[Federal Register Volume 86, Number 147 (Wednesday, August 4, 2021)]
[Rules and Regulations]
[Pages 42424-42525]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-16309]



[[Page 42423]]

Vol. 86

Wednesday,

No. 147

August 4, 2021

Part IV





Department of Health and Human Services





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Centers for Medicare & Medicaid Services





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42 CFR Parts 411, 413, 483, et al.





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 Long-Term Care Facilities Physical 
Environment Requirements; Final Rule

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

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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 Long-Term Care Facilities 
Physical Environment Requirements

AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.

ACTION: Final rule.

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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 recently-enacted 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-Service-Payment/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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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 All-Cause Readmission Measure (SNFRM) for the FY 2022 SNF VBP 
Program Year for scoring, adjusting and codifying the policy at Sec.  
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 Sec.  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 Sec.  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 Sec.  483.90(d)(1) and 
adding Sec.  483.90(d)(3).

C. Summary of Cost and Benefits
[GRAPHIC] [TIFF OMITTED] TR04AU21.218

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 post-acute 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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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-and-common-agreement and 
https://rce.sequoiaproject.org/.
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    \1\ ONC, Draft 2 Trusted Exchange Framework and Common 
Agreement, https://www.healthit.gov/sites/default/files/page/2019-04/FINALTEFCAQTF41719508version.pdf.
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    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-Fee-for-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 all-cause all-condition 
hospital readmission measure and an all-condition risk-adjusted 
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:
    <bullet> The unadjusted Federal per diem rates to be applied to 
days of covered SNF services furnished during the upcoming FY.
    <bullet> The case-mix classification system to be applied for these 
services during the upcoming FY.
    <bullet> The factors to be applied in making the area wage 
adjustment for these services.

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    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 wage-related 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.

[[Page 42428]]

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), Sec.  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.

[[Page 42429]]

[GRAPHIC] [TIFF OMITTED] TR04AU21.219

    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/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketData) on a quarterly 
basis. Additionally, as stated on the CMS website, providers can also 
email <a href="/cdn-cgi/l/email-protection#aeeae0e6fdeecdc3dd80c6c6dd80c9c1d8"><span class="__cf_email__" data-cfemail="91d5dfd9c2d1f2fce2bff9f9e2bff6fee7">[email protected]</span></a> 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, 
cost-reporting 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

[[Page 42430]]

``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 Sec.  
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), Speech-Language Pathology (SLP), Nursing, and Non-Therapy 
Ancillaries (NTA)), and

[[Page 42431]]

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

[[Page 42432]]

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

[[Page 42433]]

[GRAPHIC] [TIFF OMITTED] TR04AU21.220

    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.
[GRAPHIC] [TIFF OMITTED] TR04AU21.221

[GRAPHIC] [TIFF OMITTED] TR04AU21.222

BILLING CODE 4120-01-C

[[Page 42434]]

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 case-mix 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-Assessment-Instruments/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 three-character 
RUG-IV group into which the patient classified as well as a two-
character 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/wp-content/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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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

[[Page 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 non-
urban 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-Fee-for-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/wp-content/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/wp-content/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 
labor-related portion of the Federal rate. Each year, we calculate a 
revised labor-related 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 labor-related 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: Labor-Related 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: Labor-
Related Services; and a proportion of Capital-Related expenses. The 
methodology for calculating the labor-related 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

[[Page 42438]]

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 labor-related 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 labor-related share that was used for the FY 2021 SNF PPS final 
rule.
[GRAPHIC] [TIFF OMITTED] TR04AU21.225

    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 
labor-related 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

[[Page 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 resource-intensive 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 SNF-specific 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 Sec.  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 case-mix 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-Fee-for-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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[[Page 42441]]


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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 case-mix 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 Sec.  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 case-mix 
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-Fee-for-Service-Payment/
SNFPPS/

[[Page 42442]]

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-Fee-for-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 speech-language 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-Service-Payment/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

[[Page 42443]]

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/SNFConsolidatedBilling.
    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, RIABNI<SUP>TM</SUP> (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 non-dialysis 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

[[Page 42444]]

outside of the specified service categories themselves. Thus, while 
anti-emetics, 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 SNF-level 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, SNF-level 
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 swing-bed 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-Service-Payment/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 Sec. Sec.  
411.15(p)(2)(xviii) and 489.20(s)(18), respectively, and to update the 
regulation text at Sec. Sec.  411.15(p)(2)(xvii) and 489.20(s)(17) to 
reflect the recently-enacted 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 Sec. Sec.  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 Sec. Sec.  
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

[[Page 42445]]

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 fixed-weight, 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 hospital-based 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 Input-
Output (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

[[Page 42446]]

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 ownership-type (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 Medicare-allowable 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 Medicare-allowable total costs). 
Medicare-allowable 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 non-Medicare-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

[[Page 42447]]

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: Medicare-allowable employee benefits are 
equal to total facility benefits as reported on Worksheet S-3, part II, 
column 3, lines 17 through 19 minus non-Medicare-allowable (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 non-Medicare-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 Medicare-allowable. 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 long-term care unit. We believe that Medicaid 
patients receiving this skilled nursing care would on average have 
similar drug costs per day to dual-eligible 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

[[Page 42448]]

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 ownership-type 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 self-insurance) 
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.
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    \2\ https://www.aon.com/risk-services/thought-leadership/report-2018-long-term-care.jsp.
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    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 self-insurance) 
incurred during the provider's cost reporting year.
    (6) Capital-Related: We proposed to derive the Medicare-allowable 
capital-related 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 
``All-Other'' 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.

[[Page 42449]]

[GRAPHIC] [TIFF OMITTED] TR04AU21.229

    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.
[GRAPHIC] [TIFF OMITTED] TR04AU21.230

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 x 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).
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    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)

[[Page 42450]]

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: Nonlabor-Related 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-labor-
Related 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 
Capital-related 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-Medicare-allowable 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 non-Medicare 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-of-the-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 capital-
related expenses effective for 2018.
    Based on the 2017 SAS data, we determined that leasing expenses are 
62 percent of total leasing and capital-related 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 Medicare-
allowable capital costs of 4.2 percent derived from subtracting the 
Medicare-allowable 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 capital-related 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.

[[Page 42451]]

[GRAPHIC] [TIFF OMITTED] TR04AU21.231

    Table 15 presents the 2018-based SNF market basket and the 2014-
based SNF market basket.
BILLING CODE 4120-01-P

[[Page 42452]]

[GRAPHIC] [TIFF OMITTED] TR04AU21.232

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

[[Page 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:
    <bullet> 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).
    <bullet> 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/).
    <bullet> 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-to-date, 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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

[[Page 42454]]

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.
[GRAPHIC] [TIFF OMITTED] TR04AU21.233

    <bullet> 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 non-price 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
[GRAPHIC] [TIFF OMITTED] TR04AU21.234

    <bullet> 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

[[Page 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.
[GRAPHIC] [TIFF OMITTED] TR04AU21.235

    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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> Professional Fees: NonLabor-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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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: NonLabor-Related Services cost category, and to no

[[Page 42456]]

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.
    <bullet> 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.
    <bullet> 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.
    <bullet> 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.
    <bullet> For-Profit Interest: For the For-Profit 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.
    <bullet> 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) historical-cost average age; and (3) industry-
specific 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

[[Page 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-Data-and-Systems/Statistics-Trends-and-Reports/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.
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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

[[Page 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.
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[[Page 42461]]


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BILLING CODE 4120-01-C
4. Labor-Related Share
    We define the labor-related share (LRS) as those expenses that are 
labor-intensive and vary with, or are influenced by, the local labor 
market. Each year, we calculate a revised labor-related 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 labor-
intensive 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 labor-intensive 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

[[Page 42462]]

(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 
labor-related 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:
    <bullet> 78 percent of legal services.
    <bullet> 86 percent of accounting and auditing services.
    <bullet> 89 percent of architectural, engineering services.
    <bullet> 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 labor-related and nonlabor-related 
costs. As a result, we are designating 2.9 of the 3.5 percentage points 
total to the labor-related 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 x 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 x 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 labor-related share of 70.1 
percent (86 FR 19965).
    Comment: A few commenters appreciated the reduction of the labor-
related 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 labor-related 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).

[[Page 42463]]

[GRAPHIC] [TIFF OMITTED] TR04AU21.239

    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 labor-related 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.
[GRAPHIC] [TIFF OMITTED] TR04AU21.240


[[Page 42464]]



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-Service-Payment/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-for-ServicePayment/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 ``Sickle-cell 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, ``Vaping-related 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

[[Page 42465]]

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 non-substantive 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 ``Sickle-cell 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 non-substantive, 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.

[[Page 42466]]

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 case-mix 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 case-mix 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 
pandemic-related 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

[[Page 42467]]

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 PHE-
related 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 non-individualized 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-

[[Page 42468]]

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.
[GRAPHIC] [TIFF OMITTED] TR04AU21.241

    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

[[Page 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 PHE-related 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 well-considered 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 PHE-related 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-than-

[[Page 42470]]

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 case-mix 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

[[Page 42471]]

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

[[Page 42472]]

[GRAPHIC] [TIFF OMITTED] TR04AU21.242

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

    \4\ The 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.
---------------------------------------------------------------------------

    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

[[Page 42473]]

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, risk-adjusted 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.<SUP>7 8 9</SUP> 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.<SUP>10 11 12 13 14 15</SUP> 
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.<SUP>16 17 18 19</SUP> Monitoring SNF HAI rates would provide 
information about each facility's adeptness in infection prevention and 
management.
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    \5\ CMS. (2006). Eliminating Serious Preventable, and Costly 
Medical Errors--Never Events. Retrieved from https://www.cms.gov/newsroom/fact-sheets/eliminating-serious-preventable-and-costly-medical-errors-never-events.
    \6\ Office 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.
    \7\ Beganovic, 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.
    \8\ Cooper, 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.
    \9\ Feldstein, 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.
    \10\ Castle, 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.
    \11\ 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.
    \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.
    \13\ Cooper, 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.
    \15\ Travers, 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.
    \16\ CMS. (2006). Eliminating Serious Preventable, and Costly 
Medical Errors--Never Events. Retrieved from https://www.cms.gov/newsroom/fact-sheets/eliminating-serious-preventable-and-costly-medical-errors-never-events.
    \17\ Centers for Disease Control and Prevention (2009). The 
Direct Medical Costs of Healthcare-Associated Infections in U.S. 
Hospitals and the Benefits of Prevention. Retrieved from https://www.cdc.gov/hai/pdfs/hai/scott_costpaper.pdf.
    \18\ Ouslander, 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.
    \19\ Zimlichman, E., Henderson, D., Tamir, O., Franz, C., Song, 
P., Yamin, C.K., . . . Bates, D.W. (2013). Health care-associated 
infections: A meta-analysis 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.
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    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.<SUP>20 21</SUP> Furthermore, in SNFs, 
COVID-19 has a disproportionate impact on racial and ethnic minorities 
as well as people living with disabilities.<SUP>22 23</SUP> Emerging 
COVID-19 studies reveal higher patient spread due to poor infection 
control, staff rotations between multiple SNFs, and poor patient COVID-
19 screenings.<SUP>24 25</SUP> An analysis comparing

[[Page 42474]]

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.<SUP>27 28 29 30 31 32 33</SUP> 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.
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    \20\ Montoya, 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.
    \21\ Office 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 care-associated 
infections: Road map to elimination (pp. 194-239). Retrieved from 
https://health.gov/our-work/health-care-quality/health-care-associated-infections/national-hai-action-plan.
    \22\ Chidambaram, 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/issue-brief/racial-and-ethnic-disparities-in-covid-19-cases-and-deaths-in-nursing-homes/.
    \23\ Li 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.
    \25\ McMichael, 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 Long-Term 
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.
    \26\ The 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 Medicare-
certified nursing homes providing SNF care.
    \27\ Office 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.
    \28\ Beganovic, 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.
    \29\ 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.
    \30\ Freeman-Jobson, J.H., Rogers, J.L., & Ward-Smith, 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.
    \31\ Hutton, 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.
    \32\ Nguyen, 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.
    \33\ Sloane, 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.
    \34\ Lee, 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/.
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    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/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-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/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-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 multi-stakeholder 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,

[[Page 42475]]

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.
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    \35\ National 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.
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    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/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-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 consensus-endorsed 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 Post-Discharge 
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 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/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-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.

[[Page 42476]]

    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, risk-adjusted 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.
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    \36\ Acumen 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-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-Information.
    \37\ Office 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.
    \38\ CMS. (2006). Eliminating Serious, Preventable, and Costly 
Medical Errors--Never Events. Retrieved from https://www.cms.gov/newsroom/fact-sheets/eliminating-serious-preventable-and-costly-medical-errors-never-events.
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    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 Sec.  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 NQF-endorsed 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.
---------------------------------------------------------------------------

    \39\ Office 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.
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    Comment: Several commenters opposed the use of Medicare FFS claims 
for the SNF HAI measure. Many commenters do not believe that claims-
based measures are appropriate for measuring HAIs, and would instead 
support the use of NHSN chart-abstracted 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

[[Page 42477]]

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

    \40\ Levitt, 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-Assessment-Instruments/NursingHomeQualityInits/Downloads/SNF-HAI-Final-TEP-Report-7-15-19_508C.pdf.
---------------------------------------------------------------------------

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

    \41\ Cafardi, 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 
Conditions-Present 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.
    \42\ He, 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.
---------------------------------------------------------------------------

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

    \43\ Levitt, 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-Assessment-Instruments/NursingHomeQualityInits/Downloads/SNF-HAI-Final-TEP-Report-7-15-19_508C.pdf.
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    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 catheter-
associated 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

[[Page 42478]]

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 ``never-events'' 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.
---------------------------------------------------------------------------

    \44\ Levitt, 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-Assessment-Instruments/NursingHomeQualityInits/Downloads/SNF-HAI-Final-TEP-Report-7-15-19_508C.pdf.
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    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 patient-level 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

[[Page 42479]]

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

    \45\ National 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.
---------------------------------------------------------------------------

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

    \46\ Acumen 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-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-Information.
---------------------------------------------------------------------------

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

    \47\ Acumen 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-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-Information.
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    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.
---------------------------------------------------------------------------

    \48\ National 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_PAC-LTC.aspx.
---------------------------------------------------------------------------

    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 Sec.  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

[[Page 42480]]

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 claims-based 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\
---------------------------------------------------------------------------

    \49\ U.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.
    \50\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Retrieved from https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \51\ Centers 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.
    \52\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \53\ Centers for Disease Control and Prevention. (2020). CDC 
COVID Data Tracker. Available at https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
    \54\ Ibid.
---------------------------------------------------------------------------

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

    \55\ Associated Press. Tired to the Bone. Hospitals Overwhelmed 
with Virus Cases. November 18, 2020. Accessed on December 16, 2020, 
at https://apnews.com/article/hospitals-overwhelmed-coronavirus-cases-74a1f0dc3634917a5dc13408455cd895. Also see: New York Times. 
Just how full are U.S. intensive care units? New data paints an 
alarming picture. November 18, 2020. Accessed on December 16, 2020, 
at https://www.nytimes.com/2020/12/09/world/just-how-full-are-us-intensive-care-units-new-data-paints-an-alarming-picture.html.
    \56\ NPR. 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.
---------------------------------------------------------------------------

    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 infection-
control 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\
---------------------------------------------------------------------------

    \57\ Centers 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.
    \58\ Centers 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.
    \59\ Centers 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.
    \60\ Centers 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.
    \61\ Centers 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.
    \62\ Centers 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.
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    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

[[Page 42481]]

authorized to prevent COVID-19, outweighed its known and potential 
risks.\66\ \67\ \68\
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    \64\ Centers 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/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \65\ U.S. Food and Drug Administration. (2021). Pfizer-BioNTech 
COVID-19 Vaccine. Available at https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/pfizer-biontech-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.
    \66\ Ibid.
    \67\ U.S. Food and Drug Administration. (2021). ModernaTX, Inc. 
COVID-19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144636/download.
    \68\ U.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.
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    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\
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    \69\ The 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/speeches-remarks/2021/03/29/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations/.
    \70\ Health 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-for-distributing-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-states-prioritizing-who-will-get-the-covid-19-vaccine-first/.
    \73\ Associated 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-coronavirus-vaccine-56df745388a9fc12ae93c6f9a0d0e81f.
    \74\ Press Briefing by White House COVID-19 Response Team and 
Public Health Officials [bond] The White House.
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    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.
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    \75\ Centers for Disease Control and Prevention. Weekly COVID-19 
Vaccination Data Reporting. Accessed at https://www.cdc.gov/nhsn/ltc/weekly-covid-vac/index.html.
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    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 pre-rulemaking input on 
each measure, under section 1890A of the Act.\76\ To meet this 
requirement, the following opportunity was provided for stakeholder 
input.
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    \76\ Centers for Medicare & Medicaid Services. Pre-rulemaking. 
Accessed at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures/Pre-Rulemaking.
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    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 multi-stakeholder 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

[[Page 42482]]

measure definition for HCP, and some commenters encouraged CMS to 
continue to update the measure as new evidence comes in.
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    \77\ National 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.
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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\
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    \78\ Measure 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.
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    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 well-documented 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.
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    \80\ Ibid.
    \81\ Ibid.
---------------------------------------------------------------------------

    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\
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    \82\ 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).
    \83\ Centers 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.
---------------------------------------------------------------------------

    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 Long-term 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.
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    \84\ National 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%20abou
t,reliability%20or%20validity%20testing%20results.&text=Reliability%2
0and%20validity%20must%20be,source%20and%20level%20of%20analysis).
    \85\ Ibid.
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    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).

[[Page 42483]]

    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.
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    \86\ Centers 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/covid-19/info-by-product/clinical-considerations.html.
---------------------------------------------------------------------------

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

    \87\ Centers 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.
---------------------------------------------------------------------------

    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.
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    \88\ Chen 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.
    \89\ Centers 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.
---------------------------------------------------------------------------

    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

[[Page 42484]]

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.
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    \90\ CBS 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-surplus-vacant-appointments/.
---------------------------------------------------------------------------

    Comment: A couple of commenters expressed concern over the 
potential for inequality among SNFs because one-dose 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

[[Page 42485]]

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

    \92\ Centers for Disease Control and Prevention. Vaccine 
Administration. Available at https://www.cdc.gov/vaccines/covid-19/clinical-considerations/covid-19-vaccines-us.html. Accessed June 25, 
2021.
---------------------------------------------------------------------------

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

    \93\ Centers 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%2
0the%20virus&text=Current%20data%20suggest%20that%20COVID,after%20the
y%20are%20fully%20vaccinated. Accessed June 25, 2021.
---------------------------------------------------------------------------

    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-for-reporting 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 self-select 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-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-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

[[Page 42486]]

submission requirements. We disagree with the commenter, as the LTC 
facility requirements of participation at (requirements) at Sec.  
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 Sec.  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 Sec.  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 Sec.  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 Sec.  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-authorization-vaccines-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.
---------------------------------------------------------------------------

    \94\ U.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-about-covid-19-and-ada-rehabilitation-act-and-other-eeo-laws. Accessed June 25, 2021.
---------------------------------------------------------------------------

    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

[[Page 42487]]

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

    \95\ Medicare 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.
---------------------------------------------------------------------------

    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 post-acute 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 post-acute 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, FDA-approved 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 long-term 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

[[Page 42488]]

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

    \96\ Medscape. Disturbing Number of Hospital Workers Still 
Unvaccinated. Available at https://www.medscape.com/viewarticle/953871. Accessed July 13, 2021.
---------------------------------------------------------------------------

    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-clinical-considerations.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.<SUP>97 98 99</SUP> Therefore, we 
disagree with the commenter and do not believe the definition of the 
denominator needs to be changed.
---------------------------------------------------------------------------

    \97\ Pfizer-BioNtech COVID-19 vaccine. Available at https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/pfizer-biontech-covid-19-vaccine.
    \98\ Moderna COVID-19 vaccine. Available at https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/moderna-covid-19-vaccine.
    \99\ Janssen COVID-19 vaccine. Available at https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/janssen-covid-19-vaccine.
---------------------------------------------------------------------------

    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

[[Page 42489]]

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

    \100\ CMS. 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.
---------------------------------------------------------------------------

    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 Sec.  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.
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    \101\ NHSN. 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-toi-508.pdf.
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    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--
Post-Acute Care (PAC) Measure Beginning With the FY 2023 SNF QRP
    We proposed to update the Transfer of Health Information to the 
Patient--Post-Acute 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-Patient-Assessment-Instruments/NursingHomeQualityInits/Downloads/Final-Specifications-for-SNF-QRP-Quality-Measures-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

[[Page 42490]]

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 TOH-Provider-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 Sec.  
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 post-discharge 
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-Patient-PAC measure was proposed and 
finalized. For additional technical information regarding the TOH-
Patient-PAC 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-Patient-Assessment-Instruments/NursingHomeQualityInits/Downloads/Final-Specifications-for-SNF-QRP-Quality-Measures-and-SPADEs.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-Post-Acute 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.
[GRAPHIC] [TIFF OMITTED] TR04AU21.243


[[Page 42491]]


    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.
    <bullet> What EHR/IT systems do you use and do you participate in a 
health information exchange (HIE)?
    <bullet> How do you currently share information with other 
providers?
    <bullet> 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?
    <bullet> 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?
    <bullet> 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:
    <bullet> Recommendations for quality measures, or measurement 
domains that address health equity, for use in the SNF QRP.
    <bullet> 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.
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    \102\ https://www.cdc.gov/nhsn/ltc/weekly-covid-vac/index.html.
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    <bullet> 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

[[Page 42492]]

Program (see 84 FR 42496 through 42500)).
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    \103\ https://www.cdc.gov/nhsn/ltc/weekly-covid-vac/index.html.
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    <bullet> 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.
    <bullet> 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, long-term 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

[[Page 42493]]

SNF QRP reporting requirements for the COVID-19 Vaccination among HCP 
measure.
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    \104\ https://www.cdc.gov/nhsn/ltc/weekly-covid-vac/index.html.
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    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/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-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\
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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.
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    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 Sec.  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

[[Page 42494]]

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\
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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.
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    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-clinical-considerations.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 time-sensitive 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 web-
based surveillance system. SNFs would use the COVID-19 vaccination data 
collection module in the NHSN Long-term 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

[[Page 42495]]

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/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-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/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-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

[[Page 42496]]

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.<SUP>107 108</SUP> We will 
continue to evaluate the impact of the PHE and explore the impact of 
COVID-19 on quality reporting.
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    \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.
    \108\ McMichael, 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 Long-Term 
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.
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    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\
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    \109\ Centers 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-vaccinated-people.html.
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    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

[[Page 42497]]

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 employer-mandated 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.
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    \110\ Centers for Disease Control and Prevention. Building 
Confidence in COVID-19 Vaccines. Available at https://www.cdc.gov/vaccines/covid-19/vaccinate-with-confidence.html.
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    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\
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    \111\ Centers 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-after-vaccination.html. 
Accessed June 26, 2021.
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    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 
Sec.  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 Sec.  
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

[[Page 42498]]

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.
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    \112\ Medicare 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.
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    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, Long-Term 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.
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    \113\ https://www.phe.gov/emergency/news/healthactions/section1135/Pages/covid19-13March20.aspx.
    \114\ https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
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    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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    \115\ More 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-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Public-Reporting.

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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 partially-exempt 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).

[[Page 42500]]

    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 claims-based 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 assessment-based measures, the 
affected refresh is the January 2022 refresh; for claims-based 
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/snfqrp-covid19prtipsheet-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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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

[[Page 42502]]

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/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-QR-Reconsideration-and-Exception-and-Extension.
    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 Value-Based 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:
    <bullet> 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

[[Page 42503]]

function methodology to translate SNF performance scores into value-
based incentive payments, among other topics.
    <bullet> 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.
    <bullet> 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 low-volume facilities.
    <bullet> 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.
    <bullet> In the FY 2021 SNF PPS final rule (85 FR 47624 through 
47627), we amended regulatory text definitions at Sec.  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 Sec.  413.338(e)(1). Additionally, we codified the data suppression 
policy for low-volume SNFs at Sec.  413.338(e)(3)(i), (ii), and (iii) 
and amended Sec.  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'' (Sec.  
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 value-based incentive payment percentages based on those 
performance scores. We

[[Page 42504]]

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 value-based 
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 value-based 
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 value-based 
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:
    <bullet> Clinical guidelines, care delivery or practice, 
treatments, drugs, or related protocols, or equipment or diagnostic 
tools or materials; or
    <bullet> 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:
    <bullet> Healthcare personnel;
    <bullet> Medical supplies, equipment, or diagnostic tools or 
materials; or
    <bullet> Patient case volumes or facility-level 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 decision-making 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

[[Page 42505]]

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 
African-American SNF residents at the facility level. Dually eligible 
and African-American 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

[[Page 42506]]

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

    \116\ We 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.
---------------------------------------------------------------------------

    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 facility-level 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 net-neutral 
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 Sec.  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 high-performing and 
low-performing SNFs, and therefore, does not make value-based 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

[[Page 42507]]

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 low-volume 
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 Sec.  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 risk-adjustment 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 risk-
adjustment 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 risk-adjustment lookback period for the applicable FY 2023 
Program baseline year which would align the risk-adjustment 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 risk-adjustment 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

[[Page 42508]]

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/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-Program-Measures-and-Technical-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

[[Page 42509]]

[GRAPHIC] [TIFF OMITTED] TR04AU21.248

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

[[Page 42510]]

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

    \117\ https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertificationGenInfo/Downloads/QSO18-17-NH.pdf.
---------------------------------------------------------------------------

    We are also considering two patient-reported 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

[[Page 42511]]

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 
population-based 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

[[Page 42512]]

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 decision-making 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

[[Page 42513]]

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 Sec.  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:
[GRAPHIC] [TIFF OMITTED] TR04AU21.249

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,

[[Page 42514]]

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 Sec.  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 
value-based 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 Sec.  
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

[[Page 42515]]

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 Sec.  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 low-volume 
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 Sec.  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/provider-data/) 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

[[Page 42516]]

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 facility-level 
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 Low-Volume 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 Sec.  
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 net-neutral 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 Sec.  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 Sec.  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

[[Page 42517]]

memos, emails, and notices on the CMS SNF VBP website at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/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 value-based 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-Patient-Assessment-Instruments/Value-Based-Programs/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 Sec.  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 Sec.  413.338(e)(1) of our regulations.

I. Update to the Instructions for Requesting an ECE in Sec.  
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 
Sec.  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 Sec.  
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 Sec.  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 Sec.  483.90(d)

    In the July 18, 2019 ``Medicare and Medicaid Programs; Requirements 
for Long-Term Care Facilities: Regulatory Provisions To Promote 
Efficiency, and

[[Page 42518]]

Transparency'' proposed rule, we proposed a technical correction to 
revise Sec.  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 Sec.  483.90(d), which were 
finalized in the October 2016 final rule. Specifically, the rule 
finalized requirements at Sec.  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 Sec.  
483.90(d)(1)); (2) maintain all mechanical, electrical, and patient 
care equipment in safe operating condition at Sec.  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 Sec.  
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 Sec.  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 fee-for-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.
---------------------------------------------------------------------------

    \118\ Section 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.
---------------------------------------------------------------------------

    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 fee-for-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

[[Page 42519]]

(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 future-oriented, 
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 Sec.  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:
    <bullet> The first column shows the breakdown of all SNFs by urban 
or rural status, hospital-based or freestanding status, census region, 
and ownership.
    <bullet> 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).
    <bullet> The second column shows the number of facilities in the 
impact database.
    <bullet> 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.
    <bullet> 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

[[Page 42520]]

[GRAPHIC] [TIFF OMITTED] TR04AU21.250

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

[[Page 42521]]

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

    \119\ https://www.bls.gov/oes/current/oes_nat.htm. Accessed on 
March 30, 2021.
[GRAPHIC] [TIFF OMITTED] TR04AU21.251

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 low-volume 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 low-volume scoring adjustment), we estimated that we will 
redistribute approximately $324.5 million in value-based 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

[[Page 42522]]

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.
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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, non-profit 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-size-standards). 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

[[Page 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 x $114.24). 
Therefore, we estimate that the total cost of reviewing this regulation 
is $156,280.32 ($442.96 x 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:

[[Page 42524]]

PART 411--EXCLUSIONS FROM MEDICARE AND LIMITATIONS ON MEDICARE 
PAYMENT

0
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.


0
2. Amend Sec.  411.15 by--
0
a. Revising paragraphs (p)(2)(xiii) through (xvi);
0
b. Redesignating paragraph (p)(2)(xvii) as (p)(2)(xviii); and
0
c. Adding new paragraph (p)(2)(xvii).
    The revisions and addition read as follows:


Sec.  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

0
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.


0
4. Amend Sec.  413.338 by revising paragraphs (d)(4)(ii) and (e)(1) and 
adding paragraph (g) to read as follows:


Sec.  413.338   Skilled nursing facility value-based 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/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/SNF-VBP/Extraordinary-Circumstance-Exception-. 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 value-based incentive payment amount for each SNF using 
the methodology described in paragraph (c)(2)(ii) of this section. CMS 
will then apply low-volume 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

0
5. The authority citation for part 483 continues to read as follows:

    Authority:  42 U.S.C. 1302, 1320a-7, 1395i, 1395hh and 1396r.


0
6. Amend Sec.  483.90 by revising paragraph (d) to read as follows:


Sec.  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

[[Page 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

0
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.


0
8. Amend Sec.  489.20 by--
0
a. Revising paragraphs (s)(13) through (16);
0
b. Redesignating paragraph (s)(17) as paragraph (s)(18); and
0
c. Adding new paragraph (s)(17).
    The revisions and addition read as follows:


Sec.  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]
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