Skilled Nursing Facility 

30-Day All-Cause Readmission Measure 

(SNFRM) (NQF #2510) that we are 

currently using for the SNF VBP 

Program. We also refer readers to the FY 

2017 SNF PPS final rule (81 FR 51987 

through 51995), where we finalized the 

Skilled Nursing Facility 30-Day 

Potentially Preventable Readmission 

Measure (SNFPPR) that we will use for 

the SNF VBP Program instead of the 

SNFRM as soon as practicable, as 

required by statute. The SNFPPR 

measure’s name is now ‘‘Skilled 

Nursing Facility Potentially Preventable 

Readmissions after Hospital Discharge 

measure’’ (§ 413.338(a)(11)). We intend 

to submit the SNFPPR measure for NQF 

endorsement review during the Fall 

2021 cycle, and to assess transition 

timing of the SNFPPR measure to the 

SNF VBP Program after NQF 

endorsement review is complete. 

1. Flexibilities for the SNF VBP Program 

in Response to the Public Health 

Emergency Due to COVID–19 

In previous rules, we have identified 

the need for flexibility in our quality 

programs to account for the impact of 

changing conditions that are beyond 

participating facilities’ or practitioners’ 

control. We identified this need because 

we would like to ensure that 

participants in our programs are not 

affected negatively when their quality 

performance suffers not due to the care 

provided, but due to external factors. 

A significant example of the type of 

external factor that may affect quality 

measurement is the COVID–19 public 

health emergency (PHE), which has had, 

and continues to have, significant and 

ongoing effects on the provision of 

medical care in the country and around 

the world. The COVID–19 pandemic 

and associated PHE has impeded 

effective quality measurement in many 

ways. Changes to clinical practices to 

incorporate safety protocols for medical 

personnel and patients, as well as 

unpredicted changes in the number of 

stays and facility-level case mixes, have 

affected the data that SNFs report under 

the SNF VBP Program and the resulting 

measure calculations. CMS is 

considering whether the SNF 

readmission measure specifications 

should be updated to account for 

changes in SNF admission and/or 

hospital readmission patterns that we 

have observed during the PHE. 

Additionally, because COVID–19 

prevalence is not identical across the 

country, facilities located in different 

areas have been affected differently at 

different times throughout the 

pandemic. Under those circumstances, 

we remain concerned that the SNF 

readmission measure scores are 

distorted, which would result in skewed 

payment incentives and inequitable 

payments, particularly for SNFs that 

have treated more COVID–19 patients 

than others. 

It is not our intention to penalize 

SNFs based on measure scores that we 

believe are distorted by the COVID–19 

pandemic, and are thus not reflective of 

the quality of care that the measure in 

the SNF VBP Program was designed to 

assess. As discussed above, the COVID– 

19 pandemic has had, and continues to 

have, significant and enduring effects on 

health care systems around the world, 

and affects care decisions, including 

readmissions to the hospital as 

measured by the SNF VBP Program. As 

a result of the PHE, SNFs could provide 

care to their patients that meets the 

underlying clinical standard but results 

in worse measured performance, and by 

extension, lower incentive payments in 

the SNF VBP Program. Additionally, 

because COVID–19 prevalence has not 

been identical across the country, SNFs 

located in different regions have been 

affected differently during the PHE. As 

a result, we are concerned that regional 

differences in COVID–19 prevalence 

during the revised performance period 

for the FY 2022 SNF VBP Program, 

which includes one quarter of data 

during the pandemic (July 1, 2020 

through September 30, 2020), have 

directly affected SNF readmission 

measure scores for the FY 2022 SNF 

VBP Program Year. Although these 

regional differences in COVID–19 

prevalence rates do not reflect 

differences in the quality of care 

furnished by SNFs, they directly affect 

the value-based incentive payments that 

these SNFs are eligible to receive and 

could result in an unfair and inequitable 

distribution of those incentives. These 

inequities could be especially 

pronounced for SNFs that have treated 

a large number of COVID–19 patients. 

Therefore, we proposed to adopt a 

policy for the duration of the PHE for 

COVID–19 that would enable us to 

suppress the use of SNF readmission 

measure data for purposes of scoring 

and payment adjustments in the SNF 

VBP Program if we determine that 

circumstances caused by the PHE for 

COVID–19 have affected the measure 

and the resulting performance scores 

significantly. We proposed that under 

this policy, if we determine that the 

suppression of the SNF readmission 

measure is warranted for a SNF VBP 

Program Year, we would calculate the 

SNF readmission measure rates for that 

program year but then suppress the use 

of those rates to generate performance 

scores, rank SNFs, and generate valuebased incentive payment percentages 

based on those performance scores. We 


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would instead assign each eligible SNF 

a performance score of zero for the 

program year to mitigate the effect that 

the distorted measure results would 

otherwise have on the SNF’s 

performance score and incentive 

payment multiplier. We would also 

reduce each eligible SNF’s adjusted 

Federal per diem rate by the applicable 

percent (2 percent) and then further 

adjust the resulting amounts by a valuebased incentive payment amount equal 

to 60 percent of the total reduction. 

Those SNFs subject to the Low-Volume 

Adjustment policy would receive 100 

percent of their 2 percent withhold in 

accordance with the policy previously 

finalized in the FY 2019 SNF PPS final 

rule (83 FR 39278 through 39280). We 

would also provide each SNF with its 

SNF readmission measure rate in 

confidential feedback reports so that the 

SNF is aware of the observed changes to 

its measure rates. We would also 

publicly report the FY 2022 SNF 

readmission measure rates with 

appropriate caveats noting the 

limitations of the data due to the PHE 

for COVID–19. 

In developing this proposed policy, 

we considered what circumstances 

caused by the PHE for COVID–19 would 

affect a quality measure significantly 

enough to warrant its suppression in a 

value-based purchasing program. We 

believe that a significant deviation in 

measured performance that can be 

reasonably attributed to the PHE for 

COVID–19 is a significant indicator of 

changes in clinical conditions that affect 

quality measurement. Similarly, we 

believe that a measure may be focused 

on a clinical topic or subject that is 

proximal to the disease, pathogen, or 

other health impacts of the PHE. As has 

been the case during the COVID–19 

PHE, we believe that rapid or 

unprecedented changes in clinical 

guidelines and care delivery, potentially 

including appropriate treatments, drugs, 

or other protocols, may affect quality 

measurement significantly and should 

not be attributed to the participating 

facility positively or negatively. We also 

note that scientific understanding of a 

particular disease or pathogen may 

evolve quickly during an emergency, 

especially in cases of new disease or 

conditions. Finally, we believe that, as 

evidenced during the COVID–19 PHE, 

national or regional shortages or 

changes in health care personnel, 

medical supplies, equipment, diagnostic 

tools, and patient case volumes or 

facility-level case mix may result in 

significant distortions to quality 

measurement. 

Based on these considerations, we 

developed a number of Measure 

Suppression Factors that we believe 

should guide our determination of 

whether to propose to suppress the SNF 

readmission measure for one or more 

program years that overlap with the PHE 

for COVID–19. We proposed to adopt 

these Measure Suppression Factors for 

use in the SNF VBP Program and, for 

consistency, the following other valuebased purchasing programs: Hospital 

Value-Based Purchasing Program, 

Hospital Readmissions Reduction 

Program, HAC Reduction Program, and 

End-Stage Renal Disease Quality 

Incentive Program. We believe that 

these Measure Suppression Factors will 

help us evaluate the SNF readmission 

measure in the SNF VBP Program and 

that their adoption in the other valuebased purchasing programs noted above 

will help ensure consistency in our 

measure evaluations across programs. 

The proposed Measure Suppression 

Factors are: 

(1) Significant deviation in national 

performance on the measure during the 

PHE for COVID–19, which could be 

significantly better or significantly 

worse compared to historical 

performance during the immediately 

preceding program years. 

(2) Clinical proximity of the measure’s 

focus to the relevant disease, pathogen, 

or health impacts of the PHE for 

COVID–19. 

(3) Rapid or unprecedented changes 

in: 

• Clinical guidelines, care delivery or 

practice, treatments, drugs, or related 

protocols, or equipment or diagnostic 

tools or materials; or 

• The generally accepted scientific 

understanding of the nature or 

biological pathway of the disease or 

pathogen, particularly for a novel 

disease or pathogen of unknown origin. 

(4) Significant national shortages or 

rapid or unprecedented changes in: 

• Healthcare personnel; 

• Medical supplies, equipment, or 

diagnostic tools or materials; or 

• Patient case volumes or facilitylevel case mix. 

We stated in the proposed rule that 

we had also considered alternatives to 

this proposed policy that could also 

fulfill our objective to not hold facilities 

accountable for measure results that are 

distorted due to the PHE for COVID–19. 

As noted above, the country continues 

to grapple with the effects of the 

COVID–19 PHE, and in March 2020, we 

issued a nationwide, blanket ECE for all 

hospitals and other facilities 

participating in our quality reporting 

and value-based purchasing programs in 

response to the PHE for COVID–19. This 

blanket ECE excepted all data reporting 

requirements for Q1 and Q2 2020 data. 

For claims-based measures, we also 

stated that we would exclude all 

qualifying Q1 and Q2 2020 claims from 

our measure calculations. We 

considered extending the blanket ECE 

that we issued for Q1 and Q2 2020 to 

also include Q3 2020 data. However, 

this option would result in less than 12 

months of data being used to calculate 

the single readmissions measure in the 

Program for multiple program years, 

which we do not believe would provide 

an accurate assessment of the quality of 

care provided in SNFs. This option 

would also leave no comprehensive data 

available for us to provide confidential 

performance feedback to providers nor 

for monitoring and to inform decisionmaking for potential future 

programmatic changes, particularly as 

the PHE is extended. 

As we stated in the proposed rule, we 

view this measure suppression proposal 

as a necessity to ensure that the SNF 

VBP Program does not reward or 

penalize facilities based on factors that 

the SNF readmission measure was not 

designed to accommodate. We also 

stated that we intend for this proposed 

policy to provide short-term relief to 

SNFs when we have determined that 

one or more of the Measure Suppression 

Factors warrants the suppression of the 

SNF readmission measure. 

We invited public comments on this 

proposal for the adoption of a measure 

suppression policy for the SNF VBP 

Program for the duration of the PHE for 

COVID–19, and also on the proposed 

Measure Suppression Factors that we 

developed for purposes of this proposed 

policy. 

We also invited comment on whether 

we should consider adopting a measure 

suppression policy that would apply in 

a future national PHE, and if so, 

whether under such a policy, we should 

have the flexibility to suppress quality 

measures without specifically proposing 

to do so in rulemaking. We also 

requested comment on whether we 

should in future years consider adopting 

any form of regional adjustment for the 

proposed measure suppression policy 

that could take into account any 

disparate effects of circumstances 

affecting hospitals around the country 

that would prompt us to suppress a 

measure. For example, COVID–19 

affected different regions of the country 

at different rates depending on factors 

like time of year, geographic density, 

state and local policies, and health care 

system capacity. In future years and for 

future PHEs, should they arise, we also 

requested commenters’ feedback on 

whether we should, rather than 

suppress a measure completely, 

consider a suppression policy with 


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more granular effects based on our 

assessment of the geographic effects of 

the circumstances, and if so, how 

region-based measure suppression could 

be accounted for within the program’s 

scoring methodology. 

The following is a summary of the 

public comments received on the 

proposed Flexibilities for the SNF VBP 

Program in Response to the Public 

Health Emergency Due to COVID–19 

and our responses: 

Comment: Several commenters 

expressed support for our proposal to 

establish a measure suppression policy 

for the PHE due to COVID–19 and for 

future PHEs. Many of the commenters 

noted that the proposed measure 

suppression factors are appropriate and 

comprehensive. One commenter 

suggested we include a review of state 

and regional performance in addition to 

national performance when evaluating 

the measure suppression factors in order 

to account for regional and state 

differences in the response to the PHE 

due to COVID–19. A few commenters 

recommended that the measure 

suppression should occur anytime a 

PHE is declared and extend through the 

end of that PHE, and one commenter 

specifically urged us to continue 

measure suppression for the PHE due to 

COVID–19 in FY 2023 to account for 

late surges that occurred in late CY 2020 

and early CY 2021. A few commenters 

also expressed appreciation for our 

intent to standardize our suppression 

policy across settings and payment 

programs. 

Response: We agree that the Measure 

Suppression Factors are appropriate. In 

our development of this measure 

suppression proposal, we considered 

that COVID–19 prevalence has not been 

identical across the country and that 

SNFs located in different regions have 

been affected differently during the 

PHE. Our proposal in the FY 2022 SNF 

PPS proposed rule was to adopt a 

measure suppression policy only for the 

duration of the COVID–19 PHE and to 

suppress the SNF readmission measure 

for only the FY 2022 SNF VBP Program, 

but we are continuing to consider 

options for mitigating any potential 

negative impacts the PHE due to 

COVID–19 may have on the FY 2023 

Program. 

Comment: A few commenters noted 

that CMS should be required to go 

through the rulemaking process when 

suppressing measures to ensure that the 

approach is fully vetted. 

Response: We thank commenters and 

agree that we should use the rulemaking 

process if we consider suppressing one 

or more measures. 

After considering the public 

comments, we are finalizing our 

measure suppression policy as 

proposed. 

2. Suppression of the SNFRM for the FY 

2022 SNF VBP Program Year 

In the proposed rule, we proposed to 

suppress the SNFRM for the FY 2022 

SNF VBP Program Year under proposed 

Measure Suppression Factor: (4) 

Significant national shortages or rapid 

or unprecedented changes in: (iii) 

Patient case volumes or facility-level 

case mix. 

In response to the PHE for COVID–19, 

we granted an ECE for SNFs 

participating in the SNF VBP Program. 

Under the ECE, SNF qualifying claims 

for the period January 1, 2020 through 

June 30, 2020 are excepted from the 

calculation of the SNFRM. Because this 

ECE excepted data for 6 months of the 

performance period that we had 

previously finalized for the FY 2022 

SNF VBP program year (84 FR 38822), 

we updated the performance period for 

that program year in the ‘‘Medicare and 

Medicaid Programs, Clinical Laboratory 

Improvement Amendments, and Patient 

Protection and Affordable Care Act: 

Additional Policy and Regulatory 

Revisions in Response to the COVID–19 

Public Health Emergency’’ interim final 

rule with comment (‘‘the September 2nd 

IFC’’) (85 FR 54820). Specifically, we 

finalized that the new performance 

period for the FY 2022 SNF VBP 

program year would be April 1, 2019 

through December 31, 2019 and July 1, 

2020 through September 30, 2020 

because we believed that this period, 

which combined 9 months of data prior 

to the start of the PHE for COVID–19 

and 3 months of data after the end of the 

ECE, would provide sufficiently reliable 

data for evaluating SNFs for the FY 2022 

SNF VBP Program. However, analyses 

conducted by our contractor since the 

publication of the September 2nd IFC 

have found that when July–September 

2020 SNF data are compared with July– 

September 2019 SNF data, the July– 

September 2020 SNF data showed 25 

percent fewer SNF admissions and 26 

percent fewer readmissions from a SNF 

to a hospital. These impacts have 

affected the reliability of the SNFRM. 

Generally speaking, the SNFRM’s 

reliability decreases as the sample size 

and measured outcome (that is, 

readmissions) decrease. A drop of 25 

percent in SNF admissions and 26 

percent in readmissions to the hospital 

from July–September 2020 has 

significantly reduced the sample size 

needed to calculate both the measure 

cohort and outcome for the FY 2022 

SNF VBP Program, thus jeopardizing the 

measure’s reliability. Our contractor’s 

analysis using FY 2019 data showed 

that such changes may lead to a 15 

percent decrease in the measure 

reliability, assessed by the intra-class 

correlation coefficient (ICC). In addition, 

the current risk-adjustment model does 

not factor in COVID–19 or the fact that 

SNFs are treating different types of 

patients as a result of the COVID–19 

PHE. Nearly 10 percent of SNF residents 

in July–September 2020 had a current or 

prior diagnosis of COVID–19, with 

uneven regional impacts. The SNFRM 

does not adjust for COVID–19 in the 

risk-adjustment methodology, as the 

measure was developed before the 

pandemic. As a result, risk-adjusted 

rates, which compare SNFs to each 

other nationally, are likely to reflect 

variation in COVID–19 prevalence 

rather than variation in quality of care. 

We do not believe that assessing SNFs 

on a quality measure affected 

significantly by the varied regional 

response to the COVID–19 PHE presents 

a clear picture of the quality of care 

provided by an individual SNF. The 

data also demonstrated other important 

changes in SNF patient case-mix during 

the PHE for COVID–19, including an 18 

percent increase in the proportion of 

dually eligible residents and a 9 percent 

increase in the proportion of AfricanAmerican SNF residents at the facility 

level. Dually eligible and AfricanAmerican SNF residents have been 

disproportionately impacted by COVID, 

both in terms of morbidity and 

mortality. In the proposed rule, we 

stated we are conducting analyses to 

determine whether and how the SNFRM 

specifications may need to be updated 

to account for SNF residents with a 

primary or secondary diagnosis of 

COVID–19 for future program years. We 

also stated we plan to conduct analysis 

for the SNFPPR measure. 

We considered whether we could 

propose to remove the July 1, 2020– 

September 30, 2020 data from the 

updated performance period for the FY 

2022 SNF VBP Program Year and 

calculate the SNFRM using a 9-month 

performance period (April 1, 2019– 

December 31, 2019). To determine 

whether the measure would be reliable 

using data during this period, which 

would be closer to 8 months once we 

remove all SNF stays whose 30-day 

readmission risk-window extended to or 

after January 1, 2020, we performed 

reliability analyses using a formula that 

relates the reliability of a measure to its 

intraclass correlation coefficient (ICC), 

and found that an estimate of reliability 

using all 12 combinations of potential 8- 

month data periods from FY 2019 (that 


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116We assessed multiple 8-month data periods 

and averaged the reliability results to obtain a 

complete understanding of reliability across FY 

2019, the most recent full year of production data 

available for analysis, and avoid potential issues 

caused by seasonality. 

is, October through May, November 

through June, and so on) 116 produces an 

average reliability estimate of 0.367, 

which is lower than our generally 

accepted minimum reliability threshold 

of 0.40. 

We also considered substituting the 

July 1, 2020–September 30, 2020 period 

with an alternate data period; however, 

we are limited operationally in terms of 

which data may be used. Using data 

from further in the future would cause 

a delay in the calculation and 

dissemination of results for the FY 2022 

Program. Such a delay could require us 

to make adjustments to the otherwise 

applicable Federal per diem rate paid to 

SNFs in FY 2022 on a delayed basis, 

which would be an extremely 

burdensome process for the MACs and 

a potentially confusing process for 

SNFs. While using older data is feasible, 

and we recognize that we adopted a 

performance period in the September 

2nd IFC that duplicated the use of data 

from a previous performance period, our 

preference is to use as much new data 

as possible to assess SNF performance 

each year and to avoid, where feasible, 

using the same data as a performance 

period in multiple program years. 

Further revising the FY 2022 Program 

performance period to include older 

data would create a substantial overlap 

with the FY 2021 Program’s 

performance period. Such a significant 

overlap would result in SNFs receiving 

payments in FY 2022 based largely on 

the same performance used to assess 

SNFs for the FY 2021 SNF VBP program 

year. Using over 80 percent of the same 

data twice as a performance period 

could result in some SNFs being 

penalized (or receiving a bonus) twice 

for nearly the same performance. 

Therefore, due to concerns about the 

validity of the measure when calculated 

as currently specified on data during the 

PHE given the significant changes in 

SNF patient case volume and facilitylevel case mix described above, and 

lacking any viable alternatives, we 

proposed to suppress the use of SNF 

readmission measure data for purposes 

of scoring and payment adjustments in 

the FY 2022 SNF VBP Program Year, 

under the proposed Measure 

Suppression Factor (4) Significant 

national or regional shortages or rapid 

or unprecedented changes in: (iii) 

Patient case volumes or facility-level 

case mix. 

As we stated in the proposed rule, 

under this suppression policy, for all 

SNFs participating in the FY 2022 SNF 

VBP Program, we would use the 

previously finalized performance period 

and baseline period to calculate each 

SNF’s RSRR for the SNFRM. Then, we 

would suppress the use of SNF 

readmission measure data for purposes 

of scoring and payment adjustments. 

Specifically, we proposed to change the 

scoring methodology to assign all SNFs 

a performance score of zero in the FY 

2022 SNF VBP Program Year. This 

would result in all participating SNFs 

receiving an identical performance 

score, as well as an identical incentive 

payment multiplier. We would then 

apply the Low-Volume Adjustment 

policy as previously finalized in the FY 

2019 SNF PPS final rule (83 FR 39278 

through 39280). That is, if a SNF has 

fewer than 25 eligible stays during the 

performance period for a program year 

we would assign that SNF a 

performance score resulting in a netneutral payment incentive multiplier. 

SNFs will not be ranked for the FY 2022 

SNF VBP Program. 

As we stated in the proposed rule, 

under this policy, we would reduce 

each participating SNF’s adjusted 

Federal per diem rate for FY 2022 by 2 

percentage points and award each 

participating SNF 60 percent of that 2 

percent withhold, resulting in a 1.2 

percent payback for the FY 2022 SNF 

VBP Program Year. We believe this 

continued application of the 2 percent 

withhold is required under section 

1888(h)(5)(C)(ii)(III) of the Act and that 

a payback percentage that is spread 

evenly across all qualifying SNFs is the 

most equitable way to reduce the impact 

of the withhold in light of our proposal 

to award a performance score of zero to 

all SNFs. Those SNFs subject to the 

Low-Volume Adjustment policy would 

receive 100 percent of their 2 percent 

withhold per the previously finalized 

policy, increasing the overall payback 

percentage to an estimated 62.9 percent. 

Further, we proposed to provide 

quarterly confidential feedback reports 

to SNFs and publicly report the SNFRM 

rates for the FY 2022 SNF VBP Program 

Year. However, we stated that we would 

make clear in the public presentation of 

those data that the measure has been 

suppressed for purposes of scoring and 

payment adjustments because of the 

effects of the PHE for COVID–19 on the 

data used to calculate the measure. We 

proposed to codify this policy at 

§ 413.338(g). 

We invited public comment on this 

proposal. The following is a summary of 

the public comments we received on the 

proposed Suppression of the SNFRM for 

the FY 2022 SNF VBP Program Year, 

and our responses: 

Comment: Many commenters 

expressed support for the proposal to 

suppress the SNFRM data for the 

purposes of scoring and payment 

adjustments for the FY 2022 SNF VBP 

Program Year under Measure 

Suppression Factor (4) Significant 

national or regional shortages or rapid 

or unprecedented changes in: (iii) 

Patient case volumes or facility-level 

case mix. Commenters agreed with our 

conclusion that the inclusion of data 

during the PHE due to COVID–19 would 

significantly affect the SNF readmission 

measure and not present a clear picture 

of the quality of care provided by an 

individual SNF. Additionally, they 

noted that CMS provided a fair path 

forward given the FY 2020 average 

reliability estimate using FY 2019 data 

was lower than the minimum reliability 

threshold. 

Response: We thank the commenters 

for their support. 

Comment: One commenter stated that 

the proposed measure suppression 

policy violates the provisions of section 

1888(h)(6) of the Act, which funds 

value-based incentive payments via a 

reduction to SNFs’ adjusted Federal per 

diem rates. The commenter also stated 

that the proposed suppression policy 

does not differentiate between highperforming and low-performing SNFs, 

and therefore, does not make valuebased incentive payments as required by 

statute. 

Response: As discussed in the 

proposed rule, we proposed to suppress 

the SNFRM due to the impacts of the 

COVID–19 PHE. Specifically, we have 

concerns about the validity of the 

measure when calculated as currently 

specified using data during the PHE 

given the significant changes in SNF 

patient case volume and facility-level 

case mix. We continue to believe that 

for purposes of scoring and payment 

adjustments under the SNF VBP 

Program, the SNFRM as impacted by the 

COVID–19 PHE should not be attributed 

to the participating facility positively or 

negatively, because the performance 

scores associated with the SNFRM 

would not accurately reflect facility 

performance for national comparison 

and ranking purposes given the 

variation in COVID–19 across different 

geographies and time periods and seen 

in fluctuating case volumes and case 

mix. However, due to the SNFRM being 

the only quality measure authorized for 

use in the FY 2022 SNF VBP, 

suppression of the SNFRM would mean 

we would not be able to calculate SNF 

performance scores for any SNF or to 

differentially rank SNFs. Therefore, we 


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proposed to change the scoring 

methodology to assign all SNFs a 

performance score of zero and 

effectively rank all SNFs equally in the 

FY 2022 SNF VBP Program Year. 

Comment: Several commenters 

expressed concerns about publicly 

reporting SNFRM measure results for 

the FY 2022 SNF VBP Program Year 

despite the measure being suppressed 

because they believe that the publicly 

reported information may cause public 

confusion and misrepresent quality of 

care for a particular SNF. Two 

commenters also noted that the SNFRM 

does not adjust for COVID–19 diagnoses 

and should not be publicly reported 

until it does. 

Response: We proposed to suppress 

the SNFRM due to the impacts of the 

COVID–19 PHE for purposes of scoring 

and payment adjustments because of 

our concern that we would not be able 

to make fair, national comparisons of 

SNFs across the country or to fairly and 

accurately rank SNFs based only on 

quality performance and not other 

exogenous factors related to the PHE for 

COVID–19. We also believe it is 

important to balance fairness in 

performance-based payments with the 

public’s interest in and need for 

transparency of data from during the 

COVID–19 PHE, including hospital 

readmissions information for SNF 

patients. Therefore, we intend to make 

the data available on the Provider Data 

Catalogue (https://data.cms.gov/ 

provider-data/) website. We will make 

clear in the public presentation of the 

data that the measure has been 

suppressed for purposes of scoring and 

payment adjustments because of the 

effects of the PHE due to COVID–19. We 

will also appropriately caveat the data 

in order to mitigate public confusion 

and avoid misrepresenting quality of 

care. SNFs that qualify for the lowvolume adjustment policy will not have 

their risk-standardized readmission rate 

publicly displayed and an explanatory 

footnote will be available instead. 

We also understand the commenters’ 

concern that the SNFRM does not 

currently adjust for COVID–19 

diagnoses in the risk-adjustment 

methodology, as the measure was 

developed before the PHE. We have 

conducted internal analyses that 

indicated a large number of patients 

who were admitted to SNFs had a 

primary or secondary diagnosis of 

COVID–19 during their prior proximal 

hospitalization. The SNFRM does not 

currently account for COVID–19, and 

we believe it is important to more fully 

assess the impact of COVID–19 on the 

SNFRM, including the following: 

Whether we should add COVID–19 as a 

risk-adjustment variable, exclude 

COVID–19 patients from the 

denominator, or exclude COVID–19 

readmissions from the outcome. 

After considering the public 

comments, we are finalizing our 

proposal to suppress the SNFRM for the 

FY 2022 SNF VBP Program Year as 

proposed and codifying it, as well as the 

scoring and payment policies we are 

finalizing for FY 2022, at § 413.338(g) of 

our regulations. 

3. Revision to the SNFRM Risk 

Adjustment Lookback Period for the FY 

2023 SNF VBP Program 

In the FY 2021 SNF PPS final rule (85 

FR 47624), we finalized the FY 2023 

Program performance period as FY 2021 

(October 1, 2020–September 30, 2021). 

In the FY 2016 SNF PPS final rule (80 

FR 46418), we finalized that the riskadjustment model would account for 

certain risk-factors within 365 days 

prior to the discharge from the hospital 

to the SNF (a 365-day lookback period). 

Under the COVID–19 ECE, SNF 

qualifying claims for the period January 

1, 2020–June 30, 2020 are excepted from 

the calculation of the SNFRM; using FY 

2021 data, this results in at least 3 

months of lookback data being available 

for all SNF stays included in the 

measure without extending into or 

beyond June 30, 2020. We proposed 

instead a 90-day lookback period for 

risk-adjustment in the FY 2023 

performance period (FY 2021 data) only. 

We stated in the proposed rule that 

using a 90-day risk-adjustment period 

would allow us to use the most recent 

claims available for risk-adjustment, and 

an identical risk-adjustment lookback 

period for all stays included in the 

measure. It also allows us to avoid 

combining data from both prior to and 

during the COVID–19 PHE in the riskadjustment lookback period, which 

would be necessary if we attempted to 

maintain a 12-month lookback period 

due to the COVID–19 ECE. Using a 90- 

day lookback period for risk-adjustment 

would allow us to look back 90 days 

prior to the discharge from the hospital 

to the SNF for each SNF stay. Analyses 

conducted on FY 2019 performance data 

found that when compared to the 365- 

day lookback period traditionally used, 

a 90-day lookback period resulted in 

similar model performance (that is, the 

C-statistic was nearly identical). We also 

considered similarly reducing the riskadjustment lookback period for the 

applicable FY 2023 Program baseline 

year which would align the riskadjustment lookback period for the 

baseline and performance years in the 

FY 2023 Program; we invited comments 

on this consideration. 

We invited public comment on the 

proposed updates to the risk-adjustment 

lookback period for the FY 2023 

performance period. 

The following is a summary of the 

public comments received on the 

proposed 90-day SNFRM riskadjustment lookback period for the FY 

2023 SNF VBP Program performance 

period and our responses: 

Comment: One commenter 

recommended continued testing of the 

90-day risk-adjustment lookback period 

for FY 2023, stating that this approach 

worked well using FY 2019 performance 

data. The commenter stated that testing 

with FY 2020 data and analyses of 

regional effects based on COVID–19 

impacts would be informative before 

finalizing this approach. 

Response: We acknowledge the 

commenter’s suggestion to continue 

testing the 90-day risk-adjustment 

lookback period for FY 2023 and agree 

with the importance of continued 

testing. We note that the analyses we 

conducted on FY 2019 performance data 

resulted in nearly identical C-statistics, 

indicating that the model using a 90-day 

lookback period performed similarly to 

the model using a traditional 365-day 

lookback period. We will continue to 

test FY 2020 data in a similar fashion, 

but we believe the results from the FY 

2019 data illustrate the model 

performance for a 90-day lookback 

period for the FY 2023 performance 

period. 

After considering the public 

comments, we are finalizing our 

proposal to use a 90-day lookback 

period for risk-adjustment in the FY 

2023 performance period (FY 2021). 

4. Summary of Comments Received on 

Potential Future Measures for the SNF 

VBP Program 

On December 27, 2020, Congress 

enacted the Consolidated 

Appropriations Act, 2021 (CAA) (Pub. 

L. 116–260). Section 111(a)(1) of 

Division CC of the CAA amends section 

1888(h)(1) of the Act to, with respect to 

payments for services furnished on or 

after October 1, 2022, preclude the SNF 

VBP from applying to a SNF for which 

there are not a minimum number (as 

determined by the Secretary) of cases for 

the measures that apply to the facility 

for the performance period for the 

applicable fiscal year, or measures that 

apply to the facility for the performance 

period for the applicable fiscal year. 

Section 111(a)(2) of the CAA amended 

section 1888(h)(2)(A) of the Act to, with 

respect to payments for services 

furnished on or after October 1, 2023, 

require the Secretary to apply the 

readmission measure specified under 


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section 1888(g)(1) of the Act, and allow 

the Secretary to apply up to 9 additional 

measures determined appropriate, 

which may include measures of 

functional status, patient safety, care 

coordination, or patient experience. To 

the extent that the Secretary decides to 

apply additional measures, section 

1888(h)(2)(A)(ii) of the Act, as amended 

by section 111(a)(2)(C) of the CAA, 

requires the Secretary to consider and 

apply, as appropriate, quality measures 

specified under section 1899B(c)(1) of 

the Act. Finally, section 111(a)(3) of the 

CAA amended section 1888(h) of the 

Act by adding a new paragraph (12), 

which requires that the Secretary apply 

a process to validate the measures and 

data submitted under the SNF VBP and 

the SNF QRP, as appropriate, which 

may be similar to the process specified 

under the Hospital Inpatient Quality 

Reporting (IQR) Program for validating 

inpatient hospital measures. In the 

proposed rule, we solicited input from 

stakeholders regarding which measures 

we should consider adding to the SNF 

VBP Program. We intend to use future 

rulemaking to address these new 

statutory requirements. 

Currently, the SNF VBP Program 

includes only a single quality measure, 

the SNFRM, which we intend to 

transition to the SNFPPR measure as 

soon as practicable. Both the SNFRM 

and SNFPPR assess the risk-adjusted 

rate of readmissions to hospitals, for 

SNF residents within 30 days of 

discharge from a prior hospital stay. 

Consistent with amended section 

1888(h)(2)(A)(ii) of the Act, in 

considering which measures might be 

appropriate to add to the SNF VBP 

Program, we are considering additional 

clinical topics such as measures of 

functional status, patient safety, care 

coordination, and patient experience, as 

well as measures on those topics that 

are utilized in the SNF Quality 

Reporting Program (QRP). For more 

information about the SNF QRP 

measures, please visit https://

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

Skilled-Nursing-Facility-QualityReporting-Program/SNF-QualityReporting-Program-Measures-andTechnical-Information. 

We are also considering measures on 

clinical topics that are not included in 

the SNF QRP’s measure set because we 

believe that other clinical topics would 

be helpful to our efforts to robustly 

assess the quality of care furnished by 

SNFs. 

In expanding the SNF VBP measure 

set, we are also considering measures 

that we already require for Long-Term 

Care Facilities (LTCFs), which include 

both SNFs and nursing facilities (NFs), 

to collect and report under other 

initiatives. Approximately 94 percent of 

LTCFs are dually certified as both a SNF 

and NF (Provider Data Catalog Nursing 

Homes and Rehab Services Provider 

Information File January 2021) (https:// 

data.cms.gov/provider-data/dataset/ 

4pq5-n9py). The vast majority of LTCF 

residents are also Medicare 

beneficiaries, regardless of whether they 

are in a Medicare Part A SNF stay, 

because they are enrolled in Medicare 

Part B and receive Medicare coverage of 

certain services provided by the LTCF 

even if they are a long-term care 

resident. Therefore, we believe that 

expanding the SNF VBP measure set to 

assess the quality of care that SNFs 

provide to all residents of the facility, 

regardless of payer, would best 

represent the quality of care provided to 

all Medicare beneficiaries in the facility. 

We requested public comment on 

whether the measures in an expanded 

SNF VBP measure set should require 

SNFs to collect data on all residents in 

the facility, regardless of payer. 

We identified the measures listed in 

Table 30 as measures we could add to 

the SNF VBP Program measure set, and 

we sought comment on those measures, 

including which of those measures 

would be best suited for the program. 

We also solicited public comment on 

any measures or measure concepts that 

are not listed in Table 30 that 

stakeholders believe we should consider 

for the SNF VBP Program. In 

considering an initial set of measures 

with which SNFs should largely be 

familiar (through the SNF QRP, 5-Star 

Rating Program and/or the Nursing 

Home Quality Initiative (NHQI)), we 

believe we can implement a measure set 

that would impose minimal additional 

burden on SNFs. 

BILLING CODE 4120–01–P 


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BILLING CODE 4120–01–C 

In addition to the staffing measures 

listed in Table 30 that focus on nurse 

staffing hours per resident day and that 

are currently reported on the Nursing 

Home Care Compare website, we 

indicated in the proposed rule that we 

are also interested in measures that 

focus on staff turnover. We have been 

developing measures of staff turnover 

for data that are required to be 

submitted under section 1128I(g)(4) of 

the Act, with the goal of making the 

information publicly available. Through 

our implementation of the Payroll-Based 

Journal (PBJ) staffing data collection 

program, we have indicated that we will 

be reporting rates of employee turnover 

in the future (for more information on 


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TABLE 30: Quality Measures Under Consideration for an Expanded Skilled Nursing 

Facility Value-Based Purchasing Program 

Meaningful NQF Quality Measure Measure Area 

Minimum Data Set 

Functional A2635 Application ofIRF Functional Outcome Measure: Discharge Self-Care Score for 

Outcomes Medical Rehabilitation Patients* 

Functional A2636 Application ofIRF Functional Outcome Measure: Discharge Mobility Score for 

Outcomes Medical Rehabilitation Patients* 

Preventable 0674 Percent of Residents Experiencing One or More Falls with Major Injury (Long 

Healthcare Harm Stay)** 

Preventable 0679 Percent of High Risk Residents with Pressure Ulcers (Long Stay)** 

Healthcare Harm 

Functional NIA Percent of Residents Whose Ability to Move Independently Worsened (Long 

Outcomes Stay)** 

Functional NIA Percent of Residents Whose Need for Help with Activities of Daily Living Has 

Outcomes Increased (Long Stay)** 

Transfer of Health Transfer of Health Information to the Provider-Post Acute Care* 

Information and NIA 

Interoperabilitv 

Medication NIA Percentage of Long-Stay Residents who got an Antipsychotic Medication** 

Management 

Medicare Fee-For-Service Claims Based Measures 

Community 3481 Discharge to Community Measure-Post Acute Care Skilled Nursing Facility 

Engagement Quality Reporting Program* 

Patient-focused NIA Medicare Spending per Beneficiary (MSPB)-Post Acute Care Skilled Nursing 

Episode of Care Facilitv Qualitv Reporting Program* 

Healthcare- Skilled Nursing Facility Healthcare-Associated Infections Requiring 

Associated NIA Hospitalization Measure~ 

Infections 

Admissions and Number of hospitalizations per 1,000 long-stay resident days (Long Stay)** 

Readmissions to NIA 

Hospitals 

Patient-Reported Outcome-Based Performance Measure 

Functional NIA Patient-Reported Outcomes Measurement Information System [PROMIS]-

Outcomes PROMIS Global Health, Physical 

Survey Questionnaire (similar to Consumer Assessment of Healthcare Providers and Systems (CARPS)) 

Patient's CoreQ: Short Stay Discharge Measure 

Experience of 2614 

Care 

Payroll Based Journal 

Nurse staffing hours per resident day: Registered Nurse (RN) hours per resident 

NIA NIA per day; Total nurse staffing (including RN, licensed practical nurse (LPN), and 

nurse aide) hours per resident per day** 

* Measures adopted in the SNF Quality Reporting Program (QRP). 

** These measures are reported on the Nursing Home Care Compare website (b_ttps:/lwww.medicare.gov/carecompare/). 

~ Measure discussed in section VII. C. l of this final rule for adoption in the SNF QRP. 
42510 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

117https://www.cms.gov/Medicare/ProviderEnrollment-and-Certification/SurveyCertification

GenInfo/Downloads/QSO18-17-NH.pdf. 

this program, see CMS memorandum 

QSO–18–17–NH 117). As we plan to 

report employee turnover information in 

the near future, we also sought comment 

on inclusion of these measures in the 

SNF VBP Program. 

We are also considering two patientreported measures (the PROMIS 

measure and the CoreQ patient 

experience of care measure), as listed in 

Table 30, to assess residents’ views of 

their healthcare. 

The CoreQ: Short Stay Discharge 

Measure calculates the percentage of 

individuals discharged in a 6-month 

time period from a SNF, within 100 

days of admission, who are satisfied 

with their SNF stay. This patient 

reported outcome measure is based on 

the CoreQ: Short Stay Discharge 

questionnaire that utilizes four items: 

(1) In recommending this facility to your 

friends and family, how would you rate 

it overall; (2) Overall, how would you 

rate the staff; (3) How would you rate 

the care you receive; (4) How would you 

rate how well your discharge needs 

were met. For additional information 

about the CoreQ: Short Stay Discharge 

Measure, please visit https://

cmit.cms.gov/CMIT_public/ 

ViewMeasure?MeasureId=3436. 

We welcomed public comment on 

future measures for the SNF VBP 

Program, and on whether the measures 

in an expanded SNF VBP measure set 

should require SNFs to collect data on 

all residents in the facility, regardless of 

payer. 

The following is a summary of the 

public comments received on the 

Request for Comments on Potential 

Future Measures for the SNF VBP 

Program: 

Comment: Many commenters 

generally supported the adoption of new 

measures in the SNF VBP Program. 

However, many commenters did not 

support the Percentage of Long-Stay 

Residents who got an Antipsychotic 

Medication measure noting concerns 

with disincentivizing clinically 

appropriate access to FDA-approved 

medications, impact on patient care and 

outcomes, and that the measure is not 

NQF-endorsed. 

A few commenters supported CoreQ: 

Short Stay Discharge Measure (CoreQ) 

stating it measures outcomes important 

to residents. A few commenters 

expressed concerns that CoreQ may not 

fully reflect the patient experience and 

that the measure’s questions are vague. 

A few commenters recommended the 

use of CAHPS Nursing Home Resident 

and Family member surveys instead of 

the CoreQ questionnaire because 

commenters believe it provides more 

complete and comprehensive 

information about a resident’s 

experience and is developed through a 

more rigorous and independent process. 

A few commenters supported inclusion 

of the Skilled Nursing Facility 

Healthcare-Associated Infections 

Requiring Hospitalization Measure 

(HAI) in the SNF VBP Program to 

support and prioritize improved patient 

outcomes. A few commenters supported 

the inclusion of the Medicare Spending 

per Beneficiary (MSPB) measure 

because the measure captures elements 

of care coordination that are important 

to beneficiaries and the Medicare 

program. A few commenters did not 

support the MSPB measure, citing their 

belief that costs can vary depending 

upon beneficiary needs and that the 

measure does not reflect the immediate 

need or interests of residents or families. 

With respect to measures related to 

staffing turnover, several commenters 

supported staffing measures that assess 

the appropriate level of licensed clinical 

staff such as those that can be derived 

from the Payroll-Based Journal (PBJ) 

data collection program, including 

Registered Nurse (RN) hours per 

resident per day and total nurse staffing 

(including RN, licensed practical nurse 

(LPN), and nurse aide) hours per 

resident per day. While they supported 

these PBJ-based staffing measures, 

commenters strongly recommended that 

CMS consider staffing turnover to assess 

patterns and consistency in staffing 

levels as they are associated with and 

indicative of quality and safety issues, 

and high turnover could lead to low 

quality of care and could disrupt the 

health, safety, and well-being of 

patients. 

Several commenters expressed some 

concerns with the inclusion of a staffing 

measure. One commenter recommended 

that staffing measures should focus on 

consistent staffing rather than just 

collecting data on the number of nursing 

staff by type. One commenter noted that 

staffing measures are important to report 

but expressed concern that staffing 

measures have not been evaluated for 

use in value-based purchasing 

programs, and another commenter 

suggested that staffing requirements 

vary across states. A few commenters 

expressed concerns with the burden of 

reporting a staffing measure. A few 

commenters recommended delaying the 

addition of a staffing measure due to the 

COVID–19 pandemic. 

One commenter supported the 

inclusion of Patient Reported Outcome 

Measures (PROMs) as soon as possible 

and appreciated the consideration of the 

two PROMs (PROMIS and the CoreQ 

patient experience of care) for future 

years. One commenter supported the 

use of the PROMIS questionnaire, but 

noted additional resources would be 

needed for implementation. One 

commenter recommended that the 

patient experience measure use minimal 

questions and take into account the role 

of caregivers in helping complete the 

surveys. One commenter recommended 

that any PROMIS measure considered 

be reviewed by NQF; this commenter 

also noted that PROMIS measures were 

not developed for institutional 

populations and that CMS should 

consider the burden to collect, store, 

and transmit these data. 

Many commenters supported the use 

of patient experience measures in the 

SNF VBP Program. One commenter 

recommended that patient experience 

measures be adjusted for respondent 

characteristics. One commenter 

recommended excluding beneficiaries 

in managed care plans from a patient 

experience measure, expressing concern 

that beneficiaries may be unsatisfied 

with how their stay was managed by 

their Managed Care/Medicare 

Advantage Plan and that this would 

reflect negatively towards the SNF on a 

patient-reported outcome survey. A few 

commenters recommended delaying the 

implementation of patient experience 

surveys due to the COVID–19 pandemic. 

One commenter did not support the two 

patient-reported measures, noting the 

survey process already includes 

residents, and suggested that we focus 

on expanding the survey protocol 

instead of adding a new measure. This 

commenter also stated that the 

questions on the CoreQ measure may 

not sufficiently capture customer 

dissatisfaction. Instead, this commenter 

recommended strengthening and 

expanding the current CMS survey 

protocol. One commenter recommended 

the development and adoption of a 

standardized patient experience survey 

for the SNF QRP before potentially 

being adopted for the SNF VBP 

Program. 

A few commenters recommended 

inclusion of the NQF 3481, Discharge to 

Community Measure-Post Acute Care 

Skilled Nursing Facility Quality 

Reporting Program measure. A few 

commenters recommended inclusion of 

the NQF A2636, Application of IRF 

Functional Outcome Measure: Discharge 

Mobility Score for Medical 

Rehabilitation Patients measure. One 

commenter recommended inclusion of 

the Preventable Healthcare Harm—0674 

Percent of Residents Experiencing One 

or More Falls with Major Injury 


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measure. One commenter recommended 

inclusion of the Transfer of Health 

Information (HI) and Interoperability— 

Transfer of Health Information to the 

Provider-Post Acute Care measure to 

advance CMS’ goals of improving 

patient safety through adoption of EHR 

and FHIR standards. 

Several commenters recommended 

aligning SNF VBP readmissions 

measures with the readmission 

measures used by other CMS programs, 

including the SNF QRP. One commenter 

recommended criteria for evaluating 

which measures should be adopted in 

the SNF VBP Program, including 

measures with NQF endorsement, high 

impact on outcomes/performance, 

resident quality of life focus, low 

administrative burden, statistically 

significant variation among providers, 

risk-adjustment for social risk factors, 

and appropriate application to the SNF 

population and their health status. 

Many commenters recommended that 

any new measures added to SNF VBP be 

NQF-endorsed. One commenter 

recommended that any new measures 

should include descriptions of the 

measure’s weight and scoring 

requirements. Another commenter 

recommended that CMS balance the 

need for new quality measures with 

reducing administrative burden and 

duplicative reporting in other quality 

programs. A few commenters 

recommended a phased approach to 

adding new measures to the SNF VBP 

Program. One commenter recommended 

limiting the number of measures added 

in the first year in order to avoid 

diluting the Program’s clear focus on 

readmissions. One commenter noted 

that adding nine additional measures to 

the SNF VBP Program would be too 

aggressive in expanding the measures 

and recommended adding two or three 

measures suggesting this would be 

easier to integrate and allow providers 

time to prepare. One commenter 

recommended delaying the addition of 

measures until after the PHE has ended. 

Several commenters expressed 

support for collecting performance data 

across payers. One commenter 

supported that any and all new 

measures require data on all SNF 

residents regardless of payer. One 

commenter did not support moving to 

all-payer for most measures but did 

support the inclusion of all residents 

across payers in the patient experience 

measure to increase the sample size for 

an important measure of quality care. A 

few commenters did not support the 

inclusion of nursing home residents in 

the calculation of measure results for 

the SNF VBP Program noting differences 

in policies such as limitations on days 

of care under Medicare Advantage. A 

few commenters recommended that not 

all measures should apply to all 

residents within a nursing home and 

that there should be a distinction 

between measures for short-term and 

long-term stay residents to 

accommodate the different goals 

between these two types of residents. 

One commenter recommended that 

CMS focus on adding outcomes-based 

measures to the SNF VBP Program. A 

few commenters did not support any 

new measures based on self-reported 

MDS data, believing these data are 

inaccurate. One commenter 

recommended that measures should 

incorporate social determinants of 

health when feasible and applicable. 

One commenter did not support the 

inclusion of utilization-based measures. 

A few commenters recommended 

future consideration of new measures 

for frailty, patient reported outcomes, 

health equity, and pain, including the 

following measures: Satisfaction with 

Participation in Social Roles; Ability to 

Participate in Social Roles and 

Activities; Cognitive Function— 

Abilities; General Life Satisfaction; 

General Self-Efficacy: Self-Efficacy for 

Managing Chronic Conditions— 

Managing Daily Activities, Self-Efficacy 

for Managing Chronic Conditions— 

Managing Symptoms, and Self-Efficacy 

for Managing Chronic Conditions— 

Managing Medications and Treatment. 

Another commenter recommended 

measures of patient and workforce 

safety and reliability, clinical quality, 

and caregiver engagement that are 

evidence-based, targeted, and 

meaningful to patients and caregivers; 

this commenter also encouraged the 

collection of data based on key variables 

of inequities in patient care for all types 

of measures. One commenter 

recommended a small set of populationbased measures tied to outcomes, 

patient-experience and resource use that 

are not burdensome to report. One 

commenter recommended that CMS add 

a risk-adjustment variable for 

socioeconomic status to the hospital 

readmission measure for the SNF VBP. 

One commenter recommended a 

measure focused on resident 

‘‘dumping.’’ One commenter 

recommended a measure comparing the 

Minimum Data Set section GG: 

Functional Abilities and Goals with 

length of stay to develop an outcome 

ratio to account for patient complexity 

for facilities with short-term transitional 

care patients. 

One commenter recommended that 

CMS take steps to ensure the accuracy 

of reported data. One commenter 

recommended further clarification of 

how measure collection may impact 

providers with low-volume Medicare 

beneficiaries and whether this program 

will be extended to nursing facilities. 

One commenter recommended 

prioritizing value for residents by 

returning a higher percentage of 

withheld funds and utilizing measures 

that more directly measure outcomes 

that are important to SNF residents. 

Response: We thank the commenters 

for their responses to this request for 

comments on potential future measures 

for the SNF VBP Program. We will take 

all of this feedback into consideration as 

we develop our policies for future 

rulemaking. In addition, as previously 

indicated, we plan to report SNF 

employee turnover information in the 

near future. 

C. SNF VBP Performance Period and 

Baseline Period 

1. Background 

We refer readers to the FY 2016 SNF 

PPS final rule (80 FR 46422) for a 

discussion of our considerations for 

determining performance periods under 

the SNF VBP Program. In the FY 2019 

SNF PPS final rule (83 FR 39277 

through 39278), we adopted a policy 

whereby we will automatically adopt 

the performance period and baseline 

period for a SNF VBP Program Year by 

advancing the performance period and 

baseline period by 1 year from the 

previous program year. 

2. Updated Performance Period for the 

FY 2022 SNF VBP 

In response to the PHE for COVID–19, 

we granted an ECE for SNFs 

participating in the SNF VBP Program. 

Under the ECE, SNF qualifying claims 

for the period January 1, 2020–June 30, 

2020 are excepted from the calculation 

of the SNFRM. Because this ECE 

excepted data for 6 months of the 

performance period that we had 

previously finalized for the FY 2022 

SNF VBP Program Year (84 FR 38822), 

we updated the performance period for 

that program year in the ‘‘Medicare and 

Medicaid Programs, Clinical Laboratory 

Improvement Amendments, and Patient 

Protection and Affordable Care Act: 

Additional Policy and Regulatory 

Revisions in Response to the COVID–19 

Public Health Emergency’’ interim final 

rule with comment (‘‘the September 2nd 

IFC’’) (85 FR 54820). Specifically, we 

finalized that the new performance 

period for the FY 2022 SNF VBP 

Program Year would be April 1, 2019– 

December 31, 2019 and July 1, 2020– 

September 30, 2020 because we 

believed that this period, which 

combined 9 months of data prior to the 


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start of the PHE for COVID–19 and 3 

months of data after the end of the ECE, 

would provide sufficiently reliable data 

for evaluating SNFs for the FY 2022 

SNF VBP Program. The following is a 

summary of the public comments 

received from the September 2nd IFC 

regarding the updated FY 2022 

performance period. 

Comment: One commenter expressed 

support for the updated performance 

period, agreeing that using only 6 

months of data would not provide 

reliable results. This commenter 

encouraged CMS to extend the ECE to 

include all of 2020 and suspend the 

SNFRM measure for FY 2022. 

Response: We thank this commenter 

for their support. Additionally, we refer 

readers to section VIII.B.1. and VIII.B.2. 

of this final rule, where we have 

finalized several flexibilities that result 

in suppressing the SNFRM for FY 2022. 

Regarding the commenter’s suggestion 

to extend the ECE in section VIII.B.1. of 

the FY 2022 SNF PPS proposed rule (86 

FR 20007), we noted that while we 

considered extending the ECE, this 

option would result in less than 12 

months of data being used to calculate 

the single readmissions measure in the 

Program for multiple program years, 

which we do not believe would provide 

an accurate assessment of the quality of 

care provided in SNFs. This option 

would also leave no comprehensive data 

available for us to provide confidential 

performance feedback to providers nor 

for monitoring and to inform decisionmaking for potential future 

programmatic changes. 

Comment: One commenter opposed 

this updated performance period, noting 

that CMS would not receive reliable 

data from CY 2020, and recommended 

that CMS not score facilities for FY 2020 

performance or make associated 

payment adjustments for the FY 2022 

SNF VBP Program and resume the 

program in subsequent years once 

reliable performance data consistent 

with measure specifications are 

available. Another commenter also 

expressed concern that any CY 2020 

data would be unreliable and urged 

CMS to extend the ECE and suspend the 

SNFRM for FY 2022. 

Response: At the time of the 

publication of the September 2nd IFC, 

we adopted a performance period that 

we believed would provide sufficiently 

reliable data for evaluating SNF 

performance (85 FR 54837) and would 

be the most operationally feasible 

option that included 12 months of data. 

Since the publication of the September 

2nd IFC, additional data have become 

available, and we have conducted 

analyses on the impact of the COVID– 

19 PHE. As described more fully in 

section VIII.B.2. of this final rule, we 

continue to have concerns about the 

validity of the measure when calculated 

as currently specified on data during the 

PHE (specifically, July 1, 2020 through 

September 30, 2020) as well as the 

reliability of the measure when 

calculated using data from a shorter 

timeframe. Further, we considered 

many alternatives to the performance 

period we adopted in the September 

2nd IFC and believed that none were 

sufficient for scoring and payment. 

Therefore, we are finalizing our 

proposal to suppress the SNFRM for the 

FY 2022 SNF VBP Program Year for 

scoring and payment purposes. 

However, for the purposes of measure 

rate calculation and public reporting, to 

ensure we are providing providers and 

the public with as much information as 

possible, we believe the performance 

period adopted in the September 2nd 

IFC is the most appropriate given the 

alternatives. 

Upon consideration of public 

comments, we are finalizing the revised 

Performance Period for the FY 2022 

SNF VBP Program (April 1, 2019 

through December 31, 2019 and July 1, 

2020 through September 30, 2020) as 

established in the September 2nd IFC. 

This performance period will be used to 

calculate each SNF’s RSRR for the 

SNFRM and we will publicly report 

these results on the Provider Data 

Catalogue website (https://

data.cms.gov/provider-data/), while 

making it clear in the public 

presentation of those data that we are 

suppressing the use of those data for 

purposes of scoring and payment 

adjustments in the FY 2022 SNF VBP 

Program. 

3. Performance Period for the FY 2023 

SNF VBP Program 

In the FY 2021 SNF PPS final rule (85 

FR 47624), we finalized that the 

performance period for the FY 2023 

SNF VBP Program Year would be 

October 1, 2020–September 30, 2021 

(FY 2021) and the baseline period 

would be FY 2019 (October 1, 2018– 

September 30, 2019). We did not 

propose any updates to the performance 

period and baseline period previously 

finalized for FY 2023. 

Comment: One commenter did not 

support the previously finalized 

performance period for FY 2023 noting 

that it includes CY 2020 data that is not 

adjusted to account for the impact of 

COVID–19 and is unreliable. 

Response: We are considering 

whether we should make changes to the 

SNFRM specifications to account for 

changes in SNF admission and/or 

hospital readmission patterns that we 

have observed during the COVID–19 

PHE. Any substantive changes to the 

measure specifications would be 

proposed in future rulemaking. 

We noted in the proposed rule (86 FR 

20011 through 20012) that we had 

considered alternatives to the 

previously finalized performance period 

for FY 2023. We specifically considered 

modifying the performance period for 

the FY 2023 program year to Calendar 

Year 2021 (January 1, 2021 through 

December 31, 2021). However, CY 2021 

data are available later than FY 2021 

data and would likely result in a delay 

calculating SNFRM scores for SNFs and 

a subsequent delay in the application of 

payment incentives for the FY 2023 

program year. 

We acknowledge that the COVID–19 

PHE extends into both performance 

period options. As noted in section 

VIII.B.2., we intend to conduct analyses 

to determine whether and how the 

SNFRM specifications may need to be 

updated to account for SNF residents 

with a diagnosis of COVID–19 for future 

program years. Following the 

completion of these analyses, SNF 

readmission measure specifications may 

account for changes in SNF admission 

and/or hospital readmission patterns 

that we have observed during the PHE, 

if needed. 

We invited public comment on this 

alternative to the previously finalized 

performance period for the FY 2023 

SNF VBP program but did not receive 

any comments on this alternative. 

4. Performance Period and Baseline 

Period for the FY 2024 SNF VBP 

Program 

Under the policy finalized in the FY 

2019 SNF PPS final rule (83 FR 39277 

through 39278), for the FY 2024 

program year, the performance period 

would be FY 2022 and the baseline 

period would be FY 2020. However, 

under the ECE, SNF qualifying claims 

for a 6-month period in FY 2020 

(January 1, 2020 through June 30, 2020) 

are excepted from the calculation of the 

SNFRM, which means that we will not 

have a full year of data to calculate the 

SNFRM for the FY 2020 baseline period. 

Moreover, as described in more detail in 

section VIII.B.2. of this final rule, we are 

finalizing the suppression of the 

SNFRM for the FY 2022 program year, 

in part because there are concerns about 

the validity of the measure when 

calculated as currently specified on data 

during the PHE (specifically, July 1, 

2020 through September 30, 2020) given 

the significant changes in SNF patient 

case volume and facility-level case mix 

described above. As the SNF VBP 


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Program uses only a single measure 

calculated on 1 year of data and uses 

each year of data first as a performance 

period and then later on as a baseline 

period in the Program, the removal of 9 

months of data in light of the COVID– 

19 PHE as described above will 

necessarily result in data being used 

more than once in the Program. 

Therefore, to ensure enough data are 

available to reliably calculate the 

SNFRM, we proposed that FY 2019 data 

be used for the baseline period for the 

FY 2024 program year. We also 

considered using FY 2021, which will 

be the baseline period for the FY 2025 

program year under our current policy. 

However, it is operationally infeasible 

for us to calculate the baseline for the 

FY 2024 program year using FY 2021 

data in time to establish the 

performance standards for that program 

year at least 60 days prior to the start of 

the performance period, as required 

under section 1888(h)(3)(C) of the Act. 

We invited public comment on this 

proposal. The following is a summary of 

the public comments received on the 

proposed baseline period for the FY 

2024 SNF VBP program and our 

responses: 

Comment: One commenter noted 

concern that using FY 2019 data as the 

baseline period for the FY 2024 program 

year may not provide relevant or 

comparable data for the performance 

period in FY 2024. Therefore, the 

commenter did not support the 

proposed FY 2024 baseline period. 

Response: Due to measure reliability 

and operational feasibility 

considerations noted in section VIII.C.5. 

of this final rule, as well as FY 2019 data 

were not impacted by the COVID–19 

PHE, we continue to believe that using 

FY 2019 data as the baseline period for 

the FY 2024 performance period is 

appropriate. We are also conducting 

testing to assess whether any updates 

should be made to the specifications of 

the SNF readmission measure to 

account for changes in SNF admission 

and/or hospital readmission patterns 

that we have observed during the PHE 

which may impact the FY 2024 

performance period’s comparability to 

the FY 2024 baseline period. 

Additionally, we believe that using FY 

2019 data will be both relevant and 

comparable as the FY 2019 SNFRM data 

would reflect care delivered prior to the 

start of the Secretary’s declaration of a 

PHE for COVID–19. With regard to the 

FY 2024 performance period, we believe 

facilities will have had time to adapt to 

the changes in care delivery needed to 

respond to the COVID–19 pandemic. 

After considering the public 

comments, we are finalizing our 

proposal to use FY 2019 data for the FY 

2024 baseline period as proposed. 

D. Performance Standards 

1. Background 

We refer readers to the FY 2017 SNF 

PPS final rule (81 FR 51995 through 

51998) for a summary of the statutory 

provisions governing performance 

standards under the SNF VBP Program 

and our finalized performance standards 

policy. We adopted the final numerical 

values for the FY 2022 performance 

standards in the FY 2020 SNF PPS final 

rule (84 FR 38822) and adopted the final 

numerical values for the FY 2023 

performance standards in the FY 2021 

SNF PPS final rule (85 FR 47625). We 

also adopted a policy allowing us to 

correct the numerical values of the 

performance standards in the FY 2019 

SNF PPS final rule (83 FR 39276 

through 39277). 

We did not propose any changes to 

these performance standard policies in 

the proposed rule. 

2. SNF VBP Performance Standards 

Correction Policy 

In the FY 2019 SNF PPS final rule (83 

FR 39276 through 39277), we finalized 

a policy to correct numerical values of 

performance standards for a program 

year in cases of errors. We also finalized 

that we will only update the numerical 

values for a program year one time, even 

if we identify a second error, because 

we believe that a one-time correction 

will allow us to incorporate new 

information into the calculations 

without subjecting SNFs to multiple 

updates. We stated that any update we 

make to the numerical values based on 

a calculation error will be announced 

via the CMS website, listservs, and other 

available channels to ensure that SNFs 

are made fully aware of the update. In 

the FY 2021 SNF PPS final rule (85 FR 

47625), we amended the definition of 

‘‘Performance standards’’ at 

§ 413.338(a)(9), consistent with these 

policies finalized in the FY 2019 SNF 

PPS final rule, to reflect our ability to 

update the numerical values of 

performance standards if we determine 

there is an error that affects the 

achievement threshold or benchmark. 

We did not propose any changes to the 

performance standards correction policy 

in the proposed rule. 

3. Performance Standards for the FY 

2024 Program Year 

As discussed in section VIII.C.5. of 

this final rule, we are finalizing our 

proposal to use FY 2019 data for the 

baseline period for the FY 2024 program 

year. Based on this updated baseline 

period and our previously finalized 

methodology for calculating 

performance standards (81 FR 51996 

through 51998), the final numerical 

values for the FY 2024 program year 

performance standards are as follows: 

E. SNF VBP Performance Scoring 

We refer readers to the FY 2017 SNF 

PPS final rule (81 FR 52000 through 

52005) for a detailed discussion of the 

scoring methodology that we have 

finalized for the Program. We also refer 

readers to the FY 2018 SNF PPS final 

rule (82 FR 36614 through 36616) for 

discussion of the rounding policy we 

adopted. We also refer readers to the FY 

2019 SNF PPS final rule (83 FR 39278 

through 39281), where we adopted: (1) 

A scoring policy for SNFs without 

sufficient baseline period data, (2) a 

scoring adjustment for low-volume 

SNFs, and (3) an extraordinary 

circumstances exception policy. 

In the FY 2022 SNF PPS proposed 

rule, we proposed to suppress the 

SNFRM for the FY 2022 program year 

due to the impacts of the PHE for 

COVID–19. Specifically, for FY 2022 

scoring, we proposed that for all SNFs 

participating in the FY 2022 SNF VBP 

Program, we would use performance 

period data from April 1, 2019 through 

December 31, 2019 and July 1, 2020 

through September 30, 2020 and 

baseline period data from October 1, 

2017 through September 30, 2018, 


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TABLE 31: Final FY 2024 SNF VBP Program Performance Standards 

Measure ID Measure Description Achievement Benchmark 

Threshold 

SNFRM SNF 30-Day All-Cause Readmission Measure (NQF #2510) 0.79271 ().81033 
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which we previously finalized to 

calculate each SNF’s RSRR for the 

SNFRM. Then, we would assign all 

SNFs a performance score of zero. This 

would result in all participating SNFs 

receiving an identical performance 

score, as well as an identical incentive 

payment multiplier. We stated in the 

proposed rule that we would then apply 

the Low-Volume Adjustment policy as 

previously finalized in the FY 2019 SNF 

PPS final rule (83 FR 39278 through 

39280). That is, if a SNF has fewer than 

25 eligible stays during the performance 

period for a program year we would 

assign that SNF a performance score 

resulting in a net-neutral payment 

incentive multiplier. SNFs would not be 

ranked for the FY 2022 SNF VBP 

Program. 

The following is a summary of the 

public comments received on the 

proposal to use a special scoring policy 

for FY 2022 and our responses: 

Comment: One commenter expressed 

support for our proposed adjustments to 

FY 2022 scoring and payments if the 

SNFRM is suppressed given the 

unprecedented circumstances caused by 

the PHE due to COVID–19. 

Response: We thank this commenter 

for its support. 

Comment: One commenter suggested 

an alternative of basing payment 

adjustments on performance scores from 

the FY 2021 SNF VBP Program Year. 

Response: We did consider using 

alternative performance periods for the 

FY 2022 SNF VBP Program Year, as 

noted in section VIII.B.2. of the 

proposed rule. However, we believe 

using entirely the same data (both the 

exact same performance and baseline 

period data) for both the FY 2021 and 

FY 2022 program years would provide 

no new information for SNFs or the 

public, particularly information during 

the COVID–19 PHE, and may have the 

unintended effect of mitigating 

incentives for providers to improve 

between the overlapping program years 

or unfairly rewarding or penalizing 

SNFs by repeating the FY 2021 program. 

Comment: Several commenters 

expressed concern that our proposed 

measure suppression and scoring policy 

for FY 2022 might violate sections 

1888(h)(4)(B) and 

1888(h)(5)(C)(ii)(II)(cc) of the Act, which 

state that the Secretary shall rank SNF 

performance scores from low to high, 

and for SNFs in the lowest 40 percent 

ranking, to apply a payment rate for 

services less than the payment rate that 

would otherwise apply without the SNF 

VBP Program. 

Response: As discussed in section 

VIII.D.2. of the proposed rule and this 

final rule, we proposed and are 

finalizing suppression of the SNFRM 

due to the impacts of the COVID–19 

PHE. Specifically, we have concerns 

about the validity of the measure when 

calculated as currently specified on data 

during the PHE given the significant 

changes in SNF patient case volume and 

facility-level case mix and lacking any 

viable alternatives. We stated in the 

proposed rule our belief that for 

purposes of scoring and payment 

adjustments under the SNF VBP 

Program, the SNFRM as impacted by the 

COVID–19 PHE should not be attributed 

to the participating facility positively or 

negatively. We believe that using 

SNFRM data that has been impacted by 

the PHE due to COVID–19 could result 

in performance scores that do not 

accurately reflect SNF performance for 

making national comparisons and 

ranking purposes given the variation in 

COVID–19 across different geographies 

and time periods and seen in fluctuating 

case volumes and case mix. Due to the 

SNFRM being the only quality measure 

authorized for use in the FY 2022 SNF 

VBP, suppression of the SNFRM would 

mean we would not be able to calculate 

SNF performance scores for any SNF 

nor to differentially rank SNFs. 

Therefore, we proposed to change the 

scoring methodology to assign all SNFs 

a performance score of zero and 

effectively rank all SNFs equally in the 

FY 2022 SNF VBP Program Year. 

After considering the public 

comments, we are finalizing our 

proposed special scoring policy for the 

FY 2022 program year as proposed and 

codifying it at § 413.338(g) of our 

regulations. 

F. SNF Value-Based Incentive Payments 

We refer readers to the FY 2018 SNF 

PPS final rule (82 FR 36616 through 

36621) for discussion of the exchange 

function methodology that we have 

adopted for the Program, as well as the 

specific form of the exchange function 

(logistic, or S-shaped curve) that we 

finalized, and the payback percentage of 

60 percent. We adopted these policies 

for FY 2019 and subsequent fiscal years. 

We also discussed the process that we 

undertake for reducing SNFs’ adjusted 

Federal per diem rates under the 

Medicare SNF PPS and awarding valuebased incentive payments in the FY 

2019 SNF PPS final rule (83 FR 39281 

through 39282). 

As discussed in sections VIII.B.2. and 

VIII.E of this final rule, we are finalizing 

the suppression of the SNFRM for the 

FY 2022 program year and assigning all 

SNFs a performance score of zero, 

which would result in all participating 

SNFs receiving an identical 

performance score, as well as an 

identical incentive payment multiplier. 

In the proposed rule, we proposed to 

reduce each participating SNF’s 

adjusted Federal per diem rate for FY 

2022 by 2 percentage points and to 

award each participating SNF 60 

percent of that 2 percent withhold, 

resulting in a 1.2 percent payback for 

the FY 2022 program year. We believe 

this continued application of the 2 

percent withhold is required under 

section 1888(h)(5)(C)(ii)(III) of the Act 

and that a payback percentage that is 

spread evenly across all SNFs is the 

most equitable way to reduce the impact 

of the withhold in light of our proposal 

to award a performance score of zero to 

all SNFs. We proposed that those SNFs 

subject to the Low-Volume Adjustment 

policy would receive 100 percent of 

their 2 percent withhold per the 

previously finalized policy, increasing 

the overall payback percentage to an 

estimated 62.9 percent. We proposed to 

codify this policy at § 413.338(g). 

We invited public comment on this 

proposed change to the SNF VBP 

payment policy for the FY 2022 program 

year. 

The following is a summary of the 

public comments received on the 

proposed SNF Value-Based Incentive 

Payments and our responses: 

Comment: The majority of 

commenters supported suppressing the 

SNFRM due to the COVID–19 

pandemic. However, many commenters 

expressed concern regarding the 

payment amount in the proposed 

payment policy for the FY 2022 SNF 

VBP Program Year. Several commenters 

recommended that we not reduce each 

eligible SNF’s adjusted Federal per diem 

rate by 2 percent, or that we return all 

of the 2 percent withhold to eligible 

SNFs. Several commenters also noted 

that if we must proceed with returning 

only a portion of the 2 percent 

withhold, we should return 70 percent 

of the 2 percent withhold rather than 60 

percent and that this approach would be 

reasonable and the most fair given that 

all providers will be awarded the same 

incentive payment multiplier and 

because we are not basing distribution 

on performance. One commenter 

recommended that CMS pause the 

application of SNF incentive payment 

adjustments for performance years 

impacted by the PHE. 

Response: Though we acknowledge 

that the COVID–19 PHE has had 

unprecedented impacts on SNFs, we 

believe maintaining the 60 percent 

payback percentage will best provide for 

the stability and sustainability of the 

Medicare Program, as well as the 

stability and sustainability of other 


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programs funded by the Medicare Trust 

Fund. Increasing the payback 

percentage to 70 percent would lead to 

higher SNF PPS baseline spending that 

would lower the estimated savings 

realized by the Medicare Trust Fund in 

FY 2022 by 19 percent. Specifically, we 

estimate that increasing the payback 

percentage to 70 percent would reduce 

estimated savings from $191.64 million 

to $154.85 million for that fiscal year. 

We note that the SNF VBP Program was 

designed to be a cost-saving program for 

Medicare. We refer readers to the FY 

2018 SNF PPS final rule (82 FR 36619 

through 36621) for a discussion of the 

factors we considered when we 

specified the 60 percent payback 

percentage, including a balance between 

the number of SNFs that receive a 

positive payment adjustment, the 

marginal incentives for all SNFs to 

reduce hospital readmissions and make 

broad-based care quality improvements, 

and the Medicare Program’s long-term 

sustainability. 

Regarding the recommendation to 

pause the application of SNF incentive 

payment adjustments for all 

performance years impacted by the PHE, 

we believe that the updated FY 2022 

performance period that we adopted in 

the September 2nd IFC and are 

finalizing in this final rule, as well as 

the measure suppression and special 

scoring and payment policies we are 

finalizing in this final rule, serve to 

mitigate the impact of the PHE on SNF 

VBP performance scores for the FY 

2022. Therefore, we do not believe 

further actions to the SNF VBP 

Program’s incentive payment 

adjustments would be beneficial to the 

program at this time. We are continuing 

to analyze data that may impact the FY 

2023 Program. 

Comment: One commenter 

specifically noted that this proposal to 

reduce each eligible SNF’s adjusted 

Federal per diem rate by the applicable 

2 percent and then adjust the resulting 

amounts by a value-based incentive 

payment amount equal to 60 percent of 

the total reduction ‘‘disconnects 

payment from quality,’’ and risks 

‘‘rewarding bad actors and penalizing 

good performers.’’ 

Response: We do not believe that 

assessing SNFs on a quality measure 

affected significantly by the varied 

regional response to the COVID–19 PHE 

presents a clear picture of the quality of 

care provided by an individual SNF. 

Facility-level morbidity and mortality 

data have been shown to be significantly 

and disproportionately affected by 

COVID–19 due to changes in SNF 

patient case-mix. We are concerned that 

making payment incentive adjustments 

using the scoring and payment 

methodologies specified at § 413.338(c) 

and (d) could unintentionally award 

payment incentives to SNFs whose high 

performance was driven by one or more 

COVID–19 related factors, such as low 

COVID–19 prevalence in their locale, 

lower SNF admissions because of 

changes in health care patterns, or 

higher rates of mortality because of 

conditions related to COVID–19, rather 

than due to better performance. 

Comment: One commenter 

encouraged CMS to consider 

modifications to statutory language for 

situations such as the PHE due to 

COVID–19 where the Administration 

could hold participating SNFs harmless. 

Response: We thank the commenter 

for its suggestion and we will take it 

under consideration. 

Comment: One commenter suggested 

that in addition to the policy we 

proposed, we should also exclude 

COVID–19 diagnosed patients from the 

eligible case count, which would lead to 

additional SNFs having insufficient 

numbers of cases and thus receiving a 

low-volume adjustment rather than a 

penalty. One commenter questioned 

whether the 25 or more eligible stay 

requirement for applying the lowvolume adjustment policy is appropriate 

given the impacts of COVID–19 on SNF 

residents and facilities and suggested 

that CMS eliminate all payment cuts for 

FY 2022. 

Response: We do not agree with the 

commenter’s suggestion to exclude 

COVID–19 diagnosed patients from the 

SNFRM eligible case count for the FY 

2022 program year. As explained above, 

we believe that our proposal to suppress 

the SNFRM for FY 2022 scoring and 

payment adjustment purposes 

appropriately mitigates the effects of the 

PHE due to COVID–19. Additionally, 

excluding COVID–19 diagnosed patients 

from the eligible case count would 

negatively affect the Program’s impact 

on the Medicare Trust Fund because it 

would increase the number of SNFs 

eligible for the Low-Volume Adjustment 

policy who receive a net-neutral 

incentive payment multiplier. 

As further detailed below, we believe 

that the minimum of 25 eligible stays for 

the performance period as a threshold 

for applying the Low-Volume 

Adjustment policy is appropriate and 

important to maintain for FY 2022, even 

though we are suppressing the SNFRM 

measure for scoring and payment 

adjustment purposes. As noted 

previously, eliminating all payment cuts 

for the FY 2022 program year would 

threaten the stability and maintenance 

of the SNF VBP Program. We note that 

while this program is designed to be a 

cost-savings program, during the 

COVID–19 PHE, smaller SNFs (those 

with 45 or fewer eligible stays) and a 

disproportionate number of rural SNFs 

have been more vulnerable to 

unexpected changes in payment or 

policy as compared to larger SNFs. For 

the FY 2022 program, we are seeking in 

particular to protect small and rural 

SNFs from unexpected or adverse 

impacts of policies and not applying the 

LVA would result in those SNFs 

receiving a deduction when they 

otherwise would not have. Specifically, 

when we estimated the impact of the 

LVA in the upcoming FY 2022 program 

year, we found that, overall 28 percent 

of SNFs qualified for the LVA 

(including 43 percent of all rural SNFs 

and only 22 percent of all urban SNFs). 

In comparison to a standard program 

year, 17 percent of all SNFs would 

receive the LVA (28.2 percent rural and 

12.8 percent urban). 

After considering the public 

comments, we are finalizing our 

proposed special payment policy for the 

FY 2022 program year as proposed and 

codifying it at § 413.338(g) of our 

regulations. 

G. Public Reporting on the Nursing 

Home Compare Website or a Successor 

Website 

1. Background 

Section 1888(g)(6) of the Act requires 

the Secretary to establish procedures to 

make SNFs’ performance information on 

SNF VBP Program measures available to 

the public on the Nursing Home 

Compare website or a successor website, 

and to provide SNFs an opportunity to 

review and submit corrections to that 

information prior to its publication. We 

began publishing SNFs’ performance 

information on the SNFRM in 

accordance with this directive and the 

statutory deadline of October 1, 2017. In 

December 2020, we retired the Nursing 

Home Compare website and are now 

using the Provider Data Catalogue 

website (https://data.cms.gov/providerdata/) to make quality data available to 

the public, including SNF VBP 

performance information. 

Additionally, section 1888(h)(9)(A) of 

the Act requires the Secretary to make 

available to the public certain 

information on SNFs’ performance 

under the SNF VBP Program, including 

SNF performance scores and their 

ranking. Section 1888(h)(9)(B) of the Act 

requires the Secretary to post aggregate 

information on the Program, including 

the range of SNF performance scores 

and the number of SNFs receiving 

value-based incentive payments, and 


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the range and total amount of those 

payments. 

In the FY 2017 SNF PPS final rule (81 

FR 52009), we discussed the statutory 

requirements governing public reporting 

of SNFs’ performance information under 

the SNF VBP Program. In the FY 2018 

SNF PPS final rule (82 FR 36622 

through 36623), we finalized our policy 

to publish SNF VBP Program 

performance information on the Nursing 

Home Compare or successor website 

after SNFs have had an opportunity to 

review and submit corrections to that 

information under the two-phase 

Review and Correction process that we 

adopted in the FY 2017 SNF PPS final 

rule (81 FR 52007 through 52009) and 

for which we adopted additional 

requirements in the FY 2018 SNF PPS 

final rule. In the FY 2018 SNF PPS final 

rule, we also adopted requirements to 

rank SNFs and adopted data elements 

that we will include in the ranking to 

provide consumers and stakeholders 

with the necessary information to 

evaluate SNFs’ performance under the 

Program (82 FR 36623). 

As discussed in section VIII.B.2. of 

this final rule, we are finalizing the 

suppression of the SNFRM for the FY 

2022 program year due to the impacts of 

the PHE for COVID–19. Under this 

finalized proposal, for all SNFs 

participating in the FY 2022 SNF VBP 

Program, we will use the performance 

period we adopted in the September 

2nd IFC and are finalizing in this final 

rule, as well as the previously finalized 

baseline period to calculate each SNF’s 

RSRR for the SNFRM. We are also 

finalizing our proposal to assign all 

SNFs a performance score of zero. This 

will result in all participating SNFs 

receiving an identical performance 

score, as well as an identical incentive 

payment multiplier. Further, we are 

finalizing our proposal to apply the 

Low-Volume Adjustment policy as 

previously finalized in the FY 2019 SNF 

PPS final rule (83 FR 39278 through 

39280). That is, if a SNF has fewer than 

25 eligible stays during the performance 

period for a program year, we will 

assign that SNF a performance score 

resulting in a net-neutral payment 

incentive multiplier. 

While we will publicly report the 

SNFRM rates for the FY 2022 program 

year, we will make clear in the public 

presentation of those data that we are 

suppressing the use of those data for 

purposes of scoring and payment 

adjustments in the FY 2022 SNF VBP 

Program given the significant changes in 

SNF patient case volume and facilitylevel case mix described above. Under 

our finalized policy, SNFs will not be 

ranked for the FY 2022 SNF VBP 

Program. 

2. Data Suppression Policy for LowVolume SNFs 

In the FY 2020 SNF PPS final rule (84 

FR 38823 through 38824), we adopted a 

data suppression policy for low-volume 

SNF performance information. 

Specifically, we finalized that we will 

suppress the SNF performance 

information available to display as 

follows: (1) If a SNF has fewer than 25 

eligible stays during the baseline period 

for a program year, we will not display 

the baseline risk-standardized 

readmission rate (RSRR) or 

improvement score, although we will 

still display the performance period 

RSRR, achievement score, and total 

performance score if the SNF had 

sufficient data during the performance 

period; (2) if a SNF has fewer than 25 

eligible stays during the performance 

period for a program year and receives 

an assigned SNF performance score as a 

result, we will report the assigned SNF 

performance score and we will not 

display the performance period RSRR, 

the achievement score, or improvement 

score; and (3) if a SNF has zero eligible 

cases during the performance period for 

a program year, we will not display any 

information for that SNF. We codified 

this policy in the FY 2021 SNF PPS 

final rule (85 FR 47626) at 

§ 413.338(e)(3)(i), (ii), and (iii). 

As discussed in section VIII.B.2. of 

this final rule, we are finalizing the 

suppression of the SNFRM for the FY 

2022 program year and our proposals for 

scoring and payment in FY 2022, 

including applying the Low-Volume 

Adjustment policy as previously 

finalized. That is, if a SNF has fewer 

than 25 eligible stays during the 

performance period for FY 2022 (April 

1, 2019 through December 31, 2019 and 

July 1, 2020 through September 30, 

2020), we will assign that SNF a 

performance score resulting in a netneutral payment incentive multiplier. 

3. Public Reporting of SNF VBP 

Performance Information on Nursing 

Home Compare or a Successor Website 

Section 1888(h)(9)(A) of the Act 

requires that the Secretary make 

available to the public on the Nursing 

Home Compare website or a successor 

website information regarding the 

performance of individual SNFs for a 

fiscal year, including the performance 

score for each SNF for the fiscal year 

and each SNF’s ranking, as determined 

under section 1888(h)(4)(B) of the Act. 

Additionally, section 1888(h)(9)(B) of 

the Act requires that the Secretary 

periodically post aggregate information 

on the SNF VBP Program on the Nursing 

Home Compare website or a successor 

website, including the range of SNF 

performance scores, and the number of 

SNFs receiving value-based incentive 

payments and the range and total 

amount of those payments. In the FY 

2018 SNF PPS final rule (82 FR 36622 

through 36623), we finalized our policy 

to publish SNF measure performance 

information under the SNF VBP 

Program on Nursing Home Compare. 

In the FY 2021 SNF PPS final rule (85 

FR 47626), we finalized an amendment 

to § 413.338(e)(3) to reflect that we will 

publicly report SNF performance 

information on the Nursing Home 

Compare website or a successor website 

located at https://data.cms.gov/ 

provider-data//. We did not propose any 

changes to the public reporting policies 

in the proposed rule. 

H. Update and Codification of the Phase 

One Review and Correction Claims 

‘‘Snapshot’’ Policy 

In the FY 2017 SNF PPS final rule (81 

FR 52007 through 52009), we adopted a 

two-phase review and corrections 

process for SNFs’ quality measure data 

that will be made public under section 

1888(g)(6) of the Act and SNF 

performance information that will be 

made public under section 1888(h)(9) of 

the Act. We detailed the process for 

requesting Phase One corrections and 

finalized a policy whereby we would 

accept Phase One corrections to a 

quarterly report provided during a 

calendar year until the following March 

31. 

In the FY 2020 SNF PPS final rule (84 

FR 38824 through 38835), we updated 

this policy to reflect a 30-day Phase One 

Review and Correction deadline rather 

than through March 31st following 

receipt of the performance period 

quality measure quarterly report. 

In the FY 2021 SNF PPS final rule (85 

FR 47626 through 47627), we updated 

the 30-day deadline for Phase One 

Review and Correction and codified the 

policy at § 413.338(e)(1). Under the 

updated policy, beginning with the 

baseline period quality report issued on 

or after October 1, 2020 that contains 

the baseline period measure rate and 

underlying claim information used to 

calculate the measure rate for the 

applicable program year, SNFs have 30 

days following the date that CMS 

provides those reports to review and 

submit corrections to the data contained 

in those reports. We also stated that if 

the issuance dates of these reports are 

significantly delayed or need to be 

shifted for any reason, we would notify 

SNFs through routine communication 

channels including, but not limited to 


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memos, emails, and notices on the CMS 

SNF VBP website at https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Value-Based-Programs/ 

SNF-VBP/SNF-VBP-Page. 

We proposed to include a Phase One 

Review and Correction claims 

‘‘snapshot’’ policy beginning with the 

baseline period and performance period 

quality measure quarterly reports issued 

on or after October 1, 2021. This 

proposed policy would limit the Phase 

One Review and Correction to errors 

made by CMS or its contractors when 

calculating a SNF’s readmission 

measure rate and would not allow 

corrections to the underlying 

administrative claims data used to 

calculate those rates. Under this 

proposed policy, the administrative 

claims data we use to calculate a SNF’s 

readmission measure rate for purposes 

of a baseline period or performance 

period for a given SNF VBP Program 

Year would be held constant (that is, 

frozen in a ‘‘snapshot’’) from the time 

we extract it for that purpose. This 

proposal would align the review and 

correction policy for the SNF VBP 

Program with the review and correction 

policy we have adopted for other valuebased purchasing programs, including 

the Hospital Readmissions Reduction 

Program (HRRP), Hospital-Acquired 

Condition (HAC) Reduction Program, 

and Hospital VBP Program. 

For purposes of this program, we 

proposed to calculate the SNF 

readmission measure rates using a static 

‘‘snapshot’’ of claims updated as of 3 

months following the last index SNF 

admission in the applicable baseline 

period or performance period. The 

source of the administrative claims data 

we use to calculate the SNF readmission 

measure is the Medicare Provider 

Analysis and Review (MedPAR). For 

example, if the last index SNF 

admission date for the applicable 

baseline period or performance period is 

September 30, 2019, we would extract 

the administrative claims data from the 

MedPAR file as that data exists on 

December 31, 2019. SNFs would then 

receive their SNF readmission measure 

rate and accompanying stay-level 

information in their confidential quality 

measure quarterly reports, and they 

would have an opportunity to review 

and submit corrections to our 

calculations as part of the Phase One 

corrections process. However, SNFs 

would not be able to correct any of the 

underlying administrative claims data 

(for example, a SNF discharge 

destination code) we use to generate the 

measure rate. 

The use of a data ‘‘snapshot’’ enables 

us to provide as timely quality data as 

possible, both to SNFs for the purpose 

of quality improvement and to the 

public for the purpose of transparency. 

After the claims ‘‘snapshot’’ is taken 

through our extraction of the data from 

MedPAR, it takes several months to 

incorporate other data needed for the 

SNF readmission measure calculations, 

generate and check the calculations, as 

well as program, populate, and deliver 

the confidential quarterly reports and 

accompanying data to SNFs. Because 

several months lead-time is necessary 

after acquiring the input data to generate 

these calculations, if we were to delay 

our data extraction point beyond the 

date that is 3 months after the last SNF 

index admission attributable to a 

baseline period or performance period, 

we believe this would create an 

unacceptably long delay both for SNFs 

to receive timely data for quality 

improvement and transparency, and, 

incentive payments for purposes of this 

program. Therefore, we believe that a 3- 

month claims ‘‘run-out’’ period between 

the date of the last SNF index admission 

and the date of the data extraction is a 

reasonable period that allows SNFs time 

to correct their administrative claims or 

add any missing claims before those 

claims are used for measure calculation 

purposes while enabling us to timely 

calculate the measure. If unforeseen 

circumstances require the use of 

additional months of claims ‘‘run-out’’, 

that is, more than 3 months, we would 

notify SNFs through routine 

communication channels including, but 

not limited to, memos, emails, quarterly 

reports and notices on the CMS SNF 

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

Medicare/Quality-Initiatives-PatientAssessment-Instruments/Value-BasedPrograms/SNF-VBP/SNF-VBP-Page. 

We believe this proposed policy 

would address both fairness and 

operational concerns associated with 

calculating measure rates and would 

provide consistency across value-based 

purchasing programs. 

We also proposed to codify this policy 

in our regulations by revising 

§ 413.338(e)(1) to remove the policies 

that would no longer be applicable 

beginning October 1, 2021 and state the 

newly proposed policy that would be 

effective, if finalized, on October 1, 

2021. 

We invited public comment on this 

proposal to update the Phase One 

Review and Correction policy. 

The following is a summary of the 

public comments received on our 

proposal to Update and Codify the 

Phase One Review and Correction 

Claims ‘‘Snapshot’’ Policy and our 

responses: 

Comment: A few commenters 

supported updating the Phase One 

Review and Corrections policy to align 

with the review and corrections policy 

in other value-based purchasing 

programs. 

Response: We thank the commenters 

for their support. 

After considering the comments, we 

are finalizing the updated Phase One 

Review and Corrections claims 

‘‘snapshot’’ policy as proposed and 

codifying it at § 413.338(e)(1) of our 

regulations. 

I. Update to the Instructions for 

Requesting an ECE in § 413.338(d)(4)(ii) 

of the SNF VBP Regulations 

We proposed to update the 

instructions for a SNF to request an 

extraordinary circumstances exception 

(ECE). Specifically, we proposed to 

update the URL for our QualityNet 

website from QualityNet.org to 

QualityNet.cms.gov. We also proposed 

to update the email address that a SNF 

must use to send an ECE request. We 

also proposed to remove the separate 

reference to newspapers because 

newspapers are already included in the 

broader term ‘‘media articles.’’ We 

proposed to update § 413.338(d)(4)(ii) of 

our regulations to reflect these changes. 

We invited public comment on this 

proposal. 

The following is a summary of the 

public comments received on our 

proposal to Update the Instructions for 

Requesting an ECE in § 413.338(d)(4)(ii) 

of the SNF VBP Regulations and our 

responses: 

Comment: A few commenters 

supported our proposal to update the 

instructions to request an ECE in the 

SNF VBP regulations. 

Response: We thank these 

commenters for their support. 

After considering the public 

comments, we are finalizing our 

proposal to update the instructions for 

requesting an ECE in the SNF VBP 

regulations and codifying it at 

§ 413.338(d)(4)(ii) of our regulations. 

However, due to operational concerns, 

we are updating the regulation text to 

specify that a SNF may request an 

exception in the form and manner 

specified by CMS on the SNF VBP 

website, which will include the 

appropriate email address to which a 

SNF can send its ECE request. 

IX. Technical Correction for § 483.90(d) 

In the July 18, 2019 ‘‘Medicare and 

Medicaid Programs; Requirements for 

Long-Term Care Facilities: Regulatory 

Provisions To Promote Efficiency, and 


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118Section 321 of the 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. 

Transparency’’ proposed rule, we 

proposed a technical correction to revise 

§ 483.90(d)(1) and add paragraph (d)(3) 

to correct an error in the Code of Federal 

Regulations (CFR) (84 FR 34737). 

Previously, on July 13, 2017, we 

issued a correcting amendment entitled, 

‘‘Medicare and Medicaid Programs; 

Reform of Requirements for Long-Term 

Care Facilities’’ correcting amendment 

(82 FR 32256) to correct technical and 

typographical errors identified in the 

October 2016 ’’Medicare and Medicaid 

Programs; Reform of Requirements for 

Long-Term Care Facilities’’ final rule (81 

FR 68688). This document inadvertently 

removed revisions made to § 483.90(d), 

which were finalized in the October 

2016 final rule. Specifically, the rule 

finalized requirements at § 483.90(d) 

(incorrectly labeled paragraph (c) in the 

October 2016 final rule) for facilities 

to—(1) provide sufficient space and 

equipment in dining, health services, 

recreation, living, and program areas to 

enable staff to provide residents with 

needed services as required by these 

standards and as identified in each 

resident’s assessment and plan of care at 

§ 483.90(d)(1)); (2) maintain all 

mechanical, electrical, and patient care 

equipment in safe operating condition at 

§ 483.90(d)(2); and (3) conduct regular 

inspection of all bed frames, mattresses, 

and bed rails, if any, as part of a regular 

maintenance program to identify areas 

of possible entrapment. When bed rails 

and mattresses are used and purchased 

separately from the bed frame, the 

facility must ensure that the bed rails, 

mattress, and bed frame are compatible 

at § 483.90(d)(3). 

We did not receive comments in 

response to this proposal. Therefore, we 

are finalizing this technical correction, 

as proposed, to revise § 483.90(d)(1) and 

add paragraph (d)(3). 

X. Collection of Information 

Requirements 

Consistent with our April 15, 2021 (86 

FR 19954) proposed rule, this final rule 

will not impose any new or revised 

‘‘collection of information’’ 

requirements or burden as it pertains to 

CMS. For the purpose of this section of 

the preamble, collection of information 

is defined under 5 CFR 1320.3(c) of the 

Paperwork Reduction Act of 1995’s 

(PRA) (44 U.S.C. 3501 et seq.) 

implementing regulations. 

Consequently, this rule is not subject to 

the requirements of the PRA. 

In section VII.C.1. of this final rule, 

we are finalizing the adoption of the 

SNF HAIs Requiring Hospitalization 

measure beginning with the FY 2023 

SNF QRP. The measure is claims-based. 

All claims-based measures are 

calculated using data that are already 

reported to the Medicare program for 

payment purposes. Since the data 

source for this measure is Medicare feefor-service claims, there is no additional 

burden for SNFs. 

In section VII.C.2. of this final rule, 

we are finalizing the adoption of the 

COVID–19 Vaccination Coverage among 

Healthcare Personnel (HCP) measure 

beginning with the FY 2023 SNF QRP. 

SNFs must submit data on the measure 

through the CDC/National Healthcare 

Safety Network (NHSN). We note that 

the CDC will account for the burden 

associated with the COVID–19 

Vaccination Coverage among HCP 

measure collection under OMB control 

number 0920–1317 (current expiration 

January 31, 2024). However, the CDC 

currently has a PRA waiver for the 

collection and reporting of vaccination 

data under section 321 of the National 

Childhood Vaccine Injury Act of 1986 

(Pub. L. 99–660, enacted on November 

14, 1986) (NCVIA).118 We refer readers 

to section XI.A.5. of this final rule for 

an estimate of the burden to SNFs, and 

note that the CDC will include it in a 

revised information collection request 

under said control number. 

In section VII.C.3. of this final rule, 

we are finalizing our proposal to update 

the Transfer of Health (TOH) 

Information to the Patient—Post Acute 

Care (PAC) measure to exclude residents 

discharged home under the care of an 

organized home health service or 

hospice. This measure was adopted in 

the FY 2020 SNF PPS final rule (84 FR 

38728) and the associated burden was 

accounted for under OMB control 

number 0938–1140 (CMS–10387) 

(current expiration November 30, 2022). 

The update will not affect the 

requirements and burden that are 

currently approved under that control 

number. 

In section VII.G.3. of this final rule, 

we are finalizing our proposal that SNFs 

submit data on the COVID–19 

Vaccination among HCP measure 

through the CDC/National Healthcare 

Safety Network (NHSN). The NHSN is a 

secure, internet-based surveillance 

system that is maintained by the CDC 

and provided free of charge to 

healthcare facilities including SNFs. 

While the NHSN is currently not 

utilized by SNFs for purposes of 

meeting the SNF QRP requirements, 

nursing homes were enrolled in the 

NHSN in 2020 and are currently 

submitting mandatory COVID–19 data 

through the Long-term Care Facility 

COVID–19 module (https://

www.cdc.gov/nhsn/ltc/covid19/ 

index.html). As such, there is no 

additional information collection 

burden related to the onboarding and 

training of SNF providers to utilize this 

system. 

In section VIII.B.2. of this final rule, 

we are finalizing our proposal to 

suppress the Skilled Nursing Facility 

30-Day All-Cause Readmission Measure 

(SNFRM) for scoring and payment 

purposes for the FY 2022 SNF VBP 

Program Year. Because the data source 

for this quality measure is Medicare feefor-service claims, there is no additional 

burden for SNFs. All claims-based 

measures can be calculated based on 

data that are already reported to the 

Medicare program for payment 

purposes. 

XI. Economic Analyses 

A. Regulatory Impact Analysis 

1. Statement of Need 

This final rule updates the FY 2022 

SNF prospective payment rates as 

required under section 1888(e)(4)(E) of 

the Act. It also responds to section 

1888(e)(4)(H) of the Act, which requires 

the Secretary to provide for publication 

in the Federal Register before the 

August 1 that precedes the start of each 

FY, the unadjusted Federal per diem 

rates, the case-mix classification system, 

and the factors to be applied in making 

the area wage adjustment. As these 

statutory provisions prescribe a detailed 

methodology for calculating and 

disseminating payment rates under the 

SNF PPS, we do not have the discretion 

to adopt an alternative approach on 

these issues. 

2. Introduction 

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 Act, section 202 of the Unfunded 

Mandates Reform Act of 1995 (UMRA, 

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 


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(including potential economic, 

environmental, public health and safety 

effects, distributive impacts, and 

equity). Executive Order 13563 

emphasizes the importance of 

quantifying both costs and benefits, of 

reducing costs, of harmonizing rules, 

and of promoting flexibility. This rule 

has been designated an economically 

significant rule, under section 3(f)(1) of 

Executive Order 12866. Accordingly, we 

have prepared a regulatory impact 

analysis (RIA) as further discussed 

below. Also, the rule has been reviewed 

by OMB. 

3. Overall Impacts 

This rule updates the SNF PPS rates 

contained in the SNF PPS final rule for 

FY 2021 (85 FR 47594). We estimate 

that the aggregate impact would be an 

increase of approximately $410 million 

in Part A payments to SNFs in FY 2022. 

This reflects a $411 million increase 

from the update to the payment rates 

and a $1.2 million decrease due to the 

proposed reduction to the SNF PPS 

rates to account for the recently 

excluded blood-clotting factors (and 

items and services related to the 

furnishing of such factors) in section 

1888(e)(2)(A)(iii)(VI) of the Act. We note 

that these impact numbers do not 

incorporate the SNF VBP Program 

reductions that we estimate would total 

$191.64 million in FY 2022. We would 

note that events may occur to limit the 

scope or accuracy of our impact 

analysis, as this analysis is futureoriented, and thus, very susceptible to 

forecasting errors due to events that may 

occur within the assessed impact time 

period. 

In accordance with sections 

1888(e)(4)(E) and (e)(5) of the Act and 

implementing regulations at 

§ 413.337(d), we are updating the FY 

2021 payment rates by a factor equal to 

the market basket index percentage 

change reduced by the forecast error 

adjustment and the productivity 

adjustment to determine the payment 

rates for FY 2022. The impact to 

Medicare is included in the total 

column of Table 32. When proposing 

the SNF PPS rates for FY 2022, we 

proposed a number of standard annual 

revisions and clarifications mentioned 

elsewhere in this final rule (for example, 

the proposed update to the wage and 

market basket indexes used for adjusting 

the Federal rates). 

The annual update in this rule applies 

to SNF PPS payments in FY 2022. 

Accordingly, the analysis of the impact 

of the annual update that follows only 

describes the impact of this single year. 

Furthermore, in accordance with the 

requirements of the Act, we will publish 

a rule or notice for each subsequent FY 

that will provide for an update to the 

payment rates and include an associated 

impact analysis. 

4. Detailed Economic Analysis 

The FY 2022 SNF PPS payment 

impacts appear in Table 32. Using the 

most recently available data, in this case 

FY 2020, we apply the current FY 2021 

CMIs, wage index and labor-related 

share value to the number of payment 

days to simulate FY 2021 payments. 

Then, using the same FY 2020 data, we 

apply the FY 2022 CMIs, wage index 

and labor-related share value to 

simulate FY 2022 payments. We would 

note that, given that this same data is 

being used for both parts of this 

calculation, as compared to other 

analyses discussed in this final rule 

which compare data from FY 2020 to 

data from other fiscal years, any issues 

discussed throughout this final rule 

with regard to data collected in FY 2020 

will not cause any difference in this 

economic analysis. We tabulate the 

resulting payments according to the 

classifications in Table 32 (for example, 

facility type, geographic region, facility 

ownership), and compare the simulated 

FY 2021 payments to the simulated FY 

2022 payments to determine the overall 

impact. The breakdown of the various 

categories of data in Table 32 follows: 

• The first column shows the 

breakdown of all SNFs by urban or rural 

status, hospital-based or freestanding 

status, census region, and ownership. 

• The first row of figures describes 

the estimated effects of the various 

proposed changes on all facilities. The 

next six rows show the effects on 

facilities split by hospital-based, 

freestanding, urban, and rural 

categories. The next nineteen rows show 

the effects on facilities by urban versus 

rural status by census region. The last 

three rows show the effects on facilities 

by ownership (that is, government, 

profit, and non-profit status). 

• The second column shows the 

number of facilities in the impact 

database. 

• The third column shows the effect 

of the proposed annual update to the 

wage index. This represents the effect of 

using the most recent wage data 

available. The total impact of this 

change is 0.0 percent; however, there 

are distributional effects of the proposed 

change. 

• The fourth column shows the effect 

of all of the changes on the FY 2022 

payments. The update of 1.2 percent is 

constant for all providers and, though 

not shown individually, is included in 

the total column. It is projected that 

aggregate payments would increase by 

1.2 percent, assuming facilities do not 

change their care delivery and billing 

practices in response. 

As illustrated in Table 32, the 

combined effects of all of the changes 

vary by specific types of providers and 

by location. For example, due to 

changes in this final rule, rural 

providers would experience a 1.6 

percent increase in FY 2022 total 

payments. Finally, we note that we did 

not include in Table 32 the 

distributional impacts associated with 

the blood-clotting factor exclusion 

because the reduction is so minor that 

it does not have any visible effect on the 

distributional impacts included in the 

Table 32. 

BILLING CODE 4120–01–P 


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5. Impacts for the SNF QRP for FY 2022 

Estimated impacts for the SNF QRP 

are based on analysis discussed in 

section IX.B. of this final rule. The SNF 

QRP requirements add no additional 

burden to the active collection under 

OMB control number #0938–1140 

(CMS–10387; expiration November 30, 

2022). 

In accordance with section 

1888(e)(6)(A)(i) of the Act, the Secretary 

must reduce by 2 percentage points the 

annual payment update applicable to a 

SNF for a fiscal year if the SNF does not 

comply with the requirements of the 

SNF QRP for that fiscal year. In section 

VII.A. of this final rule, we discuss the 

method for applying the 2 percentage 

point reduction to SNFs that fail to meet 

the SNF QRP requirements. As 

discussed in section VII.C. of this final 

rule, we are finalizing the adoption of 

two new measures to the SNF QRP 

beginning with the FY 2023 SNF QRP: 

SNF Healthcare-Associated Infections 

Requiring Hospitalization Measure 

(SNF–HAI) and the COVID–19 

Vaccination Coverage among Healthcare 

Personnel (HCP) measure. The SNF– 

HAI measure is a claims-based measure, 

and therefore, would impose no 

additional burden to the SNFs. 

We believe that the burden associated 

with the SNF QRP is the time and effort 

associated with complying with the 

non-claims-based measures 

requirements of the SNF QRP. Although 

the burden associated with the COVID– 

19 Vaccination Coverage among HCP 

measure is not accounted for under the 

CDC PRA package currently approved 

under OMB control number 0920–1317 

due to the NCVIA waiver the cost and 

burden is discussed here and will be 

included in a revised information 

collection request for 0920–1317. 

Consistent with the CDC’s experience 

of collecting data using the NHSN, we 

estimate that it would take each SNF an 

average of 1 hour per month to collect 

data for the COVID–19 Vaccination 


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TABLE 32: Impact to the SNF PPS for FY 2022 

Provider Characteristics # Providers u date Wa e Data Total Chan e 

Grou 

Total 15,560 0.0% 1.2% 

Urban 10,962 -0.1% 1.1% 

Rural 4,598 0.4% 1.6% 

Hos ital-based urban 401 -0.1% 1.1% 

Freestandin urban 10,561 -0.1% 1.1% 

Hos ital-based rural 466 0.4% 1.6% 

1.6% 

New 744 -0.7% 0.5% 

Middle Atlantic 1,456 -0.5% 0.7% 

South Atlantic 1,834 0.3% 1.5% 

East North Central 2,160 -0.2% 1.0% 

East South Central 542 -0.1% 1.1% 

West North Central 924 0.3% 1.5% 

West South Central 1,363 -0.2% 0.9% 

Mountain 539 0.2% 1.4% 

1,394 0.2% 1.4% 

6 0.4% 1.6% 

ion 

New 130 -1.0% 0.2% 

Middle Atlantic 246 0.6% 1.8% 

South Atlantic 604 1.4% 2.6% 

East North Central 921 0.5% 1.7% 

East South Central 528 0.0% 1.2% 

West North Central 1,064 -0.4% 0.8% 

West South Central 769 0.3% 1.5% 

Mountain 224 0.5% 1.7% 

Pacific 112 0.2% 1.4% 

10866 0.0% 1.2% 

3,687 0.0% 1.2% 

Government 1,007 0.1% 1.3% 

Note: The Total column includes the FY 2022 1.2 percent market basket update factor. 

Additionally, we found no SNFs in rural outlying areas. 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42521 

119https://www.bls.gov/oes/current/oes_nat.htm. 

Accessed on March 30, 2021. 

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. We 

believe it would take an administrative 

assistant from 45 minutes up to 1 hour 

and 15 minutes to enter this data into 

NHSN. For the purposes of calculating 

the costs associated with the collection 

of information requirements, we 

obtained mean hourly wages from the 

U.S. Bureau of Labor Statistics’ May 

2019 National Occupational 

Employment and Wage Estimates.119 To 

account for overhead and fringe 

benefits, we have doubled the hourly 

wage. These amounts are detailed in 

Table 33. 

BILLING CODE 4120–01–C 

Based on this time range, it would 

cost each SNF between $27.47 and 

$45.78 each month or an average cost of 

$36.62 each month, and between 

$329.64 and $549.36 each year, or an 

average cost of $439.44 each year. We 

believe the data submission for the 

COVID–19 Vaccination Coverage among 

HCP measure would cause SNFs to 

incur additional average burden of 12 

hours per year for each SNF and a total 

annual burden of 180,936 hours for all 

SNFs. The estimated annual cost across 

all 15,078 SNFs in the U.S. for the 

submission of the COVID–19 

Vaccination Coverage among HCP 

measure would be between $4,970,312 

and $8,283,250.08, and an average of 

$6,625,872. 

We recognize that many SNFs may 

also be reporting other COVID–19 data 

to HHS. However, we believe the 

benefits of reporting data on the 

COVID–19 Vaccination Coverage among 

HCP measure to assess whether SNFs 

are taking steps to limit the spread of 

COVID–19 among their HCP, reduce the 

risk of transmission of COVID–19 

within their facilities, and to help 

sustain the ability of SNFs to continue 

serving their communities throughout 

the PHE and beyond outweigh the costs 

of reporting. We welcomed comments 

on the estimated time to collect data and 

enter it into NHSN. 

We did not receive any comments on 

the estimated time to collect data and 

enter it into NHSN, and are finalizing 

the revisions as proposed. 

6. Impacts for the SNF VBP Program 

The estimated impacts of the FY 2022 

SNF VBP Program are based on 

historical data from February 1, 2019 to 

September 30, 2019. In section VIII.B.2. 

of this final rule, we discuss the 

suppression of the SNFRM for the FY 

2022 program year. As finalized, we will 

award each participating SNF 60 

percent of their 2 percent withhold, 

except those SNFs subject to the lowvolume scoring adjustment, which 

would each receive 100 percent of their 

2 percent withhold. We estimated that 

the low-volume scoring adjustment 

would increase the 60 percent payback 

percentage for FY 2022 by 

approximately 2.9 percentage points (or 

$14.8 million), resulting in a payback 

percentage for FY 2022 that is 62.9 

percent of the estimated $516.2 million 

in withheld funds for that fiscal year. 

Based on the 60 percent payback 

percentage (as modified by the lowvolume scoring adjustment), we 

estimated that we will redistribute 

approximately $324.5 million in valuebased incentive payments to SNFs in FY 

2022, which means that the SNF VBP 

Program is estimated to result in 

approximately $191.6 million in savings 

to the Medicare Program in FY 2022. 

7. Impacts for Long Term Care Facilities: 

Physical Environment Requirements 

Technical Correction 

There are no impacts associated with 

this technical correction. 

8. Alternatives Considered 

As described in this section, we 

estimated that the aggregate impact for 

FY 2022 under the SNF PPS would be 

an increase of approximately $410 

million in Part A payments to SNFs. 

This reflects a $411 million increase 

from the update to the payment rates, 

and a $1.2 million decrease due to the 

proposed reduction to the SNF PPS 

rates to account for the recently 

excluded blood-clotting factors (and 

items and services related to the 

furnishing of such factors) in section 

1888(e)(2)(A)(iii)(VI) of the Act. 

Section 1888(e) of the Act establishes 

the SNF PPS for the payment of 

Medicare SNF services for cost reporting 

periods beginning on or after July 1, 

1998. This section of the statute 

prescribes a detailed formula for 

calculating base payment rates under 

the SNF PPS, and does not provide for 

the use of any alternative methodology. 

It specifies that the base year cost data 

to be used for computing the SNF PPS 

payment rates must be from FY 1995 

(October 1, 1994, through September 30, 

1995). In accordance with the statute, 

we also incorporated a number of 

elements into the SNF PPS (for example, 

case-mix classification methodology, a 

market basket index, a wage index, and 

the urban and rural distinction used in 

the development or adjustment of the 

Federal rates). Further, section 

1888(e)(4)(H) of the Act specifically 

requires us to disseminate the payment 

rates for each new FY through the 

Federal Register, and to do so before the 

August 1 that precedes the start of the 

new FY; accordingly, we are not 

pursuing alternatives for this process. 

With regard to the alternatives 

considered related to the other 

provisions contained in this final rule, 

such as the methodology for calculating 

the proportional reduction to the rates 

to account for the exclusion of blood 

clotting factors from SNF consolidated 

billing, we discuss any alternatives 

considered within those sections. 

With regard to the SNF VBP Program 

measure suppression policy, we discuss 

alternatives considered within those 

sections. 

9. Accounting Statement 

As required by OMB Circular A–4 

(available online at https://

obamawhitehouse.archives.gov/omb/ 

circulars_a004_a-4/), in Tables 34, 35, 

and 36, we have prepared an accounting 


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TABLE 33: U.S. Bureau of Labor and Statistics' May 2019 National Occupational 

E 1 mp oymen t an dW ai?;e Ef s 1ma t es 

Occupation title Occupation Mean Hourly Wage Overhead and Fringe Adjusted Hourly 

code ($/hr) Benefit ($/hr) Wage ($/hr) 

Administrative 43-6013 $18.31 $18.31 $36.62 

Assistant 
42522 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

statement showing the classification of 

the expenditures associated with the 

provisions of this final rule for FY 2022. 

Tables 32 and 34 provide our best 

estimate of the possible changes in 

Medicare payments under the SNF PPS 

as a result of the policies in this final 

rule, based on the data for 15,560 SNFs 

in our database. Table 35 provides our 

best estimate of the possible changes in 

Medicare payments under the SNF VBP 

as a result of the policies we have 

proposed for this program. Tables 33 

and 36 provide our best estimate of the 

additional cost to SNFs to submit the 

data for the SNF QRP as a result of the 

policies in this final rule. 

BILLING CODE 4210–01–P 

BILLING CODE 4120–01–C 

10. Conclusion 

This rule updates the SNF PPS rates 

contained in the SNF PPS final rule for 

FY 2021 (85 FR 47594). Based on the 

above, we estimate that the overall 

payments for SNFs under the SNF PPS 

in FY 2022 are projected to increase by 

approximately $410 million, or 1.2 

percent, compared with those in FY 

2021. We estimate that in FY 2022, 

SNFs in urban and rural areas would 

experience, on average, a 1.1 percent 

increase and 1.0036 percent increase, 

respectively, in estimated payments 

compared with FY 2021. Providers in 

the rural South Atlantic region would 

experience the largest estimated 

increase in payments of approximately 

2.6 percent. Providers in the rural New 

England region would experience the 

smallest estimated increase in payments 

of 0.2 percent. 

B. Regulatory Flexibility Act Analysis 

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 SNFs 

and most other providers and suppliers 

are small entities, either by reason of 

their non-profit status or by having 

revenues of $30 million or less in any 

1 year. We utilized the revenues of 

individual SNF providers (from recent 

Medicare Cost Reports) to classify a 

small business, and not the revenue of 

a larger firm with which they may be 

affiliated. As a result, for the purposes 

of the RFA, we estimate that almost all 

SNFs are small entities as that term is 

used in the RFA, according to the Small 

Business Administration’s latest size 

standards (NAICS 623110), with total 

revenues of $30 million or less in any 

1 year. (For details, see the Small 

Business Administration’s website at 

http://www.sba.gov/category/ 

navigation-structure/contracting/ 

contracting-officials/eligibility-sizestandards). In addition, approximately 

20 percent of SNFs classified as small 

entities are non-profit organizations. 

Finally, individuals and states are not 

included in the definition of a small 

entity. 

This rule would update the SNF PPS 

rates contained in the SNF PPS final 


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TABLE 34: Accounting Statement: Classification of Estimated Expenditures, from the 

2021 SNF PPS Fiscal Year to the 2022 SNF PPS Fiscal Year 

Category Transfers 

Annualized Monetized Transfers $410 million* 

From Whom To Whom? Federal Government to SNF Medicare Providers 

* The net increase of $410 million in transfer payments is a result of the $411 million increase due to the market 

basket update factor of 1.2 percent, reduced by $1.2 million due to the proportional reduction associated with 

excluding blood clotting factors from SNF consolidated billing. 

TABLE 35: Accounting Statement: Classification of Estimated Expenditures for the 

FY 2022 SNF VBP Program 

Category Transfers 

Annualized Monetized Transfers $324.5 million* 

From Whom To Whom? Federal Government to SNF Medicare Providers 

*This estimate does not include the 2 percent reduction to SNFs' Medicare payments (estimated to be $516.15 

million) required by statute. 

TABLE 36: Accounting Statement: Classification of Estimated Expenditures for the 

FY 2022 SNF QRP Program 

Category Transfers/Costs 

Costs for SNFs to Submit Data for QRP $6.6 million* 

*Costs associated with the submission of data for the COVID-19 Vaccination Coverage among HCP will occur in 

FY 2022 and is likely to continue in future years. 
Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42523 

rule for FY 2021 (85 FR 47594). Based 

on the above, we estimate that the 

aggregate impact for FY 2022 would be 

an increase of $410 million in payments 

to SNFs, resulting from the SNF market 

basket update to the payment rates, 

reduced by the impact of excluding 

blood clotting factors (and items and 

services related to the furnishing of such 

factors) from SNF consolidated billing 

under section 1888(e)(2)(A)(iii)(VI) and 

(e)(4)(G)(iii) of the Act. While it is 

projected in Table 32 that all providers 

would experience a net increase in 

payments, we note that some individual 

providers within the same region or 

group may experience different impacts 

on payments than others due to the 

distributional impact of the FY 2022 

wage indexes and the degree of 

Medicare utilization. 

Guidance issued by the Department of 

Health and Human Services on the 

proper assessment of the impact on 

small entities in rulemakings, utilizes a 

cost or revenue impact of 3 to 5 percent 

as a significance threshold under the 

RFA. In their March 2021 Report to 

Congress (available at http://

www.medpac.gov/docs/default-source/ 

reports/mar21_medpac_ch7_sec.pdf), 

MedPAC states that Medicare covers 

approximately 9 percent of total patient 

days in freestanding facilities and 16 

percent of facility revenue (March 2020 

MedPAC Report to Congress, 224). As 

indicated in Table 32, the effect on 

facilities is projected to be an aggregate 

positive impact of 1.2 percent for FY 

2022. As the overall impact on the 

industry as a whole, and thus on small 

entities specifically, is less than the 3 to 

5 percent threshold discussed 

previously, the Secretary has 

determined that this final rule will not 

have a significant impact on a 

substantial number of small entities for 

FY 2022. 

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 

an MSA and has fewer than 100 beds. 

This final rule will affect small rural 

hospitals that: (1) Furnish SNF services 

under a swing-bed agreement or (2) have 

a hospital-based SNF. We anticipate that 

the impact on small rural hospitals will 

be a positive impact. Moreover, as noted 

in previous SNF PPS final rules (most 

recently, the one for FY 2021 (85 FR 

47594)), the category of small rural 

hospitals is included within the analysis 

of the impact of this final rule on small 

entities in general. As indicated in Table 

32, the effect on facilities for FY 2022 

is projected to be an aggregate positive 

impact of 1.2 percent. As the overall 

impact on the industry as a whole is less 

than the 3 to 5 percent threshold 

discussed above, the Secretary has 

determined that this final rule will not 

have a significant impact on a 

substantial number of small rural 

hospitals for FY 2022. 

C. Unfunded Mandates Reform Act 

Analysis 

Section 202 of the Unfunded 

Mandates Reform Act of 1995 also 

requires that agencies assess anticipated 

costs and benefits before issuing any 

rule whose mandates require spending 

in any 1 year of $100 million in 1995 

dollars, updated annually for inflation. 

In 2021, that threshold is approximately 

$158 million. This final rule will 

impose no mandates on state, local, or 

tribal governments or on the private 

sector. 

D. Federalism Analysis 

Executive Order 13132 establishes 

certain requirements that an agency 

must meet when it issues a proposed 

rule (and subsequent final rule) that 

imposes substantial direct requirement 

costs on state and local governments, 

preempts state law, or otherwise has 

federalism implications. This final rule 

will have no substantial direct effect on 

state and local governments, preempt 

state law, or otherwise have federalism 

implications. 

E. Congressional Review Act 

This final regulation is subject to the 

Congressional Review Act provisions of 

the Small Business Regulatory 

Enforcement Fairness Act of 1996 (5 

U.S.C. 801 et seq.) and has been 

transmitted to the Congress and the 

Comptroller General for review. 

F. 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 review the rule, we 

assume that the total number of unique 

commenters on this year’s proposed rule 

will be the number of reviewers of this 

final rule. We acknowledge that this 

assumption may understate or overstate 

the costs of reviewing this rule. It is 

possible that not all commenters 

reviewed this year’s proposed rule in 

detail, and it is also possible that some 

reviewers chose not to comment on that 

proposed rule. For these reasons, we 

believe that the number of commenters 

on this year’s proposed rule is a fair 

estimate of the number of reviewers of 

this final rule. 

We also recognize that different types 

of entities are in many cases affected by 

mutually exclusive sections of the final 

rule, and therefore, for the purposes of 

our estimate we assume that each 

reviewer reads approximately 50 

percent of the rule. 

Using the national mean hourly wage 

data from the May 2020 BLS 

Occupational Employment Statistics 

(OES) for medical and health service 

managers (SOC 11–9111), we estimate 

that the cost of reviewing this rule is 

$114.24 per hour, including overhead 

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

oes/current/oes_nat.htm. Assuming an 

average reading speed, we estimate that 

it would take approximately 4 hours for 

the staff to review half of the proposed 

rule. For each SNF that reviews the rule, 

the estimated cost is $456.96 (4 hours × 

$114.24). Therefore, we estimate that 

the total cost of reviewing this 

regulation is $156,280.32 ($442.96 × 342 

reviewers). 

In accordance with the provisions of 

Executive Order 12866, this final rule 

was reviewed by the Office of 

Management and Budget. 

I, Chiquita Brooks-LaSure, 

Administrator of the Centers for 

Medicare & Medicaid Services, 

approved this document on July 21, 

2021. 

List of Subjects 

42 CFR Part 411 

Diseases, Medicare, Reporting and 

recordkeeping requirements. 

42 CFR Part 413 

Principles of reasonable cost 

reimbursement; payment for end-stage 

renal disease services; optional 

prospectively determined payment rates 

for skilled nursing facilities; payment 

for acute kidney injury dialysis. 

42 CFR Part 483 

Grant programs—health, Health 

facilities, Health professions, Health 

records, Medicaid, Medicare, Nursing 

homes, Nutrition, Reporting and 

recordkeeping requirements, Safety. 

42 CFR Part 489 

Health facilities, Medicare, Reporting 

and recordkeeping requirements. 

For the reasons set forth in the 

preamble, the Centers for Medicare & 

Medicaid Services amends 42 CFR 

chapter IV as set forth below: 


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42524 Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 

PART 411—EXCLUSIONS FROM 

MEDICARE AND LIMITATIONS ON 

MEDICARE PAYMENT 

■ 1. The authority citation for part 411 

continues to read as follows: 

Authority: 42 U.S.C. 1302, 1395w–101 

through 1395w–152, 1395hh, and 1395nn. 

■ 2. Amend § 411.15 by— 

■ a. Revising paragraphs (p)(2)(xiii) 

through (xvi); 

■ b. Redesignating paragraph (p)(2)(xvii) 

as (p)(2)(xviii); and 

■ c. Adding new paragraph (p)(2)(xvii). 

The revisions and addition read as 

follows: 

§ 411.15 Particular services excluded from 

coverage. 

* * * * * 

(p) * * * 

(2) * * * 

(xiii) Those chemotherapy items 

identified, as of July 1, 1999, by HCPCS 

codes J9000–J9020, J9040–J9151, J9170– 

J9185, J9200–J9201, J9206–J9208, J9211, 

J9230–J9245, and J9265–J9600, and as of 

January 1, 2004, by HCPCS codes 

A9522, A9523, A9533, and A9534 (as 

subsequently modified by CMS), and 

any additional chemotherapy items 

identified by CMS. 

(xiv) Those chemotherapy 

administration services identified, as of 

July 1, 1999, by HCPCS codes 36260– 

36262, 36489, 36530–36535, 36640, 

36823, and 96405–96542 (as 

subsequently modified by CMS), and 

any additional chemotherapy 

administration services identified by 

CMS. 

(xv) Those radioisotope services 

identified, as of July 1, 1999, by HCPCS 

codes 79030–79440 (as subsequently 

modified by CMS), and any additional 

radioisotope services identified by CMS. 

(xvi) Those customized prosthetic 

devices (including artificial limbs and 

their components) identified, as of July 

1, 1999, by HCPCS codes L5050–L5340, 

L5500–L5611, L5613–L5986, L5988, 

L6050–L6370, L6400–6880, L6920– 

L7274, and L7362–L7366 (as 

subsequently modified by CMS) and any 

additional customized prosthetic 

devices identified by CMS, which are 

delivered for a resident’s use during a 

stay in the SNF and intended to be used 

by the resident after discharge from the 

SNF. 

(xvii) Those blood clotting factors 

indicated for the treatment of patients 

with hemophilia and other bleeding 

disorders identified, as of July 1, 2020, 

by HCPCS codes J7170, J7175, J7177– 

J7183, J7185–J7190, J7192–J7195, J7198– 

J7203, J7205, and J7207–J7211 (as 

subsequently modified by CMS) and 

items and services related to the 

furnishing of such factors, and any 

additional blood clotting factors 

identified by CMS and items and 

services related to the furnishing of such 

factors. 

* * * * * 

PART 413—PRINCIPLES OF 

REASONABLE COST 

REIMBURSEMENT; PAYMENT FOR 

END-STAGE RENAL DISEASE 

SERVICES; PROSPECTIVELY 

DETERMINED PAYMENT RATES FOR 

SKILLED NURSING FACILITIES; 

PAYMENT FOR ACUTE KIDNEY 

INJURY DIALYSIS 

■ 3. The authority citation for part 413 

continues to read as follows: 

Authority: 42 U.S.C. 1302, 1395d(d), 

1395f(b), 1395g, 1395l(a), (i), and (n), 

1395x(v), 1395hh, 1395rr, 1395tt, and 

1395ww. 

■ 4. Amend § 413.338 by revising 

paragraphs (d)(4)(ii) and (e)(1) and 

adding paragraph (g) to read as follows: 

§ 413.338 Skilled nursing facility valuebased purchasing program. 

* * * * * 

(d) * * * 

(4) * * * 

(ii) A SNF may request an exception 

within 90 days of the date that the 

extraordinary circumstances occurred in 

the form and manner specified by CMS 

on the SNF VBP website at https://

www.cms.gov/Medicare/QualityInitiatives-Patient-AssessmentInstruments/Value-Based-Programs/ 

SNF-VBP/Extraordinary-CircumstanceException-. The request must include a 

completed Extraordinary Circumstances 

Request form (available on https://

qualitynet.cms.gov/) and any available 

evidence of the impact of the 

extraordinary circumstances on the care 

that the SNF furnished to patients 

including, but not limited to, 

photographs and media articles. 

* * * * * 

(e) * * * 

(1) CMS will provide quarterly 

confidential feedback reports to SNFs 

on their performance on the SNF 

readmission measure. Beginning with 

the baseline period and performance 

period quality measure quarterly reports 

issued on or after October 1, 2021, 

which contain the baseline period and 

performance period measure rates, 

respectively, SNFs will have 30 days 

following the date CMS provides each of 

these reports to review and submit 

corrections to the SNF readmission 

measure rates contained in that report. 

The administrative claims data used to 

calculate a SNF’s readmission measure 

rates are not subject to review and 

correction under this paragraph (e)(1). 

All correction requests must be 

accompanied by appropriate evidence 

showing the basis for the correction to 

the SNF readmission measure rates. 

* * * * * 

(g) Special rules for the FY 2022 SNF 

VBP Program. (1) CMS will calculate a 

SNF readmission measure rate for each 

SNF based on its performance on the 

SNF readmission measure during the 

performance period specified by CMS 

for fiscal year 2022, but CMS will not 

calculate a performance score for any 

SNF using the methodology described 

in paragraphs (d)(1) and (2) of this 

section. CMS will instead assign a 

performance score of zero to each SNF, 

with the exception of those SNFs 

qualifying for the low-volume scoring 

adjustment described in paragraph 

(d)(3) of this section. 

(2) CMS will calculate the value-based 

incentive payment adjustment factor for 

each SNF using a performance score of 

zero and will then calculate the valuebased incentive payment amount for 

each SNF using the methodology 

described in paragraph (c)(2)(ii) of this 

section. CMS will then apply lowvolume scoring adjustment described in 

paragraph (d)(3) of this section. 

(3) CMS will provide confidential 

feedback reports to SNFs on their 

performance on the SNF readmission 

measure in accordance with paragraphs 

(e)(1) and (2) of this section. 

(4) CMS will publicly report SNF 

performance on the SNF readmission 

measure in accordance with paragraph 

(e)(3) of this section. 

PART 483—REQUIREMENTS FOR 

STATES AND LONG TERM CARE 

FACILITIES 

■ 5. The authority citation for part 483 

continues to read as follows: 

Authority: 42 U.S.C. 1302, 1320a–7, 1395i, 

1395hh and 1396r. 

■ 6. Amend § 483.90 by revising 

paragraph (d) to read as follows: 

§ 483.90 Physical environment. 

* * * * * 

(d) Space and equipment. The facility 

must— 

(1) Provide sufficient space and 

equipment in dining, health services, 

recreation, living, and program areas to 

enable staff to provide residents with 

needed services as required by these 

standards and as identified in each 

resident’s assessment and plan of care; 

(2) Maintain all mechanical, 

electrical, and patient care equipment in 

safe operating condition; and 


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Federal Register / Vol. 86, No. 147 / Wednesday, August 4, 2021 / Rules and Regulations 42525 

(3) Conduct regular inspection of all 

bed frames, mattresses, and bed rails, if 

any, as part of a regular maintenance 

program to identify areas of possible 

entrapment. When bed rails and 

mattresses are used and purchased 

separately from the bed frame, the 

facility must ensure that the bed rails, 

mattress, and bed frame are compatible. 

* * * * * 

PART 489—PROVIDER AGREEMENTS 

AND SUPPLIER APPROVAL 

■ 7. The authority citation for part 489 

is revised to read as follows: 

Authority: 42 U.S.C. 1302, 1395i–3, 1395x, 

1395aa(m), 1395cc, 1395ff, and 1395hh. 

■ 8. Amend § 489.20 by— 

■ a. Revising paragraphs (s)(13) through 

(16); 

■ b. Redesignating paragraph (s)(17) as 

paragraph (s)(18); and 

■ c. Adding new paragraph (s)(17). 

The revisions and addition read as 

follows: 

§ 489.20 Basis commitments. 

* * * * * 

(s) * * * 

(13) Those chemotherapy items 

identified, as of July 1, 1999, by HCPCS 

codes J9000–J9020, J9040–J9151, J9170– 

J9185, J9200–J9201, J9206–J9208, J9211, 

J9230–J9245, and J9265–J9600, and as of 

January 1, 2004, by HCPCS codes 

A9522, A9523, A9533, and A9534 (as 

subsequently modified by CMS), and 

any additional chemotherapy items 

identified by CMS. 

(14) Those chemotherapy 

administration services identified, as of 

July 1, 1999, by HCPCS codes 36260– 

36262, 36489, 36530–36535, 36640, 

36823, and 96405–96542 (as 

subsequently modified by CMS), and 

any additional chemotherapy 

administration services identified by 

CMS. 

(15) Those radioisotope services 

identified, as of July 1, 1999, by HCPCS 

codes 79030–79440 (as subsequently 

modified by CMS), and any additional 

radioisotope services identified by CMS. 

(16) Those customized prosthetic 

devices (including artificial limbs and 

their components) identified, as of July 

1, 1999, by HCPCS codes L5050–L5340, 

L5500–L5611, L5613–L5986, L5988, 

L6050–L6370, L6400–6880, L6920– 

L7274, and L7362–L7366 (as 

subsequently modified by CMS) and any 

additional customized prosthetic 

devices identified by CMS, which are 

delivered for a resident’s use during a 

stay in the SNF and intended to be used 

by the resident after discharge from the 

SNF. 

(17) Those blood clotting factors 

indicated for the treatment of patients 

with hemophilia and other bleeding 

disorders identified, as of July 1, 2020, 

by HCPCS codes J7170, J7175, J7177– 

J7183, J7185–J7190, J7192–J7195, J7198– 

J7203, J7205, and J7207–J7211 (as 

subsequently modified by CMS) and 

items and services related to the 

furnishing of such factors, and any 

additional blood clotting factors 

identified by CMS and items and 

services related to the furnishing of such 

factors. 

* * * * * 

Dated: July 27, 2021. 

Xavier Becerra, 

Secretary, Department of Health and Human 

Services. 

[FR Doc. 2021–16309 Filed 7–29–21; 4:15 pm] 

BILLING CODE 4120–01–P 


lotter on DSK11XQN23PROD with RULES3