[Federal Register Volume 86, Number 213 (Monday, November 8, 2021)]
[Rules and Regulations]
[Pages 61874-62026]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-23907]
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Vol. 86
Monday,
No. 213
November 8, 2021
Part II
Department of Health and Human Services
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Centers for Medicare & Medicaid Services
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42 CFR Parts 412, 413, and 512
Medicare Program; End-Stage Renal Disease Prospective Payment System,
Payment for Renal Dialysis Services Furnished to Individuals With Acute
Kidney Injury, End-Stage Renal Disease Quality Incentive Program, and
End-Stage Renal Disease Treatment Choices Model; Final Rule
Federal Register / Vol. 86 , No. 213 / Monday, November 8, 2021 /
Rules and Regulations
[[Page 61874]]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Parts 412, 413, and 512
[CMS-1749-F]
RIN 0938-AU39
Medicare Program; End-Stage Renal Disease Prospective Payment
System, Payment for Renal Dialysis Services Furnished to Individuals
With Acute Kidney Injury, End-Stage Renal Disease Quality Incentive
Program, and End-Stage Renal Disease Treatment Choices Model
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Final rule.
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SUMMARY: This final rule updates the End-Stage Renal Disease (ESRD)
Prospective Payment System (PPS) for calendar year (CY) 2022. This rule
also updates the payment rate for renal dialysis services furnished by
an ESRD facility to individuals with acute kidney injury (AKI). In
addition, this rule updates requirements for the ESRD Quality Incentive
Program (QIP), including a measure suppression policy for the duration
of the coronavirus disease 2019 (COVID-19) public health emergency
(PHE) as well as suppression of individual ESRD QIP measures for
Payment Year (PY) 2022 under the measure suppression policy. This rule
also finalizes that CMS will not score facilities or reduce payment to
any facility under the ESRD QIP in PY 2022. Further, this rule
finalizes changes to the ESRD Treatment Choices (ETC) Model, which is a
mandatory payment model that is focused on encouraging greater use of
home dialysis and kidney transplants, to reduce Medicare expenditures
while preserving or enhancing the quality of care furnished to Medicare
beneficiaries.
DATES: These regulations are effective on January 1, 2022.
FOR FURTHER INFORMATION CONTACT:
[email protected], for issues related to the ESRD PPS and
coverage and payment for renal dialysis services furnished to
individuals with AKI.
[email protected], for issues related to the
Transitional Add-On Payment Adjustment for New and Innovative Equipment
and Supplies (TPNIES).
Delia Houseal, (410) 786-2724, for issues related to the ESRD QIP.
[email protected], for issues related to the ESRD Treatment
Choices (ETC) Model.
SUPPLEMENTARY INFORMATION: Current Procedural Terminology (CPT)
Copyright Notice: Throughout this final rule, we use CPT[supreg] codes
and descriptions to refer to a variety of services. We note that
CPT[supreg] codes and descriptions are copyright 2020 American Medical
Association (AMA). All Rights Reserved. CPT[supreg] is a registered
trademark of the AMA. Applicable Federal Acquisition Regulations (FAR)
and Defense Federal Acquisition Regulations (DFAR) apply.
Table of Contents
To assist readers in referencing sections contained in this
preamble, we are providing a Table of Contents.
I. Executive Summary
A. Purpose
B. Summary of the Major Provisions
C. Summary of Cost and Benefits
II. Calendar Year (CY) 2022 End-Stage Renal Disease (ESRD)
Prospective Payment System (PPS)
A. Background
B. Provisions of the Proposed Rule, Public Comments, and
Responses to the Comments on the CY 2022 ESRD PPS
C. Transitional Add-On Payment Adjustment for New and Innovative
Equipment and Supplies (TPNIES) for CY 2022 Payment
III. Calendar Year (CY) 2022 Payment for Renal Dialysis Services
Furnished to Individuals With Acute Kidney Injury (AKI)
A. Background
B. Summary of the Proposed Provisions, Public Comments, and
Responses to Comments on the CY 2022 Payment for Renal Dialysis
Services Furnished to Individuals With AKI
C. Annual Payment Rate Update for CY 2022
IV. End-Stage Renal Disease Quality Incentive Program (ESRD QIP)
A. Background
B. Extraordinary Circumstances Exception (ECE) Previously
Granted for the ESRD QIP Including Notification of ECE Due to ESRD
Quality Reporting System Issues
C. Flexibilities for the ESRD QIP in Response to the COVID-19
PHE
D. Special Scoring Methodology and Payment Policy for the PY
2022 ESRD QIP
E. Updates to Requirements Beginning With the PY 2024 ESRD QIP
F. Updates for the PY 2025 ESRD QIP
G. Requests for Information (RFIs) on Topics Relevant to ESRD
QIP
V. End-Stage Renal Disease Treatment Choices (ETC) Model
A. Background
B. Summary of the Proposed Provisions, Public Comments, and
Responses to Comments on the ETC Model
C. Requests for Information (RFIs) on Topics Relevant to ETC
Model
VI. Requests for Information
A. Informing Payment Reform Under the ESRD PPS
B. Public Input to the ESRD PPS RFI Topics
C. Response to the Public Input for the CY 2022 ESRD PPS RFIs
VII. Collection of Information Requirements
A. Legislative Requirement for Solicitation of Comments
B. Requirements in Regulation Text
C. Additional Information Collection Requirements
VIII. Regulatory Impact Analysis
A. Impact Analyses
B. Overall Impact
C. Detailed Economic Analysis
D. Accounting Statement
E. Regulatory Flexibility Act Analysis (RFA)
F. Unfunded Mandates Reform Act Analysis (UMRA)
G. Federalism
H. Congressional Review Act
IX. Files Available to the Public via the Internet
Regulations Text
I. Executive Summary
A. Purpose
This rule finalizes changes related to the End-Stage Renal Disease
(ESRD) Prospective Payment System (PPS), payment for renal dialysis
services furnished to individuals with acute kidney injury (AKI), the
ESRD Quality Incentive Program (QIP), and the ESRD Treatment Choices
(ETC) Model.
1. End-Stage Renal Disease (ESRD) Prospective Payment System (PPS)
On January 1, 2011, we implemented the End-Stage Renal Disease
(ESRD) Prospective Payment System (PPS), a case-mix adjusted, bundled
PPS for renal dialysis services furnished by ESRD facilities as
required by section 1881(b)(14) of the Social Security Act (the Act),
as added by section 153(b) of the Medicare Improvements for Patients
and Providers Act of 2008 (MIPPA) (Pub. L. 110-275). Section
1881(b)(14)(F) of the Act, as added by section 153(b) of MIPPA, and
amended by section 3401(h) of the Patient Protection and Affordable
Care Act (the Affordable Care Act) (Pub. L. 111-148), established that
beginning calendar year (CY) 2012, and each subsequent year, the
Secretary of the Department of Health and Human Services (the
Secretary) shall annually increase payment amounts by an ESRD market
basket increase factor, reduced by the productivity adjustment
described in section 1886(b)(3)(B)(xi)(II) of the Act. This rule
updates the ESRD PPS for CY 2022.
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2. Coverage and Payment for Renal Dialysis Services Furnished to
Individuals With Acute Kidney Injury (AKI)
On June 29, 2015, the President signed the Trade Preferences
Extension Act of 2015 (TPEA) (Pub. L. 114-27). Section 808(a) of the
TPEA amended section 1861(s)(2)(F) of the Act to provide coverage for
renal dialysis services furnished on or after January 1, 2017, by a
renal dialysis facility or a provider of services paid under section
1881(b)(14) of the Act to an individual with acute kidney injury (AKI).
Section 808(b) of the TPEA amended section 1834 of the Act by adding a
new subsection (r) that provides for payment for renal dialysis
services furnished by renal dialysis facilities or providers of
services paid under section 1881(b)(14) of the Act to individuals with
AKI at the ESRD PPS base rate beginning January 1, 2017. This rule
updates the AKI payment rate for CY 2022.
3. End-Stage Renal Disease Quality Incentive Program (ESRD QIP)
The End-Stage Renal Disease Quality Incentive Program (ESRD QIP) is
authorized by section 1881(h) of the Act. The Program fosters improved
patient outcomes by establishing incentives for dialysis facilities to
meet or exceed performance standards established by the Centers for
Medicare & Medicaid Services (CMS). This rule finalizes our proposals
to suppress the use of certain ESRD QIP measure data for scoring and
payment adjustment purposes in the PY 2022 ESRD QIP because we have
determined that circumstances caused by the Public Health Emergency
(PHE) for the coronavirus disease 2019 (COVID-19) pandemic have
significantly affected the validity and reliability of the measures and
resulting performance scores, as well as special scoring and payment
policies for PY 2022. We are also finalizing our proposal to update the
specifications for the SHR clinical measure beginning with the PY 2024
ESRD QIP. We are also finalizing our proposal to use CY 2019 data to
calculate the PY 2024 ESRD QIP performance standards. This final rule
further describes policies that will apply for PY 2025. Finally, this
final rule describes several requests for information that also
appeared in the CY 2022 ESRD PPS proposed rule. These requests for
information solicited stakeholder feedback on several important topics,
including strategies that we can use to address the gap in existing
health inequities, the addition of COVID-19 vaccination measures in
future rulemaking, and the use of digital quality measurement.
4. End-Stage Renal Disease Treatment Choices (ETC) Model
This rule finalizes changes to the End-Stage Renal Disease (ESRD)
Treatment Choices Model (ETC) Model, a mandatory Medicare payment model
tested under the authority of section 1115A of the Act. The ETC Model
is operated by the Center for Medicare and Medicaid Innovation
(Innovation Center), and tests the use of payment adjustments to
encourage greater utilization of home dialysis and kidney transplants,
in order to preserve or enhance the quality of care furnished to
Medicare beneficiaries while reducing Medicare expenditures. The ETC
Model includes ESRD facilities and certain clinicians caring for
beneficiaries with ESRD--or Managing Clinicians--located in Selected
Geographic Areas as participants.
The ETC Model was finalized as part of a final rule published in
the Federal Register on September 29, 2020, titled, ``Medicare Program;
Specialty Care Models to Improve Quality of Care and Reduce
Expenditures'' (85 FR 61114), referred to herein as the ``Specialty
Care Models final rule.'' The ETC Model is designed to test the
effectiveness of adjusting certain Medicare payments to ETC
Participants (ESRD facilities and Managing Clinicians--clinicians who
furnish and bill the Monthly Capitation Payment (MCP) for managing ESRD
Beneficiaries--who have been selected to participate in the ETC Model)
to encourage greater utilization of home dialysis and kidney
transplantation, support beneficiary modality choice, reduce Medicare
expenditures, and preserve or enhance the quality of care. In the
Specialty Care Models final rule, we established that the ETC Model
adjusts payments for home dialysis and home dialysis-related claims
with claim service dates from January 1, 2021 through December 31, 2023
through the Home Dialysis Payment Adjustment (HDPA). We are assessing
the rates of home dialysis and of kidney transplant waitlisting and
living donor transplantation, among beneficiaries attributed to ETC
Participants during the period beginning January 1, 2021, and ending
June 30, 2026. Based on those rates, we are applying the Performance
Payment Adjustment (PPA) to claims for dialysis and dialysis-related
services with claim service dates beginning July 1, 2022, and ending
June 30, 2027. We codified these provisions in a new subpart of the
Code of Federal Regulations (CFR) 42 CFR part 512, subpart C.
This final rule includes modifications to the ETC Model, including
changes to the home dialysis rate and transplant rate, the PPA
achievement benchmarking methodology, and the PPA improvement
benchmarking and scoring methodology. We are also adding processes and
requirements for ETC Participants to receive certain data from CMS and
including certain additional waivers and flexibilities as part of the
ETC Model test.
B. Summary of the Major Provisions
1. ESRD PPS
Update to the ESRD PPS base rate for CY 2022: The final CY
2022 ESRD PPS base rate is $257.90. This amount reflects the
application of the wage index budget-neutrality adjustment factor
(0.99985) and a productivity-adjusted market basket increase of 1.9
percent as required by section 1881(b)(14)(F)(i)(I) of the Act,
equaling $257.90 (($253.13 x 0.99985) x 1.019 = $257.90).
Annual update to the wage index: We adjust wage indices on
an annual basis using the most current hospital wage data and the
latest core-based statistical area (CBSA) delineations to account for
differing wage levels in areas in which ESRD facilities are located.
For CY 2022, we are updating the wage index values based on the latest
available data and continuing the 2-year transition to the Office of
Management and Budget (OMB) delineations as described in the September
14, 2018 OMB Bulletin No. 18-04.
Update to the outlier policy: We are updating the outlier
policy using the most current data, as well as updating the outlier
services fixed-dollar loss (FDL) amounts for adult and pediatric
patients and Medicare allowable payment (MAP) amounts for adult and
pediatric patients for CY 2022 using CY 2020 claims data. Based on the
use of the latest available data, the final FDL amount for pediatric
beneficiaries will decrease from $44.78 to $26.02, and the MAP amount
will decrease from $30.88 to $27.15, as compared to CY 2021 values. For
adult beneficiaries, the final FDL amount will decrease from $122.49 to
$75.39, and the MAP amount will decrease from $50.92 to $42.75. The 1.0
percent target for outlier payments was not achieved in CY 2020.
Outlier payments represented approximately 0.6 percent of total
payments rather than 1.0 percent.
Update to the offset amount for the transitional add-on
payment adjustment for new and innovative equipment and supplies
(TPNIES) for CY 2022: The
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final CY 2022 average per treatment offset amount for the transitional
add-on payment adjustment for new and innovative equipment and supplies
(TPNIES) for capital-related assets that are home dialysis machines is
$9.50. This offset amount reflects the application of the productivity-
adjusted market basket increase of 1.9 percent ($9.32 x 1.019 = $9.50).
TPNIES applications received for CY 2022: In this final
rule, we announce our determination on the one TPNIES application under
consideration for the TPNIES for CY 2022 payment.
2. Payment for Renal Dialysis Services Furnished to Individuals With
AKI
We are updating the AKI payment rate for CY 2022. The final CY 2022
payment rate is $257.90, which is the same as the base rate finalized
under the ESRD PPS for CY 2022.
3. ESRD QIP
We are adopting a measure suppression policy for the duration of
the COVID-19 PHE that enables us to suppress the use of one or more
measures in the ESRD QIP for scoring and payment adjustment purposes if
we determine that circumstances caused by the COVID-19 PHE have
significantly affected the measures and resulting performance scores.
We are also finalizing our proposal to suppress the Standardized
Hospitalization Ratio (SHR) clinical measure, the Standardized
Readmission Ratio (SRR) clinical measure, the In-Center Hemodialysis
Consumer Assessment of Healthcare Providers and Systems (ICH CAHPS)
clinical measure, and the Long-Term Catheter Rate clinical measure for
PY 2022 under the measure suppression policy. We are also finalizing
our proposal to not score or reduce payment to any facility in PY 2022.
We are finalizing our proposal to update the specifications for the SHR
clinical measure beginning with the PY 2024 ESRD QIP. We are also
finalizing our proposal for the PY 2024 ESRD QIP to use CY 2019 data to
calculate the performance standards for that payment year. This final
rule also announces the performance standards and estimated payment
reductions that will apply for PY 2024. This final rule describes
several policies continuing for PY 2025, but does not include any new
requirements beginning with the PY 2025 ESRD QIP.
This final rule includes public comments received in response to
requests for information that appeared in the CY 2022 ESRD PPS proposed
rule. In those requests for information, we solicited stakeholder
feedback on several important topics, including closing the gap in
health equity, adding a COVID-19 vaccination measure for health care
personnel (HCP) to the ESRD QIP measure set in future rulemaking,
adding a COVID-19 vaccination measure for ESRD patients to the ESRD QIP
measure set in future rulemaking, and potential actions and priority
areas that would enable us to continue moving toward a greater digital
capture of data and use of the Fast Healthcare Interoperability
Resources (FHIR[supreg]) standard in quality measurement.
4. ETC Model
We are implementing the following changes to the ETC Model
beginning for the third Measurement Year (MY3) of the Model, which
begins January 1, 2022.
Beneficiary Attribution for Living Kidney Donor
Transplants: To better reflect the care relationship between
beneficiaries who receive pre-emptive living donor transplants (LDT)
and the Managing Clinicians who provide their care, we are modifying
the methodology for attributing Pre-emptive LDT Beneficiaries to
Managing Clinicians, such that a Pre-emptive LDT Beneficiary will be
attributed to the Managing Clinician who submitted the most claims for
services furnished to the beneficiary during the 365 days prior to the
transplant date.
Home Dialysis Rate Calculation: To incentivize additional
alternative renal replacement modalities under the ETC Model, we are
adding nocturnal in-center dialysis to the calculation of the home
dialysis rate for ESRD facilities and Managing Clinicians.
Transplant Rate Beneficiary Exclusion: To better align
with common reasons transplant centers do not place patients on the
transplant waitlist, we are excluding beneficiaries with a diagnosis
of, and who are receiving treatment with chemotherapy or radiation for,
vital solid organ cancers from the calculation of the transplant rate.
Performance Payment Adjustment Achievement Benchmarking
Methodology: When we originally finalized the ETC Model, we stated our
intent to increase achievement benchmarks above rates observed in
Comparison Geographic Areas for future model years. As such, we will
increase achievement benchmarks by 10 percent over rates observed in
Comparison Geographic Areas every two MYs, beginning in MY3 (2022). We
also will stratify achievement benchmarks based on the proportion of
attributed beneficiaries who are dually-eligible for Medicare and
Medicaid or receive the Low Income Subsidy (LIS) during the MY, in
recognition that beneficiaries with lower socioeconomic status have
lower rates of home dialysis and transplant than those with higher
socioeconomic status.
Performance Payment Adjustment Improvement Benchmarking
and Scoring: In conjunction with the stratification of the achievement
benchmarks based on the proportion of beneficiaries who are dual-
eligible or LIS recipients, we will introduce the Health Equity
Incentive to the improvement scoring methodology used in calculating
the PPA. CMS expects that the Health Equity Incentive will encourage
ETC Participants to decrease disparities in renal replacement modality
choice among beneficiaries with lower socioeconomic status by rewarding
ETC Participants that demonstrate significant improvement in the home
dialysis rate or transplant rate among their attributed beneficiaries
who are dual-eligible or LIS recipients. We also will adjust the
improvement scoring calculation to avoid the scenario where an ETC
Participant cannot receive an improvement score because its home
dialysis rate or transplant rate was zero during the Benchmark Year.
Performance Payment Adjustment Reports and Related Data
Sharing: To ensure that ETC Participants have timely access to ETC
Model reports, we are establishing a process under which CMS will share
certain model data with ETC Participants.
Medicare Waivers: We are including an additional
programmatic waiver to provide Managing Clinicians who are ETC
Participants additional flexibility in furnishing the kidney disease
patient education services described in Sec. 410.48, namely a waiver
of certain telehealth requirements as necessary solely for purposes of
allowing ETC Participants to furnish kidney disease patient education
services via telehealth under the ETC Model to take effect at the end
of the COVID-19 PHE.
Kidney Disease Patient Education Services Coinsurance
Waivers: We will permit Managing Clinicians who are ETC Participants to
reduce or waive the beneficiary coinsurance for kidney disease patient
education services, subject to certain requirements. We have made the
determination that the anti-kickback statute safe harbor for CMS-
sponsored model patient incentives (42 CFR 1001.952(ii)(2)), will be
available to protect the reduction or elimination of coinsurance that
is made in compliance with our policy.
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C. Summary of Costs and Benefits
In section VIII.C.5 of this final rule, we set forth a detailed
analysis of the impacts that the changes will have on affected entities
and beneficiaries. The impacts include the following:
1. Impacts of the Final ESRD PPS
The impact table in section VIII.C.5.a of this final rule displays
the estimated change in payments to ESRD facilities in CY 2022 compared
to estimated payments in CY 2021. The overall impact of the CY 2022
changes is projected to be a 2.5 percent increase in payments.
Hospital-based ESRD facilities have an estimated 3.3 percent increase
in payments compared with freestanding facilities with an estimated 2.5
percent increase. We estimate that the aggregate ESRD PPS expenditures
will increase by approximately $290 million in CY 2022 compared to CY
2021. This reflects a $220 million increase from the payment rate
update, a $70 million increase due to the updates to the outlier
threshold amounts, and approximately $2.5 million in estimated TPNIES
payment amounts, as further described in the next paragraph. Because of
the projected 2.5 percent overall payment increase, we estimate there
will be an increase in beneficiary coinsurance payments of 2.5 percent
in CY 2022, which translates to approximately $60 million.
Section 1881(b)(14)(D)(iv) of the Act provides that the ESRD PPS
may include such other payment adjustments as the Secretary determines
appropriate. Under this authority, CMS implemented Sec. 413.236 to
establish the TPNIES, a transitional add-on payment adjustment for new
and innovative equipment and supplies, which is not budget neutral. As
discussed in section II.C.1.a. of this final rule, we have determined
that the Tablo[supreg] System, a hemodialysis machine that has FDA
authorization for home use, has met the criteria for the TPNIES for CY
2022 payment. We estimate that the overall TPNIES payment amounts in CY
2022 would be approximately $2.5 million, of which, approximately
$490,000 would be attributed to beneficiary coinsurance amounts.
2. Impacts of the Final Payment for Renal Dialysis Services Furnished
to Individuals With AKI
The impact table in section VIII.C.5.b of this final rule displays
the estimated change in payments to ESRD facilities in CY 2022 compared
to estimated payments in CY 2021. The overall impact of the CY 2022
changes is projected to be a 1.9 percent increase in payments for
individuals with AKI. Hospital-based ESRD facilities have an estimated
2.0 percent increase in payments compared with freestanding ESRD
facilities with an estimated 1.9 percent increase. The overall impact
reflects the effects of the updated wage index and the final payment
rate update. We estimate that the aggregate payments made to ESRD
facilities for renal dialysis services furnished to patients with AKI,
at the final CY 2022 ESRD PPS base rate, will increase by $1 million in
CY 2022 compared to CY 2021.
3. Impacts of the ESRD QIP
Our finalized policy to suppress measures for the PY 2022 ESRD QIP
and to revise the scoring and payment methodology such that no facility
will receive a payment reduction necessitated a modification to our
previous estimated overall economic impact of the PY 2022 ESRD QIP (84
FR 60651). In the CY 2020 ESRD PPS final rule, we estimated that the
overall economic impact of the PY 2022 ESRD QIP would be approximately
$229 million as a result of the policies we had finalized at that time.
The $229 million figure for PY 2022 included costs associated with the
collection of information requirements, which we estimated would be
approximately $211 million, and $18 million in estimated payment
reductions across all facilities. However, as a result of the policies
we are finalizing in this final rule for the PY 2022 ESRD QIP, we are
modifying our previous estimate for PY 2022. We estimate that the new
overall economic impact of the PY 2022 ESRD QIP will be approximately
$215 million. The $215 million figure for PY 2022 only includes the
costs associated with the collection of information requirements
because there will be no payment reductions in PY 2022. We estimate
that the overall economic impact of the PY 2024 ESRD QIP will be
approximately $232 million, of which $215 million is associated with
the collection of information requirements and $17 million is
associated with the estimated payment reductions across all facilities.
We also estimate that the overall economic impact of the PY 2025 ESRD
QIP will be approximately $232 million.
4. Impacts of Changes to the ETC Model
The impact estimate in section VIII.B.4 of this final rule
describes the estimated change in anticipated Medicare program savings
arising from the ETC Model over the duration of the ETC Model as a
result of the changes in this final rule. We estimate that the ETC
Model will result in $28 million in net savings over the 6.5-year
duration of the ETC Model. We also estimate that $5 million of the
estimated $28 million in net savings will be attributable to changes in
this final rule.
II. Calendar Year (CY) 2022 End-Stage Renal Disease (ESRD) Prospective
Payment System (PPS)
A. Background
1. Statutory Background
On January 1, 2011, the Centers for Medicare & Medicaid Services
(CMS) implemented the End-Stage Renal Disease (ESRD) Prospective
Payment System (PPS), a case-mix adjusted bundled PPS for renal
dialysis services furnished by ESRD facilities, as required by section
1881(b)(14) of the Social Security Act (the Act), as added by section
153(b) of the Medicare Improvements for Patients and Providers Act of
2008 (MIPPA). Section 1881(b)(14)(F) of the Act, as added by section
153(b) of MIPPA and amended by section 3401(h) of the Patient
Protection and Affordable Care Act (the Affordable Care Act),
established that beginning with CY 2012, and each subsequent year, the
Secretary of the Department of Health and Human Services (the
Secretary) shall annually increase payment amounts by an ESRD market
basket increase factor reduced by the productivity adjustment described
in section 1886(b)(3)(B)(xi)(II) of the Act.
Section 632 of the American Taxpayer Relief Act of 2012 (ATRA)
(Pub. L. 112-240) included several provisions that apply to the ESRD
PPS. Section 632(a) of ATRA added section 1881(b)(14)(I) to the Act,
which required the Secretary, by comparing per patient utilization data
from 2007 with such data from 2012, to reduce the single payment for
renal dialysis services furnished on or after January 1, 2014 to
reflect the Secretary's estimate of the change in the utilization of
ESRD-related drugs and biologicals (excluding oral-only ESRD-related
drugs). Consistent with this requirement, in the CY 2014 ESRD PPS final
rule we finalized $29.93 as the total drug utilization reduction and
finalized a policy to implement the amount over a 3- to 4-year
transition period (78 FR 72161 through 72170).
Section 632(b) of ATRA prohibited the Secretary from paying for
oral-only ESRD-related drugs and biologicals under the ESRD PPS prior
to January 1, 2016. Section 632(c) of ATRA required the Secretary, by
no later than January 1, 2016, to analyze the case-mix payment
adjustments under section 1881(b)(14)(D)(i) of the Act and make
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appropriate revisions to those adjustments.
On April 1, 2014, the Protecting Access to Medicare Act of 2014
(PAMA) (Pub. L. 113-93) was enacted. Section 217 of PAMA included
several provisions that apply to the ESRD PPS. Specifically, sections
217(b)(1) and (2) of PAMA amended sections 1881(b)(14)(F) and (I) of
the Act and replaced the drug utilization adjustment that was finalized
in the CY 2014 ESRD PPS final rule (78 FR 72161 through 72170) with
specific provisions that dictated the market basket update for CY 2015
(0.0 percent) and how the market basket should be reduced in CY 2016
through CY 2018.
Section 217(a)(1) of PAMA amended section 632(b)(1) of ATRA to
provide that the Secretary may not pay for oral-only ESRD-related drugs
under the ESRD PPS prior to January 1, 2024. Section 217(a)(2) of PAMA
further amended section 632(b)(1) of ATRA by requiring that in
establishing payment for oral-only drugs under the ESRD PPS, the
Secretary must use data from the most recent year available. Section
217(c) of PAMA provided that as part of the CY 2016 ESRD PPS
rulemaking, the Secretary shall establish a process for (1) determining
when a product is no longer an oral-only drug; and (2) including new
injectable and intravenous products into the ESRD PPS bundled payment.
Finally, on December 19, 2014, the President signed the Stephen
Beck, Jr., Achieving a Better Life Experience Act of 2014 (ABLE) (Pub.
L. 113-295). Section 204 of ABLE amended section 632(b)(1) of ATRA, as
amended by section 217(a)(1) of PAMA, to provide that payment for oral-
only renal dialysis services cannot be made under the ESRD PPS bundled
payment prior to January 1, 2025.
2. System for Payment of Renal Dialysis Services
Under the ESRD PPS, a single per-treatment payment is made to an
ESRD facility for all the renal dialysis services defined in section
1881(b)(14)(B) of the Act and furnished to individuals for the
treatment of ESRD in the ESRD facility or in a patient's home. We have
codified our definition of renal dialysis services at Sec. 413.171,
which is in 42 CFR part 413, subpart H, along with other ESRD PPS
payment policies. The ESRD PPS base rate is adjusted for
characteristics of both adult and pediatric patients and accounts for
patient case-mix variability. The adult case-mix adjusters include five
categories of age, body surface area, low body mass index, onset of
dialysis, and four comorbidity categories (that is, pericarditis,
gastrointestinal tract bleeding, hereditary hemolytic or sickle cell
anemia, myelodysplastic syndrome). A different set of case-mix
adjusters are applied for the pediatric population. Pediatric patient-
level adjusters include two age categories (under age 22, or age 22-26)
and two dialysis modalities (that is, peritoneal or hemodialysis)
(Sec. 413.235(a) and (b)).
The ESRD PPS provides for three facility-level adjustments. The
first payment adjustment accounts for ESRD facilities furnishing a low
volume of dialysis treatments (Sec. 413.232). The second adjustment
reflects differences in area wage levels developed from core-based
statistical areas (CBSAs) (Sec. 413.231). The third payment adjustment
accounts for ESRD facilities furnishing renal dialysis services in a
rural area (Sec. 413.233).
There are four additional payment adjustments under the ESRD PPS.
The ESRD PPS provides adjustments, when applicable, for: (1) A training
add-on for home and self-dialysis modalities (Sec. 413.235(c)); (2) an
additional payment for high cost outliers due to unusual variations in
the type or amount of medically necessary care (Sec. 413.237); (3) a
transitional drug add-on payment adjustment (TDAPA) for certain new
renal dialysis drugs and biological products (Sec. 413.234(c)); and
(4) a transitional add-on payment adjustment for new and innovative
equipment and supplies (TPNIES) for certain qualifying, new and
innovative renal dialysis equipment and supplies (Sec. 413.236(d)).
3. Updates to the ESRD PPS
Policy changes to the ESRD PPS are proposed and finalized annually
in the Federal Register. The CY 2011 ESRD PPS final rule was published
on August 12, 2010 in the Federal Register (75 FR 49030 through 49214).
That rule implemented the ESRD PPS beginning on January 1, 2011 in
accordance with section 1881(b)(14) of the Act, as added by section
153(b) of MIPPA, over a 4-year transition period. Since the
implementation of the ESRD PPS, we have published annual rules to make
routine updates, policy changes, and clarifications.
On November 9, 2020, we published a final rule in the Federal
Register titled, ``Medicare Program; End-Stage Renal Disease
Prospective Payment System, Payment for Renal Dialysis Services
Furnished to Individuals With Acute Kidney Injury, and End-Stage Renal
Disease Quality Incentive Program,'' referred to herein as the ``CY
2021 ESRD PPS final rule''. In that rule, we updated the ESRD PPS base
rate, wage index, and outlier policy, for CY 2021. We also finalized an
update to the ESRD PPS wage index to adopt the 2018 OMB delineations
with a transition period, changes to the eligibility criteria and
determination process for the TPNIES, an expansion of the TPNIES to
include certain new and innovative capital-related assets that are home
dialysis machines, an addition to the ESRD PPS base rate to include
calcimimetics in the ESRD PPS bundled payment, and a change to the low-
volume payment adjustment eligibility criteria and attestation
requirement to account for the coronavirus disease 2019 (COVID-19)
Public Health Emergency (PHE). For further detailed information
regarding these updates, see 85 FR 71398.
B. Provisions of the Proposed Rule, Public Comments, and Responses to
the Comments on the CY 2022 ESRD PPS
The proposed rule, titled ``Medicare Program; End-Stage Renal
Disease Prospective Payment System, Payment for Renal Dialysis Services
Furnished to Individuals With Acute Kidney Injury, End-Stage Renal
Disease Quality Incentive Program, and End-Stage Renal Disease
Treatment Choices Model'' (86 FR 36322 through 36437), referred to as
the ``CY 2022 ESRD PPS proposed rule,'' was published in the Federal
Register on July 9, 2021, with a comment period that ended on August
31, 2021. In that proposed rule, we proposed to make a number of annual
updates for CY 2022, including updates to the ESRD PPS base rate, wage
index, outlier policy, and the offset amount for TPNIES for capital-
related assets that are home dialysis machines used in the home. The
proposed rule presented a summary of the two CY 2022 TPNIES
applications that we received by the February 1, 2021 deadline and our
analysis of the applicants' claims related to substantial clinical
improvement (SCI) and other eligibility criteria for the TPNIES.
We received 286 public comments on our proposals, including
comments from kidney and dialysis organizations, such as large and
small dialysis organizations, for-profit and non-profit ESRD
facilities, ESRD networks, and a dialysis coalition. We also received
comments from patients; healthcare providers for adult and pediatric
ESRD beneficiaries; home dialysis services and advocacy organizations;
provider and legal advocacy organizations; administrators and insurance
groups; a non-profit dialysis association, a professional association,
and alliances for kidney care and home dialysis stakeholders; drug and
device manufacturers; health care systems; a
[[Page 61879]]
health solutions company; and the Medicare Payment Advisory Commission
(MedPAC).
In this final rule, we provide a summary of each proposed
provision, a summary of the public comments received and our responses
to them, and the policies we are finalizing for the CY 2022 ESRD PPS.
1. CY 2022 ESRD PPS Update
a. CY 2022 ESRD Bundled (ESRDB) Market Basket Update, Productivity
Adjustment, and Labor-Related Share
In accordance with section 1881(b)(14)(F)(i) of the Act, as added
by section 153(b) of MIPPA and amended by section 3401(h) of the
Affordable Care Act, beginning in 2012, the ESRD PPS payment amounts
are required to be annually increased by an ESRD market basket increase
factor and reduced by the productivity adjustment described in section
1886(b)(3)(B)(xi)(II) of the Act. The application of the productivity
adjustment may result in the increase factor being less than 0.0
percent for a year and may result in payment rates for a year being
less than the payment rates for the preceding year. The statute also
provides that the market basket increase factor should reflect the
changes over time in the prices of an appropriate mix of goods and
services used to furnish renal dialysis services.
As required under section 1881(b)(14)(F)(i) of the Act, CMS
developed an all-inclusive ESRD Bundled (ESRDB) input price index (75
FR 49151 through 49162). In the CY 2015 ESRD PPS final rule, we rebased
and revised the ESRDB input price index to reflect a 2012 base year (79
FR 66129 through 66136). Subsequently, in the CY 2019 ESRD PPS final
rule, we finalized a rebased ESRDB input price index to reflect a 2016
base year (83 FR 56951 through 56962).
Although ``market basket'' technically describes the mix of goods
and services used for ESRD treatment, this term is also commonly used
to denote the input price index (that is, cost categories, their
respective weights, and price proxies combined) derived from a market
basket. Accordingly, the term ``ESRDB market basket,'' as used in this
document, refers to the ESRDB input price index.
We proposed to use the CY 2016-based ESRDB market basket as
finalized and described in the CY 2019 ESRD PPS final rule (83 FR 56951
through 56962) to compute the CY 2022 ESRDB market basket increase
factor based on the best available data. Consistent with historical
practice, we proposed to estimate the ESRDB market basket update based
on IHS Global Inc.'s (IGI's) forecast using the most recently available
data. IGI is a nationally recognized economic and financial forecasting
firm with which we contract to forecast the components of the market
baskets. Using this methodology and the IGI first quarter 2021 forecast
of the CY 2016-based ESRDB market basket (with historical data through
the fourth quarter of 2020), the proposed CY 2022 ESRDB market basket
increase factor was 1.6 percent.
Under section 1881(b)(14)(F)(i) of the Act, for CY 2012 and each
subsequent year, the ESRD market basket percentage increase factor
shall be reduced by the productivity adjustment described in section
1886(b)(3)(B)(xi)(II) of the Act. The productivity adjustment is
calculated using a projection of multifactor productivity (MFP), which
is derived by subtracting the contribution of labor and capital input
growth from output growth. We finalized the detailed methodology for
deriving the projection of MFP in the CY 2012 ESRD PPS final rule (76
FR 40503 through 40504). The most up-to-date MFP projection methodology
is available on the CMS website at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/Downloads/MFPMethodology.pdf. We noted in the
CY 2022 ESRD PPS proposed rule that for CY 2022 and beyond, we are
changing the name of this adjustment to refer to it as the productivity
adjustment, which is the term used in sections 1881(b)(14)(F)(i) and
1886(b)(3)(B)(xi)(II) of the Act, rather than the multifactor
productivity or MFP adjustment. This is not a change in policy, as we
will continue to use the same methodology for deriving the adjustment
and rely on the same underlying data. Using this methodology and the
IGI first quarter 2021 forecast, the proposed productivity adjustment
for CY 2022 (the 10-year moving average of MFP for the period ending CY
2022) was 0.6 percent.
As a result of these provisions, the proposed CY 2022 ESRD market
basket increase factor reduced by the productivity adjustment was 1.0
percent. The proposed market basket increase factor is calculated by
starting with the proposed CY 2022 ESRDB market basket percentage
increase factor of 1.6 percent and reducing it by the proposed
productivity adjustment (the 10-year moving average of MFP for the
period ending CY 2022) of 0.6 percent.
As is our general practice, we proposed that if more recent data
became available after the publication of the proposed rule and before
the publication of the final rule (for example, a more recent estimate
of the CY 2016-based ESRD market basket increase factor or productivity
adjustment), we would use such data, if appropriate, to determine the
final CY 2022 market basket update and productivity adjustment in this
final rule (85 FR 36327).
We invited public comment on our proposals for the CY 2022 ESRD
market basket update and productivity adjustment. The following is a
summary of the public comments received on these proposals and our
responses.
Comment: Several commenters encouraged CMS to examine the data
sources and other elements to ensure that the market basket update
reflects ESRD facilities' current experience. The commenters stated
that while they understand CMS must follow the statutory framework for
the annual market basket update, they believe that the proposed CY 2022
market basket update appears low given inflation and rising expenses
including rent and labor. Several commenters expressed that they
support the proposed ESRD PPS annual payment rate update for CY 2022
and support the use of more recent data for the market basket update
and productivity adjustment, if available, to determine the final
update factors for CY 2022. MedPAC commented that while it recognizes
that CMS must provide the statutorily mandated payment update of the
market basket minus the productivity adjustment, the Commission has
concluded that this increase is not warranted based on their analysis
of payment adequacy, which includes an assessment of beneficiary
access, supply of ESRD facilities, and ESRD facilities' access to
capital, quality, and financial indicators for the sector. MedPAC
further recommended that Congress should eliminate the update to the
ESRD PPS base rate for CY 2022.
Response: We acknowledge the concerns of some of the commenters and
appreciate the support of some of the commenters regarding the proposed
ESRD PPS annual payment rate update and use of more recent data to
determine the market basket and productivity adjustment in
determination of the final update factor. We also appreciate MedPAC's
comments but note that the ESRD market basket increase factor is
mandated by statute. For this final rule, we have incorporated more
current historical data and revised forecasts provided by IGI that
factor in expected price and wage pressures. By incorporating the most
recent estimates available of the market basket update
[[Page 61880]]
and productivity adjustment, we believe these data reflect the best
available projection of input price inflation faced by ESRD facilities
for CY 2022, adjusted for economy-wide productivity, which is required
by statute. As stated previously in this section of the final rule,
consistent with our proposal to use more recent data, the CY 2022 ESRD
market basket increase factor is 1.9 percent based on the more recent
IGI third quarter 2021 forecast.
Comment: A few commenters noted that while they understand that the
productivity adjustment is statutorily required, they believe that the
experience of ESRD facilities argues against the idea that productivity
can be improved year-over-year.
Response: We acknowledge the commenters' concerns regarding
productivity growth at the economy-wide level and its application to
ESRD facilities. As the commenter acknowledges, however, section
1881(b)(14)(F)(i) of the Act requires the application of the
productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of
the Act to the ESRD PPS market basket increase factor for 2012 and
subsequent years. We will continue to monitor the impact of the payment
updates, including the effects of the productivity adjustment, on ESRD
provider margins as well as beneficiary access to care as reported by
MedPAC.
Comment: One commenter recommended CMS replace the current price
proxy for the non-Erythropoietin Stimulating Agents (ESA)
Pharmaceutical cost weight in the 2016-based ESRD market basket
Producer Price Index (PPI)--Commodity--Vitamin, nutrient, and hematinic
preparations) with BLS PPI Commodity Data for Chemicals and Allied
Products-Drugs and Pharmaceuticals, seasonally adjusted (BLS Series ID:
WPS063 Series). The commenter further stated that they do not believe
that the current proxy appropriately captures the price of drugs that
fall within this category as they are not over-the-counter vitamins but
prescription-only, synthesized hormones. The commenter also noted that
there are new drugs under development currently that likely will be
added to the ESRD PPS bundled payment during the next few years. The
commenter asserted that an alternative proxy for the non-ESA drugs
should be based on prescription drugs rather than the current proxy.
Response: We appreciate the commenter's suggestion and share the
commenter's desire to use the most appropriate price proxy for non-ESA
drugs in the ESRD market basket. As described in the CY 2019 ESRD PPS
final rule (83 FR 56960 through 56961), and in the CY 2021 ESRD PPS
final rule (85 FR 71428), we believe the PPI for Vitamins, Nutrients,
and Hematinic Preparation (VNHP) is the most appropriate price proxy
for non-ESA drugs and analysis of the Average Sales Price (ASP) data
for Non-ESA drugs in the ESRD PPS bundled payment suggests the trends
in the PPI VNHP trends are reasonable. We appreciate the commenter's
concern about the potential shifts in the mix of drugs within the ESRD
PPS bundled payment as new drugs enter the market. We will continue to
monitor the impact that these changes have on the relative cost share
weights and the mix of Non-ESA drugs included in the ESRD PPS bundled
payment in the ESRDB market basket, and propose changes if appropriate
in future rulemaking.
Final Rule Action: After considering the public comments,
consistent with our historical practice and our proposal, we are
estimating the market basket increase and the productivity adjustment
based on IGI's forecast using the most recent available data. Based on
IGI's third quarter 2021 forecast of the 2016-based ESRDB market basket
with historical data through the second quarter of 2021, the 2016-based
ESRDB market basket update for CY 2022 is 2.4 percent. IGI's 2021 third
quarter forecast reflects a higher CY 2022 inflationary outlook
compared to IGI's 2021 first quarter forecast, which is resulting in a
notable upward revision to the CY 2022 ESRD market basket update for
the CY 2022 ESRD PPS final rule (2.4 percent) compared to the CY 2022
ESRD PPS proposed rule (1.6 percent). As the economic impacts of the
COVID-19 pandemic ease, the relatively higher inflation is resulting in
relatively higher projected growth in wage, medical materials and
supplies, and capital prices.
Based on the more recent data available from IGI's third quarter
2021 forecast, the current estimate of the productivity adjustment for
CY 2022 (the 10-year moving average of MFP for the period ending CY
2021) is 0.5 percentage point. Therefore, the final CY 2022 ESRD market
basket adjusted for the productivity adjustment is projected to be 1.9
percent (2.4 percent market basket update reduced by 0.5 percentage
point productivity adjustment).
For the CY 2022 ESRD PPS payment update, we proposed to continue
using a labor-related share of 52.3 percent for the ESRD PPS payment,
which was finalized in the CY 2019 ESRD PPS final rule (83 FR 56963).
We invited public comment on the proposed labor-related share for CY
2022. We did not receive any comments on the proposal to continue using
a labor-related share of 52.3 percent for CY 2022 and, therefore, are
finalizing the continued use of a 52.3 percent labor-related share as
proposed.
b. CY 2022 ESRD PPS Wage Indices
(1) Background
Section 1881(b)(14)(D)(iv)(II) of the Act provides that the ESRD
PPS may include a geographic wage index payment adjustment, such as the
index referred to in section 1881(b)(12)(D) of the Act, as the
Secretary determines to be appropriate. In the CY 2011 ESRD PPS final
rule (75 FR 49200), we finalized an adjustment for wages at Sec.
413.231. Specifically, CMS adjusts the labor-related portion of the
base rate to account for geographic differences in the area wage levels
using an appropriate wage index, which reflects the relative level of
hospital wages and wage-related costs in the geographic area in which
the ESRD facility is located. We use OMB's CBSA-based geographic area
designations to define urban and rural areas and their corresponding
wage index values (75 FR 49117). OMB publishes bulletins regarding CBSA
changes, including changes to CBSA numbers and titles. The bulletins
are available online at https://www.whitehouse.gov/omb/information-for-agencies/bulletins/.
For CY 2022, we proposed to update the wage indices to account for
updated wage levels in areas in which ESRD facilities are located using
our existing methodology. We use the most recent pre-floor, pre-
reclassified hospital wage data collected annually under the inpatient
PPS. The ESRD PPS wage index values are calculated without regard to
geographic reclassifications authorized under sections 1886(d)(8) and
(d)(10) of the Act and utilize prefloor hospital data that are
unadjusted for occupational mix. For CY 2022, the updated wage data are
for hospital cost reporting periods beginning on or after October 1,
2017, and before October 1, 2018 (fiscal year [FY] 2018 cost report
data).
We have also adopted methodologies for calculating wage index
values for ESRD facilities that are located in urban and rural areas
where there is no hospital data. For a full discussion, see CY 2011 and
CY 2012 ESRD PPS final rules at 75 FR 49116 through 49117 and 76 FR
70239 through 70241, respectively. For urban areas with no hospital
data, we compute the average wage index value of all urban areas within
the State to serve as a reasonable
[[Page 61881]]
proxy for the wage index of that urban CBSA, that is, we use that value
as the wage index. For rural areas with no hospital data, we compute
the wage index using the average wage index values from all contiguous
CBSAs to represent a reasonable proxy for that rural area. We apply the
statewide urban average based on the average of all urban areas within
the State to Hinesville-Fort Stewart, Georgia (78 FR 72173), and we
apply the wage index for Guam to American Samoa and the Northern
Mariana Islands (78 FR 72172).
A wage index floor value (0.5000) is applied under the ESRD PPS as
a substitute wage index for areas with very low wage index values.
Currently, all areas with wage index values that fall below the floor
are located in Puerto Rico. However, the wage index floor value is
applicable for any area that may fall below the floor. A description of
the history of the wage index floor under the ESRD PPS can be found in
the CY 2019 ESRD PPS final rule (83 FR 56964 through 56967).
An ESRD facility's wage index is applied to the labor-related share
of the ESRD PPS base rate. In the CY 2019 ESRD PPS final rule (83 FR
56963), we finalized a labor-related share of 52.3 percent, which is
based on the 2016-based ESRDB market basket. In the CY 2021 ESRD PPS
final rule (85 FR 71436), we updated the OMB delineations as described
in the September 14, 2018 OMB Bulletin No. 18-04, beginning with the CY
2021 ESRD PPS wage index. In addition, we finalized the application of
a 5 percent cap on any decrease in an ESRD facility's wage index from
the ESRD facility's wage index from the prior CY. We finalized that the
transition would be phased in over 2 years, such that the reduction in
an ESRD facility's wage index would be capped at 5 percent in CY 2021,
and no cap would be applied to the reduction in the wage index for the
second year, CY 2022. Thus, for CY 2022, the labor-related share to
which a facility's wage index would be applied is 52.3 percent.
The comments received on the proposed CY 2022 ESRD PPS wage index
and our responses to the comments are set forth below.
Comment: A coalition of dialysis organizations and a professional
association acknowledged and supported the final phase-in of the
updated OMB delineations for CY 2022. These commenters, along with
another large dialysis organization, suggested that CMS consider ways
to better tailor the ESRD PPS wage index, including using additional
data beyond the hospital wage data. Another small dialysis organization
expressed concerns that the ESRD PPS wage index does not keep pace with
the hospital wage index, and identified several potential changes to
align the ESRD PPS wage index with the hospital wage index, including
the application of a statewide rural floor on wage indices, the
application of different labor-related share percentages for areas with
wage indices above and below 1, and allowing ESRD facilities to
reclassify to a different geographic area. Another commenter, a non-
profit kidney care alliance, expressed similar concerns and urged CMS
to promptly address these disparities between the ESRD PPS wage index
and the hospital wage index in rulemaking in the near future.
Response: We thank the commenters for their support, and we
appreciate the suggestions for improving the ESRD PPS wage index. We
did not propose changes to the ESRD PPS wage index methodology for CY
2022, and therefore we are not finalizing any changes to that
methodology in this final rule. However, we will take these comments
into consideration to potentially inform future rulemaking.
Comment: Three commenters, including a large dialysis organization,
a non-profit health insurance organization in Puerto Rico, and a
healthcare group in Puerto Rico, commented on the wage index for ESRD
facilities located in Puerto Rico. These commenters recommended that
CMS increase the wage index floor from 0.5000 to 0.5500; they noted
that in the CY 2019 ESRD PPS proposed rule, CMS reported that its own
analysis indicated that Puerto Rico's wage index likely lies between
0.5100 and 0.5500. They noted that CMS further stated that any wage
index values less than 0.5936 are considered outlier values. They
pointed out that CMS still finalized a floor at 0.50 and characterized
it as a balance between providing additional payments to affected areas
while minimizing the impact on the ESRD PPS base rate. The commenters
also recommended that CMS align the ESRD PPS wage index with the
hospital wage index by applying to the ESRD PPS wage index the policy
finalized in the FY 2020 IPPS final rule (84 FR 42326 through 42328)
that increases the wage index for hospitals with a wage index value
below the 25th percentile wage index. Two of the commenters further
suggested that CMS conduct a survey of registered nurse (RN) and health
worker wages specifically in standalone ESRD facilities in Puerto Rico
as a means for wage index reform, noting that there is specific
professional scope of practice standards for technicians in Puerto Rico
outpatient facilities. Commenters asserted that RNs must provide all
ESRD care in Puerto Rico outpatient facilities per local scope of
practice laws, and that CMS should evaluate inpatient and outpatient
facility data separately in order to get a fully accurate projection of
wage costs for ESRD providers in Puerto Rico. Another commenter
recommended that CMS evaluate policy inequities between the ESRD PPS
wage index for ESRD facilities located in Puerto Rico compared to other
states and territories, taking into consideration the unique
circumstances that affect Puerto Rico, including its shortage of
healthcare specialists and labor work force, remote geography,
transportation and freighting costs, drug pricing, and lack of
transitional care services.
Response: We thank the commenters for sharing their concerns
regarding the ESRD PPS wage index for ESRD facilities in Puerto Rico
and their suggestions for wage index reform. As noted in the CY 2018
ESRD PPS final rule (82 FR 50747) and the CY 2019 ESRD PPS final rule
(83 FR 56964 through 56967), we have received conflicting information
from commenters about the local scope of practice for RNs and other
staff impact on facility costs in Puerto Rico. Since we did not propose
any changes to the wage index floor or wage index methodology for CY
2022, we are not finalizing any changes to those policies in this final
rule. However, we appreciate the concerns that commenters have raised
and we will take these thoughtful suggestions into account when
considering future rulemaking.
Final Rule Action: We are finalizing the CY 2022 ESRD PPS wage
indices based on the latest hospital wage data as proposed. For CY
2022, the labor-related share to which a facility's wage index is
applied is 52.3 percent. As we finalized in the CY 2021 ESRD PPS final
rule (85 FR 71436), there will be no cap applied to the reduction in
the ESRD PPS wage index for CY 2022. The final CY 2022 ESRD PPS wage
index is set forth in Addendum A and is available on the CMS website at
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ESRDpayment/End-Stage-Renal-Disease-ESRD-Payment-Regulations-and-Notices. Addendum A provides a crosswalk between the CY 2021 wage index
and the CY 2022 wage index. Addendum B provides an ESRD facility level
impact analysis. Addendum B is available on the CMS website at https://
www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ESRDpayment/End-
Stage-
[[Page 61882]]
Renal-Disease-ESRD-Payment-Regulations-and-Notices.
c. CY 2022 Update to the Outlier Policy
Section 1881(b)(14)(D)(ii) of the Act requires that the ESRD PPS
include a payment adjustment for high cost outliers due to unusual
variations in the type or amount of medically necessary care, including
variability in the amount of erythropoiesis-stimulating agents (ESAs)
necessary for anemia management. Some examples of the patient
conditions that may be reflective of higher facility costs when
furnishing dialysis care would be frailty, obesity, and comorbidities,
such as secondary hyperparathyroidism. The ESRD PPS recognizes high
cost patients, and we have codified the outlier policy and our
methodology for calculating outlier payments at Sec. 413.237.
The policy provides that the following ESRD outlier items and
services are included in the ESRD PPS bundle: (1) Renal dialysis drugs
and biological products that were or would have been, prior to January
1, 2011, separately billable under Medicare Part B; (2) renal dialysis
laboratory tests that were or would have been, prior to January 1,
2011, separately billable under Medicare Part B ; (3) renal dialysis
medical/surgical supplies, including syringes, used to administer renal
dialysis drugs and biological products that were or would have been,
prior to January 1, 2011, separately billable under Medicare Part B;
(4) renal dialysis drugs and biological products that were or would
have been, prior to January 1, 2011, covered under Medicare Part D,
including renal dialysis oral-only drugs effective January 1, 2025; and
(5) renal dialysis equipment and supplies, except for capital-related
assets that are home dialysis machines (as defined in Sec.
413.236(a)(2)), that receive the transitional add-on payment adjustment
as specified in Sec. 413.236 after the payment period has ended.
In the CY 2011 ESRD PPS final rule (75 FR 49142), CMS stated that
for purposes of determining whether an ESRD facility would be eligible
for an outlier payment, it would be necessary for the facility to
identify the actual ESRD outlier services furnished to the patient by
line item (that is, date of service) on the monthly claim. Renal
dialysis drugs, laboratory tests, and medical/surgical supplies that
are recognized as outlier services were specified in Transmittal 2134,
dated January 14, 2011.\1\ Furthermore, CMS uses administrative
issuances to update the renal dialysis service items available for
outlier payment via our quarterly update CMS Change Requests, when
applicable. For example, we use these updates to identify renal
dialysis service drugs that were or would have been covered under
Medicare Part D for outlier eligibility purposes and items and services
that have been incorrectly identified as eligible outlier services.
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\1\ Transmittal 2033 issued August 20, 2010, was rescinded and
replaced by Transmittal 2094, dated November 17, 2010. Transmittal
2094 identified additional drugs and laboratory tests that may also
be eligible for ESRD outlier payment. Transmittal 2094 was rescinded
and replaced by Transmittal 2134, dated January 14, 2011, which
included one technical correction. https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/downloads/R2134CP.pdf.
---------------------------------------------------------------------------
Under Sec. 413.237, an ESRD facility is eligible for an outlier
payment if its actual or imputed Medicare Allowable Payment (MAP)
amount per treatment for ESRD outlier services exceeds a threshold. The
MAP amount represents the average incurred amount per treatment for
services that were or would have been considered separately billable
services prior to January 1, 2011. The threshold is equal to the ESRD
facility's predicted ESRD outlier services MAP amount per treatment
(which is case-mix adjusted and described in the following paragraphs)
plus the fixed-dollar loss (FDL) amount. In accordance with Sec.
413.237(c), facilities are paid 80 percent of the per treatment amount
by which the imputed MAP amount for outlier services (that is, the
actual incurred amount) exceeds this threshold. ESRD facilities are
eligible to receive outlier payments for treating both adult and
pediatric dialysis patients.
In the CY 2011 ESRD PPS final rule and codified in Sec.
413.220(b)(4), using 2007 data, we established the outlier percentage,
which is used to reduce the per treatment base rate to account for the
proportion of the estimated total payments under the ESRD PPS that are
outlier payments, at 1.0 percent of total payments (75 FR 49142 through
49143). We also established the FDL amounts that are added to the
predicted outlier services MAP amounts. The outlier services MAP
amounts and FDL amounts are different for adult and pediatric patients
due to differences in the utilization of separately billable services
among adult and pediatric patients (75 FR 49140). As we explained in
the CY 2011 ESRD PPS final rule (75 FR 49138 through 49139), the
predicted outlier services MAP amounts for a patient are determined by
multiplying the adjusted average outlier services MAP amount by the
product of the patient-specific case-mix adjusters applicable using the
outlier services payment multipliers developed from the regression
analysis used to compute the payment adjustments.
For CY 2022, we proposed that the outlier services MAP amounts and
FDL amounts would be derived from claims data from CY 2020. As we
stated in the CY 2022 ESRD PPS proposed rule (86 FR 36329), we believe
that any adjustments made to the MAP amounts under the ESRD PPS should
be based upon the most recent data year available to best predict any
future outlier payments; therefore, we proposed the outlier thresholds
for CY 2022 would be based on utilization of renal dialysis items and
services furnished under the ESRD PPS in CY 2020.
We also stated that we recognize that the utilization of ESAs and
other outlier services have continued to decline under the ESRD PPS,
and that we have lowered the MAP amounts and FDL amounts every year
under the ESRD PPS. As discussed in section II.B.1.c of this final
rule, CY 2020 claims data show outlier payments represent approximately
0.6 percent of total payments.
(1) CY 2022 Update to the Outlier Services MAP Amounts and FDL Amounts
For this final rule, the outlier services MAP amounts and FDL
amounts were updated using 2020 claims data, as we proposed to do for
CY 2022. The impact of this update is shown in Table 1, which compares
the outlier services MAP amounts and FDL amounts used for the outlier
policy in CY 2021 with the updated estimates for this final rule. The
estimates for the CY 2022 outlier policy, which are included in Column
II of Table 1, were inflation adjusted to reflect projected 2022 prices
for outlier services.
[[Page 61883]]
[GRAPHIC] [TIFF OMITTED] TR08NO21.000
As demonstrated in Table 1, the estimated FDL amount per treatment
that determines the CY 2022 outlier threshold amount for adults (Column
II; $75.39) is lower than that used for the CY 2021 outlier policy
(Column I; $122.49). The lower threshold is accompanied by a decrease
in the adjusted average MAP for outlier services from $50.92 to $42.75.
For pediatric patients, there is a decrease in the FDL amount from
$44.78 to $26.02. There is a corresponding decrease in the adjusted
average MAP for outlier services among pediatric patients, from $30.08
to $27.15.
We estimate that the percentage of patient months qualifying for
outlier payments in CY 2022 will be 7.08 percent for adult patients and
12.89 percent for pediatric patients, based on the 2020 claims data.
The outlier MAP and FDL amounts continue to be lower for pediatric
patients than adults due to the continued lower use of outlier services
(primarily reflecting lower use of ESAs and other injectable drugs).
(2) Outlier Percentage
In the CY 2011 ESRD PPS final rule (75 FR 49081) and under Sec.
413.220(b)(4), we reduced the per treatment base rate by 1 percent to
account for the proportion of the estimated total payments under the
ESRD PPS that are outlier payments as described in Sec. 413.237. Based
on the 2020 claims, outlier payments represented approximately 0.6
percent of total payments, which is below the 1 percent target due to
declines in the use of outlier services. As we stated in the CY 2022
ESRD PPS proposed rule (86 FR 36330), recalibration of the thresholds
using 2020 data is expected to result in aggregate outlier payments
close to the 1 percent target in CY 2022. We stated in the CY 2022 ESRD
PPS proposed rule that we believe the update to the outlier MAP and FDL
amounts for CY 2022 would increase payments for ESRD beneficiaries
requiring higher resource utilization. This would move us closer to
meeting our 1 percent outlier policy goal, because we are using more
current data for computing the MAP and FDL, which is more in line with
current outlier services utilization rates. We noted in the CY 2022
ESRD PPS proposed rule that recalibration of the FDL amounts would
result in no change in payments to ESRD facilities for beneficiaries
with renal dialysis items and services that are not eligible for
outlier payments.
The comments and our responses to the comments on our proposed
updates to the outlier policy are set forth below.
Comment: Several commenters suggested alternatives to our proposed
outlier MAP amounts, FDL amounts, and outlier percentage target for CY
2022. One large dialysis organization commented in support of using the
most recent available CY 2020 claims data for determining the CY 2022
outlier services MAP amounts and FDL amounts, but suggested that CMS
undertake further action to address the issue of outlier payments
falling short of the 1 percent target. A professional organization of
pediatric nephrologists expressed concern that the decreasing FDL and
MAP amounts suggest that the cost of delivering pediatric ESRD care is
not appropriately paid under Medicare by either the existing ESRD PPS
bundled payment or through the outlier adjustment. Several commenters
recommended that CMS set the CY 2022 outlier percentage less than 1
percent. For example, one commenter, a coalition of dialysis
organizations, suggested that because the CY 2020 claims data showed
that outlier payments represented approximately 0.6 percent of total
ESRD PPS payments, CMS could set the CY 2022 outlier ``pool''
[percentage] at 0.6 percent. Similarly, a professional association
suggested that because historical data shows that CMS regularly pays
out between 0.5 and 0.6 percent of ESRD PPS payments as outlier
payments, CMS should reduce the outlier percentage to better match the
use of the outlier pool. Other commenters, including a large dialysis
organization and a provider advocacy organization, urged CMS to reduce
the CY 2022 outlier pool to no more than 0.5 percent of projected
[[Page 61884]]
aggregate ESRD PPS spending. Another large dialysis organization
recommended CMS adopt the proposed FDL and MAP amounts for CY 2022, but
urged CMS to set the outlier percentage to 0.6 percent.
Additionally, several of these commenters suggested that in any
year when the outlier pool retains dollars that are not paid out, CMS
should return those dollars to providers or reallocate those dollars to
support reducing the barriers that create inequities in the care
dialysis patients receive.
Response: We appreciate the support for the proposed use of CY 2020
data and the thoughtful suggestions provided by commenters. We
acknowledge that, even with annually adjusting the MAP and FDL to
reflect the most recent utilization and costs of ESRD PPS eligible
outlier services, total outlier payments have not yet reached the 1
percent target. However, it is also true that use of eligible ESRD
outlier services declined each year. That is, ESRD facilities incurred
lower costs than anticipated, and those savings accrued to facilities
more than offsetting the extent to which the consequent outlier
payments fell short of the 1.0 percent target. We also note that
declining FDL and MAP amounts do not in themselves suggest that the
ESRD PPS fails to adequately pay for the delivery of either pediatric
or adult ESRD care. Rather, the ESRD PPS outlier policy was established
to account for unusual variations in the type or amount of medically
necessary care. Declining FDL and MAP amounts suggest that there is
less costly variation in such care that is not included in the ESRD PPS
bundled payment.
We appreciate the comments suggesting solutions for refining the
outlier policy methodology, for example, reducing the outlier
percentage withhold to less than 1 percent or establishing a mechanism
that pays back ESRD facilities those allocated outlier amounts that did
not pay out in the year projected. We did not propose any modifications
to the ESRD PPS outlier policy for CY 2022, so we are not finalizing
any changes to the methodology in this final rule. However, as
discussed in section VI.E of the CY 2022 ESRD PPS proposed rule (86 FR
36400), CMS is considering potential revisions to the calculation of
the outlier percentage to address stakeholder concerns, including
concerns about the 1 percent outlier percentage, and issued a request
for information in the CY 2022 ESRD PPS proposed rule to seek feedback
on the acceptability of possible payment adjustment methods and to
solicit information that would better inform future modifications to
the methodology through rulemaking.
Final Rule Action: After considering the public comments, we are
finalizing the updated outlier thresholds for CY 2022 displayed in
Column II of Table 1 of this final rule and based on CY 2020 data.
d. Final Impacts to the CY 2022 ESRD PPS Base Rate
(1) ESRD PPS Base Rate
In the CY 2011 ESRD PPS final rule (75 FR 49071 through 49083), CMS
established the methodology for calculating the ESRD PPS per-treatment
base rate, that is, ESRD PPS base rate, and calculating the per
treatment payment amount, which are codified at Sec. Sec. 413.220 and
413.230. The CY 2011 ESRD PPS final rule also provides a detailed
discussion of the methodology used to calculate the ESRD PPS base rate
and the computation of factors used to adjust the ESRD PPS base rate
for projected outlier payments and budget neutrality in accordance with
sections 1881(b)(14)(D)(ii) and 1881(b)(14)(A)(ii) of the Act,
respectively. Specifically, the ESRD PPS base rate was developed from
CY 2007 claims (that is, the lowest per patient utilization year as
required by section 1881(b)(14)(A)(ii) of the Act), updated to CY 2011,
and represented the average per treatment MAP for composite rate and
separately billable services. In accordance with section 1881(b)(14)(D)
of the Act and our regulation at Sec. 413.230, the per-treatment
payment amount is the sum of the ESRD PPS base rate, adjusted for the
patient specific case-mix adjustments, applicable facility adjustments,
geographic differences in area wage levels using an area wage index,
and any applicable outlier payment, training adjustment add-on, TDAPA,
and TPNIES.
(2) Annual Payment Rate Update for CY 2022
We are finalizing an ESRD PPS base rate for CY 2022 of $257.90.
This update reflects several factors, described in more detail as
follows:
Wage Index Budget-Neutrality Adjustment Factor: We compute a wage
index budget-neutrality adjustment factor that is applied to the ESRD
PPS base rate. For CY 2022, we did not propose any changes to the
methodology used to calculate this factor, which is described in detail
in the CY 2014 ESRD PPS final rule (78 FR 72174). We computed the final
CY 2022 wage index budget-neutrality adjustment factor using treatment
counts from the 2020 claims and facility-specific CY 2021 payment rates
to estimate the total dollar amount that each ESRD facility would have
received in CY 2021. The total of these payments became the target
amount of expenditures for all ESRD facilities for CY 2022. Next, we
computed the estimated dollar amount that would have been paid for the
same ESRD facilities using the ESRD PPS wage index for CY 2022. As
discussed in section II.B.1.b of this final rule, the ESRD PPS wage
index for CY 2022 includes an update to the most recent hospital wage
data, use of the 2018 OMB delineations, and no cap on wage index
decreases applied for CY 2022. The total of these payments becomes the
new CY 2022 amount of wage-adjusted expenditures for all ESRD
facilities. The wage index budget-neutrality factor is calculated as
the target amount divided by the new CY 2022 amount. When we multiplied
the wage index budget neutrality factor by the applicable CY 2022
estimated payments, aggregate payments to ESRD facilities would remain
budget neutral when compared to the target amount of expenditures. That
is, the wage index budget neutrality adjustment factor ensures that
wage index adjustments do not increase or decrease aggregate Medicare
payments with respect to changes in wage index updates. The CY 2022
wage index budget-neutrality adjustment factor is 0.99985. This
application would yield a CY 2022 ESRD PPS base rate of $253.09 prior
to the application of the market basket increase ($253.13 x 0.99985 =
$253.09).
Market Basket Increase: Section 1881(b)(14)(F)(i)(I) of the Act
provides that, beginning in 2012, the ESRD PPS payment amounts are
required to be annually increased by the ESRD market basket percentage
increase factor. The latest CY 2022 projection of the ESRDB market
basket percentage increase factor is 2.4 percent. In CY 2022, this
amount must be reduced by the productivity adjustment described in
section 1886(b)(3)(B)(xi)(II) of the Act, as required by section
1881(b)(14)(F)(i)(II) of the Act. As discussed previously in section
II.B.1.a of this final rule, the final productivity adjustment for CY
2021 is 0.5 percent, thus yielding an update to the base rate of 1.9
percent for CY 2022. Therefore, the final CY 2022 ESRD PPS proposed
base rate is $257.90 ($253.02 x 1.019 = $257.90).
The comments and our responses to the comments on our updates to
the CY 2022 ESRD PPS base rate are set forth below.
Comment: Several commenters raised concerns about the comorbidity
case-mix adjustments under the ESRD PPS
[[Page 61885]]
and recommended eliminating them for CY 2022. Two commenters, including
a large dialysis organization and a coalition of dialysis organizations
encouraged CMS to eliminate the remaining comorbidity case-mix
adjustments and thereby increase the ESRD PPS base rate for CY 2022.
These commenters noted that the percent of claims with these conditions
is relatively low and has been declining over time. These commenters
argued that as the frequency of these conditions declines in the
claims, maintaining these adjusters results in the loss of money from
the system that could be redirected toward patient care. One of these
commenters further argued that this means the dollars that Congress
intended to go to providing items and services for individuals who
receive dialysis are being inappropriately diverted away from that
care. Both commenters further suggested that the years of discussion
pertaining to patient-level adjustments, particularly the issues with
the comorbid case-mix adjusters, and CMS's questions through the
request for information (RFI) in the CY 2022 ESRD PPS proposed rule,
should constitute enough notice to support their removal from the
regression model for CY 2022, which includes the co-morbid case-mix
adjusters in the calculation of the ESRD PPS payment.
Response: As the commenters noted, we included a detailed RFI
regarding the ESRD PPS case mix adjustments in the CY 2022 ESRD PPS
proposed rule (82 FR 36398 through 36409). A summary of the comments
received in response to the RFI is provided in section VI.A of this
final rule, and we will provide further information on the CMS ESRD PPS
website in the future. CMS is considering alternative approaches to
calculating the ESRD PPS case-mix adjustments that directly address
stakeholder concerns, and appropriately reflect resource use and costs.
The RFI in the CY 2022 ESRD PPS proposed rule both sought feedback on
the variation of case-mix adjustments with duration of dialysis
treatment, and solicited information on alternative proxies for
resource utilization that can be reported at the patient/treatment
level in order to better inform future modifications to this
methodology through rulemaking.
With regard to the comment about removing the co-morbid adjustment
from the case-mix for CY 2022, we note that due to the nature of
regression analysis, which is how the current payment adjustors are
set, making that type of adjustment would affect all the patient-level
and facility-level adjustments. This can impact budget neutrality
requirements and affect provider impacts differently than if adopted
incrementally. Payment system changes can also require extensive
efforts by CMS and providers to implement, and could not be implemented
for CY 2022. While we discussed these case-mix adjustments in the RFI,
we did not propose to make changes to the comorbidity case-mix
adjustments for CY 2022; therefore, we are not finalizing any changes
to that policy in this final rule.
Comment: Two commenters, a large dialysis organization and a non-
profit health insurance organization in Puerto Rico, urged CMS to
evaluate the accuracy of the ESRD PPS base rate as applied to payments
for ESRD facilities located in Puerto Rico. These commenters encouraged
CMS to consider the differences in patient characteristics between
Puerto Rico and the mainland U.S., as well as differences in size,
service capacity, and locality between the average ESRD facility in
Puerto Rico versus other mainland providers.
Response: As mentioned previously in this section of the final
rule, and as further discussed in section VI.D of the CY 2022 ESRD PPS
proposed rule (86 FR 36399), CMS is considering alternative approaches
to calculating the case-mix adjustment, including duration of dialysis
treatment to allocate composite rate costs for patients with higher
resource use due to patient characteristics as reflected in the case-
mix adjustments. We are also considering all the commenters'
suggestions in response to the RFI for alternative proxies for
allocation of composite rate costs for those patients whose medical and
physiologic characteristics require more resource use. We appreciate
these comments and will take them into consideration to potentially
inform future rulemaking.
Final Rule Action: We are finalizing a CY 2022 ESRD PPS base rate
of $257.90. This amount reflects the CY 2022 wage index budget-
neutrality adjustment factor of 0.99985, and the CY 2022 ESRD PPS
productivity-adjusted market basket update of 1.9 percent.
e. Update to the Average per Treatment Offset Amount for Home Dialysis
Machines
In the CY 2021 ESRD PPS final rule (85 FR 71427), we expanded
eligibility for the TPNIES under Sec. 413.236 to include certain
capital-related assets that are home dialysis machines when used in the
home for a single patient. To establish the basis of payment for the
TPNIES for these items, we finalized the additional steps that the
Medicare Administrative Contractors (MACs) must follow to calculate a
pre-adjusted per treatment amount, using the prices they establish
under Sec. 413.236(e) for a capital-related asset that is a home
dialysis machine, as well as the methodology that CMS uses to calculate
the average per treatment offset amount for home dialysis machines that
is used in the MACs' calculation, to account for the cost of the home
dialysis machine that is already in the ESRD PPS base rate. For
purposes of this final rule, we will refer to this as the ``TPNIES
offset amount.''
The methodology for calculating the TPNIES offset amount is set
forth in Sec. 413.236(f)(3). Section Sec. 413.236(f)(3)(v) states
that effective January 1, 2022, CMS annually updates the amount
determined in Sec. 413.236(f)(3)(iv) by the ESRD bundled market basket
percentage increase factor minus the productivity adjustment factor.
The TPNIES for capital-related assets that are home dialysis machines
is based on 65 percent of the MAC-determined pre-adjusted per treatment
amount, reduced by the TPNIES offset amount, and is paid for 2-calendar
years.
As we discussed in the CY 2022 ESRD PPS proposed rule (86 FR
36331), the CY 2021 TPNIES offset amount for capital-related equipment
that are home dialysis machines used in the home is $9.32. We stated
that the proposed CY 2022 ESRD bundled market basket increase factor
minus the productivity adjustment is 1.0 percent (1.6 percent minus 0.6
percent). Applying the proposed update factor of 1.010 to the proposed
CY 2021 TPNIES offset amount resulted in a proposed CY 2022 TPNIES
offset amount of $9.41 ($9.32 x 1.010). We proposed to update this
calculation using the most recent data available in the CY 2022 ESRD
PPS final rule.
The comments and our responses to the comments on the proposed
update to the TPNIES offset amount are set forth below.
Comment: One large dialysis organization commented in support of
the current TPNIES policy, but recommended that CMS recalculate the
TPNIES offset amount using a 7-year depreciation schedule, which the
commenter asserted would more accurately align with real-world home
dialysis machine use. This commenter also recommended that CMS revise
the TPNIES policy to allow for a modification to the ESRD PPS base rate
to ensure ongoing access to innovative technologies.
Response: We appreciate the commenter's suggestion for improving
[[Page 61886]]
the TPNIES policy. As we discussed in the CY 2021 ESRD PPS final rule
(85 FR 71421 through 71422), section 104.17 of the Provider
Reimbursement Manual discusses that the useful life of a capital-
related asset is its expected useful life to the provider, not
necessarily the inherent useful or physical life. Further, the manual
provides that under the Medicare program, only the American Hospital
Association (AHA) guidelines may be used in selecting a proper useful
life for computing depreciation. In keeping with the Medicare policy,
we established reliance on the AHA guidelines to determine the useful
life of a capital-related asset that is a home dialysis machine, which
is 5-years and not the 7 years suggested by the commenter (see 42 CFR
413.236(f)(i)). We note that we considered alternatives, but concluded
that this approach was simpler and appropriate for encouraging and
supporting the uptake of new and innovative renal dialysis equipment
and supplies (85 FR 71422).
We did not propose changes to the methodology for updating the
TPNIES offset amount for CY 2022, and therefore we are not finalizing
any changes to that methodology in this final rule. However, we will
take these recommendations into consideration to potentially inform
future rulemaking.
Final Rule Action: We are finalizing our proposal to calculate the
CY 2022 TPNIES offset amount using the most recent data available. The
CY 2021 TPNIES offset amount for capital-related equipment that are
home dialysis machines used in the home is $9.32. As discussed
previously in section II.B.1.a of this final rule, the CY 2022 ESRD
bundled market basket increase factor minus the productivity adjustment
is 1.9 percent (2.4 percent minus 0.5 percent). Applying the
productivity adjustment factor of 1.019 to the CY 2021 TPNIES offset
amount results in a CY 2022 TPNIES offset amount of $9.50 ($9.32 x
1.019).
f. TDAPA and TPNIES Public Comments and Responses
We also received several public comments on topics related to the
TPNIES and the TDAPA policies under the ESRD PPS, including from
individuals, such as ESRD beneficiaries, individual health care
providers, manufacturers, healthcare groups, patient advocacy
organizations, hospital associations, dialysis associations, as well as
various dialysis, kidney, and professional organizations. While these
comments related to issues that we either did not discuss in the CY
2022 ESRD PPS proposed rule or that we discussed for background or
context, but for which we did not propose changes, a summary of the
significant comments and our responses are set forth below.
Comment: Commenters overwhelmingly wrote in support of innovation
in ESRD management generally and some specifically mentioned existing
or upcoming technologies they thought would benefit ESRD patients.
Other commenters expressed interest in seeing improvements in
peritoneal dialysis, including on-line generation of dialysate and
prevention of infections. Commenters also expressed support for home
hemodialysis, citing its flexibility, convenience, and the comfort it
provides patients. Commenters expressed interest in seeing improvements
in home hemodialysis such as lower costs, more availability, better
cannulation, reduced burden on patients and caregivers, and more
convenient generation of dialysate. Commenters also stated they would
like to see improvements in home dialysis that would increase
retention, improve quality of delivered dialysate, or reduce
complications.
Response: We appreciate the supportive comments regarding
innovation in ESRD therapy. Like the commenters, CMS supports
innovation in the ESRD space and we look forward to seeing new
technologies that improve care for beneficiaries with ESRD.
Comments: Commenters provided input on the substantial clinical
improvement criteria for the TPNIES under Sec. 413.236(b)(5) and Sec.
412.87(b)(1), offering specific recommendations on what CMS should
consider in making a determination of substantial clinical improvement
for the TPNIES. Commenters suggested that certain innovations could be
considered evidence of substantial clinical improvement over existing
technologies, such as: Technical specifications that make home dialysis
easier for disadvantaged persons, real time dialysis fluid preparation,
and real-time monitoring of patients' treatment sessions.
Many commenters encouraged CMS to utilize evidence outside of
randomized controlled trials (RCTs) as a way of demonstrating
significant clinical improvement due to the challenges of running
clinical trials involving patients with ESRD, including difficulty in
patient recruitment and financial barriers for innovators to conduct
these types of large-scale, long-term trials. One commenter who agreed
with this stated that CMS also should not only rely on short, small-
scale studies conducted by device manufacturers as the standard for
substantial clinical improvement. A home dialysis advocacy organization
commented that evidence from a clinical trial, abstracts of data, and
expert opinion, such as letters from medical professionals, are
sufficient to support a showing of substantial clinical improvement,
rather than RCTs. That same commenter added that given the challenges
specific to conducting studies in the ESRD space, real-world evidence
gathered from studies conducted outside the U.S. may be extrapolated to
Medicare beneficiaries when appropriate. One commenter, a beneficiary,
emphasized that patients may have a drastically different perspective
of substantial clinical improvement compared to CMS. That commenter
stated that greater flexibility is of the utmost importance to home
dialysis patients and, therefore, therapies that allow patients with
ESRD to resume their normal day-to-day activities should be considered
to show substantial clinical improvement. Other commenters also
encouraged the use of patient preferences, patient-reported outcomes,
and other patient-centered data when evaluating substantial clinical
improvement. A commenter encouraged CMS to weigh the reduction of
patient and care partner burden, improved communication with the care
team, and improved safety through the reduction of severe adverse
events in the evaluation of evidence.
Other commenters offered suggestions for CMS's current process of
evaluating evidence of substantial clinical improvement. Commenters
asked that CMS provide guidance on evidence of substantial clinical
improvement specific to the ESRD space, such as the development of a
set of ESRD patient-reported outcomes for assessing substantial
clinical improvement criteria. Other commenters also suggested using a
panel of patients with ESRD to assist with tasks such as developing the
set of patient-reported outcomes or providing insight for these
outcomes during the evaluation process. Some commenters asked CMS to
clarify how data and real-world evidence submitted as part of a TPNIES
application is reviewed and weighed during the review process.
Response: We appreciate the comments regarding the CMS evaluation
process for the substantial clinical improvement criterion for the
TPNIES. In response to commenters' suggestions regarding the use of
expert opinions, clinical trials, abstracts of data, unpublished
sources, and letters from health care providers in our analysis, we
note that under Sec. 413.236(b)(5), CMS may consider all of these
types of data,
[[Page 61887]]
among others, in making a determination of substantial clinical
improvement. A list of information sources that we may consider in our
determination is set forth in Sec. 412.87(b)(1)(iii). Additionally,
under Sec. 412.87(b)(1)(iii)(N), CMS may consider other appropriate
information sources not otherwise listed in our regulations on
substantial clinical improvement. Further, we are taking the
opportunity to clarify that RCTs, while potentially informative, are
not required under existing regulations to demonstrate substantial
clinical improvement for purpose of the TPNIES. While we did not
propose changes to the substantial clinical improvement criteria for
the TPNIES in the CY 2022 ESRD PPS proposed rule, we will consider
these comments for future rulemaking. We encourage ESRD patients and
patient advocacy organizations to submit comments on our annual ESRD
PPS proposed rules to provide their perspectives on TPNIES
applications.
Comment: Several commenters suggested changes to the TPNIES policy
under the ESRD PPS. Commenters suggested using FDA determinations (for
example, Breakthrough Device designations) in evaluating TPNIES
applications. Commenters also asked for CMS to provide increased
feedback to applicants throughout the TPNIES application process,
including providing: Parallel feedback on data needed to support a
TPNIES application as the manufacturers are working towards FDA
marketing authorization, public review of the complete application
prior to finalizing TPNIES application decisions, and an appeal process
for manufacturers whose TPNIES applications were not approved. In
addition, commenters recommended that CMS remove MACs' discretion in
determining pricing of new and innovative renal dialysis equipment and
supplies, as provided under Sec. 413.236(e), and requested that CMS
set more defined payment parameters and public transparency around
pricing. Other commenters suggested expanding the TPNIES policy to
allow TPNIES payments to ESRD facilities with home dialysis devices on
operating leases and to expand the TPNIES eligibility to include all
capital-related assets, not just home dialysis machines, as allowed
under Sec. 413.236(b)(6). We also received comments requesting various
extensions to the TPNIES application deadlines and payment periods such
as: Extending the duration of the TPNIES payment to 3 years, extending
application timetables for device manufacturers applying for the TPNIES
in the early years of the policy, and extending application timetables
for manufacturers impacted by the COVID-19 PHE.
Response: We thank the public for their comments. Because we did
not propose any changes to the TPNIES policy in the CY 2022 ESRD PPS
proposed rule, we are not making any changes to that policy in this
final rule; however, we will consider the commenters' recommendations
for future rulemaking.
Comment: Several commenters also suggested changes to the TDAPA
policy under Sec. 413.234. For example, one commenter stated that CMS
should consider implementing the substantial clinical improvement
criteria used to evaluate the TPNIES applications for the TDAPA
applications, and another commenter stated that CMS should not apply
the TDAPA to biosimilar drugs.
Response: We thank the public for their comments. Because we did
not propose any changes to the TDAPA policy in the CY 2022 ESRD PPS
proposed rule, we are not making any changes to that policy in this
final rule; however, we will consider the commenters' recommendations
for future rulemaking.
C. Transitional Add-On Payment Adjustment for New and Innovative
Equipment and Supplies (TPNIES) for CY 2022 Payment
1. Background
In the CY 2020 ESRD PPS final rule (84 FR 60681 through 60698), CMS
established the transitional add-on payment adjustment for new and
innovative equipment and supplies (TPNIES) under the ESRD PPS, under
the authority of section 1881(b)(14)(D)(iv) of the Act, in order to
support ESRD facility use and beneficiary access to these new
technologies. We established this add-on payment adjustment to help
address the unique circumstances experienced by ESRD facilities when
incorporating new and innovative equipment and supplies into their
businesses and to support ESRD facilities transitioning or testing
these products during the period when they are new to market. We added
Sec. 413.236 to establish the eligibility criteria and payment
policies for the TPNIES.
In the CY 2020 ESRD PPS final rule (84 FR 60650), we established in
Sec. 413.236(b) that for dates of service occurring on or after
January 1, 2020, we will provide the TPNIES to an ESRD facility for
furnishing a covered equipment or supply only if the item: (1) Has been
designated by CMS as a renal dialysis service under Sec. 413.171; (2)
is new, meaning granted marketing authorization by the Food and Drug
Administration (FDA) on or after January 1, 2020; (3) is commercially
available by January 1 of the particular calendar year, meaning the
year in which the payment adjustment would take effect; (4) has a
Healthcare Common Procedure Coding System (HCPCS) application submitted
in accordance with the official Level II HCPCS coding procedures by
September 1 of the particular calendar year; (5) is innovative, meaning
it meets the substantial clinical improvement criteria specified in the
Inpatient Prospective Payment System (IPPS) regulations at Sec.
412.87(b)(1) and related guidance, and (6) is not a capital related
asset that an ESRD facility has an economic interest in through
ownership (regardless of the manner in which it was acquired).
Regarding the innovation requirement in Sec. 413.236(b)(5), in the
CY 2020 ESRD PPS final rule (84 FR 60690), we stated that we will use
the following criteria to evaluate substantial clinical improvement for
purposes of the TPNIES under the ESRD PPS based on the IPPS substantial
clinical improvement criteria in Sec. 412.87(b)(1) and related
guidance:
A new technology represents an advance that substantially improves,
relative to renal dialysis services previously available, the diagnosis
or treatment of Medicare beneficiaries. First, CMS considers the
totality of the circumstances when making a determination that a new
renal dialysis equipment or supply represents an advance that
substantially improves, relative to renal dialysis services previously
available, the diagnosis or treatment of Medicare beneficiaries.
Second, a determination that a new renal dialysis equipment or supply
represents an advance that substantially improves, relative to renal
dialysis services previously available, the diagnosis or treatment of
Medicare beneficiaries means one of the following:
The new renal dialysis equipment or supply offers a
treatment option for a patient population unresponsive to, or
ineligible for, currently available treatments; or
The new renal dialysis equipment or supply offers the
ability to diagnose a medical condition in a patient population where
that medical condition is currently undetectable, or offers the ability
to diagnose a medical condition earlier in a patient population than
allowed by currently available methods, and there must also be evidence
that use of the new renal
[[Page 61888]]
dialysis service to make a diagnosis affects the management of the
patient; or
The use of the new renal dialysis equipment or supply
significantly improves clinical outcomes relative to renal dialysis
services previously available as demonstrated by one or more of the
following: A reduction in at least one clinically significant adverse
event, including a reduction in mortality or a clinically significant
complication; a decreased rate of at least one subsequent diagnostic or
therapeutic intervention; a decreased number of future hospitalizations
or physician visits; a more rapid beneficial resolution of the disease
process treatment including, but not limited to, a reduced length of
stay or recovery time; an improvement in one or more activities of
daily living; an improved quality of life; or, a demonstrated greater
medication adherence or compliance; or,
The totality of the circumstances otherwise demonstrates
that the new renal dialysis equipment or supply substantially improves,
relative to renal dialysis services previously available, the diagnosis
or treatment of Medicare beneficiaries.
Third, evidence from the following published or unpublished
information sources from within the U.S. or elsewhere may be sufficient
to establish that a new renal dialysis equipment or supply represents
an advance that substantially improves, relative to renal dialysis
services previously available, the diagnosis or treatment of Medicare
beneficiaries: Clinical trials, peer reviewed journal articles; study
results; meta-analyses; consensus statements; white papers; patient
surveys; case studies; reports; systematic literature reviews; letters
from major healthcare associations; editorials and letters to the
editor; and public comments. Other appropriate information sources may
be considered.
Fourth, the medical condition diagnosed or treated by the new renal
dialysis equipment or supply may have a low prevalence among Medicare
beneficiaries. Fifth, the new renal dialysis equipment or supply may
represent an advance that substantially improves, relative to services
or technologies previously available, the diagnosis or treatment of a
subpopulation of patients with the medical condition diagnosed or
treated by the new renal dialysis equipment or supply.
In the CY 2020 ESRD PPS final rule (84 FR 60681 through 60698), we
also established a process modeled after IPPS's process of determining
if a new medical service or technology meets the substantial clinical
improvement criteria specified in Sec. 412.87(b)(1). Specifically,
similar to the IPPS New Technology Add-On Payment, we wanted to align
our goals with the agency's efforts to transform the healthcare
delivery system for the ESRD beneficiary through competition and
innovation to provide patients with better value and results. As we
discussed in the CY 2020 ESRD PPS final rule (84 FR 60682), we believe
it is appropriate to facilitate access to new and innovative equipment
and supplies through add-on payments similar to the IPPS New Technology
Add-On Payment and to provide stakeholders with standard criteria for
both inpatient and outpatient settings. In Sec. 413.236(c), we
established a process for our announcement of TPNIES determinations and
a deadline for consideration of new renal dialysis equipment or supply
applications under the ESRD PPS. CMS will consider whether a new renal
dialysis equipment or supply meets the eligibility criteria specified
in Sec. 413.236(b) and summarize the applications received in the
annual ESRD PPS proposed rules. Then, after consideration of public
comments, we will announce the results in the Federal Register as part
of our annual updates and changes to the ESRD PPS in the ESRD PPS final
rule. In the CY 2020 ESRD PPS final rule, we also specified certain
deadlines for the application requirements. We noted that we would only
consider a complete application received by February 1 prior to the
particular calendar year. In addition, we required that FDA marketing
authorization for the equipment or supply must occur by September 1
prior to the particular calendar year. We also stated in the CY 2020
ESRD PPS final rule (84 FR 60690 through 60691) that we would establish
a workgroup of CMS medical and other staff to review the materials
submitted as part of the TPNIES application, public comments, FDA
marketing authorization, and HCPCS application information and assess
the extent to which the product provides substantial clinical
improvement over current technologies.
In the CY 2020 ESRD PPS final rule, we established Sec. 413.236(d)
to provide a payment adjustment for a new and innovative renal dialysis
equipment or supply. We stated that the TPNIES is paid for 2-calendar
years. Following payment of the TPNIES, the ESRD PPS base rate will not
be modified and the new and innovative renal dialysis equipment or
supply will become an eligible outlier service as provided in Sec.
413.237.
Regarding the basis of payment for the TPNIES, in the CY 2020 ESRD
PPS final rule, we finalized at Sec. 413.236(e) that the TPNIES is
based on 65 percent of the price established by the MACs, using the
information from the invoice and other specified sources of
information.
In the CY 2021 ESRD PPS final rule (85 FR 71410 through 71464), we
made several changes to the TPNIES eligibility criteria at Sec.
413.236. First, we revised the definition of new at Sec. 413.236(b)(2)
as within 3 years beginning on the date of the FDA marketing
authorization. Second, we changed the deadline for TPNIES applicants'
HCPCS Level II code application submission from September 1 of the
particular calendar year to the HCPCS Level II code application
deadline for biannual Coding Cycle 2 for durable medical equipment,
orthotics, prosthetics, and supplies (DMEPOS) items and services as
specified in the HCPCS Level II coding guidance on the CMS website
prior to the calendar year. In addition, a copy of the applicable FDA
marketing authorization must be submitted to CMS by the HCPCS Level II
code application deadline for biannual Coding Cycle 2 for DMEPOS items
and services as specified in the HCPCS Level II coding guidance on the
CMS website in order for the equipment or supply to be eligible for the
TPNIES the following year. Third, we revised Sec. 413.236(b)(5) to
remove a reference to related guidance on the substantial clinical
improvement criterion, as the guidance had already been codified.
Finally, in the CY 2021 ESRD PPS final rule, we expanded the TPNIES
policy to include certain capital-related assets that are home dialysis
machines when used in the home for a single patient. We explained that
capital-related assets are defined in the Provider Reimbursement Manual
(chapter 1, section 104.1) as assets that a provider has an economic
interest in through ownership (regardless of the manner in which they
were acquired). We noted that examples of capital-related assets for
ESRD facilities are dialysis machines and water purification systems.
We explained that, although we stated in the CY 2020 ESRD PPS proposed
rule (84 FR 38354) that we did not believe capital-related assets
should be eligible for additional payment through the TPNIES because
the cost of these items is captured in cost reports, they depreciate
over time, and are generally used for multiple patients, there were a
number of other factors we considered that led us to consider expanding
eligibility for these technologies in the CY 2021 ESRD PPS
[[Page 61889]]
rulemaking. We explained that, following publication of the CY 2020
ESRD PPS final rule, we continued to study the issue of payment for
capital-related assets under the ESRD PPS, taking into account
information from a wide variety of stakeholders and recent developments
and initiatives regarding kidney care. For example, we considered
various HHS home dialysis initiatives, Executive Orders to transform
kidney care, and how the risk of COVID-19 for particularly vulnerable
ESRD beneficiaries could be mitigated by encouraging home dialysis.
After closely considering these issues, we proposed a revision to
Sec. 413.236(b)(6) in the CY 2021 ESRD PPS proposed rule to provide an
exception to the general exclusion for capital-related assets from
eligibility for the TPNIES for capital-related assets that are home
dialysis machines when used in the home for a single patient and that
meet the other eligibility criteria in Sec. 413.235(b), and finalized
the exception as proposed in the CY 2021 ESRD PPS final rule. We
finalized the same determination process for TPNIES applications for
capital-related assets that are home dialysis machines as for all other
TPNIES applications; that we will consider whether the new home
dialysis machine meets the eligibility criteria specified in Sec.
413.236(b) and announce the results in the Federal Register as part of
our annual updates and changes to the ESRD PPS. Per Sec. 413.236(c),
we will only consider, for additional payment using the TPNIES for a
particular calendar year, an application for a capital-related asset
that is a home dialysis machine received by February 1 prior to the
particular calendar year. If the application is not received by
February 1, the application will be denied and the applicant is able to
reapply within 3 years beginning on the date of FDA marketing
authorization in order to be considered for the TPNIES, in accordance
with Sec. 413.236(b)(2).
In the CY 2021 ESRD PPS final rule, at Sec. 413.236(f), we
finalized a pricing methodology for capital-related assets that are
home dialysis machines when used in the home for a single patient,
which requires the MACs to calculate the annual allowance and the
preadjusted per treatment amount. The pre-adjusted per treatment amount
is reduced by an estimated average per treatment offset amount to
account for the costs already paid through the ESRD PPS base rate. The
CY 2021 TPNIES offset amount was $9.32. We finalized that this amount
will be updated on an annual basis so that it is consistent with how
the ESRD PPS base rate is updated.
We revised Sec. 413.236(d) to reflect that we would pay 65 percent
of the pre-adjusted per treatment amount minus the offset for capital-
related assets that are home dialysis machines when used in the home
for a single patient.
We revised Sec. 413.236(d)(2) to reflect that following payment of
the TPNIES, the ESRD PPS base rate will not be modified and the new and
innovative renal dialysis equipment or supply will be an eligible
outlier service as provided in Sec. 413.237, except a capital-related
asset that is a home dialysis machine will not be an eligible outlier
service as provided in Sec. 413.237.
In summary, under the current eligibility requirements in Sec.
413.236(b), CMS provides for a TPNIES to an ESRD facility for
furnishing a covered equipment or supply only if the item: (1) Has been
designated by CMS as a renal dialysis service under Sec. 413.171; (2)
Is new, meaning within 3 years beginning on the date of the FDA
marketing authorization; (3) Is commercially available by January 1 of
the particular calendar year, meaning the year in which the payment
adjustment would take effect; (4) Has a complete HCPCS Level II code
application submitted in accordance with the HCPCS Level II coding
procedures on the CMS website, by the HCPCS Level II code application
deadline for biannual Coding Cycle 2 for DMEPOS items and services as
specified in the HCPCS Level II coding guidance on the CMS website
prior to the calendar year; (5) Is innovative, meaning it meets the
criteria specified in Sec. Sec. 412.87(b)(1); and (6) Is not a
capital-related asset, except for capital-related assets that are home
dialysis machines.
We received two applications for the TPNIES for CY 2022. One
applicant, CloudCath (the applicant for the CloudCath Peritoneal
Dialysis Drain Set Monitoring System), withdrew its application from
consideration after the issuance of the CY 2022 ESRD PPS proposed rule
because it did not receive FDA marketing authorization by July 6, 2021,
which was the HCPCS Level II code application deadline for biannual
Coding Cycle 2 for DMEPOS items and services. Under Sec. Sec.
413.236(c), an applicant for the TPNIES must receive FDA marketing
authorization for its new equipment or supply by the HCPCS Level II
Code application deadline for biannual Coding Cycle 2 for DMEPOS items
and services as specified in the HCPCS Level II coding guidance on the
CMS website prior to the particular calendar year. Therefore, the
CloudCath Peritoneal Dialysis Drain Set Monitoring System is not
eligible for consideration for the TPNIES for CY 2022. We are not
including in this final rule the description and discussion of this
application, which was included in the CY 2022 ESRD PPS proposed rule.
We note that we received public comments on the application that was
withdrawn. However, because the application was withdrawn and thus the
technology is ineligible for the TPNIES for CY 2022, we are not
summarizing nor responding to public comments regarding the TPNIES
criteria for this technology in this final rule. A discussion of the
remaining application, which met this deadline, is presented in this
final rule.
The application discussed in this final rule is for a technology
commonly used for the treatment of ESRD: Hemodialysis (HD). A detailed
definition for HD is included in Chapter 11, Section 10 of the Medicare
Benefits Policy Manual (Pub. L. 100-02).\2\ In brief, HD is a process
that involves blood passing through an artificial kidney machine and
the waste products diffusing across a manmade membrane into a bath
solution known as dialysate after which the cleansed blood is returned
to the patient's body. HD is accomplished usually in 3 to 5 hour
sessions, 3 times a week.
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\2\ Medicare Benefits Policy Manual (Pub. L. 100-102), available
at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/bp102c11.pdf.
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a. Tablo[supreg] System
Outset Medical, Inc. submitted an application for the TPNIES for
the Tablo[supreg] System for CY 2022. According to the applicant, the
technology is an HD machine that has been designed for patient-driven
self-care and to minimize system training time. The applicant stated
that the system is intended to substantially improve the treatment of
people with ESRD by removing barriers to home dialysis. The applicant
explained that the Tablo[supreg] System is comprised of (1) the
Tablo[supreg] Console with integrated water purification, on-demand
dialysate production, and a touchscreen interface; (2) a proprietary,
disposable, single-use pre-strung cartridge; and (3) the Tablo[supreg]
Connectivity and Data Ecosystem. Per the applicant, the system is built
to function in a connected setting with cloud-based system monitoring,
patient analytics and clinical recordkeeping.
The applicant stated that the Tablo[supreg] System's features
combine to provide a significantly differentiated HD solution with many
benefits. First, the applicant stated that the Tablo[supreg] System's
touchscreen interface made it easy to learn and use, guiding users
through treatment using step-by-step
[[Page 61890]]
instructions with simple words and animation. The applicant also stated
that instructions include non-technical language and color-coded parts
to enable easier training, faster set-up, and simpler management
including clear alarm explanations and resolution instructions.
Second, the applicant stated that the Tablo[supreg] System can
accommodate treatments at home, allowing for flexibility in treatment
frequencies, durations, and flow rates. Per the applicant, the
Tablo[supreg] System did not have a pre-configured dialyzer, which
allows clinicians to use a broad range of dialyzer types and
manufactures, allowing for greater customization of treatment for the
patient. The applicant stated that this was an improvement over the
incumbent home device, which requires a separate device component and
complex process to switch to another dialyzer.
Third, the applicant stated that the Tablo[supreg] System is an
all-in-one system with integrated water purification and on-demand
dialysate production, eliminating the need for industrial water
treatment rooms that are required to operate traditional HD machines.
The applicant also stated that electronic data capture and automatic
wireless transmission eliminate the need for manual record keeping by
the patient, care partner, or nurse. Per the applicant, a single-use
Tablo[supreg] Cartridge with pre-strung blood, saline, and infusion
tubing and a series of sensor-receptors mounted to an organizer snaps
into the system, minimizing difficult connections that require
additional training. The applicant stated that automated features,
including an integrated blood pressure monitor, air removal, priming,
and blood return, minimize user errors, save time, and streamline the
user experience.
Fourth, the applicant stated that the Tablo[supreg] System's two-
way wireless connectivity and data analytics provide the ability to
continuously activate new capabilities and enhancements through
wireless software updates, while also enabling predictive preventative
maintenance to maximize machine uptime.
The applicant stated that currently 88 percent of patients receive
HD in a clinic 3 times per week, for 3.0 to 4.5 hours a day and fewer
than 2 percent perform HD treatment at home.\3\ The applicant stated
that 25 to 36 percent of home HD patients return to in-center care
within 1 year of initiating HD at home.4 5 Per the
applicant, barriers to home dialysis adoption and retention have been
well studied and include treatment burden for patients and care partner
fatigue; technical challenges with operating a HD machine; space, home
modifications, and supplies management; patients not wanting medical
equipment in the home; and safety concerns.6 7
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\3\ United States Renal Data System. 2020 USRDS Annual Data
Report: Epidemiology of kidney disease in the United States, End-
Stage Renal Disease Chapter 2. National Institutes of Health,
National Institute of Diabetes and Digestive and Kidney Diseases,
Bethesda, MD 2020. Available at: https://adr.usrds.org/2020/end-stage-renaldisease/introduction-to-volume-2. Accessed on Jan. 21,
2021.
\4\ Seshasai, R.K., et al. (2019). The home hemodialysis patient
experience: A qualitative assessment of modality use and
discontinuation. Hemodialysis International, 23: 139-150, 2019.
doi:10.1111/hdi.12713.
\5\ Weinhandl, Eric D., Collins Allan, Incidence of Therapy
Cessation among Home Hemodialysis Patients in the United States,
Abstract presented, American Society of Nephrology Kidney Week 2016.
\6\ Seshasai, R.K., et al (2019). The home hemodialysis patient
experience: A qualitative assessment of modality use and
discontinuation. Hemodialysis International, 23: 139-150, 2019.
doi:10.1111/hdi.12713.
\7\ Chan, Christopher T. et al. (2018). Exploring Barriers and
Potential Solutions in Home Dialysis: An NKF-KDOQI Conference
Outcomes Report American Journal of Kidney Diseases, Volume 73,
Issue 3, 363-371.
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The applicant stated that innovation in making home dialysis more
accessible to patients has been lacking due to a lack of investment
funding, limited incremental reimbursement for new technology, and a
consolidated, price-sensitive dialysis provider market where the lack
of market competition is costly and has been associated with increased
hospitalizations in dialysis patients.\8\ The applicant stated that the
Tablo[supreg] System was designed to address many system-related
barriers that result in patients deciding on in-center care and/or
stopping home modalities due to the burden of self-managed therapy.
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\8\ Erickson, K.F., Zheng, Y., Ho, V., Winkelmayer, W.C.,
Bhattacharya, J., & Chertow, G.M. (2018). Market Competition and
Health Outcomes in Hemodialysis. Health services research, 53(5),
3680-3703. https://doi.org/10.1111/1475-6773.12835.
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The applicant stated that while peritoneal dialysis (PD), like HD,
removes excess fluid and waste from the body, it has a different
mechanism of action and relies on the body's own membrane, the
peritoneum, to act as the ``dialyzer''. Per the applicant, PD requires
surgical placement of a catheter in the abdomen and utilizes a
cleansing fluid, dialysate, that must be infused and dwell in the
abdomen to remove waste products from the blood. The applicant stated
that PD must be conducted daily to achieve adequate dialysis and can be
conducted manually or via a cycler; while in contrast, HD directly
cleanses the blood with the use of a HD machine, dialysate and a
dialyzer, which acts as an artificial kidney in removing excess fluid
and toxins. The applicant stated that HD also requires surgical
placement of a dialysis access, which is usually in the form of a
catheter or a more permanent arteriovenous fistula.\9\
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\9\ Blake, P.G., Quinn, R.R., & Oliver, M.J. (2013). Peritoneal
dialysis and the process of modality selection. Peritoneal dialysis
international: Journal of the International Society for Peritoneal
Dialysis, 33(3), 233-241. https://doi.org/10.3747/pdi.2012.00119.
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The applicant asserted that PD is the dominant home therapy used
around the world, but should not be solely relied upon to increase
growth in home dialysis, as there are physiological
contraindications.\10\ The applicant also stated that there is recent
evidence that post 90-day mortality is higher in PD patients than in HD
patients. Per the applicant, multivariable risk-adjusted analyses
demonstrated that the mortality hazard ratio of HD versus PD is 0.74
(95 percent confidence interval (CI), 0.68-0.80) in the 270 to 360-day
period after starting dialysis.\11\ The applicant stated that patients
and clinicians should weigh the risks and benefits of both options and
select the one that meets the individual patient's preferences, goals,
values and physiology. Per the applicant, because PD relies on the
patient's own membrane, physiologic changes can occur and result in
patients who are unable to continue PD due to loss of the ability to
achieve adequacy. The applicant stated that these home patients could
consider home HD rather than a return to in-center and noted that the
practice of transitioning from one home modality to another is
acknowledged by experts to be underutilized and is particularly
pronounced in the U.S., where the ratio of PD use to home HD is
6:1,\12\ as compared to 4:1 in Canada.\13\
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\10\ Ibid.
\11\ Mukhopadhyay, P., Woodside, K.J., Schaubel, D.E., Repeck,
K., McCullough, K., Shahinian, V.B., . . . & Saran, R. (2020).
Survival among incident peritoneal dialysis versus hemodialysis
patients who initiate with an arteriovenous fistula. Kidney
Medicine, 2(6), 732-741.
\12\ United States Renal Data System. 2020 USRDS Annual Data
Report: Epidemiology of kidney disease in the United States, End-
Stage Renal Disease Chapter 2. National Institutes of Health,
National Institute of Diabetes and Digestive and Kidney Diseases,
Bethesda, MD 2020. Available at: https://adr.usrds.org/2020/end-stage-renaldisease/introduction-to-volume-2. Accessed on Jan 21,
2021.
\13\ Canada Institute for Health Information (2020): Annual
Statistics. Available at: https://secure.cihi.ca/estore/productSeries.htm?locale=en&pc=PCC24&_ga=2.265337481.729263172.1612199530-510791291.1610562424. Accessed on Jan. 31, 2021.
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[[Page 61891]]
The applicant asserted that the Tablo[supreg] System presented a
significant clinical improvement over NxStage[supreg] System
OneTM (NxStage[supreg]), the current standard of home HD
care, with the goal of getting patients access to easier to use
technology and increasing the number of patients who can do dialysis at
home. Per the applicant, NxStage[supreg] is the only other mobile HD
machine that is approved for home use.
(1) Renal Dialysis Service Criterion (Sec. 413.236(b)(1))
With respect to the first TPNIES eligibility criterion under Sec.
413.236(b)(1), whether the item has been designated by CMS as a renal
dialysis service under Sec. 413.171, maintenance dialysis treatments
and all associated services, including historically defined dialysis-
related drugs, laboratory tests, equipment, supplies, and staff time,
were included in the composite rate for renal dialysis services as of
December 31, 2010 (75 FR 49036). An in-home HD machine would be
considered equipment essential for the provision of maintenance
dialysis. We received no public comments on whether the Tablo[supreg]
System meets this criterion. Based on its status as an in-home HD
machine, we consider the Tablo[supreg] System to be a renal dialysis
service under Sec. 413.171.
(2) Newness Criterion (Sec. 413.236(b)(2))
With respect to the second TPNIES eligibility criterion under Sec.
413.236(b)(2), whether the item is new, meaning within 3 years
beginning on the date of the FDA marketing authorization, the applicant
indicated that the Tablo[supreg] System received FDA marketing
authorization for home use on March 31, 2020.\14\ We received no public
comments on whether the Tablo[supreg] System meets the newness
criterion. Based on the information provided by the applicant, we agree
that the Tablo[supreg] System meets the newness criterion.
---------------------------------------------------------------------------
\14\ As we stated in the CY 2022 ESRD PPS proposed rule (86 FR
36334), in reviewing the enclosure to which the March 31, 2020 FDA
authorization letter refers, the applicant's Section 510(k)
submission indicated that the Tablo[supreg] Cartridge was reviewed
separately from the Tablo[supreg] System and has its own separate
510(k) clearance. We further stated that, in the CY 2021 ESRD PPS
final rule, CMS determined that the cartridge did not meet the
newness criterion for the TPNIES (85 FR 71464) and as such, the
cartridge was not new.
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(3) Commercial Availability Criterion (Sec. 413.236(b)(3))
With respect to the third eligibility criterion under Sec.
413.236(b)(3), whether the item is commercially available by January 1
of the particular calendar year, meaning the year in which the payment
adjustment would take effect, applicant indicated that the
Tablo[supreg] System became available for home use on April 1, 2020. We
received no public comments on whether the Tablo[supreg] System meets
the commercial availability criterion. Based on the information
provided by the applicant, we agree that the Tablo[supreg] System meets
the commercial availability criterion.
(4) HCPCS Level II Application Criterion (Sec. 413.236(b)(4))
The fourth TPNIES eligibility criterion, under Sec. 413.236(b)(4),
is whether the applicant has submitted a complete HCPCS Level II code
application in accordance with the HCPCS Level II coding procedures on
the CMS website, by the HCPCS Level II code application deadline for
biannual Coding Cycle 2 for DMEPOS items and services as specified in
the HCPCS Level II coding guidance on the CMS website prior to the
particular calendar year. The applicant indicated that it submitted a
HCPCS Level II code application on July 6, 2021, which was same day as
the deadline specified HCPCS Level II code application deadline for
biannual Coding Cycle 2 for DMEPOS items and services specified in CMS
guidance.\15\ We received no public comments on whether the
Tablo[supreg] System meets this criterion. Based on the information
provided by the applicant, we agree the applicant has met the HCPCS
Level II application criterion.
---------------------------------------------------------------------------
\15\ https://www.cms.gov/Medicare/Coding/MedHCPCSGenInfo/Downloads/2020-HCPCS-Application-and-Instructions.pdf.
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(5) Innovation Criterion (Sec. Sec. 413.236(b)(5) and 412.87(b)(1))
With respect to the fifth TPNIES eligibility criterion under Sec.
413.236(b)(5), that the item is innovative, meaning it meets the
substantial clinical improvement criteria specified in Sec.
412.87(b)(1), the applicant claimed that the Tablo[supreg] System
significantly improves clinical outcomes relative to the current
standard of care for home HD services, which it identified as the
incumbent NxStage[supreg] home dialysis machine. The applicant
presented the following substantial clinical improvement claims: (1)
Decreased treatment frequency with adequate dialysis clearance; (2)
increased adherence to dialysis treatment and retention to home
therapy; and (3) improved patient quality of life. The applicant
supported these claims with the Tablo[supreg] System Investigational
Device Exemption (IDE) Study \16\ and secondary support from four
papers 17 18 19 20 and two posters.21 22 The
applicant also provided comparison data from three studies directly
related to the incumbent 23 24 25 and an additional study
that, based on the timeframe of the study, likely involved participants
undergoing treatment with NxStage[supreg] although the article does not
directly reference the incumbent.\26\
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\16\ Clinicaltrials.gov website. https://www.clinicaltrials.gov/ct2/show/NCT02460263. Last Updated July 1, 2020. https://www.clinicaltrials.gov/ProvidedDocs/63/NCT02460263/Prot_000.pdf.
\17\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
\18\ Leypoldt, J.K., Prichard, S., Chertow, G.M., & Alvarez, L.
(2019). Differential molecular modeling predictions of mid and
conventional dialysate flows. Blood purification, 47(4), 369-376.
\19\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
\20\ Plumb, Troy J., Luis Alvarez, Dennis L. Ross, Joseph J.
Lee, Jeffrey G. Mulhern, Jeffrey L. Bell, Graham E. Abra, Sarah S.
Prichard, Glenn M. Chertow, and Michael A. Aragon. ``Self-care
training using the Tablo hemodialysis system.'' Hemodialysis
International (2020).
\21\ Alvarez, Luis et al. Urea Clearance Results in Patients
Dialyzed Thrice-weekly Using a Dialysate Flow of 300 mL/min,
clinical abstract, presented March 2019, Annual Dialysis Conference,
Dallas, TX.
\22\ Chahal, Y., Plumb, T., Aragon M. (2020). Patient Device
Preference for Home Hemodialysis: A Subset Analysis of the Tablo
Home IDE Trial. Poster Presentation at National Kidney Foundation
Spring Clinical Conference, March 2020.
\23\ Kraus, M., et al, A comparison of center-based vs. home-
based daily hemodialysis for patients with end-stage renal disease.
Hemodialysis International, 11: 468-477, (2007).
\24\ Finkelstein, F.O., et al. (2012). At-home short daily
hemodialysis improves the long-term health-related quality of life.
Kidney international, 82(5), 561-569.
\25\ Weinhandl, E.D., Gilbertson, D.T., & Collins, A.J. (2016).
Mortality, hospitalization, and technique failure in daily home
hemodialysis and matched peritoneal dialysis patients: A matched
cohort study. American Journal of Kidney Diseases, 67(1), 98-110.
\26\ Suri, R.S., Li, L., & Nesrallah, G.E. (2015). The risk of
hospitalization and modality failure with home dialysis. Kidney
international, 88(2), 360-368.
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We provided an overview of these ten sources in the CY 2022 ESRD
PPS proposed rule (86 FR 36333 through 36343), followed by the
applicant's summary of how the data support each claim of substantial
clinical improvement.\27\ We also included in the CY 2022 ESRD PPS
proposed rule a discussion of how we were applying the requirements of
Sec. 413.236(b)(5) to our review of the application and a summary of
our preliminary concerns.
[[Page 61892]]
We stated that we did not include detailed summaries of the remaining
supplemental content included with the application. Specifically, the
applicant submitted numerous supplemental background materials related
to the dialysis industry, reimbursement patterns, modalities, treatment
frequencies, patient adherence, hospitalization rates, and quality of
life. The applicant also submitted several letters of support for the
Tablo[supreg] System; three from dialysis patients, three from
nephrologists, and one from a dialysis clinic nurse. These letters
emphasized benefits of the Tablo[supreg] System, including reduced
frequency of dialysis treatment, improved home dialysis retention,
reduced patient and caregiver burden, reduced patient fatigue, and
improved patient quality of life.
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\27\ 86 FR 36335-36342.
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(a) Applicant Substantial Clinical Improvement Sources
As we discussed in the CY 2022 ESRD PPS proposed rule (86 FR
36335), the applicant's primary support for its three substantial
clinical improvement claims came from a prospective, multicenter, open-
label, non-randomized crossover study that compared in-center and in-
home HD performance using the Tablo[supreg] System. Per the applicant,
this study is referred to as the Tablo[supreg] System Investigational
Device Exemption (IDE) Study and the original study protocol and
amendments were approved by FDA and registered on http://www.clinicaltrials.gov as ID: NCT02460263. The applicant stated that of
the 30 participants enrolled (17 White and 13 Black or African
American), 28 (18 men and 10 women) completed the study. Thirteen of
the participants had previous home HD experience with NxStage[supreg],
and the remainder had previously received conventional in-center HD
care. The applicant also noted that the Tablo[supreg] System IDE study
sample was comprised of a representative cohort of dialysis patients
and reported that it was similar to the population studied for the IDE
study for the incumbent NxStage[supreg]. As described in the study
protocol, the primary and secondary efficacy endpoints were a
standardized weekly Kt/V of greater than or equal to 2.1 and
ultrafiltration (fluid removal) value as reported by the device within
ten percent of the expected fluid removal based on the ultrafiltration
prescription and the Tablo[supreg] System Console fluid removal
algorithm, respectively.\28\ We clarified in the CY 2022 ESRD PPS
proposed rule that Kt/V is a value used to quantify dialysis treatment
adequacy and ``K'' = dialyzer clearance, ``t'' = time, and ``V'' =
Volume of distribution of urea. The applicant stated that each study
participant served as his or her own control and remained in the trial
for approximately 21 weeks, during which time they were prescribed HD
with the Tablo[supreg] System on a 4 times per week schedule. The
applicant explained that the trial consisted of 4 treatment periods:
(1) A 1 week, in-center run-in period; (2) an in-center period of 32
treatments (approximately 8 weeks) during which ESRD facility staff
managed the dialysis treatments; (3) a transition period of up to 4
weeks to train the patient and care partner in managing the dialysis;
and (4) a final in-home period of 32 treatments (approximately 8
weeks).
---------------------------------------------------------------------------
\28\ Clinicaltrials.gov website. https://www.clinicaltrials.gov/ct2/show/NCT02460263. Last Updated July 1, 2020. https://www.clinicaltrials.gov/ProvidedDocs/63/NCT02460263/Prot_000.pdf.
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With respect to the applicant's secondary sources of support, a
poster presentation from Alvarez, et al., presented dialysis adequacy
data collected from a retrospective review of 29 patients' (18 males,
11 females and 17 percent Black, 10 percent Hispanic) dialysis records.
The study compared Kt/V results of patients aged 34-84 receiving
dialysis using the Tablo[supreg] System to patients receiving dialysis
from a conventional HD machine. The majority of patients used a fistula
or graft (59 percent fistula, 28 percent graft, 10 percent catheter).
One hundred ninety two dialysis treatments were conducted on a thrice-
weekly schedule using the Tablo[supreg] System with a dialysate flow
rate of 300 mL per minute. A single pool Kt/V of greater than 1.2 was
achieved in 94 percent of treatments in patients less than 90 kg with
an average duration of treatment at 224 +/-29 minutes and in 79 percent
of treatments in patients greater than 90 kg with an average duration
of treatment at 249 +/-27 minutes. The average achieved Kt/V was 1.4 +/
-0.2 among treatments provided with the Tablo[supreg] System. Eighty-
eight treatments were conducted using a conventional HD machine with a
dialysate flow rate of 500 mL per minute. A single pool Kt/V of greater
than 1.2 was achieved in 93 percent of treatments in patients less than
90 kg with an average duration of treatment at 227 +/-21 minutes and in
83 percent of treatments in patients greater than 90 kg with an average
duration of treatment at 249 +/-14 minutes. The average achieved Kt/V
was 1.6 +/-0.4 among the conventional HD treatments.\29\
---------------------------------------------------------------------------
\29\ Alvarez, Luis et al. Urea Clearance Results in Patients
Dialyzed Thrice-weekly Using a Dialysate Flow of 300 mL/min,
clinical abstract, presented March 2019, Annual Dialysis Conference,
Dallas, TX.
---------------------------------------------------------------------------
Next, an article from Chertow, et al., described additional data
from the Tablo[supreg] System IDE study (discussed previously),
including health-related quality of life, to further assess the safety
of home HD with the Tablo[supreg] System. Demographic information
identified the mean age as 49.8 + 13 years, 62 percent male, 62 percent
White, 38 percent Black or African American, 23 percent Hispanic or
Latino, 68 percent Not Hispanic or Latino, and 8 percent not reported,
among patients established on home HD. Among the patients new to home
HD, the mean age was identified as 54.2 + 10.4 years, 65 percent male,
53 percent White, 47 percent Black or African American, 29 percent
Hispanic or Latino, 71 percent Not Hispanic or Latino, and 0 percent
not reported. Twenty-eight of 30 patients (93 percent) completed all
trial periods. Adherence to the prescribed 4 treatments per week
schedule was 96 percent in-center and 99 percent in-home. The median
time to recovery was 1.5 hours during the in-center and 2 hours during
the at-home phase of the trial. Median index values on the 5-level
EuroQol-5 Dimension (EQ-5D-5L) (a self-assessed, health related,
quality of life questionnaire) were similar during the in-center as
compared to in-home dialysis at 0.832 and 0.826, respectively. Patients
new to home HD had lower median values (0.751) for both in-center and
in-home periods. Patients who had used home dialysis prior to the trial
had higher median values during both in-center (0.903) and in-home
(0.906) periods. Patients reported feeling alert or well-rested with
little difficulty falling or staying asleep or feeling tired and worn
out when using the Tablo[supreg] System in either environment. The
authors concluded that when using the Tablo[supreg] System in-home,
patients reported similar time to recovery, general health status, and
sleep quality compared to using the Tablo[supreg] System in-center.\30\
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\30\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
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Next, an article from Leypoldt, et al., described the use of uremic
solute kinetic models to assess dialysis adequacy via theoretical
single pool Kt/V levels when varying the dialysis blood flow rates and
the patient urea volume of distribution. A comparison was made between
dialysate flows of 300 and 500 mL/min at blood flows of both 300 and
400 mL/min. The patient urea volume of
[[Page 61893]]
distribution range modeled by the authors ranged from 25 to 45 L. Under
ideal conditions, the authors demonstrated that with a blood flow of
300 mL per minute, a single pool Kt/V of greater than 1.2 could be
achieved in patients with a urea volume of distribution of 35 L and 240
minutes of dialysis. Patients with a urea volume of distribution of 40
L would require 255 minutes of dialysis. Patients with a urea volume of
distribution of 45 L would require over 270 minutes of dialysis. With a
blood flow of 400 mL per minute, patients with a urea volume of
distribution of 40 L could achieve the target single pool Kt/V of
greater than 1.2 with 240 minutes of dialysis. Patients with a volume
of distribution of 45 L could achieve the target with 270 minutes of
dialysis. The authors did not model urea kinetics for patients with
volumes of distribution greater than 45 L.\31\
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\31\ Leypoldt, J.K., Prichard, S., Chertow, G.M., & Alvarez, L.
(2019). Differential molecular modeling predictions of mid and
conventional dialysate flows. Blood purification, 47(4), 369-376.
---------------------------------------------------------------------------
Next, an article by Plumb, et al., described the Tablo[supreg]
System IDE study (discussed previously). Demographic information
reflected the mean age as 52.3 + 11.6 years, 19 men and the following
racial and ethnic representation: 17 White, 13 Black or African
American, 8 Hispanic or Latino, and 21 Not Hispanic or Latino.
Comparisons among the 28 patients in this study and subsequent
secondary analyses were either made between the 8 weeks of using the
Tablo[supreg] System for in-center HD and the 8 weeks of the
Tablo[supreg] System for in-home HD or between using the Tablo[supreg]
System in-home HD and the treatment provided prior to study enrollment.
In both settings, patients dialyzed using the Tablo[supreg] System 4
times per week. The primary efficacy endpoint was achievement of a
weekly standard Kt/V greater than or equal to 2.1 in both the 8-week
in-center phase of the study and the 8-week in-home phase of the study.
This endpoint was achieved in 199 of 200 weeks in the in-center
dialysis period and in 168 of 171 weeks in the in-home dialysis period.
The primary safety endpoint of adverse event rates were similar at 1.9
percent in the in-center dialysis period and 1.8 percent in the in-home
dialysis period. The secondary efficacy endpoint was whether the
ultrafiltration volume and rate achieved the prescribed levels. In both
in-center and in-home dialysis, 94 percent of treatments achieved
successful delivery of ultrafiltration, defined as a rate within ten
percent of the prescribed value. Of 960 in-center dialysis services and
896 in-home dialysis services, 922 and 884 were completed respectively,
yielding adherence rates of 96 percent and 99 percent.\32\
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\32\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
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Next, a separate article by Plumb et al., reported additional data
from the Tablo[supreg] System IDE study (previously discussed)
regarding participants' assessment of the Tablo[supreg] System's ease-
of-use, the degree of dependence on health care workers and caregivers
after training with the system was complete, and the training time
required for a participant to be competent in self-care. Demographic
information reflected the mean age as 52.6 years, 18 men, 10 women, 16
White, 7 Hispanic or Latino, 9 Not Hispanic or Latino, and 12 Black or
African American. Participants were stratified according to whether
they were previously on self-care dialysis at home or conventional in-
center HD. Thirteen participants had previous experience performing
self-care HD. The remaining 15 participants had previous experience
with in-center HD only. All participants rated the Tablo[supreg]
System's setup, treatment, and takedown on a scale from 1 (very
difficult) to 5 (very simple) and indicated whether they had required
assistance with treatment over the prior 7 days. Set up times were
similar regardless of whether the participants were previously on self-
care HD or conventional in-center HD. For the participants previously
on in-center HD, the average set up time for the concentrates was 0.93
minutes and for the cartridge, 9.35 minutes. For participants
previously on self-care home HD, the average set up time for the
concentrates was 1.22 minutes and for the cartridge, 10.28 minutes. The
average rating of the Tablo[supreg] System's ease of use for setup was
4.5, treatment 4.6, and take down 4.6 among the participants previously
on self-care home HD. In comparison, based on recollection (not based
on rating during time of use) these participants' average rating of
their previous device's ease of use for setup was 3.5, treatment 3.3,
and take down 3.8. The average rating of the Tablo[supreg] System's
ease of use for setup and treatment was 4.6 and 4.7 for take down among
participants without prior self-care experience.
Among patients surveyed, caregiver assistance was required in 62
percent of patient-weeks during home self-care. Participants previously
on self-care home HD required some caregiver assistance in 42 percent
of the in-home dialysis treatment weeks. Participants previously on
conventional in-center dialysis required some caregiver assistance in
35 percent of the in-home dialysis treatment weeks. The requirement for
some form of assistance among participants with or without previous
self-care experience was not meaningfully different. Finally, the
authors noted that a protocol amendment allowed for the recording of
the number of training sessions necessary to deem a patient competent
to do self-care dialysis. This recording was limited to the last 15
participants enrolled into the study. Five of these participants had
previous self-care dialysis at home experience. The average number of
training sessions required to be deemed competent was 3.6 for
participants with previous self-care dialysis at home experience and
3.9 sessions for participants with only conventional in-center HD
experience.\33\
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\33\ Plumb, Troy J., Luis Alvarez, Dennis L. Ross, Joseph J.
Lee, Jeffrey G. Mulhern, Jeffrey L. Bell, Graham E. Abra, Sarah S.
Prichard, Glenn M. Chertow, and Michael A. Aragon. ``Self-care
training using the Tablo hemodialysis system.'' Hemodialysis
International (2020).
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Next, a poster presentation from Chahal, et al., reported patient
device preference of prior in-home HD patients based on data from the
Tablo[supreg] System IDE study (previously discussed). The authors
noted that 13 of the 30 participants in the Tablo[supreg] System IDE
trial were performing in-home HD at the time of enrollment and that
prior to the study, dialysis prescriptions averaged 4.5 treatments per
week with an average time of 3.1 hours per session. Trial prescriptions
were for 4 days per week and an average of 3.4 hours per session.
Adherence to the study regimen was 97 percent and 92 percent of surveys
were completed. The authors concluded that participants with prior home
HD experience preferred the Tablo[supreg] System compared to their
prior device and 85.6 percent found that the Tablo[supreg] System was
easier to use.\34\
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\34\ Chahal, Y., Plumb, T., Aragon M. (2020). Patient Device
Preference for Home Hemodialysis: A Subset Analysis of the Tablo
Home IDE Trial. Poster Presentation at National Kidney Foundation
Spring Clinical Conference, March 2020.
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As stated previously in the CY 2022 ESRD PPS proposed rule (86 FR
36337), the applicant submitted several sources pertaining to the
incumbent, NxStage[supreg]. First, an article from Kraus et al.,
described a feasibility study to demonstrate the safety of center-based
versus home-based daily HD with the NxStage[supreg] portable HD device.
This retrospective analysis examined the extent to which clinical
effects
[[Page 61894]]
previously associated with short-daily dialysis were also seen using
the NxStage[supreg] device. The authors conducted a prospective, two-
treatment, two-period, open-label, crossover study of in-center HD vs.
home HD in 32 patients treated at six U.S. centers. Demographic
information reflected the mean age as 51 years, 63 percent male, 38
percent female, 24 White, 6 Black or African American, 1 American
Indian or Alaskan native, and 1 Asian. The 8-week In-Center Phase (6
days/week) was followed by a 2-week transition period and then followed
by the 8-week Home Phase (6 days/week). Data was collected
retrospectively on HD treatment parameters immediately preceding the
study in a subset of patients. Twenty-six out of 32 patients (81
percent) successfully completed the study. Treatment compliance
(defined as completing 43 to 48 treatments in a given phase) was
comparable between the 2 treatment environments (88 percent In-Center
vs. 89 percent Home). Successful delivery of at least 90 percent of
prescribed fluid volume (primary endpoint) was achieved in 98.5 percent
of treatments in-center and 97.3 percent at home. Total effluent volume
as a percentage of prescribed volume was between 94 percent and 100
percent for all study weeks. The composite rate of intradialytic and
interdialytic adverse events per 100 treatments was significantly
higher for the In-Center Phase (5.30) compared with the Home Phase
(2.10; p=0.007). Compared with the period immediately preceding the
study, there were reductions in blood pressure, antihypertensive
medications, and interdialytic weight gain. The study concluded that
daily home HD with a small, easy-to-use HD device is a viable dialysis
option for ESRD patients capable of self/partner administered
dialysis.\35\
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\35\ Kraus, M., et al., A comparison of center-based vs. home-
based daily hemodialysis for patients with end-stage renal disease.
Hemodialysis International, 11: 468-477, (2007).
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Second, an article from Finkelstein et al., reported on interim
results of the Following Rehabilitation, Economics and Everyday-
Dialysis Outcome Measurements (FREEDOM) study, a multi-center,
prospective, cohort study of at-home short daily HD with a planned 12-
month follow-up (ClinicalTrials.gov identifier, NCT00288613). Eligible
patients were adults with ESRD requiring dialysis who were being
initiated on short daily HD (prescribed 6 times per week) at home using
the NxStage[supreg] cycler and who had Medicare as their primary
insurance payer. The authors examined the long-term effect of short
daily HD on health-related quality of life, as measured by the Short
Form-36 (SF-36) health survey. The survey was administered at baseline,
4 and 12 months after initiation of short daily HD to 291 (total
cohort) participants. Demographic information reflected the mean age as
53 years, 66 percent male and 70 percent White. Of the 291
participants, 154 completed the 12-month follow-up (as-treated cohort).
In the total cohort analysis, both the physical- and mental-
component summary scores improved over the 12-month period, as did all
8 individual domains of the SF-36. The as-treated cohort analysis
showed similar improvements with the exception of the role-emotional
domain. Significantly, in the as-treated cohort, the percentage of
patients achieving a physical component summary score at least
equivalent to the general population more than doubled. The authors
concluded by noting that at-home short daily HD is associated with
long-term improvements in various physical and mental health-related
quality of life measures.\36\
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\36\ Finkelstein, F.O., et al. (2012). At-home short daily
hemodialysis improves the long-term health-related quality of life.
Kidney International, 82(5), 561-569.
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Third, in Weinhandl, et al., authors described a cohort study in
which 4,201 new home HD patients in 2007 were matched with 4,201 new PD
patients in 2010 from the United States Renal Data System (USRDS)
database to assess relative mortality, hospitalization, and technique
failure. Demographic information reflected the mean age as 53.8 + 14.9
years, 67 percent male, 33 percent female, 24.4 percent Black, and 75.6
percent Nonblack. Daily home HD patients initiated use of
NxStage[supreg] from 2007 through 2010. Authors reported home HD was
associated with 20 percent lower risk for all-cause mortality, 8
percent lower risk for all-cause hospitalization, and 37 percent lower
risk for technique failure, all relative to PD. Regarding
hospitalization, risk comparisons favored home HD for cardiovascular
disease and dialysis access infection and PD for bloodstream infection.
Authors noted that matching was unlikely to reduce confounding
attributable to unmeasured factors, including residual kidney function;
lack of data regarding dialysis frequency, duration, and dose in daily
home HD patients and frequency and solution in PD patients; and
diagnosis codes used to classify admissions. The authors concluded that
these data suggest that relative to PD, daily home HD is associated
with decreased mortality, hospitalization, and technique failure but
that risks for mortality and hospitalization were similar with these
modalities in new dialysis patients.\37\
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\37\ Weinhandl, E.D., Gilbertson, D.T., & Collins, A.J. (2016).
Mortality, hospitalization, and technique failure in daily home
hemodialysis and matched peritoneal dialysis patients: a matched
cohort study. American Journal of Kidney Diseases, 67(1), 98-110.
---------------------------------------------------------------------------
Fourth, in Suri et al., 1116, daily home HD patients were matched
by propensity scores to 2,784, contemporaneous USRDS patients receiving
home PD. The authors compared hospitalization rates from
cardiovascular, infectious, access-related or bleeding causes, and
modality failure risk. Similar analyses were performed for 1,187, daily
home HD patients matched to 3,173, USRDS patients receiving in-center
conventional HD. Demographic information identified the mean age as
50.5 years, 67.3 percent male, 70.9 percent White, 26.6 percent Black,
and 2.5 percent Other, among the daily home HD patients. Among the home
PD patients, the mean age was identified as 50.9 years, 66.9 percent
male, 73.1 percent White, 25.1 percent Black and 1.2 percent Other. The
composite hospitalization rate was significantly lower with daily home
HD than with PD (0.93 vs. 1.35/patient-year). Daily home HD patients
spent significantly fewer days in the hospital than PD patients (5.2
vs. 9.2 days/patient-year), and significantly more daily home HD
patients remained admission-free (52 percent daily home dialysis vs. 32
percent PD). In contrast, there was no significant difference in
hospitalizations between daily home HD and conventional HD (0.93 vs.
1.10/patient-year). Cardiovascular hospitalizations were lower with
daily home HD than with conventional HD (0.68) while infectious and
access hospitalizations were higher (1.15) and 1.25 respectively).
Significantly more PD than daily home HD patients switched back to in-
center HD (44 percent vs. 15 percent). In this prevalent cohort, daily
home HD was associated with fewer admissions and hospital days than PD,
and a substantially lower risk of modality failure.\38\
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\38\ Suri, R.S., Li, L., & Nesrallah, G.E. (2015). The risk of
hospitalization and modality failure with home dialysis. Kidney
International, 88(2), 360-368.
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(b) Applicant Substantial Clinical Improvement Claims
Regarding the applicant's first claim that the Tablo[supreg] System
decreases treatment frequency with adequate
[[Page 61895]]
dialysis clearance, the applicant stated that the Tablo[supreg] System
is the only mobile HD device approved for use in the home that can
achieve adequate dialysis in as little as 3 treatments per week, while
also providing flexibility for more frequent dialysis and thus greater
personalization of care. The applicant stated that adequate dialysis
for a standard, thrice-weekly treatment schedule is a single treatment
clearance of urea, expressed as a single-pool Kt/V (spKt/V) of greater
than 1.2 where ``K'' = dialyzer clearance, ``t'' = time, and ``V'' =
Volume of distribution of urea. The applicant also stated that dialyzer
clearance, or ``K'', is dependent on the mass transfer coefficient
(KoA) characteristics of the prescribed dialyzer and prescribed blood
and dialysate flow rates. The applicant further noted that limitations
in ``K'' or ``t'' affect the ability of a patient to achieve adequate
clearance during a dialysis treatment. Per the applicant, across a
broad range of weights, patients using the Tablo[supreg] System can
achieve the target of dialysis adequacy, a single pool Kt/V of 1.2,
with 3 treatments per week in less than 4 hours.\39\ The applicant also
stated that when used 4 times per week, patients using the
Tablo[supreg] System had a higher mean weekly standard Kt/V with
equivalent or better dialysis-related hospitalization rates,\40\ as
compared to NxStage[supreg] IDE patients prescribed therapy at 6 days
per week.\41\
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\39\ Alvarez, Luis et al. Urea Clearance Results in Patients
Dialyzed Thrice-weekly Using a Dialysate Flow of 300 mL/min,
clinical abstract, presented March 2019, Annual Dialysis Conference,
Dallas, TX.
\40\ Plumb, T.J., Alvarez, L., Ross, D.L., Lee, J.J., Mulhern,
J.G., Bell, J.L., Abra, G., Prichard, S.S., Chertow, G.M. and
Aragon, M.A. (2019). Safety and efficacy of the Tablo hemodialysis
system for in-center and home hemodialysis. Hemodialysis
International.
\41\ NxStage Clearance Calculator. Available at: https://dosingcalculator.nxstage.com/DosingCalculator/. Accessed on Jan 21,
2021.
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The applicant stated that the Tablo[supreg] System's on-demand
dialysate production has no limitation to the volume of dialysate that
can be produced and used during a single treatment. The applicant
further stated that this facilitates the delivery of adequate dialysis
clearance (Kt/V) in a standard duration and target frequency of 3 times
per week, as well as alternate frequencies and durations as preferred
by a patient or recommended by a health care provider.
The applicant asserted that NxStage,[supreg] when attached to its
PureFlowTM device, requires users to batch a set amount of
dialysate (maximum of 60 liters) in advance of a treatment or use
sterile dialysate bags (maximum of 30 liters). The applicant also
stated that at its maximum dialysate flow rate (Qd) of 300ml/min,
NxStage[supreg] greatly limits time by restricting treatment to a
maximum of 200 minutes before exhausting its dialysate capacity (200
min = 60L/300ml/min). The applicant stated that Dialysis Outcomes and
Practice Patterns Study (DOPPS) data demonstrate that the current U.S.
practice for thrice-weekly dialysis occurs at an average treatment time
of greater than 220 minutes, and has increased in the last 25
years.\42\ Per the applicant, with the limited ``t'', a single-pooled
Kt/V of >1.2 cannot be expected to be achieved for the majority of U.S.
patients with ESRD on a thrice-weekly schedule, requiring increased
treatment frequency \43\ at home for these patients to meet the desired
clearance level.
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\42\ Tentori F, Zhang J, Li Y, Karaboyas A, Kerr P, Saran R,
Bommer J, Port F, Akiba T, Pisoni R, Robinson B. Longer dialysis
session length is associated with better intermediate outcomes and
survival among patients on in-center three times per week
hemodialysis: Results from the Dialysis Outcomes and Practice
Patterns Study (DOPPS). Nephrol Dial Transplant. 2012
Nov;27(11):4180-8. doi: 10.1093/ndt/gfs021. Epub 2012 Mar 19. PMID:
22431708; PMCID: PMC3529546.
\43\ Health Management Associates (HMA) analysis of 2018 100%
Medicare Outpatient file.
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In citing Leypoldt, et al., the applicant stated that data from the
Hemodialysis (HEMO) trial combined with modeling results from Leypoldt,
et al.,\44\ allowed for an estimation of the patients with ESRD, based
on weight, that cannot be expected to achieve target clearance with
standard thrice-weekly dialysis at this treatment duration. The
applicant explained that because urea is evenly distributed throughout
a body's water, the volume of distribution of urea is equal to a
patient's total volume of water. The applicant also stated that total
body water and volume of distribution of urea can be expressed as a
volume or as a percentage of total weight and can vary based on
numerous factors including disease state. The applicant stated that it
is possible to estimate the percent of water for the ESRD population
from the HEMO trial as summarized in Leypoldt et al.\45\ The applicant
stated that in the trial, the mean patient weight was 69.8kg and the
mean patient volume of body water (V) was 30.9L. The applicant further
explained that from this, total body water (and volume of distribution
of urea) were calculated as 44.3 percent of the mean weight of patients
with ESRD (44.3 = 30.9L/69.8kg x 100). Per the applicant, applying this
44.3 percent of total body weight to the volumes of distribution in
Leypoldt et al.\46\ allowed for the conversion of the kinetic model
described into anticipated patient weights. The applicant further
stated that in calculating with standard blood flow and a higher
dialyzer mass transfer area coefficient for urea (KoA) dialyzer, a 200
minute treatment at a dialysate flow rate (Qd) of 300ml/min would not
achieve what the applicant refers to as the CMS target spKt/V target
1.2 for patients with a volume of distribution of urea (V) of 35L or
greater. The applicant stated that these assumptions were drawn from
NxStage[supreg] technical specifications.47 48 The applicant
stated that at 44.3 percent of total weight, this volume of
distribution of urea correlated to patients with ESRD with a mean
weight above 79 kg (79 = 35L/.443) or approximately 174 pounds. Per the
applicant, patients at or above this weight cannot be expected to
achieve a spKt/V urea of 1.2 on a thrice-weekly schedule using the
NxStage[supreg] system at its maximal dialysate flow rate.
---------------------------------------------------------------------------
\44\ Leypoldt, J.K., Prichard, S., Chertow, G.M., & Alvarez, L.
(2019). Differential molecular modeling predictions of mid and
conventional dialysate flows. Blood purification, 47(4), 369-376.
\45\ Ibid.
\46\ Ibid.
\47\ Leypoldt, J.K., Prichard, S., Chertow, G.M., & Alvarez, L.
(2019). Differential molecular modeling predictions of mid and
conventional dialysate flows. Blood purification, 47(4), 369-376.
\48\ Daugirdas JT, Greene T, Depner TA, Chumela C, Rocco, MJ,
Chertow, GM for the Hemodialysis (HEMO) Study Group.
Anthropometrically Estimated Total Body Water Volumes are Larger
than Modeled Urea Volume in Chronic Hemodialysis Patients: Effects
of Age, Race and Gender. 2003. Kidney Int. 64:1108-1119.
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The applicant stated that for the majority of the U.S. prevalent
ESRD population between the ages of 22-74, whose mean weight is between
84.3-89.1 kg by age group,\49\ thrice-weekly therapy at home on
NxStage[supreg] would not achieve the Medicare coverage standard.
Specifically, per the applicant, Medicare's national coverage policy is
to reimburse for dialysis care 3 times per week, regardless of the
modality that is used, and health care providers are expected to ensure
that patients receive adequate clearance with the 3 times per week
cadence. The applicant also stated that MACs have discretion in
reimbursing additional treatments with medical justification.\50\ Per
the applicant, an analysis of Medicare
[[Page 61896]]
claims data from 2018 found that despite the limitations of the
reimbursement policy, Medicare paid for 5 or more treatments per week
in 50 percent of home HD patients nationwide, amounting to an estimated
annual cost to Medicare of $122 to $126 million.\51\ However, as we
stated in the CY 2022 ESRD PPS proposed rule (86 FR 36339), based on
CMS review of dialysis facility claims data, among all beneficiaries
who had home dialysis treatments in 2018, 39.1 percent had 5 or more
dialysis sessions at least once during any week. The overall percentage
of beneficiary-weeks that had 5 or more home HD sessions in 2018 was
20.9 percent. Medicare payment for these additional sessions totaled
$17 million. We noted that, as indicated in Local Coverage
Determination ID L35014, ``Frequency of Dialysis'' (revised effective
September 26, 2019),\52\ CMS established payment for HD based on
conventional treatment which is defined as 3 times per week. Sessions
in excess of 3 times per week must be both reasonable and necessary in
order to receive payment. Covered indications include metabolic
conditions (acidosis, hyperkalemia, hyperphosphatemia), fluid positive
status not controlled with routine dialysis, pregnancy, heart failure,
pericarditis, and incomplete dialysis secondary to hypotension or
access issues. The applicant asserted that the use of the Tablo[supreg]
System would decrease the number of necessary dialysis treatments,
without affecting patient outcomes such as clearance or
hospitalizations.
---------------------------------------------------------------------------
\49\ United States Renal Data System. 2020 USRDS Annual Data
Report: Epidemiology of kidney disease in the United States, End-
Stage Renal Disease Chapter 2. National Institutes of Health,
National Institute of Diabetes and Digestive and Kidney Diseases,
Bethesda, MD, 2020. Available at: https://adr.usrds.org/2020/end-stage-renaldisease/introduction-to-volume-2. Accessed on Jan 21,
2021.
\50\ Wilk, A.S., Hirth, R.A., Zhang, W., Wheeler, J.R., Turenne,
M.N., Nahra, T. A., . . . & Messana, J.M. (2018). Persistent
variation in Medicare payment authorization for home hemodialysis
treatments. Health services research, 53(2), 649-670.
\51\ Health Management Associates (HMA) analysis of 2018 100
percent Medicare Outpatient file.
\52\ Medicare Coverage Database. Retrieved May 24, 2021 from:
https://www.cms.gov/medicare-coverage-database/details/lcd-details.aspx?LCDId=35014&ver=39&NCDId=79&ncdver=1&SearchType=Advanced&CoverageSelection=Both&NCSelection=NCA%7CCAL%7CNCD%7CMEDCAC%7CTA%7CMCD&ArticleType=Ed%7CKey%7CSAD%7CFAQ&PolicyType=Final&s=-%7C5%7C6%7C66%7C67%7C9%7C38%7C63%7C41%7C64%7C65%7C44&KeyWord=transplant&KeyWordLookUp=Doc&KeyWordSearchType=Exact&kq=true&bc=IAAAADgAAAAA&
.
---------------------------------------------------------------------------
The applicant stated that there was clinical evidence and expert
consensus that as treatment frequency increases, native residual kidney
function drops, patient and care partner burden increases, and vascular
access complications increase.53 54 Per the applicant, home
use of the Tablo[supreg] System could reduce the need for a fifth or
sixth weekly treatment without increasing patients' symptom burden.\55\
The applicant stated that by achieving adequacy targets with fewer
treatments, Tablo[supreg] System patients could be expected to have
fewer vascular access interventions and health care providers will have
increased flexibility in personalizing the frequency and duration of
patient treatments.56 57 The applicant stated that reducing
treatment frequency while maintaining adequate patient clearance levels
may also reduce complications that lead to hospitalizations. The
applicant stated that during the Tablo[supreg] System IDE study,
patients using the Tablo[supreg] System 4 times per week, for an
average duration of less than 4 hours per treatment, had an all-cause
hospital admission rate of 426 per 1,000 patient-years whereas in the
general dialysis population, the all-cause admission rate was 1,688 per
1,000 patient-years, and for patients who utilized PD, the
hospitalization rate was 1,460 per 1,000 patient years.\58\
---------------------------------------------------------------------------
\53\ National Kidney Foundation. KDOQI clinical practice
guideline for hemodialysis adequacy: 2015 update. Am J Kidney Dis.
2015; 66(5):884-930.
\54\ Shafi T, Wilson RF, Greer R, Zhang A, Sozio S, Tan M, Bass
EB. End-stage Renal Disease in the Medicare Population: Frequency
and Duration of Hemodialysis and Quality of Life Assessment.
Technology Assessment Program Project ID No. JHE51000. (Prepared by
the Johns Hopkins University Evidence-based Practice Center under
contract number HHSA 290-2015-00006I) Rockville, MD: Agency for
Healthcare Research and Quality. July 2020. Available at: http://www.ahrq.gov/research/findings/ta/index.html.
\55\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
\56\ FHN Trial Group. (2010). In-center hemodialysis six times
per week versus three times per week. New England Journal of
Medicine, 363(24), 2287-2300.
\57\ Kuo, T.H., Tseng, C.T., Lin, W.H., Chao, J.Y., Wang, W.M.,
Li, C.Y., & Wang, M.C. (2015). Association Between Vascular Access
Dysfunction and Subsequent Major Adverse Cardiovascular Events in
Patients on Hemodialysis: A Population-Based Nested Case-Control
Study. Medicine, 94(26).
\58\ United States Renal Data System. 2020 USRDS Annual Data
Report: Epidemiology of kidney disease in the United States, End-
Stage Renal Disease Chapter 2. National Institutes of Health,
National Institute of Diabetes and Digestive and Kidney Diseases,
Bethesda, MD, 2020. Available at: https://adr.usrds.org/2020/end-stage-renaldisease/introduction-to-volume-2. Reference Table G2.
---------------------------------------------------------------------------
The applicant stated that while NxStage[supreg] has not
specifically reported the hospitalization rates per patient-year from
its IDE study, published data from Weinhandl et al.,\59\ and Suri et
al.,\60\ reported hospital admission rates amongst patients on daily
home HD ranging from 930 to 1,663 per 1,000 patient-years, using a
national sample of dialysis patients matched for comparison to similar
peritoneal and in-center dialysis patients. We clarified in the CY 2022
ESRD PPS proposed rule (86 FR 36339-36340) that this would represent
930 to 1,663 cases observed among 1,000 persons during 1 year. The
applicant also noted that all data on home patients in Weinhandl et al.
came from a matched cohort of NxStage[supreg] patients. Per the
applicant, in Suri et al., data were collected prior to 2015 and that
during this timeframe, it could be reasonably assumed that home HD
patients were using NxStage[supreg] for treatment. The applicant stated
that the results from these studies suggested that patients receiving
treatment at home with NxStage[supreg] 5 to 6 times per week do not
have a lower all-cause hospitalization rate, relative to matched in-
center HD patients. The applicant concluded by stating that because of
the clinical and demographic diversity of the Tablo[supreg] System's
patient population, the applicant's results showed incremental
improvement over the hospitalization rate of the current home HD
population.
---------------------------------------------------------------------------
\59\ Weinhandl, E.D., Gilbertson, D.T., & Collins, A.J. (2016).
Mortality, hospitalization, and technique failure in daily home
hemodialysis and matched peritoneal dialysis patients: a matched
cohort study. American Journal of Kidney Diseases, 67(1), 98-110.
\60\ Suri, R.S., Li, L., & Nesrallah, G.E. (2015). The risk of
hospitalization and modality failure with home dialysis. Kidney
international, 88(2), 360-368.
---------------------------------------------------------------------------
Regarding the applicant's second claim that the Tablo[supreg]
System increased adherence to dialysis treatment and retention to home
therapy, the applicant stated that patients using the Tablo[supreg]
System have improved adherence to prescribed treatments and a higher
rate of retention to home therapy. The applicant further stated that
this increased adherence and retention is likely to improve patient
outcomes by reducing the rate of dialysis-related hospitalizations and
other adverse events associated with missing treatment in this patient
population.\61\
---------------------------------------------------------------------------
\61\ Chan, K.E., Thadhani, R.I., & Maddux, F.W. (2014).
Adherence barriers to chronic dialysis in the United States. Journal
of the American Society of Nephrology, 25(11), 2642-2648. Supporting
evidence of association between decreased dialysis adherence and
poor patient health and utilization outcomes.
---------------------------------------------------------------------------
The applicant stated that adherence to prescribed dialysis
treatments is crucial for dialysis patients because missed treatments
increased the risk of dialysis dropout, hospitalization, and death.\62\
Per the applicant, the Tablo[supreg] System IDE study demonstrated a 99
percent treatment adherence rate to all
[[Page 61897]]
prescribed home treatments \63\ among both prior in-center participants
and prior self-care home HD participants who used NxStage[supreg]. The
applicant also stated that the Tablo[supreg] System's adherence rates
were similar among both the prior in-center and prior self-care
participants. The applicant stated that these results represent a
significant improvement over the treatment adherence rate reported in
the NxStage[supreg] IDE, where the treatment compliance rate was
defined less stringently as missing 5 or fewer treatments of the 48
possible treatments and was only 89 percent among patients at home and
during the study period.\64\ Per the applicant, using a comparable
metric of missing 5 or fewer of all possible treatments at home,
Tablo[supreg] System IDE patients at home had a 100 percent treatment
compliance rate.
---------------------------------------------------------------------------
\62\ Weinhandl, Eric D., Collins Allan, Incidence of Therapy
Cessation among Home Hemodialysis Patients in the United States,
Abstract presented, American Society of Nephrology Kidney Week 2016.
\63\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
\64\ Kraus, M., et al. A comparison of center-based vs. home-
based daily hemodialysis for patients with end-stage renal disease.
Hemodialysis International, 11: 468-477, (2007). The authors
performed a feasibility study to demonstrate the safety of center-
based vs. home-based daily hemodialysis with the NxStage System One
portable hemodialysis device.
---------------------------------------------------------------------------
The applicant stated that technique failure in home HD, defined as
reduced retention at home and a return to in-center care, has been high
with NxStage[supreg]. Per the applicant, real world data show that
technique failure occurs in 36 percent of home HD patients using
NxStage[supreg] within 1 year of initiating treatment.\65\ The
applicant stated that this was challenging for the patient and taxing
on the healthcare system that had invested in providing patients with
home dialysis training and in paying for more frequent therapy.
---------------------------------------------------------------------------
\65\ Weinhandl, Eric D., Collins Allan, Incidence of Therapy
Cessation among Home Hemodialysis Patients in the United States,
Abstract presented, American Society of Nephrology Kidney Week 2016.
---------------------------------------------------------------------------
The applicant stated that by directly comparing the Tablo[supreg]
System's retention to that of NxStage[supreg], the applicant assessed
rates in the analogous IDE populations while excluding those who exited
either study for reasons unrelated to the device such as receipt of a
transplant or death. The applicant stated that the Tablo[supreg] System
demonstrated a 97 percent (28 of 29) patient retention rate for the
entire IDE study and a 100 percent retention rate in the in-home phase
of the trial among both prior NxStage[supreg] users and prior in-center
patients.\66\ The applicant stated that in comparison, 81 percent of
participants completed the NxStage[supreg] IDE study.\67\
---------------------------------------------------------------------------
\66\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
\67\ Kraus M, Burkart J, Hegeman R, Solomon R, Coplon N, Moran
J. A comparison of center-based vs. home-based daily hemodialysis
for patients with end-stage renal disease. Hemodial Int. 2007 Oct;
11(4):468-77. doi: 10.1111/j.1542-4758.2007.00229.x. PMID: 17922746.
---------------------------------------------------------------------------
The applicant stated that the Tablo[supreg] System's ease of use
contributed to the improved adherence and retention rates and that the
Tablo[supreg] System is designed to enable patients to become
proficient and independent in using the Tablo[supreg] System after an
average of 3.9 days.\68\ Per the applicant, published NxStage[supreg]
IDE data \69\ reported an average of 14.5 days ``to complete device
training on NxStage[supreg].'' The applicant stated that, in
comparison, device-related training time is reduced by at least 50
percent on the Tablo[supreg] System. Per the applicant, the reduced
training time and ease of use would likely improve retention and
potentially reduce the number of reimbursable training sessions. The
applicant stated that because of the significant role that caregivers
play in supporting home dialysis treatments,\70\ care partner burnout
and a patient's perception of being a burden is associated with
discontinuation of home therapy.71 72
---------------------------------------------------------------------------
\68\ Plumb, Troy J., Luis Alvarez, Dennis L. Ross, Joseph J.
Lee, Jeffrey G. Mulhern, Jeffrey L. Bell, Graham E. Abra, Sarah S.
Prichard, Glenn M. Chertow, and Michael A. Aragon. ``Self-care
training using the Tablo hemodialysis system.'' Hemodialysis
International (2020).
\69\ Kraus, M., et al, A comparison of center-based vs. home-
based daily hemodialysis for patients with end-stage renal disease.
Hemodialysis International, 11: 468-477, (2007).
\70\ Seshasai, R.K., et al. (2019) The home hemodialysis patient
experience: A qualitative assessment of modality use and
discontinuation. Hemodialysis International, 23: 139-150 (2019).
\71\ Suri, R.S., Larive, B., Hall, Y., Kimmel, P.L., Kliger,
A.S., Levin, N., . . . & Frequent Hemodialysis Network (FHN) Trial
Group. (2014). Effects of frequent hemodialysis on perceived
caregiver burden in the Frequent Hemodialysis Network trials.
Clinical Journal of the American Society of Nephrology, 9(5), 936-
942.
\72\ Jacquet, S., & Trinh, E. (2019). The potential burden of
home dialysis on patients and caregivers: a narrative review.
Canadian journal of kidney health and disease, 6, 2054358119893335.
---------------------------------------------------------------------------
Per the applicant, the 28 patients who entered the home phase of
the Tablo[supreg] System IDE study were asked weekly if they needed
help with their dialysis treatments during the prior 7 days. The
applicant stated that a 96 percent response rate (216 of 224 possible)
was achieved at the end of the study and that for both prior-in-center
and NxStage[supreg] study participants, in 79 percent of the treatment
weeks, patients reported needing no assistance from their care partner
in performing dialysis set-up, treatment, or breakdown. The applicant
explained that among the 13 prior in-home patients, all of whom were
formerly NxStage[supreg] users, participants reported needing help from
a trained individual with dialysis treatment in 69 percent of treatment
weeks, with 46 percent of instances involving a need for device-related
help. We clarified in the CY 2022 ESRD PPS proposed rule (86 FR 36340--
36341) that per Plumb, et al.,\73\ this was the baseline percentage and
reflected 9 of the 13 patients with previous self-care experience. The
applicant stated that patients reported needing help with treatment in
only 42 percent of treatment weeks while using the Tablo[supreg]
System, which was a 39 percent reduction from baseline NxStage[supreg]
use; and only 18 percent of these instances related to use of the
Tablo[supreg] System, which was a 61 percent reduction in rate from
baseline NxStage[supreg] use.\74\
---------------------------------------------------------------------------
\73\ Plumb, Troy J., Luis Alvarez, Dennis L. Ross, Joseph J.
Lee, Jeffrey G. Mulhern, Jeffrey L. Bell, Graham E. Abra, Sarah S.
Prichard, Glenn M. Chertow, and Michael A. Aragon. ``Self-care
training using the Tablo hemodialysis system.'' Hemodialysis
International (2020).
\74\ Ibid.
---------------------------------------------------------------------------
The applicant stated that it collected weekly data from patients by
asking them to rate the extent to which they believed that they were a
burden on a scale of 1 to 5, with 1 representing never and 5
representing always. The applicant stated that this measure was adapted
from an instrument used in assessing terminally ill patients.\75\ The
applicant stated that the subpopulation of study participants who had
previously used NxStage[supreg] reported an average score of 3.1 for
self-perceived burden on their care partner when using their prior
device, which subsequently reduced to 2.4 when using the Tablo[supreg]
System (a 23 percent reduction in score from baseline NxStage[supreg]
use).\76\ Per the applicant, these data underscored that a significant
increase in patients' confidence, ability to achieve treatment
independence at home, and subsequent reduction in the sense of self
burden can positively contributed to success in the home setting. The
applicant further noted that the ease of use, reduced training time,
and substantial reduction in care partner assistance required for
[[Page 61898]]
the Tablo[supreg] System correlated to the improved retention and
adherence rates in the Tablo[supreg] System IDE study. The applicant
stated that on a population level, this likely translated to reduced
barriers to continuing home HD once initiated, and ultimately, a
reduced risk of adverse outcomes due to missed treatments. The
applicant also stated that the Tablo[supreg] System's electronic data
capture and automatic wireless transmission eliminates the need for
manual record keeping, which represented an improvement with respect to
burden and monitoring as compared to NxStage[supreg].
---------------------------------------------------------------------------
\75\ Chochinov, H.M., Kristjanson, L.J., Hack, T.F., Hassard,
T., McClement, S., & Harlos, M. (2007). Burden to others and the
terminally ill. Journal of pain and symptom management, 34(5), 463-
471.
\76\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
---------------------------------------------------------------------------
Regarding the applicant's third claim that the Tablo[supreg] System
improved patient quality of life, the applicant stated that patients on
the Tablo[supreg] System experienced reduced disease burden, dialysis
related symptoms, and an improved quality of life at home as compared
to in-center and existing home care options. Per the applicant,
patients with ESRD experience significant dialysis-related symptoms
including difficulty sleeping, dizziness, and pain associated with
recovery time that affect mental and physical health and lead to
decreased overall quality of life.\77\ Per the applicant, the
Tablo[supreg] System IDE study assessed several validated Patient-
Reported Outcome Measures (PROMs) to better understand overall health-
related quality of life (HR-QoL). The applicant explained that the
overall measure was the EQ-5D-5L, a validated, preference-based PROM in
which patients self-assess mobility, self-care, usual activities, pain/
discomfort, and anxiety/depression.\78\ The applicant stated that from
these domains, an index value is calculated to report a summary score
that ranges from 0 (death) to 1 (full health).
---------------------------------------------------------------------------
\77\ Gabbay, E., Meyer, K.B., Griffith, J.L., Richardson, M.M.,
& Miskulin, D.C. (2010). Temporal trends in healthrelated quality of
life among hemodialysis patients in the United States. Clinical
journal of the American Society of Nephrology, 5(2), 261-267.
\78\ Yang, F., Wong, C.K., Luo, N., Piercy, J., Moon, R., &
Jackson, J. (2019). Mapping the kidney disease quality of life 36-
item short form survey (KDQOL-36) to the EQ-5D-3L and the EQ-5D-5L
in patients undergoing dialysis. The European Journal of Health
Economics, 20(8), 1195-1206.
---------------------------------------------------------------------------
Per the applicant, while the NxStage[supreg] IDE study did not
report results for a quality-of-life instrument, HR-QoL was assessed in
NxStage[supreg] patients in a prospective multicenter observational
study referred to as the FREEDOM trial, which examined the effects of
at-home dialysis 6 times per week with the NxStage[supreg] System on
costs and HR-QoL using the SF-36 instrument. The applicant further
stated that the reported results at 4-month follow-up among these
patients \79\ translates to a mean EQ-5D score of 0.70. The applicant
included an appendix describing the Methodology to Derive EQ-5D Scores
from the FREEDOM Study Results in its application and derived a
predicted mean EQ-5D score of 0.695-0.70 at follow up for the FREEDOM
study. The applicant further noted that because this estimate is based
on the average aggregate change for an adjusted measure that was then
translated to the EQ-5D scale, and the applicant did not have access to
standard error estimates for the Mental Component Score (MCS) and
Physical Component Score (PCS), its interpretation of this estimate and
its variance is limited. Per the applicant, nonetheless, it provided a
sense of the comparable HR-QoL of this sample of NxStage[supreg]
patients at follow-up. The applicant further noted that mean EQ-5D
index values for traditional HD and PD patients reported from a meta-
analysis of existing studies in the literature are 0.56 (95 percent CI:
0.49-0.62) and 0.58 (95 percent CI: 0.5-0.67), respectively.\80\
---------------------------------------------------------------------------
\79\ Finkelstein, F.O., et al. (2012). At-home short daily
hemodialysis improves the long-term health-related quality of life.
Kidney international, 82(5), 561-569.
\80\ Liem, Y.S., Bosch, J.L., & Hunink, M.M. (2008). Preference-
based quality of life of patients on renal replacement therapy: a
systematic review and meta-analysis. Value in Health, 11(4), 733-
741.
---------------------------------------------------------------------------
Per the applicant, patients in the Tablo[supreg] System IDE study
reported mean EQ-5D index values of 0.821 (SD: 0.163) \81\
in the home phase of the study with final measures taken at
approximately 5 months from trial start. The applicant stated that this
is a significant improvement when using traditional HD patients as a
comparator, and higher overall HR-QoL as compared to NxStage[supreg]
patients. The applicant emphasized that participants in the
Tablo[supreg] System IDE trial underwent a reduced treatment frequency
as compared to participants in the FREEDOM study who were prescribed 6
treatments per week on NxStage[supreg]. The applicant stated that among
patients in the Tablo[supreg] System IDE study who had previously been
using NxStage[supreg], the mean EQ-5D score during the in-home phase of
the study was 0.906 (SD: 0.119) and asserted that this is
significantly greater than index population values for HD and PD.
---------------------------------------------------------------------------
\81\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
---------------------------------------------------------------------------
The applicant stated that sleep problems are present in 60 percent
of patients with chronic kidney disease (CKD) and ESRD \82\ and that
patients ranked fatigue and lack of energy as the most important
contributor to their decreased quality of life.\83\ Per the applicant,
the frequency of sleep-related symptoms among the Tablo[supreg]
System's patients was assessed by a survey that was administered weekly
during the Tablo[supreg] System IDE study. The applicant stated that,
in the absence of a well-validated sleep survey specific to the ESRD
population, study investigators selected survey questions from
previously validated sleep questionnaires in the non-ESRD population,
based on their relevance to the study population.84 85 The
applicant explained that questions were designed to focus on quality of
sleep and restfulness and noted that these measures are validated for
use among chronically ill populations and measure the frequency of 4
key sleep-related symptoms. The applicant stated that, while at home,
patients on the Tablo[supreg] System reported improved quality of
sleep, with a measurable reduction in rate of patient-reported sleep
symptoms ranging from a 10-60 percent reduction, depending on
symptom.\86\ The applicant stated that this reduction was observed
among study participants who were previously receiving dialysis in-
center (average magnitude of reduction in rate across symptoms: 42
percent) and among study participants who were previously receiving in-
home dialysis on NxStage[supreg] (average magnitude of reduction in
rate across symptoms: 27 percent). Per the applicant, on average,
sleep-related difficulties reduced from being reported in 33 percent of
treatment weeks while on NxStage[supreg] to 23 percent of treatment
weeks while on the Tablo[supreg] System.
---------------------------------------------------------------------------
\82\ Davison SN, Levin A, Moss AH, Jha V, Brown EA, Brennan F,
Murtagh FE, Naicker S, Germain MJ, O'Donoghue DJ, Morton RL, Obrador
GT; Kidney Disease: Improving Global Outcomes. Executive summary of
the KDIGO Controversies Conference on Supportive Care in Chronic
Kidney Disease: developing a roadmap to improving quality care.
Kidney Int. 2015 Sep;88(3):447-59.
\83\ Urquhart-Secord, Rachel et al (2016). Patient and Caregiver
Priorities for Outcomes in Hemodialysis: An International Nominal
Group Technique Study American Journal of Kidney Diseases, Volume
68, Issue 3, 444-454.
\84\ Morin, C.M., Belleville, G., B[eacute]langer, L., & Ivers,
H. (2011). The Insomnia Severity Index: psychometric indicators to
detect insomnia cases and evaluate treatment response. Sleep, 34(5),
601-608.
\85\ Natale, V., Fabbri, M., Tonetti, L., & Martoni, M. (2014).
Psychometric goodness of the mini sleep questionnaire. Psychiatry
and clinical neurosciences, 68(7), 568-573.
\86\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
---------------------------------------------------------------------------
[[Page 61899]]
The applicant stated that hypotensive symptoms such as feelings of
dizziness and lightheadedness are associated with the drops in blood
pressure that can occur during dialysis and are also among the top ten
symptoms dialysis patients report that impact their quality of
life.\87\ Per the applicant, participants in the Tablo[supreg] System
IDE study were asked at the time of enrollment regarding symptoms
previously experienced during dialysis. The applicant also stated that
at the end of each study treatment, participants were surveyed
regarding the presence of any symptoms during that treatment on the
Tablo[supreg] System. Per the applicant, a total of 8 (26.7 percent)
subjects reported hypotensive symptoms during the Tablo[supreg] System
treatments during the in-home treatment period, compared to 27 (90
percent) subjects reporting hypotensive symptoms at baseline (prior to
initiating care on the Tablo[supreg] System). The applicant reported a
70 percent reduction in the rate of patient-reported hypotensive
symptoms while on the Tablo[supreg] System, though, as we stated in the
CY 2022 ESRD PPS proposed rule (86 FR 36342), we were unable to
validate the source of this statement.
---------------------------------------------------------------------------
\87\ Urquhart-Secord, Rachel et al (2016). Patient and Caregiver
Priorities for Outcomes in Hemodialysis: An International Nominal
Group Technique Study American Journal of Kidney Diseases, Volume
68, Issue 3, 444-454.
---------------------------------------------------------------------------
The applicant stated that currently, ESRD patients on dialysis
report meaningfully lower quality of life compared to those with other
chronic illnesses.\88\ The applicant further noted that decreased
quality of life is associated with a meaningful decline in continuation
of home therapy, dialysis frequency, and worse clinical and health care
utilization outcomes.\89\
---------------------------------------------------------------------------
\88\ Liem, Y.S., Bosch, J.L., Arends, L.R., Heijenbrok-Kal,
M.H., & Hunink, M.M. (2007). Quality of life assessed with the
Medical Outcomes Study Short Form 36-Item Health Survey of patients
on renal replacement therapy: a systematic review and meta-analysis.
Value in Health, 10(5), 390-397.
\89\ Lowrie, E.G., Curtin, R.B., LePain, N., & Schatell, D.
(2003). Medical outcomes study short form-36: a consistent and
powerful predictor of morbidity and mortality in dialysis patients.
American Journal of Kidney Diseases, 41(6), 1286-1292.
---------------------------------------------------------------------------
The applicant concluded by asserting that the totality of evidence
submitted in support of the Tablo[supreg] System demonstrates
substantial clinical improvement over the current standard of home
dialysis care. The applicant also stated that patient preference for
devices is currently used by FDA to guide marketing authorization
decisions and provides important information on the benefit and risks
that some patients are willing to trade when choosing a device.\90\ Per
the applicant, patients may be more likely to choose home dialysis to
the extent that the device is both accessible and easy to use. The
applicant also stated that 86 percent of prior NxStage[supreg] patients
in the Tablo[supreg] System IDE study found the Tablo[supreg] System
easier to use than their incumbent device and preferred to remain on
the Tablo[supreg] System at the end of the study.\91\
---------------------------------------------------------------------------
\90\ Food and Drug Administration Center for Devices and
Radiological Health (2020). ``Patient Preference-Sensitive Areas:
Using Patient Preference Information in Medical Device Evaluation''
Available at: https://www.fda.gov/about-fda/cdrh-patient-engagement/patient-preference-sensitive-areas-using-patientpreference-information-medical-device-evaluation. Accessed Jan 21, 2021.
\91\ Chahal, Y., Plumb, T., Aragon M. (2020). Patient Device
Preference for Home Hemodialysis: A Subset Analysis of the Tablo
Home IDE Trial. Poster Presentation at National Kidney Foundation
Spring Clinical Conference, March 2020.
---------------------------------------------------------------------------
In summary, the applicant claimed that the Tablo[supreg] System
improves the treatment of Medicare beneficiaries relative to the
incumbent by focusing on outcomes set forth in Sec.
412.87(b)(1)(ii)(C), including a decreased number of treatments to
achieve dialysis adequacy, which the applicant stated leads to greater
adherence to prescribed therapy, and improved quality of life.
(c) CMS Assessment of Substantial Clinical Improvement Claims and
Sources
As discussed in the CY 2022 ESRD PPS proposed rule (86 FR 36342),
after a review of the information provided by the applicant, we had
identified the following preliminary concerns regarding the substantial
clinical improvement eligibility criterion for the TPNIES. We noted
that, consistent with Sec. 413.236(c), CMS would announce its final
determination regarding whether the Tablo[supreg] System meets the
substantial clinical improvement criterion and other eligibility
criteria for the TPNIES in this CY 2022 ESRD PPS final rule.
With respect to the applicant's claim that patients can achieve
dialysis adequacy in as little as 3 treatments per week, we noted that
the Tablo[supreg] System IDE study did not test whether patients
receive adequate dialysis on a thrice-weekly schedule. Instead, data
published from the Tablo[supreg] System IDE study addressed a weekly
measure of dialysis adequacy among patients treated on a 4 times per
week schedule. The applicant relied on modeling and unpublished data on
patients receiving thrice-weekly dialysis in making the conclusion that
dialysis adequacy can be reached on a thrice-weekly schedule.
Specifically, the applicant referred to a theoretical modeling study
based on historical data from the USRDS, Medicare claims, and
historical outcomes from NxStage[supreg] observational studies. The
applicant also stated that findings from a retrospective review of 29
patients receiving treatment with the Tablo[supreg] System on a thrice-
weekly schedule affirmed the results from the modeling study. We also
noted that the authors in Alvarez et al.\92\ stated that conclusions
about fluid removal could not be made from their study.
---------------------------------------------------------------------------
\92\ Alvarez, Luis et al. Urea Clearance Results in Patients
Dialyzed Thrice-weekly Using a Dialysate Flow of 300 mL/min,
clinical abstract, presented March 2019, Annual Dialysis Conference,
Dallas, Texas.
---------------------------------------------------------------------------
We stated that we were interested in whether additional studies
were available that address issues related to effective fluid removal
using home self-care dialysis thrice-weekly with the Tablo[supreg]
System. We invited comments on whether less frequent dialysis sessions
would represent substantial clinical improvement over shorter, more
frequent sessions that, according to the applicant, were common among
users of the incumbent technology.
The applicant's second claim was that the Tablo[supreg] System
increased adherence to dialysis treatment and retention to home
therapy, which may reduce dialysis-related hospitalizations and other
adverse events associated with missing treatment. This claim was
supported by the Tablo[supreg] System IDE study (28 participants
completed the study) and the use of historical comparisons to prior
studies involving the NxStage[supreg] System. The applicant noted that
hospitalization rates from the Tablo[supreg] System IDE trial were
lower than rates in the general dialysis population and rates reported
in two observational studies of patients using the NxStage[supreg]
device. While the applicant cited an all-cause hospitalization rate of
426 per 1000 patient years in the Tablo[supreg] System IDE study, we
pointed out in the CY 2022 ESRD PPS proposed rule that it did not
appear that the sources 93 94 published these
hospitalization rates. We further noted that the applicant relied on
historical comparisons in asserting that that patients treated with the
Tablo[supreg] System experience reduced
[[Page 61900]]
disease burden and improved quality of life.
---------------------------------------------------------------------------
\93\ Safety and efficacy of the Tablo hemodialysis system for
in-center and home hemodialysis Plumb, T.J., Alvarez, L., Ross,
D.L., Lee, J.J., Mulhern, J.G., Bell, J.L., Abra, G., Prichard,
S.S., Chertow, G.M. and Aragon, M.A. (2019), Hemodialysis
International.
\94\ Chertow, G.M., Alvarez, L., Plumb, T.J., Prichard, S.S., &
Aragon, M. (2020). Patient-reported outcomes from the
investigational device exemption study of the Tablo hemodialysis
system. Hemodialysis International, 24(4), 480-486.
---------------------------------------------------------------------------
We noted in the CY 2022 ESRD PPS proposed rule (86 FR 36343) that
in the Tablo[supreg] System IDE study, the before-after comparisons in
patients with NxStage[supreg] regarding improved sleep compared to
prior to the Tablo[supreg] System may be prone to recall bias in that
participants' experiences with NxStage[supreg] were not recorded at the
time they were receiving NxStage[supreg] treatments, but rather, were
based on recall at the time of the Tablo[supreg] System IDE study.
We stated that we understood that greater flexibility for patients
in the way that they receive their dialysis treatments may represent a
benefit to Medicare beneficiaries who are candidates to receive this
treatment in the home setting. We invited comments on whether this
potential benefit represents substantial clinical improvement,
including whether the Tablo[supreg] System represented an advance that
substantially improves, relative to renal dialysis services previously
available, the treatment of Medicare beneficiaries.
We received multiple comments on the substantial clinical
improvement claims made in the TPNIES application for the Tablo[supreg]
System, ranging from commenters with concerns about the claims,
including from a manufacturer of a competitor device, to comments in
support of the application, including from the applicant. The comments
on the three substantial clinical improvement claims made by the
applicant, and our responses to the comments, are set forth below.
Comment: A commenter, a manufacturer of a competitor device,
asserted that the Tablo[supreg] System does not meet the substantial
clinical improvement criterion. The commenter asserted that the
applicant's claims were not supported by robust clinical evidence. The
commenter made several criticisms about the Tablo[supreg] System IDE
trial and the other clinical evidence provided by the applicant,
emphasizing the lack of a direct head-to-head comparison with the
NxStage[supreg] device as well as relying on theoretical modeling. For
example, the commenter stated that the applicant did not submit
adequate evidence to demonstrate its first claim, that decreased home
HD treatment frequency with the Tablo[supreg] System offered a
substantial clinical benefit for home HD patients, because the
applicant's study examined patients that dialyzed on the Tablo[supreg]
System more than three times per week and did not compare the
Tablo[supreg] System machine to the NxStage[supreg] machine, which the
commenter claimed is also capable of thrice-weekly dialysis. Further,
the commenter stated that current models of the NxStage[supreg] System
OneTM offer dialysate flow rates of 300ml/minute and
NxStage[supreg] patients can currently dialyze with any amount of
dialysate prescribed by their doctor. The commenter asserted that the
NxStage[supreg] machine is more flexible than the Tablo[supreg] System
and that other incumbent systems, such as the Fresenius
2008K@homeTM, are capable of even more urea clearance than
the Tablo[supreg] System in the same amount of time. Even though the
commenter stated that patients using other home HD machines are able to
achieve dialysis adequacy on a thrice-weekly dialysis schedule, the
commenter also stated that it was not aware of any additional data in
support of adequate fluid removal using a thrice-weekly dialysis
schedule with the Tablo[supreg] System.
The commenter also expressed concerns with the applicant's claim
that less frequent dialysis sessions may represent substantial clinical
improvement over shorter, more frequent sessions because certain
clinical and quality of life advancements, like more energy and
vitality, are closely linked to more frequent treatments, which more
closely mirror the natural function of a patient's kidney. This same
point was also raised by other commenters, including health care
providers. These other commenters also expressed a preference for more
frequent dialysis stating that it results in increased energy levels,
improved sleep and mental health, and that patients undergoing more
frequent dialysis need fewer dietary restrictions and antihypertensive
and phosphate binder medications. Additionally, the commenter stated
that evidence suggests there is no disadvantage in access complications
for patients that undergo more frequent dialysis, while also noting
that the applicant did not present studies that compared vascular
access with the Tablo[supreg] System to NxStage[supreg].
The commenter stated that the applicant did not provide sufficient
clinical evidence for its claim that the Tablo[supreg] System results
in an incremental improvement in hospitalization rates because the
sources that the applicant provided were not yet published.
Similarly, the commenter asserted that the applicant did not
demonstrate that the Tablo[supreg] System increases adherence to the
dialysis treatment and retention to home therapy because the studies
cited by the applicant did not compare adherence, retention, or ease of
use for the Tablo[supreg] System with the NxStage[supreg] or the
Fresenius 2008K@homeTM systems. The commenter stated that
the Tablo[supreg] System IDE study on which the applicant relied to
demonstrate treatment adherence and retention had several weaknesses
including a small patient population, narrow patient inclusion
criteria, and short duration. While the commenter acknowledged that the
applicant did compare adherence rates from the Tablo[supreg] System IDE
Study to adherence in the NxStage[supreg] IDE study, the commenter
explained that this methodology was not appropriate because the studies
had different definitions of treatment compliance. The commenter noted
that the applicant's comparison of patient retention rates from the
Tablo[supreg] System and NxStage[supreg] IDE studies was similarly not
appropriate because the equipment used during the time of the
NxStage[supreg] IDE study was completely different from that which is
widely used today (that is, NxStage[supreg] touchscreen
VersiHDTM, Express Warmer, PureFlowTM SL).
Also, regarding the applicant's adherence claim, the commenter
identified several factors that it argued may reduce dialysis adherence
using the Tablo[supreg] System and restrict its use to a small subset
of dialysis patients. First, the commenter stated that patients without
consistent access to clean tap water may be at risk for disruptions in
dialysis treatment with the Tablo[supreg] System. The commenter
identified potential tap water disruptions such as water main breaks or
the loss tap water during power outages for patients who rely on well-
based water. The commenter further stated that water source disruptions
do not hinder NxStage[supreg] patients from continuing their treatment
because they can treat with pre-mixed dialysate bags. The commenter
concluded that the Tablo[supreg] System's on-demand dialysate
production is not a substantial clinical improvement over the
NxStage[supreg] System OneTM with PureFlowTM SL's
on-site dialysate production. Second, the commenter stated, as did
several other commenters, that the Tablo[supreg] System increases
electric and water utility expenses by requiring a large volume of
water to complete the reverse osmosis process and because the system
must heat the water prior to use for dialysate and for sterilization
after treatment. Third, the commenter stated that the Tablo[supreg]
System has not received FDA marketing authorization for solo home
hemodialysis (hemodialysis without a care partner) during waking hours,
as well as nocturnal home hemodialysis, whereas the NxStage[supreg]
System OneTM has received these FDA marketing
authorizations.
[[Page 61901]]
The commenter stated that the applicant did not provide sufficient
evidence to advance its claim that the Tablo[supreg] System improves
patient quality of life. The commenter stated that no comparison of
incremental benefit in quality of life of the Tablo[supreg] System over
NxStage[supreg] was provided. The commenter further stated that studies
involving hundreds of patients have been specifically designed to test
quality of life outcomes, among NxStage[supreg] users and have been
published in peer-reviewed journals demonstrating quality of life
improvements among NxStage[supreg] users. The commenter stated that
there is a high bar for relying on quality of life evidence to
demonstrate innovation, recognizing the breadth of evidence that exists
for current technologies. Regarding the applicant's evidence on its
improved patient quality of life claim, the commenter stated that it
was unable to confirm the applicant's claim of a 70 percent reduction
in the rate of patient-reported hypotensive symptoms while on the
Tablo[supreg] System and asserted that data also supports a reduction
in intradialytic hypotensive episodes among NxStage[supreg] patients,
referring to an article by Murashima et al.\95\
---------------------------------------------------------------------------
\95\ Murashima M, Kumar D, Doyle AM, Glickman JD. Comparison of
intradialytic blood pressure variability between conventional
thrice-weekly hemodialysis and short daily hemodialysis. Hemodial
Int. 2010 Jul;14(3):270-7. doi: 10.1111/j.1542-4758.2010.00438.x.
PMID: 20337744.
---------------------------------------------------------------------------
The commenter similarly questioned the applicant's claims regarding
sleep quality and related symptoms stating that the Tablo[supreg]
System IDE data did not compare the Tablo[supreg] System to NxStage,
relied on a small sample size, was of short duration, and was not
accurate because study results may have been affected by recall bias.
Regarding the recall bias concern, additional commenters also wrote in
with concurring comments. These commenters explained that participants'
experiences with NxStage[supreg] were not recorded at the time they
were receiving NxStage[supreg] treatments, but rather, were based on
recall at the time of the Tablo[supreg] System IDE study.
Regarding the applicant's claim that the Tablo[supreg] System users
spend less time in training compared to existing technologies, the
commenter questioned the applicant's reference to 14.5 days to complete
training on NxStage, stating that this timeframe includes training
about aspects of home dialysis beyond the functionality of the machine.
The commenter stated that only approximately 5 session-equivalents are
machine-focused during training with NxStage[supreg]. The commenter
also stated that because 13 patients in the Tablo[supreg] System IDE
study had previous home HD experience, the study participants would
have already been trained on the most difficult aspects of home
therapy, such as self-cannulation. Therefore, the commenter suggested
review of a larger number of patients who are truly new to home
therapy.
The commenter rejected the applicant's assertions that the
Tablo[supreg] System's features are unique and stated that the
applicant did not submit data demonstrating that the Tablo[supreg]
System is easier to use than other devices. The commenter stated its
belief that many aspects of the Tablo[supreg] System are more difficult
to use than NxStage[supreg] and highlighted key features that have
become available since publication of the NxStage[supreg] IDE study.
The commenter also challenged the applicant's description of the
Tablo[supreg] System's cartridge as being ``pre-strung'' compared to
existing cartridges and stated that NxStage[supreg] offers a cartridge
that requires 4 fewer blood tubing connections. The commenter also
stated that NxStage[supreg] systems are the only home HD systems
approved for self-treatment without a care partner, addressing partner
fatigue.
The commenter and several members of the public identified the
ability to travel as a quality of life issue. They stated that because
the Tablo[supreg] System weighs nearly 200 pounds, it is not portable,
while the NxStage[supreg] device is lighter and portable. Due to its
portability, the competitor commenter added that 70 percent of
NxStage[supreg] users reported traveling while using the machine.
Finally, this commenter stated that while certain patients may
prefer certain features of the Tablo[supreg] System, the presence of an
additional option for home dialysis machine does not in itself
represent a clinical improvement.
Response: We appreciate the input provided by the commenters. We
have taken this information into consideration in our determination of
whether the Tablo[supreg] System meets the eligibility criteria at
Sec. 413.236(b)(5) and Sec. 412.87(b)(1), and have responded in
further detail to comments discussing the significant clinical
improvement claims for the Tablo[supreg] System at the end of this
section of the final rule.
Comment: We received a comment from the applicant in support of the
TPNIES approval for the Tablo[supreg] System.
With respect to the claim that patients can achieve dialysis
adequacy in as little as three treatments per week and the concern we
expressed in the CY 2022 ESRD PPS proposed rule that the Tablo[supreg]
System IDE study did not test whether patients receive adequate
dialysis on a thrice-weekly schedule, the applicant clarified that the
intent was not to position three times per week home dialysis as
substantial clinical improvement over short daily or more frequent
dialysis. Instead, their claim is that more frequent dialysis, which
they believe is a requirement for NxStage, is significantly more
burdensome for patients with ESRD for whom thrice-weekly treatments may
be appropriate.
The applicant stated that the Tablo[supreg] System's ability to
achieve Kt/V targets of 1.2 on a thrice-weekly treatment schedule at
home represents substantial clinical improvement because they believe
it allows patients the benefits of home dialysis whether administered
three or four times per week, which had not been an option previously
because of the technical limitations of the NxStage[supreg] system.
Specifically, per the applicant, on a standard treatment duration,
three day per week schedule patients with weights above 79kg do not
have sufficient dialysate with NxStage[supreg] (maximum of 60L) to
achieve the CMS mandated target without increasing the amount of time
per treatment that the patient has to dialyze. The applicant further
stated that the Tablo[supreg] System can achieve levels of efficiency
nearly on par with in-center hemodialysis on conventional hardware. The
applicant also noted that patients treated with NxStage[supreg] would
exhaust its dialysate at 3 hours 20 minutes at an equivalent dialysate
flow rate of 300ml/min. In support of that claim, the applicant
referred to kinetic modeling, the clearance kinetics of the
NxStage[supreg] dialyzer, and the percentage of body water
96 97 in patients weighing 174 pounds or greater. The
applicant concluded that patients treated with NxStage[supreg] would
require greater than thrice-weekly treatments to achieve hemodialysis
adequacy with spKt/V of >1.2. The applicant stated that because the
Tablo[supreg] System is able to generate dialysate on demand at 300ml/
min for up to 12 hours without volume limitations, it allows patients
the flexibility to adequately dialyze at the frequency that is best for
them rather
[[Page 61902]]
than requiring them to perform more frequent treatments.
---------------------------------------------------------------------------
\96\ Leypoldt, J. K., Prichard, S., Chertow, G. M., & Alvarez,
L. (2019). Differential molecular modeling predictions of mid and
conventional dialysate flows. Blood purification, 47(4), 369-376.
Depner T, Beck G, Daugirdas J, Kusek J, Eknoyan G. Lessons from the
Hemodialysis (HEMO) Study: an improved measure of the actual
hemodialysis dose. Am J Kidney Dis. 1999 Jan;33(1):142-9.
\97\ Depner T, Beck G, Daugirdas J, Kusek J, Eknoyan G. Lessons
from the Hemodialysis (HEMO) Study: an improved measure of the
actual hemodialysis dose. Am J Kidney Dis. 1999 Jan;33(1):142-9.
---------------------------------------------------------------------------
The applicant stated that their evidence on achieving Kt/V of 1.2
on a conventional three times per week dialysis schedule came from an
observational study conducted on an in-center patient population using
the Tablo[supreg] System prior to its FDA marketing authorization for
home HD. The applicant referred to abstracts presented at the 2019
Annual Dialysis Conference as summarized in the CY 2022 ESRD PPS
proposed rule. The applicant emphasized that evidence from published
and unpublished sources may be sufficient in establishing substantial
clinical improvement.
In response to concerns regarding the sufficiency of the clinical
evidence presented, the applicant commented that because the patient
population in the Tablo[supreg] System IDE study, was more diverse and
reflective of the general dialysis population with respect to diabetes
and other comorbidities than the population in the NxStage[supreg] IDE
study, study results regarding Tablo[supreg] System can be better
applied to the Medicare population.
In their application, the applicant claimed that Tablo[supreg]
System patients can be expected to have fewer vascular access
interventions, and health care providers will have increased
flexibility in personalizing the frequency and duration of patient
treatments.98 99 The applicant emphasized in its comment
that Tablo[supreg] System users may experience reduced vascular access
infection related hospitalizations, relying on data from the
Tablo[supreg] System IDE study. The applicant stated that patients
prescribed 5-6 days weekly dialysis sessions with NxStage[supreg] who
were converted to 4 weekly dialysis sessions with the Tablo[supreg]
System, experienced no hospitalizations during the home arm of the
trial. The applicant commented that these data were not included in the
Tablo[supreg] System IDE publication because the sample size was modest
and relatively few patients required hospitalization. The applicant
also stated that 14 of the 35 patients enrolled in the NxStage[supreg]
IDE dropped out before completing the trial, making it difficult to
calculate an unbiased estimate of the hospitalization rate. The
applicant compared the Tablo[supreg] System IDE hospitalization rate to
two North American observational studies by Weinhandl et al.\100\ and
Suri et al.\101\ of patients receiving home HD (likely NxStage[supreg]
or K@Home). The applicant further stated that Suri et al. reported a
hospitalization rate of 930 per 1000 patient-years and Weinhandl et al.
noted a rate of 1663 per 1000 patient-years. The applicant stated that
results from these studies suggest that patients receiving treatment at
home with NxStage[supreg] 5-6 times per week had similar, not lower,
rates of hospitalization relative to matched patients receiving in-
center hemodialysis. The applicant further noted that the modest sample
size of the Tablo[supreg] System IDE precludes valid inference testing,
but that the hospitalization rate observed (426 per 1000 patient-years)
was roughly one-quarter that seen among a national cohort of patients
on home HD in the US, and less than one-half that seen among a Canadian
cohort, despite the high proportion of non-white patients and patients
with diabetes, characteristics typically associated with higher rates
of hospitalization.
---------------------------------------------------------------------------
\98\ FHN Trial Group. (2010). In-center hemodialysis six times
per week versus three times per week. New England Journal of
Medicine, 363(24), 2287-2300.
\99\ Kuo, T.H., Tseng, C.T., Lin, W.H., Chao, J.Y., Wang, W.M.,
Li, C.Y., & Wang, M.C. (2015). Association Between Vascular Access
Dysfunction and Subsequent Major Adverse Cardiovascular Events in
Patients on Hemodialysis: A Population-Based Nested Case-Control
Study. Medicine, 94(26).
\100\ Weinhandl, E. D., Gilbertson, D. T., & Collins, A. J.
(2016). Mortality, hospitalization, and technique failure in daily
home hemodialysis and matched peritoneal dialysis patients: a
matched cohort study. American Journal of Kidney Diseases, 67(1),
98-110.
\101\ Suri, R. S., Li, L., & Nesrallah, G. E. (2015). The risk
of hospitalization and modality failure with home dialysis. Kidney
international, 88(2), 360-368.
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With respect to the claim that the Tablo[supreg] System increases
adherence to dialysis treatment and retention to home therapy, the
applicant provided additional support. Specifically, the applicant
stated that in its real-world home population, to date, no patients
have chosen to return to in-center HD once going home with the
Tablo[supreg] System. The applicant submitted new data to further
establish first-year attrition comparisons. The applicant stated that
it contracted with a third-party research firm \102\ to conduct an
analysis of patients dialyzing at home using the Tablo[supreg] System,
matched to patients in the USRDS who completed home HD training between
the years 2016 through 2018. Per the applicant, home HD attrition was
defined as either death or conversion to in-facility HD and kidney
transplantation was excluded from attrition. The applicant further
stated that the cohort included 39 patients that initiated home HD with
the Tablo[supreg] System since the device's FDA marketing authorization
for home use in March of 2020.
---------------------------------------------------------------------------
\102\ Analysis conducted by the Chronic Disease Research Group
(CDRG), a division of the Hennepin Healthcare Research Institute.
---------------------------------------------------------------------------
The applicant further clarified that this patient population is
separate and distinct from the participants in the Tablo[supreg] System
IDE study. The applicant stated that there were 4 attrition events
among the 39 Tablo[supreg] System users and 3,602 attrition events
among the 9,827 home HD starts in the broader population of patients
receiving home HD. The applicant further noted that the cumulative
incidence of attrition at 1 year was 26.8 percent among Tablo[supreg]
System users and 42.5 percent among all home HD starts with the
unadjusted Cox regression hazard ratio of home HD attrition among
Tablo[supreg] System users versus home HD starts in years 2016 through
2018 at 0.38 (95% confidence interval, 0.14-1.02; p = 0.06), a more
than 60 percent reduction in attrition with the Tablo[supreg] System.
The applicant also acknowledged that the limited sample size reduces
power in demonstrating a statistically significant result, but asserted
that the preliminary data suggest that use of the Tablo[supreg] System
should reduce home HD attrition.
In the CY 2022 ESRD PPS proposed rule, CMS acknowledged the
applicant's claim regarding the benefit of greater flexibility for
patients in the way that they receive their dialysis treatments. The
applicant stated in their comment that the Tablo[supreg] System
represents substantial clinical improvement over NxStage[supreg] in
several ways: Allowing patients, in consultation with their clinicians,
to develop a treatment schedule tailored to their individual needs,
reducing the time spent on dialysis-related tasks including the
elimination of a 6-8 hour pre-treatment dialysate production, and
reducing supply storage requirements.
With respect to the claim that the Tablo[supreg] System improves
patient quality of life, the applicant stated in their comment that
Tablo[supreg] System IDE showed favorable effects on patient-reported
outcomes, including the EQ-5D survey instrument that has been widely
applied to many chronic disease populations, as well as a number of
surveys related to the process of home dialysis.
The applicant's comment included the results from an online survey
conducted by a third-party research firm \103\ and a network of
dialysis organizations and regional offices \104\ between July 29 and
August 9, 2021. Per
[[Page 61903]]
the applicant, 184 nephrologists and 202 patients were surveyed
regarding a list of potential benefits and system features of a blinded
home HD system concept reflecting the features of the Tablo[supreg]
System. The applicant stated that 77 percent of nephrologists rated the
Tablo[supreg] System's features as a substantial clinical improvement
in home HD care and 98 percent indicated that the Tablo[supreg]
System's benefits would make them more likely to recommend home HD to
their patients. The applicant further stated that 72 percent of
patients receiving in-center HD or PD rated the Tablo[supreg] System's
features as a significant improvement in home HD care and 77 percent of
those patients stated they would be more likely to try home HD. The
applicant stated that of the current home HD population dialyzing on
the incumbent device, 84 percent rated the Tablo[supreg] System's
features as a significant improvement in home HD care.
---------------------------------------------------------------------------
\103\ Health Advances, US Home Hemodialysis Nephrologist and
Patient Perspectives Presentation, August 13, 2021.
\104\ National Kidney Foundation.
---------------------------------------------------------------------------
The applicant's comment acknowledged that NxStage[supreg] would be
an available option to patients who prefer to travel with a home
dialysis device but stated that the majority of patients ranked the
effectiveness of treatment above the ability to travel with their
device.
With respect to CMS's recall bias concern that participants'
experiences with NxStage[supreg] were not recorded at the time they
were receiving NxStage[supreg] treatments, but rather, were based on
recall at the time of the Tablo[supreg] System IDE study, the applicant
clarified that 13 of the 29 Tablo[supreg] System IDE study participants
who completed the trial had been dialyzing at home with NxStage[supreg]
in advance of the Tablo[supreg] System IDE study and that baseline
surveys were taken while patients were actively treating with
NxStage[supreg]. The applicant commented that survey questions were
sourced from validated sleep questionnaires and did not ask patients
for a comparison to a prior time point, but focused on a rating of
sleep during the prior week.
The applicant commented that to further assess the prevalence of
sleep related symptoms in home HD patients, a third-party research firm
conducted a survey of current non-Tablo[supreg] System HD patients. The
applicant stated that of home HD respondents, 64 percent reported very
poor to poor sleep quality and all respondents stating that improved
sleep would represent substantial clinical improvement.\105\ The
applicant stated that collectively, its results confirm that achieving
satisfactory sleep remains a major challenge for patients on dialysis
and that using the Tablo[supreg] System has the potential to improve
sleep quality, which may also enhance physical, cognitive, and sexual
function, and expand functional capacity.
---------------------------------------------------------------------------
\105\ Health Advances, US Home Hemodialysis Nephrologist and
Patient Perspectives Presentation, August 13, 2021.
---------------------------------------------------------------------------
The applicant's comment emphasized the safety features and ease-of-
use of the Tablo[supreg] System. The applicant stated that the
Tablo[supreg] System offers patients a differentiated level of safety
in having met higher, more updated safety standards of performance,
such as fluid removal, air detection, temperature, dialysate flow rate
and other parameters than the previously approved NxStage[supreg]
device. The applicant also stated that the remote monitoring and remote
technical support features are only available with the Tablo[supreg]
System and reduce patient apprehension to perform treatments at home.
The applicant's comment again asserted that, overall, the totality of
the evidence demonstrates that the Tablo[supreg] System offers
substantial clinical improvement in home HD treatment.
Response: We thank the applicant for their comment and have taken
the additional information provided into consideration in our
determination of whether the Tablo[supreg] System meets the eligibility
criteria at Sec. 413.236(b)(5) and Sec. 412.87(b)(1). We have
responded in further detail to comments discussing the significant
clinical improvement claims for the Tablo[supreg] System at the end of
this section (II.C.5.c) of the final rule.
Comment: We received many comments from clinicians, patients, and
caregivers supporting the Tablo[supreg] System's TPNIES application.
For example, many commenters stated that using the Tablo[supreg] System
is convenient and allows for the flexibility to personalize treatment
for a diversity of patient needs. Commenters stated that patients are
allowed to create their own schedules, which enables them to continue
working and enjoying life's activities. Patient commenters stated that
they have become more active and engaged participants in their own
care. Commenters appreciated the convenience and comfort of being able
to dialyze at home instead of in-center, stating that doing so
alleviates stress, reduces exposure to COVID-19 and reduces the burden
of arranging for and traveling to in-center treatments.
Patient and caregiver commenters expressed appreciation for the
Tablo[supreg] System's on-demand dialysate for several reasons. First,
commenters stated that patients have more dialysis-free time by not
needing to prepare solution or handle heavy bags of dialysate. Second,
commenters stated that there are fewer supplies to store for the
Tablo[supreg] System as compared to the NxStage[supreg] System for
which it was necessary to store up to 20 boxes of dialysate and
supplies. Third, commenters stated that dialysate delivery may be
challenged in regions with extreme climates and could compromise
treatment. Commenters also stated that there is less wasted dialysate
with use of the Tablo[supreg] System.
Patient commenters identified several clinical improvements that
they attribute to treatment with the Tablo[supreg] System including
reduced cramping and fatigue after dialysis treatment, reduced need for
blood pressure medication, improved mood, and less frequent use and
wear on the vascular access site with fewer weekly treatments.
Commenters also stated that that features and conveniences of the
Tablo[supreg] System result in less burn out \106\ of patients and
caregivers, better adherence, retention and overall quality of life.
---------------------------------------------------------------------------
\106\ As discussed in the CY 2021 ESRD PPS final rule (85 FR
71462), a significant challenge to increasing the use of home
dialysis includes burn out (or technique failure) and return to in-
center HD. According to one recent observational study,
approximately 25 percent of patients who initiate home HD return to
in-center HD within the first year (Seshasai RK, Mitra N, Chaknos
CM, Li J, Wirtalla C, Negoianu D, Glickman JD, Dember LM. Factors
Associated With Discontinuation of Home Hemodialysis. Am J Kidney
Dis. 2016 Apr;67(4):629-37.)
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Many commenters including patients, caregivers and clinicians
commented on the Tablo[supreg] System's features and ease-of-use.
Commenters stated that the complexity of a dialysis machine and lengthy
training can be intimidating and act as a deterrent in the adoption of
home dialysis. Commenters stated that some patients and caregivers
cannot afford extended absences from work, childcare or other
responsibilities to complete dialysis training and that training with
the Tablo[supreg] System ranges from 10 days to 2 weeks compared to
training with NxStage[supreg] which averages 4-6 weeks. Several
commenters stated that patients with prior home dialysis experience can
begin home treatments using the Tablo[supreg] System after just 3-4
training days. One commenter stated that a comparison of training for
the Tablo[supreg] System versus other devices in the market does not
exist.
Commenters stated that patients may also fear not being able to
remember what to do in an urgent situation and highlighted the
Tablo[supreg] System's safety features that prevent patient harm,
including step-by-step instructions with less memorization, and fewer
treatment steps, and 24/7 technical support.
[[Page 61904]]
Commenters stated that remote treatment monitoring in real time, allows
clinicians to intervene as needed with treatment modifications.
Commenters stated that the Tablo[supreg] System's instructions can be
set in other languages. Commenters also expressed appreciation for the
Tablo[supreg] System's built-in warmer that helps to prevent
hypothermia during treatment, built-in blood pressure monitoring, flush
feature, closed loop cartridge to minimize risk of infection, automatic
record keeping, and the quicker set up and take down times. Commenters
stated that the Tablo[supreg] System looks less like an intrusive
medical device and the built-in wheels make it easy to move it from
room to room.
One commenter stated that patients previously not deemed suitable
for home HD, due to large body size, work schedules, etc. may now
become candidates with the use of the Tablo[supreg] System. Another
commenter stated that patients lacking social support and financial
resources may not be good candidates for home dialysis.
Response: We appreciate the input provided by these commenters. We
have taken this information into consideration in our determination of
whether the Tablo[supreg] System meets the eligibility criteria at
Sec. 413.236(b)(5) and Sec. 412.87(b)(1). We have responded in
further detail to comments discussing the significant clinical
improvement claims for the Tablo[supreg] System at the end of this
section (II.C.5.c) of the final rule.
Comment: We received several comments from health care providers
and patients regarding the Tablo[supreg] System and less frequent
dialysis treatments. A physician commenter stated that the question of
whether less frequent dialysis is clinically preferable to shorter,
more frequent [dialysis] sessions does not appear to be definitively
decided in clinical research for all patients. The commenter stated
that while patients derive significant benefit from more frequent
dialysis, having the ability to achieve at least adequate dialysis at
three days per week is a significant advancement compared with what has
been offered. Commenters stated that the treating clinician remains in
the best position to prescribe the appropriate frequency of dialysis
for their patients but that it is possible for researchers to
accurately assess improvements in clinical outcomes related to
frequency of dialysis treatments. A commenter, who is a health care
provider, shared their experience with the Tablo[supreg] System in a
dialysis unit, stating that their unit tested the Tablo[supreg] System
and found that on the whole, the patients could reach dialysis adequacy
on a traditional thrice-weekly frequency. While this commenter referred
to an abstract documenting these results, it was not provided.
Response: We appreciate the input provided by these commenters. We
have taken this information into consideration in our determination of
whether the Tablo[supreg] System meets the eligibility criteria at
Sec. 413.236(b)(5) and Sec. 412.87(b)(1). We have responded in
further detail to comments discussing the significant clinical
improvement claims for the Tablo[supreg] System at the end of this
section (II.C.5.c) of the final rule.
Comment: We received several comments from the public, including
health care providers and patients, regarding how to demonstrate
substantial clinical improvement in connection with a home hemodialysis
machine such as the Tablo[supreg] System. One commenter stated that
clinical trials, abstract data and expert opinion is sufficient to
support substantial clinical improvement and that this type of evidence
is often the basis of clinical guidelines from the National Kidney
Foundation (NKF) Kidney Disease Outcome Quality Initiative. The
commenter stated that new companies are not equipped to conduct in-
depth studies until they have significant numbers of patients on their
device or therapy which creates a barrier to recruiting study
participants and thus, limiting investment in the new technology.
Another commenter stated that the ESRD sector does not easily lend
itself to robust clinical trials, and this fact should be considered
when determining whether an applicant for TPNIES has demonstrated
substantial clinical improvement. Commenters referred to the CMS TPNIES
application template, which indicates that published, unpublished, and
clinical expertise are all acceptable forms of supporting evidence and
that placing a heavy emphasize on published long-term studies for
purposes of evaluating substantial clinical improvement limits the
ability of new companies to enter the market and deprives patients of
potentially lifesaving technologies. A non-profit dialysis association
stated that CMS should consider the extent to which the technology has
demonstrated improved quality of life in determining whether the
technology represents substantial clinical improvement.
Many commenters stated that patients should be given a choice in
deciding which home hemodialysis machine is best for them, and that
providing patients with an additional choice is evidence of substantial
clinical improvement. A physician commenter indicated that it is not
clear why patients prefer one machine over another or feel better with
one prescription over another, but a choice based on patient preference
can improve patient retention to a particular therapy, one of the ways
to demonstrate substantial clinical improvement. This commenter stated
that evidence that a home dialysis machine improves retention should be
sufficient evidence to approve the TPNIES for that home dialysis
machine.
Response: We appreciate the commenters' input regarding whether the
Tablo[supreg] System meets the innovation criterion at Sec.
413.236(b)(5) and substantial clinical improvement criteria at Sec.
412.87(b)(1). After carefully reviewing the application, the
information submitted by the applicant addressing our concerns raised
in the CY 2022 ESRD PPS proposed rule, as well as the many comments
submitted by the public, we agree with the applicant and several
members of the dialysis community that the Tablo[supreg] System
represents an advance that substantially improves, relative to renal
dialysis services previously available, the treatment of Medicare
beneficiaries. We find that the data submitted demonstrate greater
medication adherence or compliance of home HD among users of the
Tablo[supreg] System that is not as evident for users of existing home
HD technologies, as specified under Sec. 412.87(b)(1)(C)(7). We also
believe that the Tablo[supreg] System may provide added flexibility
around the frequency and duration of home HD that could benefit some
patients, specifically, patients who may prefer fewer, slightly longer
treatments but who would otherwise be limited to more frequent home HD
treatments. We believe additional flexibilities around home HD
treatments may represent an improvement in one or more activities of
daily living and an improved quality of life for Medicare
beneficiaries, as specified under Sec. 412.87(b)(1)(C)(4) and Sec.
412.87(b)(1)(C)(5), respectively. We also recognize that patient
preference and choice is especially important for patients with ESRD,
who undergo demanding, often grueling, dialysis therapy, and we believe
that patients who prefer their method and frequency of dialysis are
more likely to adhere to the therapy, and thus increase adherence rates
overall.
We acknowledge the concerns raised by commenters regarding the
substantial clinical improvement claims in the Tablo[supreg] System
application. As we had previously noted in the CY 2022 ESRD PPS
proposed rule, we had some of the same concerns as commenters regarding
[[Page 61905]]
the evidence submitted to support the claims of significant clinical
improvement. However, at this time, we feel that our concerns have been
sufficiently addressed. For example, with respect to the applicant's
claim that the Tablo[supreg] System increases adherence to dialysis
treatment and retention to home therapy, although the adherence and
retention data provided in the initial application had limitations,
additional information was submitted by the applicant to support this
claim in its comment on the CY 2022 ESRD PPS proposed rule. This data
showed lower attrition rates at 1 year between patients using the
Tablo[supreg] System for home HD, separate from the group of patients
in the Tablo[supreg] System IDE, matched with patients who had
completed home HD patients, using data from the USRDS. With respect to
the applicant's claim that the Tablo[supreg] System improves patient
quality of life, we note that the applicant addressed our concerns
about the potential for recall bias in their claim of improved sleep
quality and related symptoms in their comment, explaining that baseline
surveys were taken while patients were actively treating with
NxStage[supreg]. Also, while some commenters opposed the applicant's
use of unpublished data to support its claim of improved
hospitalization, we note that under Sec. 413.236(b)(5) and
412.87(b)(1)(iii), CMS may consider unpublished data in making a
determination of substantial clinical improvement as we recognize in
some situations, published data may not be available. Overall, we
believe the applicant was able to address our concerns about its
substantial clinical improvement claims from the discussion in the CY
2022 ESRD proposed rule.
We also note that, under our TPNIES policy and Sec.
412.87(b)(1)(i), CMS is required to consider the totality of the
circumstances when making a determination that a new renal dialysis
equipment or supply represents an advance that substantially improves,
relative to renal dialysis services previously available, the diagnosis
or treatment of Medicare beneficiaries. We believe the circumstances we
may consider in our review of the TPNIES applications, specifically
within the context of the ESRD PPS, include the state of the ESRD
landscape and the particular challenges and vulnerabilities of patients
with ESRD. While we recognize that published studies and randomized
controlled trials are often the gold standard in demonstrating
superiority of one product over another, our review is not limited to
evidence from large randomized controlled trials; we also consider a
range of evidence from published or unpublished information sources,
including other appropriate information sources not otherwise listed
under Sec. 412.87(b)(1)(iii). As codified under Sec.
412.87(b)(1)(iii), evidence from published or unpublished information
sources may be sufficient to establish that a new technology represents
a substantial clinical improvement.
Additional information we considered in our review of the
Tablo[supreg] System was the new data provided by the applicant
surveying over 180 nephrologists and over 200 patients undergoing
dialysis treatment HD, along with substantial supportive comments from
patients, caregivers, and health care providers, about the benefits of
the Tablo[supreg] System in providing an improved quality of life, an
improvement in one or more activities of daily living, and a decreased
rate of at least one subsequent therapeutic intervention, as specified
under Sec. Sec. 12.87(b)(1)(C)(6), 412.87(b)(1)(C)(5),
412.87(b)(1)(C)(2), respectively.
We also note that, at this time, patients with ESRD are facing new,
additional risks when receiving dialysis treatment due to the COVID-19
pandemic. As some of the commenters noted, ESRD patients are among the
most vulnerable in the Medicare population and are at an increased risk
for COVID-19 associated morbidity and mortality.107 108 As
we discussed in the CY 2021 ESRD PPS final rule, Medicare's ESRD
population aligns with the profile of patients who are more susceptible
to COVID-19. As we stated in that rule, we believe it is important to
reduce the risk of infection among beneficiaries with ESRD, and this
can be done through isolating patients from in-center exposure by
encouraging home HD (85 FR 71416). We also believe that providing
patients with an additional option for home HD is especially important
given that the adoption of home HD has been limited, with approximately
only 1% of ESRD patients utilizing this modality.\109\ Therefore, we
are interested in supporting the use of technologies that expand
patient options for dialyzing safely at home at this time.
---------------------------------------------------------------------------
\107\ Ziemba R, Campbell KN, Tang T, et al. Excess Death
Estimates in Patients with End-Stage Renal Disease--United States,
February-August 2020. MMWR Morb Mortal Wkly Rep 2021;70:825-829. DOI
http://dx.doi.org/10.15585/mmwr.mm7022e2.
\108\ https://www.cdc.gov/coronavirus/2019-ncov/hcp/dialysis/home-dialysis.html.
\109\ Mailloux LU, Blagg CR. Berns JS (ed.) Home Hemodialysis.
Uptodate. Nov 18, 2016.
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For all of these reasons, we conclude that the Tablo[supreg] System
meets the TPNIES innovation criteria under Sec. 413.236(b)(5) and
Sec. 412.87(b)(1).
(6) Capital Related Assets Criterion (Sec. 413.236(b)(6))
Regarding the final TPNIES eligibility criterion under Sec.
413.236(b)(6), whether the item is a ``capital-related asset'' that is
a ``home dialysis machine,'' these terms are defined in Sec.
413.236(a)(2). The applicant identified the Tablo[supreg] System as an
asset that an ESRD facility has an economic interest in through
ownership, is subject to depreciation, and is an HD machine that
received FDA marketing authorization for home use. We received no
public comments on this criterion. We agree that the Tablo[supreg]
System is a capital-related asset and home dialysis machine and
therefore meets this criterion.
The remaining comments and our responses regarding the
Tablo[supreg] System and its eligibility for the TPNIES are set forth
below.
Comment: We received a comment that 70% of the patient population
in the Tablo[supreg] System IDE study were non-white, suggesting
Tablo[supreg] System's ability to create greater home adoption and
retention in ways that are aligned with the proposed incentive for
closing gaps in health equity access to home HD.
Response: We thank the commenter for their input. While health
equity is not a specific TPNIES eligibility criteria under Sec.
413.236(b), we strongly support health equity and believe that the
approval of the Tablo[supreg] System under the criterion of Sec.
413.236(b) will encourage uptake of home HD for vulnerable patients
with ESRD.
Comment: We received several comments pertaining to the
relationship between the cost of the Tablo[supreg] System and its
connection to beneficiary access. Several commenters stated that the
initial cost of the Tablo[supreg] System is 2 to 3 times that of older
technologies, and that combined with potentially fewer treatments over
which to amortize the cost, it would be difficult for ESRD facilities
to incorporate the Tablo[supreg] System into their businesses without a
payment adjustment under the ESRD PPS. These commenters expressed
support for CMS approving the TPNIES for the Tablo[supreg] System.
The applicant stated that after the initial capital investment, the
per treatment costs of using the Tablo[supreg] System are considerably
less than that of the NxStage[supreg] System. Another commenter stated
that the Tablo[supreg] System is more affordable than other home
dialysis machines and is cost
[[Page 61906]]
effective. Commenters stated that a TPNIES approval for the
Tablo[supreg] System would help to offset the Tablo[supreg] System's
acquisition costs, particularly for small and mid-size dialysis
organizations and independent providers and facilitate economies of
scale, allowing ESRD facilities to lower the cost of home HD care in
the future.
Commenters also asserted that a TPNIES approval would increase home
dialysis utilization and retention of patients on home dialysis, and
improve clinical and patient-reported outcomes, overall. For example,
several commenters stated that use of the Tablo[supreg] System may help
to push the national home hemodialysis prevalence above its stagnant
level of 2 percent and a TPNIES approval would further support the
goals of the ETC Model.
Response: We appreciate the commenters' input. We note that cost is
not a consideration for TPNIES eligibility under Sec. 413.236(b), and
therefore is not relevant to our review of the Tablo[supreg] System's
application. However, we believe that approval of the Tablo[supreg]
System supports the goals of the ETC model by expanding beneficiary
access to and retention of home HD.
Comment: The Tablo[supreg] System applicant commented on the CMS
spending estimate of Medicare payment for additional home HD sessions,
noting differences between its analysis and that of CMS but agreeing
with CMS' estimates on spending for the fifth treatment. Several
commenters stated that while existing guidance \110\ allows for
treatments more than three times per week when they are reasonable and
necessary, coverage decisions are unrelated to the TPNIES eligibility
determination. A commenter stated that the applicant provided no
evidence regarding dialysis frequency for the population of patients
that meet Medicare's clinical coverage criteria for additional
treatments.
---------------------------------------------------------------------------
\110\ Medicare Coverage Database. Retrieved May 24, 2021 from:
https://www.cms.gov/medicarecoverage-database/details/lcd-details.aspx?LCDId=35014&ver=39&NCDId=79&ncdver=1&SearchType=Advanced&CoverageSelection=Both&NCSelection=NCA%7CCAL%7CNCD%7CMEDCAC%7CTA%7CMCD&ArticleType=Ed%7CKey%7CSAD%7CFAQ&PolicyType=Final&s=-%7C5%7C6%7C66%7C67%7C9%7C38%7C63%7C41%7C64%7C65%7C44&KeyWord=transplant&KeyWordLookUp=Doc&KeyWordSearchType=Exact&kq=true&bc=IAAAADgAAAAA&
.
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Response: We thank the commenters for their input and note that our
CMS spending estimate of Medicare payment for additional home HD
sessions that was included in the CY 2022 ESRD PPS proposed rule (86 FR
36339) was not part of our analysis of the TPNIES eligibility criteria
in Sec. 413.236(b). In addition, while Medicare clinical coverage
criteria are beyond the scope of this rulemaking, we are not suggesting
that the way in which ESRD facilities reflect home HD treatments on
their claims would change due to our decision on the Tablo[supreg]
System application.
Comment: We received several comments from health care
professionals with experience in using the Tablo[supreg] System in a
clinical setting, rather than a home setting. One commenter stated that
the Tablo[supreg] System is a benefit for ESRD facilities with staffing
shortages because less time will need to be spent with each patient.
Several commenters shared their favorable experiences in using the
Tablo[supreg] System in the hospital inpatient and intensive care unit
settings and in treating COVID-19 patients. One commenter stated that
15 AKI inpatients with a mean age of 65 years were provided multiple
Tablo[supreg] System treatments 3-6 times per week. The commenter
further explained that the best urea reduction ratio achieved in the
first 1-4 treatments, if available, was 41%; most treatments were
successful and were slowed for hypotension or tachycardia; and some
were aborted because of water pressure alarms signaling the need for
filter replacement or clotted lines related to hypercoagulability among
COVID-19 patients. The commenter further stated that most treatments
were limited to 3-4 hours but up to 8 hours. Some commenters stated
that patients treated with the Tablo[supreg] System in the hospital or
ESRD facility setting gain familiarity and comfort with the device
making it an easier transition to using the system at home.
Response: We thank the commenters for their input. Currently, the
only capital-related assets not excluded from eligibility for the
TPNIES under Sec. 413.236(b)(6) are home dialysis machines used in the
home for a single patient, as defined in Sec. 413.236(a)(2). While
these commenters' experiences with the Tablo[supreg] System do not
involve its use in the home setting, we appreciate the additional input
regarding the benefits of the Tablo[supreg] System.
After a consideration of all the public comments received, we have
determined that the evidence and public comments submitted are
sufficient to demonstrate that the Tablo[supreg] System meets all of
the eligibility criteria to qualify for the TPNIES for CY 2022. As a
result, the Tablo[supreg] System will be paid for using a TPNIES per
Sec. 413.236(d).
III. Calendar Year (CY) 2022 Payment for Renal Dialysis Services
Furnished to Individuals With Acute Kidney Injury (AKI)
A. Background
The Trade Preferences Extension Act of 2015 (TPEA) (Pub. L. 114-27)
was enacted on June 29, 2015, and amended the Act to provide coverage
and payment for dialysis furnished by an ESRD facility to an individual
with acute kidney injury (AKI). Specifically, section 808(a) of the
TPEA amended section 1861(s)(2)(F) of the Act to provide coverage for
renal dialysis services furnished on or after January 1, 2017, by a
renal dialysis facility or a provider of services paid under section
1881(b)(14) of the Act to an individual with AKI. Section 808(b) of the
TPEA amended section 1834 of the Act by adding a subsection (r) to
provide payment, beginning January 1, 2017, for renal dialysis services
furnished by renal dialysis facilities or providers of services paid
under section 1881(b)(14) of the Act to individuals with AKI at the
ESRD PPS base rate, as adjusted by any applicable geographic adjustment
applied under section 1881(b)(14)(D)(iv)(II) of the Act and adjusted
(on a budget neutral basis for payments under section 1834(r) of the
Act) by any other adjustment factor under section 1881(b)(14)(D) of the
Act that the Secretary elects.
In the CY 2017 ESRD PPS final rule, we finalized several coverage
and payment policies to implement subsection (r) of section 1834 of the
Act and the amendments to section 1881(s)(2)(F) of the Act, including
the payment rate for AKI dialysis (81 FR 77866 through 77872, and
77965). We interpret section 1834(r)(1) of the Act as requiring the
amount of payment for AKI dialysis services to be the base rate for
renal dialysis services determined for a year under the ESRD PPS base
rate as set forth in Sec. 413.220, updated by the ESRD bundled market
basket percentage increase factor minus a productivity adjustment as
set forth in Sec. 413.196(d)(1), adjusted for wages as set forth in
Sec. 413.231, and adjusted by any other amounts deemed appropriate by
the Secretary under Sec. 413.373. We codified this policy in Sec.
413.372 (81 FR 77965).
B. Summary of the Proposed Provisions, Public Comments, and Responses
to Comments on the CY 2022 Payment for Renal Dialysis Services
Furnished to Individuals With AKI
The proposed rule, titled ``Medicare Program; End-Stage Renal
Disease Prospective Payment System, Payment
[[Page 61907]]
for Renal Dialysis Services Furnished to Individuals With Acute Kidney
Injury, End-Stage Renal Disease Quality Incentive Program, and End-
Stage Renal Disease Treatment Choices Model'' (86 FR 36322 through
36437), referred to as the ``CY 2022 ESRD PPS proposed rule,'' was
published in the Federal Register on July 9, 2021, with a comment
period that ended on August 31, 2021. In that proposed rule, we
proposed to update the AKI dialysis payment rate for CY 2022. We
received 6 public comments on our proposal from large dialysis
organizations, a non-profit dialysis association, a professional
association, a provider advocacy organization, and a healthcare group.
In this final rule, we provide a summary of each proposed
provision, a summary of the public comments received and our responses
to them, and the policies we are finalizing for CY 2022 payment for
renal dialysis services furnished to individuals with AKI.
C. Annual Payment Rate Update for CY 2022
The payment rate for AKI dialysis is the ESRD PPS base rate
determined for a year under section 1881(b)(14) of the Act, which is
the finalized ESRD PPS base rate, including the applicable annual
productivity-adjusted market basket payment update, geographic wage
adjustments, and any other discretionary adjustments, for such year. We
note that ESRD facilities could bill Medicare for non-renal dialysis
items and services and receive separate payment in addition to the
payment rate for AKI dialysis.
As discussed in section II.B.1.d of this final rule, the CY 2022
ESRD PPS base rate is $257.90, which reflects the application of the CY
2022 wage index budget-neutrality adjustment factor of 0.99985 and the
CY 2022 ESRDB market basket increase of 2.4 percent reduced by the
productivity adjustment of 0.5 percentage point, that is, 1.9 percent.
Accordingly, we are finalizing a CY 2022 per treatment payment rate of
$257.90 for renal dialysis services furnished by ESRD facilities to
individuals with AKI. This payment rate is further adjusted by the wage
index, as discussed in the next section of this final rule.
2. Geographic Adjustment Factor
Under section 1834(r)(1) of the Act and Sec. 413.372, the amount
of payment for AKI dialysis services is the base rate for renal
dialysis services determined for a year under section 1881(b)(14) of
the Act (updated by the ESRD bundled market basket and reduced by the
productivity adjustment), as adjusted by any applicable geographic
adjustment factor applied under section 1881(b)(14)(D)(iv)(II) of the
Act. Accordingly, we apply the same wage index under Sec. 413.231 that
is used under the ESRD PPS and discussed in section II.B.1.b of this
final rule. The AKI dialysis payment rate is adjusted by the wage index
for a particular ESRD facility in the same way that the ESRD PPS base
rate is adjusted by the wage index for that facility (81 FR 77868).
Specifically, we apply the wage index to the labor-related share of the
ESRD PPS base rate that we utilize for AKI dialysis to compute the wage
adjusted per-treatment AKI dialysis payment rate. As stated previously,
we are finalizing a CY 2022 AKI dialysis payment rate of $257.90,
adjusted by the ESRD facility's wage index.
The comments and our responses to the comments on our AKI dialysis
payment proposal are set forth below.
Comment: Several commenters, including a large dialysis
organization and a professional association, commented in support of
the proposed update to the AKI dialysis payment rate for CY 2022. They
also expressed support for using the same methodology as in previous
years for the AKI update. A large dialysis organization expressed
specific appreciation for the detailed explanation of the CMS process
and methodology to develop the AKI payment amount that has been
included in prior rules. This organization noted that CMS has
recognized that treatment for AKI differs from treatment for ESRD. The
organization stated that although the services provided to AKI patients
may be the same, their frequency may exceed those typically required by
patients with ESRD. The organization also noted that in the CY 2017
ESRD PPS final rule, CMS indicated that it planned to make available
public use files on utilization of services by AKI patients once the
agency had compiled one full year of claims. The organization stated
that CMS subsequently reported that the agency would continue to
monitor utilization trends of items and services furnished to
individuals with AKI. Along with other commenters, the large dialysis
organization supports the data collection effort and CMS's commitment
to ensure a data-driven approach to developing methodological changes
to the AKI's rate development. The commenters urged CMS to share its
monitoring plans to allow the public to better understand the specific
data elements that CMS is collecting and analyzing.
Response: We appreciate the comments in support of the AKI payment
rate update. As the commenter stated, we have been monitoring the
trends of AKI beneficiaries in ESRD facilities and acute inpatient
hemodialysis. This has included quantification of drugs, laboratory
tests and other services provided on acute inpatient dialysis claims.
We also examine other diagnoses recorded before an acute inpatient
dialysis claim.
During the TEP held in December 2020, we reviewed dialysis-related
costs, resource utilization and characteristics of the AKI-D
(outpatient dialysis for patients with AKI) population beginning
January 1, 2017, when their outpatient dialysis treatment first became
eligible under the ESRD PPS claims. That report can be found at the
following link: https://www.cms.gov/files/document/end-stage-renal-disease-prospective-payment-system-technical-expert-panel-summary-report-april-2021.pdf. As we continue to analyze costs, utilization and
patient characteristics, we will also examine data as it relates to an
additional site of service for AKI patients. We will also incorporate
additional data monitoring for COVID-19 patients who have experienced
AKI. The results of the data analysis will be shared in the future in
public use files on the ESRD PPS website.
Final Rule Action: We are finalizing the AKI payment rate as
proposed, that is, the AKI payment rate is based on the finalized ESRD
PPS base rate. Specifically, the final CY 2022 ESRD PPS base rate is
$257.90. Accordingly, we are finalizing a CY 2022 payment rate of
$257.90 for renal dialysis services furnished by ESRD facilities to
individuals with AKI.
IV. End-Stage Renal Disease Quality Incentive Program (ESRD QIP)
A. Background
For a detailed discussion of the End-Stage Renal Disease Quality
Incentive Program's (ESRD QIP's) background and history, including a
description of the Program's authorizing statute and the policies that
we have adopted in previous final rules, we refer readers to the
following final rules:
CY 2011 ESRD PPS final rule (75 FR 49030),
CY 2012 ESRD PPS final rule (76 FR 628),
CY 2012 ESRD PPS final rule (76 FR 70228),
CY 2013 ESRD PPS final rule (77 FR 67450),
CY 2014 ESRD PPS final rule (78 FR 72156),
CY 2015 ESRD PPS final rule (79 FR 66120),
CY 2016 ESRD PPS final rule (80 FR 68968),
[[Page 61908]]
CY 2017 ESRD PPS final rule (81 FR 77834),
CY 2018 ESRD PPS final rule (82 FR 50738),
CY 2019 ESRD PPS final rule (83 FR 56922),
CY 2020 ESRD PPS final rule (84 FR 60648), and
CY 2021 ESRD PPS final rule (85 FR 71398).
We have also codified many of our policies for the ESRD QIP at 42
CFR 413.177 and 413.178.
B. Extraordinary Circumstances Exception (ECE) Previously Granted for
the ESRD QIP Including Notification of ECE Due to ESRD Quality
Reporting System Issues
1. Extraordinary Circumstance Exception (ECE) Previously Granted in
Response to the COVID-19 PHE
On March 22, 2020, in response to the COVID-19 PHE, we announced
relief for clinicians, providers, hospitals, and facilities
participating in Medicare quality reporting and value-based purchasing
programs.\111\ On March 27, 2020, we published a supplemental guidance
memorandum that described the scope and duration of the ECEs we were
granting under each Medicare quality reporting and value-based
purchasing (VBP) program.\112\ Each of these ECEs relieved these
providers and facilities of their obligation to report data for Q4 CY
2019, Q1 and Q2 CY 2020, but we stated that we would score such data if
optionally reported.
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\111\ CMS, Press Release, CMS Announces Relief for Clinicians,
Providers, Hospitals and Facilities Participating in Quality
Reporting Programs in Response to COVID-19 (Mar. 22, 2020), https://www.cms.gov/newsroom/press-releases/cms-announces-relief-clinicians-providers-hospitals-and-facilities-participating-quality-reporting.
\112\ CMS, 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 (Mar. 27, 2020), https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
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The September 2020 IFC updated the ECE we granted in response to
the COVID-19 PHE for the ESRD QIP and several other quality reporting
programs (85 FR 54827 through 54838).
In the IFC, we updated the ECE policy for the ESRD QIP (85 FR 54828
through 54830). First, we updated our regulations at Sec.
413.178(d)(7) to state that a facility has opted out of the ECE for
COVID-19 with respect to the reporting of Q4 CY 2019 NHSN data if the
facility actually reported the data by the March 31, 2020 deadline but
did not notify CMS that it would do so. Additionally, we finalized that
facilities would not have the option to opt-out of the ECE we granted
with respect to Q1 and Q2 2020 ESRD QIP data. We stated that measures
calculated using excepted data could affect the national comparability
of these data due to the geographic differences of COVID-19 incidence
rates and hospitalizations along with different impacts resulting from
different State and local law and policy changes implemented in
response to COVID-19, and therefore may not provide a nationally
comparable assessment of performance in keeping with the program goal
of national comparison.
In the September 2020 IFC, we welcomed public comments on our
policy to update our regulations at Sec. 413.178(d)(7) to consider a
facility as having opted out of the ECE with respect to NHSN data
reported for Q4 2019 if the facility actually reported the data by the
submission deadline, without notifying CMS, and on the exception we
finalized to the ECE opt out policy for the ESRD QIP to exclude any
ESRD QIP data that facilities optionally reported during Q1 and Q2 2020
from our calculation of PY 2022 TPSs and from the baseline for PY 2023.
The comments we received on these policies and our responses are set
forth below.
Comment: Several commenters supported CMS' updated application of
the ECE granted in response to the PHE due to COVID-19. A few
commenters also agreed with CMS' concerns regarding the national
comparability of data from Q1 and Q2 of CY 2020 and noted that the
integrity and validity of any measurement calculations associated with
these data could be compromised.
Response: We thank commenters for their support.
Comment: A few commenters expressed strong concern that the data
collected under the ESRD QIP will not adequately reflect the quality of
care provided due to the impact of COVID-19 and the shortened data
collection period. A few commenters noted that the data collected under
the ESRD QIP for 2020 will be limited due to the COVID-19 PHE and the
nationwide ECE excluding Q1 and Q2 data from consideration, and will
undermine the reliability of measure results for scoring purposes. A
few commenters recommended that CMS suspend penalties and payment
adjustments for the 2020 performance year, expressing concern that the
data collected under the ESRD QIP will not adequately reflect the
quality of care provided due to the impact of the COVID-19 PHE and the
nationwide ECE.
Response: We share commenters' concerns regarding the potential
impact on ESRD QIP measure calculations for PY 2022 due to the COVID-19
PHE and the shortened data collection period resulting from the
nationwide ECE. In order to avoid unfairly penalizing facilities based
on data that may not accurately reflect the quality of care provided
due to circumstances beyond their control, in section IV.D of this
final rule we are finalizing our proposal to adopt a special scoring
and payment policy for PY 2022, under which we will not score or apply
payment reductions to any ESRD facilities for PY 2022 under the ESRD
QIP.
Comment: A few commenters expressed strong support for extending
the ECE through the end of 2020, noting the continuing impact of COVID-
19 on dialysis facilities. A few commenters also noted that COVID-19
case rates were higher in Q3 and Q4 of 2020 for patients attributed to
dialysis facilities in certain geographic regions, and that these
higher case rates may have affected performance scores under ESRD QIP.
Response: We agree that the impact of COVID-19 on dialysis
facilities in 2020 has affected our ability to accurately measure their
performance. We resumed data collection for the ESRD QIP on July 1,
2020 because we believe that collecting ESRD QIP measure data is
important in order to better understand the impact of COVID-19 on the
data as it relates to factors such as the changing geographic
differences in COVID-19 incidence and the quality of ESRD care provided
to Medicare beneficiaries. However, to avoid unfairly penalizing
facilities based on data that may not accurately reflect their quality
of care, we are finalizing a measure suppression policy for the
duration of the COVID-19 PHE and a special scoring and payment policy
for PY 2022 in sections IV.C. and IV.D. of this final rule.
Comment: One commenter expressed support for CMS' intention to
provide subregulatory notice of decisions surrounding payment
adjustments and penalties under the ESRD QIP.
Response: In the September 2020 IFC, we stated that in the interest
of time and transparency, we may provide subregulatory advance notice
of our intentions regarding payment adjustments and penalties (85 FR
54830). However, we would like to clarify that we would use rulemaking
to propose any actual modifications to the ESRD QIP scoring and payment
adjustment methodologies and that we
[[Page 61909]]
are using this final rule to finalize our scoring and payment
adjustment policy for PY 2022.
Comment: One commenter requested that CMS provide further guidance
to facilities regarding the criteria for requesting an ECE during a
pandemic.
Response: The criteria for requesting an ECE under the ESRD QIP
during a pandemic are the same as the criteria for requesting an ECE
under the ESRD QIP due to other extraordinary circumstances beyond a
facility's control. These requirements can be found in our regulations
at 42 CFR 413.178(d)(3) through (7). Under these requirements, a
facility may request an ECE within 90 days of the extraordinary
circumstance occurring and must submit an ECE request form to CMS with
the following information:
(i) Facility CCN.
(ii) Facility name.
(iii) CEO name and contact information.
(iv) Additional contact name and contact information.
(v) Reason for requesting an exception.
(vi) Dates affected.
(vii) Date the facility will start submitting data again, with
justification for this date.
(viii) Evidence of the impact of the extraordinary circumstances,
including but not limited to photographs, newspaper, and other media
articles.
In certain circumstances, such as a determination that an
extraordinary circumstance has occurred that affects an entire region
or locale, CMS may grant exceptions to facilities without a request. We
note that facilities may also reject an ECE granted by CMS under
certain circumstances. Technical details can be viewed on the
QualityNet website.\113\
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\113\ https://qualitynet.cms.gov/esrd/esrdqip/participation#tab5.
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As established in the September 2020 IFC, we have finalized our
updated application of the ECE granted in response to the COVID-19 PHE.
2. ECE Due to ESRD Quality Reporting System (EQRS) Issues
On November 9, 2020,\114\ we launched the ESRD Quality Reporting
System (EQRS). The EQRS contains the functionalities of the following
three legacy ESRD Systems in one global application: (1) A quality
measure and VBP performance score review system (ESRD QIP System); (2)
an ESRD patient registry and quality measure reporting system through
the Consolidated Renal Operations in a Web-enabled Network (CROWNWeb);
and (3) Medicare coverage determination support through the Renal
Management Information System (REMIS). The transition to EQRS supports
our efforts to consolidate the functionalities of the CROWNWeb, ESRD
QIP System, and REMIS applications into a single system, and aims to
provide ongoing support to the ESRD user community to foster accurate
and timely monthly data submission. This migration eliminates the need
for multiple user accounts, and will in the long-term also improve the
overall user experience and reduce burden due to enhanced navigation
features.
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\114\ https://mycrownweb.org/2020/11/november-2020-newsletter/.
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In order to access EQRS, all authorized users must create an
account with the Health Care Quality Information Systems (HCQIS) Access
Roles and Profile, known as HARP, which is a secure identity management
portal provided by CMS. Previously, users created separate accounts for
each ESRD application through CMS' Enterprise Identity Data Management
(EIDM) system. Creating an account via HARP provides users with a user
ID and password that can be used to access many CMS applications. It
also provides a single location for users to modify their profile,
change their password, update their challenge question, and add or
remove two-factor authentication devices. Users can register for a HARP
account by going to the QualityNet HARP Registration page, available at
https://harp.cms.gov/register/profile-info.
We stated in the CY 2022 ESRD PPS proposed rule (86 FR 36348) that
since the launch of EQRS, several critical data submission issues had
been identified that impact the overall quality and accuracy of data
available to support the implementation of the ESRD QIP, and we
suspended all clinical data submissions into EQRS to allow time to
resolve the issue.\115\ Based on our assessment, the data submission
issues only impacted ESRD QIP, Dialysis Star Ratings, Dialysis Facility
Compare and data submitted for ESRD Network quality improvement
activities. In the proposed rule, we noted that we had analyzed the
data submission issues and stated our belief that the data systems
issues would be resolved on or about July 12, 2021.\116\
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\115\ https://mycrownweb.org/2021/02/eqrs-data-reporting-update-feb-2021/.
\116\ On July 9, 2021, we announced that the EQRS data
suspension will be concluded as of July 12, 2021, and that EQRS
testing had been performed to ensure that the system is working as
expected. https://mycrownweb.org/2021/07/eqrs-data-reporting-to-resume/.
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We recognized that these operational systems issues would prevent
facilities from submitting ESRD QIP clinical data until the data
systems issues were resolved. Therefore, we announced a blanket
extension of remaining CY 2020 clinical reporting deadlines (86 FR
36348 through 36349). Under this extension, facilities would have until
September 1, 2021 to submit September through December 2020 ESRD QIP
clinical data. In the proposed rule (86 FR 36348), we stated our belief
that this reporting extension aligned with the time estimated for
resolution of our operational systems issues and would give dialysis
facilities nearly 7 weeks to submit their data to EQRS. We stated that
we would provide further details to facilities when the EQRS issues
were resolved, as well as when facilities could begin submitting their
data for CY 2020 and CY 2021, through routine communication channels to
facilities, vendors, Quality Improvement Organizations (QIOs) and ESRD
Networks. We stated that the communications could include memos,
emails, and notices on the public QualityNet website (https://www.qualitynet.org/). As this situation was ongoing at the time, we
stated in the proposed rule that we would announce any relevant
extension deadlines and data submission requirements for impacted CY
2021 data through the routine communication channels discussed above.
On September 3, 2021, we announced that the September 1, 2021 data
submission deadline for September-December 2020 clinical data had been
extended to September 15, 2021 in order to give facilities additional
time to submit their data.\117\
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\117\ https://mycrownweb.org/2021/09/clarified-eqrs-2020-data-submission-deadline-extension-2021-clinical-data-submission-deadline/. We also have provided additional information at: https://mycrownweb.org/wp-content/uploads/2021/07/FAQ_Resuming-2020_2021Clinical-Data-Submission_Final_508.pdf.
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Because the current data submissions issue would not be resolved
until or about July 12, 2021 and had impacted all facilities that
participate in ESRD QIP, we stated our belief that granting a blanket
ECE to all facilities without a request under 42 CFR 413.178(d)(6)(ii)
was the appropriate remedy under these circumstances. We also stated
our belief that requiring facilities to report the CY 2020 data
impacted by this ECE by September 1, 2021 was reasonable. In our data
suspension announcements, we noted that facilities were expected to
continue to use EQRS to collect clinical data to complete tasks such as
admit and discharge patients, complete CMS
[[Page 61910]]
forms (such as the CMS-2728: End Stage Renal Disease Medical Evidence
Report Medicare Entitlement and/or Patient Registration, CMS-2744: End
Stage Renal Disease Annual Facility Survey Form, and CMS-2746: ESRD
Death Notification), add or update treatment summaries, resolve
notifications within a timely manner, and should also continue to keep
facilities' information up-to-date.\118\ In other words, although
facilities were unable to submit clinical data through EQRS, facilities
were advised that they must continue to collect the clinical data.
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\118\ https://mycrownweb.org/2021/02/eqrs-data-reporting-update-feb-2021/.
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In the proposed rule (86 FR 36349), we stated that while we were
working to resolve all known systems issues by July 12, 2021 and reopen
submissions so that facilities may submit their September through
December 2020 ESRD QIP data no later than September 1, 2021, we would
only be able to ensure the validity of the impacted data after they are
submitted. Given that the system issues experienced during the initial
implementation of the EQRS, if not fully resolved, could potentially
impact the accuracy and reliability of the data reported, we were
concerned that facilities may be unfairly penalized because the current
systems issues may impact the quality of the data. The EQRS system
issues had resulted in multiple or incorrect dates of patient
admissions and/or discharges, as well as showing duplicate patient
records. Facilities had also expressed concerns about their experience
with EQRS issues, noting that there was no way for a facility to verify
accuracy or completeness. They had reported issues including missing
record status in response files, which meant that facilities did not
know if the records were accepted or received an error response, and
issues with determining whether clinical data were accepted because the
information did not show in the user interface or the reports that
facilities were receiving from EQRS.
We stated in the proposed rule that we recognized stakeholders'
concerns about the potential impact to the quality of data for CY 2020.
We stated our belief that the observed system issues, and any
unresolved issues that may be identified only after data submissions
are resumed, could impact the quality and accuracy of the data needed
to calculate accurate ESRD QIP scores used for PY 2022 ESRD QIP
calculations because patient admittance dates, discharge dates, record
status in response files, clinical data, and the number of active
patient cases are data points that are included in measure calculations
for all of the PY 2022 ESRD QIP measures. If these data points were
incorrect, then this would impact our ability to accurately calculate
measures and would distort a facility's measure performance.
Therefore, because of the EQRS system issues described above, and
additionally, due to the impact of the COVID-19 PHE on some of the PY
2022 ESRD QIP measures, as described more fully in section IV.C. of
this final rule, we proposed to not score or award a TPS to any
facility, or reduce payment to any facility, in PY 2022. As discussed
more fully in section IV.D below, we are finalizing that proposal in
this final rule.
Although we considered if there may be any alternative data sources
for the measures impacted by these EQRS system issues, we concluded
that this was not feasible for several reasons. First, all 14 ESRD QIP
measures for PY 2022 were impacted by these system issues. Although
certain measures do not require that facilities submit clinical data
into EQRS, we use EQRS data to determine whether a facility has treated
a sufficient number of patients in order to meet the measure's minimum
patient case threshold necessary to calculate the measure for ESRD QIP.
For example, the National Healthcare Safety Network (NHSN) Bloodstream
Infection (BSI) clinical measure requires that facilities report data
to NHSN. However, the measure also has a requirement to exclude
facilities that do not treat at least 11 eligible in-center
hemodialysis patients during the 12 month performance period. In order
to determine whether a facility has treated at least 11 eligible
patients, we use EQRS admission data and Medicare claims data in order
to determine whether the facility is eligible to receive a score on the
measure.\119\
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\119\ https://www.cms.gov/files/document/cy-2021-final-technical-specifications-20201130.pdf.
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We ultimately decided to propose the special rule for PY 2022, as
described further, because not only do these system issues impact all
ESRD QIP measures, which could lead to distorted performance scores and
unfair penalties, but we also wanted to provide facilities with the
business certainty they need regarding their PY 2022 payments. In order
to determine whether all data quality issues have been resolved when
EQRS reopens for data submissions, we stated that we would need time to
validate the impacted data after facilities are able to resume data
submission. Due to the timing of this reporting extension, we stated
our belief that there were no feasible alternative data sources for PY
2022. Therefore, we stated that the scoring and payment modifications
we proposed for PY 2022 were appropriate in this situation.
Comment: Several commenters expressed appreciation and support for
the reporting extension granted due to EQRS issues. A few commenters
noted that facilities have experienced challenges with reporting data
to EQRS and that the extension is helpful particularly as facilities
continue to also address the impact of the COVID-19 PHE.
Response: We thank the commenters for their support.
Comment: A few commenters requested that CMS extend the reporting
extension to the end of CY 2021, noting the ongoing COVID-19 PHE and
continued challenges with data reporting. One commenter expressed the
belief that extending the reporting deadline to the end of CY 2021 will
help to ensure the accuracy and completeness of the data submitted. One
commenter expressed concern that EQRS issues may not be fully resolved
by the anticipated deadline, and requested that CMS issue further
flexibilities if necessary.
Response: Although we initially extended the data submission
deadline to September 1, 2021, we subsequently extended that deadline
to September 15, 2021 in order to give facilities additional time to
submit their data. We note that all outstanding EQRS issues have been
resolved and we reopened access to EQRS on July 12, 2021. We believe
that 2 months was sufficient time for facilities to report September
through December 2020 ESRD QIP data.
Comment: A few commenters expressed support for the issuance of
notifications through routine communication channels, in the event that
an additional extension is granted due to unresolved EQRS issues.
Response: We thank the commenters for their support.
C. Flexibilities for the ESRD QIP in Response to the COVID-19 PHE
1. Adoption of a Measure Suppression Policy for the Duration of the
COVID-19 PHE
In the CY 2022 ESRD PPS proposed rule, we stated that in previous
rules, we have identified the need for flexibility in our quality
measurement programs to account for changing conditions that are beyond
participating facilities' or practitioners' control. We identified this
need because we would like to ensure that participants in our
[[Page 61911]]
programs are not affected negatively when their quality performance
suffers for reasons not due to the care provided, but instead due to
external factors.
A significant example of the type of external factor that may
affect quality measurement is the COVID-19 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 have impeded effective quality measurement in many
ways. Changes to clinical practices to accommodate 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
used in quality measurement and the resulting quality scores. Measures
used in the ESRD QIP need to be evaluated to determine whether their
specifications need to be updated to account for new clinical
guidelines, diagnosis or procedure codes, and medication changes that
we have observed during the PHE. Additionally, because COVID-19
prevalence is not consistent across the country, dialysis facilities
located in different areas have been affected differently at different
times throughout the pandemic. Under those circumstances, we stated in
the proposed rule that we remain significantly concerned that the ESRD
QIP's quality measure scores that are calculated using data submitted
during the PHE for COVID-19 will be distorted and will result in skewed
payment incentives and inequitable payments, particularly for dialysis
facilities that have treated more COVID-19 patients than others.
We further stated that it is not our intention to penalize dialysis
facilities based on measure scores that we believe are distorted by the
COVID-19 pandemic and, thus, not reflective of the quality of care that
the measures in the ESRD QIP were designed to assess. As previously
discussed, 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 those made on clinical
topics covered by the ESRD QIP's measures. As a result of the COVID-19
PHE, dialysis facilities could provide care to their patients that
meets the underlying clinical standard but results in worse measured
performance, and by extension, payment penalties in the ESRD QIP. We
also stated that we are concerned that regional differences in COVID-19
prevalence during the performance period for PY 2022 have directly
affected dialysis facilities' measure scores on the ESRD QIP for PY
2022. Although these regional differences in COVID-19 prevalence rates
do not reflect differences in the quality of care furnished by dialysis
facilities, they could directly affect the payment penalties that these
facilities could receive and could result in an unfair and inequitable
distribution of those penalties. These inequities could be especially
pronounced for dialysis facilities that have treated a large number of
COVID-19 patients.
We therefore proposed to adopt a policy for the duration of the
COVID-19 PHE that would enable us to suppress the use of ESRD QIP
measure data for all facilities if we determine that circumstances
caused by the COVID-19 PHE have affected those measures and the
resulting total performance scores (TPSs) significantly (86 FR 36350).
We also proposed to suppress certain measures for the PY 2022 program
year because we have determined that circumstances caused by the COVID-
19 PHE have affected those measures significantly. In addition, due to
both the impacts of the COVID-19 PHE on certain measures and the EQRS
system issues described in section IV.B.2. we proposed to adopt a
special scoring and payment rule for PY 2022, as described more fully
in section IV.D.
In developing the proposed policy, we considered what circumstances
caused by the COVID-19 PHE would affect a quality measure significantly
enough to warrant its suppression in a value-based purchasing (VBP)
program. We stated our belief that a significant deviation in measured
performance that can be reasonably attributed to the COVID-19 PHE is a
significant indicator of changes in clinical conditions that affect
quality measurement. Similarly, we stated our belief 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 pandemic, we stated our belief 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 noted 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 stated our belief that, as
evidenced during the COVID-19 pandemic, national or regional shortages
or changes in health care personnel, medical supplies, equipment,
diagnostic tools, and patient case volumes or 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 ESRD QIP measures for one or more
payment years that overlap with the COVID-19 PHE. We proposed to adopt
these Measure Suppression Factors for use in the ESRD QIP and, for
consistency, the following other VBP programs: Hospital VBP Program,
Hospital Readmissions Reduction Program, Hospital-Acquired Condition
(HAC) Reduction Program, and Skilled Nursing Facility VBP Program (see,
for example, 86 FR 25460 through 25462, 25470 through 25472, and 25497
through 25499). We stated our belief that these Measure Suppression
Factors will help us evaluate measures in the ESRD QIP and that their
adoption in the other VBP programs noted previously will help ensure
consistency in our measure evaluations across programs. The proposed
Measure Suppression Factors are as follows:
Factor 1: Significant deviation in national performance on
the measure during the COVID-19 PHE, which could be significantly
better or significantly worse compared to historical performance during
the immediately preceding program years.
Factor 2: Clinical proximity of the measure's focus to the
relevant disease, pathogen, or health impacts of the COVID-19 PHE.
Factor 3: Rapid or unprecedented changes in:
++ Clinical guidelines, care delivery or practice, treatments,
drugs, or related protocols, or equipment or diagnostic tools or
materials; or
++ the generally accepted scientific understanding of the nature or
biological pathway of the disease or pathogen, particularly for a novel
disease or pathogen of unknown origin.
Factor 4: Significant national shortages or rapid or
unprecedented changes in:
++ Healthcare personnel;
++ medical supplies, equipment, or diagnostic tools or materials;
or
++ patient case volumes or facility-level case mix.
In the CY 2022 ESRD PPS proposed rule, we also considered
alternatives to this proposed policy that could fulfill our objective
to not penalize dialysis facilities for measure results that are
distorted due to the COVID-19 PHE. As previously noted, the country
continues to grapple with the effects of the COVID-19 pandemic, and in
March
[[Page 61912]]
2020, CMS issued a nationwide, blanket Extraordinary Circumstances
Exception (ECE) for all hospitals and other facilities participating in
our quality reporting and VBP programs in response to the COVID-19 PHE.
This blanket ECE excepted all data reporting requirements for Q1 and Q2
2020 data, including claims data and data collected through the CDC's
web-based surveillance system for this data period, and quality data
collection resumed on July 1, 2020. 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 this blanket ECE that
we issued for Q1 and Q2 2020 to also include Q3 and Q4 2020. This
alternative would have protected providers and suppliers from having
their quality data used for quality scoring purposes if those data were
likely to have been affected significantly by the COVID-19 PHE.
However, this option would have made quality data collection and
reporting to CMS no longer mandatory and would have left us with no
comprehensive data available 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 an alternative to the proposed quality measure suppression
policy, we also considered not suppressing any measures under the ESRD
QIP. However, this alternative would mean assessing dialysis facilities
using quality measure data that has been significantly affected by the
COVID-19 pandemic. Additionally, given the geographic disparities in
the COVID-19 pandemic's effects, we stated in the proposed rule that
implementation of the PY 2022 ESRD QIP as previously finalized would
place dialysis facilities in regions that were more heavily impacted by
the pandemic in Q3 and Q4 of 2020 at a disadvantage compared to
facilities in regions that were more heavily impacted during the first
two quarters for CY 2020 (86 FR 36350 through 36351).
We stated in the proposed rule that we viewed this measure
suppression proposal as a necessity to ensure that the ESRD QIP does
not penalize facilities based on external factors that were beyond the
control of facilities. We intended for this proposed policy to provide
short-term relief to dialysis facilities when we have determined that
one or more of the Measure Suppression Factors warrants the suppression
of an ESRD QIP measure.
We welcomed public comments on this proposal for the adoption of a
measure suppression policy for the duration of the COVID-19 PHE, and
also on the proposed Measure Suppression Factors that we developed for
purposes of this proposed policy. The comments we received and our
responses are set forth below.
Comment: Many commenters expressed support for the measure
suppression policy for the duration of the COVID-19 PHE. Several
commenters expressed appreciation that the proposed measure suppression
policy would help to address the ongoing challenges of the COVID-19
PHE. Several commenters expressed support for the proposed measure
suppression policy, noting that measure scores may be distorted due to
the substantial impact of the COVID-19 PHE on facility performance and
that such a policy would help to avoid penalizing facilities based on
potentially distorted data due to the COVID-19 PHE.
Response: We thank commenters for their support.
Comment: One commenter acknowledged the benefit of the proposed
measure suppression policy, but also expressed concern regarding the
exclusion of data showing the high morbidity and mortality of ESRD
patients with COVID-19.
Response: Although we will not score facilities using data
submitted during the ECE, we do intend to make individual facility data
that was reported available to that facility so that the facility has
an opportunity assess the impact of COVID-19 on its ESRD patients. We
will also publicly report the measure rates with appropriate caveats.
We believe that providing as much information as possible to facilities
in this way while also publicly reporting performance data to the
public with appropriate caveats balances fairness in our value-based
purchasing programs with the public's need for transparency.
Comment: Several commenters expressed support for the proposals to
address the negative impact of the pandemic on the ESRD QIP and
recommended that CMS consider similar considerations for CY 2021
measure data. A few commenters strongly recommended that CMS consider
extending relief under the ESRD QIP to PY 2023, citing the rise of the
Delta variant and continuing impact of COVID-19 on facilities as well
as the healthcare system nationwide. These commenters noted the
continuing impact of the PHE on ESRD QIP measures, due both to the
impact of COVID-19 on ESRD patients which may result in new hospital
admissions and impact facility performance on SHR and SRR measures, as
well as the strain on the healthcare system due to the influx of COVID-
19 patients which may impact the availability of vascular access
procedures and transplant evaluations. A few commenters noted that
geographic variations in the COVID-19 PHE during CY 2021 continue to
exacerbate distortions in ESRD QIP measure performance.
Response: The measure suppression policy that we are finalizing in
this final rule applies for the duration of the COVID-19 PHE. We will
continue to monitor the impact of the COVID-19 PHE on dialysis
facilities, and we would consider proposing in a future rulemaking to
suppress one or more individual ESRD QIP measures for a future ESRD QIP
payment year if we conclude that circumstances caused by the COVID-19
PHE have affected those measures and the resulting TPSs based on CY
2021 data.
Comment: Several commenters expressed support for the proposed
Measure Suppression Factors. Several commenters noted that they will
help to mitigate the negative impact of the challenges presented by the
COVID-19 PHE such as significant deviation in national performance, the
distorting impact on measures themselves, changing guidelines and
protocols related to the PHE, and challenges due to shortages in both
medical supplies, staffing, and patient volume and case-mix on quality
measures. One commenter expressed support for the proposed Measure
Suppression Factors, noting that they will help to ensure consistency
in measure evaluation and suppression.
Response: We thank commenters for their support.
Comment: A few commenters expressed concern regarding the proposed
Measure Suppression Factors. One commenter expressed concern that
proposed Measure Suppression Factor 2 may overlook indirect or
downstream clinical impacts that may not be considered ``proximate,''
noting for example the impact of the COVID-19 PHE shutdown on non-
urgent scheduled vascular placement procedures leading to reduced
catheter insertions and fistula rates as well as a delay in patient
follow up regarding such procedures due to patient fears of COVID-19
exposure. One commenter expressed concern that proposed Measure
Suppression Factor 4 does not sufficiently address regional or State-
by-State impacts on personnel, patient volumes or case-mix, and medical
[[Page 61913]]
supplies or equipment, and recommended that CMS broaden application of
its scope to include sub-national, regional, and State impacts. One
commenter recommended that CMS consider under Measure Suppression
Factor 4 the impact of healthcare personnel shortages on ESRD
facilities as a result of the COVID-19 PHE. One commenter recommended
that CMS consider including under Measure Suppression Factor 4
circumstances where there is a statistically meaningful lower
denominator from prior years due to factors outside of a facility's
control, such as changes in demographics.
Response: We developed the Measure Suppression Factors based on
several considerations specifically related to the PHE for COVID-19,
including national, regional, and State impacts. For example, we note
that Measure Suppression Factor 4 addresses healthcare shortages in
personnel as well as patient volumes and facility-level case mix. We
believe the Measure Suppression Factors we are adopting for the COVID-
19 PHE are sufficient to guide us in identifying whether circumstances
caused by the COVID-19 PHE have affected ESRD QIP measures and the
resulting TPSs.
Comment: One commenter recommended adding an additional measure
suppression factor to suppress a measure in cases where the measure
denominator is statistically meaningfully lower due to circumstances
beyond the facility's control such as COVID-19 mortality, noting that
this may significantly also impact measure performance.
Response: We believe that the commenter's suggestion would be
captured by the proposed Measure Suppression Factor 4. As we discussed
in the proposed rule (86 FR 36350), we developed these suppression
factors to assess changing conditions due to the COVID-19 PHE and
proposed them consistently in several of our value-based purchasing
programs. As we stated above, we believe the Measure Suppression
Factors we are adopting for the COVID-19 PHE are sufficient to guide us
in identifying whether circumstances caused by the COVID-19 PHE have
affected ESRD QIP measures and the resulting TPSs.
Comment: A few commenters expressed support for the proposal to
provide confidential feedback reports to dialysis facilities under the
proposed measure suppression policy, noting that it will allow
facilities to focus on performance improvement and also allow CMS to
track developments in the field.
Response: We thank the commenters for their support and note that
we are finalizing this proposal in this final rule.
Comment: One commenter expressed support for the public reporting
of performance scores from CY 2020 with appropriate caveats.
Response: We thank the commenter for its support.
Comment: A few commenters did not support the public reporting of
suppressed measures, noting reliability concerns due to the impact of
the COVID-19 PHE on measure data.
Response: We believe it is important to balance fairness with the
public's need for transparency. Therefore, we intend to make the data
publicly available. In order to address concerns about publicly
reporting data that was collected by facilities during the COVID-19
PHE, we will appropriately caveat the publicly displayed data for
suppressed measures to note that the measures have been suppressed for
purposes of scoring and payment adjustments because of the effects of
the COVID-19 PHE. We believe these caveats will mitigate any public
confusion that could otherwise result from the display.
Final Rule Action: After considering public comments, we are
finalizing our proposal to adopt a measure suppression policy for the
duration of the COVID-19 PHE. We are also finalizing the proposed
Measure Suppression Factors that we proposed for purposes of this
measure suppression policy. We will also publicly report the data with
appropriate caveats.
2. Suppression of Four ESRD QIP Measures for PY 2022
a. Background
In response to the PHE for COVID-19, we conducted analyses of the
14 current ESRD QIP measures to determine whether and how COVID-19 may
have impacted the validity of these measures. For the reasons discussed
in the CY 2022 ESRD PPS proposed rule, we concluded that COVID-19 has
so severely impacted the validity of four measures that we believe we
cannot fairly and equitably score these measures for the PY 2022
program year. Accordingly, we proposed to suppress these measures for
the PY 2022 program year for all ESRD QIP participants (86 FR 36351).
Specifically, the measures we proposed to suppress for the PY 2022 ESRD
QIP are as follows:
SHR clinical measure (under Measure Suppression Factor 1,
Significant deviation in national performance on the measure during the
COVID-19 PHE, which could be significantly better or significantly
worse compared to historical performance during the immediately
preceding program years; and Measure Suppression Factor 4, Significant
national shortages or rapid or unprecedented changes in:
++ healthcare personnel;
++ medical supplies, equipment, or diagnostic tools or materials;
or
++ patient case volumes or facility-level case mix);
Standardized Readmission Ratio (SRR) clinical measure
(under Measure Suppression Factor 1, Significant deviation in national
performance on the measure during the COVID-19 PHE, which could be
significantly better or significantly worse compared to historical
performance during the immediately preceding program years; and Measure
Suppression Factor 4, Significant national shortages or rapid or
unprecedented changes in:
++ healthcare personnel;
++ medical supplies, equipment, or diagnostic tools or materials;
or
++ patient case volumes or facility-level case mix);
In-Center Hemodialysis Consumer Assessment of Healthcare
Providers and Systems (ICH CAHPS) Survey Administration clinical
measure (under Measure Suppression Factor 1, Significant deviation in
national performance on the measure during the COVID-19 PHE, which
could be significantly better or significantly worse compared to
historical performance during the immediately preceding program years);
and
Long-Term Catheter Rate clinical measure (under Measure
Suppression Factor 1, Significant deviation in national performance on
the measure during the COVID-19 PHE, which could be significantly
better or significantly worse compared to historical performance during
the immediately preceding program years).
We received comments on additional measures that we should consider
suppressing and address them below.
Comment: Several commenters recommended that we suppress the
Standardized Fistula Rate measure. A few commenters noted that the
Standardized Fistula Rate measure and the Long-Term Catheter Rate
measure are both Hemodialysis Vascular Access measures, but only the
Long-Term Catheter Rate measure is proposed for suppression. A few
commenters noted that AV fistula placements may have been delayed
because it was not clear whether such procedures were considered an
``elective surgery'' in the beginning of the PHE and also because
[[Page 61914]]
ESRD patients may have delayed or avoided medical treatments because of
COVID-19 concerns. Several commenters recommended that CMS suppress the
Percentage of Prevalent Patients Waitlisted (PPPW) measure, noting that
the COVID-19 PHE had a significant negative impact on transplant
surgeries, referrals and waitlists, as well as other related areas. A
few commenters also noted that waitlist additions significantly
decreased during the COVID-19 PHE.
A few commenters recommended that CMS consider suppressing the Kt/V
Dialysis Adequacy measure, noting that the impact of the COVID-19 PHE
on catheter rates has a corresponding impact on the Kt/V measure, as
patients with catheters will have lower Kt/V rates. One commenter
recommended suppressing the Kt/V Dialysis Adequacy measure under
proposed Measure Suppression Factor 1, due to significant deviation in
national measure performance. One commenter recommended that CMS
suppress the NHSN BSI clinical measure under Measure Suppression Factor
3 and Factor 4, noting that challenges in care delivery and treatment
related to catheter removal and AVF insertion resulted in an increased
likelihood of patient infection, as well as an increase in patient
volume and case-mix due to COVID-19 patients developing AKI and
requiring catheterization.
Response: At the time of the proposed rule, there was not
sufficient data to determine whether suppression was appropriate for
the Standardized Fistula Rate measure, the PPPW measure, the Kt/V
Dialysis Adequacy measure, or the NHSN BSI clinical measure. We note
that the status of the data remains unchanged since the proposed rule
was published. Although we agree with commenters that performance on
the Standardized Fistula Rate measure is linked to measure performance
on the Long-Term Catheter Rate measure, the data that was available at
the time of the proposed rule indicated that the COVID-19 PHE had a
comparatively lower impact on the Standardized Fistula Rate measure.
For the PPPW measure, our analysis of the relevant data available
at the time of the proposed rule indicated temporal declines in
waitlist removal among prevalent patients and similarly a decline in
waitlisting and transplants in incident ESRD patients in March 2020
through May 2020 compared to prior years. However, we also observed
that trends generally returned to normal starting in June and July 2020
and reflected data similar to prior years.
Although performance on the Kt/V Dialysis Adequacy measure deviated
temporarily, our analysis indicated that Kt/V rates stabilized shortly
thereafter and reflect measure performance similar to prior years.
Based on our analysis, Kt/V rates in CY 2020 were similar to rates in
CY 2019 until April, where they dropped by an average of 0.4 percent.
However, beginning in June 2020, Kt/V rates were the same as or higher
than national average rates in March 2020.
We were unable to assess the impact of the COVID-19 PHE on the NHSN
BSI clinical measure, which requires a full 12 months of data in order
to calculate measure performance. The CDC will not be able to calculate
measure performance for the NHSN BSI clinical measure because the
nationwide ECE granted in response to the COVID-19 PHE excepted data
from Q1 and Q2 of CY 2020. As a result, facilities will not receive
scores for the NHSN BSI clinical measure. We also note that suppressing
the NHSN BSI clinical measure would be unlikely under Measure
Suppression Factor 3 and Factor 4, as the links between those factors
and the impacts on measure performance cited by the commenter are not
sufficiently direct. Although challenges in care delivery and treatment
related to catheter removal and AVF insertion resulted in an increased
likelihood of patient infection, as well as an increase in patient
volume and case-mix due to COVID-19 patients developing AKI and
requiring catheterization, neither of those directly caused patients to
develop more bloodstream infections as a result of the COVID-19 PHE.
However, we will continue to monitor and review the data and
consider proposing in a future rulemaking to suppress one or more
individual ESRD QIP measures for a future ESRD QIP payment year if we
conclude that circumstances caused by the COVID-19 PHE have affected
those measures and the resulting TPSs based on CY 2021 data.
b. Suppression of the SHR clinical measure for PY 2022
In the CY 2022 ESRD PPS proposed rule (86 FR 36351 through 36352),
we proposed to suppress the SHR clinical measure for the PY 2022
program year under proposed Measure Suppression Factor 1, Significant
deviation in national performance on the measure during the COVID-19
PHE, which could be significantly better or significantly worse as
compared to historical performance during the immediately preceding
program years. The SHR clinical measure is an all-cause, risk-
standardized rate of hospitalizations during a 1-year observation
window. The standardized hospitalization ratio is defined as the ratio
of the number of hospital admissions that occur for Medicare ESRD
dialysis patients treated at a particular facility to the number of
hospitalizations that would be expected given the characteristics of
the dialysis facility's patients and the national norm for dialysis
facilities. This measure is calculated as a ratio but can also be
expressed as a rate. The intent of the SHR clinical measure is to
improve health care delivery and care coordination to help reduce
unplanned hospitalization among ESRD patients.
Based on our analysis of Medicare dialysis patient data from
January 2020 through August 2020, we found that hospitalizations
involving patients diagnosed with COVID-19 resulted in higher mortality
rates, higher rates of discharge to hospice or skilled nursing
facilities, and lower rates of discharge to home than hospitalizations
involving patients who were not diagnosed with COVID-19. Specifically,
the hospitalization rate for Medicare dialysis patients diagnosed with
COVID-19 was more than 7 times greater than the hospitalization rate
during the same period for Medicare dialysis patients who were not
diagnosed with COVID-19, which is much greater than the relative risk
of hospitalization for any other comorbidity. In the proposed rule (86
FR 36351), we stated that this indicates that COVID-19 has had a
significant impact on the hospitalization rate for dialysis patients.
Because COVID-19 Medicare dialysis patients are at significantly
greater risk of hospitalization, and the SHR clinical measure was not
developed to account for the impact of COVID-19 on this patient
population, we expressed our concern about the effects of the observed
COVID-19 hospitalizations on the SHR clinical measure. We also noted
that 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. Because of the
increased hospitalization risk associated with COVID-19 and the
Medicare dialysis patient population, we expressed our concern that
these regional differences in COVID-19 rates have led to distorted
hospitalization rates such that we could not reliably measure national
performance on the SHR clinical measure.
Our analysis of the available Medicare claims data indicated that
the COVID-19 PHE has had significant effects on hospital admissions of
dialysis patients,
[[Page 61915]]
and would result in significant deviation in national performance on
the measure during the COVID-19 PHE which could be significantly worse
as compared to historical performance during the immediately preceding
program years. Not only are there effects on patients diagnosed with
COVID-19, but the presence of the virus strongly affected hospital
admission patterns of dialysis patients from March 2020 to June 2020,
and we expressed our concern that similar effects would be seen in the
balance of the calendar year (CY) as the PHE continued. Because the
COVID-19 pandemic swept through geographic regions of the country
unevenly, we expressed our concern that dialysis facilities in
different regions of the country would have been affected differently
throughout the 2020 year, thereby skewing measure performance and
affecting national comparability due to significant and unprecedented
changes in patient case volumes or facility-level case mix. Given the
limitations of the data available to us for CY 2020, we stated our
belief the resulting performance measurement on the SHR clinical
measure would not be sufficiently reliable or valid for use in the ESRD
QIP.
We proposed to suppress this measure for the PY 2022 program year,
rather than remove it, because we believe that the SHR clinical measure
is an important part of the ESRD QIP measure set. However, we were
concerned that the COVID-19 PHE affected measure performance on the
current SHR clinical measure such that we would not be able to score
facilities fairly or equitably on it. Additionally, we stated that we
would continue to collect the measure's claims data from participating
facilities so that we could monitor the effect of the circumstances on
quality measurement and determine the appropriate policies in the
future. We would also continue to provide confidential feedback reports
to facilities as part of program activities to ensure that they are
made aware of the changes in performance rates that we observe. We also
stated our intent to publicly report PY 2022 data where feasible and
appropriately caveated.
In the proposed rule, we stated that we were currently exploring
ways to adjust effectively for the systematic effects of the COVID-19
PHE on hospital admissions for the SHR clinical measure. However, we
are still working to improve these COVID-19 adjustments and verify the
validity of a potential modified version of the SHR clinical measure as
additional data become available. As an alternative, we considered
whether we could exclude patients with a diagnosis of COVID-19 from the
SHR clinical measure cohort, but we determined suppression will provide
us with additional time and additional months of data potentially
impacted by COVID-19 to more thoroughly evaluate a broader range of
alternatives. We want to ensure that the measure reflects care provided
to Medicare dialysis patients and we are concerned that excluding
otherwise eligible patients may not accurately reflect the care
provided, particularly given the unequal distribution of COVID-19
patients across facilities and hospitals over time. As an alternative
approach, we stated that we also might consider updating the
specifications for the SHR clinical measure to eliminate any exposure
time and events after infection for patients who contract COVID-19, as
COVID-19 symptoms may continue to affect patients after infection. We
stated our belief that this approach might help distinguish between
ESRD-related hospitalizations and COVID-19 related hospitalizations
that might otherwise impact SHR clinical measure calculations.
We welcomed public comment on our proposal to suppress the SHR
clinical measure for PY 2022. The comments we received and our
responses are set forth below.
Comment: Several commenters expressed support for the proposal to
suppress the SHR clinical measure for PY 2022, agreeing that the COVID-
19 PHE has impacted the validity and reliability of performance scoring
for PY 2022.
Response: We thank the commenters for their support.
Final Rule Action: After considering public comments, we are
finalizing our proposal to suppress the SHR clinical measure for PY
2022.
c. Suppression of the SRR Clinical Measure for PY 2022
In the CY 2022 ESRD PPS proposed rule (86 FR 36352 through 36353),
we proposed to suppress the SRR clinical measure for the PY 2022
program year under proposed Measure Suppression Factor 1, Significant
deviation in national performance on the measure during the COVID-19
PHE, which could be significantly better or significantly worse
compared to historical performance during the immediately preceding
program years. The SRR assesses the number of readmission events for
the patients at a facility, relative to the number of readmission
events that would be expected based on overall national rates and the
characteristics of the patients at that facility as well as the number
of discharges. The intent of the SRR clinical measure is to improve
care coordination between dialysis facilities and hospitals to improve
communication prior to and post discharge.
Based on our analysis, we found that index discharge
hospitalizations involving dialysis patients diagnosed with COVID-19
resulted in lower readmissions and higher mortality rates within the
first 7 days. We used index hospitalizations occurring from January 1,
2020 through June 30, 2020 to identify eligible index hospitalizations
and unplanned hospital readmissions. In an analysis of unadjusted
readmission and death rates by COVID-19 hospitalization status and days
since index discharge, during the first 4 to 7 days after discharge
there was a readmission rate of 81.3 percent of dialysis patients
hospitalized with COVID-19, as compared to 82.6 percent of dialysis
patients hospitalized without COVID-19. During that same 4 to 7 day
time period, the unadjusted mortality rate for dialysis patients
hospitalized with COVID-19 was 16.9 percent, compared with 10.9 percent
of patients hospitalized without COVID-19. Based on this discrepancy,
we were concerned about the effects of these observations on the
calculations for the SRR clinical measure. The denominator of SRR
reflects the expected number of index discharges followed by an
unplanned readmission within 4 to 30 days in each facility, which is
derived from a model that accounts for patient characteristics, the
dialysis facility to which the patient is discharged, and the
discharging acute care or critical access hospitals involved. Our
analysis indicated potential competing risks of higher mortality and
lower readmissions due to patient death or discharge to hospice, both
of which would remove them from the denominator for the SRR clinical
measure. If readmissions rates are lower because patient mortality is
higher due to the impact of COVID-19 on dialysis patients, then
readmission rates would be distorted by appearing significantly better
compared to historical performance during the immediately preceding
program years. Based on the impact of COVID-19 on SRR results,
including the deviance in measurement, we concluded that the SRR
clinical measure met our criteria for Factor 1 where performance data
would significantly deviate from historical data performance and would
be considered unreliable. Therefore, we stated our belief that the
resulting performance measurement on the SRR clinical
[[Page 61916]]
measure would not be sufficiently reliable or valid for use in the ESRD
QIP.
We proposed to suppress this measure for the PY 2022 program year,
rather than remove it, because we believe that the SRR clinical measure
is an important part of the ESRD QIP Program measure set. However, we
were concerned that the PHE for the COVID-19 pandemic affected measure
performance on the current SRR clinical measure such that we would not
be able to score facilities fairly or equitably on it. Additionally, we
stated that we would continue to collect the measure's claims data from
participating facilities so that we could monitor the effect of the
circumstances on quality measurement and determine the appropriate
policies in the future. We would also continue to provide confidential
feedback reports to facilities as part of program activities to ensure
that they are made aware of the changes in performance rates that we
observe. We also stated our intent to publicly report PY 2022 data
where feasible and appropriately caveated.
In the proposed rule, we stated that we were currently exploring
ways to adjust effectively for the systematic effects of the COVID-19
PHE on hospital admissions for the SRR clinical measure. However, we
are still working to improve these COVID-19 adjustments and verify the
validity of a potential modified version of the SRR clinical measure as
additional data becomes available. As an alternative approach, we
stated that we might also consider eliminating from the calculation of
the SRR clinical measure any cases of patients who had a COVID-19 event
prior to or at the time of index hospitalization. We stated our belief
this approach might help distinguish between ESRD-related readmissions
and COVID-19 related readmissions that might otherwise impact SRR
clinical measure calculations.
We welcomed public comment on our proposal to suppress the SRR
clinical measure for PY 2022. The comments we received and our
responses are set forth below.
Comment: Several commenters expressed support for the proposal to
suppress the SRR clinical measure for PY 2022, agreeing that the COVID-
19 PHE has impacted the validity and reliability of performance scoring
for PY 2022.
Response: We thank the commenters for their support.
Final Rule Action: After considering public comments, we are
finalizing our proposal to suppress the SRR clinical measure for PY
2022.
d. Suppression of the ICH CAHPS Clinical Measure for PY 2022
In the CY 2022 ESRD PPS proposed rule (86 FR 36353), we proposed to
suppress the ICH CAHPS clinical measure for the PY 2022 program year
under proposed Measure Suppression Factor 1, Significant deviation in
national performance on the measure during the COVID-19 PHE, which
could be significantly better or significantly worse compared to
historical performance during the immediately preceding program years.
Based on our analysis of CY 2020 ICH CAHPS data, we found a significant
decrease in response scores as compared to previous years.
The ICH CAHPS clinical measure is scored based on three composite
measures and three global ratings.\120\ Global ratings questions employ
a scale of 0 to 10, worst to best; each of the questions within a
composite measure use either ``Yes'' or ``No'' responses, or response
categories ranging from ``Never'' to ``Always'' to assess the patient's
experience of care at a facility. Facility performance on each
composite measure is determined by the percent of patients who choose
``top-box'' responses (that is, most positive or ``Always'') to the ICH
CAHPS survey questions in each domain. The ICH CAHPS survey is
administered twice yearly, once in the spring and once in the fall.
---------------------------------------------------------------------------
\120\ Groupings of questions and composite measures can be found
at https://ichcahps.org/Portals/0/SurveyMaterials/ICH_Composites_English.pdf.
---------------------------------------------------------------------------
Because of the ECE we granted in response to the COVID-19 PHE,
facilities were not required to submit CY 2020 spring ICH CAHPS data
for purposes of the ESRD QIP. On September 2, 2020, we published an
interim final rule with comment (IFC) in the Federal Register titled,
``Medicare and Medicaid Programs, Clinical Laboratory Improvement
Amendments (CLIA), and Patient Protection and Affordable Care Act;
Additional Policy and Regulatory Revisions in Response to the COVID-19
Public Health Emergency'' (85 FR 54820) referred to herein as the
``September 2020 IFC''. In the September 2020 IFC, we noted that we
would not use any first or second quarter CY 2020 data to calculate
TPSs for the applicable performance period (85 FR 54829 through 54830).
Because the PY 2022 performance period for the ICH CAHPS measure is
January 1, 2020 through December 31, 2020, and the ICH CAHPS survey is
administered twice a year (once in the spring and once in the fall), in
the proposed rule we stated that we only have data available from the
fall CY 2020 survey to calculate facility performance on this measure.
Therefore, facilities would only be scored on data based on one ICH
CAHPS survey administration for CY 2020, rather than two. Even if we
were to score facilities based on the one ICH CAHPS survey administered
in the fall, our preliminary data indicated that 95 percent of
facilities would not be eligible for scoring on ICH CAHPS for CY 2020.
By contrast, 58.9 percent of facilities were not eligible for ICH CAHPS
during CY 2018. If we were to score the 5 percent of eligible
facilities on ICH CAHPS, we stated our belief that there would be a
significant deviation in national performance on this measure compared
to the national performance based on 41.1 percent of facilities
eligible for scoring on ICH CAHPS during 2018 (86 FR 36353). We also
stated that this is a significant deviation in national performance on
this measure compared to historical performance during the immediately
preceding program years. Given this significant deviation in national
performance during the PHE, we expressed our belief that the ICH CAHPS
clinical measure meets the criteria for Measure Suppression Factor 1.
We also stated our belief that this significant change in
performance may unfairly penalize facilities and that suppressing this
measure for the PY 2022 program year would address concerns about the
potential unintended consequences of penalizing facilities that treat
COVID-19 diagnosed patients in the ESRD QIP. As alternative approaches,
we considered changing the performance period or scoring facilities on
one survey administration, but otherwise meeting the 30 completed
surveys requirement. However, we found that neither of these approaches
were feasible; extending the performance period would not accurately
reflect ICH CAHPS performance during CY 2020, and as discussed above,
an estimated 95 percent of facilities would not be eligible for ICH
CAHPS scoring on one survey. Therefore, to avoid unfairly penalizing
facilities due to their performance on the ICH CAHPS survey for the PY
2022 ESRD QIP, we stated our belief that it is appropriate to suppress
the ICH CAHPS measure for CY 2020, which is the performance period for
the PY 2022 ESRD QIP program year (83 FR 57010).
We proposed to suppress this measure for the PY 2022 program year,
rather than remove it, because we believe that the ICH CAHPS measure is
an important part of the ESRD QIP measure set.
[[Page 61917]]
However, we were concerned that the COVID-19 PHE affected measure
performance on the current ICH CAHPS measure such that we would not be
able to score facilities fairly or equitably on it. Additionally,
participating facilities would continue to report the measure's data to
CMS so that we could monitor the effect of the circumstances on quality
measurement and determine the appropriate policies in the future. In
the proposed rule, we stated that we would also continue to provide
confidential feedback reports to facilities as part of program
activities to ensure that they are made aware of the changes in
performance rates that we observe (86 FR 36353). We also stated our
intent to publicly report PY 2022 data where feasible and appropriately
caveated.
We welcomed public comment on our proposal to suppress the ICH
CAHPS measure for the PY 2022 program year. The comments we received
and our responses are set forth below.
Comment: Several commenters expressed support for the proposal to
suppress the ICH CAHPS measure for PY 2022, agreeing that the COVID-19
PHE has impacted the validity and reliability of performance scoring
for PY 2022.
Response: We thank the commenters for their support.
Final Rule Action: After considering public comments, we are
finalizing our proposal to suppress the ICH CAHPS measure for PY 2022.
e. Suppression of the Long-Term Catheter Rate Clinical Measure for PY
2022
In the CY 2022 ESRD PPS proposed rule (86 FR 36353 through 36354),
we proposed to suppress the Long-Term Catheter Rate clinical measure
for the PY 2022 program year under proposed Measure Suppression Factor
1, Significant deviation in national performance on the measure during
the COVID-19 PHE, which could be significantly better or significantly
worse compared to historical performance during the immediately
preceding program years. Based on our analysis of Long-Term Catheter
Rate clinical measure data during CY 2020, we found a significant
increase in long-term catheter use as compared to previous years, which
may be the result of hesitancy to seek medical treatment among dialysis
patients concerned about being exposed to COVID-19 during the PHE.
In the CY 2018 ESRD PPS final rule, we finalized the inclusion of
the Hemodialysis Vascular Access: Long-Term Catheter Rate clinical
measure in the ESRD QIP measure set beginning with the PY 2021 program
(82 FR 50778). The Long-Term Catheter Rate clinical measure is defined
as the percentage of adult hemodialysis patient-months using a catheter
continuously for three months or longer for vascular access. The
measure is based on vascular access data reported in CROWNWeb (now
EQRS) and excludes patient-months where a patient has a catheter in
place and has a limited life expectancy.
Our analysis based on the available data indicated that long-term
catheter use rates increased significantly during the COVID-19 PHE.
Average long-term catheter rates were averaging around 12 percent in CY
2017 and CY 2018. In CY 2019, rates increased to average around 12.25
percent. This increase continued into CY 2020, with rates reaching a
peak of 14.7 percent in June 2020 and declining slightly to 14.3
percent in July and August 2020. After remaining around 12 percent for
3 consecutive years, in the proposed rule we stated that we view a
sudden 2 percent increase in average long-term catheter rates as a
significant deviation compared to historical performance during
immediately preceding years (86 FR 36354). We were concerned that the
COVID-PHE impacted the ability of ESRD patients to seek treatment from
medical providers regarding their catheter use, either due to
difficulty accessing treatment due to COVID-19 precautions at
healthcare facilities, or due to increased patient reluctance to seek
medical treatment because of risk of COVID-19 exposure and increased
health risks resulting therefrom, and that these contributed to the
significant increase in long-term catheter use rates.
We proposed to suppress this measure for the PY 2022 program year,
rather than remove it, because we believe that the Long-Term Catheter
Rate clinical measure is an important part of the ESRD QIP measure set.
However, we were concerned that the PHE for COVID-19 affected measure
performance on the current Long-Term Catheter Rate clinical measure
such that we would not be able to score facilities fairly or equitably
on it. Additionally, participating facilities would continue to report
the measure's data to CMS so that we could monitor the effect of the
circumstances on quality measurement and determine the appropriate
policies in the future. In the proposed rule (86 FR 36354), we stated
that we would also continue to provide confidential feedback reports to
facilities as part of program activities to ensure that they are made
aware of the changes in performance rates that we observe. We also
stated our intent to publicly report PY 2022 data where feasible and
appropriately caveated.
We welcomed public comment on our proposal to suppress the Long-
Term Catheter Rate clinical measure for the PY 2022 program year. The
comments we received and our responses are set forth below.
Comment: Several commenters expressed support for the proposal to
suppress the Long-Term Catheter Rate clinical measure for PY 2022,
agreeing that the COVID-19 PHE has impacted the validity and
reliability of performance scoring for PY 2022.
Response: We thank the commenters for their support.
Final Rule Action: After considering public comments, we are
finalizing our proposal to suppress the Long-Term Catheter Rate
clinical measure for PY 2022.
D. Special Scoring Methodology and Payment Policy for the PY 2022 ESRD
QIP
As described in section IV.B.2. of the proposed rule, we have
considered the impact of operational systems issues preventing
facilities from submitting September through December 2020 patient and
clinical data into the EQRS from November 1, 2020 through on or about
July 12, 2021. Even when facilities are able to submit the September
through December 2020 patient and clinical data by September 1, 2021,
we will need time to validate the quality and reliability of the
impacted data in order to determine whether all data quality issues
have been resolved (86 FR 36354). In addition, as described in section
IV.C. we stated our belief that four of the ESRD QIP measures have been
impacted by the COVID-19 PHE that could result in distorted measure
performance for PY 2022.
It is not our intention to penalize dialysis facilities based on
the performance on data that are not reliable, thus, not reflective of
the quality of care that the measures in the program are designed to
assess. Therefore, we proposed a special rule for PY 2022 scoring for
the ESRD QIP under which we would calculate measure rates for all
measures, but would not calculate achievement and improvement points
for any of them because they have all been impacted by the operational
systems issues and, as we stated previously, we believe that four of
them have additionally been significantly impacted by COVID-19. Because
we would not calculate achievement and improvement scores for any
measures, we also proposed under this special rule that we would
[[Page 61918]]
not score any of the measures in the four domains or calculate or award
Total Performance Scores for any facility. We also proposed to not
apply any payment reductions to ESRD facilities for PY 2022.
In order to ensure that a facility is aware of any changes to its
measure rates that we have observed, we proposed to provide
confidential feedback reports that contain the measure rates we
calculated for PY 2022. Performance scores for facilities would be
released on Dialysis Facility Compare and footnoted to indicate
potential accuracy concerns with the scores. Performance score
certificates would be generated with the TPS showing as ``Not
Applicable.''
We proposed to codify these policies for PY 2022 at 42 CFR
413.177(a) and 413.178(h).
However, we stated that if the proposed measure suppression
policies and proposed special scoring and payment policies in the
proposed rule were not finalized, the PY 2022 ESRD QIP payment would be
implemented in accordance with our current policy, as well as the
payment reduction ranges finalized in the CY 2020 ESRD PPS final rule
(84 FR 60725 through 60727).
We invited public comment on this proposed special scoring and
payment policy for the PY 2022 ESRD QIP. The comments we received and
our responses are set forth below.
Comment: Many commenters expressed support for the proposed special
scoring methodology and payment policy for PY 2022. Several commenters
agreed that quality measure data submitted during the COVID-19 PHE
should not be used for performance scoring or payment in the ESRD QIP,
and expressed their concerns regarding the impact of the COVID-19 PHE
on quality measure data. Several commenters agreed that facilities
should not be penalized due to the potential impact of EQRS issues on
the reliability and accuracy of the data. One commenter expressed the
belief that this proposal would allow staff members to remain focused
on COVID-19 safety.
Response: We thank the commenters for their support.
Comment: A few commenters recommended that CMS apply this special
scoring methodology and payment policy to PY 2023 and possibly future
years, noting the continuing impact of the COVID-19 PHE on facilities
and the ESRD patient population. A few commenters expressed the belief
that it is appropriate to let the healthcare system stabilize from the
effects of the PHE before imposing penalties.
Response: We thank the commenters for this feedback. We acknowledge
the continuing impact of the COVID-19 PHE on facilities and the ESRD
patient population. We will continue to monitor the impact of the
COVID-19 PHE on the ESRD QIP in order to consider, based on the data,
whether to propose changes to the scoring methodology for PY 2023.
Final Rule Action: After considering public comments, we are
finalizing our special scoring and payment policy for the PY 2022 ESRD
QIP as proposed. We are also finalizing our proposal to codify these
policies for PY 2022 at 42 CFR 413.177(a) and 413.178(h).
E. Updates to Requirements Beginning With the PY 2024 ESRD QIP
1. PY 2024 ESRD QIP Measure Set
Under our current policy, we retain all ESRD QIP measures from year
to year unless we propose through rulemaking to remove them or
otherwise provide notification of immediate removal if a measure raises
potential safety issues (77 FR 67475). Accordingly, the PY 2024 ESRD
QIP measure set will include the same 14 measures as the PY 2023 ESRD
QIP measure set (85 FR 71465 through 71466). These measures were
described in Table 2 in the CY 2022 ESRD PPS proposed rule (86 FR
36355) and are described in Table 2 in this final rule. For the most
recent information on each measure's technical specifications for PY
2024, we refer readers to the CMS ESRD Measures Manual for the 2021
Performance Period.\121\
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\121\ https://www.cms.gov/files/document/esrd-measures-manual-v61.pdf. We note that information for the 2022 Performance Period is
also now available at: https://www.cms.gov/files/document/esrd-measures-manual-v70.pdf.
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BILLING CODE 4120-01-P
[[Page 61919]]
[GRAPHIC] [TIFF OMITTED] TR08NO21.001
BILLING CODE 4120-01-C
We discuss our proposal to update the SHR clinical measure in the
following section.
a. Update to the Standardized Hospitalization Ratio (SHR) Clinical
Measure Beginning With the PY 2024 ESRD QIP
In the CY 2017 ESRD PPS final rule, we adopted the SHR clinical
measure under the authority of section 1881(h)(2)(B)(ii) of the Act (81
FR 77906 through 77911). The SHR clinical measure is a National Quality
Forum (NQF)-endorsed all-cause, risk-standardized rate of
hospitalizations during a 1-year observation window. The standardized
hospitalization ratio is defined as the ratio of the number of hospital
admissions that occur for Medicare ESRD dialysis patients treated at a
particular facility to the number of hospitalizations that would be
expected
[[Page 61920]]
given the characteristics of the dialysis facility's patients and the
national norm for dialysis facilities. This measure is calculated as a
ratio but can also be expressed as a rate.
In the CY 2022 ESRD PPS proposed rule (86 FR 36356), we stated that
hospitalizations are an important indicator of patient morbidity and
quality of life. On average, dialysis patients are admitted to the
hospital nearly twice a year and spend an average of 11.2 days in the
hospital per year.\122\ Hospitalizations account for approximately 33
percent of total Medicare expenditures for ESRD patients.\123\ Studies
have shown that improved health care delivery and care coordination may
help reduce unplanned acute care including hospitalization.\124\
Hospitalization rates vary across dialysis facilities even after
adjustment for patient characteristics, suggesting that
hospitalizations might be influenced by dialysis facility practices. An
adjusted facility-level standardized hospitalization ratio, accounting
for differences in patients' characteristics, plays an important role
in identifying potential problems, and helps facilities provide cost-
effective quality health care to help limit escalating medical costs.
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\122\ United States Renal Data System. 2018 United States Renal
Data System annual data report: Epidemiology of kidney disease in
the United States. National Institutes of Health, National Institute
of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2018.
\123\ Ibid.
\124\ Office of the Assistant Secretary for Planning and
Evaluation, U.S. Department of Health & Human Services. Advancing
American Kidney Health. 2019. Available at: https://aspe.hhs.gov/system/files/pdf/262046/AdvancingAmericanKidneyHealth.pdf.
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In the CY 2017 ESRD PPS final rule, we finalized our proposal to
adopt the SHR clinical measure, which was a modified version of the
NQF-endorsed SHR clinical measure (NQF #1463), as part of the ESRD QIP
measure set (81 FR 77911). In that final rule, we stated that our
modified SHR clinical measure would incorporate 210 prevalent
comorbidities into our risk adjustment calculation, as our analyses
suggested that incorporating prevalent comorbidities would result in a
more robust and reliable measure of hospitalization (81 FR 77906
through 77907). In that final rule, we explained that data used to
calculate the SHR clinical measure are derived from an extensive
national ESRD patient database (81 FR 77908). We noted that the
database is comprehensive for Medicare Parts A and B patients, and that
non-Medicare patients are included in all sources except for the
Medicare payment records. In that final rule, we also stated that the
Standard Information Management System/CROWNWeb provides tracking by
dialysis provider and treatment modality for non-Medicare patients, and
information on hospitalizations and patient comorbidities are obtained
from Medicare Inpatient Claims Standard Analysis Files. In the CY 2019
ESRD PPS final rule, we increased the weight of the SHR clinical
measure from 8.25 percent to 14 percent of the TPS (83 FR 56992 through
56997).
On November 20, 2020, NQF completed its most recent review of the
SHR clinical measure, a measure maintenance review, and renewed the
measure's endorsement. As part of this review, the NQF endorsed
updating the prevalent comorbidity adjustment, which would group 210
individual ICD-9-CM prevalent comorbidities into 90 condition groups,
derived from the Agency for Healthcare Research and Quality (AHRQ)
Clinical Classifications Software (CCS) groups. The updated prevalent
comorbidity adjustment would also limit the source of prevalent
comorbidities to inpatient claims. The switch to using only Medicare
inpatient claims to identify prevalent comorbidities is due to the lack
of Medicare outpatient claims data for the growing Medicare Advantage
(MA) patient population. By using the original set of Medicare claims
datasets (inpatient, outpatient, hospice, skilled nursing, and home
health), the NQF stated its concern that MA patient prevalent
comorbidities would be systematically biased. These MA patient
prevalent comorbidities would only be populated by Medicare inpatient
claims, as compared to non-MA patient prevalent comorbidities that
would be populated by the aforementioned set of Medicare claim sources.
The updated NQF-endorsed SHR clinical measure would also include all
time at risk for MA patients, and added a MA indicator for adjustment
in the model. The NQF-endorsed specifications also included updates to
parameterization of existing adjustment factors and re-evaluation of
interactions, and also created three distinct groups of patients to use
in the SHR model based on time spent in a skilled nursing facility,
noting that nursing home residence is a marker of higher morbidity.
The updated SHR clinical measure was included on the publicly
available ``List of Measures under Consideration for December 21,
2020'' (MUC List), a list of measures under consideration for use in
various Medicare programs.\125\ When the Measure Applications
Partnership Hospital Workgroup convened on January 11, 2021, it
reviewed the MUC List, including the SHR clinical measure. The Measure
Applications Partnership Hospital Workgroup recognized that
hospitalization rates vary across dialysis facilities, even after
adjusting for patient characteristics, which suggests that
hospitalizations might be influenced by dialysis facility practices.
The Measure Applications Partnership Hospital Workgroup also noted that
the SHR clinical measure seeks to improve patient outcomes by measuring
hospitalization ratios among dialysis facilities, and that the measure
seeks to promote communication between the dialysis facilities and
other care settings to improve care transitions.\126\ In its final
report, the Measure Applications Partnership supported this measure for
rulemaking.\127\
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\125\ 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 29 2021.
\126\ Measure Applications Partnership. Measure Applications
Partnership Preliminary Recommendations 2020-2021. Accessed on
January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
\127\ Measure Applications Partnership. Measure Applications
Partnership 2020-2021: Considerations for Implementing Measures in
Federal Programs: Clinician, Hospital & PAC/LTC. Accessed on April
28, 2021 at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94893.
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In the CY 2022 ESRD PPS proposed rule (86 FR 36356), we proposed to
update the SHR clinical measure specifications to align with the NQF-
endorsed updates. These included updates to the risk adjustment method
of the measure, which include a prevalent comorbidity adjustment, the
addition of MA patients and a MA indicator in the model, updates to
parameterization of existing adjustment factors and re-evaluation of
interactions, and an indicator for a patient's time spent in a skilled
nursing facility.
In the proposed rule, we expressed our belief that adopting these
updates would be consistent with our stated goal of evaluating
opportunities to more closely align ESRD QIP measures with NQF measure
specifications (84 FR 60724). The SHR clinical measure seeks to improve
patient outcomes by measuring hospitalization ratios among dialysis
facilities, and we stated our belief that these updates would result in
a more reliable and robust SHR clinical measure.
We sought comment on this proposal to update the SHR clinical
measure
[[Page 61921]]
specifications for use in the ESRD QIP beginning with PY 2024. The
comments we received and our responses are set forth below.
Comment: A few commenters expressed support for the proposed
updates to the SHR clinical measure specifications. One commenter noted
that such updates are NQF-endorsed and supported by the MAP.
Response: We thank the commenters for their support.
Comment: A few commenters expressed concern regarding the proposed
updates to the risk adjustment method of the SHR clinical measure and
recommended that CMS perform a sensitivity analysis of the risk model
fit, comparing the prior risk model's outcomes with the updated risk
model's performance to assess the impact of the new approach.
Response: We are finalizing the proposed updates to the SHR
clinical measure because they are endorsed by the NQF and would align
the specifications of the SHR clinical measure with the NQF-endorsed
specifications. Although we are not bound by the NQF's decisions
regarding measure specifications, we believe that adopting these
updates is consistent with our stated goal of evaluating opportunities
to more closely align ESRD QIP measures with NQF measure specifications
(84 FR 60724). The updates to the SHR clinical measure were reviewed
and endorsed by NQF in 2020. As part of that NQF review, both the
current and proposed SHR risk adjustment model results were presented
in the Testing Forms and were available for discussion during the NQF
review process. In addition, the NQF review included comparisons of
both the prior and updated risk adjustment model performance for other
aspects of the Scientific Acceptability criteria (reliability and
validity). Both the NQF Methodology Panel and Admissions/Readmissions
Standing Committee had the opportunity to review the models'
performance (that is, the ``risk model fit'') on those and other
endorsement criteria prior to NQF's decision to endorse the proposed
model changes. Because the NQF review included an analysis of the risk
model's performance, we believe that the NQF review effectively
constituted a sensitivity review (that is, an analysis of the degree to
which the elements of the risk model contribute to the risk of
hospitalization) of the proposed specification changes, because it
compared all important criteria used by NQF between the prior and
proposed versions of SHR.
Comment: A few commenters expressed concern that the proposed
update to the comorbidity adjustment may skew the model toward a sicker
patient population, noting that the approach would result in
inaccurately low hospitalization rates leading to erroneously high
scores. One commenter expressed concern that this may be misleading to
patients and might disincentivize improvements that might actually
lower hospitalizations.
Response: We developed the proposed updated version of the SHR
clinical measure to directly correct a progressive bias related to our
prior definition of an ``active Medicare patient'' in the context of
the rapid increase in Medicare chronic dialysis patients with Medicare
Advantage coverage. In the prior version of the SHR clinical measure,
``active'' Medicare status was defined by ``use'' criteria. An
individual patient met our use criteria if they either had $900 or more
in paid Medicare outpatient dialysis claims or an acute inpatient
hospitalization. Either claims-based criterion conveyed active Medicare
status for purposes of the measure for the event month and two
consecutive following months. Nearly all Medicare fee-for-service
patients meet the use criterion of $900 paid claims for dialysis
because this amount reflects between 2 to 3 outpatient dialysis
treatments at current reimbursement rates. However, the only MA
patients meeting these use criteria were those hospitalized in the
year. As a result, the time at risk calculated in the old SHR clinical
measure underestimated the time at risk for MA patients because not all
are hospitalized in a year and virtually no MA patients meet the other
use criterion, due to CMS' lack of access to outpatient claims for MA
enrollees. The proposed updated version of the SHR clinical measure
currently utilizes Medicare's Enrollment Database to identify Medicare
Advantage patient status monthly. Combined with our patient-level
treatment history file, we are able to calculate true MA patient time
at risk at a given dialysis facility, without bias from the ``use''
test.
For the purposes of identifying co-morbidities from Medicare Claims
for risk adjustment, we use all inpatient claims in the prior calendar
year. We are able to obtain inpatient claims for both Medicare fee-for-
service patients as well as MA patients, as hospitals and other
inpatient providers furnish inpatient claims for MA patients to their
Medicare Administrative Contractors (MACs) for informational purposes.
For beneficiaries enrolled in Medicare Advantage, those inpatient
claims are often referred to as ``shadow'' claims, as they are not used
for direct billing. For Medicare Fee-for Service beneficiaries, we only
use paid inpatient claims. Unlike for Medicare fee-for-service
beneficiaries, CMS has virtually no access to outpatient claims for
Medicare Advantage beneficiaries. We no longer use outpatient claims
sources to identify co-morbidities, eliminating potential bias related
to the lack of access to outpatient claims for MA patients.
Identification of prevalent comorbidities based on only inpatient
claims results in fewer comorbidities for each patient compared to use
of the universe of Medicare claims. However, use of only inpatient
claims results in similar numbers and types of comorbidities for MA
patients and other Medicare patients. For instance, in an analysis of a
set of comorbidity groups used in a recent SRR calculation, we found
that inpatient claims identified 12 comorbid conditions for MA patients
on average compared to 12.4 comorbid conditions for other (non-MA)
Medicare patients.
In the revised SHR clinical measure, we use all available inpatient
claims in the prior calendar year for both Fee-For-Service (FFS) and MA
patients. While we agree that limiting co-morbidity ascertainment to
inpatient claims results in a less comprehensive set of co-morbidities,
our proposed updated risk-adjustment methodology protects against
potential bias in determining comorbidity burden due to differences in
our access to claims data for FFS and MA patients discussed above. As
the SHR clinical measure relies on use of inpatient claims to identify
co-morbidities in the prior calendar year, we expect that this lookback
period reflects more current conditions that are more likely to be
predictive of hospitalization risk. Therefore, we do not believe that
outpatient claim derived co-morbidities are as clinically relevant to
the risk-adjustment needed for the SHR clinical measure. Moreover, our
approach does not require us to exclude MA patients from the measures.
We do not want to eliminate a sizable percentage of the current
observations from the SHR clinical measure, particularly given the
anticipated growth of MA patients with diagnoses of ESRD that will
result from changes to the MA program regulations related to the
ability of prevalent ESRD patients to choose MA plans beginning in
2021, as finalized in the Medicare Program; Contract Year 2021 Policy
and Technical Changes to the Medicare Advantage Program, Medicare
Prescription Drug Benefit Program, and Medicare Cost Plan Program final
rule
[[Page 61922]]
(85 FR 33821 through 33824), which implemented provisions of the 21st
Century Cures Act to remove the prohibition on ESRD beneficiaries
enrolling in an MA plan.\128\ Finally, to account for potential
underlying co-morbidity differences between MA and FFS patients that
cannot be observed due to potentially incomplete claims-based
ascertainment of health status for MA patients, we included all time at
risk for Medicare Advantage patients and added a Medicare Advantage
indicator for adjustment in the model.
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\128\ The 21st Century Cures Act (Pub. L. 114-255) amended
sections 1851, 1852, and 1853 of the Act to expand enrollment
options for individuals with ESRD and make associated payment and
coverage changes to the MA and original Medicare programs.
Specifically, since the beginning of the MA program, individuals
with ESRD have not been able to enroll in MA plans subject to
limited exceptions. Section 17006(a) of the Cures Act removed this
prohibition effective for plan years beginning on or after January
1, 2021.
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Regarding the possibility that the SHR risk model changes described
above would increase model bias, we disagree and believe that the
concern that the revised model would bias the SHR toward sicker
patients is unfounded. First, we have discussed above the frequency of
inpatient claims diagnoses for FFS and MA patients under the new
approach. The average number of diagnoses reported from inpatient
claims for FFS and MA patients are very similar, strongly suggesting
that using only the inpatient claims source is an accurate reflection
of the comorbidities for both patient populations. The proposed SHR
risk model also includes a Medicare Advantage indicator variable in the
model that would guard against bias by minimizing the potential impact
of differences in unobserved comorbidities from outpatient claims
sources. Considering that the proposed model eliminates a sizeable
known bias related to the lack of data about outpatient claims for MA
patients, we believe the proposed SHR risk model provides a more
accurate representation of dialysis facility performance and,
therefore, utility to the dialysis community.
Comment: A few commenters expressed concern regarding the
parameterization modifications of existing adjustment factors included
in the proposed updates to the SHR clinical measure. Although a few
commenters agreed that the updated parameterization of existing
adjustment factors and reevaluation of interactions is important, they
expressed concern that the p-values, or calculated probability values,
of SHR risk models indicate that the model would not be generalizable.
Response: We believe that the proposed risk adjustment model, which
includes updates to the parameterization of existing adjustment factors
(that is, modifying the functional forms of adjustment factors) and re-
evaluation of interactions, is more appropriate because it captures all
Medicare patients. Since we are only using the SHR risk models for
purposes of the SHR clinical measure, we believe that generalizability
is not an issue.
Comment: One commenter requested that CMS indicate how Medicare
Advantage patients will be identified under the proposed SHR measure
specifications.
Response: Medicare Advantage patient status will be obtained from
the Medicare Enrollment Database (EDB). We will confirm the presence of
usable ICD diagnosis codes from MA inpatient claims.
Comment: A few commenters recommended that the ESRD QIP should use
true risk-standardized rate measures in order to more accurately
reflect facility performance, as the ratio measures have relatively
wide confidence intervals that can lead to facilities being
misclassified and their actual performance not being reported. One
commenter expressed the belief that a more direct, transparent, risk-
adjusted rate measure would result in more significant improvement,
noting that ESRD patient hospitalization rates have increased between
2016 and 2018 and questioned whether the SHR clinical measure has had a
meaningful impact.
Response: We believe that the use of a ratio is appropriate for the
SHR clinical measure. The ratio estimate that we proposed is the ratio
of the facility adjusted rate to the standard rate. The ratio is also a
scientifically valid approach, and ratio measures are well accepted in
the published literature. Additionally, the risk-adjustment approach
(which is based on application of a specific risk-adjustment model)
currently used for the SHR, SRR, and SWR measures leads naturally to a
standardized ratio, which compares the rate for this facility with the
national rate, having adjusted for the patient mix and is relatively
straightforward. We do not believe that rates are more direct and
transparent than ratios, and we disagree with the commenter who stated
that a risk-adjusted rate measure would lead to significant improvement
in performance on the SHR clinical measure. Like ratios, risk-adjusted
rates are not the same as actual rates and require a consideration of
the patient mix adjustment for interpretation. Furthermore, because the
indirect standardized rate is equal to the multiplication of the
indirect standardized ratio and a national rate, where the national
rate is a constant for all facilities, classifications of facilities
based on indirect standardized ratios and rates are equivalent.
Finally, we disagree that hospitalization rates have increased between
2016 and 2018. Hospitalization rates have decreased since 2015 as
evidenced by the negative coefficients for calendar year from the SHR
model. The hospitalization rate for 2016 decreased by 2.7 percent
compared to 2015 (p-value <0.0001). Subsequent years had a larger
decrease in the hospitalization rate compared to 2015 at 6.8 percent
lower for 2017 and about 5.7 percent lower for 2018 (p-value<0.0001 for
both) compared to 2015. Although 2018 had a slightly higher rate than
2017, there is an overall downward trend.
Final Rule Action: After considering public comments, we are
finalizing our proposal to update the SHR clinical measure
specifications for use in the ESRD QIP beginning with PY 2024.
2. Performance Standards for the PY 2024 ESRD QIP
Section 1881(h)(4)(A) of the Act requires the Secretary to
establish performance standards with respect to the measures selected
for the ESRD QIP for a performance period with respect to a year. The
performance standards must include levels of achievement and
improvement, as required by section 1881(h)(4)(B) of the Act, and must
be established prior to the beginning of the performance period for the
year involved, as required by section 1881(h)(4)(C) of the Act. We
refer readers to the CY 2013 ESRD PPS final rule (76 FR 70277) for a
discussion of the achievement and improvement standards that we have
established for clinical measures used in the ESRD QIP. We define the
terms ``achievement threshold,'' ``benchmark,'' ``improvement
threshold,'' and ``performance standard'' in our regulations at Sec.
413.178(a)(1), (3), (7), and (12), respectively.
a. Update to the Performance Standards Applicable to the PY 2024
Clinical Measures
Our current policy is to automatically adopt a performance and
baseline period for each year that is 1 year advanced from those
specified for the previous payment year (84 FR 60728). Under this
policy, CY 2022 is currently the performance period and CY 2020 is the
baseline period for the PY 2024 ESRD QIP. However, under the nationwide
ECE that we granted in
[[Page 61923]]
response to the COVID-19 PHE, first and second quarter data for CY 2020
are excluded from scoring for purposes of the ESRD QIP. In the CY 2022
ESRD PPS proposed rule (86 FR 36357), we stated that we were concerned
that it would be difficult to assess levels of achievement and
improvement if the performance standards were based on partial year
data.\129\ Our preliminary analysis indicated that the effect of the
excluded data would create higher performance standards for certain
measures and lower performance standards for other measures, which may
skew achievement and improvement thresholds for facilities and
therefore may result in performance standards that do not accurately
reflect levels of achievement and improvement.
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\129\ We note that for most ESRD QIP measures, this partial year
data would be measure data from July and August 2020.
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Our current policy substitutes the performance standard,
achievement threshold, and/or benchmark for a measure for a performance
year if final numerical values for the performance standard,
achievement threshold, and/or benchmark are worse than the numerical
values for that measure in the previous year of the ESRD QIP (82 FR
50764). We stated in the proposed rule that we adopted this policy
because we believe that the ESRD QIP should not have lower performance
standards than in previous years (86 FR 36357). However, our general
policy provides flexibility to substitute the performance standard,
achievement threshold, and benchmark in appropriate cases (82 FR
50764).
Although the lower performance standards would be substituted with
those from the prior year, the higher performance standards would be
used to set performance standards for certain measures, even though
they would be based on partial year data. In the proposed rule (86 FR
36357), we stated that we were concerned that this may create
performance standards for certain measures that would be difficult for
facilities to attain with a full 12 months of data.
Therefore, in the CY 2022 ESRD PPS proposed rule (86 FR 36357), we
proposed to calculate the performance standards for PY 2024 using CY
2019 data, which are the most recently available full calendar year of
data we can use to calculate those standards. Due to the impact of CY
2020 data that are excluded from the ESRD QIP for scoring purposes, we
stated our belief that using CY 2019 data for performance standard
setting purposes is appropriate. Consistent with our established
policy, we would continue to use the prior year's numerical values for
performance standard, achievement threshold, and benchmark if the most
recent full CY's final numerical values are worse.
We welcomed public comments on this proposal. The comments we
received and our responses are set forth below.
Comment: Several commenters expressed support for the proposed use
of CY 2019 data for calculating performance standards, achievement
thresholds, and benchmarks for PY 2024. A few commenters noted that the
significant impact of the COVID-19 PHE would make CY 2020 measure data
inappropriate for setting PY 2024 performance standards. A few
commenters supported the proposal because CY 2019 is the most recently
available full calendar year of data.
Response: We thank the commenters for their support.
Comment: One commenter expressed concern with the proposed use of
CY 2019 data for calculating performance standards, achievement
thresholds, and benchmarks for PY 2024, noting that the ongoing COVID-
19 PHE continues to impact measure performance and that using CY 2019
as a pre-pandemic baseline for setting performance standards may
unfairly penalize facilities.
Response: We acknowledge the commenter's concern regarding the
ongoing impact of the COVID-19 PHE, but disagree that using CY 2019
data for calculating performance standards will unfairly penalize
facilities. We note that, due to the nationwide ECE granted in response
to the COVID-19 PHE that excluded first and second quarter data from CY
2020, only 6 months of CY 2020 data would be used to calculate
performance standards, achievement thresholds, and benchmarks for PY
2024. We believe that there is a greater risk of unfairly penalizing
facilities based on performance standards calculated using only 6
months of CY 2020 data, as our preliminary analysis indicated that the
effect of the excluded data would create higher performance standards
for certain measures and lower performance standards for other measures
which may not accurately reflect levels of achievement and improvement.
Comment: One commenter expressed concern that the proposed update
only addresses achievement scores, and requested that CMS clarify what
year improvement scores will be based on.
Response: We proposed to use CY 2019 data to calculate all
performance standards for PY 2024, including achievement and
improvement thresholds. This is consistent with the definition of
``performance standards'' codified at 42 CFR 413.178(a)(12), which
includes all of the performance levels used to award points to a
facility. Therefore, the improvement scores will be calculated using CY
2019 as the baseline year.
Final Rule Action: After considering public comments, we are
finalizing our proposal to calculate the performance standards for PY
2024 using CY 2019 data.
b. Finalized Performance Standards for the PY 2024 ESRD QIP
Table 3 displays the achievement thresholds, 50th percentiles of
the national performance, and benchmarks for the PY 2024 clinical
measures, and in the proposed rule we stated that we would use these
standards if our proposal to use CY 2019 as the baseline period is
finalized (86 FR 36357). As discussed in IV.E.2.a. of this final rule,
we are finalizing our proposal to calculate the performance standards
for the PY 2024 ESRD QIP using CY 2019 data.
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In addition, we summarize in Table 4 existing requirements for
successful reporting on reporting measures in the PY 2024 ESRD QIP. We
did not make any proposals to change these standards as a result of the
COVID-19 PHE.
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3. Eligibility Requirements for the PY 2024 ESRD QIP
Our current minimum eligibility requirements for scoring the ESRD
QIP measures are described in Table 5.
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4. Payment Reduction Scale for the PY 2024 ESRD QIP
Under our current policy, a facility will not receive a payment
reduction for a payment year in connection with its performance for the
ESRD QIP if it achieves a TPS that is at or above the minimum TPS
(mTPS) that we establish for the payment year. We have defined the mTPS
in our regulations at Sec. 413.178(a)(8) as, with respect to a payment
year, the TPS that an ESRD facility would receive if, during the
baseline period it performed at the 50th percentile of national
performance on all clinical measures and the median of national ESRD
facility performance on all reporting measures.
Our current policy, which is codified at Sec. 413.177 of our
regulations, also implements the payment reductions on a sliding scale
using ranges that reflect payment reduction differentials of 0.5
percent for each 10 points that the facility's TPS falls below the mTPS
(76 FR 634 through 635).
For PY 2024, based on available data, a facility must meet or
exceed a mTPS of 57 in order to avoid a payment reduction. We note that
the mTPS in this final rule is based on data from CY 2019 because we
are finalizing our proposal to calculate the performance standards
using CY 2019 data.
We refer readers to Table 3 of this final rule for the finalized
values of the 50th percentile of national performance for each clinical
measure. We stated in the CY 2022 ESRD PPS proposed rule that under our
current policy, a facility that achieves a TPS of 56 or below would
receive a payment reduction based on the TPS ranges indicated in Table
6 (86 FR 36360 through 36361). Table 6 of this final rule is a
reproduction of Table 6 from the CY 2022 ESRD PPS proposed rule without
any changes.
[[Page 61927]]
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In the CY 2022 ESRD PPS proposed rule (86 FR 36361), we stated that
if we did not finalize the proposed update to our performance standards
policy as described in the proposed rule (86 FR 36357), then we would
update the mTPS for PY 2024, as well as the payment reduction ranges
for that payment year, in the CY 2022 ESRD PPS final rule using data
from CY 2020. However, as discussed in section IV.E.2.a. of this final
rule, we are finalizing as proposed the update to our performance
standards for PY 2024, and therefore we will use the mTPS and payment
reduction ranges for PY 2024 that are described in Table 6.
F. Updates for the PY 2025 ESRD QIP
1. Continuing Measures for the PY 2025 ESRD QIP
Under our previously adopted policy, the PY 2024 ESRD QIP measure
set will also be used for PY 2025. We did not propose to adopt any new
measures beginning with the PY 2025 ESRD QIP.
2. Performance Period for the PY 2025 ESRD QIP
We continue to believe that 12-month performance and baseline
periods provide us sufficiently reliable quality measure data for the
ESRD QIP. Under this policy, we would adopt CY 2023 as the performance
period and CY 2021 as the baseline period for the PY 2025 ESRD QIP.
We did not propose any changes to this policy.
3. Performance Standards for the PY 2025 ESRD QIP
Section 1881(h)(4)(A) of the Act requires the Secretary to
establish performance standards with respect to the measures selected
for the ESRD QIP for a performance period with respect to a year. The
performance standards must include levels of achievement and
improvement, as required by section 1881(h)(4)(B) of the Act, and must
be established prior to the beginning of the performance period for the
year involved, as required by section 1881(h)(4)(C) of the Act. We
refer readers to the CY 2012 ESRD PPS final rule (76 FR 70277) for a
discussion of the achievement and improvement standards that we have
established for clinical measures used in the ESRD QIP. We define the
terms ``achievement threshold,'' ``benchmark,'' ``improvement
threshold,'' and ``performance standard'' in our regulations at Sec.
413.178(a)(1), (3), (7), and (12), respectively. In section IV.E.2.a.
of this final rule, we note that we are finalizing our proposal to use
CY 2019 data for purposes of calculating the performance standards for
PY 2024 because, due to the anticipated impact of CY 2020 data that is
excluded from the ESRD QIP for scoring purposes during CY 2020, we
believe that using CY 2019 data for performance standard setting
purposes would be appropriate.
a. Performance Standards for Clinical Measures in the PY 2025 ESRD QIP
At this time, we do not have the necessary data to assign numerical
values to the achievement thresholds, benchmarks, and 50th percentiles
of national performance for the clinical measures for the PY 2025 ESRD
QIP because we do not have CY 2021 data. We intend to publish these
numerical values, using CY 2021 data, in the CY 2023 ESRD PPS final
rule.
b. Performance Standards for the Reporting Measures in the PY 2025 ESRD
QIP
In the CY 2019 ESRD PPS final rule, we finalized the continued use
of existing performance standards for the Screening for Clinical
Depression and Follow-Up reporting measure, the Ultrafiltration Rate
reporting measure, the NHSN Dialysis Event reporting measure, and the
MedRec reporting measure (83 FR 57010 through 57011). In the CY 2022
ESRD PPS proposed rule (86 FR 36361), we stated that we will continue
use of these performance standards in PY 2025.
4. Scoring the PY 2025 ESRD QIP
a. Scoring Facility Performance on Clinical Measures
In the CY 2014 ESRD PPS final rule, we finalized policies for
scoring performance on clinical measures based on achievement and
improvement (78 FR 72215 through 72216). In the CY 2019 ESRD PPS final
rule, we finalized a policy to continue use of this methodology for
future payment years (83 FR 57011) and we codified these scoring
policies at Sec. 413.178(e).
We did not propose any changes to this policy for PY 2025.
b. Scoring Facility Performance on Reporting Measures
Our policy for scoring performance on reporting measures is
codified at Sec. 413.178(e), and more information on our scoring
policy for reporting measures can be found in the CY 2020 ESRD PPS
final rule (84 FR 60728). We previously finalized policies for scoring
performance on the NHSN Dialysis Event reporting measure in the CY 2018
ESRD PPS final rule (82 FR 50780 through 50781), as well as policies
for scoring the MedRec reporting measure and Clinical Depression
Screening and Follow-up reporting measure in the CY 2019 ESRD PPS final
rule (83 FR 57011). We also previously finalized the scoring policy for
the STrR reporting measure in the CY 2020 ESRD PPS final rule (84 FR
60721 through 60723). In the CY 2021 ESRD PPS final rule, we finalized
our updated scoring methodology for the Ultrafiltration Rate reporting
measure (85 FR 71468 through 71470).
We did not propose any changes to these policies for PY 2025.
[[Page 61928]]
5. Weighting the Measure Domains and the TPS for PY 2025
Under our current policy, we assign the Patient & Family Engagement
Measure Domain a weight of 15 percent of the TPS, the Care Coordination
Measure Domain a weight of 30 percent of the TPS, the Clinical Care
Measure Domain a weight of 40 percent of the TPS, and the Safety
Measure domain a weight of 15 percent of the TPS.
In the CY 2019 ESRD PPS final rule, we finalized a policy to assign
weights to individual measures and a policy to redistribute the weight
of unscored measures (83 FR 57011 through 57012). In the CY 2020 ESRD
PPS final rule, we finalized a policy to use the measure weights we
finalized for PY 2022 for the PY 2023 ESRD QIP and subsequent payment
years, and also to use the PY 2022 measure weight redistribution policy
for the PY 2023 ESRD QIP and subsequent payment years (84 FR 60728
through 60729). We did not propose any updates to these policies for PY
2025.
G. Requests for Information (RFIs) on Topics Relevant to ESRD QIP
1. Closing the Health Equity Gap in CMS Quality Programs Request for
Information
Persistent inequities in health care outcomes exist in the United
States (U.S.), including among Medicare patients. In recognition of
persistent health disparities and the importance of closing the health
equity gap, in the CY 2022 ESRD PPS proposed rule we requested
information on expanding several related CMS programs to make reporting
of health disparities based on social risk factors and race and
ethnicity, and disability more comprehensive and actionable for
dialysis facilities, providers, and patients (86 FR 36362 through
36369). The RFI that was included in the proposed rule is part of an
ongoing effort across CMS to evaluate appropriate initiatives to reduce
health disparities. Feedback will be used to inform the creation of a
future, comprehensive, RFI focused on closing the health equity gap in
CMS programs and policies. This RFI contained four parts:
Background. This section provided information on existing
statements describing our commitment to health equity, and existing
initiatives with an emphasis on reducing disparity.
Current CMS Disparity Methods. This section described the
methods, measures, and indicators of social risk currently used with
the CMS Disparity Methods.
Future potential stratification of quality measure
results. This section described four potential future expansions of the
CMS Disparity Methods, including (a) Future potential stratification of
quality measure results by dual eligibility; (b) Future potential
stratification of quality measure results by race and ethnicity; (c)
Improving Demographic Data Collection; and (d) Potential Creation of an
ESRD Facility Equity Score to Synthesize Results Across Multiple Social
Risk Factors.
Solicitation of public comment. This section specified 11
requests for feedback on these topics. We reviewed feedback on these
topics and note our intention for an additional RFI or rulemaking on
this topic in the future.
a. Background
Significant and persistent inequities in health care outcomes exist
in the U.S.\130\ Belonging to a racial or ethnic minority group, living
with a disability, being a member of the lesbian, gay, bisexual,
transgender, and queer (LGBTQ+) community, living in a rural area, or
being near or below the poverty level, is often associated with worse
health outcomes.131 132 133 134 135 136 137 138 Such
disparities in health outcomes are the result of number of factors, but
importantly for CMS programs, although not the sole determinant, poor
access and provision of lower quality health care contribute to health
disparities. For instance, numerous studies have shown that among
Medicare beneficiaries, racial and ethnic minority individuals often
receive lower quality of care, report lower experiences of care, and
experience more frequent hospital readmissions and operative
complications.139 140 141 142 143 144 Readmission rates for
common conditions in the Hospital Readmissions Reduction Program are
higher for Black Medicare beneficiaries and higher for Hispanic
Medicare beneficiaries with Congestive Heart Failure and Acute
Myocardial Infarction.145 146 147 148 149 Although Black
Americans represent 7.5 percent of all older adult Medicare
beneficiaries, they represent 28 percent of those with ESRD.\150\ Among
individuals with ESRD the odds of 30-day hospital readmission are 19
percent higher for Black beneficiaries as compared with white
beneficiaries.\151\ Studies have also shown that African Americans are
significantly more likely than white Americans to die prematurely from
heart disease and
[[Page 61929]]
stroke.\152\ The COVID-19 pandemic has further illustrated many of
these longstanding health inequities with higher rates of infection,
hospitalization, and mortality among Black, Latino, and Indigenous and
Native American persons relative to white persons.\153\ \154\ In the
ESRD patient population, one study found that the rate of COVID-19
hospitalizations among dialysis patients peaked at 40 times higher than
the rate in the general population during the pandemic, with Black,
Latino, and Asian persons hospitalized at a higher rate than white
persons.\155\ As noted by the Centers for Disease Control and
Prevention, ``long-standing systemic health and social inequities have
put many people from racial and ethnic minority groups at increased
risk of getting sick and dying from COVID-19.''\156\ One important
strategy for addressing these important inequities is by improving data
collection to allow for better measurement and reporting on equity
across our programs and policies.
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\130\ United States Department of Health and Human Services.
``Healthy People 2020: Disparities. 2014.'' Available at: https://www.healthypeople.gov/2020/about/foundation-health-measures/Disparities.
\131\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for
Medicare Beneficiaries by Race and Site of Care. JAMA.
2011;305(7):675-681.
\132\ Lindenauer PK, Lagu T, Rothberg MB, et al. Income
Inequality and 30 Day Outcomes After Acute Myocardial Infarction,
Heart Failure, and Pneumonia: Retrospective Cohort Study. British
Medical Journal. 2013;346.
\133\ Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and Equity
of Care in U.S. Hospitals. New England Journal of Medicine.
2014;371(24):2298-2308.
\134\ Polyakova, M., et al. Racial Disparities In Excess All-
Cause Mortality During The Early COVID-19 Pandemic Varied
Substantially Across States. Health Affairs. 2021; 40(2): 307-316.
\135\ Rural Health Research Gateway. Rural Communities: Age,
Income, and Health Status. Rural Health Research Recap. November
2018.
\136\ Polyakova, M., et al. Racial Disparities In Excess All-
Cause Mortality During The Early COVID-19 Pandemic Varied
Substantially Across States. Health Affairs. 2021; 40(2): 307-316.
\137\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
\138\ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7386532/.
\139\ Martino, SC, Elliott, MN, Dembosky, JW, Hambarsoomian, K,
Burkhart, Q, Klein, DJ, Gildner, J, and Haviland, AM. Racial,
Ethnic, and Gender Disparities in Health Care in Medicare Advantage.
Baltimore, MD: CMS Office of Minority Health. 2020.
\140\ Guide to Reducing Disparities in Readmissions. CMS Office
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
\141\ Singh JA, Lu X, Rosenthal GE, Ibrahim S, Cram P. Racial
disparities in knee and hip total joint arthroplasty: An 18-year
analysis of national Medicare data. Ann Rheum Dis. 2014
Dec;73(12):2107-15.
\142\ Rivera-Hernandez M, Rahman M, Mor V, Trivedi AN. Racial
Disparities in Readmission Rates among Patients Discharged to
Skilled Nursing Facilities. J Am Geriatr Soc. 2019 Aug;67(8):1672-
1679.
\143\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for
Medicare Beneficiaries by Race and Site of Care. JAMA.
2011;305(7):675-681.
\144\ Tsai TC, Orav EJ, Joynt KE. Disparities in surgical 30-day
readmission rates for Medicare beneficiaries by race and site of
care. Ann Surg. Jun 2014;259(6):1086-1090.
\145\ Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha AK.
Readmission rates for Hispanic Medicare beneficiaries with heart
failure and acute myocardial infarction. Am Heart J. Aug
2011;162(2):254-261 e253.
\146\ Centers for Medicare and Medicaid Services. Medicare
Hospital Quality Chartbook: Performance Report on Outcome Measures;
2014.
\147\ Guide to Reducing Disparities in Readmissions. CMS Office
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
\148\ Prieto-Centurion V, Gussin HA, Rolle AJ, Krishnan JA.
Chronic obstructive pulmonary disease readmissions at minority-
serving institutions. Ann Am Thorac Soc. Dec 2013;10(6):680-684.
\149\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for
Medicare Beneficiaries by Race and Site of Care. JAMA.
2011;305(7):675-681.
\150\ https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/ESRD-Infographic.pdf.
\151\ Ibid.
\152\ HHS. Heart disease and African Americans. (March 29,
2021). https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
\153\ https://www.cms.gov/files/document/medicare-covid-19-data-snapshot-fact-sheet.pdf.
\154\ Ochieng N, Cubanski J, Neuman T, Artiga S, and Damico A.
Racial and Ethnic Health Inequities and Medicare. Kaiser Family
Foundation. February 2021. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/.
\155\ Weinhandl ED, Wetmore, JB, Peng Y, et al. Initial effects
of COVID-19 on patients with ESKD. J Am Soc Nephrol. Published
online April 8, 2021.doi:10.1681/ASN.2021010009.
\156\ https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
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We are committed to achieving equity in health care outcomes for
our beneficiaries by supporting providers in quality improvement
activities to reduce health inequities, enabling them to make more
informed decisions, and promoting provider accountability for health
care disparities.\157\ For the purposes of this rule, we are using a
definition of equity established in Executive Order 13985, as ``the
consistent and systematic fair, just, and impartial treatment of all
individuals, including individuals who belong to underserved
communities that have been denied such treatment, such as Black,
Latino, and Indigenous and Native American persons, Asian Americans and
Pacific Islanders and other persons of color; members of religious
minorities; lesbian, gay, bisexual, transgender, and queer (LGBTQ+)
persons; persons with disabilities; persons who live in rural areas;
and persons otherwise adversely affected by persistent poverty or
inequality.'' \158\ We note that this definition was recently
established by the Biden administration, and provides a useful, common
definition for equity across different areas of government, although
numerous other definitions of equity exist.
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\157\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
\158\ https://www.federalregister.gov/documents/2021/01/25/2021-01753/advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government.
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Our ongoing commitment to closing the equity gap in CMS quality
programs is demonstrated by a portfolio of programs aimed at making
information on the quality of health care providers and services,
including disparities, more transparent to consumers and providers. The
CMS Equity Plan for Improving Quality in Medicare outlines a path to
equity which aims to support Quality Improvement Networks and Quality
Improvement Organizations (QIN-QIOs); Federal, State, local, and tribal
organizations; providers; researchers; policymakers; beneficiaries and
their families; and other stakeholders in activities to achieve health
equity.\159\ The CMS Equity Plan for Improving Quality in Medicare
focuses on three core priority areas which inform our policies and
programs: (1) Increasing understanding and awareness of disparities;
(2) developing and disseminating solutions to achieve health equity;
and (3) implementing sustainable actions to achieve health equity.\160\
The CMS Quality Strategy \161\ and Meaningful Measures Framework \162\
include elimination of racial and ethnic disparities as a central
principle. Our efforts aimed at closing the health equity gap to date
have included both providing transparency of health disparities,
supporting providers with evidence-informed solutions to achieve health
equity, and reporting to providers on gaps in quality in the following:
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\159\ Centers for Medicare & Medicaid Services Office of
Minority Health. The CMS Equity Plan for Improving Quality in
Medicare. 2015. https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
\160\ Centers for Medicare & Medicaid Services Office of
Minority Health. Paving The Way To Equity: A Progress Report. 2015-
2021. https://www.cms.gov/files/document/paving-way-equity-cms-omh-progress-report.pdf.
\161\ Centers for Medicare & Medicaid Services. CMS Quality
Strategy. 2016. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
\162\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
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The CMS Mapping Medicare Disparities Tool which is an
interactive map that identifies areas of disparities and is a starting
point to understand and investigate geographic, racial and ethnic
differences in health outcomes for Medicare patients.\163\
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\163\ https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH-Mapping-Medicare-Disparities.
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The Racial, Ethnic, and Gender Disparities in Health Care
in Medicare Advantage Stratified Report, which highlights racial and
ethnic differences in health care experiences and clinical care,
compares quality of care for women and men, and looks at racial and
ethnic differences in quality of care among women and men separately
for Medicare Advantage plans.\164\
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\164\ https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
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The Rural-Urban Disparities in Health Care in Medicare
Report which details rural-urban differences in health care experiences
and clinical care.\165\
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\165\ Centers for Medicare & Medicaid Services. Rural-Urban
Disparities in Health Care in Medicare. 2019. https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Rural-Urban-Disparities-in-Health-Care-in-Medicare-Report.pdf.
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The Standardized Patient Assessment Data Elements for
certain post-acute care Quality Reporting Programs, which now includes
data reporting for race and ethnicity and preferred language, in
addition to screening questions for social needs (84 FR 42536 through
42588).
The CMS Innovation Center's Accountable Health Communities
Model which includes standardized collection of health-related social
needs data.
The Guide to Reducing Disparities which provides an
overview of key issues related to disparities in readmissions and
reviews set of activities that can help hospital leaders reduce
readmissions in diverse populations.\166\
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\166\ Guide to Reducing Disparities in Readmissions. CMS Office
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
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The Chronic Kidney Disease Disparities: Educational Guide
for Primary Care, which is intended to foster the development of
primary care practice teams in order to enhance care for vulnerable
patients with chronic kidney disease (CKD) and are at risk of
progression of disease or complications. The guide provides information
about disparities in the care of patients with CKD, presents potential
actions that
[[Page 61930]]
may improve care, and suggests other available resources that may be
used by primary care practice teams in caring for vulnerable
patients.\167\
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\167\ CMS. Chronic Kidney Disease Disparities: Educational Guide
for Primary Care. February 2020. Available at: https://www.cms.gov/files/document/chronic-kidney-disease-disparities-educational-guide-primary-care.pdf.
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The CMS Disparity Methods which provide hospital-level
confidential results stratified by dual eligibility for condition-
specific readmission measures currently included in the Hospital
Readmissions Reduction Program (see 84 FR 42496 through 42500 for a
discussion of using stratified data in additional measures).
These programs are informed by reports by the National Academies of
Science, Engineering and Medicine (NASEM) \168\ and the Office of the
Assistant Secretary for Planning and Evaluation (ASPE) \169\ which have
examined the influence of social risk factors on several of our quality
programs. In this request for public comment, we addressed only the
eighth initiative listed above, the CMS Disparity Methods, which we
have implemented for measures in the Hospital Readmissions Reduction
Program and are considering in other programs, including the ESRD QIP.
We discussed the implementation of these methods to date and presented
considerations for continuing to improve and expand these methods to
provide providers and ultimately consumers with actionable information
on disparities in health care quality to support efforts at closing the
equity gap.
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\168\ National Academies of Sciences, Engineering, and Medicine.
2016. Accounting for Social Risk Factors in Medicare Payment:
Identifying Social Risk Factors. Washington, DC: The National
Academies Press. https://doi.org/10.17226/21858.
\169\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
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b. Current CMS Disparity Methods
We first sought public comment on potential confidential and public
reporting of ESRD QIP measure data stratified by social risk factors in
the CY 2018 ESRD PPS proposed rule (82 FR 31202). We initially focused
on stratification by dual eligibility, which is consistent with
recommendations from ASPE's First Report to Congress which was required
by the Improving Medicare Post-Acute Care Transformation (IMPACT) Act
of 2014 (Pub. L. 113-185).\170\ This report found that in the context
of value-based purchasing (VBP) programs, dual eligibility was among
the most powerful predictors of poor health outcomes among those social
risk factors that ASPE examined and tested.
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\170\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
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In the FY 2018 IPPS/LTCH PPS final rule, we also solicited feedback
on two potential methods for illuminating differences in outcomes rates
among patient groups within a provider's patient population that would
also allow for a comparison of those differences, or disparities,
across providers for the Hospital IQR Program (82 FR 38403 through
38409). The first method (the Within-Hospital disparity method)
promotes quality improvement by calculating differences in outcome
rates among patient groups within a hospital while accounting for their
clinical risk factors. This method also allows for a comparison of the
magnitude of disparity across hospitals, so hospitals could assess how
well they are closing disparity gaps compared to other hospitals. The
second methodological approach (the Across-Hospital method) is
complementary and assesses hospitals' outcome rates for dual-eligible
patients only, across hospitals, allowing for a comparison among
hospitals on their performance caring for their patients with social
risk factors. In the CY 2018 ESRD PPS proposed rule (82 FR 31202
through 31203), we also specifically solicited feedback on which social
risk factors provide the most valuable information to stakeholders. In
addition, feedback was solicited on the methodology for illuminating
differences in outcomes rates among patient groups within a provider's
patient population that would also allow for a comparison of those
differences, or disparities, across providers. Overall, comments
supported the use of dual eligibility as a proxy for social risk,
although commenters also suggested investigation of additional social
risk factors, and we continue to consider commenter suggestions for
which risk factors provide the most valuable information to
stakeholders.
c. Future Potential Expansion of the CMS Disparity Methods to the ESRD
QIP
We are committed to advancing health equity by improving data
collection to better measure and analyze disparities across programs
and policies.\171\ As we previously noted, we have been considering,
among other things, expanding our efforts to provide stratified data
for additional social risk factors and measures, optimizing the ease-
of-use of the results, enhancing public transparency of equity results,
and building towards provider accountability for health equity. We
sought public comment on the potential stratification of quality
measures in the ESRD QIP across two social risk factors: dual
eligibility and race/ethnicity.
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\171\ Centers for Medicare & Medicaid Services. CMS Quality
Strategy. 2016. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
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(1) Stratification of Quality Measure Results--Dual Eligibility
As described in the previous section, landmark reports by NASEM
\172\ and ASPE,\173\ which have examined the influence of social risk
factors on several of our quality programs, have shown that in the
context of VBP programs, dual eligibility, as an indicator of social
risk, is a powerful predictor of poor health outcomes. We are
considering stratification of quality measure results in the ESRD QIP
and are considering which measures would be most appropriate for
stratification and if dual eligibility would be a meaningful social
risk factor for stratification.
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\172\ National Academies of Sciences, Engineering, and Medicine.
2016. Accounting for Social Risk Factors in Medicare Payment:
Identifying Social Risk Factors. Washington, DC: The National
Academies Press. https://doi.org/10.17226/21858.
\173\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
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For the ESRD QIP, we would consider disparity reporting using two
disparity methods derived from the Within-Facility and Across-Facility
methods. The first method (based on the Within-Hospital disparity
method, described previously) would aim to promote quality improvement
by calculating differences in outcome rates between dual and non-dual
eligible patient groups within a facility while accounting for their
clinical risk factors. This method would allow for a comparison of
those differences, or disparities, across facilities, so facilities
could assess how well they are closing disparity gaps compared to other
facilities. The second approach (based on the Across-Hospital method)
would be complementary and assesses facilities' outcome rates for
subgroups of patients, such as dual eligible patients, across
facilities, allowing for a comparison among facilities on their
performance caring for their patients with social risk factors.
(2) Stratification of Quality Measure Results--Race and Ethnicity
The Administration's Executive Order on Advancing Racial Equity and
Support for Underserved Communities
[[Page 61931]]
Through the Federal Government directs agencies to assess potential
barriers that underserved communities and individuals may face to
enrollment in and access to benefits and services in Federal programs.
As summarized earlier in the preamble, studies have shown that among
Medicare beneficiaries, racial and ethnic minority persons often
experience worse health outcomes, including more frequent hospital
readmissions and procedural complications.\174\ We also note that the
prevalence of ESRD is higher among racial minorities.\175\ For example,
in 2016 ESRD prevalence was approximately 9.5 times greater in Native
Hawaiians and Pacific Islanders, 3.7 times greater in African
Americans, 1.5 times greater in American Indians and Alaska Natives,
and 1.3 times greater in Asians.\176\ An important part of identifying
and addressing inequities in health care is improving data collection
to allow us to better measure and report on equity across our programs
and policies. We are considering stratification of quality measure
results in the ESRD QIP by race and ethnicity, and are identifying
which measures would be most appropriate for stratification.
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\174\ https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/.
\175\ United States Renal Data System. 2018 Annual Data Report:
ESRD Incidence, Prevalence, Patient Characteristics, and Treatment
Modalities. Available online at https://www.usrds.org/2018/view/Default.aspx.
\176\ United States Renal Data System. 2018 Annual Data Report,
Vol 2, Figure 1.12. Available online at https://www.usrds.org/2018/view/Default.aspx.
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As outlined in the 1997 Office of Management and Budget (OMB)
Revisions to the Standards for the Collection of Federal Data on Race
and Ethnicity, the racial and ethnic categories which may be used for
reporting the disparity methods are considered to be social and
cultural, not biological or genetic.\177\ The 1997 OMB Standard lists
five minimum categories of race: (1) American Indian or Alaska Native;
(2) Asian; (3) Black or African American; (4) Native Hawaiian or Other
Pacific Islander; (5) and White. In the OMB standards, Hispanic or
Latino is the only ethnicity category included, and since race and
ethnicity are two separate and distinct concepts, persons who report
themselves as Hispanic or Latino can be of any race.\178\ Another
example, the ``Race & Ethnicity--CDC'' code system in Public Health
Information Network (PHIN) Vocabulary Access and Distribution Systems
(VADS) \179\ permits a much more granular structured recording of a
patient's race and ethnicity with its inclusion of over 900 concepts
for race and ethnicity. The recording and exchange of patient race and
ethnicity at such a granular level can facilitate the accurate
identification and analysis of health disparities based on race and
ethnicity. Further, the ``Race & Ethnicity--CDC'' code system has a
hierarchy that rolls up to the OMB minimum categories for race and
ethnicity and, thus, supports aggregation and reporting using the OMB
standard. The Office of the National Coordinator for Health Information
Technology (ONC) includes both the CDC and OMB standards in its
criterion for certified health IT products.\180\ For race and
ethnicity, a certified health IT product must be able to express both
detailed races and ethnicities using any of the 900 plus concepts in
the ``Race & Ethnicity--CDC'' code system in PHIN VADS, as well as
aggregate each one of a patient's races and ethnicities to the
categories in the OMB standard for race and ethnicity. This approach
can reduce burden on providers recording demographics using certified
products.
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\177\ Executive Office of the President Office of Management and
Budget, Office of Information and Regulatory Affairs. Revisions to
the standards for the classification of federal data on race and
ethnicity. Vol 62. Federal Register. 1997:58782-58790.
\178\ https://www.census.gov/topics/population/hispanic-origin/about.html.
\179\ https://phinvads.cdc.gov/vads/ViewValueSet.action?id=67D34BBC-617F-DD11-B38D-00188B398520.
\180\ ONC criteria for certified health IT products: https://www.healthit.gov/isa/representing-patient-race-and-ethnicity.
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Self-reported race and ethnicity data remain the gold standard for
classifying an individual according to race or ethnicity. However,
historical inaccuracies in Federal data systems and limited collection
classifications have contributed to the limited quality of race and
ethnicity information in our administrative data systems.\181\ In
recent decades, to address these data quality issues, we have
undertaken numerous initiatives, including updating data taxonomies and
conducting direct mailings to some beneficiaries to enable more
comprehensive race and ethnic identification.\182\ \183\ Despite those
efforts, studies reveal varying data accuracy in identification of
racial and ethnic groups in Medicare administrative data, with higher
sensitivity for correctly identifying white and Black individuals, and
lower sensitivity for correctly identifying individuals of Hispanic
ethnicity or of Asian/Pacific Islander and American Indian/Alaskan
Native race.\184\ Incorrectly classified race or ethnicity may result
in overestimation or underestimation in the quality of care received by
certain groups of beneficiaries.
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\181\ Eicheldinger, C., & Bonito, A. (2008). More accurate
racial and ethnic codes for Medicare administrative data. Health
Care Financing Review, 29(3), 27-42.
\182\ Filice CE, Joynt KE. Examining Race and Ethnicity
Information in Medicare Administrative Data. Med Care.
2017;55(12):e170-e176. doi:10.1097/MLR.0000000000000608.
\183\ Eicheldinger, C., & Bonito, A. (2008). More accurate
racial and ethnic codes for Medicare administrative data. Health
Care Financing Review, 29(3), 27-42.
\184\ Centers for Medicare & Medicaid Services. Building an
Organizational Response to Health Disparities Inventory of Resources
for Standardized Demographic and Language Data Collection. 2020.
https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
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We continue to work with public and private partners to better
collect and leverage data on social risk to improve our understanding
of how these factors can be better measured in order to close the
health equity gap. Among other things, we have developed an Inventory
of Resources for Standardized Demographic and Language Data Collection
\185\ and supported collection of specialized International
Classification of Disease, 10th Edition, Clinical Modification (ICD-10-
CM) codes for describing the socioeconomic, cultural, and environmental
determinants of health, and sponsored several initiatives to
statistically estimate race and ethnicity information when it is
absent.\186\
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\185\ Centers for Medicare & Medicaid Services. Building an
Organizational Response to Health Disparities Inventory of Resources
for Standardized Demographic and Language Data Collection. 2020.
https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
\186\ https://pubmed.ncbi.nlm.nih.gov/18567241/, https://pubmed.ncbi.nlm.nih.gov/30506674/, Eicheldinger C, Bonito A. More
accurate racial and ethnic codes for Medicare administrative data.
Health Care Finance Rev. 2008;29(3):27-42. Haas A, Elliott MN,
Dembosky JW, et al. Imputation of race/ethnicity to enable
measurement of HEDIS performance by race/ethnicity. Health Serv Res.
2019;54(1):13-23. doi:10.1111/1475-6773.13099.
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ONC included social, psychological, and behavioral standards in the
2015 Edition health information technology certification criteria (2015
Edition), providing interoperability standards LOINC (Logical
Observation Identifiers Names and Codes) and SNOMED CT (Systematized
Nomenclature of Medicine--Clinical Terms) for financial strain,
education, social connection and isolation, and others. Additional
stakeholder efforts underway to expand capabilities to capture
additional social determinants of health data elements include the
Gravity Project to identify and harmonize social risk factor data for
interoperable electronic health
[[Page 61932]]
information exchange for EHR fields, as well as proposals to expand the
ICD-10 (International Classification of Diseases, Tenth Revision) Z-
codes, the alphanumeric codes used worldwide to represent
diagnoses.\187\
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\187\ https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
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While development of sustainable and consistent programs to collect
data on social determinants of health can be considerable undertakings,
we recognize that another method to identify better race and ethnicity
data is needed in the short term to address the need for reporting on
health equity. In working with our contractors, two algorithms have
been developed to indirectly estimate the race and ethnicity of
Medicare beneficiaries (as described further in the next section). We
believe that using indirect estimation can help to overcome the current
limitations of demographic information and enable timelier reporting of
equity results until longer term collaborations to improve demographic
data quality across the health care sector materialize. The use of
indirectly estimated race and ethnicity for conducting stratified
reporting does not place any additional collection or reporting burdens
on facilities as these data are derived using existing administrative
and Census-linked data.
Indirect estimation relies on a statistical imputation method for
inferring a missing variable or improving an imperfect administrative
variable using a related set of information that is more readily
available.\188\ Indirectly estimated data are most commonly used at the
population level (such as the facility or health plan-level), where
aggregated results form a more accurate description of the population
than existing, imperfect data sets. These methods often estimate race
and ethnicity using a combination of other data sources which are
predictive of self-identified race and ethnicity, such as language
preference, information about race and ethnicity in our administrative
records, first and last names matched to validated lists of names
correlated to specific national origin groups, and the racial and
ethnic composition of the surrounding neighborhood. Indirect estimation
has been used in other settings to support population-based equity
measurement when self-identified data are not available.\189\
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\188\ IOM. 2009. Race, Ethnicity, and Language Data:
Standardization for Health Care Quality Improvement. Washington, DC:
The National Academies Press.
\189\ IOM. 2009. Race, Ethnicity, and Language Data:
Standardization for Health Care Quality Improvement. Washington, DC:
The National Academies Press.
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As discussed earlier in the preamble, we have previously supported
the development of two such methods of indirect estimation of race and
ethnicity of Medicare beneficiaries. One indirect estimation approach,
developed by our contractor, uses Medicare administrative data, first
name and surname matching, derived from the U.S. Census and other
sources, with beneficiary language preference, State of residence, and
the source of the race and ethnicity code in Medicare administrative
data to reclassify some beneficiaries as Hispanic or Asian Pacific
Islander (API).\190\ In recent years, we have also worked with another
contractor to develop a new approach, the Medicare Bayesian Improved
Surname Geocoding (MBISG), which combines Medicare administrative data,
first and surname matching, geocoded residential address linked to the
2010 U.S. Census, and uses both Bayesian updating and multinomial
logistic regression to estimate the probability of belonging to each of
six racial/ethnic groups.\191\
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\190\ Eicheldinger, C., & Bonito, A. (2008). More accurate
racial and ethnic codes for Medicare administrative data. Health
Care Financing Review, 29(3), 27-42.
\191\ Haas, A., Elliott, M. et al (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23.
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The MBISG model is currently used to conduct the national,
contract-level, stratified reporting of Medicare Part C & D performance
data for Medicare Advantage Plans by race and ethnicity.\192\
Validation testing reveals concordances with self-reported race and
ethnicity of 0.96-0.99 for API, Black, Hispanic, and White
beneficiaries for MBISG version 2.1.\193\ \194\ The algorithms under
consideration are considerably less accurate for individuals who self-
identify as American Indian or Alaskan Native as well as for those who
self-identify as multiracial.\195\ Indirect estimation can be a
statistically reliable approach for calculating population-level equity
results for groups of individuals (such as the facility-level) and is
not intended, nor being considered, as an approach for inferring the
race and ethnicity of an individual.
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\192\ https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
\193\ Haas, A., Elliott, M. et al (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23.
\194\ https://www.cms.gov/files/document/racial-ethnic-gender-disparities-health-care-medicare-advantage.pdf.
\195\ Haas, A., Elliott, M. et al. (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23 and Bonito AJ, Bann C,
Eicheldinger C, Carpenter L. Creation of New Race-Ethnicity Codes
and Socioeconomic Status (SES) Indicators for Medicare
Beneficiaries. Final Report, Sub-Task 2. (Prepared by RTI
International for the Centers for Medicare and Medicaid Services
through an interagency agreement with the Agency for Healthcare
Research and Policy, under Contract No. 500-00-0024, Task No. 21)
AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency for
Healthcare Research and Quality. January 2008.
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However, despite the high degree of statistical accuracy of the
indirect estimation algorithms under consideration there remains the
small risk of unintentionally introducing bias. For example, if the
indirect estimation is not as accurate in correctly estimating race and
ethnicity in certain geographies or populations it could lead to some
bias in the method results. Such bias might result in slight
overestimation or underestimation of the quality of care received by a
given group. We believe this amount of bias is considerably less than
would be expected if stratified reporting was conducted using the race
and ethnicity currently contained in our administrative data. Indirect
estimation of race and ethnicity is envisioned as an intermediate step,
filling the pressing need for more accurate demographic information for
the purposes of exploring inequities in service delivery, while
allowing newer approaches, as described in the next section, for
enhancing demographic data collection. We expressed interest in
learning more about, and solicited comments about, the potential
benefits and challenges associated with measuring facility equity using
an imputation algorithm to enhance existing administrative data quality
for race and ethnicity until self-reported information is sufficiently
available.
(3) Improving Demographic Data Collection
Stratified facility-level reporting using indirectly estimated race
and ethnicity and dual eligibility would represent an important advance
in our ability to provide equity reports to facilities. However, self-
reported disability status, race, ethnicity, sexual orientation and
gender identity data remain the gold standard for classifying an
individual according to disability status, race, or ethnicity. The CMS
Quality Strategy outlines our commitment to strengthening
infrastructure and data systems by ensuring that standardized
demographic information is collected to identify disparities in health
care delivery outcomes.\196\ Collection and
[[Page 61933]]
sharing of a standardized set of social, psychological, and behavioral
data by facilities, including disability status and race and ethnicity,
using electronic data definitions which permit nationwide,
interoperable health information exchange, can significantly enhance
the accuracy and robustness of our equity reporting.\197\ This could
potentially include expansion to additional social risk factors, such
as language preference and disability status, where accuracy of
administrative data is currently limited. We are mindful that
additional resources, including data collection and staff training may
be necessary to ensure that conditions are created whereby all patients
are comfortable answering all demographic questions, and that
individual preferences for non-response are maintained.
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\196\ The Centers for Medicare & Medicaid Services. CMS Quality
Strategy. 2016. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
\197\ The Office of the National Coordinator for Health
Information Technology. United State Core Data for Interoperability
Draft Version 2. 2021. https://www.healthit.gov/isa/sites/isa/files/2021-01/Draft-USCDI-Version-2-January-2021-Final.pdf.
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We are also interested in learning about and solicited comments on
current data collection practices by facilities to capture demographic
data elements (such as race, ethnicity, sex, sexual orientation and
gender identity (SOGI), language preference, and disability status).
Further, we are interested in potential challenges facing facility
collection of a minimum set of demographic data elements in alignment
with national data collection standards (such as the standards
finalized by the Affordable Care Act \198\) and standards for
interoperable exchange (such as the U.S. Core Data for Interoperability
put forth by ONC for incorporation in certified health IT products as
part of the 2015 Edition of health IT certification criteria \199\).
Advancing data interoperability through collection of a minimum set of
demographic data collection has the potential for improving the
robustness of the disparity methods results, potentially permitting
reporting using more accurate, self-reported, information, such as race
and ethnicity, and expanding reporting to additional dimensions of
equity, including stratified reporting by disability status.
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\198\ https://minorityhealth.hhs.gov/assets/pdf/checked/1/Fact_Sheet_Section_4302.pdf.
\199\ https://www.healthit.gov/sites/default/files/2020-08/2015EdCures_Update_CCG_USCDI.pdf.
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(4) Potential Creation of an ESRD Facility Equity Score To Synthesize
Results Across Multiple Social Risk Factors
As we describe previously, we are considering expanding the
disparity methods to include two social risk factors (dual eligibility
and race/ethnicity). This approach would improve the comprehensiveness
of health equity information provided to facilities. Aggregated results
from multiple measures and multiple social risk factors, from the CMS
Disparity Methods, in the format of a summary score, can improve the
usefulness of the equity results. In working with our contractors, we
recently developed an equity summary score for Medicare Advantage
contract/plans, the Health Equity Summary Score (HESS), with
application to stratified reporting using two social risk factors: Dual
eligibility and race and as described in Incentivizing Excellent Care
to At-Risk Groups with a Health Equity Summary Score.\200\
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\200\ Agniel D, Martino SC, Burkhart Q, et al. Incentivizing
Excellent Care to At-Risk Groups with a Health Equity Summary Score.
J Gen Intern Med. Published online November 11, 2019 Nov 11. doi:
10.1007/s11606-019-05473-x.
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The HESS calculates standardized and combined performance scores
blended across the two social risk factors. The HESS also combines
results of the within-plan (similar to the Within-Facility method) and
across-plan method (similar to the Across-Facility method) across
multiple performance measures.
We are considering building an ESRD Facility Equity Score, not yet
developed, which would be modeled off the HESS but adapted to the
context of risk-adjusted facility outcome measures and potentially
other ESRD QIP quality measures. We envision that the ESRD Facility
Equity Score would synthesize results for a range of measures and using
multiple social risk factors, using measures and social risk factors
which would be reported to facilities as part of the CMS Disparity
Methods. We believe that creation of the ESRD Facility Equity Score has
the potential to supplement the overall measure data already reporting
on the Care Compare or successor website, by providing easy to
interpret information regarding disparities measured within individual
facilities and across facilities nationally. A summary score would
decrease burden by minimizing the number of measure results provided
and providing an overall indicator of equity.
The ESRD Facility Equity Score under consideration would
potentially:
Summarize facility performance across multiple social risk
factors (initially dual eligibility and indirectly estimated race and
ethnicity, as described above).
Summarize facility performance across the two disparity
methods (that is, the Within-Facility Disparity Method and the Across-
Facility Disparity Method) and potentially multiple measures.
Prior to any future public reporting of stratified measure data
using indirectly estimated race and ethnicity information, if we
determine that an ESRD Facility Equity Score can be feasibly and
accurately calculated, we would provide results of the ESRD Facility
Equity Score, in confidential facility specific reports which
facilities and their ESRD Networks would be able to download. Any
potential future proposal to display the ESRD Facility Equity Score on
the Care Compare or successor website would be made through future RFI
or rulemaking.
d. Solicitation of Public Comment
We sought comment on the possibility of stratifying ESRD QIP
measures by dual eligibility and race and ethnicity. We solicited
public comments on the application of the within-facility or across-
facility disparities methods if we were to stratify ESRD QIP measures.
We also sought comment on the possibility of facility collection of
standardized demographic information for the purposes of potential
future quality reporting and measure stratification. In addition, we
sought comment on the potential design of a facility equity score for
calculating results across multiple social risk factors and measures,
including race and disability. Any data pertaining to these areas that
are recommended for collection for measure reporting for a CMS program
and any potential public disclosure on Care Compare or successor
website would be addressed through a separate and future notice-and-
comment rulemaking. We plan to continue working with ASPE, facilities,
the public, and other key stakeholders on this important issue to
identify policy solutions that achieve the goals of attaining health
equity for all patients and minimizing unintended consequences. We
noted for readers that responses to the RFI will not directly impact
payment decisions. We also noted our intention for additional RFI or
rulemaking on this topic in the future.
Specifically, we invited public comment on the following:
[[Page 61934]]
Future Potential Stratification of Quality Measure Results
The possible stratification of facility-specific reports
for ESRD QIP measure data by dual-eligibility status, including which
measures would be most appropriate for stratification;
The potential future application of indirect estimation of
race and ethnicity information to permit stratification of measure data
for reporting ESRD facility-level disparity results;
Appropriate privacy safeguards with respect to data
produced from the indirect estimation of race and ethnicity to ensure
that such data is properly identified if/when it is shared with
facilities.
Ways to address the challenges of defining and collecting,
accurate and standardized self-identified demographic information,
including information on race and ethnicity, disability, and language
preference for the purposes of reporting, measure stratification and
other data collection efforts relating to quality.
Recommendations for other types of readily available data
elements for measuring disadvantage and discrimination for the purposes
of reporting, measure stratification and other data collection efforts
relating to quality, in addition, or in combination with race and
ethnicity
Recommendations for types of quality measures or
measurement domains to prioritize for stratified reporting by dual
eligibility, race and ethnicity, and disability.
Examples of approaches, methods, research, and/or
considerations for use of data-driven technologies that do not
facilitate exacerbation of health inequities, recognizing that biases
may occur in methodology or be encoded in datasets.
We received comments on these topics.
Comments: Many commenters expressed support for stratification by
dual eligibility, race, and ethnicity. A few commenters expressed the
belief that stratification of quality measures by social risk factors,
such as dual eligibility and race and ethnicity, is essential to
advancing health equity as such factors have been shown to have a
likely impact on health outcomes. A few commenters expressed the belief
that stratification will improve transparency, help identify existing
disparities and inform efforts to reduce those disparities. A few
commenters recommended that CMS take a stepwise approach to
stratification. A few commenters stated that stratifying data is
important to help identify health equity gaps, but recommended that CMS
take action on its findings in order to address the health equity gap
and reduce disparities in care. A few commenters recommended that CMS
make stratified data publicly available to inform both CMS and
stakeholders of the diverse needs of different patient populations, and
identify needed policy changes to improve patient access to treatment.
A few commenters expressed support for stratification but suggested
setting a threshold at the 10th decile of low-income patient
distribution to include facilities that serve a disproportionately high
percentage of low-income patients. One commenter recommended that
adjusting measures for social risk factors, including dual-eligibility
or income, may reduce the likelihood of program penalties increasing
existing disparities. One commenter supported the proposed
stratification of facility-specific reports for ESRD QIP measure data
by dual-eligibility status and race and ethnicity; however, this
commenter also recommended CMS monitor for unintended consequences
believing that stratification risks disparities in patient treatment.
Many commenters expressed support for stratification by dual
eligibility. A few commenters supported stratification by dual eligible
status, noting that it can be used as a proxy for socio-economic status
and is an objective classification that may have less biased data. A
few commenters expressed the belief that stratification could help
facilities identify and reduce disparities, but noted that differences
in Medicaid eligibility between states may impact comparability when
stratifying measures by dual eligibility. One commenter expressed
concern that dual eligibility may be too blunt a data point to identify
the underlying cause of disparity, noting that disparities experienced
by ESRD patients stem from a wide range of social risk factors. One
commenter noted that understanding differences between dual-eligible
and non-dual-eligible patients in baseline chronic kidney disease care
could inform ways to allocate resources aimed at slowing the
progression of CKD. One commenter noted the correlation between a
facility's dual-eligible patient population and a facility's payment
reduction based on its ESRD QIP scores, citing studies indicating that
facilities serving a higher proportion of dual eligible/low-income
patients are more likely to have higher ESRD QIP payment reductions.
Several commenters noted that, although stratification may help
identify and address health equity gaps, many disparities begin decades
prior to starting dialysis, and encouraged CMS to explore ways to
address health disparities earlier in the progression of kidney
disease. One commenter expressed concern that stratification may create
unintended consequences such as disparities in patient treatment based
on social determinants of health. One commenter recommended CMS
consider options beyond stratification of ESRD QIP measures by dual
eligible status or race and ethnicity to address health equity gaps.
One commenter expressed its belief that the segmentation of populations
using dual eligibility or race and ethnicity as the proxy for ``social
risk,'' for example, is problematic and that the primary goal across
all CMS programs should be to prioritize self-reported race, ethnicity,
and other social determinants of health data as the sole source of
stratifying populations to understand disparities.
Many commenters expressed support for stratification of measures by
race and ethnicity, noting that such factors have been identified as
likely having an impact on health outcomes. A few commenters expressed
support for the use of indirect estimation of race and ethnicity for
purposes of calculating facility level performance measures as a
preliminary step while more precise methods are developed. One
commenter expressed support for the expansion of CMS Disparity Methods
to the ESRD QIP and stratifying by race and ethnicity, both within and
across facilities. One commenter recommended that disparities methods
should be implemented in a way that is minimally burdensome and
confidentially reported.
A few commenters requested clarification regarding the application
of disparity methods to the ESRD QIP, noting that disparity methods are
currently applied to hospital readmissions measures which may be linked
to factors outside the facility's ability to influence. A few
commenters expressed concern regarding the indirect estimation of race
and ethnicity, believing that it was not worth the increased and
unknown risk of bias that it could unintentionally create and
recommended that indirect data be evaluated to ensure CMS is not
introducing bias into the system or underestimating or overestimating
the quality of care for a certain population. A few commenters
expressed concern that the imputation method is imprecise, particularly
for indigenous and multi-racial patients and recommended that self-
reported data was more accurate. One commenter
[[Page 61935]]
questioned whether either of the two disparities methods would help
close the health equity gap, and suggested that CMS consider whether an
indirect estimation approach might divert resources away from
developing better methods. One commenter recommended a step-wise
approach to use the ``Within Facility Disparity Method'' before
expanding to apply an ``Across-Facility Disparity Method'' to assess
how a facility is addressing equity, as well as to better establish
what resources may be required to effectively address equity.
Several commenters expressed support for the stratification of the
SRR, STrR, and SHR measures by dual-eligibility status and race/
ethnicity, noting that evidence has indicated disparities may factor
into measure performance in other healthcare settings, and that such
stratification may inform clinical practices and care. Several
commenters suggested that the vascular access measures are appropriate
for stratification by dual eligibility and race/ethnicity. A few
commenters also recommended that these measures be stratified by
insurance status at the time of dialysis initiation in order to provide
insight into patients' abilities to access pre-dialysis care and
vascular access placement. A few commenters stated that the PPPW
measure is appropriate for potential stratification by dual eligibility
status, race/ethnicity, as well as geographic area. A few commenters
recommended that stratification is adopted for measures where it has
been shown, or is clearly suspected based on research from other care
settings, that disparities are driving differences in the outcomes
being reported. A few commenters expressed the belief that most ESRD
QIP measures would benefit from stratification. One commenter
recommended that CMS encourage all health care providers and
organizations to collect and stratify both patient and caregiver data
for all measures.
A few commenters recommended that CMS develop best practices to
ensure the security of data and its utilization, noting the sensitive
nature of the data and the importance of gaining beneficiaries' trust.
A few commenters agreed that data elements should be subject to
existing privacy and security requirements, and recommended that CMS
establish an open and transparent process to work with NQF and other
stakeholders to develop data options. One commenter expressed its
belief in the unassailable importance of privacy safeguards for all
uses of sensitive personal information such as race, ethnicity, and
other social risk factors and recommended CMS consider using only self-
reported data to alleviate risk of misidentification and to promote
robust collection of patient-reported information.
A few commenters expressed the belief that patient self-reporting
is the most appropriate way to collect social determinants of health
data such as race and ethnicity, agreeing with CMS' assessment that
self-reported patient data is the gold standard. A few commenters noted
that one challenge may be that the concept of race is subjective and
may be imprecise due to differences in cultural understanding. A few
commenters recommended that CMS encourage facilities to collect self-
reported race and ethnicity data, as well as establish a timeframe for
meeting specific data collection goals including data completeness and
accuracy requirements. One commenter noted that many health care
organizations are already collecting self-reported demographic
information and have been for years. One commenter expressed its belief
that the primary goal across all CMS programs should be to prioritize
self-reported race, ethnicity, and other social determinants of health
data as the sole source of stratifying populations to understand
disparities. One commenter recommended that, given the importance of
self-reported data, CMS work on developing data collection language
that is more person-centric in order to encourage trust among those
patients whose data are being collected.
Several commenters expressed support for collecting additional
information that will likely impact patient outcomes, such as insurance
status at dialysis initiation and geographic area of residence. Several
commenters recommended the use of Z-codes or other data sources to
collect data to report on factors such as housing insecurity, financial
insecurity, caregiver support, mental illness, physical illness, age,
education level, transportation insecurity, food insecurity, marital
status, violence, safety concerns, and child care. One commenter
recommended that CMS adopt a definition of health equity that takes
into account the needs of various patient populations and structural
issues associated with equity, such as race, ethnicity, sex, SOGI,
language preference, tribal membership, and disability status.
A few commenters recommended that CMS work with the kidney care
community to develop risk adjusters for measures. A few commenters
requested that methodologies use data elements that are available to
providers and that calculations can be replicated to promote
transparency. A few commenters recommended that CMS also consider
eliminating bias in kidney function testing, noting for example that
the eGFR test is biased based on racial assumptions and can impact
transplant eligibility among Black patients. One commenter expressed
concern that many approaches based on data-driven technologies are less
accessible to vulnerable patient populations and would potentially
exacerbate existing inequities. This commenter also noted that
smartphone technologies may be more promising as an example of a data-
driven technology that does not facilitate exacerbation of health
inequities.
Response: We appreciate all of the comments and interest in this
topic. We believe that this input is very valuable in the continuing
development of the CMS health equity quality measurement efforts. We
will continue to take all concerns, comments, and suggestions into
account for future development and expansion of our health equity
quality measurement efforts.
Improving Demographic Data Collection
Experiences of users of certified health IT regarding
local adoption of practices for collection of social, psychological,
and behavioral data elements, the perceived value of using these data
for improving decision-making and care delivery, and the potential
challenges and benefits of collecting more granular, structured
demographic information, such as the ``Race & Ethnicity--CDC'' code
system.
The possible collection of a minimum set of social,
psychological, and behavioral data elements by ESRD facilities at the
time of admission using structured, interoperable electronic data
standards, for the purposes of reporting, measure stratification and
other data collection efforts relating to quality.
We received comments on these topics.
Comments: Many commenters expressed support for CMS' efforts to
address inequities in health outcomes through improving data collection
and patient outcome measurement. Several commenters supported the use
of minimally burdensome data collection efforts. A few commenters noted
that much of the information that CMS would like to collect is reported
on Form 2728--ESRD Medical Evidence Report Medicare Entitlement And/Or
Patient Registration (OMB control number 0938-0046), and encouraged
that CMS to be economical in its expansion of data collection on the
Form 2728 so as to not create additional patient concerns. One
commenter recommended that a system of data
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collection and reporting should not add to the confusion about what the
terms race and ethnicity mean, and what labels appropriately fit either
of these broad concepts. One commenter recommended that CMS collect
data on demographic characteristics in a way that aligns with adoption
of FHIR standards, noting that FHIR may be used to appropriately group
demographic characteristics in a standardized way. One commenter noted
the potential challenge of uploading data from facility EMR systems to
CMS for measure calculation purposes. A few commenters expressed
concerns with adjusting for social factors when there is a ``small
numbers'' problem in ESRD QIP that can impact the accuracy of
performance measurement and that will be aggravated with dividing
categories into smaller subsets. One commenter expressed its belief
that modifications to current data collection related to social,
psychological, and behavioral data could be useful to CMS to address
equity and quality of care. However, the commenter did not recommend
the application of CDC's 900-variable system of identifying race and
ethnicity, as provided in the CDC's Race and Ethnicity Code Set Version
1.0, in a highly granular way believing the volume of data that would
need to be collected would make the process labor intensive for
clinical staff. One commenter recommended that CMS work to improve and
standardize the underlying data collection and metrics; this commenter
recommended a joint development process that includes the Center for
Medicare & Medicaid Innovation (CMMI) and the Office of the National
Coordinator for Health Information Technology (ONC) in collaboration
with health systems, practices, and patient/community representation.
Other commenters noted the importance of closing the health equity
gap through measurement of demographic characteristics. One commenter
suggested that agencies leverage the role of social workers in
identifying sociodemographic factors and barriers to health equity.
Another commenter supported this method, noting that although this may
add another step to data collection processes, it would be valuable in
addressing health equity gaps. To reduce possible workload burden on
organizations that are new to this process, a commenter recommended a
gradual approach to data collection. In addition, commenters suggested
reducing burden by adopting standardized screening tools to collect
this information, such as ICD-10-CM Z-codes, which in practice would
allow patients to be referred to resources and initiatives when
appropriate. Several commenters encouraged collection of comprehensive
social determinants of health and demographic information in addition
to race and ethnicity, such as disability, sexual orientation, and
primary language. Several commenters provided feedback on the potential
use of an indirect estimation algorithm when race and ethnicity are
missing or incorrect, and emphasized the sensitivity of demographic
information and recommended that CMS use caution when using estimates
from the algorithm, including assessing for potential bias, reporting
the results of indirect estimation alongside direct self-report at the
organizational level for comparison, and establishing a timeline to
transition to entirely directly collected data. Commenters also advised
that CMS be transparent with beneficiaries and explain why data are
being collected and the plans to use these data. A commenter noted that
information technology infrastructure should be established in advance
to ensure that this information is being used and exchanged
appropriately.
Response: We appreciate all of the comments and interest in this
topic. We believe that this input is very valuable in the continuing
development of the CMS health equity quality measurement efforts. We
will continue to take all concerns, comments, and suggestions into
account for future development and expansion of our health equity
quality measurement efforts.
Potential Creation of an ESRD Facility Equity Score To Synthesize
Results Across Multiple Social Risk Factors
The possible creation and confidential reporting of an
ESRD Facility Equity Score to synthesize results across multiple social
risk factors and disparity measures.
Interventions ESRD facilities could institute to improve a
low facility equity score and how improved demographic data could
assist with these efforts.
We received comments on these topics.
Comments: Several commenters expressed support for the concept of
an ESRD Facility Equity Score, but requested that CMS provide further
details. Several commenters recommended that CMS work with stakeholders
in the kidney care community to develop an equity score in order to
ensure transparency and to make sure providers are able to address
identified inequities. One commenter recommended that CMS include
education, training, and resources for implementation of an equity
score.
A few commenters noted the challenge of developing a scoring
methodology that could address risk across different factors. A few
commenters questioned whether the score would be meaningful for
patients. A few commenters expressed concern for public reporting of a
Facility Equity Score, noting that it might be misleading to patients
and may not reflect quality of care because facilities are limited in
their ability to influence disparities that impact health outcomes. One
commenter expressed the belief that a Facility Equity Score is
premature, and that CMS should focus on establishing the right set of
patient characteristics and contrasting them with meaningful clinical
and consumer measures in order to develop a meaningful scoring
methodology to propose in future notice and comment rulemaking. One
commenter expressed caution that the component measures should reflect
actual differences in care provided by ESRD facilities and not factors
outside of those facilities' control, believing the inclusion of
measures not much under the control of ESRD facilities will penalize
those facilities serving a large number of ``vulnerable'' patients and
not really speak to issues of equity in the care provided. This
commenter recommended that measures are selected carefully to reflect
activities and factors that are under facilities' control and then
apply all of the standard tools of quality improvement. One commenter
expressed its belief that the use of an imputed race/ethnicity
methodology risks misattributing people to the wrong categories, and
carrying that over into a facility equity score could lead to incorrect
or misguided responses. This commenter recommended a careful, inclusive
development process to avoid establishing processes and metrics that
exacerbate harms and recommended a CMMI initiative to test and shape
reporting.
A few commenters expressed support for the production of reports to
help facilities, patients and payers understand the disparities in
their patient populations. A few commenters noted that many barriers
such as anti-kickback rules and other regulations prevent facilities
from providing additional services and supports that would help to
address health disparities, and recommended that CMS work to find ways
to remove these barriers. A few commenters recommended that CMS provide
support to facilities in order to help them close gaps in health
equity. One
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commenter recommended that additional resources be allocated to help
assist and support facilities in their health equity goals, such as
taking money from ESRD QIP penalties to reward facilities that attain
the benchmarks and also allocate funds to help low performing
facilities improve. One commenter noted that anything that requires
additional staff time and effort without either additional payment or
some tangible savings elsewhere, will not be sustainable. This
commenter gave examples of care coordination, more time in patient
education, more frequent patient home visits, and additional electronic
home monitoring, as potential paths to equity improvement that require
additional funding.
We appreciate all of the comments and interest in this topic. We
believe that this input is very valuable in the continuing development
of the CMS health equity quality measurement efforts. We will continue
to take all concerns, comments, and suggestions into account for future
development and expansion of our health equity quality measurement
efforts.
We also received comments on the general topic of health equity in
the ESRD QIP.
Comments: Many commenters expressed overall support of CMS' goals
to advance health equity. There were a few comments regarding the need
to further extend and specify the definition of equity provided in the
proposed rule. Commenters also noted that equity initiatives should be
based on existing disparities and population health goals, be mindful
of the needs of the communities served, and work to bridge dialysis
facilities with community-based providers. Several commenters
recommended that CMS further investigate ways to provide outreach and
education aimed at slowing down the progress of chronic kidney disease
and address health disparities before dialysis is necessary. Several
commenters encouraged CMS to be mindful about whether collection of
additional quality measures and standardized patient assessment
elements might increase provider burden.
We appreciate all of the comments and interest in this topic. We
believe that this input is very valuable in the continuing development
of the CMS health equity quality measurement efforts. We will continue
to take all concerns, comments, and suggestions into account for future
development.
2. COVID-19 Vaccination Measures Request for Information
a. Background
On January 31, 2020, the Secretary declared a PHE for the U.S. in
response to the global outbreak of SARS-CoV-2, a novel (new)
coronavirus that causes a disease named ``coronavirus disease 2019''
(COVID-19).\201\ COVID-19 is a contagious respiratory infection \202\
that can cause serious illness and death. Older individuals and those
with underlying medical conditions are considered to be at higher risk
for more serious complications from COVID-19.\203\
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\201\ 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. Available at:
https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
\202\ 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.
\203\ Ibid.
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As of April 2, 2021, the U.S. reported over 30 million cases of
COVID-19 and over 550,000 COVID-19 deaths.\204\ Hospitals and health
systems saw significant surges of COVID-19 patients as community
infection levels increased.\205\ From December 2, 2020 through January
30, 2021, more than 100,000 Americans were in the hospital with COVID-
19 at the same time.\206\ As of September 16, 2021, the U.S. has
reported over 41.5 million cases of COVID-19 and over 666,000 COVID-19
deaths.\207\
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\204\ Centers for Disease Control and Prevention. (2020). CDC
COVID Data Tracker. Available at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
\205\ 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.
\206\ US Currently Hospitalized [verbar] The COVID Tracking
Project. Accessed January 31, 2021 at: https://covidtracking.com/data/charts/us-currently-hospitalized.
\207\ Centers for Disease Control and Prevention. (2021). CDC
COVID Data Tracker. Available at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
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Evidence indicates that COVID-19 primarily spreads when individuals
are in close contact with one another.\208\ 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.\209\ Thus, the CDC advises that infections mainly
occur through exposure to respiratory droplets when a person is in
close contact with someone who has COVID-19.\210\ Although less common,
COVID-19 can also spread when individuals are not in close contact if
small droplets or particles containing the virus linger in the air
after the person who is infected has left the space.\211\ Another means
of less common transmission is contact with a contaminated
surface.\212\
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\208\ Centers for Disease Control and Prevention. (2021). How
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
\209\ Ibid.
\210\ Ibid.
\211\ Ibid.
\212\ Ibid.
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Subsequent to the publication of the proposed rule, the CDC
confirmed that the three main ways that COVID-19 is spread are: (1)
Breathing in air when close to an infected person who is exhaling small
droplets and particles that contain the virus; (2) Having these small
droplets and particles that contain virus land on the eyes, nose, or
mouth, especially through splashes and sprays like a cough or sneeze;
and (3) Touching eyes, nose, or mouth with hands that have the virus on
them.\213\ 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.\214\ Although personal protective equipment (PPE) and
other infection-control precautions can reduce the likelihood of
transmission in health care settings, COVID-19 can spread between
healthcare personnel (HCP) and patients, or from patient to patient
given the close contact that may occur during the provision of
care.\215\ The CDC has emphasized that health care settings can be
high-risk places for COVID-19 exposure and transmission.\216\
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\213\ 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.
\214\ Centers for Disease Control and Prevention. (2021). When
to Quarantine. Accessed on April 2, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/if-you-are-sick/quarantine.html.
\215\ Centers for Disease Control and Prevention. (2021).
Interim U.S. Guidance for Risk Assessment and Work Restrictions for
Healthcare Personnel with Potential Exposure to COVID-19. Accessed
on April 2 at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html#Transmission.
\216\ 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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[[Page 61938]]
Vaccination is a critical part of the nation's strategy to
effectively counter the spread of COVID-19 and ultimately help restore
societal functioning.\217\ On December 11, 2020, FDA issued the first
Emergency Use Authorization (EUA) for a COVID-19 vaccine in the
U.S.\218\ Subsequently, FDA issued EUAs for additional COVID-19
vaccines and approved a vaccine.\219\
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\217\ Centers for Disease Control and Prevention. (2020). COVID-
19 Vaccination Program Interim Playbook for Jurisdiction Operations.
Accessed on April 3, 2021 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
\218\ U.S. Food and Drug Administration. (2020). Pfizer-BioNTech
COVID-19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/150386/download. (as reissued on September 22,
2021)
\219\ U.S. Food and Drug Administration. (2020). Moderna COVID-
19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144636/download (as reissued on August 12, 2021);
U.S. Food and Drug Administration. (2021). Janssen COVID-19 Vaccine
EUA Letter of Authorization. Available at https://www.fda.gov/media/146303/download (as reissued on June 10, 2021). FDA Approves First
COVID-19 Vaccine, Available at https://www.fda.gov/news-events/press-announcements/fda-approves-first-covid-19-vaccine.
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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 outlined a
goal of administering 200 million shots in 100 days.\220\ After
achieving this goal,\221\ the Biden Administration announced a new goal
to administer at least one COVID-19 vaccine shot to 70 percent of the
U.S. adult population by July 4, 2021.\222\ Although the goal of the
U.S. government is to ensure that every American who wants to receive a
COVID-19 vaccine can receive one, Federal agencies recommended that
early vaccination efforts focus on those critical to the PHE response,
including HCP providing direct care to patients with COVID-19, and
individuals at highest risk for developing severe illness from COVID-
19.\223\ 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.\224\
Research suggests most states followed this recommendation,\225\ and
HCP began receiving the vaccine in mid-December of 2020.\226\ Although
the vaccination strategy for individuals at highest risk for developing
severe illness from COVID-19, including ESRD patients, has varied from
State to State,\227\ ACIP recommendations indicated that ESRD patients
would be offered the COVID-19 vaccine based on their high-risk status
as part of phase 1c.\228\
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\220\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. Accessed on April 3, 2021
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/.
\221\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. Accessed on June 2, 2021
at: https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/04/21/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations-2/.
\222\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. Accessed on June 4, 2021,
at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/05/04/fact-sheet-president-biden-to-announce-goal-to-administer-at-least-one-vaccine-shot-to-70-of-the-u-s-adult-population-by-july-4th/.
\223\ 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.
\224\ 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.
\225\ 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/.
\226\ 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.
\227\ Kates, J, Michaud, J, Tolbert, J. ``The COVID-19 Vaccine
Priority Line Continues to Change as States Make Further Updates.''
Kaiser Family Foundation. January 21, 2021. Accessed on January 29
at https://www.kff.org/policy-watch/the-covid-19-vaccine-priority-line-continues-to-change-as-states-make-further-updates/.
\228\ Dooling K, Marin M, Wallace M, et al. ``The Advisory
Committee on Immunization Practices' Updated Interim Recommendation
for Allocation of COVID-19 Vaccine--United States, December 2020.''
MMWR Morb Mortal Wkly Rep 2021; 69:1657-1660. ACIP recommended that
the COVID-19 vaccine should be offered to persons aged >=75 years
and non-health care frontline essential workers in Phase 1b, and to
persons aged 16-64 years with high-risk medical conditions in Phase
1c.
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As of July 30, 2021 the CDC reported that over 344 million doses of
COVID-19 vaccine had been administered, and approximately 164.2 million
people had received a complete vaccination course.\229\ President Biden
indicated on April 6, 2021 that the U.S. has sufficient vaccine supply
to make every adult eligible to receive a vaccine beginning April 19,
2021.\230\ Furthermore, on March 25, 2021, the Biden Administration
announced a new partnership with dialysis facilities to provide COVID-
19 vaccinations directly to people receiving dialysis and HCP in
dialysis facilities.\231\ Finally, as part of the Biden
Administration's efforts to vaccinate those who are still unvaccinated
through increasing the number of Americans covered by vaccination
requirements,\232\ on September 9, 2021, the Biden Administration
announced that COVID-19 vaccination will be required of all staff
within Medicare and Medicaid-certified facilities to protect both
patients and HCP against COVID-19.\233\
---------------------------------------------------------------------------
\229\ Centers for Disease Control and Prevention. COVID Data
Tracker. COVID-19 Vaccinations in the United States. Accessed June
23, 2021 at: https://covid.cdc.gov/covid-data-tracker/#vaccinations.
\230\ The White House. Remarks by President Biden Marking the
150 Millionth COVID-19 Vaccine Shot. Accessed April 8, 2021 at:
https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/04/06/remarks-by-president-biden-marking-the-150-millionth-covid-19-vaccine-shot/.
\231\ The White House. FACT SHEET: Biden Administration
Announces Historic $10 Billion Investment to Expand Access to COVID-
19 Vaccines and Build Vaccine Confidence in Hardest-Hit and Highest-
Risk Communities. March 25, 2021. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/03/25/fact-sheet-biden-administration-announces-historic-10-billion-investment-to-expand-access-to-covid-19-vaccines-and-build-vaccine-confidence-in-hardest-hit-and-highest-risk-communities/.
\232\ The White House. Path Out of the Pandemic: President
Biden's COVID-19 Action Plan. Accessed on October 14, 2021.
Available at: https://www.whitehouse.gov/covidplan/#vaccinate.
\233\ CMS. Press Release: Biden-Harris Administration to Expand
Vaccination Requirements for Health Care Settings. September 9,
2021. Available at: https://www.cms.gov/newsroom/press-releases/biden-harris-administration-expand-vaccination-requirements-health-care-settings. In order to implement this plan, CMS is working with
the CDC to develop an Interim Final Rule with Comment Period that
will extend emergency regulations to require vaccination among staff
in a wide range of healthcare settings including dialysis
facilities. This action will create a consistent standard across the
country, while giving patients assurance of the vaccination status
of those delivering care.
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b. COVID-19 Vaccination Coverage Among Healthcare Personnel (HCP)
Measure
In the CY 2022 ESRD PPS proposed rule (86 FR 36369), we stated our
belief that it is important to incentivize and track HCP vaccination in
dialysis facilities through quality measurement in order to protect
health care workers, patients, and caregivers, and to help sustain the
ability of these facilities to
[[Page 61939]]
continue serving their communities throughout the PHE and beyond. We
recognize the importance of COVID-19 vaccination, and have finalized
proposals to include a COVID-19 HCP vaccination measure in various pay
for reporting programs, such as the Inpatient Psychiatric Facility
Quality Reporting Program (86 FR 42633 through 42640), the Hospital
Inpatient Quality Reporting Program (86 FR 45374 through 45382), the
PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) Program (86 FR
45428 through 45434), the Long-Term Care Hospital Quality Reporting
Program (LTCH QRP) (86 FR 45438 through 45446), the Inpatient
Rehabilitation Facility Quality Reporting Program (IRF QRP) (86 FR
42385 through 42396), and the Skilled Nursing Facility Quality
Reporting Program (86 FR 42480 through 42489). In the proposed rule, we
noted that there is not a pay for reporting program under the ESRD PPS,
however, we stated our belief that the public reporting of vaccination
data on Dialysis Facility Compare is important and would help to inform
patients of a facility's COVID-19 vaccination rates of HCP. Currently,
there is a measure for HCP \234\ and another for patient COVID-19
vaccination \235\ rates and such measures are currently reported to
CDC's National Healthcare Safety Network via ESRD Networks. The two
measures track the proportions of a facility's HCP and patient
population, respectively, that have been fully vaccinated against
COVID-19. Facilities were able to begin weekly COVID-19 vaccination
reporting for HCP in December 2020,\236\ and were able to begin weekly
COVID-19 vaccination reporting for patients in March 2021.\237\ When
the proposed rule was published, we noted that 89 percent of ESRD
facilities were reporting HCP vaccination rates and almost 95 percent
of ESRD facilities were reporting patient vaccination rates on these
measures. In the proposed rule (86 FR 36369), we stated that we were
evaluating options for publicly reporting the data on official CMS
datasets that compare the quality of care provided in Medicare-
certified dialysis facilities nationwide. We further stated that we
were also exploring the potential future inclusion of a COVID-19
vaccination measure to the ESRD QIP. Therefore, we sought public
comment on adding a new measure, COVID-19 Vaccination Coverage Among
HCP, to the ESRD QIP measure set in the next rulemaking cycle. The
measure would assess the proportion of a facility's health care
workforce that has been vaccinated against COVID-19.
---------------------------------------------------------------------------
\234\ https://www.cdc.gov/nhsn/hps/weekly-covid-vac/index.html.
\235\ https://www.cdc.gov/nhsn/dialysis/pt-covid-vac/index.html.
\236\ https://www.cdc.gov/nhsn/pdfs/hps/covidvax/weekly-covid-guidance-508.pdf.
\237\ https://www.cdc.gov/nhsn/pdfs/dialysis/covidvax/getting-started-508.pdf.
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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. In
the proposed rule (86 FR 36369), we stated our belief that facilities
should track the level of vaccination among their HCP as part of their
efforts to assess and reduce the risk of transmission of COVID-19
within their facilities. HCP vaccination can potentially reduce illness
that leads to work absence and limit disruptions to care.\238\ Data
from influenza vaccination demonstrates that provider uptake of the
vaccine is associated with that provider recommending vaccination to
patients,\239\ and we stated our belief that HCP COVID-19 vaccination
in dialysis facilities could similarly increase uptake among that
patient population. We also stated our belief that publishing the HCP
vaccination rates 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 measure would address the
quality priority of ``Promoting Effective Prevention and Treatment of
Chronic Disease'' through the Meaningful Measures Area of ``Preventive
Care.''
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\238\ Centers for Disease Control and Prevention. Overview of
Influenza Vaccination among Health Care Personnel. October 2020.
(2020) Accessed March 16, 2021 at: https://www.cdc.gov/flu/toolkit/long-term-care/why.htm.
\239\ Measure Application Committee Coordinating Committee
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021
at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
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c. COVID-19 Vaccination Coverage for Patients in End-Stage Renal
Disease (ESRD) Facilities Measure
In the CY 2022 ESRD PPS proposed rule (86 FR 36370), we stated our
belief that it is important to encourage patient vaccination in
dialysis facilities in order to protect health care workers, patients,
and caregivers, and to help sustain the ability of these facilities to
continue serving their communities throughout the PHE and beyond.
COVID-19 can cause outbreaks in ESRD facilities, and may
disproportionately affect ESRD patients due to the nature of the
treatment and sharing of common spaces.\240\ Many patients treated in
ESRD facilities have other underlying chronic conditions, and therefore
are highly susceptible to illness and disease.\241\ Sufficient
vaccination coverage among patients in ESRD facilities may reduce
transmission of SARS-CoV-2, thereby protecting them from COVID-19
mortality. Therefore, we sought public comment on adding new measure,
COVID-19 Vaccination Coverage Among Patients, to the ESRD QIP measure
set in future rulemaking. The measure would assess the proportion of a
facility's patient population that has been vaccinated against COVID-
19.
---------------------------------------------------------------------------
\240\ Verma, A., Patel, A., Tio, M., Waikar, S., ``Caring for
Dialysis Patients in a Time of COVID-19''. Kidney Medicine, Volume
2, Issue 6, 2020, Pages 787-792, ISSN 2590-0595. Available at
https://doi.org/10.1016/j.xkme.2020.07.006.
\241\ Ibid.
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In the proposed rule, we stated our belief that facilities should
track the level of vaccination among their patients as part of their
efforts to assess and reduce the risk of transmission of COVID-19
within their facilities. We also expressed our belief that publishing
the vaccination rates would be helpful to many ESRD 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 measure addresses the
quality priority of ``Promoting Effective Prevention and Treatment of
Chronic Disease'' through the Meaningful Measures Area of ``Preventive
Care.''
d. Review by the Measures Application Partnership and NQF
The COVID-19 HCP vaccination measure and the COVID-19 patient
vaccination measure were included on the publicly available ``List of
Measures under Consideration for December 21, 2020'' (MUC List), a list
of measures under consideration for use in various Medicare
programs.\242\ When the Measure Applications Partnership Hospital
Workgroup convened on January 11, 2021, it reviewed measures on the MUC
List including the two COVID-19 vaccination measures. The Measure
Applications Partnership Hospital Workgroup recognized that the
proposed measures represent a promising effort to advance measurement
for an evolving national pandemic and that it would bring value to the
ESRD QIP measure set by
[[Page 61940]]
providing transparency about an important COVID-19 intervention to help
prevent infections in HCP and patients.\243\ The Measure Applications
Partnership Hospital Workgroup also stated that collecting information
on COVID-19 vaccination coverage among HCP and ESRD patients, and
providing feedback to facilities, will allow facilities to benchmark
coverage rates and improve coverage in their facility. The Measure
Applications Partnership Hospital Workgroup further noted that reducing
rates of COVID-19 in HCP and ESRD patients may reduce transmission
among a patient population that is highly susceptible to illness and
disease, and also reduce instances of staff shortages due to
illness.\244\
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\242\ 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 29 2021.
\243\ Measure Applications Partnership. MAP Preliminary
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
\244\ Ibid.
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In its preliminary recommendations, the Measure Applications
Partnership Hospital Workgroup did not support these two measures for
rulemaking, subject to potential for mitigation.\245\ To mitigate its
concerns, the Measure Applications Partnership Hospital Workgroup
believed that both measures needed well-documented evidence, finalized
specifications, testing, and NQF endorsement prior to
implementation.\246\ Subsequently, the Measure Applications Partnership
Coordinating Committee met on January 25, 2021, and reviewed the COVID-
19 Vaccination Coverage Among HCP measure and the COVID-19 Vaccination
Coverage for Patients in ESRD Facilities Measure. In the 2020-2021
Measure Applications Partnership Final Recommendations, Measure
Applications Partnership offered conditional support for rulemaking
contingent on CMS bringing the measures back to Measure Applications
Partnership once the specifications are further refined.\247\ The
Measure Applications Partnership specifically stated, ``the incomplete
specifications require immediate mitigation and further development
should continue.'' \248\ The Measure Applications Partnership further
noted that the measures would add value to the ESRD QIP measure set by
providing visibility into an important intervention to limit COVID-19
infections in HCP and the ESRD patients for whom they provide
care.\249\ CMS brought both measures back to the Measure Applications
Partnership on March 15, 2021 to provide additional information and
continue discussing mitigation.
---------------------------------------------------------------------------
\245\ Ibid.
\246\ Ibid.
\247\ Measure Applications Partnership. 2020-2021 MAP Final
Recommendations. Accessed on February 3, 2021 at: http://www.qualityforum.org/Setting_Priorities/Partnership/Measure_Applications_Partnership.aspx.
\248\ Measure Applications Partnership. 2020-2021 MAP Final
Recommendations. Accessed on February 23, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
\249\ Measure Applications Partnership. 2020-2021 MAP Final
Recommendations. Accessed on February 23, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
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e. Request for Public Comment
In the proposed rule, we sought public comment on potentially
adding the two new COVID-19 vaccination measures discussed above, the
COVID-19 vaccination measure for HCP and the COVID-19 vaccination
measure for patients, to the ESRD QIP measure set.\250\
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\250\ Specifications for both measures available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94650.
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We were also interested in public comment on data collection,
submission, and reporting for the COVID-19 vaccination measure for HCP
and the COVID-19 vaccination measure for patients. For example, we
stated that we were considering requiring reporting for these measures
on an annual basis for the performance period for each calendar year
corresponding to the associated payment year, and the reporting period
would be January 1 through December 31 annually. Based on the measures
currently being developed by the CDC that were submitted to the Measure
Applications Partnership, facilities would report the measures through
the National Healthcare Safety Network (NHSN) web-based surveillance
system. We also sought public comment from stakeholders on other ways
to collect data on COVID-19 vaccination rates at dialysis facilities
for ESRD QIP purposes and their associated costs and burdens. Given the
immediacy of the PHE for COVID-19, as well as the importance of
continuing to monitor and make publicly available COVID-19 vaccination
rates as the PHE ends, we stated that we anticipate rulemaking on this
requirement in the CY 2023 rulemaking cycle.
The comments we received and our responses are set forth below.
Comment: Several commenters expressed support for future adoption
of both COVID-19 vaccination measures. Several commenters expressed the
belief that COVID-19 vaccination measures are important because they
would help to prevent the spread of COVID-19 in a facility and would
also help to prevent mortality due to the impact of COVID-19 on an
immunocompromised patient population. A few commenters stated that such
measures would help encourage COVID-19 vaccination for both staff and
patients at ESRD facilities. One commenter noted that the nature of
treatment sessions in the dialysis care setting may make other COVID-19
mitigation strategies less effective.
A few commenters expressed support for the possible adoption of
both COVID-19 vaccination measures, noting that making such data
publicly available would help patients make informed choices. A few
commenters expressed support for reporting possible COVID-19
vaccination measures through NHSN as it already does so and therefore
would be less burdensome.
Several commenters expressed support for tracking and reporting
COVID-19 vaccination rates among HCPs and ESRD patients on Care Compare
or Dialysis Facility Compare in order to help patients make informed
decisions when choosing a dialysis facility. One commenter expressed
support the application of a uniform reporting metric for COVID-19
vaccination among HCPs and patients across all Medicare-covered health
settings.
A few commenters expressed support for all efforts to increase
vaccination coverage among HCPs for their own safety and for patient
safety as well. One commenter expressed its belief that all medically-
eligible HCPs should be vaccinated against COVID-19.
A few commenters expressed support for the COVID-19 Vaccination
among ESRD patients measure. One commenter expressed the belief that it
may be useful for the public to know the percent of patients vaccinated
at a facility.
Response: We thank the commenters for their support, and will take
commenters' feedback into consideration for future rulemaking.
Comment: Although several commenters expressed support for
vaccination efforts and the belief that patients and HCPs should follow
CDC vaccination guidelines, these commenters did not support the
inclusion of COVID-19 vaccination measures in the ESRD QIP. A few
commenters recommended that COVID-19 vaccination measures should not be
added to the ESRD QIP, noting the MAP's initial hesitancy to recommend
the measures. A few commenters expressed the belief that such measures
would not help to address vaccine hesitancy among patients and HCPs,
and suggested that Federal agencies
[[Page 61941]]
coordinate vaccination education and outreach efforts instead. A few
commenters expressed concern that including COVID-19 vaccination
measures in the ESRD QIP would hold facilities accountable for
vaccination rates of patients and HCPs, noting that the individual
decision to get vaccinated is beyond the facility's control.
One commenter recommended that such measures incorporate factors
that take into account facility vaccination efforts, rather than a
numeric threshold. One commenter expressed support for including the
COVID-19 vaccination measures as performance measures in the ESRD QIP.
One commenter recommended that such measures be included in the ESRD
QIP as reporting measures.
Response: We thank the commenters for their feedback, and will take
this input into consideration for future rulemaking. We note that the
MAP now recommends both COVID-19 vaccination measures for inclusion in
the ESRD QIP.\251\ We also note that the COVID-19 vaccination measures
that we describe in this final rule and are considering for adoption in
future rulemaking would be reporting measures. Under these measures,
facilities would only be required to report vaccination rates and would
not be penalized based on the vaccination rates themselves.
---------------------------------------------------------------------------
\251\ Measure Applications Partnership. 2020-2021 MAP Final
Recommendations. Accessed on September 29, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
---------------------------------------------------------------------------
Comment: Several commenters expressed concern that establishing the
specifications for such measures would be challenging due to changing
COVID-19 vaccination guidelines and differences in regional policies,
which may undermine the validity or reliability of a COVID-19
vaccination measure. A few commenters requested that CMS provide more
specific details regarding proposed vaccination measure specifications,
including defined numerators and denominators, as well as inclusion and
exclusion criteria.
A few commenters expressed concern that defining the denominator
for the COVID-19 HCP Vaccination measure will be challenging because
many ESRD facilities are parts of larger organizations and may share
staff who spend some time working in the ESRD unit or facility and time
working elsewhere. One commenter requested that the possible COVID-19
Vaccination among HCP measure limit data collection to HCPs employed by
the dialysis organizations and only require the reporting of
information within the facilities' purview, noting that the CDC is able
to obtain non-clinic staff information directly from providers.
Response: We thank the commenters for their feedback, and will take
this input into consideration for future rulemaking. We acknowledge
that measure specifications may evolve based on changes to COVID-19
vaccination guidelines, and would provide more specific details
regarding measure specifications in future rulemaking as part of our
proposals to adopt the COVID-19 vaccination measures.
Comment: A few commenters expressed concern that implementing such
measures would result in staff quitting in order to avoid vaccination,
which would in turn negatively impact patient care.
Response: We acknowledge that staffing shortages are a national
issue, especially for the healthcare system. However, we disagree that
staffing shortages would impact patient safety more than unvaccinated
HCPs. We believe that vaccination is one of the most effective tools
right now for protecting an immunocompromised patient population that
has particularly high mortality rates due to COVID-19 infection. We
also note that the COVID-19 Vaccination among HCP measure that we are
considering for future adoption would not require vaccination, but
would rather require facilities to report vaccination rates.
Comment: One commenter recommended that patients (such as children
11 and under) who are not yet eligible for vaccination under an EUA or
approval should be excluded from any vaccination measure.
Response: The current COVID-19 Vaccination among Patients measure
being considered for possible adoption in future rulemaking excludes
patients who are ineligible for vaccination.
Comment: A few commenters did not support the future inclusion of a
COVID-19 Vaccination among Patients measure. One commenter acknowledged
that a COVID-19 patient vaccination measure likely would marginally
increase and sustain vaccination rates, but expressed concern that
tying a COVID-19 patient vaccination measure to payment may have
unintended consequences such as undermining patient autonomy and
creating barriers to facility access for unvaccinated patients. One
commenter did not support the COVID-19 vaccination measure for patients
believing there is no point to collecting data that mostly reflects
patient demographics based on vaccination status, not clinical quality.
This commenter stated its belief that providers are already motivated
to ensure their patients are vaccinated given the high COVID-19
mortality rate among ESRD patients.
Response: The COVID-19 patient vaccination measure that we are
considering for adoption in future rulemaking is a reporting measure;
facilities would only be required to report vaccination rates and would
not be penalized based on actual vaccination rates. We agree that the
COVID-19 vaccination measure for patients would collect data that
indicates patient vaccination rates at an individual facility. However,
we also believe that this measure would motivate providers to ensure
their patients are vaccinated against COVID-19 and that this
information is also relevant to patient safety since a facility's
vaccination rates would be important for patients to know when choosing
an individual facility for treatment.
3. Advancing to Digital Quality Measurement and the Use of Fast
Healthcare Interoperability Resources (FHIR)
We aim to move fully to digital quality measurement in CMS quality
reporting and value-based purchasing programs by 2025. As part of this
modernization of our quality measurement enterprise, we issued a
request for information (RFI). The purpose of this RFI was to gather
broad public input solely for planning purposes for our transition to
digital quality measurement. Any updates to specific program
requirements related to providing data for quality measurement and
reporting provisions would be addressed through future rulemaking, as
necessary. This RFI contained four parts:
Background. This part provided information on our quality
measurement programs and our goal to move fully to digital quality
measurement by 2025. This part also provided a summary of other recent
HHS policy developments that are advancing interoperability and could
support our move towards full digital quality measurement.
Definition of Digital Quality Measures (dQMs). This part
provided a potential definition for dQMs. Specific requests for input
are included in the section.
Changes Under Consideration to Advance Digital Quality
Measurement: Actions in Four Areas to Transition to Digital Quality
Measures by 2025. This part introduced four possible steps that would
enable transformation of CMS' quality measurement enterprise to be
[[Page 61942]]
fully digital by 2025. Specific requests for input are included in the
section.
Solicitation of Comments. This part listed all requests
for input included in the above sections of this RFI.
a. Background
As required by law, we implemented quality measurement programs and
value-based purchasing programs across a broad range of inpatient,
outpatient, and post-acute care (PAC) settings, consistent with our
mission to improve the quality of health care for Americans through
measurement, transparency, and increasingly, value-based purchasing.
These quality programs are foundational for incentivizing value-based
care, contributing to improvements in health care, enhancing patient
outcomes, and informing consumer choice. We aim to move fully to
digital quality measurement by 2025. We acknowledge providers within
the various care and practice settings covered by our quality programs
may be at different stages of readiness, and therefore, the timeline
for achieving full digital quality measurement across our quality
reporting programs may vary.
We also continue to evolve the Medicare Promoting Interoperability
Program that advances the use of certified electronic health record
(EHR) technology, from an initial focus on electronic data capture to
enhancing information exchange and expanding quality measurement (83 FR
41634). However, reporting quality data via EHRs remains burdensome,
and our current approach to quality measurement does not readily
incorporate emerging data sources such as patient-reported outcomes
(PRO) and patient-generated health data (PGHD).\252\ There is a need to
streamline our approach to data collection, calculation, and reporting
to fully leverage clinical and patient-centered information for
measurement, improvement, and learning.
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\252\ What are patient generated health data: https://www.healthit.gov/topic/otherhot-topics/what-are-patient-generated-health-data.
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Additionally, advancements in technical standards and regulatory
initiatives to improve interoperability of healthcare data are creating
an opportunity to significantly improve our quality measurement
systems. In May 2020, we finalized interoperability requirements in the
CMS Interoperability and Patient Access final rule (85 FR 25510) to
support beneficiary access to data held by certain payers. At the same
time, the Office of the National Coordinator for Health Information
Technology (ONC) finalized policies in the ONC 21st Century Cures Act
final rule (85 FR 25642) to advance the interoperability of health IT
as defined in section 4003 of the Cures Act, including the ``complete
access, exchange, and use of all electronically accessible health
information.'' Closely working with ONC, we collaboratively identified
HL7 Fast Healthcare Interoperability Resources (FHIR[supreg]) Release
4.0.1 as the standard to support Application Programming Interface
(API) policies in both rules. ONC, on behalf of HHS, adopted the HL7
FHIR Release 4.0.1 for APIs and related implementation specifications
at 45 CFR 170.215. We believe the FHIR standard has the potential to be
a more efficient and modular standard to enable APIs. We also believe
this standard enables collaboration and information sharing, which is
essential for delivering high-quality care and better outcomes at a
lower cost. By aligning technology requirements for payers, health care
providers, and health IT developers, HHS can advance-an interoperable
health IT infrastructure that ensures providers and patients have
access to health data when and where it is needed.
In the ONC 21st Century Cures Act final rule ONC adopted a
``Standardized API for Patient and Population Services'' certification
criterion for health IT that requires the use of the FHIR Release 4 and
several implementation specifications. Health IT certified to this
criterion will offer single patient and multiple patient services that
can be accessed by third party applications (85 FR 25742).\253\ The ONC
21st Century Cures Act final rule also requires health IT developers
update their certified health IT to support the U.S. Core Data for
Interoperability (USCDI) standard.\254\ The scope of patient data
identified in the USCDI and the data standards that support this data
set are expected to evolve over time, starting with data specified in
Version 1 of the USCDI. In November 2020, ONC issued an interim final
rule with comment period extending the date when health IT developers
must make technology meeting updated certification criteria available
under the ONC Health IT Certification Program until December 31, 2022
(85 FR 70064).\255\
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\253\ Application Programming Interfaces (API) Resource Guide,
Version 1.0. Available at: https://www.healthit.gov/sites/default/files/page/2020-11/API-Resource-Guide_v1_0.pdf.
\254\ https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
\255\ Information Blocking and the ONC Health IT Certification
Program: Extension of Compliance Dates and Timeframes in Response to
the Covid-19 Public Health Emergency. https://www.govinfo.gov/content/pkg/FR-2020-11-04/pdf/2020-24376.pdf.
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The CMS Interoperability and Patient Access final rule (85 FR
25510) and program policies build on the ONC 21st Century Cures Act
final rule (85 FR 25642). The CMS Interoperability and Patient Access
final rule and policies require certain payers (for example, Medicare
Advantage organizations, Medicaid, and CHIP fee for service programs,
Medicaid managed care plans, CHIP managed care entities, and Qualified
Health Plan [QHP] issuers on the Federally-facilitated Exchanges
[FFEs]) to implement and maintain a standards-based Patient Access API
using HL7 FHIR Release 4.0.1 to make available certain data to their
enrollees and beneficiaries (called ``patients'' in the CMS
interoperability rule). These certain data include data concerning
claims and encounters, with the intent to ensure access to their own
health care information through third-party software applications. The
rule also established new Conditions of Participation for Medicare and
Medicaid participating hospitals, psychiatric hospitals, and critical
access hospitals (CAHs), requiring them to send electronic
notifications to another healthcare facility or community provider or
practitioner when a patient is admitted, discharged, or transferred (85
FR 25603). In the CY 2021 Physician Fee Schedule (PFS) final rule (85
FR 84472), we finalized a policy to align the certified EHR technology
required for use in the Promoting Interoperability programs and the
MIPS Promoting Interoperability performance category with the updates
to health IT certification criteria finalized in the ONC 21st Century
Cures Act. Under this policy, eligible clinicians, MIPS eligible
clinicians, and eligible hospitals and CAHs participating in the
Promoting Interoperability Programs, must use technology meeting the
updated certification criteria for performance and reporting periods
beginning in 2023 (85 FR 84825).
The use of APIs can also reduce long-standing barriers to quality
measurement. Currently, health IT developers are required to implement
individual measure specifications within their health IT product. The
health IT developer must also accommodate how that product connects
with the unique variety of systems within a specific care setting.\256\
[[Page 61943]]
This may be further complicated by systems which integrate a wide range
of data schemas. This process is burdensome and costly, and it is
difficult to reliably obtain high quality data across systems. As
health IT developers map their health IT data to the FHIR standard and
related implementation specifications, APIs can enable these data to be
easily accessible for measurement or other use cases, such as care
coordination, clinical decision support, and supporting patient access.
---------------------------------------------------------------------------
\256\ The Office of the National Coordinator for Health
Information Technology, Strategy on Reducing Regulatory and
Administrative Burden Relating to the Use of Health IT and EHRs,
Final Report (Feb. 2020). Available at: https://www.healthit.gov/sites/default/files/page/2020-02/BurdenReport_0.pdf.
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We believe the emerging data standardization and interoperability
enabled by APIs will support the transition to full digital quality
measurement by 2025, and are committed to exploring and seeking input
on potential solutions for the transition to digital quality
measurement as described in this RFI.
b. Definition of Digital Quality Measures
In the proposed rule, we sought to refine the definition of digital
quality measures (dQMs) to further operationalize our objective of
fully transitioning to dQMs by 2025. We previously noted dQMs use
``sources of health information that are captured and can be
transmitted electronically and via interoperable systems'' (85 FR
84845). In this RFI, we sought input on future elaboration that would
define a dQM as a software that processes digital data to produce a
measure score or measure scores. Data sources for dQMs may include
administrative systems, electronically submitted clinical assessment
data, case management systems, EHRs, instruments (for example, medical
devices and wearable devices), patient portals or applications (for
example, for collection of patient-generated health data), health
information exchanges (HIEs) or registries, and other sources. We also
noted that dQMs are intended to improve the patient experience
including quality of care, improve the health of populations, and/or
reduce costs.
We discuss one potential approach to developing dQM software in
section IV.G.3.c. of this final rule. In this section, we sought
comment on the potential definition of dQMs in this RFI.
We also sought feedback on how leveraging advances in technology
(for example, FHIR APIs) to access and electronically transmit
interoperable data for dQMs could reinforce other activities to support
quality measurement and improvement (for example, the aggregation of
data across multiple data sources, rapid-cycle feedback, and alignment
of programmatic requirements).
The transition to dQMs relies on advances in data standardization
and interoperability. As providers and payers work to implement the
required advances in interoperability over the next several years, we
will continue to support reporting of eCQMs through CMS quality
reporting programs and through the Promoting Interoperability
programs.\257\ These fully digital measures continue to be important
drivers of interoperability advancement and learning. We are currently
re-specifying and testing these measures to use FHIR rather than the
currently adopted Quality Data Model (QDM) in anticipation of the wider
use of FHIR standards. We intend to apply significant components of the
output of this work, such as the re-specified measure logic and the
learning done through measure testing with FHIR APIs, to define and
build future dQMs that take advantage of the expansion of standardized,
interoperable data.
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\257\ eCQI Resource Center, https://ecqi.healthit.gov/.
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c. Changes Under Consideration To Advance Digital Quality Measurement:
Potential Actions in Four Areas To Transition to Digital Quality
Measures by 2025
Building on the advances in interoperability and learning from
testing of FHIR-converted eCQMs, we aim to move fully to dQMs,
originating from sources of health information that are captured and
can be transmitted electronically via interoperable systems, by 2025.
To enable this transformation, we are considering further
modernizing the quality measurement enterprise in four major ways: (1)
Leverage and advance standards for digital data and obtain all EHR data
required for quality measures via provider FHIR-based APIs; (2)
redesign our quality measures to be self-contained tools; (3) better
support data aggregation; and (4) work to align measure requirements
across our reporting programs, other Federal programs and agencies, and
the private sector where appropriate.
These changes would enable us to collect and utilize more timely,
actionable, and standardized data from diverse sources and care
settings to improve the scope and quality of data used in quality
reporting and payment programs, reduce quality reporting burden, and
make results available to stakeholders in a rapid-cycle fashion. Data
collection and reporting efforts would become more efficient, supported
by advances in interoperability and data standardization. Aggregation
of data from multiple sources would allow assessments of costs and
outcomes to be measured across multiple care settings for an individual
patient or clinical conditions. We believe that aggregating data for
measurement can incorporate a more holistic assessment of an
individual's health and healthcare and produce the rich set of data
needed to enable patients and caregivers to make informed decisions by
combining data from multiple sources (for example, patient reported
data, EHR data, and claims data) for measurement.
Perhaps most importantly, these steps would help us deliver on the
full promise of quality measurement and drive us toward a learning
health system that transforms healthcare quality, safety, and
coordination and effectively measures and achieves value-based care.
The shift from a static to a learning health system hinges on the
interoperability of healthcare data, and the use of standardized data.
dQMs would leverage this interoperability to deliver on the promise of
a learning health system wherein standards-based data sharing and
analysis, rapid-cycle feedback, and quality measurement and incentives
are aligned for continuous improvement in patient-centered care.
Similarly, standardized, interoperable data used for measurement can
also be used for other use cases, such as clinical decision support and
care coordination and care decision support, which impacts health care
and care quality.
We requested comments on four potential future actions that would
enable transformation to a fully digital quality measurement enterprise
by 2025.
(1) Leveraging and Advancing Standards for Digital Data and Obtaining
All EHR Data Required for Quality Measures via Provider FHIR-Based APIs
We are considering targeting the data required for our quality
measures that utilize EHR data to be data retrieved via FHIR-based APIs
based on standardized, interoperable data. Utilizing standardized data
for EHR-based measurement (based on FHIR and associated implementation
guides) and aligning where possible with interoperability requirements
can eliminate the data collection burden providers currently experience
with required chart-abstracted quality measures and reduce the burden
of reporting digital quality measure results. We can fully leverage
this advance to adapt eCQMs and expand to other
[[Page 61944]]
dQMs through the adoption of interoperable standards across other
digital data sources. We are considering methods and approaches to
leverage the interoperability data requirements for APIs set by the ONC
21st Century Cures Act final rule for certified health technology to
support modernization of CMS quality measure reporting. As discussed
previously, these requirements will be included in certified technology
in future years (85 FR 84825), including availability of data included
in the USCDI via standards-based APIs, and CMS will require clinicians
and hospitals participating in MIPS and the Promoting Interoperability
Programs, respectively, to transition to use of certified technology
updated consistent with the 2015 Cures Edition Update (85 FR 84825).
Digital data used for measurement could expand beyond data captured
in traditional clinical settings, administrative claims data, and EHRs.
Many important data sources are not currently captured digitally, such
as survey and PGHD. We intend to work to innovate and broaden the
digital data used across the quality measurement enterprise beyond the
clinical EHR and administrative claims. Agreed upon standards for these
data, and associated implementation guides will be important for
interoperability and quality measurement. We will consider developing
clear guidelines and requirements for these digital data that align
with interoperability requirements, for example, expressing in
standards, exposing via APIs, and incentivizing technologies that
innovate data capture and interoperability.
High quality data are also essential for reliable and valid
measurement. Hence, in implementing the shift to capture all clinical
EHR data via FHIR-based APIs, we would support efforts to strengthen
and test the quality of the data obtained through FHIR-based APIs for
quality measurement. We currently conduct audits of electronic data
with functions including checks for data completeness and data
accuracy, confirmation of proper data formatting, alignment with
standards, and appropriate data cleaning. These functions would
continue and be applied to dQMs and further expanded to automate the
manual validation of the data compared to the original data source (for
example, the medical record) where possible. Analytic advancements such
as natural language processing, big data analytics, and artificial
intelligence, can support this evolution. These techniques can be
applied to validating observed patterns in data and inferences or
conclusions drawn from associations, as data are received, to ensure
high quality data are used for measurement.
We sought feedback on the goal of aligning data needed for quality
measurement with interoperability requirements and the strengths and
limitations of this approach. We also sought feedback on the importance
of and approaches to supporting inclusion of PGHD and other currently
non-standardized data. We also welcomed comment on approaches for
testing data quality and validity.
(2) Redesigning Quality Measures To Be Self-Contained Tools
We are considering approaches for deploying quality measures to
take advantage of standardized data and interoperability requirements
that have expanded flexibility and functionality compared to CMS'
current eCQMs. We are considering defining and developing dQM software
as end-to-end measure calculation solutions that retrieve data from
primarily FHIR resources maintained by providers, payers, CMS, and
others; calculate measure score(s); and produce reports. In general, we
believe to optimize the use of standardized and interoperable data, the
software solution for dQMs should do the following:
Have the flexibility to support calculation of
single or multiple quality measure(s).
Perform three functions: (i) Obtain data via
automated queries from a broad set of digital data sources (initially
from EHRs, and in the future from claims, PRO, and PGHD); (ii)
calculate the measure score according to measure logic; and (iii)
generate measure score report(s).
Be compatible with any data source systems that
implement standard interoperability requirements.
Exist separately from digital data source(s) and
respect the limitations of the functionality of those data sources.
Be tested and updated independently of the data
source systems.
Operate in accordance with health information
protection requirements under applicable laws and comply with
governance functions for health information exchange.
Have the flexibility to be deployed by
individual health systems, health IT vendors, data aggregators, and
health plans; and/or run by CMS depending on the program and measure
needs and specifications.
Be designed to enable easy installation for
supplemental uses by medical professionals and other non-technical end-
users, such as local calculation of quality measure scores or quality
improvement.
Have the flexibility to employ current and
evolving advanced analytic approaches such as natural language
processing.
Be designed to support pro-competitive practices
for development, maintenance, and implementation and diffusion of
quality measurement and related quality improvement and clinical tools
through for example the use of open-source core architecture.
We sought comment on these suggested functionalities and other
additional functionalities that quality measure tools should ideally
have particularly in the context of the pending availability of
standardized and interoperable data (for example, standardized EHR data
available via FHIR-based APIs).
We were also interested whether and how this more open, agile
strategy may facilitate broader engagement in quality measure
development, the use of tools developed for measurement for local
quality improvement, and/or the application of quality tools for
related purposes such as public health or research.
(3) Building a Pathway to Data Aggregation in Support of Quality
Measurement
Using multiple sources of collected data to inform measurement
would reduce data fragmentation (or, different pieces of data regarding
a single patient stored in many different places). Additionally, we are
also considering expanding and establishing policies and processes for
data aggregation and measure calculation by third-party aggregators
that include, but are not limited to, HIEs and clinical registries.
Qualified Clinical Data Registries and Qualified Registries that report
quality measures for eligible clinicians in the Merit-based Incentive
Payment System (MIPS) program are potential examples \258\ at 42 CFR
414.1440(b)(2)(iv) and (v) and Sec. 414.1440(c)(2)(iii) and (iv) and
can also support measure reporting. We are considering establishing
similar policies for third-party aggregators to maintain the integrity
of our measure reporting process and to encourage market innovation.
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\258\ Calendar Year (CY) 2021 Physician Fee Schedule Final Rule:
Finalized (New and Updated) Qualified Clinical Data Registry (QCDR)
and Qualified Registry Policies, https://qpp-cm-prod-content.s3.amazonaws.com/uploads/1362/QCDR%20and%20QR%20Updates%202021%20Final%20Rule%20Fact%20Sheet.pdf.
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We sought feedback on aggregation of data from multiple sources
being used
[[Page 61945]]
to inform measurement. We also sought feedback on the role data
aggregators can and should play in CMS quality measure reporting in
collaboration with providers, and how we can best facilitate and enable
aggregation.
(4) Potential Future Alignment of Measures Across Reporting Programs,
Federal and State Agencies, and the Private Sector
We are committed to using policy levers and working with
stakeholders to solve the issue of interoperable data exchange and to
transition to full digital quality measurement. We are considering the
future potential development and multi-staged implementation of a
common portfolio of dQMs across our regulated programs, agencies, and
private payers. This common portfolio would require alignment of: (1)
Measure concepts and specifications including narrative statements,
measure logic, and value sets, and (2) the individual data elements
used to build these measure specifications and calculate the measure
logic. Further, the required data elements would be limited to
standardized, interoperable data elements to the fullest extent
possible; hence, part of the alignment strategy will be the
consideration and advancement of data standards and implementation
guides for key data elements. We would coordinate closely with quality
measure developers, Federal and State agencies, and private payers to
develop and to maintain a cohesive dQM portfolio that meets our
programmatic requirements and that fully aligns across Federal and
State agencies and payers to the extent possible.
We intend for this coordination to be ongoing and allow for
continuous refinement to ensure quality measures remain aligned with
evolving healthcare practices and priorities (for example, PROs,
disparities, care coordination), and track with the transformation of
data collection, alignment with health IT module updates including
capabilities and standards adopted by ONC (for example, standards to
enable APIs). This coordination would build on the principles outlined
in HHS' National Health Quality Roadmap.\259\ It would focus on the
quality domains of safety, timeliness, efficiency, effectiveness,
equitability, and patient-centeredness. It would leverage several
existing Federal and public-private efforts including our Meaningful
Measures 2.0 Framework; the Federal Electronic Health Record
Modernization (DoD/VA); the Agency for Healthcare Research and
Quality's Clinical Decision Support Initiative; the Centers for Disease
Control and Prevention's Adapting Clinical Guidelines for the Digital
Age initiative; the Core Quality Measure Collaborative, which convenes
stakeholders from America's Health Insurance Plans (AHIP), CMS, NQF,
provider organizations, private payers, and consumers and develops
consensus on quality measures for provider specialties; and the NQF-
convened Measure Applications Partnership, which recommends measures
for use in public payment and reporting programs. We would coordinate
with HL7's ongoing work to advance FHIR resources in critical areas to
support patient care and measurement such as social determinants of
health. Through this coordination, we would identify which existing
measures could be used or evolved to be used as dQMs, in recognition of
current healthcare practice and priorities.
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\259\ Department of Health and Human Services, National Health
Quality Roadmap (May 2020). Available at: https://www.hhs.gov/sites/default/files/national-health-quality-roadmap.pdf.
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This multi-stakeholder, joint Federal and industry, made possible
and enabled by the pending advances towards true interoperability,
would yield a significantly improved quality measurement enterprise.
The success of the dQM portfolio would be enhanced by the degree to
which the measures achieve our programmatic requirements for measures
as well as the requirements of other agencies and payers.
We sought feedback on initial priority areas for the dQM portfolio
given evolving interoperability requirements (for example, measurement
areas, measure requirements, tools, and data standards). We also sought
to identify opportunities to collaborate with other Federal agencies,
states, and the private sector to adopt standards and technology-driven
solutions to address our quality measurement priorities across sectors.
d. Solicitation of Comments
We plan to continue working with other agencies and stakeholders to
coordinate and to inform any potential transition to dQMs by 2025. We
have summarized the comments to this RFI below but note that we will
not be responding to them in this final rule. We will actively consider
all input as we develop future regulatory proposals or future
subregulatory policy guidance. Any updates to specific program
requirements related to quality measurement and reporting provisions
would be addressed through separate and future notice-and-comment
rulemaking, as necessary.
As noted previously, we sought input on the future development of
the following:
Definition of Digital Quality Measures: We
sought feedback on the following as described in section IV.G.3.c.(2).:
++ Do you have feedback on the dQM definition?
++ Does this approach to defining and deploying dQMs to interface
with FHIR-based APIs seem promising? We also welcomed more specific
comments on the attributes or functions to support such an approach of
deploying dQMs.
We received comments on these topics.
Comment: Several commenters expressed support for the proposed
definition of dQM. Several commenters recommended additional clarity on
the proposed definition of dQM, including more detail on what the
measures would be, how they differ from current ESRD QIP measures, and
the sources of data for those measures. One commenter recommended that
CMS refine its definition of dQMs, focus on currently available valid
and reliable digital data sources, and set clear and specific
parameters for what they expect of dialysis providers during this
transition.
Several commenters expressed support for transitioning toward
interoperability through dQMS to interface with FHIR-based resources.
One commenter noted that FHIR cannot solve or improve data quality
alone without extensive development of FHIR extensions and profiles
noting that many ESRD-specific data elements are not part of hospital
EHR systems because they are not part of meaningful use requirements;
this commenter made recommendations for data elements to be included in
future versions of United States Core Data for Interoperability
(USCDI). One commenter recommended that CMS evaluate the progress of
developers and providers in adopting FHIR standards to ensure that the
adoption of FHIR standards is not cost-prohibitive or overly burdensome
and that CMS establish a clear timeframe for adoption of FHIR
standards, including a trial or voluntary participation period prior to
formal adoption. One commenter recommended that CMS ensure that dQMs
can be linked with patient-level data such as patient experience of
care and patient-reported outcomes. One commenter expressed support for
CMS' approach to defining and deploying dQMs on FHIR believing it has
the potential to further enhance value-based care that puts patient
interests as the focal point. This
[[Page 61946]]
commenter recommended that implementation of dQMs be gradual,
transparent, and based on robust technology. The commenter also noted
its belief that the market of software developers would very quickly be
able to respond to the CMS request for dQMs. One commenter expressed
agreement that data sources should include administrative systems,
electronically submitted clinical assessment data, case management
systems, electronic health records, instruments such as medical devices
or wearable devices, patient portals or applications, health
information exchanges or registries, and other sources. One commenter
recommended that dQMs be developed using standardized data collection
measures that enable end users to interact with quality measures in an
interoperable and consistent format and to ensure consistency in the
collection and data analysis. This commenter also recommended the use
of Smart on FHIR apps using a FHIR Questionnaire to enable powerful
data capture, reduce burden, and that would allow for the continuous
data driven development of quality measures over time, with the
software/hardware layers providing greater stability. One commenter
recommended that CMS add a digital measure confirming the presence and
accessibility of advance directive information.
Several commenters expressed concerns about shifting to a FHIR-
based application programming interface including that the utility of
an ESRD-specific FHIR standard outside of quality reporting to CMS is
limited, it introduces complicating factors, the burden may outweigh
the benefit with CMS' current focus on CROWNWeb and EQRS, it may not
achieve the data flow intended by CMS for the dialysis industry, and
that shifting to a new system does not make sense at this time. One
commenter expressed caution about the adoption of FHIR noting that the
current ESRD quality data submission process captures 90 percent of
data electronically and recommended piloting the FHIR approach to
ensure that FHIR improves quality reporting over and above EQRS. One
commenter recommended that CMS consider the burden on facilities
related to compliance, noted implementation uncertainties, and
recommended CMS allocate resources to help with the transition to new
data systems and processes. One commenter expressed concerns with
transitioning the ESRD programs to another platform and recommended
that interoperability standards should be incorporated into the EQRS.
One commenter recommended that CMS not reinvent the wheel but rather
continue to work with the kidney care community to address the next
generation of quality and data policies.
Response: 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 reporting and value-based purchasing programs by 2025. We will
continue to take all comments into account as we develop future
regulatory proposals or other guidance for our digital quality
measurement efforts.
Changes Under Consideration To Advance Digital
Quality Measurement: Actions in Four Areas To Transition to Digital
Quality Measures by 2025
++ We sought feedback on the following as described in section
IV.G.3.c.(1). of this final rule:
--Do you agree with the goal of aligning data needed for quality
measurement with that required for interoperability? What are the
strengths and limitations of this approach?
--How important is a data standardization approach that also supports
inclusion of PGHD and other currently non-standardized data?
--What are possible approaches for testing data quality and validity?
We received comments on these topics.
Comments: Several commenters expressed support for the goal of
aligning data needed with interoperability. One commenter expressed its
belief that quality measurement data must be aligned with and based on
tools and methods of interoperability within healthcare believing this
is core to the achievement of value-based healthcare. This commenter
also noted its belief that aligning the incentives for all major
stakeholders in healthcare (patients, providers, payers, regulators) is
key to enabling a robust healthcare system and that when quality is
measured according to the patient through the proxy measures of
outcomes and cost of care, having data that are interoperable among
these stakeholders is crucial. One commenter expressed support
conceptually for the goal of aligning data, but needed more clarity on
the specific quality measures CMS is considering for these purposes.
One commenter recommended approaches for standardization including
that CMS develop: (1) Standard sets of outcomes measures only utilize
validated PROMs as defined by ISOQOL validation guidelines; (2)
strictly defined standard sets (standardized outcome definition
including allowed response options, validated PROMs and defined data
collection time points) ensures consistency in data collection and
allow for consistent data quality checks; and (3) variables used in
standard sets mapped to SNOMED/LOINC concepts allow for in-depth data
validity audits. One commenter recommended that CMS establish guidance
to ensure data security and to define roles and responsibilities
regarding data validation and data cleaning. This commenter also noted
that data validation and cleaning is currently managed by third party
intermediaries and is necessary to maintain measure integrity and for
reducing provider burden.
One commenter expressed its concerns with standardization including
burden on providers and questioned the value of moving from a
standardized data format that already serves 90 percent of the dialysis
community to an interoperability format that is standardized for data
movement between providers beyond the dialysis industry.
A few commenters expressed concerns with the inclusion of patient
generated health data and other currently non-standardized data into a
data standardized approach. One commenter noted that CMS' definition of
patient gathered health data is overly broad. One commenter expressed
its belief that such data elements will vary by therapeutic area and be
difficult to standardize. One commenter expressed its belief that
additional research is needed prior to integration of patient-generated
health data into quality measurement believing that while the data can
augment the overall picture of health, it can be full of bias, noise,
and variability.
Response: 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 reporting and value-based purchasing programs by 2025. We will
continue to take all comments into account as we develop future
regulatory proposals or other guidance for our digital quality
measurement efforts.
++ We sought feedback on the following as described in section
IV.G.3.c.(2). of this final rule:
--What functionalities, described in section IV.G.3.c.(2). of this
final rule
[[Page 61947]]
or others, should quality measure tools ideally have in the context of
the pending availability of standardized and interoperable data (for
example, standardized EHR data available via FHIR-based APIs)?
--How would this more open, agile strategy for end-to-end measure
calculation facilitate broader engagement in quality measure
development, the use of tools developed for measurement for local
quality improvement, and/or the application of quality tools for
related purposes such as public health or research?
We received comments on these topics.
Comments: One commenter recommended common measure sets that gather
data based on standard ontologies (for example, ICD-10, SNOMED-CT)
believing that the use of resources that enable the use of shareable,
digital data need be part of quality measure tools. The commenter also
noted that the use of such measure sets, such as ICHOM Standard Sets,
are also essential when on FHIR in a fully interoperable context.
One commenter expressed its belief that broader engagement would
lead to incremental gains on quality measure development noting that
CMS already provides its contracted measure developers with access to
the CROWNWeb and EQRS data for measure development and to the community
via USRDS, an NIH sponsored registry, and noted that FHIR API may
provide these data in a timelier fashion than providing data files.
One commenter noted that international experience has shown that
open cycle work groups, developed under an agile method, leads to the
establishment of value based healthcare in a manner that works best for
patient outcomes, and in a manner that develops the standards in a way
that is independent to the payment rate-setting development process,
which can lead to better outcomes for patients and better methods for
data collection for providers. This commenter also expressed its belief
that making measure collection seamless through the use of standard
ontologies and FHIR-based API apps will allow both large scale data
collection for use in value-based healthcare initiatives and the local
usage of data for improvement of care as well as reducing reporting
burden.
One commenter expressed concern that the investments and progress
the ESRD community has made to develop the current digital quality
framework would be reversed with the adoption of a third new digital
quality measurement approach.
Response: 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 reporting and value-based purchasing programs by 2025. We will
continue to take all comments into account as we develop future
regulatory proposals or other guidance for our digital quality
measurement efforts.
++ We sought feedback on the following as described in section
IV.G.3.c.(3). of this final rule:
--Do you have feedback on policy considerations for aggregation of data
from multiple sources being used to inform measurement?
--Do you have feedback on the role data aggregators can and should play
in CMS quality measure reporting in collaboration with providers? How
can CMS best facilitate and enable aggregation?
We received comments on these topics.
Comments: One commenter expressed support for CMS gathering data
from multiple sources to inform quality measurement; however, this
commenter also expressed caution about the use of FHIR API as the most
appropriate digital data collection method. One commenter expressed its
belief that CMS is best served to very early define the format in which
they need to have the measures reported and that an open publication of
the requested data formats and annotation, for example, a common data
model, is the key to initiate a health market adjustment. This
commenter recommended that CMS set forth policy that requires the
collection of data using standardized measure sets, based on easily
collectable data (using standard ontologies and PGHD tools), and
transported using the FHIR interoperable transport API.
A few commenters expressed their belief that aggregation of data
from multiple sources is not an issue for the renal community noting
the use of CROWNWeb, EQRS, and HIE.
A few commenters expressed their concerns with the use of data
aggregators. One commenter expressed its concerns that moving to an
undefined new standard under FHIR will require significant additional
investments from industry when such investments already have been made
to create the highly efficient HIE and other means of electronic data
submission. One commenter expressed its belief that there is no need
for data aggregators for the ESRD quality program because of existing
data standardization and availability of required data in provider EMRs
or CMS claims data noting the successful ability of 90 percent of the
industry to submit data electronically in a standard format via batch,
and the remaining 10 percent to do the same via manual interface;
however, this commenter also noted that if CMS requires data elements
that are not able to be collected by dialysis providers then data
aggregators may be helpful.
Response: 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 reporting and value-based purchasing programs by 2025. We will
continue to take all comments into account as we develop future
regulatory proposals or other guidance for our digital quality
measurement efforts.
++ We sought feedback on the following as described in section
IV.G.3.c.(4). of this final rule:
--What are initial priority areas for the dQM portfolio (for example,
measurement areas, measure requirements, tools)?
--We also sought to identify opportunities to collaborate with other
Federal agencies, states, and the private sector to adopt standards and
technology-driven solutions to address our quality measurement
priorities and across sectors.
We received comments on these topics.
Comments: One commenter recommended that the priority areas for the
dQM portfolio be around health equity and quality measures for which
data supports that additional access to care can improve quality
outcomes.
A few commenters had recommendations for CMS collaboration related
to adopting standards and technology-driven solutions. One commenter
recommended opportunities to collaborate with the Social Security
Administration, Centers for Disease Control and Prevention, and the
United Network for Organ Sharing. One commenter recommended
collaboration with an objective, independent and patient centered non-
profit organization that collaborates with patients and healthcare
professionals. One commenter recommended that CMS work with states and
other Federal agencies who might require these same data elements as an
API from EQRS then that could create benefit and reduce administrative
burden.
Response: We appreciate all of the comments on and interest in this
topic.
[[Page 61948]]
We believe that this input is very valuable in the continuing
development of our transition to digital quality measurement in CMS
quality reporting and value-based purchasing programs by 2025. We will
continue to take all comments into account as we develop future
regulatory proposals or other guidance for our digital quality
measurement efforts.
V. End-Stage Renal Disease Treatment Choices (ETC) Model
A. Background
1. Overview of the ETC Model
As described in the Specialty Care Models final rule (85 FR 61114),
beneficiaries with ESRD are among the most medically fragile and high-
cost populations served by the Medicare program. ESRD Beneficiaries
require dialysis or kidney transplantation to survive, and the majority
of ESRD Beneficiaries receiving dialysis receive hemodialysis in an
ESRD facility. However, as described in the Specialty Care Models final
rule, alternative renal replacement modalities to in-center
hemodialysis, including home dialysis and kidney transplantation, are
associated with improved clinical outcomes, better quality of life, and
lower costs than in-center hemodialysis (85 FR 61264).
Section 1115A of the Act authorizes the Innovation Center to test
innovative payment and service delivery models expected to reduce
Medicare, Medicaid, and CHIP expenditures while preserving or enhancing
the quality of care furnished to such programs' beneficiaries. The
purpose of the ETC Model is to test the effectiveness of adjusting
certain Medicare payments to ESRD facilities and Managing Clinicians to
encourage greater utilization of home dialysis and kidney
transplantation, support beneficiary modality choice, reduce Medicare
expenditures, and preserve or enhance the quality of care.
The ETC Model is a mandatory payment model, as we seek to test the
effect of payment incentives on availability and choice of treatment
modality among a diverse group of providers and suppliers. ESRD
facilities and Managing Clinicians are selected as ETC Participants
based on their location in Selected Geographic Areas--a set of 30
percent of Hospital Referral Regions (HRRs) that have been randomly
selected to be included in the ETC Model, as well as HRRs with at least
20 percent of component ZIP codes \260\ located in Maryland. CMS
excludes all U.S. Territories from the Selected Geographic Areas.
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\260\ ZIP code\TM\ is a trademark of the United States Postal
Service.
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Under the ETC Model, ETC Participants are subject to two payment
adjustments. The first is the Home Dialysis Payment Adjustment (HDPA),
which is an upward adjustment on certain payments made to participating
ESRD facilities under the ESRD PPS on home dialysis claims, and an
upward adjustment to the MCP paid to participating Managing Clinicians
on home dialysis-related claims. The HDPA applies to claims with claim
service dates beginning in January 1, 2021, and ending on December 31,
2023.
The second payment adjustment under the ETC Model is the
Performance Payment Adjustment (PPA). For the PPA, we assess ETC
Participants' home dialysis rate and transplant rate during a
Measurement Year (MY), which includes 12 months of performance data.
Each MY overlaps with the previous MY, if any, and the subsequent MY,
if any, for a period of 6 months. Each MY has a corresponding PPA
Period--a 6-month period which begins 6 months after the conclusion of
the MY. We adjust certain payments for ETC Participants during the PPA
Period based on the ETC Participant's home dialysis rate and transplant
rate, calculated as the sum of the transplant waitlist rate and the
living donor transplant rate, during the corresponding MY. Based on an
ETC Participant's achievement in relation to benchmarks based on the
home dialysis rate and transplant rate observed in Comparison
Geographic Areas during the Benchmark Year, and the ETC Participant's
improvement in relation to its own home dialysis rate and transplant
rate during the Benchmark Year, we make an upward or downward
adjustment to certain payments to the ETC Participant. The magnitude of
the positive and negative PPAs for ETC Participants increases over the
course of the ETC Model. These PPAs apply to claims with claim service
dates beginning July 1, 2022, and ending June 30, 2027.
2. Summary of Proposed Changes to the ETC Model
The proposed rule, titled ``Medicare Program; End-Stage Renal
Disease Prospective Payment System, Payment for Renal Dialysis Services
Furnished to Individuals With Acute Kidney Injury; End-Stage Renal
Disease Quality Incentive Program, and End-Stage Renal Disease
Treatment Choices Model'' (85 FR 36322 through 36437), referred to
herein as the ``CY 2022 ESRD PPS proposed rule,'' was published in the
Federal Register on July 9, 2021. In the CY 2022 ESRD PPS proposed
rule, we proposed a number of policy changes to the ETC Model beginning
for the third Measurement Year (MY3) of the Model, which begins January
1, 2022. We proposed changes to the methodology for attributing Pre-
emptive LDT Beneficiaries to Managing Clinicians to better reflect the
care relationship between beneficiaries who receive pre-emptive LDT
transplants and the Managing Clinicians who provide their care. We
proposed to include nocturnal in-center dialysis in the numerator of
the home dialysis rate calculation for ESRD facilities not owned in
whole or in part by a large dialysis organization (LDO) as well as
Managing Clinicians, to incentivize additional alternative renal
replacement modalities. In addition, we proposed to exclude
beneficiaries who are diagnosed with and receiving treatment with
chemotherapy or radiation for vital solid organ cancers from the
transplant rate to align with common transplant center requirements.
We proposed to modify the PPA achievement benchmarking methodology
to increase achievement benchmarks by 10 percent above rates observed
in Comparison Geographic Areas every two MYs, beginning for MY3 (2022).
We proposed to stratify PPA achievement benchmarks based on the
proportion of attributed beneficiaries who are dually-eligible for
Medicare and Medicaid or receive the LIS during the MY, and to
introduce the Health Equity Incentive to the PPA improvement scoring
methodology, both in an effort to encourage ETC Participants to address
disparities in renal replacement modality choice among beneficiaries
with lower socioeconomic status. We proposed to modify the PPA
improvement benchmarking and scoring methodology to ensure an ETC
Participant can receive an improvement score even if its home dialysis
rate or transplant rate was zero during the relevant Benchmark Year.
We proposed to add processes and requirements for CMS to share
certain model data with ETC Participants. We also proposed an
additional programmatic waiver as necessary solely for purposes of
allowing Managing Clinicians who are ETC participants to furnish kidney
disease patient education services via telehealth under the ETC Model.
In addition, we proposed to permit Managing Clinicians who are ETC
Participants to reduce or waive beneficiary coinsurance for kidney
disease patient education services, subject to certain requirements. In
the CY 2022 ESRD PPS proposed rule, we stated our expectation that the
proposed changes would continue to
[[Page 61949]]
promote the larger goals of increased renal replacement modality choice
and are based on many of the issues we laid out in the Specialty Care
Models final rule as issues for which CMS was considering further
rulemaking, including updating benchmarks for ETC Participants and
adjusting model parameters based on our implementation experience (86
FR 36376).
3. Impact of the Changes on the ETC Model Evaluation
As we described in the Specialty Care Models final rule, an
evaluation of the ETC Model will be conducted in accordance with
section 1115A(b)(4) of the Act, which requires the Secretary to
evaluate each model tested by the Innovation Center. We noted that we
believe an independent evaluation of the Model is necessary to
understand the impacts of the Model on quality of care and Medicare
program expenditures (85 FR 61345).
In the CY 2022 ESRD PPS proposed rule (86 FR 36376), we proposed to
update the evaluation plan presented in the Specialty Care Models final
rule to account for all the policies in that proposed rule, if
finalized. However, we noted that changes in the construction of the
PPA would have no impact on the evaluation approach to analyzing the
final PPA values. This is because the evaluation plan already includes
a consideration of the final PPA values, rather than an evaluation of
each step in the PPA calculation. However, we stated our expectation
that we would conduct subgroup analyses in the evaluation to determine
the effect of the proposed Health Equity Incentive, if finalized, in
reducing health disparities among beneficiaries with lower
socioeconomic status.
As part of the detailed economic analysis included in the CY 2022
ESRD PPS proposed rule and in section VIII.D.4 of this final rule, the
transplant waitlist benchmarks were annually inflated by approximately
3-percentage points growth. This was a change from the Specialty Care
Models final rule (85 FR 61352), in which the waitlist benchmarks were
annually inflated by approximately 2-percentage points growth observed
during years 2017 through 2019 to project rates of growth. By
increasing the expected effect to a 3-percentage point change, we
improve our ability to detect such an effect at the ETC Model's current
size. In the Specialty Care Models final rule, we stated that to detect
a 2-percentage point increase in the transplant waitlist rate, we would
need 30 percent of the 306 HRRs in order to detect an effect of this
size with 80 percent power and an alpha of 0.05. Further, we stated
that a model of this size would be large enough to detect a one and
one-half percentage point change in the home dialysis rate (85 FR
61280). In the CY 2022 ESRD PPS proposed rule (86 FR 36376), we
clarified that our unadjusted power calculations show that the model
requires 30 percent of the 306 HRRs to detect the one and one-half
percentage point change in the home dialysis rate with 80 percent power
and an alpha of 0.05. Given the updated expectation that the transplant
waitlist rate is likely to increase by 3-percentage points as a result
of the ETC Model, the power analysis shows the evaluation would also
have sufficient sample size to detect, as statistically significant, a
3-percentage point change in the transplant waitlist rate with 80
percent power and an alpha of 0.05.
We did not receive any comments regarding our proposal to update
the evaluation plan presented in the Specialty Care Models final rule
to account for all the policies in the CY 2022 ESRD PPS proposed rule,
if finalized. We are therefore finalizing our proposal and will modify
the model evaluation to analyze the impact of the policies finalized in
this final rule.
B. Summary of the Proposed Provisions, Public Comments, Responses to
Comments, and Finalized Policies for the ETC Model
The CY 2022 ESRD PPS proposed rule was published in the Federal
Register on July 9, 2021, with a comment period that ended on August
31, 2021. In that proposed rule, we proposed to make a number of
changes to the ETC Model, to begin January 1, 2022, as described
previously in section I.B.4 of this rule. We received 64 timely public
comments on our proposals, including comments from: ESRD facilities;
national renal, nephrologist, and patient organizations; patients;
manufacturers; health care systems; and individual clinicians,
including nephrologists, nurses, and social workers.
We also received comments related to issues that we did not discuss
in the CY 2022 ESRD PPS proposed rule. These include, for example,
comments recommending that CMS incorporate staff-assisted home dialysis
into the ETC Model, support the training and education of home dialysis
nurses, and including transplant providers as ETC Participants. These
comments expressed concern over implementing home dialysis programs or
the negative payment adjustments included in the Model. While we are
generally not addressing those comments in this final rule, we thank
the commenters for their input and may consider their recommendations
in future rulemaking.
In this final rule, we provide a summary of each proposed
provision, a summary of the public comments received and our responses
to them, and the policies we are finalizing for the ETC Model. These
policies take effect January 1, 2022, unless otherwise specified.
Comment: Many commenters supported the goals of the ETC Model. Some
of these commenters stated that they appreciate the effort to advance
home dialysis during the COVID-19 pandemic since dialyzing at home
allows patients to socially distance and avoid going into hospitals or
medical centers.
Response: We thank the commenters for the support of the Model's
goals.
Comment: One commenter suggested that CMS implement the ETC Model
nationwide in order to improve quality of care for all ESRD
beneficiaries.
Response: Section 1115A of the Act authorizes the Secretary to test
payment and service delivery models intended to reduce Medicare costs
while preserving or improving care quality that, if effective, are
considered for expansion to the Medicare program. As noted in the
Specialty Care Models final rule (85 FR 61280), the randomized
selection of 30 percent of HRRs allows CMS sufficient statistical power
to assess the effect of the ETC Model. If the test of the ETC Model
satisfies the criteria for expansion in section 1115A(c) of the Act,
CMS may consider expanding the duration and scope of the ETC Model,
including on a nationwide basis.
Comment: One commenter suggested that the ETC Model be an Advanced
Alternative Payment Model (APM) allowing ETC Participants to be
eligible as qualifying APM participants (QP), similar to what is
proposed for the Radiation Oncology (RO) Model.
Regarding the commenter's reference to the RO Model, we finalized
our proposal that the RO Model be designed to qualify as an Advanced
APM and MIPS APM in the Specialty Care Models final rule (85 FR 61231
through 61238).
Response: As noted in the Specialty Care Models final rule (85 FR
61326), modifying the ETC Model to be an Advanced APM would subject ETC
Participants to significant downside risk from the outset, which we
believe would put many ETC Participants in a difficult financial
position. As further noted in the Specialty Care Models final rule (85
FR 61274), Managing Clinicians may simultaneously participate in the
ETC Model and the complementary Kidney Care Choices Model, a voluntary
[[Page 61950]]
model we anticipate will meet the criteria to be an Advanced APM
beginning in 2022.
Comment: Several commenters urged that patients should have the
choice of modality that works best for them, and the ETC Model should
support patient choices.
Response: We appreciate the commenters' feedback to support
beneficiary choice of treatment modality. The ETC Model, as described
in the Specialty Care Models final rule, aims to support beneficiaries
choosing alternatives to in-center dialysis. Additionally, ETC
Participants are subject to provisions protecting beneficiary freedom
of choice set forth at Sec. 512.120 of our regulations, as discussed
in the Specialty Care Models final rule (85 FR 61339).
1. Technical Clarifications
For ESRD facilities that are ETC Participants, the ETC Model makes
certain upward and downward adjustments to the Adjusted ESRD PPS per
Treatment Base Rate for certain dialysis claims via the Home Dialysis
Payment Adjustment (HDPA) and the Performance Payment Adjustment (PPA).
The term ``Adjusted ESRD PPS per Treatment Base Rate'' is defined at 42
CFR 512.310 as the per-treatment payment amount as defined in Sec.
413.230 of this chapter, including patient-level adjustments and
facility-level adjustments, and excluding any applicable training
adjustment, add-on payment amount, outlier payment amount, TDAPA
amount, and TPNIES amount. In the CY 2022 ESRD PPS proposed rule (86 FR
36376), we clarified the claims that are subject to adjustment under
the ETC Model. Specifically, as Sec. 413.230 is specific to the
calculation of payment amounts under the ESRD PPS, we clarify that the
HDPA and PPA do not apply to claims from ESRD facilities that are not
paid under ESRD PPS and are instead paid through other Medicare payment
systems.
We are also updating the name of one of the sources of data used
throughout the ETC Model. In the Specialty Care Models final rule, we
specified that one source of data for the ETC Model is CROWNWeb, a data
management system that CMS uses to collect data from ESRD facilities
(85 FR 61317). As we explained in the CY 2022 ESRD PPS proposed rule
(86 FR 36376), since publication of the Specialty Care Models final
rule, CMS has replaced CROWNWeb with the End Stage Renal Disease
Quality Reporting System (EQRS). As such, we will refer to CROWNWeb for
data that was generated before the change to EQRS, which CMS began
using in 2020, and EQRS for data that was generated after the change to
EQRS.
The following is a summary of the comments received on our
technical clarifications related to claims subject to adjustment under
the ETC Model and the replacement of CROWNWeb data with EQRS data and
our responses.
Comment: A few commenters stated that they support the technical
clarification that the HDPA and PPA do not apply to claims from ESRD
facilities that are not paid under ESRD PPS and are instead paid
through other Medicare payment systems.
Response: We appreciate commenters' support for this technical
clarification.
Comment: A few commenters stated that they support the technical
clarification that the ETC Model will refer to EQRS data in place of
CROWNWeb data.
Response: We appreciate commenters' support for this technical
clarification.
Comment: A few commenters expressed concerns related to the
challenges faced during the transition from CROWNWeb to EQRS, and
resulting concerns over data quality.
Response: As discussed elsewhere in this final rule, we are aware
of concerns related to the transition from CROWNWeb to EQRS. For the
purposes of the ETC Model, we will continue to use the best data
available and will work with ETC Participants to address any data
issues that arise.
2. Performance Payment Adjustment (PPA) Beneficiary Attribution for
Living Kidney Donor Transplants
In the Specialty Care Models final rule (85 FR 61297), we
established that beneficiaries are attributed to Managing Clinicians
for the purposes of calculating the home dialysis rate and transplant
rate. For the home dialysis rate and the transplant waitlist and living
donor kidney transplant portions of the transplant rate, as described
in 42 CFR 512.360(c)(2)(i), an ESRD Beneficiary is generally attributed
to the Managing Clinician with the earliest monthly capitation payment
(MCP) claim billed during the month. If more than one Managing
Clinician submits a claim for the MCP furnished to a single ESRD
Beneficiary with the same earliest claim service date at the claim line
through date for the month, the ESRD Beneficiary is randomly attributed
to one of these Managing Clinicians.
However, a beneficiary who receives a pre-emptive living donor
transplant (Pre-emptive LDT Beneficiary) is not on dialysis and
therefore cannot be attributed to a Managing Clinician using an MCP
claim. As a result, under Sec. 512.360(c)(2)(ii), a Pre-emptive LDT
Beneficiary is generally attributed to the Managing Clinician with whom
the Pre-emptive LDT Beneficiary had the most claims between the start
of the MY and the month of the transplant. If no Managing Clinician has
had the plurality of claims for a given Pre-emptive LDT Beneficiary
such that multiple Managing Clinicians each had the same number of
claims for that beneficiary during the MY, the Pre-emptive LDT
Beneficiary is attributed to the Managing Clinician associated with the
latest claim service date during the MY up to and including the month
of the transplant, as described in Sec. 512.360(c)(2)(ii)(A). If no
Managing Clinician had the plurality of claims for a given Pre-emptive
LDT Beneficiary such that multiple Managing Clinicians each had the
same number of services for that beneficiary during the MY, and more
than one of those Managing Clinicians had the latest claim service date
during the MY up to and including the month of the transplant, the Pre-
emptive LDT Beneficiary is randomly attributed to one of these Managing
Clinicians, as described in Sec. 512.360(c)(2)(ii)(B).
As stated in the CY 2022 ESRD PPS proposed rule (86 FR 36377), upon
further review of the beneficiary attribution methodology for living
donor kidney transplants, we realized that an unintended consequence of
the current attribution methodology is that Pre-emptive LDT
Beneficiaries may be attributed to the nephrologist who manages their
transplant, not the Managing Clinician who has seen them through the
living donor transplant process. As stated in the CY 2022 ESRD PPS
proposed rule, to avoid this effect, CMS believes it is necessary to
update the attribution methodology for Pre-emptive LDT Beneficiaries.
Living donor transplants are relatively rare events that require
nephrologist support over time in order to inform beneficiaries of
their transplant options and to assist them in finding a living donor.
However, the current Pre-emptive LDT Beneficiary attribution
methodology is based on visits from the beginning of a MY. As a result,
if a Pre-emptive LDT Beneficiary has a transplant early in a MY, the
beneficiary may be attributed to a transplant nephrologist who may have
had only a single visit with the beneficiary, rather than the Managing
Clinician who oversaw the largest share of the care that led to the
beneficiary receiving the living donor transplant.
As a result, we proposed to update the attribution methodology for
Pre-emptive
[[Page 61951]]
LDT Beneficiaries to Managing Clinicians, beginning for MY3, in new
provisions at Sec. 512.360(c)(2)(iii). Rather than attributing a Pre-
emptive LDT Beneficiary to the Managing Clinician with the plurality of
claims from the start of the MY and the month of the transplant,
beginning for MY3, we proposed to attribute Pre-emptive LDT
Beneficiaries to the Managing Clinician with whom the beneficiary has
had the most claims during the 365 days prior to the transplant date.
Further, we proposed that if no Managing Clinician has had the most
claims for the Pre-emptive LDT Beneficiary such that multiple Managing
Clinicians each had the same number of claims for that beneficiary in
the 365 days preceding the date of the transplant, the Pre-emptive LDT
Beneficiary would be attributed to the Managing Clinician associated
with the latest claim service date at the claim line through date
during the 365 days preceding the date of the transplant. We proposed
that if more than one of those Managing Clinicians had the latest claim
service date at the claim line through date during the 365 days
preceding the date of the transplant, the Pre-emptive LDT Beneficiary
would be randomly attributed to one of these Managing Clinicians. We
proposed that the Pre-emptive LDT Beneficiary would be considered
eligible for attribution to a Managing Clinician under this proposed
new Sec. 512.360(c)(2)(iii) if the Pre-emptive LDT Beneficiary has at
least 1 eligible-month during the 12-month period that includes the
month of the transplant and the 11 months prior to the transplant
month. We proposed that an eligible month would refer to a month during
which the Pre-emptive LDT Beneficiary not does not meet exclusion
criteria in Sec. 512.360(b). We proposed changes for Pre-emptive LDT
Beneficiary attribution to Managing Clinicians in order to identify and
attribute Pre-emptive LDT Beneficiaries to the Managing Clinician who
assisted the Beneficiary through the living donor transplant process.
We sought comment on these proposed changes for Pre-emptive LDT
Beneficiary attribution to Managing Clinicians beginning for MY3 in
proposed new Sec. 512.360(c)(2)(iii).
The following is a summary of the comments received on the proposed
changes for Pre-emptive LDT Beneficiary attribution to Managing
Clinicians beginning for MY3 and our responses.
Comment: Several commenters supported our proposal to update the
attribution methodology for Pre-emptive LDT Beneficiaries to Managing
Clinicians to identify and attribute Pre-emptive LDT Beneficiaries to
the Managing Clinician that assisted the Beneficiary through the living
donor transplant process.
Response: We appreciate the support and feedback.
Comment: A few commenters expressed that the proposed changes to
the attribution methodology for Pre-emptive LDT Beneficiaries would
have a limited impact, due to the small number of Pre-emptive LDT
Beneficiaries.
Response: We appreciate the feedback from commenters and recognize
the small number of Pre-emptive LDT Beneficiaries. We nonetheless
believe it is necessary to update this methodology to ensure that those
Pre-emptive LDT Beneficiaries are attributed to the Managing Clinician
who oversaw the largest share of the care that led to the beneficiary
receiving the living donor transplant to more accurately measure
Managing Clinician performance.
Final Rule Action: After considering public comments, we are
finalizing our proposal in our regulation at Sec. 512.360(c)(2)(iii)
to change Pre-emptive LDT Beneficiary attribution to Managing
Clinicians beginning for MY3, without modification.
3. PPA Home Dialysis Rate
a. Background on Home Dialysis Rate Calculation
A primary goal of the ETC Model is to support beneficiary modality
choice by encouraging ETC Participants to support beneficiaries in
selecting alternatives to in-center dialysis. Under 42 CFR 512.365(b),
CMS includes in-center self-dialysis treatment beneficiary years in the
numerator of the home dialysis rate. Specifically, the home dialysis
rate for both Managing Clinicians and ESRD facilities is calculated as
the number of dialysis treatment beneficiary years during the MY in
which attributed beneficiaries received dialysis at home, plus one half
of the total number of dialysis treatment beneficiary years during the
MY in which the attributed beneficiaries received self-dialysis in
center. As described in the Specialty Care Models final rule, we
included self-dialysis in the home dialysis rate calculation because we
believe in-center self-dialysis may provide a gradual transition from
in-center to home dialysis, and provide beneficiaries with the time
needed to get comfortable conducting dialysis by themselves, under
medical supervision (85 FR 61306).
The denominator for the home dialysis rate is the total dialysis
treatment beneficiary years for attributed ESRD beneficiaries during
the MY, as described in Sec. Sec. 512.365(b)(1)(i) and
512.365(b)(2)(i). This includes the months during which attributed
beneficiaries received maintenance dialysis at home or in an ESRD
facility.
b. Nocturnal Dialysis
Nocturnal in-center dialysis is a form of in-center dialysis
conducted overnight for extended hours while the beneficiary is asleep.
This dialysis is longer and slower than traditional in-center dialysis,
can take more than 5 hours per treatment, and can be performed 3 to 7
days a week. As this type of in-center dialysis is conducted overnight,
it allows the beneficiary more time and flexibility to have a
continuous job, as well as a social and family life.\261\
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\261\ Wilk, Adam S., Lea, Janice P. (2019). How Extended
Hemodialysis Treatment Time Can Affect Patient Quality of Life.
Clinical Journal of the American Society of Nephrology, 23, 479-485.
doi:10.1111/hdi.12782.
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Dialysis conducted at a slower rate over a longer period of time is
also associated with positive health impacts in comparison to
traditional dialysis, including improved blood pressure control, better
phosphate control, better management of anemia and bone and mineral
metabolism, improved cardiovascular disease, increases in urea
reduction ratio, and better beneficiary quality of life
measures.262 263 264 265 266
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\262\ Burton, J. and Graham-Brown, M., 2018. Nocturnal
hemodialysis. Current Opinion in Nephrology and Hypertension, 27(6),
pp.472-477.
\263\ Kalim, S., Wald, R., Yan, A.T., Goldstein, M.B., Kiaii,
M., Xu, D., . . . Perl, J. (2018). Extended duration nocturnal
hemodialysis and changes in plasma metabolite profiles. Clinical
Journal of the American Society of Nephrology, 13(3), 436-444.
doi:10.2215/cjn.08790817.
\264\ Nesrallah, G.E., Lindsay, R.M., Cuerden, M.S., Garg, A.X.,
Port, F., Austin, P.C., . . . Suri, R.S. (2012). Intensive
hemodialysis associates with improved survival compared with
CONVENTIONAL HEMODIALYSIS. Journal of the American Society of
Nephrology, 23(4), 696-705. doi:10.1681/asn.2011070676.
\265\ Wong, B., Collister, D., Muneer, M., Storie, D., Courtney,
M., Lloyd, A., . . . Pauly, R.P. (2017). In-center nocturnal
hemodialysis versus conventional hemodialysis: A systematic review
of the evidence. American Journal of Kidney Diseases, 70(2), 218-
234. doi: 10.1053/j.ajkd.2017.01.047.
\276\ Wilk, Adam S., Lea, Janice P. (2019). How Extended
Hemodialysis Treatment Time Can Affect Patient Quality of Life.
Clinical Journal of the American Society of Nephrology, 23, 479-485.
doi:10.1111/hdi.12782.
\266\ Lacson E, Diaz-Buxo J. In-center nocturnal hemodialysis
performed thrice-weekly--a provider's perspective. Semin Dial. 2011
Nov-Dec;24(6):668-73. doi: 10.1111/j.1525-139X.2011.00998.x. Epub
2011 Nov 22. PMID: 22106828.
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In addition to the clinical benefits, nocturnal in-center dialysis
also provides an alternative to traditional in-center dialysis for
those beneficiaries for whom home dialysis is not an option
[[Page 61952]]
due to limited financial resources, housing insecurity, lack of social
support, or personal preference. For example, a beneficiary
experiencing housing insecurity may be unable to dialyze at home due to
inability to receive and store home dialysis materials. However, that
beneficiary could receive nocturnal in-center dialysis, thereby
receiving the clinical benefits of a longer, slower dialysis process
and the flexibility associated with not having to receive traditional
in-center dialysis during the day.267 268
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\267\ Bugeja A, Dacouris N, Thomas A, Marticorena R, McFarlane
P, Donnelly S, Goldstein M. In-center nocturnal hemodialysis:
Another option in the management of chronic kidney disease. Clin J
Am Soc Nephrol. 2009 Apr;4(4):778-83. doi: 10.2215/CJN.05221008.
Epub 2009 Apr 1. PMID: 19339410; PMCID: PMC2666425.
\268\ Lacson E, Diaz-Buxo J. In-center nocturnal hemodialysis
performed thrice-weekly--a provider's perspective. Semin Dial. 2011
Nov-Dec;24(6):668-73. doi: 10.1111/j.1525-139X.2011.00998.x. Epub
2011 Nov 22. PMID: 22106828.
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While nocturnal in-center dialysis offers some of the same clinical
and quality of life benefits as home dialysis in comparison to
traditional in-center dialysis, use of nocturnal in-center dialysis is
rare. Based on analyses described in the CY 2022 ESRD PPS proposed rule
and in section VIII.D.4.e of this final rule, less than 1 percent of
beneficiaries eligible for attribution to ETC Participants were
receiving self-dialysis or nocturnal in-center dialysis in 2019.
Potential limitations to nocturnal in-center dialysis utilization
include supply factors. At present, few ESRD facilities offer nocturnal
dialysis; in 2019, approximately 1 percent of ESRD facilities furnished
nocturnal in-center dialysis based on our analysis of claims data. ESRD
facilities may face staffing challenges to initiating a nocturnal
dialysis program. Potential limitations to nocturnal in-center dialysis
also include demand factors: Beneficiaries may be unaware of nocturnal
in-center dialysis, or may be averse to sleeping at an ESRD facility or
experience difficulty sleeping while receiving dialysis.\269\
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\269\ Ibid.
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c. Inclusion of Nocturnal In-Center Dialysis in Home Dialysis Rate
We proposed to modify the home dialysis rate calculation, for ETC
Participants that are either ESRD facilities not owned in whole or in
part by an LDO or Managing Clinicians, to include nocturnal in-center
dialysis in the numerator beginning for MY3. As described in the CY
2022 ESRD PPS proposed rule and previously in this section of the final
rule, we believe this modality allows beneficiaries to continue to
receive maintenance dialysis in an ESRD facility under medical
supervision, but at a time of day that is more convenient for them, and
in a manner that is associated with improved health outcomes. In
particular, in the CY 2022 ESRD PPS proposed rule (86 FR 36378), we
stated our belief that including nocturnal in-center dialysis in the
home dialysis rate may improve access to alternative renal replacement
modalities for beneficiaries who are unable to dialyze at home.
In addition to promoting access to the benefits of additional
alternative renal replacement modalities for ESRD Beneficiaries who may
not be able to dialyze at home, in the CY 2022 ESRD PPS proposed rule
we stated our belief that including nocturnal in-center dialysis in the
calculation of the home dialysis rate offers an additional pathway to
success for ETC Participants with more limited resources. As described
in the Specialty Care Models final rule, we received comments that some
ESRD facilities, particularly independent ESRD facilities or ESRD
facilities owned by small dialysis organizations, may be unable to
develop and maintain a home dialysis program (85 FR 61322 through
61324). Operating a home dialysis program requires specialized staff,
as well as upfront investment in additional equipment and
certification. Establishing a nocturnal in-center dialysis program does
not require additional equipment or certification, and may be more
feasible for independent ESRD facilities or ESRD facilities owned by
small dialysis organizations, and by extension, the Managing Clinicians
who serve their patients.
In the CY 2022 ESRD PPS proposed rule (86 FR 36378), we considered
including nocturnal in-center dialysis in the numerator of the home
dialysis rate for ESRD facilities owned in whole or in part by LDOs as
well. However, we noted in the CY 2022 ESRD PPS proposed rule that we
do not believe that ESRD facilities owned in whole or in part by LDOs
face the same resource constraints in establishing a home dialysis
program as independent ESRD facilities or ESRD facilities owned by
small dialysis organizations. ESRD facilities owned in whole or in part
by LDOs may be more likely to have access to a home dialysis program,
either in the ESRD facility itself or within the network of facilities
owned by the same parent company in that facility's aggregation group.
ESRD facilities owned in whole or in part by LDOs may also have greater
access to the upfront capital necessary to establish a home dialysis
program if they do not already have, or have access to, a home dialysis
program.
At present, there is not a single definition of what qualifies a
legal entity that owns ESRD facilities as an LDO. In general,
definitions of LDO focus on the number of ESRD facilities owned by the
legal entity. Other Innovation Center models have used such
definitions: The Comprehensive ESRD Care (CEC) Model defined an LDO as
a legal entity owning 200 or more ESRD facilities; the Kidney Care
Choices (KCC) Model defines an LDO as a legal entity owning 35 or more
ESRD facilities. Outside of Innovation Center models, definitions used
by academic researchers vary significantly. For example, in 2015, the
United States Renal Data System (USRDS), a national data registry
funded by the National Institutes of Health (NIH), defined an LDO as a
dialysis organization one that owns and operates 200 or more ESRD
facilities.\270\ Other academic research has employed thresholds as low
as owning 20 or more ESRD facilities and as high as owning 1,000 or
more ESRD facilities to consider a legal entity an
LDO.271 272 Other definitions do not focus on the number of
ESRD facilities owned, but on the relative size of dialysis
organizations in the market, or rather, the individual dialysis
organizations themselves. For example, in its March 2021 report to
Congress, the Medicare Payment Advisory Commission (MedPAC) refers to
the two largest dialysis organizations in the country as LDOs based on
their relative share of ESRD facilities and Medicare treatments.\273\
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\270\ United States Renal Data System. 2015. ``2015 Researcher's
Guide to the USRDS Database.'' https://usrds.org/media/2219/2015_usrds_researchers_guide_15.pdf.
\271\ Mehrotra R, Khawar O, Duong U, Fried L, Norris K,
Nissenson A, Kalantar-Zadeh K. Ownership patterns of dialysis units
and peritoneal dialysis in the United States: Utilization and
outcomes. Am J Kidney Dis. 2009 Aug;54(2):289-98. doi: 10.1053/
j.ajkd.2009.01.262. Epub 2009 Apr 8. PMID: 19359081.
\272\ Gander JC, Zhang X, Ross K, et al. Association Between
Dialysis Facility Ownership and Access to Kidney Transplantation.
JAMA. 2019;322(10):957-973. doi:10.1001/jama.2019.12803.
\273\ Medicare Payment Advisory Commission. 2021. Report to the
Congress: Medicare and the health care delivery system. Washington,
DC: MedPAC. http://www.medpac.gov/docs/default-source/reports/mar21_medpac_report_to_the_congress_sec.pdf.
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Based on our review of definitions commonly used, for the purposes
of the ETC Model we proposed to define the term ``ETC Large Dialysis
Organization,'' abbreviated ``ETC LDO,'' as a legal entity that owns,
in whole or in part, 500 or more ESRD facilities (86 FR 36379). Based
on the current
[[Page 61953]]
distribution of numbers of ESRD facilities owned by dialysis
organizations operating in the market, we stated our belief that this
threshold is appropriate, as it differentiates the largest dialysis
organizations, which at present own over 2,500 ESRD facilities, from
smaller dialysis organizations, the next largest of which owns
approximately 350 ESRD facilities. We further stated our belief that
the difference in size represents a meaningful difference in access to
resources necessary to establish a home dialysis program, as well as
the likelihood that an ESRD facility's aggregation group would have at
least one ESRD facility with a home dialysis program in the aggregation
group. We solicited comment on our proposal to include nocturnal in-
center dialysis beneficiary years in the numerator of the home dialysis
rate calculation only for ESRD facilities not owned in whole or in part
by an ETC LDO, as well as our proposal to define an ETC LDO as a legal
entity owning 500 or more ESRD facilities.
While nocturnal in-center dialysis can potentially result in better
patient health outcomes and savings to Medicare compared to traditional
in-center dialysis, we acknowledged in the CY 2022 ESRD PPS proposed
rule that its inclusion in the home dialysis rate may reduce the
incentive for ESRD facilities not owned in whole or in part by an LDO
to invest in a home dialysis infrastructure. We therefore proposed to
include nocturnal in-center dialysis as one half of the total number of
dialysis treatment beneficiary years during the MY in which the
attributed beneficiaries received nocturnal in-center dialysis in the
numerator of the home dialysis rate calculation for ESRD facilities not
owned in whole or in part by an ETC LDO as well as Managing Clinicians.
We further stated our belief that this policy would effectively balance
the benefits of nocturnal in-center dialysis and its ability to help
beneficiaries transition to home dialysis with the recognition that in-
center nocturnal dialysis is not home dialysis and does not have all of
the same benefits. As described in the Specialty Care Models final
rule, we included one half of the total number of dialysis treatment
beneficiary years during the MY in which the attributed beneficiaries
received self-dialysis in center in the home dialysis rate calculation
for a similar reason (85 FR 61306).
As such, we proposed to amend Sec. 512.365(b) such that, beginning
for MY3, the numerator for the home dialysis rate for ESRD facilities
not owned in whole or in part by an ETC LDO and Managing Clinicians
would be the total number of dialysis treatment beneficiary years
during the MY in which attributed ESRD Beneficiaries received
maintenance dialysis at home, plus one half of the total number of
dialysis treatment beneficiary years during the MY in which attributed
ESRD Beneficiaries received maintenance dialysis via self-dialysis,
plus one half of the total number of dialysis treatment beneficiary
years during the MY in which attributed ESRD Beneficiaries received
maintenance dialysis via in-center nocturnal dialysis. We further
proposed to add paragraph (C) to both Sec. Sec. 512.365(b)(1)(ii) and
512.365(b)(2)(ii) to specify that nocturnal in-center dialysis
beneficiary years included in the numerator of the home dialysis rate
calculation would be composed of those months during which attributed
ESRD Beneficiaries received nocturnal in-center dialysis, such that 1-
beneficiary year is comprised of 12-beneficiary months. The months in
which an attributed ESRD Beneficiary received nocturnal in-center
dialysis would be identified by claims with Type of Bill 072X, where
the type of facility code is 7 and the type of care code is 2, and with
the modifier UJ, which specifies that a claim with Type of Bill 072X is
for nocturnal in-center dialysis. We sought comment on these proposed
changes to Sec. 512.365(b).
The following is a summary of the comments received on our proposal
to include nocturnal in-center dialysis in the home dialysis rate
beginning for MY3 and our responses, and on the home dialysis rate in
general.
Comment: Several commenters expressed support for the ETC Model for
creating incentives to increase patient choice in the modality of their
dialysis care. A few commenters also expressed support for the Model's
potential to close gaps in health equity by making home dialysis more
available to previously underserved populations.
Response: We appreciate the feedback and support from commenters.
Comment: A commenter expressed concern that the PPA may not account
for barriers to home dialysis such as patient socioeconomic status,
energy and infrastructure needs, and caregiver status, and may
inadvertently penalize the Managing Clinician if home dialysis is not a
suitable option for the beneficiary.
Response: As we noted in the Specialty Care Models final rule (85
FR 61267), we recognize that there are a variety of barriers that
prevent ESRD Beneficiaries from choosing home dialysis at present. ESRD
facilities and Managing Clinicians are the clinical experts in dialysis
provision in general, and in the clinical and non-clinical needs of
individual ESRD Beneficiaries specifically. We therefore continue to
believe that ESRD facilities and Managing Clinicians are uniquely
positioned to assist ESRD Beneficiaries in overcoming these barriers,
given their close care relationship to and frequent interaction with
ESRD Beneficiaries. Therefore, we have designed the ETC Model to test
whether outcomes-based payment adjustments for ESRD facilities and
Managing Clinicians can maintain or improve quality and reduce costs by
increasing rates of home dialysis, transplant waitlisting, and living
donor transplants. The payment adjustments in the ETC Model test one
approach to addressing existing disincentives to home dialysis and
transplant in the current Medicare FFS payment system.
There are several features of how we assess a Managing Clinician's
performance on the home dialysis rate to calculate the Managing
Clinician's PPA that address the concern about barriers that prevent
individual ESRD Beneficiaries from choosing home dialysis. First, we
exclude certain ESRD Beneficiaries from attribution who may not be
suitable candidates for home dialysis or transplantation, detailed in
Sec. 512.360(b). Second, in this final rule, we are finalizing our
proposals to modify the Model's benchmark methodology to recognize the
additional resources required to increase the home dialysis rate and
transplant rate among beneficiaries who are dual-eligible or LIS
recipients. Specifically, as described in section V.B.5.c.(2) of this
final rule, we are finalizing our proposal to stratify achievement
benchmarks based on dual eligible and LIS recipient status in
recognition that socioeconomic factors impact a beneficiary's
likelihood of dialyzing at home. Additionally, as described in section
V.B.6.c.(2) of this final rule, we are finalizing our proposal to add a
Health Equity Incentive to the improvement scoring methodology for ETC
Participants who demonstrate sufficiently significant improvement on
the home dialysis rate or transplant rate among their attributed
beneficiaries who are dual eligible or receive the LIS between the
Benchmark Year and the MY. Lastly, as described in section V.B.3.c of
this final rule, we are finalizing our proposal to include partial
credit for nocturnal in-center dialysis in the home dialysis rate,
which may be a more accessible alternative to traditional in-center
dialysis for ESRD Beneficiaries facing the barriers identified by the
commenter.
[[Page 61954]]
Comment: Several commenters expressed their support for nocturnal
dialysis as an alternative to traditional in-center dialysis. A few
commenters noted that nocturnal in-center dialysis is a valuable
treatment option for beneficiaries for whom limited financial
resources, housing insecurity, or lack of social support make electing
home dialysis difficult, and would thereby promote health equity. A
commenter stated that evidence exists to support nocturnal dialysis as
an alternative to traditional in-center dialysis because it is
associated with improved clinical markers, better sleep and fewer apnea
events, and improved nutritional status, and because nocturnal dialysis
creates greater opportunity for beneficiaries to hold gainful
employment compared to traditional in-center dialysis.
Response: We appreciate the feedback and support from the
commenters.
Comment: Multiple commenters expressed agreement with barriers to
the provision of nocturnal dialysis identified in the CY 2022 ESRD PPS
proposed rule, including supply factors and lack of patient awareness.
Commenters also identified system-level factors that may impact an ESRD
facility's ability to offer nocturnal dialysis, including labor and
operational costs associated with keeping a facility open overnight and
the need for additional equipment such as additional water systems to
support nocturnal dialysis machines and beds or recliners to facilitate
beneficiary sleep. One commenter also noted that beneficiaries would
still be required to come into the ESRD facility during traditional
hours to receive additional related services, such as nutrition
counseling, which cannot be done while the beneficiary is asleep.
Response: We recognize that there are a variety of barriers that
prevent ESRD Beneficiaries from choosing nocturnal in-center dialysis
at present. As noted previously in this section of this final rule,
nocturnal in-center dialysis also provides an alternative to
traditional in-center dialysis for those beneficiaries for whom home
dialysis is not an option due to limited financial resources, housing
insecurity, lack of social support, or personal preference. We believe
encouraging the provision of nocturnal in-center dialysis helps to
promote beneficiary choice of treatment modalities while mitigating
some of the barriers beneficiaries face when considering home dialysis.
Comment: Several commenters expressed their support for including
nocturnal in-center dialysis beneficiary years in the numerator of the
home dialysis rate calculation. These commenters agreed with CMS's
position that incentivizing nocturnal in-center dialysis will create
more patient choice and improve health outcomes, and may address
certain socioeconomic factors that inhibit beneficiaries from selecting
home dialysis.
Response: We agree with commenters that including nocturnal in-
center dialysis in the home dialysis rate may improve access for
beneficiaries who, due to their home condition, cannot dialyze at home.
We believe that supporting patient choice in modality selection is
vital, and we believe the ETC Model will support providers and
suppliers in their ability to assist beneficiaries choosing renal
replacement modalities other than traditional in-center dialysis.
Comment: A few commenters noted that including nocturnal in-center
dialysis in the numerator of the home dialysis rate calculation may not
provide sufficient incentive for an ESRD facility to launch or expand a
nocturnal in-center dialysis program due to increased labor and
operational costs. A commenter recommended that to address these
challenges, CMS should consider including beneficiaries that are
referred to a nocturnal in-center dialysis program in the home dialysis
rate numerator.
Response: We recognize that there are a variety of barriers that
prevent ESRD facilities from offering nocturnal in-center dialysis.
However, we believe including nocturnal in-center dialysis in the home
dialysis rate calculation will help promote beneficiary choice of
treatment modalities while mitigating some of the barriers
beneficiaries face when considering home dialysis. We are not
considering including referrals to nocturnal in-center dialysis in the
home dialysis rate calculation at this time. We believe the
administrative burden associated with tracking referrals may be too
great to implement this policy in the ETC Model; however, we may take
this recommendation into consideration in the future.
Comment: A few commenters expressed concern that including
nocturnal in-center dialysis in the PPA rate may slow adoption of home
dialysis, as nocturnal in-center dialysis allows ESRD facilities to use
existing the existing in-center dialysis infrastructure rather than
modifying or creating new infrastructure and processes to implement a
home dialysis program.
Response: A focus of the ETC Model remains promoting beneficiary
choice of alternative treatment modalities to traditional in-center
dialysis and improving beneficiary adoption of home dialysis. We
believe including nocturnal in-center dialysis in the numerator of the
home dialysis rate will effectively balance the benefits of nocturnal
in-center dialysis and its ability to transition ESRD Beneficiaries to
home dialysis, with the recognition that nocturnal in-center dialysis
is not home dialysis and does not have all of the same benefits.
Specifically, each beneficiary month for which an attributed
beneficiary receives nocturnal in-center dialysis will contribute only
one-half month to the numerator.
Comment: A commenter urged CMS to further define nocturnal in-
center dialysis. The commenter stated that a Medicare manual indicates
that nocturnal in-center dialysis should be for periods greater than
five hours and performed while the patient is sleeping. The commenter
further noted that this definition may allow for in-center dialysis
conducted outside of traditional business hours to be considered
nocturnal dialysis. The commenter recommended that CMS define nocturnal
in-center dialysis as ``in-center hemodialysis treatments dialyzing for
at least five hours with a treatment time beginning on one day and
terminating after 1 a.m. on the following day'' to avoid confusion and
consistency in billing.
Response: As the commenter points out, nocturnal in-center dialysis
is already defined by Medicare. Specifically, effective January 1,
2017, nocturnal hemodialysis is identified under the ESRD PPS by the
modifier UJ, which identifies services provided at night. The UJ
modifier is for ESRD facilities to indicate that the treatment
furnished is for nocturnal hemodialysis. That is, longer and slower
hemodialysis that can be performed at home or in-facility for greater
than 5 hours per treatment, 3 to 7 days a week. Consistent with this
definition, as described elsewhere in this final rule, we are
finalizing our proposal to identify months in which an attributed ESRD
Beneficiary received nocturnal in-center dialysis by claims with Type
of Bill 072X, where the type of facility code is 7 and the type of care
code is 2, and with the modifier UJ, which specifies that a claim with
Type of Bill 072X is for nocturnal in-center dialysis. As such, we do
not believe it is necessary to further define nocturnal in-center
dialysis in this final rule.
Comment: A few commenters agreed with the proposal to include
nocturnal in-center dialysis in the home dialysis rate calculation for
Managing Clinicians and for ESRD facilities not owned in whole or in
part by an ETC LDO.
Response: We appreciate the commenters' support and feedback.
[[Page 61955]]
Comment: Multiple commenters expressed opposition to the proposal
to not include nocturnal in-center dialysis in the home dialysis rate
for ESRD facilities owned in whole or in part by an ETC LDO. Commenters
stated that this policy undermines the incentive to increase access to
nocturnal in-center dialysis, as ESRD facilities owned in whole or in
part by an ETC LDO provide approximately 75 percent of dialysis care
nationally. A few commenters stated that excluding ESRD facilities
owned in whole or in part by an ETC LDO from the proposal to include
nocturnal in-center dialysis beneficiary years in the numerator of the
home dialysis rate calculation may severely limit beneficiary access to
the modality, especially beneficiaries in rural and high-poverty areas,
which are majority serviced by ESRD facilities owned in whole or in
part by an ETC LDO, as these LDOs may not expand their nocturnal in-
center dialysis capabilities without the proper incentive. Commenters
noted that Managing Clinicians often partner with LDOs and should not
be incentivized to refer patients to ESRD facilities not owned in whole
or in part by an ETC LDO. Several commenters expressed concern that the
proposed policy would arbitrarily apply different standards to ESRD
facilities in the Model based on ownership and would set a precedent
for future Medicare programs, and may exceed the scope of the
Innovation Center's authority.
Response: We agree with commenters that excluding ESRD facilities
owned in whole or in part by an ETC LDO from the proposal to include
nocturnal in-center dialysis in the home dialysis rate calculation
would exclude the majority of beneficiaries from the potential benefits
of the policy, as ESRD facilities owned in whole or in part by an ETC
LDO provide the majority of dialysis care. We continue to recognize the
differences in resource availability to invest in home dialysis
programs between ESRD facilities owned in whole or in part by LDOs, and
those ESRD facilities that are either independent or owned by small
dialysis organizations. However, after considering the comments
received, we now believe that it is more important to incentivize
access to nocturnal in-center dialysis for all ESRD Beneficiaries,
regardless of the ownership of the ESRD facility at which they dialyze.
As such, we will not be finalizing the proposal to exclude ESRD
facilities owned in whole or in part by an ETC LDO from the
modification to include nocturnal in-center dialysis in the home
dialysis rate.
Comment: We received multiple comments from multiple smaller
dialysis organizations, commonly referred to as non-large dialysis
organizations (non-LDO), agreeing with the definition of an ETC LDO as
a legal entity that owns, in whole or in part, 500 or more ESRD
facilities. These commenters pointed out the resource differential
faced by smaller companies from larger companies. Another commenter
urged more changes to the ETC Model to relieve potential financial
burden for non-LDOs such as including referrals made to nocturnal in-
center dialysis programs in the numerator of the home dialysis rate.
Response: As described previously in this section of the final
rule, we are not finalizing our proposal include nocturnal in-center
dialysis in the numerator only for those ESRD facilities not owned in
whole or in part by an ETC LDO. Therefore, we will not be finalizing a
definition of an ETC LDO in this final rule. However, we also will not
be updating model parameters to include referrals made to nocturnal in-
center dialysis programs in the numerator of the home dialysis rate, as
suggested by the commenter. As stated previously in this final rule, we
believe the administrative burden associated with tracking such
referrals may be too great to implement in the ETC Model; however, we
may take this recommendation into consideration in the future.
Comment: We received comments from an LDO pointing out that the
proposed definition of ETC LDO as a legal entity owning 500 or more
ESRD facilities could be viewed as arbitrary, pointing out different
definitions used across CMS and in other areas, which range from 20
facilities to 1,000 facilities.
Response: As we noted in the CY 2022 ESRD PPS proposed rule (85 FR
36378), at present there is not a single definition of what qualifies
as a legal entity that owns ESRD facilities as an LDO. CMS chose the
proposed definition after reviewing definitions commonly used to align
with the current distribution of numbers of ESRD facilities owned by
dialysis organizations operating in the market. Specifically, our
proposed definition differentiated the largest dialysis organizations,
which at present each own over 2,500 ESRD facilities, from smaller
dialysis organizations, the next largest of which owns under 400 ESRD
facilities. This definition is also currently used by the Kidney Care
Choices Model, which changed its definition of an LDO after the
publication of the CY 2022 ESRD PPS proposed rule, such that the Kidney
Care Choices Model now defines an LDO as a legal entity that owns, in
whole or in part, 500 or more ESRD facilities. However, as noted above,
we will not be finalizing a definition of an ETC LDO in this final
rule.
Comment: A few commenters suggested giving ETC Participants who
refer patients to home dialysis programs credit in the home dialysis
rate, regardless if the home dialysis program is located in the same
HRR.
Response: We are not considering this change at this time. As noted
previously in this final rule, we believe the administrative burden
associated with tracking such referrals may be too great to implement
in the ETC Model; however, we may take this recommendation into
consideration in the future.
Final Rule Action: After considering public comments, we are
finalizing our proposal to amend Sec. 512.365(b) with modification. We
are modifying our proposal such that the numerator of the home dialysis
rate calculation for all ESRD facilities and for Managing Clinicians
includes one half of the total number of nocturnal in-center dialysis
beneficiary years for attributed ESRD Beneficiaries. Therefore, we are
modifying Sec. 512.365(b)(1)(ii) to remove references to a separate
home dialysis rate calculation for ESRD facilities owned in whole or in
part by an ETC LDO. Similarly, we are not finalizing the proposed ETC
LDO definition at this time.
4. PPA Transplant Rate
a. Status of Organ Availability
The ETC Model is designed to encourage greater rates of
transplantation. In the proposed rule published on July 18, 2019 in the
Federal Register titled, ``Medicare Program; Specialty Care Models to
Improve Quality of Care and Reduce Expenditures'' (84 FR 34478),
referred to herein as the ``Specialty Care Models proposed rule,'' CMS
proposed to include the rate of transplants, both living and deceased
donor transplants, in the numerator for the ETC Model's transplant
rate. However, in the Specialty Care Models final rule, we recognized
the limitations of supply of deceased donor organs and updated the
transplant rate to be calculated as the sum of the transplant waitlist
rate and the living donor transplant rate (85 FR 61310). We stated that
though a transplant is often the best treatment for a beneficiary with
ESRD, in light of the current shortage of deceased donor organs for
transplant, the transplant
[[Page 61956]]
waitlist rate and living donor transplant rate are currently more
within the control of an ETC Participant (85 FR 61309).
However, in the Specialty Care Models final rule, we indicated our
intent to observe the supply of deceased donor organs available for
transplantation, with the goal of potentially modifying the transplant
rate calculation for the future (85 FR 61309). Since the Specialty Care
Models final rule was published on September 29, 2020, there have been
several initiatives pursued by the Federal Government that could
potentially have the effect of increasing the supply of both living
donor organs and deceased donor organs.
On September 22, 2020, the Health Resources and Services
Administration (HRSA) published a final rule in the Federal Register
titled ``Removing Financial Disincentives to Living Organ Donation''
(85 FR 59438). This rule removes financial barriers to organ donation
by expanding the scope of reimbursable expenses incurred by living
organ donors to include lost wages, and child-care and elder-care
expenses incurred by a caregiver. The rule went into effect on October
22, 2020.
Additionally, on December 2, 2020, CMS published in the Federal
Register a final rule titled, ``Medicare and Medicaid Programs; Organ
Procurement Organizations Conditions for Coverage: Revisions to the
Outcome Measure Requirements for Organ Procurement Organizations'' (85
FR 77898), revising Conditions for Coverage (CfCs) for Organ
Procurement Organizations (OPOs). The final rule revised the CfCs for
OPOs in order to increase donation rates and organ transplantation
rates and replaced the old outcome measures with new transparent,
reliable, and objective measures. The final rule went into effect on
March 30, 2021. The new outcome measures will be implemented for the
recertification cycle beginning in 2022 and ending in 2026. The goals
of this rule are complementary to the goals of the ETC Model, as the
revised CfCs are intended to increase the supply of organs, and the ETC
Model is designed to incentivize higher rates of transplantation.
Finally, as described in the Specialty Care Models final rule, CMS
is in the process of implementing the ETC Learning Collaborative (85 FR
61346). The ETC Learning Collaborative is a voluntary learning system
focused on increasing the availability of deceased donor kidneys for
transplantation. The ETC Learning Collaborative works with and supports
ETC Participants and other stakeholders required for successful kidney
transplantation, such as transplant centers, OPOs, and large donor
hospitals. CMS is currently in the process of jointly implementing the
ETC Learning Collaborative with HRSA.
We are pleased that these efforts have progressed since the
publication of the Specialty Care Models final rule. However, given
that these efforts are still in the implementation process, we stated
in the CY 2022 ESRD PPS proposed rule that we do not believe it would
be appropriate to update the transplant rate to include accountability
for deceased donor transplants, rather than transplant waitlisting, at
this time (86 FR 36380). We further stated that we still intend to
update the transplant rate through future rulemaking to include
accountability for deceased donor transplants, but we are not proposing
to do so at this time.
The following is a summary of the comments received on the status
of organ availability and related topics and our responses.
Comment: Multiple commenters expressed support for continuing to
monitor the transplant rate for ETC Participants based on transplant
waitlisting, rather than updating the transplant rate to include
accountability for deceased donor transplants.
Response: We appreciate the support and will continue to monitor
organ supply, with the goal of eventually including accountability for
deceased donor transplants through future rulemaking.
Comment: One commenter stated that an artificial kidney would have
the best outcomes for transplant recipients and supports continued
research towards the development of an artificial kidney.
Response: We agree that the creation of an artificial kidney could
have clinical benefits for beneficiaries. To assist in the development
of new technologies such as an artificial kidney, HHS is part of the
KidneyX public-private partnership to accelerate innovation in the
prevention, diagnosis, and treatment of kidney diseases. More
information on the KidneyX initiative is available at kidneyx.org.
Comment: One commenter stated that we should create a larger model
that includes other key actors in the transplant process, including
organ procurement organizations and transplant centers.
Response: We appreciate the feedback and will keep it in mind as we
think about designing future models for testing. We view the ETC Model,
including its ETC Learning Collaborative, as complementary to other
efforts around the Department related to increasing the number of
transplants, including the Kidney Care Choices Model, the OPO
Conditions for Coverage updates (85 FR 77898), and the HRSA rule on
Removing Financial Disincentives to Living Organ Donation (85 FR
59438). We will evaluate the ETC Model's interventions in the context
of the effects of existing regulatory initiatives, but we may also
consider a larger transplant model in the future.
Comment: One commenter suggested that we measure the number of
beneficiaries referred for transplant rather than the length of time a
beneficiary is on the transplant waitlist.
Response: In the Specialty Care Models final rule (85 FR 61310), we
recognized the limitations of supply of deceased donor organs and
updated the transplant rate to be calculated as the sum of the
transplant waitlist rate and the living donor transplant rate. We
selected the transplant waitlist rate specifically because inclusion on
the waitlist was more within the control of the ETC Participant. While
we did not discuss the possibility of referrals for transplant in the
Specialty Care Models final rule, we believe that referrals for
transplant is one step further removed from the actual receipt of a
transplant relative to the beneficiary's inclusion on the transplant
waitlist. A measure based on referrals would be operationally
burdensome for CMS to collect and for ETC Participants to report.
Additionally, such a measure would seem to have the potential for
gaming, as ETC Participants could be incentivized to submit numerous
referrals for individuals who would not qualify for inclusion on the
transplant waitlist, or even for individuals previously denied
inclusion. Accordingly, we are not adopting the commenter's suggestion
at this time.
Comment: One commenter suggested that CMS establish new metrics for
transplant providers, under the ETC Model, similar to the CMS quality
measures published for ESRD facilities, as transplant providers play a
large role in transplantation. One other commenter suggested that CMS
establish a payment adjustment for transplant personnel to conduct
transplant-related education activities in order to provide more
accurate details about transplant to beneficiaries.
Response: At this time, we are not contemplating incorporating
additional participant types, such as transplant providers, into the
ETC Model. Accordingly, we are not adding quality measures or payment
adjustments for transplant personnel, into the Model in this final
rule. However, we appreciate
[[Page 61957]]
the feedback and suggestions, which we may use to inform future model
design.
b. Beneficiary Exclusions From the Transplant Rate
As we discussed in the Specialty Care Models final rule (85 FR
61300), CMS received comments about excluding ESRD Beneficiaries with
cancer from attribution to ETC Participants, as there was concern about
treatment appropriateness. However, at that time, CMS did not have any
evidence to suggest that this is a concern. Accordingly, we did not
exclude beneficiaries with cancer from attribution to ETC Participants
for purposes of calculating the home dialysis rate or the transplant
rate in the Specialty Care Models final rule.
Nevertheless, as described in the CY 2022 ESRD PPS proposed rule
(86 FR 36380), after we published the Specialty Care Models final rule,
we conducted further analysis, to determine if a difference existed in
either the home dialysis rate or transplant rate in beneficiaries with
cancer and beneficiaries without cancer. Using the Medicare claims data
and input from clinical specialists in the field of nephrology, we
found that the majority of ESRD Beneficiaries with cancer, specifically
ESRD Beneficiaries with cancer in vital solid organs (heart, lung,
liver, and kidney), are not considered to be eligible candidates for
transplant. Many transplant centers do not consider these beneficiaries
for transplant and require them to be cancer-free for a specific period
of time prior to assessing their eligibility for transplant. This is
true for getting on a transplant waitlist and for receiving living
donor transplants, as a beneficiary either needs to be cancer-free or
be in an initial stage of cancer diagnosis to be considered for
transplant.
In addition, we found that ESRD Beneficiaries who have a diagnosis
of solid organ cancer for which they were receiving treatment,
specifically radiation or chemotherapy, are less likely to be in the
numerator of the transplant rate--so, being placed on the transplant
waitlist or receive a living donor transplant--than ESRD Beneficiaries
without a diagnosis of vital solid organ cancer. By contrast, we did
not find any evidence to suggest that ESRD Beneficiaries with cancer
had a significant difference in the home dialysis rate compared to the
ESRD Beneficiaries without cancer.
As noted previously, under Sec. Sec. 512.310 and 512.365(c), the
transplant rate has two components: The transplant waitlist rate and
the living donor transplant rate. Upon further review and analysis,
beginning for MY3, we proposed to exclude ESRD Beneficiaries and, if
applicable, Pre-emptive LDT Beneficiaries who have been diagnosed with
vital solid organ cancers (heart, lung, liver, and kidney) and who are
receiving treatment, in the form of radiation or chemotherapy, for such
cancers from both components of the denominator of the transplant rate
for both ESRD facilities and Managing Clinicians for the duration of
the MY.
Furthermore, we proposed to include a lookback period, a period of
time prior to the MY, to appropriately identify the ESRD Beneficiaries
and, if applicable, Pre-emptive LDT Beneficiaries with a diagnosis of
vital solid organ cancer for which they are receiving chemotherapy or
radiation therapy. Both a diagnosis code and a treatment code are
necessary to appropriately identify an ESRD Beneficiary or Pre-emptive
LDT Beneficiary with a vital solid organ cancer who is receiving
treatment with either radiation or chemotherapy. However, through our
analysis we have identified beneficiaries who have only a treatment
code available during the MY and do not have a diagnosis code during
that period. Hence, we proposed to include a lookback period of 6-
months prior to the MY, so that the appropriate diagnosis code can be
identified for ESRD Beneficiaries and Pre-emptive LDT Beneficiaries who
have only treatment codes available in the current MY. In the
alternative, we considered a 12-month lookback period, but did not find
any significant difference in the number of ESRD Beneficiaries and Pre-
emptive LDT Beneficiaries that had a diagnosis code for a vital organ
solid cancer during a 12-month lookback period as compared to a 6-month
lookback period.
We proposed to identify ESRD Beneficiaries and, if applicable, Pre-
emptive LDT Beneficiaries with a diagnosis of vital solid organ cancer
and receiving treatment with radiation or chemotherapy by using
Medicare claims. For purposes of the transplant rate calculations, we
proposed that an ESRD Beneficiary or Pre-emptive LDT Beneficiary would
be considered to have a diagnosis of vital solid cancer during the MY,
if the ESRD Beneficiary has a claim with one of the following ICD-10
diagnosis codes:
C22.0-C22.9 (malignant neoplasm of liver and intrahepatic
bile ducts),
C34.10-C34.12 (malignant neoplasm of upper lobe, bronchus
or lung),
C34.2 (malignant neoplasm of middle lobe, bronchus or
lung),
C34.30-C34.32 (malignant neoplasm of lower lobe, bronchus
or lung),
C34.80-C34.82 (malignant neoplasm of overlapping sites of
bronchus and lung),
C34.90-C34.92 (malignant neoplasm of unspecified part of
bronchus or lung),
C38.0 (malignant neoplasm of heart),
C38.8 (malignant neoplasm of overlapping sites of heart,
mediastinum and pleura),
C46.50-C46.52 (Kaposi's sarcoma of lung),
C64.1, C64.2, C64.9 (malignant neoplasm of kidney, except
renal pelvis),
C78.00-C78.02 (secondary malignant neoplasm of lung),
C78.7 (secondary malignant neoplasm of liver and
intrahepatic bile duct),
C79.00-C79.02 (secondary malignant neoplasm of kidney and
renal pelvis),
C7A.090 (malignant carcinoid tumor of the bronchus and
lung),
C7A.093 (malignant carcinoid tumor of the kidney), or
C7B.02 (secondary carcinoid tumors of liver).
We proposed that for the purposes of the transplant rate
calculations, an ESRD Beneficiary or Pre-emptive LDT Beneficiary would
be considered to be receiving treatment for vital solid organ cancer
with either chemotherapy or radiation in the MY if the ESRD Beneficiary
or Pre-emptive LDT Beneficiary has a claim with one of the following
codes:
CPT[supreg] 96401-96402, 96405-96406, 96409, 96411, 96413,
96415-96417, 96420, 96422-26423, 96425, 96440, 96446 (chemotherapy
administration);
CPT[supreg] 96549 (unlisted chemotherapy procedure);
CPT[supreg] 77373 (stereotactic body radiation therapy);
CPT[supreg] 77401-77402, 77407, 77412 (radiation treatment
delivery);
CPT[supreg] 77423 (high energy neutron radiation treatment
delivery);
CPT[supreg] 77424-77425 (Intraoperative radiation
treatment delivery);
CPT[supreg] 77520, 77522-77523, 77525 (proton treatment
delivery);
CPT[supreg] 77761-77763 (intracavitary radiation source
application);
CPT[supreg] 77770-77772, 77778, 77789, 77799 (clinical
brachytherapy radiation treatment);
CPT[supreg] 79005, 79101, 79200, 79300, 79403, 79440,
79445, 79999 (radiopharmaceutical therapy);
ICD-10-PCS DB020ZZ, DB021ZZ, DB022ZZ, DB023Z0, DB023ZZ,
[[Page 61958]]
DB024ZZ, DB025ZZ, DB026ZZ, DB1297Z, DB1298Z, DB1299Z, DB129BZ, DB129CZ,
DB129YZ, DB12B6Z, DB12B7Z, DB12B8Z, DB12B9Z, DB12BB1, DB12BBZ, DB12BCZ,
DB12BYZ, DB22DZZ, DB22HZZ, DB22JZZ, DBY27ZZ, DBY28ZZ, DBY2FZZ, DBY2KZZ
(radiation of lung);
ICD-10-PCS DB070ZZ, DB071ZZ, DB072ZZ, DB073Z0, DB073ZZ,
DB074ZZ, DB075ZZ, DB076ZZ, DB1797Z, DB1798Z, DB1799Z, DB179BZ, DB179CZ,
DB179YZ, DB17B6Z, DB17B7Z, DB17B8Z, DB17B9Z, DB17BB1, DB17BBZ, DB17BCZ,
DB17BYZ, DB27DZZ, DB27HZZ, DB27JZZ, DBY77ZZ, DBY78ZZ, DBY7FZZ, DBY7KZZ
(radiation of chest wall);
ICD-10-PCS DF000ZZ, DF001ZZ, DF002ZZ, DF003Z0, DF003ZZ,
DF004ZZ, DF005ZZ, DF006ZZ, DF1097Z, DF1098Z, DF1099Z, DF109BZ, DF109CZ,
DF109YZ, DF10B6Z, DF10B7Z, DF10B8Z, DF10B9Z, DF10BB1, DF10BBZ, DF10BCZ,
DF10BYZ, DF0DZZ, DF20HZZ, DF20JZZ, DFY07ZZ, DFY08ZZ, DFY0CZZ, DFY0FZZ,
DFY0KZZ (radiation of liver);
ICD-10-PCS DT000ZZ, DT001ZZ, DT002ZZ, DT003Z0, DT003ZZ,
DT004ZZ, DT005ZZ, DT006ZZ, DT1097Z, DT1098Z, DT1099Z, DT109BZ, DT109CZ,
DT109YZ, DT10B6Z, DT10B7Z, DT10B8Z, DT10B9Z, DT10BB1, DT10BBZ, DT10BCZ,
DT10BYZ, DT20DZZ, DT20HZZ, DT20JZZ, DTY07ZZ, DTY08ZZ, DTY0CZZ, DTY0FZZ
(radiation of kidney);
ICD-10-PCS DW020ZZ, DW021ZZ, DW022ZZ, DW023Z0, DW023ZZ,
DW024ZZ, DW025ZZ, DW026ZZ, DW1297Z, DW1298Z, DW1299Z, DW129BZ, DW129CZ,
DW129YZ, DW12B6Z, DW12B7Z, DW12B8Z, DW12B9Z, DW12BB1, DW12BBZ, DW12BCZ,
DW12BYZ, DW22DZZ, DW22HZZ, DW22JZZ, DWY27ZZ, DWY28ZZ, DWY2FZZ
(radiation of chest); or
ICD-10-PCS DW030ZZ, DW031ZZ, DW032ZZ, DW033Z0, DW033ZZ,
DW034ZZ, DW035ZZ, DW036ZZ, DW1397Z, DW1398Z, DW1399Z, DW139BZ, DW139CZ,
DW139YZ, DW13B6Z, DW13B7Z, DW13B8Z, DW13B9Z, DW13BB1, DW13BBZ, DW13BCZ,
DB13BYZ, DW23DZZ, DW23HZZ, DW23JZZ, DWY37ZZ, DWY38ZZ, DWY3FZZ
(radiation of abdomen).
We sought comment on the proposal to amend Sec. 512.365(c) to
exclude ESRD Beneficiaries and, if applicable, Pre-emptive LDT
Beneficiaries with a diagnosis of vital solid organ cancer and
receiving treatment with chemotherapy or radiation from the denominator
of the transplant rate as a whole, including both the transplant
waitlist rate component and the living donor transplant rate component,
for the duration of the MY for both ESRD facilities and Managing
Clinicians.
The following is a summary of the comments received on the proposal
to exclude ESRD beneficiaries and, if applicable, Pre-emptive LDT
Beneficiaries, with a diagnosis of vital solid organ cancer and
receiving treatment with chemotherapy or radiation from the denominator
of the transplant rate for the duration of the MY, beginning for MY3,
and our responses.
Comment: Several commenters stated they agree with the proposal to
exclude beneficiaries, including Pre-emptive LDT Beneficiaries, with
vital solid organ (heart, liver, lung, and kidney) cancers from the
denominator of the transplant rate. The majority of these commenters
also agreed with our proposal to use a six-month lookback period to
identify these beneficiaries.
Response: We appreciate the commenters' support.
Comment: Several commenters suggested that CMS exclude additional
beneficiaries from the transplant rate based on one or more criteria. A
few of these commenters suggested that CMS exclude beneficiaries with
all cancers, while one of the commenters suggested specific additional
cancers. Another commenter suggested that CMS add breast cancer to the
list of cancer exclusions, if CMS does not exclude beneficiaries with
all cancers. Another commenter, suggested that CMS exclude
beneficiaries with all active malignancies.
Response: In response to the commenters' suggestions to exclude
beneficiaries with additional cancers, all active malignancies, or all
cancers from the transplant rate, we recognize that transplant centers
may vary in the cancers used to determine eligibility for transplant.
However, having cancer may not automatically eliminate a beneficiary
from being eligible for transplant. As noted in the proposed rule (86
FR 36380), our internal analysis identified that ESRD Beneficiaries
with cancer in vital solid organs (heart, kidney, liver, lung) for
which they are receiving treatment with radiation or chemotherapy, are
less likely to be in the numerator of the transplant rate--so being
placed on the transplant waitlist or receiving a living donor
transplant--than ESRD Beneficiaries without a diagnosis of vital solid
organ cancer. As noted in the Specialty Care Models final rule (85 FR
61301), CMS would like to encourage ETC Participants to provide home
dialysis and transplantation for as many beneficiaries that would
benefit from these care modalities. Accordingly, we are excluding from
the transplant rate calculation only those beneficiaries who are
particularly unlikely to be eligible for transplants; specifically,
those beneficiaries with vital solid organ cancers who are receiving
treatment through radiation or chemotherapy.
Comment: One commenter suggested that CMS exclude all beneficiaries
who have untreatable cardiopulmonary, cardiovascular, peripheral
vascular disease, significant physical disability (Karnofsky Score <40
percent), severe pulmonary issues, severe morbid obesity (BMI >50), or
recurrent chronic infections. In addition, other commenters suggested
that we exclude beneficiaries with end-stage Chronic Obstructive
Pulmonary Disease (COPD) and diagnoses involving heart failure.
Response: As noted above, transplant centers have varying criteria
when considering a beneficiary as eligible for transplant. For
instance, many transplant centers do not reject a beneficiary for
transplant solely on the basis of the non-cancer conditions suggested
by commenters. Thus, the general categorization of these conditions for
exclusion is not appropriate. Moreover, as noted previously, CMS would
like to encourage ETC Participants to provide home dialysis and
transplantation for as many beneficiaries that would benefit from these
care modalities; our ability to achieve this aim would be compromised
were CMS to exclude too many categories of beneficiaries from the
Model's financial calculations. Accordingly, we are not adding these
conditions for beneficiary exclusion from the transplant rate at this
time. Nonetheless, we will continue to consider whether any additional
conditions should be added to the exclusion criteria for transplant
rate through future rulemaking.
Comment: One commenter suggested that CMS operationalize the
exclusion of beneficiaries with cancer in vital solid organs from the
transplant rate by using only diagnosis codes, rather than a
combination of diagnosis codes and treatment codes, to identify such
beneficiaries, as treatment might not have started or might not be
appropriate.
Response: As we noted in the CY 2022 ESRD PPS proposed rule (86 FR
36380), we proposed to include a lookback period, a period of time
prior to the MY, to appropriately identify beneficiaries with a
diagnosis of a vital
[[Page 61959]]
solid organ cancer for which they are receiving treatment in light of
internal analysis that identified beneficiaries who have a treatment
code, but not a diagnosis code, during the MY. In order to capture the
ESRD beneficiaries with the vital solid organ cancer diagnosis
appropriately, we proposed to include a lookback period of 6 months.
While we considered a 12-month lookback period, as noted in the CY 2022
ESRD PPS proposed rule (86 FR 36380), our internal analysis did not
identify any significant difference in the number of beneficiaries that
had a diagnosis for a vital solid organ cancer during a 12-month
lookback period as compared to a 6-month lookback period. In addition,
a longer lookback period was not considered to identify diagnosis
code(s) as the exclusion is to identify beneficiaries with active
cancer because our internal analysis did not identify any significant
difference in the number of beneficiaries that had a diagnosis for a
vital solid organ cancer during a lookback period longer than 12 months
as compared to a 6-month lookback period. We therefore decline to adopt
the commenter's suggestion of using a 2-year lookback period to
identify cancer diagnosis.
In the CY 2022 ESRD PPS proposed rule (86 FR 36280), we did not
propose a lookback period for treatment codes. However, CMS did
previously identify beneficiaries with a diagnosis code and no
treatment code during the MY. Given that several commenters suggested
that CMS include a lookback period for treatment, and considering that
a beneficiary could have ended their most recent course of treatment
immediately prior to the start of a given MY, we are modifying our
proposal to include a lookback period of 6-months to identify radiation
or chemotherapy treatment codes for beneficiaries with diagnosis code
of vital solid organ cancer during the MY, similar to the proposed
lookback period for diagnosis codes that we are finalizing in this
rule. We are limiting the lookback period to identify radiation or
chemotherapy treatment code(s) to 6 months because the purpose of this
particular exclusion is to exclude from the transplant rate
beneficiaries who have an active cancer and are receiving treatment, as
these beneficiaries are less likely to be placed on the transplant
waitlist. Beneficiaries who received radiation or chemotherapy
treatment greater than 6 months before the start of the MY are unlikely
to be actively receiving treatment and thus do not need to be excluded
from the transplant rate for that reason.
After considering the comments received, we are finalizing a 6-
month lookback period, as proposed, for identifying a vital solid organ
cancer diagnosis code for beneficiaries who have only a treatment code
during the MY. In addition, we are adding in a 6-month lookback period
for identifying radiation and chemotherapy treatment codes for
beneficiaries who have only a diagnosis code during the MY.
Final Rule Action: After considering public comments, we are
finalizing our proposal with modification. First, we are amending our
regulation at Sec. 512.365(c) to exclude ESRD beneficiaries and, if
applicable, Pre-emptive LDT Beneficiaries, who had a diagnosis of vital
solid organ cancer and were receiving treatment with chemotherapy or
radiation for vital solid organ cancer during the MY from the
denominator of the transplant rate calculation, beginning for MY3.
Second, we are making two modifications to correct the information
included in the proposed rule (86 FR 36380-36381). Specifically, we are
clarifying the list of ICD-10 diagnosis codes included in Sec.
512.365(c)(1)(i)(A)(1) to replace ``C22.1-C22.9,'' with ``C22.0, C22.1,
C22.2, C22.3, C22.4, C22.7, C22.8 and C22.9.'' The codes C22.1-C22.9
are not sequential--that is, there is no C22.5 or C22.6--and therefore
should not have been grouped. In addition, while we referenced C22.0 in
the preamble of the CY 2022 ESRD PPS proposed rule, this code was left
out of the proposed regulation text in error. C22.2 was also left out
of the proposed regulation text in error. In addition, we are also
modifying the list of treatment codes at Sec.
512.365(c)(1)(i)(A)(2)(ii) to correct a typo of the ICD-10-PCS codes
from ``DF0DZZ,'' to ``DF20DZZ,'' which refers to radiation of the
liver. Third, we are adding a 6-month lookback period to identify
radiation and chemotherapy treatment codes for beneficiaries who only
have a vital solid organ cancer diagnosis code during the MY.
5. PPA Achievement Benchmarking
a. Background on Achievement Benchmarking
Under the ETC Model, the PPA is a positive or negative adjustment
on dialysis and dialysis-related Medicare payments, for both home
dialysis and in-center dialysis. To calculate an ETC Participant's PPA,
we assess ETC Participant achievement on the home dialysis rate and
transplant rate in relation to achievement and improvement benchmarks,
as described in 42 CFR 512.370(b) and Sec. 512.370(c), respectively.
The Model more heavily weights achievement of results, allowing
participating Managing Clinicians or ESRD facilities to earn up to 2
points in the scoring methodology, as opposed to only 1.5 points for
maximum level of improvement, as described in Sec. Sec. 512.370(b) and
512.370(c).
The achievement benchmarks are constructed based on the home
dialysis rate and transplant rate observed in Comparison Geographic
Areas during corresponding Benchmark Years. Achievement benchmarks are
percentile based, and an ETC Participant receives the achievement
points that correspond with its performance, at the aggregation group
level, on the home dialysis rate and transplant rate in relation to the
achievement benchmarks, as described in Sec. 512.370(b). Table 7
details the achievement score scale described in Sec. 512.370(b).
[[Page 61960]]
[GRAPHIC] [TIFF OMITTED] TR08NO21.006
In the Specialty Care Models proposed rule, we proposed to apply
this achievement benchmark policy only for MY1 and MY2, and stated our
intent to increase achievement benchmarks for ETC Participants above
the rates observed in Comparison Geographic Areas. We stated our belief
that increasing the achievement benchmarks for future MYs, which we
would do through subsequent rulemaking, was necessary in order to
provide sufficient incentive for ETC Participants to increase rates of
home dialysis and transplantation at a rate faster than would occur
absent the ETC Model (84 FR 34556 through 34557). In the Specialty Care
Models final rule, in response to comments, we finalized the
applicability of the achievement benchmarks for MY1 through MY2 and for
subsequent MYs (85 FR 61323), but reiterated our intent to establish a
different method for establishing achievement benchmarks for future
years of the Model through subsequent rulemaking (85 FR 61320). We
stated our belief that future modifications to the achievement
benchmark methodology finalized in the Specialty Care Models final rule
would be necessary to provide sufficient incentive for ETC Participants
to raise home dialysis and transplant rates at a rate faster than would
occur absent the ETC Model (85 FR 61321). However, we clarified that
while we had stated a goal of 80 percent of an ETC Participant's
receiving home dialysis or a transplant in order to receive the maximum
upward payment adjustment by the final MYs, we were not finalizing that
goal in the Specialty Care Models final rule (85 FR 61321).
b. Addressing Socioeconomic Factors That Impact ETC Participant
Achievement
In the Specialty Care Models final rule, we acknowledged
commenters' concerns that non-clinical factors, such as socioeconomic
status, may impact a beneficiary's likelihood to receive home dialysis
or transplant. We discussed commenters' suggestions to incorporate
consideration of socioeconomic status in two elements of the ETC Model:
(1) Beneficiary attribution; and (2) risk adjustment. However, we
declined to exclude beneficiaries from attribution based on
socioeconomic status. Noting the importance of not excluding these
beneficiaries, CMS stated its intent to assess the use of various codes
for purposes of adding any additional beneficiary exclusions from
attribution to ETC Participants based on socioeconomic status,
homelessness, or other social determinants of health through future
rulemaking (85 FR 61299). We also noted that commenters' suggestions
for ways to risk adjust the home dialysis rate based on socioeconomic
status were a significant departure from the policy originally proposed
(85 FR 61315).
In the CY 2022 ESRD PPS proposed rule (86 FR 36382), we continued
to acknowledge the impact that non-clinical factors, such as
socioeconomic status, have on a beneficiary's likelihood to receive
home dialysis or a transplant. Our additional analysis of Medicare
claims data shows that beneficiaries who are dual-eligible for Medicare
and Medicaid or receive the Medicare Low-Income Subsidy (LIS) are less
likely than beneficiaries who are not dual-eligible and are not LIS
recipients to dialyze at home or to receive a kidney transplant. As
such, ETC Participants who have a higher proportion of attributed
beneficiaries who are dual-eligible or LIS recipients may be less
likely to achieve high home dialysis and transplant rates than ETC
Participants who have a lower proportion of attributed beneficiaries
who are dual-eligible or LIS recipients.
c. Achievement Benchmarking and Scoring
(1) Achievement Benchmarking and Scoring for MY3 Through MY10
We proposed to modify the percentile-based achievement benchmarking
methodology based on the home dialysis rate and transplant rate
observed in Comparison Geographic Areas during the Benchmark Year as
the basis for achievement benchmarks in MY3 through MY10 (86 FR 36382).
Rather than using rates observed in Comparison Geographic Areas, we
proposed to modify Sec. 512.370(b)(1) to use rates observed in
Comparison Geographic Areas as the base for the achievement benchmarks,
and to increase the achievement benchmarks above the Comparison
Geographic Area rates during the Benchmark Year by 10 percent every two
MYs, beginning for MY3. As such, we proposed that achievement
benchmarks would be calculated by multiplying the percentile rate
observed in Comparison Geographic Areas during the Benchmark Year by
1.1 for MY3 and MY4, by 1.2 for MY5 and MY6, by 1.3 for MY7 and MY8,
and by 1.4 for MY9 and MY10.
Based on our analyses detailed in the CY 2022 ESRD PPS proposed
rule and in section VIII.C.4 of this final rule, this proposed
methodology for increasing benchmarks by 10 percent every two MYs would
produce results in keeping with the initial impact estimates for the
ETC Model, as described in the Specialty Care Models final rule (85 FR
61353 through 61354). In the Specialty Care Models final rule, we
estimated impacts based on projected growth rates for the home dialysis
and transplant rates based on historical observation, projected a 1.5
percentage point growth rate (86 FR 36383). In the CY 2022 ESRD PPS
proposed rule and in section VIII.C.4 of this final rule, updated
projections assume the same projected growth rate, but note that
observed rates of increase have accelerated in more recent data. As
such, in the CY 2022
[[Page 61961]]
ESRD PPS proposed rule we stated our belief that this rate of increase
would be attainable for ETC Participants, as initial impact estimates
were based on rates of increase observed on the home dialysis rate and
transplant rate before the ETC Model began (85 FR 61353). We also noted
that, unlike in the Specialty Care Models proposed rule (84 FR 34556),
we were not proposing to increase achievement benchmarks such that of
80 percent of an ETC Participant's attributed beneficiaries would need
to be receiving home dialysis or a transplant in order for the ETC
Participant to receive the maximum upward payment adjustment by the
final MYs. Table 8 details the proposed scoring methodology for
assessment of MY3 through MY10 achievement scores.
[GRAPHIC] [TIFF OMITTED] TR08NO21.007
In the CY 2022 ESRD PPS proposed rule, we considered increasing
achievement benchmarks by a percentage point amount, rather than by a
percent amount, every two MYs (for example, increasing achievement
benchmarks by 10-percentage points for MY3 and MY4, by 20-percentage
points for MY5 and MY6, etc.). However, we stated our belief that this
percentage point-based approach would be less flexible to and
accommodating of variation in the underlying distributions of home
dialysis and transplant rates than the percent-based approach we are
proposing. We also stated our belief that this percentage point-based
approach would add additional complexity, as we would likely need to
develop separate percentage point amounts by which to increase
benchmarks as the home dialysis rate and transplant rate observed in
Comparison Geographic Areas are not sufficiently similar to expect the
same percentage point growth rate for the two rates.
In the CY 2022 ESRD PPS proposed rule, we also considered proposing
to modify the Benchmark Year, such that the Benchmark Year would be a
fixed duration (for example, July 1, 2018 through June 30, 2019),
rather than a period of time defined in relation to the relevant MY.
However, we determined that this approach would not account for
aggregate changes in the home dialysis rate and transplant rate over
time.
In the CY 2022 ESRD PPS proposed rule we stated our belief that the
proposed approach for increasing achievement benchmarks over the course
of the ETC Model would balance the intent of the model design to
increase rates of home dialysis and transplantation above what would
have occurred in the absence of the Model with what is achievable for
ETC Participants, based on rates of home dialysis and transplantation
observed at the high ends of the distributions (for additional
discussion, see 86 FR 36427). We also stated our belief that the
proposed approach would provide
[[Page 61962]]
clarity to ETC Participants about the benchmarking methodology for the
duration of the ETC Model while maintaining flexibility in that
methodology to address long term trends in the home dialysis rate and
transplant rate.
We sought public comment on our proposal to modify the achievement
benchmarking methodology under Sec. 512.370(b) beginning for MY3 to
increase achievement benchmarks, and the proposal to increase
achievement benchmarks by 10 percent every two MYs above percentile-
based rates of observed in Comparison Geographic Areas.
The following is a summary of the comments received on our proposal
to modify the achievement benchmarking methodology beginning for MY3 to
increase achievement benchmarks by 10 percent every two MYs above rates
observed in Comparison Geographic Areas, and our responses.
Comment: Many commenters stated that they support increasing
achievement benchmarks over the duration of the ETC Model.
Response: We appreciate the support for increasing the PPA
achievement benchmarks throughout the duration of the ETC Model.
Comment: Two commenters opposed increasing achievement benchmarks
over time. One such commenter stated that the increasing magnitude of
the PPA, and the use of improvement scoring, collectively create a
sufficient incentive for ETC Participants to continue to increase rates
of home dialysis and transplant. The other such commenter stated that
they opposed increasing achievement benchmarks over time, as doing so
will ensure that ETC Participants cannot be successful in the ETC
Model, resulting in payment cuts.
Response: In response to the comment that the increasing magnitude
of the PPA and use of improvement scoring create a sufficient incentive
to promote continued increases in rates of home dialysis and
transplant, we disagree that these two factors alone are sufficient. As
such, we believe it is necessary to increase achievement benchmarks
over the course of the ETC Model. Similarly, we disagree with the
commenter that increasing achievement benchmarks will result in payment
cuts for all ETC Participants. While we project that the ETC Model will
reduce Medicare expenditures, ETC Participants can still earn positive
payment adjustments through their performance in the Model.
Comment: Several commenters stated that they appreciate and support
that CMS is establishing the achievement benchmarking methodology for
the remaining years of the Model through this rulemaking.
Response: As stated in the Specialty Care Models final rule (85 FR
61321), we believe that establishing changes to the achievement
benchmarking methodologies for subsequent MYs through notice-and-
comment rulemaking is transparent and will provide sufficient notice to
ETC Participants to plan for the updated achievement benchmarking
methodology.
Comment: Several commenters stated that CMS should ensure that
achievement benchmarks are achievable for ETC Participants.
Response: We agree that the achievement benchmarks should be
achievable, while ensuring that there is sufficient incentive for ETC
Participants to continue to increase rates of home dialysis and
transplantation through the duration of the Model. As discussed in the
CY 2022 ESRD PPS proposed rule and section V.B.5.c.(1) of this final
rule, we believe that the achievement benchmarking methodology we are
finalizing is achievable.
Comment: Several commenters stated that they agree with the
proposal to increase achievement benchmarks by 10 percent every two
MYs. One of these commenters stated that this increase is necessary to
sustain continued growth in the home dialysis rate and transplant rate.
Response: We appreciate the commenters' support for increasing
benchmarks by 10 percent every two MYs. We agree that this increase is
necessary to sustain continued growth in rates of home dialysis and
transplantation in the ETC Model.
Comment: A few commenters stated that increasing the home dialysis
rate by 10 percent is, or may be, achievable based on growth in home
dialysis rates observed in 2019, 2020, and 2021.
Response: We appreciate commenters' statements that a 10 percent
increase in the home dialysis rate is or may be achievable for ETC
Participants. We agree that a 10 percent increase is achievable for ETC
Participants based on recent historical growth rates. Specifically, in
the Specialty Care Models final rule (85 FR 61354), we projected a 1.5
percentage point growth rate in the home dialysis and transplant rates.
While the updated projections in the CY 2022 ESRD PPS proposed rule and
in section VIII.C.4 of this final rule assume the same projected growth
rate, initial impact estimates were based on rates of increase observed
on the home dialysis rate and transplant rate before the ETC Model
began and observed rates of increase have accelerated in more recent
data.
Comment: Several commenters stated that CMS should not increase
achievement benchmarks by 10 percent every two MYs. Some such
commenters stated that 10 percent is an arbitrary amount, that 10
percent is too large, and that 10 percent is not achievable. As
evidence that a 10 percent increase in achievement benchmarks every two
MYs is not achievable, one such commenter pointed to the lack of growth
in home dialysis observed as a result of the shift to the ESRD PPS
bundled payment system in 2011, and between 2018 and 2021, and that
transplant waitlist rates were relatively stable between 2014 and 2019.
Another commenter, who is a dialysis provider, stated that 10 percent
home dialysis growth is not consistent with their own growth rate over
the past year.
Response: We disagree with commenters that a 10 percent increase in
the achievement benchmarks every two MYs is not attainable, as we
believe that 10 percent is neither too large nor not achievable. We
also disagree that a 10 percent increase is arbitrary. As stated in the
CY 2022 ESRD PPS proposed rule and in sections V.B.5.c.(1) and
VIII.C.5.d.(10) of this final rule, we selected 10 percent based on
analysis of historical observations, attainability, transparency for
ETC Participants, and the need to preserve the expectation for model
net savings. We have also noted, as did a few commenters, that in the
recent years these observed rates of increase in the home dialysis rate
and transplant rate have accelerated and as such we continue to believe
the proposed rate of increase would be attainable for ETC Participants.
In regards to the home dialysis rate specifically, CMS acknowledges
the lack of growth in home dialysis observed following the shift to the
ESRD PPS bundled payment system in 2011. Indeed, as described in the
Specialty Care Models final rule (85 FR 61273), while CMS has
undertaken previous efforts expected to increase rates of home
dialysis, low rates of home dialysis have persisted. Therefore, the ETC
Model was designed to test the effectiveness of more significant
incentives to increase rates of home dialysis by tying payment
incentives directly to increasing rates of home dialysis. However, we
disagree with the commenter that stated that home dialysis rates have
not grown in recent years. Prior to the announcement of the ETC Model
in 2019, the home dialysis rate increased by 7.9 percent among
prevalent patients with ESRD from 2017
[[Page 61963]]
to 2018.\274\ More recently, as described in section VIII.C.5.d.(3) of
this final rule, the aggregate home dialysis rate grew by approximately
4 percent in CY 2020. Regarding the commenter who stated that 10
percent was not consistent with their own historical growth rate for
home dialysis, we have not asserted that any individual dialysis
provider has experienced this growth rate, nor do we expect any
individual dialysis provider's experience prior to the ETC Model to be
representative of future potential growth in home dialysis rates for
all ETC Participants. Instead, we have set the 10 percent increase in
the achievement benchmark based on projected growth rates in home
dialysis and transplant, based on historical observations, and we
believe that a 10-percent increase will be attainable for ETC
Participants.
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\274\ United States Renal Data System. 2020. 2020 Annual Data
Report. ``Figure 1.13 Number of prevalent ESRD patneits performing
home dialysis, 2000-2018.'' https://adr.usrds.org/2020/end-stage-renal-disease/1-incidence-prevalence-patient-characteristics-and-treatment-modalities.
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Regarding the transplant rate specifically, we acknowledge that the
transplant waitlist rates were stable between 2014 and 2019, as noted
by the commenter. However, CMS and HHS are undertaking a number of
efforts regarding transplantation, as we described in the CY 2022 ESRD
PPS proposed rule and in section V.B.4.a of this final rule. This
coordinated effort around transplant availability did not exist prior
to 2019, and we believe that this effort will facilitate increasing
rates of transplantation during the remaining MYs of the ETC Model.
Comment: One commenter stated that if CMS increases achievement
benchmarks as proposed, it should do so only for ESRD facilities owned
by LDOs, as the commenter is concerned about the ability of ESRD
facilities not owned by LDOs to increase their home dialysis and
transplant rates.
Response: We disagree with the commenter that CMS should increase
achievement benchmarks only for ESRD facilities owned by LDOs. As
discussed in the Specialty Care Models final rule (85 FR 61284), the
ETC Model is designed to test the effectiveness of using payment
adjustments to maintain or improve quality while decreasing costs by
increasing rates of home dialysis and transplants for all types of ESRD
facilities nationally, including those owned by both large and small
dialysis organizations. To determine if payment adjustments can achieve
the Model's goals of increasing rates of home dialysis utilization and
kidney transplant and, as a result, improving or maintaining the
quality of care while reducing Medicare expenditures among all types of
ESRD facilities, we need to test the model with ESRD facilities owned
by all types of dialysis organizations. By extension, we believe that
it is necessary to increase the achievement benchmarks in a consistent
manner for all ESRD facilities participating in the ETC Model,
regardless of type of ownership, to create the same incentives for all
ESRD facilities to increase rates of home dialysis and transplants.
Using the same achievement benchmarks also increases the
generalizability of the ETC Model results.
Comment: A few commenters stated that they agreed with the proposal
to set achievement benchmarks in relation to rates observed in
Comparison Geographic Areas.
Response: We appreciate commenters' support for setting achievement
benchmarks in relation to rates observed in Comparison Geographic
Areas.
Comment: Several commenters opposed setting achievement benchmarks
in relation to rates observed in Comparison Geographic Areas. These
commenters stated that basing benchmarks on BY rates in Comparison
Geographic Areas may cause dialysis organizations with ESRD facilities
to focus their resources on increasing rates in Selected Geographic
Areas to the detriment of those in Comparison Geographic Areas.
Similarly, these commenters, including LDOs, stated that this approach
could create an opportunity for dialysis organizations with ESRD
facilities in both Selected Geographic Areas and Comparison Geographic
Areas to manipulate achievement benchmarks by keeping home dialysis and
transplant rates artificially low in Comparison Geographic Areas. These
commenters stated that any such gaming by dialysis organizations would
be harmful to beneficiaries and would run counter to the intent of the
ETC Model. Another commenter stated that this dynamic could
disadvantage ESRD facilities not owned by LDOs, and further market
consolidation. Several commenters stated that CMS should use
``absolute'' or ``fixed'' benchmarks, to avoid gaming opportunities by
dialysis organizations with ESRD facilities in both Selected Geographic
Areas and Comparison Geographic Areas. These commenters suggested
setting fixed benchmarks based on rates observed in Comparison
Geographic Areas during a fixed period of time, such as Benchmark Year
1, or based on historical rates observed in Selected Geographic Areas
instead of Comparison Geographic Areas.
Response: We understand commenters' concerns that entities that own
ESRD facilities in both Selected Geographic Areas and Comparison
Geographic Areas may choose to engage in practices that limit the
growth of home dialysis and transplantation in Comparison Geographic
Areas, either because they are incentivized under the Model to focus on
Selected Geographic Areas or because they seek to manipulate or
``game'' achievement benchmarks based on rates observed in Comparison
Geographic Areas for financial gain.
The purpose of the ETC Model is to test whether the Model's payment
adjustments will change the behavior of ETC Participants to increase
rates of home dialysis and transplantation such that quality is
maintained or improved while costs are reduced. If the Model test
achieves these aims, we expect ETC Participants to behave differently
than ESRD facilities and Managing Clinicians who are not ETC
Participants. That is, we expect ETC Participants to respond to the
Model's incentives to increase rates of home dialysis and
transplantation over the course of the Model.
However, we do not expect or intend that testing the ETC Model will
harm or disadvantage beneficiaries whose ESRD facilities and Managing
Clinicians are not ETC Participants. First, there are a number of
factors that mitigate the risk that ESRD facilities owned by entities
operating in both Selected Geographic Areas and Comparison Geographic
Areas can manipulate achievement benchmarks based on rates observed in
Comparison Geographic Areas. For instance, organizations that own ESRD
facilities in both Selected Geographic Areas and Comparison Geographic
Areas do not have sole control over the rates of home dialysis,
transplant waitlisting, or living donation in Comparison Geographic
Areas. Each ESRD Beneficiary has a Managing Clinician who is
responsible for managing their dialysis care, as well as other
healthcare providers. Managing Clinicians, in particular, provide
education about renal replacement options to ESRD Beneficiaries and
Preemptive LDT Beneficiaries, and prescribe dialysis for ESRD
Beneficiaries. Unlike ESRD facilities owned by organizations with ESRD
facilities in both Selected Geographic Areas and Comparison Geographic
Areas, few Managing Clinicians are in practices that operate in both
Selected Geographic Areas and Comparison Geographic Areas, and as such
are unlikely to even be able to provide differential care in different
areas.
[[Page 61964]]
Regarding the transplant rate in particular, we recognize that ESRD
facilities play an important role in transplant waitlisting and living
donor transplants. As ESRD Beneficiaries interact with their ESRD
facility multiple times a week, ESRD facilities are well positioned to
support beneficiaries through the transplant process. Additionally,
ESRD facilities are required to conduct certain transplant-related
activities for their patients, as described in 42 CFR 494.70, 494.80,
and 494.90. However, an ESRD Beneficiary's Managing Clinician and other
healthcare providers are equally important for supporting a beneficiary
through the transplant process.
Regarding the home dialysis rate in particular, while we recognize
that certain ESRD facilities located in both Selected Geographic Areas
and Comparison Geographic Areas--namely those owned in whole or in part
by LDOs--provide the majority of dialysis, they are not the sole
providers of dialysis. Smaller chains and independent ESRD facilities,
many of which do not operate in both Selected Geographic Areas and
Comparison Geographic Areas, provide a significant volume of dialysis
services and are less likely to face the incentive described by
commenters to provide differential care in different areas, for either
resource or gaming reasons. Additionally, if the demand for home
dialysis increases but ESRD facilities owned by organizations that
operate in both Selected Geographic Areas and Comparison Geographic
Areas are unable or unwilling to increase the availability of home
dialysis in Comparison Geographic Areas, ESRD facilities owned by
smaller chains or independent ESRD facilities may be able to increase
supply to meet the unmet demand in those areas.
Second, as described in the Specialty Care Models final rule (85 FR
61320), CMS will engage in active monitoring for adverse outcomes,
including behavior described by commenters, and we intend to make
adjustments to the Model through subsequent rulemaking should such
unintended consequences arise. We also note that CMS may take remedial
action under Sec. 512.160 of our regulations if an ETC Participant
fails to comply with any terms of the Model, including the provisions
protecting beneficiary freedom of choice and availability of services
under Sec. 512.120 of our regulations, or if an ETC Participant has
taken any action that threatens the health or safety of a beneficiary
or other patient.
Taken together we believe that these factors, coupled with CMS's
monitoring efforts and ability to take remedial action, mitigate the
risk that entities that own ESRD facilities in both Selected Geographic
Areas and Comparison Geographic areas will alter achievement benchmarks
by manipulating rates in Comparison Geographic Areas.
Comment: A few commenters stated that CMS should use the
methodology used to set the performance standards under the ESRD QIP
for setting achievement benchmarks under the ETC Model. One such
commenter stated that the ESRD QIP performance standard setting
methodology is preferable to the achievement benchmarking approaches
described in the CY 2022 ESRD PPS proposed rule because it would
continue to incentivize improved performance while not relying on rates
observed in Comparison Geographic Areas, and is simple and familiar to
ESRD facilities. This commenter also stated that the ESRD QIP
methodology was preferable because it does not allow performance
standards to decrease over time.
Response: As stated in the Specialty Care Models final rule, we do
not believe the ESRD QIP methodology is well suited for the ETC Model
(85 FR 61322 through 61323). In particular, we continue to believe that
the ESRD QIP performance standard setting methodology does not ensure
escalating performance standards over time, which is an important
design feature for the ETC Model. Similarly, we continue to recognize
that, while ESRD facilities are familiar with the ESRD QIP performance
standard setting methodology because they are already subject to it,
Managing Clinicians are not.
Comment: A few commenters stated that CMS should use population-
weighted achievement benchmarks, to account for variation in size among
aggregation groups. One such commenter stated that population-weighted
benchmarks are more appropriate because of the difference in absolute
change necessary for larger and smaller aggregation groups to achieve
the same relative performance. That is, relative to smaller aggregation
groups, larger aggregation groups need to have a larger number of
individual beneficiaries change from in-center dialysis to home
dialysis, self-dialysis, or nocturnal in-center dialysis to increase
their home dialysis rate; or to have a larger number of individual
beneficiaries be waitlisted for transplant or receive a living donor
transplant to increase their transplant rate to achieve the same level
of performance. The commenter also stated that larger aggregation
groups have a larger absolute impact on the number of beneficiaries who
dialyze at home or are placed on the transplant waitlist, and therefore
should not be compared to smaller aggregation groups who may have the
same relative level of performance but a smaller absolute impact.
Response: We appreciate commenters' suggestion that we use
population-weighted benchmarks. However, we did not propose this
approach, and we are not contemplating this change at this time.
Additionally, we disagree with the commenter who stated that
population-weighted benchmarks are more appropriate because larger
aggregation groups need to increase rates of home dialysis, transplant
waitlisting, and living donor transplants among a larger number of
beneficiaries relative to smaller aggregation groups to achieve the
same level of performance. We believe that that this approach would
unfairly disadvantage smaller aggregation groups, holding them to a
higher relative standard solely because they have fewer attributed
beneficiary months. We also disagree that larger aggregation groups
should be held to a lower relative standard than smaller aggregation
groups because they have a larger absolute impact.
Comment: One commenter opposed the negative payment adjustments
included in the ETC Model and suggested that the Model instead have
only positive payment adjustments.
Response: As noted in the Specialty Care Models final rule (85 FR
61264), the purpose of the ETC Model is to test whether the payment
adjustments included in the Model will reduce Medicare expenditures
while improving or maintaining quality of care. As further stated in
the Specialty Care Models final rule (85 FR 61323), we believe that
downside risk is a critical component of this Model in order to create
strong incentives for behavioral change among ETC Participants, that is
by encouraging participating Managing Clinicians and ESRD facilities to
support beneficiaries choosing home dialysis and transplantation. We
therefore disagree that eliminating the negative adjustments would
provide sufficient incentive to encourage behavior change leading to
the achievement of the goals of the Model.
Comment: One commenter stated that, instead of increasing
achievement benchmarks to increase rates of home dialysis and
transplantation, CMS should instead focus on increasing participation
in the ETC Model in more areas of the country, if the ETC Model is
successful at increasing rates of home dialysis and transplantation.
[[Page 61965]]
Response: As described previously in section V.A.3 of this final
rule, the purpose of the ETC Model is to test the effectiveness of
adjusting certain Medicare payments to ESRD facilities and Managing
Clinicians to encourage greater utilization of home dialysis and kidney
transplantation, support beneficiary modality choice, reduce Medicare
expenditures, and preserve or enhance the quality of care. If the Model
meets the criteria set forth in section 1115A(c) of the Act, we may
consider expanding the duration and scope of the ETC Model. However,
the Model calculates benchmarks and assesses ETC Participant
performance against rates of home dialysis, transplant waitlisting, and
living donor transplantation among similar Managing Clinicians or ESRD
facilities located in Comparison Geographic Areas. A limitation on
Model participation is therefore currently necessary to ensure there
are sufficient comparators for these purposes.
Comment: One commenter stated that we should update the PPA
methodology by increasing the weight of the transplant rate to be equal
to the home dialysis rate, or by separating out the transplant rate
completely so that one is not dependent on the other.
Response: As discussed in the Specialty Care Models final rule (85
FR 61319), CMS had considered making the home dialysis rate score and
the transplant rate score equal components of the Modality Performance
Score (MPS) used in calculating the PPA. However, we recognized that
transplant rates may be more difficult for ETC Participants to improve
than home dialysis rates, due to the limited supply of organs and the
number of other providers or suppliers that are part of the transplant
process. For this reason, under the PPA methodology, home dialysis
rates take a greater weight than transplant rates.
Comment: One commenter suggested that CMS modify the Model such
that the MPS applies only to Managing Clinicians as, by the time a
beneficiary begins dialysis with an ESRD facility, it is too late for
the ESRD facility to encourage pre-emptive transplant and pre-emptive
transplant recipients will see an ESRD facility only after a transplant
rejection.
Response: We would like to clarify for the commenter that the MPS
is calculated for all ETC Participants based on their home dialysis
rate and transplant rate, in order to determine the ETC Participant's
PPA. However, the pre-emptive transplant rate is part of the transplant
rate calculation only for Managing Clinicians.
Final Rule Action: After considering public comments, we are
finalizing our proposal in our regulation at Sec. 512.370(b) to
increase achievement benchmarks by 10 percent every two MYs above rates
observed in Comparison Geographic Areas, as proposed.
(2) Achievement Benchmark Stratification by Dual-Eligible and Low
Income Subsidy (LIS) Status
We also proposed to modify Sec. 512.370(b) to stratify achievement
benchmarks based on the proportion of beneficiary years attributed to
the ETC Participant's aggregation group for which attributed
beneficiaries were dually-eligible for Medicare and Medicaid or
received the LIS, based on rates in Comparison Geographic Areas (86 FR
36384). Under our proposal, we would create two strata with the
cutpoint set at 50 percent of attributed beneficiary years being for
attributed beneficiaries who were dual-eligible or received the LIS. As
such, there would be one stratum for ETC Participants whose aggregation
groups had 50 percent or more of their attributed beneficiary years
during the MY for beneficiaries who were dual-eligible or received the
LIS, based on rates in Comparison Geographic Areas for aggregation
groups with 50 percent or more attributed beneficiary years during the
Benchmark Year being for dual-eligible or LIS beneficiaries. There
would be a second stratum for ETC Participants whose aggregation groups
had less than 50 percent of their attributed beneficiary years during
the MY for beneficiaries who were dual-eligible or received the LIS,
based on rates in Comparison Geographic Areas for aggregation groups
with less than 50 percent attributed beneficiary years during the
Benchmark Year being for dual-eligible or LIS beneficiaries. We
proposed to determine whether an attributed beneficiary was dual-
eligible or received the LIS for a given month using Medicare
administrative data. In the CY 2022 ESRD PPS proposed rule, we stated
our belief that this proposal would address concerns that socioeconomic
factors may impact a beneficiary's likelihood to receive alternative
renal replacement modalities, lowering the transplant rate and home
dialysis rates for ETC Participants who provide services to low income
beneficiaries. We also stated our expectation that stratifying the
achievement benchmarks as proposed would increase home dialysis rate
and transplant rates for such ETC Participants.
In the CY 2022 ESRD PPS proposed rule, we considered using more
than two strata, in order to increase the precision of the achievement
benchmarks and the degree of similarity between ETC Participants within
a given stratum. However, we noted that increasing the number of strata
would decrease the number of observations within each stratum, in turn
decreasing statistical reliability. Additionally, analysis of the
distribution of the home dialysis rate and transplant rate demonstrates
that the underlying distribution does not lend itself to more than two
strata, as the distribution is not multi-modal. For this reason, we
proposed only two strata.
We sought public comment on our proposal to amend Sec. 512.370(b)
to stratify achievement benchmarks based on the proportion of
attributed beneficiary years for which attributed beneficiaries were
dual-eligible or received the LIS, and on our proposal to create two
strata for this purpose.
The following is a summary of the comments received on our proposal
to stratify achievement benchmarks based on the proportion of
attributed beneficiary years for which attributed beneficiaries were
dual eligible or received the LIS beginning for MY3, including our
policy to create two strata for this purpose, and our responses.
Comment: Two commenters expressed support for addressing
socioeconomic factors that impact ETC Participant achievement. These
commenters also specifically supported CMS's recognition of the two
proposed categories of beneficiaries who are economically disadvantaged
for this purpose, namely beneficiaries who are dual-eligible or are LIS
recipients. Several commenters stated that they agree that
beneficiaries who are dual eligible or LIS recipients may be less
likely to dialyze at home or receive a kidney transplant.
Response: We appreciate the commenters' support.
Comment: Multiple commenters stated that they supported stratifying
the achievement benchmarks based on the proportion of beneficiary years
attributed to the ETC Participant's aggregation group for which
attributed beneficiaries were dual-eligible or LIS recipients. Several
of these commenters expressed specific reasons for their support. A few
of these commenters expressed support for stratification because they
agree that stratification will support the goal of not disadvantaging
ETC Participants who treat a high proportion of socioeconomically
disadvantaged beneficiaries. One of these commenters
[[Page 61966]]
stated that stratification addresses concerns that socioeconomic
factors outside the ETC Participant's control may impact a
beneficiary's likelihood to receive alternative renal replacement
modalities.
Response: We appreciate the commenters' support.
Comment: One commenter indicated that while dually eligible and
LIS-recipient beneficiaries are important groups of underserved
beneficiaries, this proxy does not illuminate the diversity of
underserved communities or individuals facing health disparities due to
complex socioeconomic circumstances in the United States.
Response: We understand that beneficiaries face challenges and
barriers to choosing alternatives to traditional in-center dialysis in
particular, and to accessing healthcare generally, related to their
socioeconomic circumstances. We have recognized that there is variation
in rates of home dialysis and transplantation by socioeconomic status.
As discussed in the CY 2022 ESRD PPS proposed rule and in this section
of this final rule, we know that socioeconomic status impacts the
likelihood of a beneficiary receiving home dialysis or a transplant. In
order to address these socioeconomic factors that impact ETC
Participant Achievement, one of our proposals is to stratify
achievement benchmarks based on the proportion of attributed
beneficiaries who are dually-eligible for Medicare and Medicaid or
receive the LIS during the MY, in recognition that beneficiaries with
lower socioeconomic status have lower rates of home dialysis and
transplant than those with higher socioeconomic status.
Comment: One commenter asked that, if the Innovation Center intends
to proceed with the proposal to stratify achievement benchmarks by the
proportion of beneficiaries who are dual eligible or received the LIS,
CMS should release information to the public regarding LIS
beneficiaries so that the commenter could adequately analyze the ETC
Model, and implement work plans to address the needs of this
population.
Response: We generally do not share beneficiary-identifiable data
related to a model tested under section 1115A of the Act with
individuals or entities who are not participants in said model.
However, CMS data for research is available via the Research Data
Assistance Center (ResDAC). Additional information about ResDAC is
available at resdac.org. A variety of aggregate data is also available
directly from CMS at data.cms.gov, including the Mapping Medicare
Disparities Tool.
Comment: One commenter supported any and all measures that
incentivize care for beneficiaries who are dual-eligible or LIS
recipients. However, this commenter expressed that the proposal to
stratify achievement benchmarks based on the proportion of attributed
beneficiary years for which attributed beneficiaries were dual eligible
or received the LIS might make dual-eligible and LIS recipients feel
pressured to try a method of care that will not be successful for them.
This commenter stated that these patients are often not used to
advocating for themselves, so an incentive to the providers may seem
like a threat to the patients.
Response: We believe that addressing disparities experienced by
beneficiaries who are dual-eligible or LIS recipients by stratifying
the achievement benchmarks, as proposed, will encourage ETC
participants to decrease disparities in renal replacement modality
choice across beneficiaries of different socioeconomic status. However,
we are sensitive to concerns about ETC Participants exerting undue
influence on this beneficiary population, in particular. As stated in
the Specialty Care Models final rule, ETC Participants are prohibited
from interfering with a beneficiary's freedom of choice or access to
services under 42 CFR 512.120, and CMS will monitor for ETC Participant
compliance with this requirement, including beneficiary complaints and
appeals (85 FR 61341 through 61343).
Comment: A few commenters expressed concern about the proposal to
stratify benchmarks by the proportion of attributed beneficiaries who
are dual-eligible or LIS recipients. These commenters stated that they
believed this approach could unnecessarily set a lower bar for
achieving access to transplant and home dialysis by conflating
differences owing to social risk factors and true differences in
quality of care. Two of these commenters stated that they do not
believe patient income or dual eligible status should be a factor in
access to home dialysis or transplant and remain concerned that
benchmark stratification could possibly worsen inequities by reducing
Model-specific incentives to increase access to home dialysis for all
patients.
Response: As discussed in the CY 2020 ESRD PPS proposed rule and in
section V.B.6.c this final rule, we believe that stratifying
achievement benchmarks based on the proportion of beneficiary years
attributed to the ETC Participant's aggregation group for which
attributed beneficiaries were dually-eligible for Medicare and Medicaid
or received the LIS, based on rates in Comparison Geographic Areas,
will address concerns that socioeconomic factors may impact a
beneficiary's likelihood to receive alternative renal replacement
modalities, lowering the transplant rate and home dialysis rates for
ETC Participants who provide services to low income beneficiaries.
We do not believe that stratifying benchmarks by dual eligible and
LIS recipients would unnecessarily set a lower bar for achieving access
to transplant and home dialysis for these individuals. Rather, as
discussed in the CY 2020 ESRD PPS proposed rule and in section V.B.6.c
of this final rule, we expect that stratifying the achievement
benchmarks as proposed will increase home dialysis rate and transplant
rates for those ETC Participants who provide services to low-income
beneficiaries. Specifically, rather than giving ETC Participants
permission to provide lower levels of care to beneficiaries, we believe
this approach will enable ETC Participants to address disparities in
renal replacement modality choice among beneficiaries who are dual-
eligible or LIS recipients by not disadvantaging them by comparing them
to a standard set including a substantively different beneficiary
population. While we understand that stratification would not provide a
direct financial incentive for ETC Participants to focus on reducing
disparities by improving the home dialysis rate and transplant rate for
beneficiaries who are dual-eligible or receive the LIS, as ETC
Participants who provide services to socioeconomically disadvantaged
beneficiaries are likely to have lower home dialysis rates and
transplant rates, stratification makes it more likely they will achieve
a positive PPA that they can invest in caring for these beneficiaries.
We believe ETC Participants will be able to use additional funds
received as a result of receiving a positive PPA to improve their
performance dialysis rates and transplant rates for all beneficiaries,
including beneficiaries who are dual eligible and recipients of LIS.
Comment: Several commenters indicated that they supported
stratifying achievement benchmarks based on dual eligible and LIS
recipient status, but suggested modifications to the proposed approach.
Some of these commenters suggested using a different cutpoint. Of the
commenters suggesting a different cutpoint, some suggested a higher
cutpoint and others suggested a lower cutpoint than 50 percent of
attributed beneficiary years being for attributed
[[Page 61967]]
beneficiaries who were dual eligible or received the LIS. One commenter
suggesting a higher cutpoint stated that this approach would better
enable ETC Participants serving the highest percentage of low-income
patients to successfully perform in the ETC Model. Some commenters
suggesting modifications had suggested using more than two strata--
including suggestions of three to ten strata--or using a sliding scale.
Some commenters suggesting using more than two strata stated that doing
so would provide more nuance to the PPA calculation. Generally,
commenters suggesting alternative cutpoints or more than two strata
stated that their suggested cutpoint or number of strata was more
reflective of the commenters' own analysis of available data.
Response: We appreciate the commenters support for stratifying
achievement benchmarks. As discussed in the proposed rule and
previously in this section of the final rule, we considered using more
than two strata in order to increase the precision of the achievement
benchmarks and the degree of similarity between ETC Participants within
a given stratum. This would have required the use of additional
cutpoints--both lower and higher than 50 percent. In response to
suggestions that we use more than two strata, as described in the CY
2022 ESRD PPS proposed rule and previously in this section of this
final rule, increasing the number of strata would decrease the number
of observations within each stratum, in turn decreasing statistical
reliability. We continue to believe that that using more than two
strata would decrease statistical reliability. Additionally, as
described in the CY 2022 ESRD PPS proposed rule and in this section of
this final rule, our analysis of the distribution of the home dialysis
rate and transplant rate demonstrated that the underlying distribution
does not lend itself to more than two strata, as the distribution is
not multi-modal. In response to suggestions that we use a different
cutpoint between strata, we believe that 50 percent is an appropriate
cutpoint based on our analysis of the data. Based on the statistical
properties of the underlying distribution, the 50 percent cutpoint is
statistically appropriate, stable over time, and easily comprehendible
to ETC Participants.
Comment: One commenter stated that while they support
stratification, CMS should adjust performance within each stratum to
account for variation within the stratum.
Response: While we recognize that there will be variation within
each stratum, the commenter did not articulate what adjusting
performance within each stratum should entail. Therefore, we are unable
to respond with specificity to the suggestion that we adjust
performance within each stratum. We continue to believe that
stratification addresses variation in rates of home dialysis and
transplantation for beneficiaries who are dual eligible or LIS
recipients, but remain open to specific feedback regarding further
adjustments for potential inclusion in future rulemaking.
Comment: Several commenters expressed support for CMS' proposal to
use dual eligible and LIS recipient as proxies for socioeconomic
status. One of these commenters stated that they agree that these are
useful metrics to identify patients who may face clinical and non-
clinical challenges to electing home dialysis or receiving a
transplant.
Response: We thank commenters for their support.
Comment: A few commenters stated that they agreed with the intent
behind, or the need for, an approach to address how socioeconomic
factors impact beneficiaries' likelihood of receiving home dialysis or
a kidney transplant and how that relationship impacts ETC Participants'
performance, but stated that there may be better ways to account for
this than stratification of the achievement benchmark. A few of these
commenters suggested that CMS incorporate risk adjustment into the
achievement benchmarking methodology, either instead of or in addition
to stratification. Commenters suggesting risk adjustment stated that
risk adjustment is more precise, because it is applied at the
beneficiary-level, rather than the aggregate level. However, one such
commenter acknowledged that, while they recommend risk adjustment,
stratification may also address the same underlying issues.
Response: We considered other approaches for accounting for how the
socioeconomic status of an ETC Participant's attributed beneficiaries
may impact an ETC Participant's performance. However, we did not
contemplate using risk adjustment for this purpose. While we appreciate
that risk adjustment accounts for factors at an individual beneficiary
level, adopting this policy would represent a significant departure
from our proposal and would present its own challenges. For instance,
without sufficient protections, the use of risk adjustment can result
in payment inaccuracies due to factors such as upcoding. In addition,
depending on the factors being used for risk-adjustment, there may be
limitations in the available data, as discussed below. After
considering the comments, we continue to believe that stratification of
achievement benchmarks based on dual eligible and LIS recipient status
is an appropriate approach for considering socioeconomic status under
the ETC Model.
Comment: A few commenters recommended that CMS also consider
incorporating additional social risk factors into the achievement
benchmarking methodology. One such commenter acknowledged that current
data on social determinants of health necessary to develop such a
methodology is limited, citing Z-code data in particular, and that in
the interim, stratification may address many of the concerns related to
differential rates of home dialysis and transplantation between
beneficiaries of higher and lower socioeconomic status. Another
commenter stated that while dual eligibility and LIS recipient status
can serve as proxies for social risk factors, this is not equivalent to
patient-level data on individual risk factors. This commenter also
pointed out that criteria for dual eligibility vary between states, and
that being a LIS recipient is dependent on the beneficiary having been
enrolled in a Part D plan.
Response: As stated in the CY 2022 ESRD PPS proposed rule and this
section of this final rule, we continue to acknowledge that non-
clinical factors, such as socioeconomic status, may impact a
beneficiary's likelihood to receive home dialysis or a transplant.
However, revising the proposed policy to include additional risk
adjustments in the home dialysis rate based on socioeconomic status, as
suggested by some of the commenters, would be a significant departure
from the policy originally proposed. We also agree with the commenter
who acknowledged the current limitations in data on individual-level
social determinants of health. At this time, we continue to believe
stratification using the proportion of attributed beneficiaries who are
dual-eligible or LIS recipients is an appropriate means of considering
socioeconomic status under the ETC Model. Moreover, while we
acknowledge that dual eligibility and LIS recipient status may not
capture socioeconomic status in the same way for all beneficiaries--due
to variation between states or the necessity of being enrolled in a
Part D plan to be an LIS recipient--as stated in the CY 2022 ESRD PPS
proposed rule and in section V.B.5.b of this final rule, dual
eligibility and LIS recipient status are correlated with lower rates of
home dialysis and transplantation. As such, ETC
[[Page 61968]]
Participants who have a higher proportion of attributed beneficiaries
who are dual eligible or LIS recipients may be less likely to achieve
high home dialysis and transplant rates than ETC Participants who have
a lower proportion of attributed beneficiaries who are dual-eligible or
LIS recipients. Therefore, we believe dual eligible and LIS status are
appropriate proxies for socioeconomic status. If Z-codes become more
widely used and more such codes become available for use into the
claims process, such that Z-code data becomes appropriate for use, we
may consider incorporating such data into the ETC Model methodology
through future rulemaking.
Final Rule Action: After considering public comments, we are
finalizing our proposal in our regulation at Sec. 512.370(b)(2) to
stratify achievement benchmarks based on the proportion of attributed
beneficiary years for which attributed beneficiaries were dual eligible
or received the LIS beginning for MY3, and to create two strata for
this purpose, without modification.
6. PPA Improvement Benchmarking and Scoring
a. Background on Improvement Benchmarking and Scoring
Another part of the scoring methodology for the PPA is improvement
scoring. We calculate an ETC Participant's improvement score under
Sec. 512.370(c) by comparing MY performance on the home dialysis rate
and transplant rate against past ETC Participant performance. As
described in the Specialty Care Models final rule, the purpose of the
improvement score is to acknowledge efforts made in practice
transformation to improve rates of home dialysis and transplants (85 FR
61318). The percentage improvement in the ETC Participant's MY
performance on the home dialysis rate and the transplant rate relative
to the Benchmark Year rate is scored as follows:
Greater than 10 percent improvement relative to the Benchmark
Year rate: 1.5 points
Greater than 5 percent improvement relative to the Benchmark
Year rate: 1 point
Greater than 0 percent improvement relative to the Benchmark
Year rate: 0.5 points
Less than or equal to the Benchmark Year rate: 0 points
However, when the Benchmark Year rate is zero, an improvement score
for the MY cannot be calculated. This is because, when calculating
percent change, as used in improvement scoring, the Benchmark Year rate
is the denominator. As such, we cannot calculate percent improvement
for an aggregation group with a rate of zero during the Benchmark Year
because the denominator of the improvement score calculation is zero,
and division by zero is undefined. Thus, an aggregation group in this
situation will not receive an improvement score if the Benchmark Year
rate is zero, even if the aggregation group has made improvements in
the home dialysis rate and/or the transplant rate between the Benchmark
Year and MY.
b. Incentivizing Improvement for Socioeconomically Disadvantaged
Beneficiaries
As described in the CY 2022 ESRD PPS proposed rule and in section
V.B.5.b of this final rule, beneficiaries who are dual-eligible or
receive the LIS are less likely than beneficiaries who are not dual-
eligible and do not receive the LIS to dialyze at home or receive a
kidney transplant. As described in the CY 2022 ESRD PPS proposed rule
and previously in this section of the final rule, we proposed to
stratify achievement benchmarks by the proportion of attributed
beneficiary years for beneficiaries who are dual-eligible or LIS
recipients to avoid disadvantaging ETC Participants who provide care
for a high proportion of these beneficiaries. However, we noted that
the proposed stratification would not provide a direct financial
incentive for ETC Participants to focus on reducing disparities by
improving the home dialysis rate and transplant rate for beneficiaries
who are dual-eligible or receive the LIS. In the CY 2022 ESRD PPS
proposed rule, we stated our interest in creating that incentive as
part of the ETC Model, as these beneficiaries may require additional
support from ETC Participants to pursue home dialysis and transplant as
alternative renal replacement modalities (86 FR 36384).
c. Changes to Improvement Benchmarking and Scoring
(1) Revised Improvement Calculation
As described previously, when the Benchmark Year rate for an
aggregation group is zero, the aggregation group cannot receive an
improvement score, even if the aggregation group has made improvements
in the home dialysis rate and transplant rate between the Benchmark
Year and MY. To address this issue, we proposed to amend Sec.
512.370(c)(1) to change the improvement calculation such that the
aggregation group's Benchmark Year rate cannot be zero. Specifically,
for MY3 through MY10, we proposed to add one beneficiary month to the
numerator of the home dialysis rate and the transplant rate for the
Benchmark Year rate for an ETC Participant's aggregation group
Benchmark Year when that rate is zero (86 FR 36384). CMS did not
propose to change the denominator of the Benchmark Year rate
calculations because doing so would negate the purpose of
mathematically correcting ETC Participants' improvement scoring. In the
CY 2022 ESRD PPS proposed rule, we stated that CMS does not expect that
adding a beneficiary month to the numerator of the Benchmark Year rate
calculations, as proposed, would affect the improvement scoring enough
to change the number of points awarded to the ETC Participant, and has
the advantage that it would enable an improvement score to be
calculated, even when the Benchmark Year rate is zero.
The following is a summary of the comments received on our proposal
to modify the calculation of the an ETC Participant's Benchmark Year
home dialysis rate and transplant rate to prevent it from being zero,
such that an improvement score can be calculated, and our responses.
Comment: A few commenters stated that they support the proposal to
add one beneficiary month to the numerator of the home dialysis rate
and the transplant rate for the Benchmark Year rate for an ETC
Participant's aggregation group Benchmark Year when that rate is zero.
Response: We appreciate commenters' support for this proposal.
Comment: One commenter suggested that CMS change the improvement
scoring methodology to allow ETC Participants to attain the top tier of
scoring--2 points--through improvement alone.
Response: As stated in the Specialty Care Models final rule (85 FR
61322), while we acknowledge the importance of incentivizing
improvement over time, we do not award full points for improvement for
consistency with other CMS programs and initiatives employing similar
improvement scoring methodologies. Additionally, with the introduction
of the Health Equity Incentive, as described in the CY 2022 ESRD PPS
proposed rule and in section V.B.6.c.(2) of this final rule, ETC
Participants are able to, beginning for MY3, attain the full 2 points
for improvement if they demonstrate greater than 10 percent improvement
relative to the Benchmark Year rate and earn the Health Equity
Incentive.
Final Rule Action: After considering public comments, we are
finalizing our
[[Page 61969]]
proposal in our regulation at Sec. 512.370(c)(1) to add one
beneficiary month to the numerator of the ETC Participant's Aggregation
Group's home dialysis rate and transplant rate for the Benchmark Year
when calculating the ETC Participant's improvement score beginning for
MY3, without modification.
(2) Health Equity Incentive
To incentivize ETC Participants to decrease disparities in the home
dialysis rate and transplant rate between beneficiaries who are dual-
eligible or LIS recipients and those who are not, we proposed to add a
Health Equity Incentive to the improvement scoring methodology (86 FR
36385). We proposed to define the Health Equity Incentive at Sec.
512.310 as the amount added to the ETC Participant's improvement score
calculated as described in Sec. 512.370(c)(1) if the ETC Participant's
aggregation group demonstrated sufficient improvement on the home
dialysis rate or transplant rate for attributed beneficiaries who are
dual-eligible or LIS recipients between the Benchmark Year and the MY.
We proposed that this improvement on the home dialysis rate or
transplant rate would be based on the performance of the ETC
Participant's aggregation group.
As noted in the CY 2022 ESRD PPS proposed rule and previously in
this section of the final rule, socioeconomic factors impact a
beneficiary's receipt of alternative renal replacement modalities.
Beneficiaries with limited resources may require more assistance from
ESRD facilities and Managing Clinicians to use alternative renal
replacement modalities. In the CY 2022 ESRD PPS proposed rule, we
stated our belief that our proposal to add a Health Equity Incentive
would benefit these beneficiaries and improve scoring for home dialysis
rate and transplant rate for ETC Participants that serve
disproportionately high numbers of beneficiaries with lower
socioeconomic status. To earn the Health Equity Incentive, ETC
Participants would have to demonstrate sufficiently significant
improvement on the home dialysis rate or transplant rate among their
attributed beneficiaries who are dual eligible or receive the LIS
between the Benchmark Year and the MY. ETC Participants who earn the
Health Equity Incentive would receive a 0.5-point increase on their
improvement score, thus increasing the maximum improvement score to 2
points. In the CY 2022 ESRD PPS proposed rule, we stated our belief
that the proposed Health Equity Incentive would benefit attributed
beneficiaries who are dual eligible or receive the LIS, by encouraging
ETC Participants to address disparities in access to alternative renal
replacement modalities among these beneficiaries. We also stated our
belief that providing this incentive for ETC Participants to increase
their home dialysis and transplant rate among their dual eligible or
LIS beneficiary population would ultimately reduce this disparity in
access for the beneficiaries in question. Therefore, we stated our
belief that this incentive to reduce socioeconomic disparities in
access to alternative renal replacement modalities would be an
improvement to the PPA scoring methodology.
We proposed to amend Sec. 512.370(c) to add the Health Equity
Incentive to the improvement scoring methodology, beginning for MY3. We
proposed that the Health Equity Incentive would be equal to 0.5 points,
which would be added to the ETC Participant's improvement score for the
home dialysis rate or for the transplant rate, calculated as described
in Sec. 512.370(c)(1), such that the maximum improvement score would
increase from 1.5 points to 2 points for ETC Participants that earn the
Health Equity Incentive. Therefore, for those ETC Participants that
earn the Home Equity Incentive, we proposed that the ETC Participant's
improvement score for the home dialysis rate and for the transplant
rate would be the sum of the improvement score calculated as described
in Sec. 512.370(c)(1) and the Health Equity Incentive. We noted in the
CY 2022 ESRD PPS proposed rule that the Health Equity Incentive would
allow ETC Participants to increase their improvement score, and thereby
increase their payment adjustment.
We proposed to award the Health Equity Incentive to an ETC
Participant if the ETC Participant's aggregation group's home dialysis
rate and/or transplant rate among attributed beneficiaries who are
dual-eligible or LIS recipients increases by 5 or more percentage
points from the Benchmark Year to the MY. We stated our belief in the
CY 2022 ESRD PPS proposed rule that 5-percentage points is the correct
threshold for awarding the Health Equity Incentive based on our
analysis of Medicare claims. Five percentage points is one standard
deviation above the average difference between the home dialysis rate
and the transplant rate for attributed beneficiaries who are dual-
eligible or LIS recipients and those beneficiaries who are not dual-
eligible or LIS recipients, rounded to the nearest integer. In the CY
2022 ESRD PPS proposed rule, we noted that we anticipate improvement in
home dialysis and transplant rates among dual-eligible or LIS
recipients between the MY and the Benchmark Year, but that we expect
that attaining the proposed threshold for earning the Health Equity
Incentive would generally require significant effort on the part of the
ETC Participant.
We proposed that an ESRD Beneficiary or Pre-emptive LDT Beneficiary
would be considered to be dual-eligible or a LIS recipient for a given
month if at any point during the month the beneficiary was dually
eligible for Medicare and Medicaid or a LIS recipient. We proposed to
determine whether an attributed beneficiary was dual-eligible or
received the LIS using Medicare administrative data.
We proposed to modify Sec. 512.370(c) such that the improvement
benchmarking and scoring methodology for MY1 and MY2 would be specified
at Sec. 512.370(c)(1), and the improvement benchmarking and scoring
methodology for MY3 through MY10, described earlier, would be specified
at Sec. 512.370(c)(2). We sought comment on the proposal to modify
Sec. 512.370(c) accordingly.
In the CY 2022 ESRD PPS proposed rule, we considered using a
rolling approach to setting the threshold for earning the Health Equity
Incentive, such that the threshold would be recalculated every other
MY, to reflect changes in underlying disparities. Under this approach,
we would calculate the threshold as one standard deviation above the
average difference between the home dialysis rate and the transplant
rate for attributed beneficiaries who are dual-eligible or LIS
recipients and those beneficiaries who are not dual-eligible or LIS
recipients, rounded to the nearest integer. We would calculate this
threshold either using data from the Benchmark Year, such that ETC
Participants would know the threshold for earning the Health Equity
Incentive in advance of the MY, or using data from the MY, such that
the threshold for earning the Health Equity Incentive would accurately
reflect the magnitude of the disparity observed during the MY. However,
we stated our belief that setting a threshold for earning the Health
Equity Incentive applicable for all MYs, beginning for MY3, would be
more appropriate. We noted that this approach would be in keeping with
the intent of the proposed Health Equity Incentive, which is to provide
ETC Participants a financial incentive to focus on decreasing the
disparity in the home dialysis and transplant rates between
beneficiaries who are dual-eligible or LIS recipients, and those who
[[Page 61970]]
are not. We further stated our belief that providing ETC Participants
clear information about what they need to achieve to earn the Health
Equity Incentive in advance would best enable them to work towards the
goal.
We proposed that ETC Participants in aggregation groups that fall
below a low-volume threshold would be ineligible to earn the Health
Equity Incentive (86 FR 36386). Specifically, we proposed that an ETC
Participant in an aggregation group with fewer than 11 attributed
beneficiary years comprised of months in which ESRD Beneficiaries and,
if applicable, Pre-emptive LDT Beneficiaries are dual eligible or LIS
recipients during either the Benchmark Year or the MY would be
ineligible to earn the Health Equity Incentive. We selected this
particular low-volume threshold for consistency with the low-volume
threshold for the applicability of the PPA generally, as specified at
Sec. 512.385. We stated our belief that it is necessary to apply a low
volume threshold in determining whether an ETC Participant has earned
the Home Equity Incentive to ensure statistical reliability of the home
dialysis rate and transplant rate calculations. This statistical
reliability provides consistency in the home dialysis rate and
transplant rate calculations. Therefore, similar results are produced
under consistent conditions when applying a low volume threshold to ETC
Participants. We proposed a low-volume threshold specific to attributed
beneficiaries who are dual-eligible or receive the LIS because whether
an ETC Participant has earned the Health Equity Incentive is being
assessed on this subset of attributed beneficiaries.
We proposed to amend the Modality Performance Score (MPS)
methodology to incorporate the Health Equity Incentive. To that end, we
proposed to modify Sec. 512.370(d) such that the calculation of the
MPS for MY1 and MY2 is specified at Sec. 512.370(d)(1), and the
calculation of the MPS for MY3 through MY10 is specified at Sec.
512.370(d)(2). We proposed that the formula for the MPS for MY3 through
MY10 would be the following:
Modality Performance Score
= 2 x (Higher of the home dialysis achievement or (home dialysis
improvement score + Health Equity Bonus [dagger]))
+ (Higher of the transplant achievement or (transplant improvement
score + Health Equity Bonus [dagger]))
[dagger] The Health Equity Incentive is applied to the home
dialysis improvement score or transplant improvement score only if
earned by the ETC Participant and provided that the ETC Participant
is not ineligible to receive the Home Equity Incentive as described
in proposed Sec. 512.370(c)(2)(iii).
We sought comment on our proposed definition for the Health Equity
Incentive at Sec. 512.310 and our proposal to amend Sec. 512.370(c)
to add the Health Equity Incentive to the improvement scoring
methodology for the home dialysis rate and the transplant rate. We also
sought comment on our proposal to set the threshold for earning the
Health Equity Incentive at 5-percentage points improvement from the
Benchmark Year to the MY.
The following is a summary of the comments received on the proposal
to introduce the Health Equity Incentive to the improvement scoring
methodology beginning for MY3, and our responses.
Comment: Many commenters expressed support for the concept of
addressing socioeconomic disparities in access to alternative renal
replacement modalities through the ETC Model. A few commenters
highlighted that particular groups that tend to experience healthcare
disparities--including patients of lower socioeconomic status and
patients from racial and ethnic minorities--make up a significant
portion of dialysis patients.
Response: We appreciate the commenters' support.
Comment: One commenter stated that the racial and ethnic
disparities in access to home dialysis care have long existed, but that
the COVID-19 pandemic has exacerbated them. According to the commenter,
increased access to home dialysis modalities would give those
historically disadvantaged patients the chance to avoid potentially
dangerous contact with COVID-19 infected individuals by reducing visits
to a dialysis clinic or doctor's office. The commenter stated that, for
all of these important reasons, they strongly support CMS's efforts to
advance home dialysis through the ETC Model.
Response: We agree with the commenter that COVID-19 pandemic has
highlighted one of the benefits of home dialysis--that dialyzing at
home reduces the risk that an individual patient is exposed to COVID-19
or other communicable diseases in the course of their dialysis care--
and we agree that beneficiaries should have equal access to this
modality for this and other reasons.
Comment: A few commenters expressed concerns about the impact of
the ETC Model on health disparities. One commenter expressed concern
about certain design aspects of the ETC Model that could have
unintended effects that perpetuate existing kidney health disparities.
Another commenter stated that CMS is not providing additional resources
to ETC Participants to give extra assistance to disadvantaged patients.
Response: We believe that the ETC Model will improve access to
alternative renal replacement modalities, including home dialysis and
transplantation, for all types of beneficiaries. We further believe the
Model will not cause any unintended effects that perpetuate existing
kidney health disparities. Indeed, with the introduction of achievement
benchmark stratification and the Health Equity Incentive, as described
in the CY 2022 ESRD PPS proposed rule and sections V.B.5.c.(2) and
V.B.6.c.(2) of this final rule, respectively, we are testing ways to
directly address socioeconomic disparities in access to alternative
renal replacement modalities. We believe the proposed Health Equity
Incentive, in particular, will benefit attributed beneficiaries who are
dual eligible or receive the LIS, by encouraging ETC Participants to
address disparities in access to alternative renal replacement
modalities among these beneficiaries.
Comment: The majority of commenters generally supported the Health
Equity Incentive. Most of these commenters supported the Health Equity
Incentive proposal without providing any additional recommendations.
Response: We appreciate commenters' support.
Comment: Several commenters stated that they supported creating a
Health Equity Incentive, but indicated that it is important that the
thresholds for earning the Health Equity Incentive are achievable for
ETC Participants.
Response: We agree that it is important for the thresholds for
earning the Health Equity Incentive to be achievable for ETC
Participants. We believe that this is the case. First, by establishing
the thresholds for all MYs, starting for MY3, through this rulemaking,
ETC Participants will have clear information in advance about what they
need to achieve to earn the Health Equity Incentive to enable them to
work towards the goal of increasing access to home dialysis and
transplant for beneficiaries who are dual eligible and LIS recipients
for the remaining duration of the ETC Model test. Second, as described
in greater detail below, we are modifying our proposal such that we
would award the Health Equity Incentive to an ETC Participant if the
ETC Participant's aggregation group's home dialysis rate and/or
transplant rate among attributed beneficiaries who are dual eligible or
LIS recipients increases
[[Page 61971]]
by at least 2.5 percentage points from the Benchmark Year to the MY,
which we believe will be a more attainable threshold for ETC
Participants than the proposed threshold of 5 percentage points.
Comment: Several commenters expressed specific support for our
proposal that the Health Equity Incentive would be worth 0.5
improvement points.
Response: We appreciate the commenters support.
Comment: Several commenters stated that they supported the
introduction of the Health Equity Incentive, but recommended that we
set a lower threshold for ETC Participants to earn the Health Equity
Incentive. These commenters stated that they believed that a five-
percentage point increase to earn the Health Equity Incentive is too
high, and may not be attainable for ETC Participants. A few of these
commenters stated that setting the threshold too high would be
discouraging--that ETC Participants would not try to increase home
dialysis rates and transplant rats among their beneficiaries who are
dual eligible or LIS recipients because they would not believe
attaining a five-percentage point increase would be possible. One
commenter stated that a lower threshold would mean that more ETC
Participants would earn the incentive, which would result in higher
payments and therefore more resources for those participants to support
disadvantaged beneficiaries choosing alternative renal replacement
modalities. One commenter stated that a 5-percentage point increase
from year to year is likely an unachievable goal based on historic
data. Several commenters suggested alternative methods for awarding the
Health Equity Incentive. A few of these commenters suggested a lower
percentage point threshold, such as 1.25-percentage points. Others
suggested alternative methodologies, such as a percentage or percentage
point increase over the Benchmark Year rate, or a percent increase
instead of a percentage point increase.
Response: We appreciate commenters' suggestions of alternative
methods for awarding the Health Equity Incentive. We agree with
commenters' concerns that setting the threshold for awarding the Health
Equity Incentive too high could undermine the intent of the policy. As
stated in the CY 2022 ESRD PPS proposed rule (86 FR 36385) and in this
section of this final rule, 5 percentage points is equal to one
standard deviation above the average difference between the home
dialysis rate and the transplant rate for attributed beneficiaries who
are dual-eligible or LIS recipients and those beneficiaries who are not
dual-eligible or LIS recipients, rounded to the nearest integer. We
also stated our expectation that attaining the proposed threshold for
earning the Health Equity Incentive would generally require significant
effort on the part of the ETC Participant. However, we are persuaded by
the specific evidence provided by commenters that our proposed
threshold was likely unachievable based on historic data. As such, we
agree with commenters that we should lower the threshold for awarding
the Health Equity Incentive.
After considering the alternatives suggested by commenters, we
continue to believe that a percentage-point increase is appropriate for
awarding the Health Equity Incentive. However, rather than a 5-
percentage point increase, we believe that at 2.5-percentage point
increase is more appropriate. Specifically, we believe that a 2.5
percentage point threshold presents a more achievable goal than the 5-
percentage point increase described in the proposed rule. However, as
compared to the 1.25 percentage point increase suggested by the
commenters, we believe using a 2.5 percentage point increase as the
threshold for earning the Health Equity Incentive will incentivize ETC
Participants to make substantial reductions in disparities between
their Beneficiaries who are dual eligible or LIS recipients and those
who are not over the course of the ETC Model.
Comment: One commenter stated that the Health Equity Incentive
should be considered for other value-based care models.
Response: If we adopt the Health Equity Incentive for one or more
other models, we would do so by amending that model's governing
documentation, which may involve notice and comment rulemaking.
Comment: A few commenters encouraged CMS to explore and consider
adding additional characteristics or social drivers of health
disparities in addition to dual eligibility and LIS status as part of
the Health Equity Incentive calculation under the ETC Model. A few of
these commenters suggested that we do so now, and one of these
commenters suggested that we do so pending further study and analysis.
One commenter suggested that we include race as part of the Health
Equity Incentive calculation.
Response: We appreciate the suggestion that we consider including
other factors in the Health Equity Incentive calculation under the ETC
Model. However, we agree with the commenter who suggested that we
consider adding additional characteristics or social drivers of health
disparities only after further study and analysis. Thus, while we are
only awarding the Health Equity Incentive on the basis of improvement
among beneficiaries who are dual eligible or LIS recipients at this
time, we may consider additional factors for the future after we
complete research and analysis on those factors. Any additional factors
would be incorporated through subsequent rulemaking.
Final Rule Action: After considering public comments, we are
finalizing our proposal in our regulation at Sec. 512.370(c) to add
the Health Equity Incentive to the improvement scoring methodology,
with one modification. Specifically, we are modifying our regulation at
Sec. Sec. 512.370(c)(2)(i) and (c)(2)(ii) to change the threshold for
earning the Health Equity Incentive from a 5-percentage point increase
to a 2.5-percentage point increase in the ETC Participant's home
dialysis rate and transplant rate, respectively, among attributed
beneficiaries who are dual-eligible or LIS recipients from the
Benchmark Year to the MY. We are also finalizing our proposed
definition of Health Equity Incentive at Sec. 512.310 without
modification.
7. PPA Reports and Data Sharing
a. Background on Beneficiary Attribution and Performance Reporting
Under the ETC Model, as described in 42 CFR 512.360, CMS attributes
ESRD Beneficiaries and, if applicable, Pre-emptive LDT Beneficiaries to
an ETC Participant for each month during a MY based on the
beneficiary's receipt of services during that month. CMS performs this
attribution for a MY retrospectively, after the end of the MY. As
described in Sec. 512.365, each ETC Participant's performance is
assessed based on the transplant rate and home dialysis rate among the
population of beneficiaries attributed to the ETC Participant. As
described in 42 CFR 512.370 and 42 CFR 512.380, these rates are used to
calculate the ETC Participant's MPS and, in turn, the ETC Participant's
PPA. The PPA is then used to adjust certain Medicare payments of the
ETC Participant during 6-month PPA periods, with the first PPA Period
taking place from July 1, 2022, through December 31, 2022. As described
in 42 CFR 512.390(a), CMS will notify each ETC Participant, in a form
and manner determined by CMS, of the ETC Participant's attributed
beneficiaries, MPS, and PPA for a PPA Period no later
[[Page 61972]]
than one month before the start of the applicable PPA Period.
In order to ensure ETC Participants have timely access to these ETC
Model reports, in the CY 2022 ESRD PPS proposed rule (86 FR 36386
through 36391), we proposed to add a new paragraph (b) to Sec. 512.390
to establish a process for CMS to share certain beneficiary-
identifiable and aggregate data with ETC Participants pertaining to
their participation in the ETC Model. As we stated in the CY 2022 ESRD
PPS proposed rule, CMS believes that ETC Participants need this data to
successfully coordinate the care of their ESRD Beneficiaries and, if
applicable, Pre-emptive LDT Beneficiaries; to succeed under the ETC
Model; and to assess CMS's calculations of the individual ETC
Participant's PPA for a given PPA Period. Specifically, we stated CMS
believes that ETC Participants must have a clear understanding of the
beneficiaries CMS has attributed to them under the ETC Model and how
each attributed beneficiary has factored into the ETC Participant's
home dialysis rate, transplant waitlist rate, and living donor
transplant rate, to better identify care coordination and care
management opportunities, and to have the opportunity to seek targeted
review of CMS's calculation of the MPS. We noted that the purpose of
the targeted review process, established under current Sec.
512.390(b), which we would redesignate as paragraph (c), is to
determine whether an incorrect PPA has been applied during the PPA
Period. We stated that CMS additionally believes that timely access to
this data is important and proposed to require CMS to make this data
available twice a year, prior to each PPA Period in an MY.
In the following sections of this final rule, we describe the
process that we proposed for CMS to share and for ETC Participants to
retrieve certain beneficiary-identifiable attribution data and
performance data, as well as the protections that we proposed to apply
to this data under a data sharing agreement with CMS. We also describe
our proposed process for sharing certain aggregate, de-identified
performance data with ETC Participants.
b. CMS Sharing of Beneficiary-Identifiable Data
We proposed to establish a process in new Sec. 512.390(b)(1) under
which CMS would share certain beneficiary-identifiable data with ETC
Participants regarding their attributed beneficiaries and performance
under the ETC Model. We proposed that, in accordance with the timing of
the notification requirement described in Sec. 512.390(a), CMS would
be required to make the beneficiary-identifiable data pertaining to a
given PPA Period available for retrieval by ETC Participants no later
than 1 month before the start of that PPA Period. The ETC Participant
would be able to retrieve this data at any point during the relevant
PPA Period, but, in accordance with current Sec. 512.390(b)(1), which
would be redesignated as paragraph (c)(1), the ETC Participant would
have 90 days from the date that CMS shares the MPS, including the data
CMS used in calculating the MPS, to request a targeted review. We
proposed that CMS would notify ETC Participants of the availability of
the beneficiary-identifiable data for a relevant PPA Period and the
process for retrieving that data, through the ETC listserv and through
the ETC Model website, available at https://innovation.cms.gov/innovation-models/esrd-treatment-choices-model.
Regarding the specific beneficiary-identifiable data that CMS would
be required to share with ETC Participants, we proposed in Sec.
512.390(b)(1)(ii)(A) to include, when available, the following data for
each PPA Period: The ETC Participant's attributed beneficiaries' names,
Medicare Beneficiary Identifiers (MBIs), dates of birth, dual-eligible
status, and LIS recipient status. We stated in the CY 2022 ESRD PPS
proposed rule that we believe that the patient's name, MBI, and date of
birth constitute the minimum elements to enable an ETC Participant to
properly identify an attributed beneficiary, and to confirm the
identity of an attributed beneficiary during any communications with a
beneficiary or a beneficiary's caregiver, as appropriate and allowable.
In addition, we stated the ETC Participant needs to be aware of each
attributed beneficiary's dual-eligible status and LIS recipient status
to understand how each attributed beneficiary contributed to how CMS
calculated the ETC Participant's Health Equity Incentive, if finalized.
We proposed in Sec. 512.390(b)(1)(ii)(B) that this beneficiary-
identifiable data also would include, when available, data regarding
the ETC Participant's performance under the ETC Model, including, for
each attributed beneficiary, as applicable, the number of months the
beneficiary was attributed to the ETC Participant, received home
dialysis, self-dialysis, or nocturnal in-center dialysis, or was on a
transplant waitlist; and the number of months that have passed since
the beneficiary has received a living donor transplant, as applicable.
We stated that we believe that sharing these data elements would help
the ETC Participant understand and, as appropriate, seek targeted
review of CMS's calculation of the ETC Participant's MPS, and otherwise
understand how CMS adjusted the ETC Participant's Medicare payments by
the PPA.
In the CY 2022 ESRD PPS proposed rule (86 FR 36387), we stated that
we recognized there are sensitivities surrounding the disclosure of
individually-identifiable (beneficiary-specific) health information,
and we noted that a number of laws place constraints on the sharing of
individually identifiable health information. We noted that, for
example, section 1106 of the Act generally bars the disclosure of
information collected under the Act without consent unless a law
(statute or regulation) permits for the disclosure. In this instance,
the Health Insurance Portability and Accountability Act of 1996 (HIPAA)
Privacy Rule permits this proposed disclosure of individually
identifiable health information by us to ETC Participants if this
proposed disclosure is required by law. We explained that under the
HIPAA Privacy Rule, covered entities (defined as health care plans,
health care providers that submit certain transactions electronically,
and health care clearinghouses) are barred from using or disclosing
protected health information (PHI) in a manner that is not explicitly
permitted or required under the HIPAA Privacy Rule, without the
individual's authorization. The Medicare FFS program, a ``health plan''
function of the Department, is subject to the HIPAA Privacy Rule
limitations on the disclosure of PHI, without an individual's
authorization. ETC Participants are also covered entities, provided
they are health care providers as defined by 45 CFR 160.103 and they or
their agents electronically engage in one or more HIPAA standard
transactions, such as for claims, eligibility, or enrollment
transactions.
As we discussed in the CY 2022 ESRD PPS proposed rule, the proposed
disclosure of ETC Model beneficiary-identifiable data would be
permitted by the HIPAA Privacy Rule under the provisions that permit
disclosures of PHI as ``required by law.'' Under 45 CFR 164.512(a)(1),
a covered entity may use or disclose PHI to the extent that such use or
disclosure is required by law and the use or disclosure complies with
and is limited to the relevant requirements of such law.\275\ We
proposed to establish
[[Page 61973]]
a requirement under Sec. 512.390(b)(1) for CMS to share this data with
ETC Participants.
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\275\ Under 45 CFR 164.103, ``Required by law'' means ``a
mandate contained in law that compels an entity to make a use or
disclosure of protected health information and that is enforceable
in a court of law.'' It includes, among other things, ``statutes or
regulations that require the production of information, including
statutes or regulations that require such information if payment is
sought under a government program providing public benefits.''
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In the CY 2022 ESRD PPS proposed rule, we further noted that the
Privacy Act of 1974 also places limits on agency data disclosures. The
Privacy Act applies when Federal agencies maintain systems of records
by which information about an individual is retrieved by use of one of
the individual's personal identifiers (name, Social Security number, or
any other codes or identifiers that are assigned to the individual).
The Privacy Act generally prohibits disclosure of information from a
system of records to any third party without the prior written consent
of the individual to whom the records apply, 5 U.S.C. 552a(b).
``Routine uses'' are an exception to this general principle. A routine
use is a disclosure outside of the agency that is compatible with the
purpose for which the data was collected. Routine uses are established
by means of a publication in the Federal Register about the applicable
system of records describing to whom the disclosure will be made and
the purpose for the disclosure. We stated in the CY 2022 ESRD PPS
proposed rule that we believe that the proposed data disclosures are
consistent with the purposes for which the data discussed in this rule
was collected, and thus, should not run afoul of the Privacy Act,
provided we ensure that an appropriate Privacy Act system of records
``routine use'' is in place prior to making any disclosures. The
systems of records from which CMS would share data are the Medicare
Integrated Data Repository (``IDR''), system of records number 09-70-
0571, and the Health Resources and Services Administration (``HRSA'')
Organ Procurement and Transplantation Network (``OPTN'')/Scientific
Registry of Transplant Recipients (``SRTR'') Data System, system of
records number 09-15-0055.
In the CY 2022 ESRD PPS proposed rule, we expressed that
establishing a regulatory requirement for CMS to share the beneficiary-
identifiable data described previously would be appropriate for the ETC
Model for several reasons. First, we stated that we believe that all
ETC Participants not only desire but need this data to know which
beneficiaries CMS has attributed to them (and thus is holding them
financially accountable for such beneficiaries' individual
contributions to the ETC Participant's performance measures described
in 42 CFR part 512, subpart C, with the proposed modifications
described in this proposed rule, if finalized), and for each ETC
Participant to understand the basis by which CMS computed their MPS.
Second, we stated that CMS believes that all ETC Participants,
regardless of size, would have the capability of managing and
meaningfully using the shared data. We noted that we would provide the
data in a form and manner that CMS believes is user-friendly. In
addition, the ETC Participant would be able to review the beneficiary-
identifiable data along with the aggregated data, which should help the
ETC Participant understand the data CMS would share with the ETC
Participant. Finally, we stated that CMS believes that any other
approach to making beneficiary-identifiable data available, including
the alternative proposal considered by CMS and described later in this
section, would impose additional operational burdens on CMS and
administrative burdens on both CMS and the ETC Participants without
producing any meaningful privacy or security benefit.
In the CY 2022 ESRD PPS proposed rule, we noted that we considered
an alternative proposal for making beneficiary-identifiable data
available to ETC Participants based on the data sharing policies
currently used in many models tested under section 1115A of the Act,
which would involve ETC Participants formally requesting the data from
CMS before CMS could share the data. In particular, ETC Participants
would have the opportunity to request the ``minimum necessary'' PHI for
their own ``health care operations'' as defined in 45 CFR 164.501 and
CMS would be permitted to disclose the requested data based on the
HIPAA Privacy Rule provisions that permit disclosures of PHI for the
recipient's health care operations purposes as described in 45 CFR
164.506(c)(4). We stated that under this alternative approach, ETC
Participants that request this information would have to attest to
compliance with specific HIPAA requirements in addition to, or as part
of, the data sharing agreement described in section V.B.7.b.c of the CY
2022 ESRD PPS proposed rule and the next section of this final rule.
In the CY 2022 ESRD PPS proposed rule, we stated that after
considering this option, we believed that having the ETC Participant
request the data from CMS would add steps in the process that would
cause administrative burden for both CMS and ETC Participants, and
operational cost and burden for CMS. We also stated that we further
believed that adding these steps would not produce a meaningful privacy
or security benefit based on the specific circumstances of this ETC
Model. We noted that both this option and the proposed approach would
require that the ETC Participant complete and sign a data sharing
agreement, and both would allow an ETC Participant to decline receiving
beneficiary-identifiable data by declining to complete or sign a data
sharing agreement. As such, we stated that there would be no meaningful
privacy or security benefits that this option would create that were
not already realized by the proposed approach to data sharing in the
ETC Model. We also anticipated that all ETC Participants would want and
need, and overwhelmingly would request, the data described previously,
would be capable of handling such data, and would take the steps
necessary to obtain the data. In addition, we stated that under an
alternative approach based on the HIPAA provisions for the ETC
Participant's ``health care operations,'' CMS would only be able to
disclose the beneficiary-identifiable data for a purpose listed in
paragraph (1) or (2) of the definition of ``health care operations'' in
45 CFR 164.501. However, we noted that we also believe it is crucial
that an ETC Participant has the opportunity to understand how CMS
calculated the ETC Participant's PPA for a PPA Period, and have the
information needed to request a targeted review of CMS's MPS
calculation if the ETC Participant believes CMS made an error.
Given the policies we were proposing for data sharing, we also
proposed to modify the title of Sec. 512.390 from ``Notification and
targeted review'' to ``Notification, data sharing, and targeted
review.'' We proposed this change so that the section title would more
accurately reflect the contents of the section.
We solicited public comment on our proposal to require, under
proposed Sec. 512.390(b)(1), that CMS make available certain
beneficiary-identifiable attribution and performance data for retrieval
by ETC Participants no later than one month prior to the start of each
PPA Period, and on our considered alternative to this proposal.
The following is a summary of the comments received on our proposal
to require that CMS make available certain beneficiary identifiable
attribution and performance data for retrieval by ETC Participants no
later than one month prior to the start of each PPA Period, and our
responses.
[[Page 61974]]
Comment: We received many comments in support of the need for data
sharing under the ETC Model. One commenter asserted that it is
essential for ETC Participants to have access to the data elements CMS
described in the CY 2022 ESRD PPS proposed rule to allow ETC
Participants to make informed decisions and implement changes to
clinical processes that permit improvement over time. Another commenter
stated that the availability of beneficiary-level data under the ETC
Model would be helpful in caring for and providing appropriate care to
ESRD Beneficiaries. Another commenter stated that the data CMS proposed
to share would assist ETC Participants in establishing targeted
interventions to increase rates of the contemplated dialysis modalities
and transplant waitlisting, and that it would help ETC Participants
decrease health disparities.
Response: We thank the commenters for their support.
Comment: One commenter expressed agreement with the expected uses
of beneficiary-identifiable data by ETC Participants that CMS described
in the CY 2022 ESRD PPS proposed rule, including requesting targeted
review of the MPS calculation, care management or coordination, and
quality improvement.
Response: We appreciate this comment. We continue to believe that
requesting targeted review of the MPS calculation, care management or
coordination, and quality improvement constitute appropriate uses of
the beneficiary-identifiable data that CMS would share with ETC
Participants, and we are pleased this commenter agrees with these
expected uses.
Comment: We received some comments regarding the timing and
frequency of data sharing under the ETC Model. Some commenters
expressed support for our proposal to share data prior to each PPA
Period. A few commenters proposed that CMS share data more frequently
than proposed. A couple commenters proposed that CMS share the data
described in the CY 2022 ESRD PPS proposed rule on a quarterly basis.
Another commenter proposed that CMS share the data on as close to a
real-time basis as possible, suggesting either a quarterly or a monthly
basis. This commenter asserted that sharing data on a quarterly or
monthly basis would help ensure that the data is not outdated, and that
it could better help guide interventions by ETC Participants to
increase home dialysis and transplant rates.
A couple commenters recommended that CMS share the data on a
monthly basis. One such commenter maintained that, for an ETC
Participant to meaningfully track its performance, the ETC Participant
should have access to monthly reports detailing its attributed
beneficiary population. The same commenter also suggested that they
anticipate that sharing data on a monthly basis would impose minimal
burden on CMS, that such data sharing frequency would allow CMS and ETC
Participants to address potential errors through targeted reviews on a
smaller scale and on a rolling basis, and that more timely access to
data would better support ETC Participants in increasing transplant
waitlisting and monitoring their performance.
Response: We thank the commenters for their feedback. While we
agree, in general, that having access to more timely data would incur
many benefits for CMS and ETC Participants alike, including the ones
identified by commenters, we believe that the schedule we proposed for
sharing data affords ETC Participants sufficient time to conduct the
activities for which CMS proposed allowing the ETC Participant to use
the data, namely: To assess CMS's calculations underlying the ETC
Participant's MPS, and to conduct care management, care coordination,
and quality improvement activities. In addition, we believe that
sharing data biannually, no later than one month ahead of each PPA
Period, gives ETC Participants sufficient opportunity to track or
monitor their performance and otherwise increase transplant
waitlisting. Further, as described in Sec. 512.360 of our regulations,
CMS conducts beneficiary attribution for each month of a MY
retrospectively after the end of each MY. Accordingly, CMS would not
necessarily have accurate beneficiary-identifiable data to share with
the ETC Participant on a monthly or quarterly basis to the extent that
a beneficiary's attribution status can change during a given MY. In
other words, CMS is unable to share accurate, final beneficiary-
identifiable data on the ETC Participant's attributed beneficiaries
more often than biannually, after the end of the applicable MY.
In addition, because we conduct beneficiary attribution
retrospectively, we disagree with the commenter's suggestion that
sharing data monthly would impose minimal burden on CMS. Sharing data
monthly or quarterly would in effect require CMS to conduct beneficiary
attribution monthly or quarterly, even though CMS is basing its MPS
calculations on beneficiary attribution run only biannually, which
would impose more than minimal burden on CMS. We similarly disagree
with the commenter's suggestion that sharing data more frequently would
enable CMS and ETC Participants to address potential errors through
targeted reviews on a smaller scale and on a rolling basis. CMS did not
propose any changes to when CMS computes the MPS or applies it to
determine the ETC Participant's PPA. Because CMS will still be applying
the PPA according to the schedule provided in Sec. 512.355, sharing
data more frequently than proposed would not give CMS and ETC
Participants the ability to address potential errors through targeted
reviews on a smaller scale or on a rolling basis.
For the same reasons, we disagree with the commenter's concern
that, under CMS's proposal to share beneficiary-identifiable data prior
to each PPA Period, the data shared would be outdated. Under Sec.
512.365, CMS calculates the ETC Participant's MPS based on the ETC
Participant's performance during a given MY. Any beneficiary-
identifiable data shared during an MY would not necessarily be accurate
because a beneficiary's attribution status can change during an MY. In
other words, to share beneficiary-identifiable data more frequently
would require CMS to share data that is not yet final and may be
inaccurate. Thus, unlike the data we proposed to share under Sec.
512.390(b)(1), an ETC Participant could not use this interim data to
assess CMS's calculation of the MPS.
Comment: One commenter suggested that CMS make available to ETC
Participants a list of beneficiaries who are dual-eligible or LIS
recipients prospectively (which, in the context of the ETC Model, we
interpret to mean in advance of the applicable MY), explaining that
sharing such data in advance would give ETC Participants a clearer
understanding of their patient population as it will be analyzed by
CMS. The commenter also stated that neither the commenter nor
healthcare providers are able to fully model the impact of CMS's
proposal to stratify achievement benchmarks based on the proportion of
beneficiaries who are dual-eligible or LIS recipients, as they do not
have access to public information regarding ESRD Beneficiaries' LIS
eligibility.
Response: As noted previously, under Sec. 512.360, CMS conducts
beneficiary attribution retrospectively in the ETC Model, and thus data
on the dual eligibility and LIS recipient status of each attributed
beneficiary will not be available for CMS to share with ETC
Participants prospectively in advance of the MY. Any beneficiary-
identifiable
[[Page 61975]]
data we could share in advance of an MY would include at least a few
beneficiaries that, when we conduct attribution for the MY at the end
of that MY, would not be attributed to the ETC Participant, or at least
not attributed to the ETC Participant for all months of the MY. Because
we conduct beneficiary attribution monthly, attribution is subject to
change, and the benefits that the commenter asserts could be gained by
CMS sharing dual-eligible and LIS-eligible status data in advance of an
MY would likely be undermined by the fact that such data may not be
complete or accurate. In other words, CMS cannot know in advance of an
MY which beneficiaries, or more specifically, which beneficiary-months,
will count for the purpose of conducting attribution and calculating
performance; we can only know this after the MY has ended. For this
reason, we believe that limiting beneficiary-identifiable data sharing
to after the MY, but prior to its corresponding PPA Period--in advance
of when the ETC Participant's payments will be adjusted--best ensures
that CMS is sharing the most accurate beneficiary-identifiable data as
relevant to the ETC Participant's attributed beneficiaries and
performance under the ETC Model, while providing the ETC Participant
the opportunity to understand and, as needed, request a targeted review
of the calculation of the MPS under Sec. 512.390(b) of our
regulations. Finally, dual-eligibility and LIS-eligibility data shared
prior to a PPA Period could also be viewed as prospective in nature.
Specifically, while a beneficiary's attribution status is subject to
change during and between MYs, such data will provide ETC Participants
with a rough estimate of their population of attributed beneficiaries
who are dual-eligible and LIS recipients for the upcoming MY.
Regarding the commenter's concern that neither the commenter nor
healthcare providers are able to fully model the impact of CMS's
proposal to stratify achievement benchmarks based on the proportion of
beneficiaries who are dual-eligible or LIS recipients, CMS declines to
make beneficiary-identifiable LIS-eligibility data publicly available,
or to share with the ETC Participant beneficiary-identifiable LIS-
eligibility data on ESRD Beneficiaries who are not attributed to the
ETC Participant, as such policies would raise privacy concerns. If the
commenter is instead expressing concern that there does not exist
publicly available aggregate data regarding ESRD beneficiaries who are
LIS-eligible, such broad data dissemination is beyond the scope of this
rulemaking for the ETC Model.
Comment: Several commenters provided feedback on the data elements
CMS proposed to share with ETC Participants. One commenter expressed
support for the data elements that CMS proposed to provide under the
ETC Model, noting that, even without claims data, the data CMS proposed
to provide would assist ETC Participants in establishing targeted
interventions to increase the rates of home dialysis, self-dialysis,
and nocturnal in-center dialysis modalities, as well as transplant
waitlist rates. The same commenter also recommended that CMS make
claims data available to ETC Participants, as claims data would better
assist ETC Participants in establishing appropriate care coordination
and quality improvement initiatives, thereby improving care for
beneficiaries. The commenter also noted that CMS has deemed claims data
necessary to share with participants under other models tested under
section 1115A of the Act, and that CMS should take the same position
here.
Response: We agree that making certain beneficiary-identifiable
data available under the ETC Model will help ETC Participants conduct
care coordination and quality improvement activities, and realize the
goals of the ETC Model of promoting beneficiary choice of renal
replacement modality. We believe that our proposal struck the
appropriate balance between sharing enough data to ensure that ETC
Participants understand which beneficiaries were attributed to them
during a given MY for purposes of care management and coordination and
quality improvement, providing treatment to the subject beneficiary,
and to assess CMS's calculation of the corresponding MPS, while also
remaining sensitive to the privacy interests of attributed
beneficiaries and sharing only the ``minimum necessary'' amount of
beneficiary-identifiable data, as required by the HIPAA Privacy Rule,
to support the ETC Model for the purposes we described in the CY 2022
ESRD PPS proposed rule. In most other models tested under section 1115A
of the Act under which CMS has made available beneficiary-identifiable
Medicare claims data, CMS shares such data only when formally requested
by model participants for certain ``health care operations,'' and only
after such model participants attest to meeting specific HIPAA
requirements, including that the particular claims data requested meet
the ``minimum necessary'' for their respective ``health care
operations.'' These disclosures are based on the HIPAA Privacy Rule
provisions that permit disclosures of PHI for the recipient's health
care operations purposes as described in 45 CFR 164.506(c)(4) and Sec.
164.501.
For the ETC Model, we proposed to establish a requirement under
Sec. 512.390(b)(1) for CMS to share the beneficiary-identifiable data
described in the CY 2022 ESRD PPS proposed rule with ETC Participants.
Our proposal did not include a process whereby ETC Participants could
request the beneficiary-identifiable data for their ``health care
operations.'' As we explained in the CY 2022 ESRD PPS proposed rule (86
FR 36388), having the ETC Participant formally request the beneficiary-
identifiable data from CMS would add steps in the process that would
cause administrative burden for both CMS and ETC Participants, and
operational cost and burden for CMS. We also noted that adding these
steps would not produce a meaningful privacy or security benefit based
on the specific circumstances of this ETC Model. We agree that Medicare
claims data likely would help many ETC Participants' care coordination
and quality improvement efforts. However, we do not believe, at this
time, that making claims data available is appropriate given the nature
of this model, which is focused on making payment adjustments related
to relatively specific outcomes, namely increasing rates of home
dialysis and transplant. We believe that the data elements we proposed
to share with ETC Participants are sufficient to position ETC
Participants to meaningfully conduct care coordination and quality
improvement activities to increase rates of home dialysis, self-
dialysis, nocturnal in-center dialysis, and transplant waitlisting.
Moreover, we do not believe that Medicare claims data are necessary for
ETC Participants to assess CMS's calculations underlying the payment
adjustments made under the ETC Model.
Comment: One commenter recommended that CMS add the following data
elements to the beneficiary-identifiable data that CMS would be
required to share with ETC Participants: ``Modality attribution
status,'' the name of the transplant center at which the beneficiary is
listed on the transplant waitlist, and the date on which the
beneficiary joined their respective waitlist.
Response: We thank the commenter for this feedback. We believe our
proposed data elements capture two of the commenter's three suggested
data elements. Specifically, we believe our proposal to provide data on
the number
[[Page 61976]]
of months the beneficiary was attributed to the ETC Participant,
received home dialysis, self-dialysis, or nocturnal in-center dialysis,
or was on a transplant waitlist; and the number of months that have
passed since the beneficiary has received a living donor transplant, as
applicable, sufficiently capture a beneficiary's ``modality attribution
status'' (which we interpret to mean the dialysis modality that CMS
understands the beneficiary to be receiving) and, even if indirectly,
provides the date (or an approximation thereof) that the beneficiary
was placed on a transplant waitlist.
CMS did not propose to provide the name of the transplant center at
which the beneficiary is listed on the transplant waitlist, and CMS
does not believe, at this time, that it is appropriate to make such
information available. An ETC Participant should be able to obtain such
information from the subject beneficiary, as we anticipate that an ETC
Participant would first talk to a beneficiary, and likely obtain the
beneficiary's explicit consent, prior to contacting a transplant center
on his or her behalf. That said, we may consider this suggestion for
future rulemaking related to the ETC Model.
Comment: One commenter suggested that CMS provide more granular
data on attributed beneficiaries, and suggested that CMS include the
following elements: ``Patient ID,'' ``Date (year/month),''
``Modality,'' and ``Status (active or not active on transplant list.''
Response: CMS believes that its proposed data elements under Sec.
512.390(b)(1)(ii) capture all of the elements the commenter suggested.
CMS proposed sharing the beneficiary's name and MBI, which CMS believes
would serve as a ``Patient ID.'' CMS also proposed sharing the number
of months a beneficiary was attributed to the ETC Participant, home
dialysis months, self-dialysis months, nocturnal in-center dialysis
months, transplant waitlist months, and months following a living donor
transplant. We believe these data elements capture the ``Date (year/
month),'' ``Modality,''modality, and ``Status (active or not active on
transplant list'' elements suggested by the commenter. ``Date (year/
month)'' could be ascertained by the number of months a beneficiary was
attributed to the ETC Participant; ``Modality'' could be ascertained by
the beneficiary's data regarding home dialysis months, self-dialysis
months, and nocturnal in-center dialysis months; and ``Status (active
or not active on transplant list)'' could be ascertained by the
transplant waitlist months or months following a living donor
transplant.
Comment: Two commenters expressed support for CMS's proposal to
provide beneficiary-identifiable data to ETC Participants without
establishing a process for ETC Participants to request it. Both
commenters asserted that the approach described in the CY 2022 ESRD PPS
proposed rule of requiring CMS by law to make available the
beneficiary-identifiable data identified in the CY 2022 ESRD PPS
proposed rule, rather than allowing ETC Participants to request the
data, would decrease burden on both CMS and ETC Participants.
Response: We thank the commenters for their support. We agree that
the proposed approach of requiring CMS by law to make available the
described beneficiary-identifiable data would reduce burden on both CMS
and ETC Participants, and that it is otherwise appropriate for sharing
beneficiary-identifiable data under the ETC Model.
Final Rule Action: After considering public comments, we are
finalizing our proposal to require in our regulation at Sec.
512.390(b)(1) that CMS make available for retrieval by ETC Participants
certain beneficiary-identifiable data no later than one month before
the start of each PPA Period, without modification. This beneficiary-
identifiable data will include, when available: The ETC Participant's
attributed beneficiaries' names, Medicare Beneficiary Identifiers,
dates of birth, dual eligible status, and LIS recipient status; and
data regarding the ETC Participant's performance under the ETC Model,
including, for each attributed beneficiary, as applicable: The number
of months the beneficiary was attributed to the ETC Participant, home
dialysis months, self-dialysis months, nocturnal in-center dialysis
months, transplant waitlist months, and month following a living donor
transplant. As we stated in the CY 2022 ESRD PPS proposed rule, an
appropriate Privacy Act system of records ``routine use'' will need to
be in place prior to the disclosure of this data.
(1) Conditions for Retrieving Beneficiary-Identifiable Data
Given the sensitive nature of the beneficiary-identifiable data
that CMS would be required to share under our proposal, in the CY 2022
ESRD PPS proposed rule (86 FR 36388), we proposed certain conditions
for ETC Participants to be able to retrieve this data and certain
protections that would govern use of the data following retrieval.
First, we proposed that CMS would only share the beneficiary-
identifiable data on the condition that the ETC Participant observes
all relevant statutory and regulatory provisions regarding the
appropriate use of data and the confidentiality and privacy of
individually identifiable health information as would apply to a
covered entity under the HIPAA regulations and agrees to comply with
the terms of a separate data sharing agreement. Although we stated that
we expected ETC Participants are covered entities and must comply with
the HIPAA regulations directly, we proposed to include this provision
to ensure an ETC Participant would abide by those rules with respect to
the data, even if, for example, the ETC Participant is a hybrid entity
under HIPAA and the component requesting the data has not been
designated as a health care component under 45 CFR 164.105. We proposed
that the HIPAA provisions that the ETC Participant would have to
observe would include, but would not be necessarily limited to,
standards regarding the use and disclosure of PHI; administrative,
physical, and technical safeguards and other security provisions; and
breach notification.
We proposed that, if an ETC Participant wishes to retrieve the
beneficiary-identifiable data, the ETC Participant would be required to
first complete, sign, and submit--and thereby agree to the terms of--a
data sharing agreement with CMS, which we would call the ETC Data
Sharing Agreement. We proposed that this agreement would include
certain protections and limitations on the ETC Participant's use and
further disclosure of the beneficiary-identifiable data, and would be
provided in a form and manner specified by CMS, which we discussed in
more detail in later sections of the CY 2022 ESRD PPS proposed rule and
describe below. We also stated that this agreement would potentially
require the ETC Participant to make certain attestations, for example,
if required under the applicable Privacy Act system of records notice.
We proposed that an ETC Participant that wishes to retrieve the
beneficiary-identifiable data would be required to complete and submit
a signed ETC Data Sharing Agreement at least annually. We stated that
we believe that it is important for the ETC Participant to complete and
submit a signed ETC Data Sharing Agreement at least annually so that
CMS has up-to-date information that the ETC Participant wishes to
retrieve the beneficiary-identifiable data, attestations (if required),
and information on the designated data custodian(s). As described in
greater detail in the CY 2022 ESRD PPS proposed rule (86 FR 36388--
36389),
[[Page 61977]]
we proposed that a designated data custodian would be the individual(s)
that an ETC Participant would identify as responsible for ensuring
compliance with all privacy and security requirements and for notifying
CMS of any incidents relating to unauthorized disclosures of
beneficiary-identifiable data.
In the CY 2022 ESRD PPS proposed rule, we stated our belief that it
is important for the ETC Participant to first complete and submit a
signed ETC Data Sharing Agreement before it retrieves any beneficiary-
identifiable data to help protect the privacy and security of any
beneficiary-identifiable data shared by CMS with the ETC Participant.
As described in section V.B.7.b of the CY 2022 ESRD PPS proposed rule
and previously in this final rule, there are important sensitivities
surrounding the sharing of this type of individually identifiable
health information, and CMS must ensure to the best of its ability that
any beneficiary-identifiable data that it shares with ETC Participants
would be further protected in an appropriate fashion.
In the CY 2022 ESRD PPS proposed rule, we considered an alternative
under which ETC Participants would not need to complete and submit a
signed ETC Data Sharing Agreement, but we concluded that, if we
proceeded with this option, we would not have adequate assurances that
the ETC Participants would appropriately protect the privacy and
security of the beneficiary-identifiable data that we are proposing to
share with them. We also considered, in the CY 2022 ESRD PPS proposed
rule, an alternative under which the ETC Participant would need to
complete and submit a signed ETC Data Sharing Agreement only once for
the duration of the ETC Model. However, we concluded that this
similarly would not give CMS adequate assurances that the ETC
Participant would protect the privacy and security of the beneficiary-
identifiable data from CMS. We concluded in the CY 2022 ESRD PPS
proposed rule that it is critical that we have up-to-date information
and designated data custodians, and that requiring the ETC Participant
to submit an ETC Data Sharing Agreement at least annually would
represent the best means of achieving this goal.
We solicited public comment on our proposal to require, in Sec.
512.390(b)(1)(iii), that the ETC Participant agree to comply with all
applicable laws and the terms of the ETC Data Sharing Agreement as a
condition of retrieving the beneficiary-identifiable data, and on our
proposal in Sec. 512.390(b)(1)(iv) that the ETC Participant would need
to submit the signed ETC Data Sharing Agreement at least annually if
the ETC Participant wishes to retrieve the beneficiary-identifiable
data.
The following is a summary of the comments received on our
proposals regarding the conditions for retrieving beneficiary-
identifiable data, and our responses.
Comment: Some commenters expressed support for our proposal to
require an ETC Participant to complete an ETC Data Sharing Agreement
prior to CMS making the beneficiary-identifiable data described in the
CY 2022 ESRD PPS proposed rule available to the ETC Participant. One
such commenter noted that CMS's proposals strike a good balance between
crucial privacy goals and ETC Participants' need to assess their
performance under the Model. Another commenter claimed that the
proposed process would be consistent with the process CMS followed in
the Comprehensive ESRD Care (CEC) Model and is following in the Kidney
Care Choices (KCC) Model Options.
Response: We agree that requiring an ETC Participant to complete an
ETC Data Sharing Agreement prior to CMS making the beneficiary-
identifiable data described in the CY 2022 ESRD PPS proposed rule
available to the ETC Participant strikes an appropriate balance between
the important goals of making ETC Participants aware of which
beneficiaries CMS has attributed to them and enabling ETC Participants
to understand the basis by which CMS computed their MPS, while
protecting the privacy interests of attributed beneficiaries. We
clarify, however, that the process CMS followed in the CEC Model and is
following in the KCC Model Options is different from the process CMS
proposed for the ETC Model. In the CEC Model CMS offered model
participants the opportunity to request beneficiary-identifiable data
for their ``health care operations,'' in accordance with HIPAA Privacy
Rule provisions at 45 CFR 164.506(c)(4), contingent upon the
participants making certain attestations and agreeing to certain
privacy and security protections as part of the participation
agreements for those models. CMS is taking this same approach with the
KCC Model Options. For the ETC Model, we proposed that CMS would be
required by law to provide certain beneficiary-identifiable data to ETC
Participants, in accordance with the HIPAA Privacy Rule provisions at
45 CFR 164.512(a), contingent upon the ETC Participant annually signing
an ETC Data Sharing Agreement.
Comment: One commenter expressed specific support for CMS's
proposal to require an ETC Participant to complete an ETC Data Sharing
Agreement on an annual basis. A couple of commenters recommended that
CMS require the ETC Participant to complete an ETC Data Sharing
Agreement only once during the Model. One such commenter further
suggested that CMS require an ETC Participant to complete a subsequent
ETC Data Sharing Agreement if material changes occur requiring a new
agreement, rather than requiring an ETC Participant to complete an ETC
Data Sharing Agreement annually. This commenter stated that this
approach would align with the approach the Innovation Center takes in
certain other alternative payment models, and that annual completion of
an ETC Data Sharing Agreement would be overly burdensome for ETC
Participants.
Response: We believe that it is appropriate to require the ETC
Participant to complete an ETC Data Sharing Agreement on an annual
basis. It is critical that CMS guarantees, to the best of its ability,
that it always has an up-to-date, completed ETC Data Sharing Agreement
from each ETC Participant that wishes to obtain the beneficiary-
identifiable data CMS described in the CY 2022 ESRD PPS proposed rule.
We believe that requiring the ETC Participant to complete an ETC Data
Sharing Agreement annually, rather than only when material changes
occur, would better ensure that CMS achieves this goal. Even if CMS
were to articulate specific elements of what constitutes a ``material
change,'' such a policy would require that an ETC Participant
appropriately identify when such a change as occurred and timely notify
CMS, and would require CMS to conduct additional monitoring and
outreach activities to ensure compliance. Such an approach imposes
additional and substantial burden on CMS in the context of the ETC
Model, which includes approximately 7,000 ETC Participants, and this
burden is disproportionate to the burden imposed on ETC Participants by
completing an ETC Data Sharing Form annually. We believe that requiring
the ETC Participant to complete an ETC Data Sharing Agreement annually
strikes a reasonable balance between ensuring, to the extent possible,
that CMS has up-to-date information, while minimizing the
administrative burden imposed on a given ETC Participant in completing
the form.
While CMS has not required the annual completion of a data sharing
agreement in every alternative payment model, the ETC Model importantly
[[Page 61978]]
differs from other section 1115A models insofar as participation in the
ETC Model changes in a different way than other models. ESRD facilities
and Managing Clinicians located in a Selected Geographic Area are
required to participate in the ETC Model under Sec. 512.325(a). As
such, participation in the ETC Model can fluctuate between MYs when
ESRD facilities or Managing Clinicians move in or out of a Selected
Geographic Area. This element of the ETC Model differs from many
voluntary section 1115A models, such as the CEC Model or Primary Care
First, where individuals or entities apply to participate, and accepted
individuals or entities continue to participate until the section 1115A
model ends or the participant or CMS terminates the participation
agreement. The potential fluctuation in participation between MYs
creates a need for CMS to require the ETC Participant to complete a
data sharing agreement more frequently than it permits or requires in
other section 1115A models, and we believe that requiring an ETC
Participant to complete the data sharing agreement annually is
sufficiently frequent to ensure that CMS has up-to-date data sharing
agreements in place.
In addition, other alternative payment models generally provide,
within their respective participation agreements, terms and conditions
relating to data protection, uses and disclosures, retention, and
destruction, and those participation agreements are often amended,
which typically requires model participants to complete new data
request and attestation forms during the model's performance period.
Our CY 2022 ESRD PPS proposed rule indicated that the specific terms
relating to privacy, security, data retention, breach notification, and
data destruction, which are found for other section 1115A models in the
models', governing documentation would be found in the ETC Data Sharing
Agreement, and we believe it is important that ETC Participants review
these terms at least once a year, including in completing an annual ETC
Data Sharing Agreement.
In addition, the ETC Model includes a larger number of participants
than many other section 1115A models; as described in the Specialty
Care Models final rule, this larger scale is necessary to obtain the
minimum sample size needed to produce robust and reliable evaluation
results (85 FR 61280). With so many participants receiving beneficiary-
identifiable data, CMS believes that the privacy interests of
beneficiaries would be best protected by requiring the ETC Participant
to complete an ETC Data Sharing Agreement annually, helping CMS to
ensure that the ETC Data Sharing Agreement submitted by an ETC
Participant is reasonably up-to-date. Moreover, CMS believes that
completing an ETC Data Sharing Agreement represents a low burden for an
ETC Participant. As discussed later in this final rule, the ETC Data
Sharing Agreement form will be available on the same web-based platform
as the beneficiary-identifiable and aggregate data, which the ETC
Participant likely would be accessing at least twice a year to obtain
data when available at least 30 days prior to a PPA Period.
Comment: One commenter recommended that CMS follow its approach in
the Kidney Care Choices Model of requiring, in the commenter's words,
``eligible signatories for the ETC Data Sharing Agreement.''
Response: We thank the commenter for this feedback. We agree that
it is important that the individual who signs the ETC Data Sharing
Agreement has the authority to bind the ETC Participant to its terms
and conditions. We believe this is standard for any binding agreement,
and thus we do not believe we must specify this in our regulations.
Final Rule Action: After considering public comments, we are
finalizing our proposal in our regulation at Sec. 512.390(b)(1)(iii)
and Sec. 512.390(b)(1)(iv) to require that the ETC Participant observe
all applicable laws regarding the appropriate use of data and the
confidentiality and privacy of individually identifiable health
information as would apply to a covered entity under the HIPAA
regulations, and agree to comply with the terms of the ETC Data Sharing
Agreement, to be signed at least annually, as a condition of receiving
the beneficiary identifiable data, with one modification. Specifically,
we are making a technical change at Sec. 512.390(b)(1)(iii) to replace
the phrase ``HIPAA regulations'' with ``regulations found at 45 CFR
parts 160 and 164 promulgated under the Health Insurance Portability
and Accountability Act of 1996 (HIPAA), as amended'' to clarify the
applicable regulations, as the regulations initially promulgated under
HIPAA have been amended by the Health Information Technology for
Economic and Clinical Health (HITECH) Act, and may be amended by other
statutes in the future.
(2) Content of ETC Data Sharing Agreement Provisions for Beneficiary-
Identifiable Data
We proposed in new Sec. 512.390(b)(iv) that, under the ETC Data
Sharing Agreement, ETC Participants would agree to certain terms,
namely: (1) To comply with the requirements for use and disclosure of
this beneficiary-identifiable data that are imposed on covered entities
by the HIPAA regulations and the requirements of the ETC Model set
forth in 42 CFR part 512; (2) to comply with additional privacy,
security, and breach notification requirements to be specified by CMS
in the ETC Data Sharing Agreement; (3) to contractually bind each
downstream recipient of the beneficiary-identifiable data that is a
business associate of the ETC Participant or performs a similar
function for the ETC Participant, to the same terms and conditions to
which the ETC Participant is itself bound in its data sharing agreement
with CMS as a condition of the downstream recipient's receipt of the
beneficiary-identifiable data retrieved by the ETC Participant under
the ETC Model; and (4) that if the ETC Participant misuses or discloses
the beneficiary-identifiable data in a manner that violates any
applicable statutory or regulatory requirements or that is otherwise
non-compliant with the provisions of the ETC Data Sharing Agreement,
the ETC Participant would no longer be eligible to retrieve the
beneficiary-identifiable data and may be subject to additional
sanctions and penalties available under the law. In the CY 2022 ESRD
PPS proposed rule (86 FR 36389), we stated that we believe these terms
for sharing beneficiary-identifiable data with ETC Participants are
appropriate and important, as CMS must ensure to the best of its
ability that any beneficiary-identifiable data that it shares with ETC
Participants would be further protected by the ETC Participant, and any
business associates of the ETC Participant, in an appropriate fashion.
We stated that we believe that these proposals would allow CMS to
accomplish that.
CMS solicited public comment on the additional privacy, security,
breach notification, and other requirements that we would include in
the ETC Data Sharing Agreement. As we noted in the CY 2022 ESRD PPS
proposed rule, CMS has these types of agreements in place as part of
the governing documents of other models tested under section 1115A of
the Act and in the Medicare Shared Savings Program. In these
agreements, CMS typically requires the identification of data
custodian(s) and imposes certain requirements related to
administrative, physical, and technical safeguards relating to data
storage and transmission; limitations on further use and disclosure of
the data; procedures for responding to data incidents and breaches; and
data destruction and
[[Page 61979]]
retention. We proposed that these provisions would be imposed in
addition to any restrictions required by law, such as those provided in
the HIPAA privacy, security, and breach notification regulations. We
additionally proposed that these provisions would not prohibit the ETC
Participant from making any disclosure of the data otherwise required
by law.
We noted in the CY 2022 ESRD PPS proposed rule that we were
considering limiting the use of beneficiary-identifiable data for
specific purposes, either alone or in combination. We noted that, for
example, in the ETC Data Sharing Agreement, CMS considered imposing
limits on how the ETC Participant may use the beneficiary-identifiable
data without prior written authorization from CMS to specific purposes,
such as assessing CMS's calculation of the MPS for a given PPA Period,
the ETC Participant's clinical care or ``treatment'' (as that term is
defined at 45 CFR 164.501) of an attributed beneficiary, and certain
``health care operations'' (as that term is defined at 45 CFR 164.501)
of the ETC Participant. As noted previously in the CY 2022 ESRD PPS
proposed rule and this final rule, CMS believes that ETC Participants
would require this data to be able to request a targeted review of
CMS's calculation of the MPS as it relates to a given PPA Period, as
understanding and being able to seek review of CMS's calculation of the
MPS, and thus the reason CMS adjusted the ETC Participant's Medicare
payments in the manner it did, is critical for the ETC Model. In the CY
2022 ESRD PPS proposed rule, we noted that importantly, there is no
other source of this information outside of CMS. In addition to
potentially limiting use to reviewing how CMS calculated the ETC
Participant's MPS, we stated in the CY 2022 ESRD PPS proposed rule that
we were considering limiting, in the ETC Data Sharing Agreement, use of
the beneficiary-identifiable data without prior written authorization
from CMS to use for clinical treatment purposes. We stated our belief
that this beneficiary-identifiable data would be important in helping
the ETC Participant determine which of its ESRD Beneficiaries are not
on the transplant waitlist or have not received a living donor
transplant, to inform how the ETC Participant engages in clinical care
of the subject ESRD Beneficiary.
In addition to the previous two uses, we stated in the CY 2022 ESRD
PPS proposed rule that we also were considering limiting, in the ETC
Data Sharing Agreement, the ETC Participant's use of the beneficiary-
identifiable data without prior written authorization from CMS to care
management and coordination, quality improvement activities, and
provider incentive design and implementation, to the extent these
activities would constitute ``health care operations'' that fall within
the first and second paragraphs of the definition of that phrase under
the HIPAA Privacy Rule (45 CFR 164.501). As it relates to case
management and coordination and quality improvement activities, we
stated in the CY 2022 ESRD PPS proposed rule that CMS believes that
this beneficiary-identifiable data would help the ETC Participant to
conduct the important task of identifying which ESRD Beneficiaries are
not currently on the transplant waitlist and thus better enable the ETC
Participant to engage those beneficiaries, as clinically appropriate,
about the process of signing up for the transplant waitlist, thereby
improving the ETC Participant's performance on the transplant waitlist
rate, and increasing the likelihood that the subject ESRD Beneficiaries
would receive a transplant. In addition, we noted our belief that
sharing this data with the ETC Participant would help the ETC
Participant to conduct the important task of identifying which ESRD
Beneficiaries are receiving dialysis in-center, and to consider whether
furnishing kidney disease patient education services or otherwise
making such beneficiaries aware of the possibility of receiving home
dialysis, self-dialysis, or nocturnal in-center dialysis, as clinically
appropriate in the ESRD Beneficiary's individual situation.
We sought public comment on how an ETC Participant might need to,
and want to, use the beneficiary-identifiable data retrieved from CMS
under the ETC Model to accomplish the goals of the ETC Model in
accordance with applicable law.
We also sought public comment on what further disclosures of the
beneficiary-identifiable data might be appropriate to permit or
prohibit under the ETC Data Sharing Agreement. For example, we stated
in the CY 2022 ESRD PPS proposed rule that CMS considered prohibiting,
in the ETC Data Sharing Agreement, any further disclosure, not
otherwise required by law, of the beneficiary-identifiable data
described previously in this section of the CY 2022 ESRD PPS proposed
rule to anyone who is not a HIPAA covered entity or business associate,
as defined in 45 CFR 160.103, or to an individual practitioner in a
treatment relationship with the subject ESRD Beneficiary or Pre-emptive
LDT Beneficiary, or that practitioner's business associates. Such a
prohibition would be similar to that imposed by CMS in other models
tested under section 1115A of the Act in which CMS shares beneficiary-
identifiable data with model participants. In the alternative, we
noted, CMS also considered including more restrictive prohibitions in
the ETC Data Sharing Agreement, which would limit further discloses to
only some, one, or none of the categories of individuals or entities
described above.
We explained in the CY 2022 ESRD PPS proposed rule that we
considered all of these possibilities because there exist important
legal and policy limitations on the sharing of the beneficiary-
identifiable data discussed previously in the CY 2022 ESRD PPS proposed
rule, and CMS must consider carefully the ways in which and reasons for
which we would provide access to this data for purposes of the ETC
Model. We stated that we believe that some ETC Participants may require
the assistance of business associates, such as contractors, to perform
data analytics or other functions using this beneficiary-identifiable
data to support the ETC Participant's review of CMS's MPS calculations,
care management and coordination, quality improvement activities, or
clinical treatment of attributed beneficiaries. We further noted that
we believe that this beneficiary-identifiable data may be helpful for
any HIPAA covered entities who are in a treatment relationship with the
subject ESRD Beneficiary or Pre-emptive LDT Beneficiary.
We sought public comment on how an ETC Participant might need to,
and want to, disclose the beneficiary-identifiable data to other
individuals and entities to accomplish the goals of the ETC Model, in
accordance with applicable law.
Under our proposal, the ETC Data Sharing Agreement would include
other provisions, including requirements regarding data security,
retention, destruction, and breach notification. For example, we
considered including, in the ETC Data Sharing Agreement, a requirement
that the ETC Participant designate one or more data custodians who
would be responsible for ensuring compliance with the privacy, security
and breach notification requirements for the data set forth in the ETC
Data Sharing Agreement; various security requirements like those found
in other models tested under section 1115A of the Act, but no less
restrictive than those provided in the relevant Privacy Act system of
records notices; how and when beneficiary-identifiable data could be
retained by the ETC Participant or its downstream recipients of the
[[Page 61980]]
beneficiary-identifiable data; procedures for notifying CMS of any
breach or other incident relating to the unauthorized disclosure of
beneficiary-identifiable data; and provisions relating to destruction
of the data. We noted that these are only examples, and are not the
only terms CMS would potentially include in the ETC Data Sharing
Agreement.
We solicited public comment on this proposal that CMS, by adding
Sec. 512.390(b)(1)(iv)(B), would impose certain requirements in the
ETC Data Sharing Agreement related to privacy, security, data
retention, breach notification, and data destruction.
Finally, as described previously in section V.B.7.b(2) of this
final rule, we proposed, at Sec. 512.390(b)(1)(iv)(D), that the ETC
Data Sharing Agreement would include a term providing that if the ETC
Participant misuses or discloses the beneficiary-identifiable data in a
manner that violates any applicable statutory or regulatory
requirements or that is otherwise non-compliant with the provisions of
the ETC Data Sharing Agreement, the ETC Participant would no longer be
eligible to retrieve beneficiary-identifiable data under proposed Sec.
512.390(b)(1)(i) and may be subject to additional sanctions and
penalties available under law. We also proposed to make conforming
amendments to 42 CFR 512.160. Section 512.160(b) outlines the remedial
actions available under the RO Model and ETC Model, and paragraph
(b)(8), in particular provides that, if CMS determines that one or more
grounds for remedial action specified in Sec. 512.160(a) has taken
place, CMS may discontinue the provision of data sharing and reports to
the model participant. We proposed to add a new Sec. 512.160(a)(9) to
specify that, for the ETC Model only, CMS may take remedial action if
the model participant misuses or discloses the beneficiary-identifiable
data in a manner that violates any applicable statutory or regulatory
requirements or that is otherwise non-compliant with the provisions of
the applicable data sharing agreement. We noted that this proposed
change would align the regulatory provision on remedial action with the
remedial action we would include in the ETC Data Sharing Agreement.
We solicited public comment on this proposal, to prohibit the ETC
Participant from obtaining beneficiary-identifiable data pertaining to
the ETC Model if the ETC Participant fails to comply with applicable
laws and regulations, the terms of the ETC Model, or the ETC Data
Sharing Agreement.
The following is a summary of the comments received on additional
privacy, security, breach notification, and other requirements that we
proposed to include in the ETC Data Sharing Agreement, and our
responses.
Comment: One commenter expressed general support for having strong
safeguards to protect sensitive beneficiary information and to ensure
the data's appropriate use.
Response: We appreciate this comment. We agree that it is critical
that any data sharing policy we finalize for the ETC Model have strong
safeguards designed to protect sensitive beneficiary information and to
ensure, to the best of our ability, the appropriate use of the data by
ETC Participants and their downstream users.
Comment: One commenter expressed support for allowing an ETC
Participant to disclose the beneficiary-identifiable data shared by CMS
under the ETC Model with other covered entities in a treatment
relationship with ESRD Beneficiaries, and with the ETC Participant's
business associates. The commenter noted that this proposal would allow
the data to be used in quality improvement activities by ETC
Participants, and that many clinicians partner with third-party data
vendors as business associates under the HIPAA rules, since such
vendors have expertise in the field of data analytics and in analyzing
trends and identifying areas for quality improvement.
Response: CMS agrees that it is appropriate to allow an ETC
Participant to disclose the beneficiary-identifiable data shared by CMS
under the ETC Model with other covered entities in a treatment
relationship with ESRD Beneficiaries, to help ensure that other covered
entities who furnish care to ESRD Beneficiaries have the benefit of
this important information related to the subject beneficiary's kidney
care. In addition, CMS agrees that many clinicians contract with third
parties for analytics support, and that such support can assist
clinicians in conducting quality improvement activities. As we describe
later in this section of the final rule, CMS is finalizing a data
sharing policy that will allow an ETC Participant to disclose the
beneficiary-identifiable data shared by CMS under the ETC Model with a
business associate of the ETC Participant, so long as the ETC
Participant contractually binds the business associate to the same
terms and conditions to which the ETC Participant is itself bound in
its ETC Data Sharing Agreement with CMS as a condition of the business
associate's receipt of the beneficiary-identifiable data. The policy we
are finalizing places limits on the ETC Participant's further
disclosures of the beneficiary-identifiable data shared by CMS.
Specifically, the policy we are finalizing requires that any non-
covered entity with whom the ETC Participant discloses beneficiary-
identifiable data made available to the ETC Participant under the ETC
Model must be a business associate of the ETC Participant--and cannot
be a downstream recipient who is neither a covered entity nor a
business associate of the ETC Participant--except as otherwise required
by law. CMS is making this modification because it believes that
limiting downstream recipients of beneficiary-identifiable data shared
under the ETC Model to those who have a business associate agreement in
place with the ETC Participant, and that business associate agreement
adopts the terms required under this regulation, will best safeguard
the privacy and security interests of beneficiaries.
Comment: One commenter expressed support for the data shared to be
protected by existing Federal privacy and confidentiality laws, but
requested that CMS clarify the differences between the privacy
protections required under the ETC Model and those required by HIPAA.
Response: It is critical to clarify that the policies we are
finalizing in this section of the final rule are for the ETC Model only
and are not intended to modify the HIPAA Privacy Rule or change
existing legal obligations under the HIPAA Privacy Rule or other
privacy laws. By finalizing our proposal in this final rule, we are
establishing a requirement under Sec. 512.390(b)(1) for CMS to share
beneficiary-identifiable data in a manner that is consistent with the
HIPAA Privacy Rule, 45 CFR 164.512(a). We are also establishing
additional protections for the beneficiary-identifiable data shared
with ETC Participants under the ETC Model that they must, in turn,
impose on any business associates. These additional requirements and
safeguards include, but are not limited to, the annual completion and
submission of an ETC Data Sharing Agreement; specific instructions
relating to breach notification and data retention and destruction; and
the identification of one or more data custodians who will be
responsible for ensuring compliance with the privacy, security, and
breach notification requirements set forth in the ETC Data Sharing
Agreement. Further, under our final policy, we are placing additional
limits on how the ETC Participant may use and further disclose the
beneficiary-identifiable identifiable data received from CMS under the
ETC
[[Page 61981]]
Model, beyond what may otherwise be permitted under the HIPAA Privacy
Rule. In particular, ETC Participants will be limited to using and
further disclosing the beneficiary-identifiable data under the ETC
Model for the following purposes (other than disclosures otherwise
required by law), without obtaining prior written permission from CMS:
The ETC Participant's ``health care operations'' that fall within the
first and second paragraphs of the definition of that phrase under the
HIPAA Privacy Rule (45 CFR 164.501), to the extent they relate to care
management and coordination, quality improvement activities, and
provider incentive design and implementation; for clinical care or
``treatment'' (as that term is defined in 45 CFR 164.501) of the
subject beneficiary; and for assessing CMS's calculations underlying
the MPS for the relevant PPA Period. We believe these uses and bases
for further disclosure represent the only appropriate uses and bases
for further disclosure for the beneficiary-identifiable data made
available to the ETC Participant under the Model, and the only
appropriate uses for business associates to whom the ETC Participant
discloses such data, for the reasons we provide below in response to
other comments.
Comment: One commenter recommended that CMS not impose additional
restrictions on data sharing beyond those required by the HIPAA Privacy
Rule, and asserted that an ETC Participant should be able to use the
beneficiary-identifiable data for the same ``treatment'' and ``health
care operations'' activities permitted under HIPAA. Another commenter
similarly suggested that CMS not impose additional limitations on an
ETC Participant's use or further disclosure of the beneficiary-
identifiable data beyond those imposed by existing law, and
additionally recommended that CMS not require the ETC Participant to
obtain permission from CMS or another agency prior to any permitted
data use.
Response: We agree that an ETC Participant should be able to use
the beneficiary-identifiable data made available by CMS under the ETC
Model for the ``treatment'' (as that term is defined in 45 CFR 164.501)
of the subject beneficiary, and we are finalizing our proposal to allow
an ETC Participant to use such data for treatment. We believe it is
important that an ETC Participant be able to use such data to inform
their direct care of the beneficiary, especially as it relates to
discussing renal replacement modalities and transplantation.
The definition of ``health care operations'' in the HIPAA Privacy
Rule at 45 CFR 164.501 covers a broad array of activities, most of
which we believe are not relevant or necessary for purposes of the ETC
Participant's performance in the Model. For example, an ETC Participant
would not need to perform ``underwriting, enrollment, premium rating,
and other activities related to the creation, renewal, or replacement
of a contract of health insurance or health benefits[,]'' as described
in the third paragraph of the definition. In addition, other uses and
disclosures generally allowed under HIPAA without obtaining individual
authorization, such as ``payment,'' are not relevant to the ETC
Participant's performance in the Model. To appropriately safeguard the
beneficiary-identifiable data, we will limit the permitted uses and
further disclosures of the PHI shared under the ETC Model to the ETC
Participant's ``health care operations'' that fall within the first and
second paragraphs of the definition of that phrase under the HIPAA
Privacy Rule (45 CFR 164.501), to the extent they relate to care
management and coordination, quality improvement activities, and
provider incentive design and implementation; treatment of the subject
beneficiary; assessing CMS's calculations of the ETC Participant's MPS;
and as otherwise required by law. In addition, under our final policy,
we will permit the ETC Participant to use and further disclose
beneficiary-identifiable retrieved under the ETC Model for assessing
CMS's calculations underlying the MPS, which sufficiently covers the
ETC Participant's need to use such data for ``[b]usiness planning and
development'' as permitted under the fifth paragraph of the ``health
care operations'' definition.
Moreover, we agree that it is not desirable to require an ETC
Participant to obtain permission from CMS or another agency prior to
engaging in any particular use or further disclosure of the
beneficiary-identifiable data. Once the ETC Participant has completed
its annual ETC Data Sharing Agreement, we do not expect the ETC
Participant will need to obtain additional permission from CMS or
another agency to use or further disclose the beneficiary-identifiable
data in the ways we describe in this final rule or will describe in the
ETC Data Sharing Agreement, or that CMS may otherwise authorize in
writing.
Comment: One commenter recommended that CMS implement a warning
system prior to deeming an ETC Participant ineligible to retrieve
beneficiary-identifiable data under the ETC Model, because without
access to the beneficiary-identifiable data that CMS proposed to make
available to ETC Participants under the Model, an ETC Participant would
be unable to identify its dual-eligible or LIS-eligible beneficiaries,
or trends in the data for the purpose of conducting quality
improvement. The commenter additionally asserted that rendering an ETC
Participant ineligible to retrieve such data would lead to a decrease
in the quality of care provided, negatively affecting both ETC
Participants and attributed beneficiaries. The commenter further
suggested that an instance of noncompliance with the relevant
requirements under the proposed regulation at Sec. 512.390(b) or the
ETC Data Sharing Agreement could arise due to an inadvertent error.
Response: We thank the commenter for this feedback. As we noted in
the CY 2022 ESRD PPS proposed rule and in this section of this final
rule, there are important sensitivities surrounding the sharing of this
type of individually identifiable health information, and we must
ensure to the best of our ability that any beneficiary-identifiable
data shared with ETC Participants would be further protected in an
appropriate fashion. Further, errors or other conduct resulting in the
improper disclosure of beneficiary-identifiable data, inadvertent or
otherwise, threaten the privacy interests of attributed beneficiaries.
However, we also understand that not every improper use, disclosure, or
other handling of beneficiary-identifiable data shared under the ETC
Model would equally threaten the privacy interests of attributed
beneficiaries. We agree with the commenter that we should retain a
level of discretion in responding to instances of noncompliance.
However, we disagree that we should implement an explicit warning
system prior to deeming an ETC Participant ineligible to retrieve
beneficiary-identifiable data under the ETC Model. If CMS believed that
a given instance of noncompliance warranted a warning, CMS would have
discretion under Sec. 512.160 to impose various remedial actions,
including but not limited to notifying the ETC Participant of the
violation. We also have the discretion under Sec. 512.160 to require
the ETC Participant to provide additional information to CMS or its
designees; subject the model participant to additional monitoring,
auditing, or both; or to require the ETC Participant to submit a
corrective action plan. In other words, CMS already has the authority
impose remedial actions less severe than discontinuing data sharing, if
CMS
[[Page 61982]]
determines the situation so warranted, without implementing an explicit
warning system that would impose burden and limit CMS's discretion.
Accordingly, we decline to implement an explicit warning system prior
to deeming an ETC Participant ineligible to retrieve beneficiary-
identifiable data under the Model.
Instead, we are finalizing Sec. 512.390(b)(1)(iv)(D) with a
modification to grant CMS more discretion in determining whether an ETC
Participant's misuse or improper disclosure of beneficiary-identifiable
data warrants CMS deeming an ETC Participant ineligible to retrieve
beneficiary-identifiable data during performance of the Model. Under
this modification, CMS may deem an ETC Participant ineligible to
retrieve such data for any amount of time, meaning it could be for the
entire period of the Model or for a shorter time, or CMS could impose a
lesser remedial action. This language would better align with our
proposal to add a new Sec. 512.160(a)(9) to specify that, for the ETC
Model only, CMS may take remedial action under Sec. 512.160(b) if CMS
determines that the model participant misuses or discloses the
beneficiary-identifiable data in a manner that violates any applicable
statutory or regulatory requirements or that is otherwise non-compliant
with the provisions of the applicable data sharing agreement.
Final Rule Action: After considering public comments, we are
finalizing our proposal in our regulation at Sec. 512.390(b)(iv)(A)-
(D) related to additional privacy, security, breach notification, and
other requirements that we would include in the ETC Data Sharing
Agreement, with modification. First, we are modifying our proposal at
Sec. 512.397(b)(iv)(C) to remove language related to downstream
recipients who perform a similar function or service to that of a
business associate, to clarify that the ETC Participant may only
further disclose beneficiary-identifiable data made available under the
ETC Model to business associates of the ETC Participant. Second, we are
modifying our proposed policy that an ETC Participant that misuses or
discloses the beneficiary-identifiable data retrieved under the ETC
Model in a manner that violates any applicable statutory or regulatory
requirements, or that is otherwise noncompliant with the provisions of
the ETC Data Sharing Agreement, would be automatically ineligible to
retrieve beneficiary-identifiable data under the ETC Model. Instead, we
are finalizing a policy that would give CMS discretion to take
appropriate remedial action in the instance that an ETC Participant
engages in such misuse or improper disclosure. Specifically, we are
modifying the proposed language at Sec. 512.390(b)(1)(iv)(D) to
provide that, if an ETC Participant wishes to retrieve the beneficiary
identifiable data specified in Sec. 512.390(b)(1)(ii), the ETC
Participant agrees, in signing and completing the ETC Data Sharing
Agreement, that if the ETC Participant misuses or discloses the
beneficiary-identifiable data in a manner that violates any applicable
statutory or regulatory requirements, or that is otherwise non-
compliant with the provisions of the data sharing agreement, CMS may
deem the ETC Participant ineligible to retrieve the beneficiary-
identifiable data under Sec. 512.390(b)(1)(i) for any amount of time,
and the ETC Participant may be subject to additional sanctions and
penalties available under the law. We are otherwise finalizing our
proposal to include privacy, security, breach notification, and other
requirements in the ETC Data Sharing Agreement.
(3) Process for Retrieving the ETC Data Sharing Agreement and
Beneficiary-Identifiable Data
In the CY 2022 ESRD PPS proposed rule (86 FR 36390), we proposed
that we would make the ETC Data Sharing Agreement and beneficiary-
identifiable data available in a form and manner specified by CMS. We
stated that we expected to provide a web-based platform for ETC
Participants to use to retrieve the beneficiary-identifiable data. We
noted that CMS would provide ETC Participants further information about
this web-based platform through the ETC listserv and the ETC Model
website at a date to be determined by CMS, but at least 1 month before
the first PPA Period begins on June 1, 2022. We also stated that we
expect that CMS would notify ETC Participants of each opportunity to
retrieve a new set of beneficiary-identifiable data and the process for
accessing the web-based platform to receive the data through the ETC
listserv and on the ETC Model website. Under this proposal, the ETC
Participant would be required to use the form and manner specified by
CMS (which we expect will be a web-based platform) to retrieve the
data. We proposed that if the ETC Participant did not use the form and
manner specified by CMS or did not agree to the ETC Data Sharing
Agreement, the ETC Participant would be unable to retrieve the
beneficiary-identifiable data described previously in this section of
the CY 2022 ESRD PPS proposed rule. We proposed that ETC Participants
would be permitted to retrieve this data at any point during the
relevant PPA Period. In the CY 2022 ESRD PPS proposed rule, we
considered establishing certain periods of time within a PPA Period
during which the ETC Participant would be able to retrieve the data,
but we concluded that permitting the ETC Participant to obtain the data
at any point during the relevant PPA Period would be relatively
operationally low-burden for CMS while providing additional flexibility
to the ETC Participant.
We stated that we believe that it is important that the ETC
Participant complete and submit its signed ETC Data Sharing Agreement,
and retrieve the beneficiary-identifiable data, in the same form and
manner (which we expect to be a web-based platform).
In the alternative, we considered providing the beneficiary-
identifiable data to ETC Participants via paper mail rather than
through a web-based platform, but we concluded that making the data
available through a web-based platform would reduce administrative
burden on both CMS and the ETC Participants. We also concluded that
making this beneficiary-identifiable data available through a web-based
platform would allow CMS to provide the data in a manner that is more
secure than if CMS were to make the data available through paper mail.
As we explained in the CY 2022 ESRD PPS proposed rule, by using a web-
based platform, to be further described by CMS through the ETC listserv
and the ETC Model website, CMS would help ensure that only authorized
users would be able to obtain the data, and would be able to implement
a two-factor authentication to help ensure that no one other than an
ETC Participant would have access to the data. In addition, we
concluded that it would be more efficient to provide the ETC Data
Sharing Agreement and the beneficiary-identifiable data itself through
the same form and manner (which we expect to be a web-based platform),
rather than using two different processes and that using a web-based
platform would be more efficient than paper mail. For these reasons, we
stated that we believe the best option would be for us to use only the
web-based platform both for providing the ETC Data Sharing Agreement
and for sharing data pertaining to the ETC Model.
We solicited public comment on our proposal to require the ETC
Participant to complete and submit a signed ETC Data Sharing Agreement
before the ETC Participant could retrieve the beneficiary-identifiable
data, and on our
[[Page 61983]]
proposal that the ETC Participant would be required to retrieve the
beneficiary-identifiable data in the same form and manner as the ETC
Participant receives and submits the ETC Data Sharing Agreement. We
also solicited comment regarding our expectation that we will use a
web-based platform, rather than paper mail, for these purposes.
The following is a summary of the comments received on our proposed
process for retrieving the ETC Data Sharing Agreement and beneficiary-
identifiable data, and our responses.
Comment: Two commenters expressed support for CMS making the
beneficiary-identifiable data available to the ETC Participant via a
web-based platform. One such commenter expressed opposition to the
alternative process that CMS considered; namely, to share the
beneficiary-identifiable data via paper mail, as data sent via paper
mail would be inconvenient to both CMS and ETC Participants. The
commenter also stated that sharing the beneficiary-identifiable data by
paper mail would increase the risk of the data being viewed by the
wrong parties, and that mailing data would be contradictory to CMS's
initiatives promoting interoperability.
Response: We agree that a web-based platform is an appropriate
process for sharing beneficiary-identifiable data in the ETC Model, and
is a more appropriate process than sharing such data through paper
mail. We believe, as we expressed in the CY 2022 ESRD PPS proposed
rule, that making the data available through a web-based platform would
reduce administrative burden on both CMS and ETC Participants, and that
a web-based platform would be more secure than making the data
available through paper mail. We agree with the commenter's concern
that sharing data via paper mail would increase the risk of a data
breach compared to sharing data via a web-based platform. While we do
not believe sharing data via paper mail would necessarily contradict
CMS's efforts promoting interoperability, we do believe that sharing
data via paper mail would make it more burdensome for ETC Participants
to ingest the data in a software that could exchange information with
other healthcare providers or suppliers, or business associates, as
appropriate.
Final Rule Action: After considering public comments, we are
finalizing our proposal in our regulation at Sec. 512.390(b) that an
ETC Participant must obtain an ETC Data Sharing Agreement, sign and
complete an ETC Data Sharing Agreement, and retrieve beneficiary
identifiable data all in a form and manner to be specified by CMS,
without modification. As stated in the CY 2022 ESRD PPS proposed rule,
we expect that ``form and manner'' will be via a web-based platform,
and CMS will provide ETC Participants further information about this
web-based platform via the ETC listserv and ETC Model website at least
one month before the first PPA Period begins on June 1, 2022.
e. CMS Sharing of Aggregate Data
In addition to the proposed process for sharing beneficiary-
identifiable data described previously in this section, we proposed in
Sec. 512.390(b)(2) that CMS would make available certain aggregate
data for retrieval by the ETC Participant, in a form and manner to be
specified by CMS, no later than one month before each PPA Period. We
proposed that this aggregate performance data, would include, when
available, the following information for each PPA Period, de-identified
in accordance with 45 CFR 164.514(b): The ETC Participant's performance
scores on the home dialysis rate, transplant waitlist rate, living
donor transplant rate, and, if finalized, Health Equity Incentive; the
ETC Participant's aggregation group's scores on the home dialysis rate,
transplant waitlist rate, living donor transplant rate, and, if
finalized, Health Equity Incentive; information on how the ETC
Participant's and ETC Participant's aggregation group's scores relate
to the achievement benchmark and improvement benchmark (that is,
whether the ETC Participant met or exceeded the threshold for each such
benchmark); and the ETC Participant's MPS and PPA for the corresponding
PPA Period. We stated in the CY 2022 ESRD PPS proposed rule (86 FR
36391) that we believe sharing this aggregate, de-identified data with
the ETC Participant would be important to help the ETC Participant
better understand its performance in the ETC Model relative to its
aggregation group and to the achievement and improvement benchmarks
against which CMS is measuring the ETC Participant's performance. We
stated that whereas the beneficiary-identifiable data described
previously in the CY 2022 ESRD PPS proposed rule and this section of
the final rule would indicate which ESRD Beneficiaries and, if
applicable, Pre-emptive LDT Beneficiaries the ETC Participant could
devote greater resources to, CMS believes this aggregate, de-identified
data would better enable the ETC Participant to see which performance
rates the ETC Participant might need to improve to more generally
improve its performance under the ETC Model.
We proposed that CMS would make this data available to the ETC
Participant for retrieval in a form and manner to be specified by CMS
no less than one month prior to each PPA Period. We stated that we
expected that CMS would make this data available to the ETC Participant
on the same web-based platform on which CMS would be providing the
beneficiary-identifiable data described previously in this section. We
proposed that the ETC Participant would be required to use the form and
manner specified by CMS to retrieve this aggregate data, but would not
have to agree to the ETC Data Sharing Agreement to retrieve this
aggregated data, as it is not beneficiary-identifiable. We noted our
belief that using a web-based platform for sharing this aggregate data
would be appropriate for the same reasons it would be appropriate for
sharing the beneficiary-identifiable data. By using a web-based
platform, CMS would help ensure that only authorized users would be
able to obtain the data, and would be able to implement a two-factor
authentication to help ensure that no one other than an ETC Participant
would have access to the data. In addition, we stated, because CMS
would be providing the ETC Data Sharing Agreement and beneficiary-
identifiable data on the same web-based platform, we believe it would
be convenient for the ETC Participant if CMS shared the aggregate data
on the same web-based platform.
In the alternative, we considered sending this aggregate data to
the ETC Participant via paper mail. However, CMS concluded in the CY
2022 ESRD PPS proposed rule that it would be more convenient to the ETC
Participant to retrieve this data from a web-based platform rather than
via paper mail, and that sending this data via paper mail would
represent significant administrative and operational burdens for CMS.
We solicited public comment on our proposal to share aggregate data
generally, to share aggregated data in the same form and manner we are
proposing to use for sharing beneficiary-identifiable data. We also
solicited public comment on our expectation to use a web-based platform
for this purpose, as well as our considered alternative to share the
aggregate data via paper mail.
The following is a summary of the comments received on our proposed
process for sharing aggregate data, and our responses.
Comment: Some commenters expressed support for our proposal to
[[Page 61984]]
share aggregate data. One such commenter stated that aggregate data
will help an ETC Participant determine its previous rates for different
dialysis modalities, and allow the ETC Participant to focus on
increasing rates of the dialysis modalities measured for payment
adjustments under the ETC Model. The commenter further noted that
without knowledge of the ETC Participant's current rates on the
different modalities, the ETC Participant would have difficulty
understanding when the ETC Participant's actions have resulted in
positive change. Another commenter noted that many small ETC
Participants may lack the resources to perform detailed analytics with
the beneficiary-identifiable data, and that the proposed aggregate data
would thus be helpful for such ETC Participants. The same commenter
additionally noted that the proposed aggregate data would be useful for
ETC Participants that can and do perform detailed analytics with the
beneficiary-identifiable data to help validate the results of such
analytics.
Response: We agree that sharing the aggregate data, as proposed,
would prove helpful for ETC Participants, regardless of the individual
ETC Participant's analytics capacity. We also agree that such data can
be used to compare the ETC Participant's previous home dialysis and
transplant rates, and performance with current rates and performance,
and thus can help signal to the ETC Participants when interventions are
producing positive results.
Comment: One commenter expressed support for our proposal to not
require the ETC Participant to sign an ETC Data Sharing Agreement to
obtain aggregate data from CMS.
Response: We agree; we do not believe an ETC Data Sharing Agreement
is necessary to protect the aggregate data because it will be fully de-
identified in accordance with HIPAA requirements under 45 CFR
164.514(b) and will not contain any beneficiary-identifiable data.
Comment: One commenter recommended that CMS make available
aggregate comparative data to ETC Participants quarterly to allow an
ETC Participant to assess where it stands on its home dialysis rate and
transplant rate in terms of ranking relative to other ETC Participants'
performance.
Response: We appreciate this comment. For the same reason that we
are not making beneficiary-identifiable data available on a more
frequent cadence as discussed in section V.B.7.b of this final rule, we
are not making aggregate data available on a more frequent cadence.
Specifically, we believe that the proposed schedule for sharing
aggregate data affords the ETC Participant sufficient time to derive
benefit, such as monitoring the ETC Participant's performance over the
course of the ETC Model from the aggregate data. Further, as described
in Sec. 512.360, CMS conducts beneficiary attribution for each month
retrospectively after the end of each MY, at which time CMS calculates
the ETC Participant's MPS. Accordingly, CMS would not have aggregate
data to share with the ETC Participant on a quarterly basis; CMS is
unable to share aggregate data on the ETC Participant's performance
more often than biannually, after the end of the applicable MY.
In addition, we do not believe it is necessary for CMS to release
aggregate comparative data to ETC Participants at this time. As
described in Sec. 512.370(b), to assess the ETC Participant's
achievement score, CMS assesses the ETC Participant performance at the
aggregation group level against benchmarks constructed among
aggregation groups of ESRD facilities and Managing Clinicians located
in Comparison Geographic Areas during the Benchmark Year. The
beneficiary-identifiable data we proposed to share includes the ETC
Participant's MPS, and the aggregate data we proposed to share includes
information on how the ETC Participant's and the ETC Participant's
aggregation group's scores relate to the achievement benchmark and
improvement benchmark. In this way, the data CMS is already planning to
share will provide the ETC Participant with insight into how the ETC
Participant and the ETC Participant's aggregation group performed
relative to other health care providers in the corresponding Comparison
Geographic Area during the applicable Benchmark Year.
Final Rule Action: After considering public comments, we are
finalizing our proposal in our regulation at Sec. 512.390(b)(2) to
share aggregate data and to specify the aggregate data that CMS would
share and the process by which CMS would make available and the ETC
Participant would obtain such aggregate data, without modification.
Specifically, we are finalizing our proposal to require CMS to share
make aggregate data available for retrieval by the ETC Participant, in
a form and manner to be specified by CMS, no later than one month
before each PPA Period. This de-identified data includes, when
available, the ETC Participant's performance scores on the home
dialysis rate, transplant waitlist rate, living donor transplant rate,
and the Health Equity Incentive; the ETC Participant's aggregation
group's scores on the home dialysis rate, transplant waitlist rate, and
living donor transplant rate, and the Health Equity Incentive;
information on how the ETC Participant's and ETC Participant's
aggregation group's scores relate to the achievement benchmark and
improvement benchmark; and the ETC Participant's MPS and PPA for the
corresponding PPA Period.
8. Medicare Waivers and Additional Flexibilities
a. Background on Kidney Disease Patient Education Services Waiver
Pursuant to section 1861(ggg)(1) of the Act and Sec. 410.48 of our
regulations, Medicare Part B covers outpatient, face-to-face kidney
disease patient education services provided by certain qualified
persons to beneficiaries with Stage IV chronic kidney disease. As noted
in the Specialty Care Models final rule, kidney disease patient
education services play an important role in educating patients about
their kidney disease and to help them make informed decisions on the
appropriate type of care and/or dialysis needed for them (85 FR 61337).
In addition, we noted in the Specialty Care Models final rule that
kidney disease patient education services are designed to educate and
inform beneficiaries about the effects of kidney disease, their options
for transplantation, dialysis modalities, and vascular access (85 FR
61337). Because kidney disease patient education services have been
infrequently billed, we found it necessary for purposes of testing the
ETC Model to waive select requirements of kidney disease patient
education services authorized in section 1861(ggg)(1) of the Act and in
the implementing regulation at 42 CFR 410.48. Specifically, to broaden
the availability of kidney disease patient education services under the
ETC Model, we have used our authority under section 1115A(d) of the Act
to waive certain requirements for individuals and entities that furnish
and bill for kidney disease patient education services. We codified
these waivers at Sec. 512.397(b). These include waivers to allow more
types of beneficiaries to have access to kidney disease patient
education services, as well as greater flexibility in how the kidney
disease patient education services are performed. For instance, CMS
waived the requirement that kidney disease patient education services
are covered only for Stage IV chronic kidney disease (CKD) patients to
permit beneficiaries to receive kidney disease patient education
[[Page 61985]]
services if they are diagnosed with CKD Stage V or are in the first 6
months of starting dialysis to receive the benefit. CMS also waived the
requirements in section 1861(ggg)(2)(A)(i) of the Act and Sec.
410.48(a) and (c)(2)(i) of the applicable regulations pertaining to the
definition of ``qualified person'' such that registered dieticians/
nutrition professionals, licensed clinical social workers, or a clinic/
group practice may furnish kidney disease patient education services
under the direction of, and incident to the services of a Managing
Clinician who is an ETC Participant.
Finally, CMS waived two requirements relating to the content of
kidney disease patient education services furnished to a beneficiary.
CMS waived the requirement under Sec. 410.48(d)(1) of our regulations
that the content of kidney disease patient education services include
the management of co-morbidities, including delaying the need for
dialysis, when such services are furnished to beneficiaries with CKD
Stage V or ESRD, unless such content is relevant for the beneficiary.
In addition, CMS waived the requirement under Sec. 410.48(d)(5)(iii)
of our regulations that an outcomes assessment designed to measure
beneficiary knowledge about chronic kidney disease and its treatment be
performed during one of the kidney disease patient education services,
requiring instead that such outcomes assessment is performed within 1
month of the final kidney disease patient education services session
furnished by qualified staff.
b. Kidney Disease Patient Education Services Telehealth Waiver and
Additional Flexibilities
Many changes took place in 2020 and early 2021 due to the COVID-19
PHE. Legislation enacted to address the PHE for COVID-19 provided the
Secretary with new authorities under section 1135(b)(8) of the Act to
waive or modify Medicare telehealth payment requirements during the PHE
for COVID-19. We established several flexibilities to accommodate these
changes in the delivery of care. Through waiver authority under section
1135(b)(8) of the Act, in response to the PHE for COVID-19, we
temporarily waived the geographic and site of service originating site
restrictions in section 1834(m)(4)(C) of the Act. For example, CMS
waived the rural area requirement at section 1834(m) of the Act to
allow for telehealth services, including kidney disease patient
education services that can be furnished via telehealth, to be
furnished to beneficiaries in any geographic area, regardless of
location and in their homes, for the duration of the PHE. These waivers
are set to terminate at the end of the COVID-19 PHE.
In the CY 2022 ESRD PPS proposed rule, we stated that we believe
that, once the PHE ends, these waivers removing the geographic and site
of service originating site restrictions for kidney disease patient
education services furnished via telehealth would be necessary solely
for purposes of testing the ETC Model (86 FR 36392). Except under very
limited circumstances, under section 1834(m) of the Act and its
implementing regulations, the originating site where the beneficiary is
located at the time a telehealth service is furnished is limited to
certain, mostly rural, geographic locations and a site of service that
is one of certain types of health care facilities. We also stated our
belief that allowing qualified staff to furnish kidney disease patient
education services via telehealth, regardless of the beneficiary's
geographic area or the site of the beneficiary, and regardless of the
site of service of the practitioner, would increase access to kidney
disease patient education services for a few reasons. First, some
beneficiaries may not have access to reliable transportation,
especially those beneficiaries who suffered economically during the
ongoing PHE, but may have access to the technology necessary for
practitioners to furnish kidney disease patient education services.
Moreover, some beneficiaries, even those with reliable transportation,
may be more comfortable receiving kidney disease patient education
services via telehealth rather than appearing in person after over a
year of social distancing, even when it becomes safe according to
Federal guidance for such beneficiaries to enter physical spaces with
other individuals. We noted that this is especially likely to be the
case for instances in which a practitioner would furnish kidney disease
patient education services in a group session rather than an individual
session. We further noted that increasing access to kidney disease
patient education services is consistent with one of the main goals of
the ETC Model, insofar as we believe that education, as delivered
through kidney disease patient education services, helps improve
beneficiary choice of dialysis modality.
In addition, we stated that we believe that removing beneficiary
cost barriers for kidney disease patient education services would be
helpful. As we demonstrate below in this final rule, there is a
significant relationship between household income or poverty status and
kidney disease, and removing or mitigating cost barriers to access to
kidney disease patient education services would likely increase the
number of beneficiaries who would be willing to receive kidney disease
patient education services.
We therefore proposed that, starting in MY3, kidney disease patient
education services may be furnished to certain beneficiaries via
telehealth in a manner that is more flexible than that required under
existing telehealth requirements. In addition, we proposed to permit
the reduction or waiver of coinsurance for the kidney disease patient
education services, starting in MY3.
(1) Kidney Disease Patient Education Services Telehealth Waiver
CMS proposed to amend Sec. 512.397 to add a waiver of certain
telehealth requirements to provide qualified staff, as we proposed to
define for purposes of the ETC Model at Sec. 512.310 as described
below, the flexibility to furnish kidney disease patient education
services via telehealth for the reasons described above (86 FR 36392).
Specifically, we proposed to waive the geographic and site of service
originating site requirements in sections 1834(m)(4)(B) and
1834(m)(4)(C) of the Act, and in our regulations at 42 CFR 410.78(b)(3)
and (4), for kidney disease patient education services furnished via
telehealth. We stated, in the CY 2022 ESRD PPS proposed rule, that we
believe the kidney disease patient education services telehealth waiver
would allow more Medicare beneficiaries to receive kidney disease
patient education services via telehealth by removing the originating
site restrictions, thus allowing for the beneficiary to be located
anywhere, and including at a site not specified in Sec. 410.78(b)(3)
of our regulations; and by allowing for the beneficiary to be located
outside of a rural area. We also proposed to waive the requirement in
section 1834(m)(2)(B) of the Act and 42 CFR 414.65(b) such that CMS
would not pay an originating site facility fee for kidney disease
patient education services furnished via telehealth to a beneficiary at
a site not specified in Sec. 410.78(b)(3) of our regulations under
this proposed waiver, if finalized. However, we did not propose to
waive the requirement under section 1834(m)(1) of the Act and 42 CFR
410.78(b) that telehealth services be furnished via an ``interactive
telecommunications system,'' as that term is defined in Sec.
410.78(a)(3) to mean multimedia communications equipment
[[Page 61986]]
that includes, at a minimum, audio and video equipment permitting two-
way, real-time interactive communication between the patient and
distant site physician or practitioner. Accordingly, we proposed that
we would continue to require that the kidney disease patient education
services furnished via telehealth be provided through an interactive
telecommunications system; audio-only telehealth services would not be
permitted.
We proposed that kidney disease patient education services could be
furnished via telehealth only by qualified staff. We noted, in the CY
2022 ESRD PPS proposed rule, that we used the terms ``clinical staff''
and ``qualified staff'' in the Specialty Care Models final rule, but
did not provide definitions of these terms. For clarity, we proposed to
define ``clinical staff'' and ``qualified staff'' in 42 CFR 512.310. We
proposed to define ``clinical staff'' to mean a licensed social worker
or registered dietician/nutrition professional who furnishes services
for which payment may be made under the physician fee schedule under
the direction of and incident to the services of the Managing Clinician
who is an ETC Participant. We proposed to define the term clinical
staff in this manner to describe those clinicians who are authorized to
furnish kidney disease patient education services only pursuant to the
waiver specified at Sec. 512.390(b)(1)--namely licensed social workers
and registered dieticians/nutrition professionals. The remaining
clinicians currently specified in Sec. 512.390(b)(1)--doctors,
physician assistants, nurse practitioners, and clinical nurse
specialists--fall within the existing definition of qualified person at
42 CFR 410.48(a). We therefore proposed to define ``qualified staff''
to mean both clinical staff and any qualified person (as defined at
Sec. 410.48(a) of our regulations) who is an ETC Participant.
We sought comment on our proposal to waive the originating site
requirements for telehealth services to allow qualified staff to
furnish kidney disease patient education services via telehealth to a
beneficiary regardless of where the beneficiary is geographically
located such that kidney disease patient education services could be
furnished via telehealth regardless of the beneficiary's location,
including at a site not specified in Sec. 410.78(b)(3) of our
regulations. We further sought comment on our proposal to waive the
originating site facility fee requirements such that CMS would not pay
an originating site facility fee for kidney disease patient education
services furnished via telehealth to a beneficiary at a site not
specified in Sec. 410.78(b)(3) of our regulations.
The following is a summary of the comments received on our proposed
definitions of ``qualified staff'' and ``clinical staff,'' as well as
our proposal to waive certain requirements for furnishing kidney
disease patient education services such that they can be furnished via
telehealth, and our responses.
Comment: A few commenters expressed support for the proposed
definitions of ``clinical staff'' and ``qualified staff.'' One such
commenter reasoned that these definitions would provide clarity on
which clinicians are authorized to furnish kidney disease patient
education services pursuant to the waivers implemented in the ETC
Model.
Response: We agree that the proposed definitions of ``clinical
staff'' and ``qualified staff'' add clarity regarding the types of
staff authorized to furnish kidney disease patient education services
under the ETC Model waivers implemented in Sec. 512.397(b) of our
regulations.
Comment: Many commenters expressed support for the use of
telehealth in general, noting that telehealth is particularly good for
kidney patients, especially kidney patients who live in rural areas or
otherwise face barriers to accessing care. In addition, many commenters
expressed support for the specific telehealth waiver in the CY 2022
ESRD PPS proposed rule. Two such commenters reasoned that the proposed
telehealth waiver would materially increase attributed beneficiaries'
access to kidney disease patient education services. A few commenters
who expressed support reasoned that the proposed telehealth waiver
would address some barriers to access such services for attributed
beneficiaries, such as lack of reliable transportation, lack of
childcare, inability to take time away from work, and other
socioeconomic barriers, and would afford attributed beneficiaries the
choice to receive kidney disease patient education services in a
location of their choice. Several commenters referenced the positive
experience with and benefits of increased access to telehealth during
the PHE. A few commenters expressed support for the proposed telehealth
waiver because they believed it would increase the utilization of
kidney disease patient education services, which they deem an important
benefit.
One commenter expressed support for the proposed telehealth waiver
because they believe it will both allow more beneficiaries to receive
kidney disease patient education services and advance health equity.
Another commenter expressed support for the proposed telehealth waiver
because they believe it would help address the challenge of increasing
rates of kidney disease in rural areas.
Response: We appreciate the comments and support. We agree with the
reasons cited by commenters in support of telehealth generally and the
proposed telehealth waiver specifically. However, because the COVID-19
PHE and the section 1135(b)(8) waiver of geographic and site of service
restrictions for telehealth originating sites in section 1834(m)(4)(C)
of the Act are still ongoing, as described in greater detail below, we
are modifying our proposal such that the proposed ETC telehealth waiver
policy will apply beginning upon the expiration of the COVID-19 PHE,
rather than beginning in MY3 as proposed.
Comment: One commenter expressed support for CMS's proposal to
waive the requirements in Section 1834(m)(2)(B) of the Act and 42 CFR
414.65(b) so that CMS does not pay an originating site facility fee for
kidney disease patient education services furnished via telehealth at a
site not specified in Sec. 410.78(b)(3) of our regulations.
Response: We appreciate the commenter's support.
Comment: One commenter expressed opposition to CMS's proposal to
waive the originating site fee when telehealth services are offered
under the ETC Model's telehealth waiver for kidney disease patient
education services furnished via telehealth at a site not specified in
Sec. 410.78(b)(3) of our regulations. The commenter stated that the
originating site fee was not waived for telehealth services furnished
under the section 1135(b)(8) telehealth waiver in effect during the
COVID PHE. The commenter also stated that the inclusion of the
originating site fee provides an incentive for ETC Participants to
offer kidney disease patient education services via telehealth to a
broader population. The commenter further noted that, consistent with
the proposed incentives to increase access to alternative renal
replacement modalities for dual-eligible and LIS-eligible beneficiaries
under the ETC Model, allowing ETC Participants to receive the
originating site fee for services furnished under the Model's
telehealth waivers could assist in increasing access to kidney disease
patient education services for dual-eligible and LIS-eligible
beneficiaries.
Response: While we appreciate the comment, we respectfully
disagree.
[[Page 61987]]
First, to clarify, CMS did not propose to waive the originating site
fee altogether when telehealth services are offered under the ETC
Model's telehealth waiver for kidney disease patient education
services. That is, CMS will still pay the originating site facility fee
when kidney disease patient education services are furnished via
telehealth at a site specified in Sec. 410.78(b)(3) of our
regulations. This is true even if the originating site is located in a
geographic area not described in Sec. 410.78(b)(4) of our regulations,
as we have waived the geographic requirements in Sec. 410.78(b)(4) for
purposes of kidney disease patient education services furnished by
qualified staff via telehealth in accordance with this section,
regardless of the location of the beneficiary or qualified staff.
Second, while our proposal to implement a telehealth waiver under
the ETC Model was informed by the section 1135(b)(8) telehealth waiver
in effect during the COVID PHE, our proposed waiver was designed
specifically for purposes of the ETC Model. We do not believe it is
appropriate, under the ETC Model, for CMS to pay an originating site
facility fee to an ETC Participant when an ETC Participant furnishes
kidney disease patient education services to a beneficiary via
telehealth at a site not specified in Sec. 410.78(b)(3) of our
regulations. We anticipate that when an ETC Participant is furnishing
kidney disease patient education services to a beneficiary via
telehealth at an originating site not specified in Sec. 410.78(b)(3),
the site will be the home of a beneficiary, or caregiver, family
member, or friend of the beneficiary, or otherwise at a site not
maintained by the ETC Participant. We believe this because, relative to
many other Medicare services, renal replacement therapy (in particular
home dialysis) require the involvement of a caregiver and other family
and friends for support, both directly in assisting the beneficiary in
learning how to perform home dialysis, and indirectly in preparing a
beneficiary's residence for home dialysis (such as ensuring that there
is adequate space available for equipment).
When an ETC Participant is furnishing kidney disease patient
education services to a beneficiary via telehealth at an originating
site not specified in Sec. 410.78(b)(3), the ETC Participant is
generally not providing administrative, clinical support, or overhead
for the site where the beneficiary is located. Not paying an
originating site facility fee under these circumstances is consistent
with Medicare payment policy generally, as CMS does not pay an
originating site facility fee for telehealth services furnished at an
originating site that is the home of an individual.
While CMS does pay the originating site facility fee if the
originating site is a patient's home that has been made provider-based
to a hospital during the COVID-19 PHE, such a site is not technically
considered the patient's home. Additionally, this policy was adopted in
recognition of the changes in practice patterns adopted during the PHE
for infection control purposes. CMS clarified that, during the COVID-
PHE, if applicable requirements are met, a patient's home may be
considered a provider-based department of a hospital (HOPD) in
recognition that when a physician or other practitioner who ordinarily
practices in the HOPD furnishes a telehealth service to a patient who
is located in the home, the hospital would often still provide some
administrative and technical support for the service (85 FR 27565). We
do not believe this policy is appropriate for the ETC Model, as the ETC
Model's telehealth waiver will not become effective until the COVID-19
PHE expires, as described elsewhere in this final rule.
Third, for calendar year 2021, the payment amount for the
originating site facility fee is 80% of $27.02, or $21.62. It is
possible (and indeed, we hope that) the telehealth waiver will increase
clinically appropriate furnishing of kidney disease patient education
services. We are concerned that paying the originating site facility
fee for services furnished via telehealth at an originating site not
specified in Sec. 410.78(b)(3) would likely represent too large an
impact on the ETC Model's savings estimates, potentially jeopardizing
our ability to continue to test the model. In addition, we are
concerned that permitting the originating site facility fee for kidney
disease patient education services furnished via telehealth to a
beneficiary at a site not specified in Sec. 410.78(b)(3) of our
regulations would increase the 20 percent coinsurance owed by a
beneficiary when not reduced or waived by an ETC Participant pursuant
to Sec. 512.390(c). The increased coinsurance obligation may dissuade
a beneficiary from accessing this important service.
For these reasons, we are finalizing our proposed waiver of the
requirement in section 1834(m)(2)(B) of the Act and 42 CFR 414.65(b)
such that CMS will not pay an originating site facility fee for kidney
disease patient education services furnished via telehealth to a
beneficiary at a site not specified in Sec. 410.78(b)(3) of our
regulations.
Comment: One commenter expressed support for CMS's proposal to not
waive the requirement under section 1834(m)(1) of the Act and 42 CFR
410.78(b) that telehealth services be furnished via an ``interactive
telecommunications system,'' as that term is defined in Sec.
410.78(a)(3) to mean multimedia communications equipment that includes,
at a minimum, audio and video equipment permitting two-way, real-time
interactive communication between the patient and distant site
physician or practitioner.
Response: We agree that it is appropriate to continue to require
that kidney disease patient education services furnished via telehealth
be provided through an interactive telecommunications system, such that
audio-only telehealth services are not permitted. We are concerned that
audio-only kidney disease patient education services would not be
effective in meaningfully educating beneficiaries on kidney disease
given the complexity of the subject matter. We believe it is important
that telehealth kidney disease patient education services include, or
at least have the opportunity to include, images, demonstrations, and
other visual cues to most effectively accomplish the objectives of
kidney disease patient education services.
Comment: A few commenters expressed concern regarding our proposal
to not waive the requirement under section 1834(m)(1) of the Act and 42
CFR 410.78(b) that telehealth services be furnished via an interactive
telecommunications system, and recommended that CMS allow the provision
of audio-only telehealth services for kidney disease patient education
services. Two such commenters reasoned that not every beneficiary has
access to interactive telecommunications systems, and one of whom
further suggested that requiring the use of video systems would
preclude those beneficiaries who may most need access to kidney disease
patient education services from benefiting from the proposed telehealth
waiver.
The same commenter additionally suggested that CMS should give ETC
Participants the opportunity to determine how many beneficiaries would
take advantage of audio-only kidney disease patient education services
sessions to allow CMS to determine whether such services would
represent an effective method of providing beneficiary education.
Another commenter suggested that allowing audio-only telehealth
services
[[Page 61988]]
for kidney disease patient education services would align with other
proposed changes to the ETC Model, which, the commenter points out,
include a significant focus on health equity.
Response: We do not believe waiving the requirement that telehealth
services be furnished via an interactive telecommunications system is
necessary to test the ETC Model, either Model-wide or on an ETC
Participant-specific basis. We believe that the telehealth waiver, as
proposed, will accomplish the goal of increasing access to kidney
disease patient education services, and we are interested in learning
whether this goal is realized through this particular proposed waiver.
While we share the concerns raised by commenters that not every
beneficiary has access to an interactive telecommunications system, we
are also concerned that audio-only kidney disease patient education
services would not be effective in meaningfully educating beneficiaries
on kidney disease. As such, we do not agree, at this time, that
allowing audio-only telehealth services for kidney disease patient
education services would align with CMS's focus on health equity
insofar as such a policy may result in beneficiaries of lesser means
systematically receiving lower quality kidney education. However, CMS
will monitor the extent to which there are barriers in access to
interactive telecommunciations systems among attributed beneficiaries.
Based on our experience testing this telehealth waiver in the ETC
Model, we may consider waiving the requirement that telehealth services
be furnished via an interactive telehealth communications system, or
other waivers or initiatives necessary to mitigate or eliminate
barriers to accessing interactive telehealth communications systems, at
a later time, either as part of the ETC Model test or in another
initiative.
Final Rule Action: After considering public comments, we are
finalizing our proposal in our regulation at Sec. 512.397(b)(5) to
waive geographic and site of service originating site requirements in
section 1834(m)(4)(B) and 1834(m)(4)(C) of the Act and Sec.
410.78(b)(3) and (4) of our regulations for the purposes of kidney
disease patient education services furnished by qualified staff via
telehealth in accordance with Sec. 512.397, regardless of the location
of the beneficiary or qualified staff, and the requirement in section
1834(m)(2)(B) of the Act and Sec. 414.65(b) of our regulations that
CMS pay a facility fee to the originating site with respect to
telehealth services furnished to a beneficiary in accordance with Sec.
512.397 at an originating site that is not one of the locations
specified in Sec. 410.78(b)(3), with modification. Specifically, we
are modifying our proposed regulatory text at Sec. 512.397(b)(5) to
change the date on which these waivers become effective. We are
modifying both instances of the phrase, ``Beginning January 1, 2022,''
proposed in Sec. 512.397(b)(5) to the phrase ``Beginning the upon the
expiration of the Public Health Emergency (PHE) for the COVID-19
pandemic[.]''
(2) Kidney Disease Patient Education Services Beneficiary Coinsurance
Waiver
Available data and scholarly research suggest that there is a
significant relationship between socioeconomic status and prevalence of
CKD. For example, evidence suggests that CKD is more prevalent among
individuals with lower income.\276\ In addition, at least one study
suggests that as an individual's CKD severity increases (for example,
from CKD III to CKD IV), the likelihood of the CKD patient falling into
poverty increases.\277\ In light of this research, we stated in the CY
2022 ESRD PPS proposed rule that CMS believes that cost represents a
meaningful barrier for beneficiaries in accessing kidney disease
patient education services (86 FR 36393). While we also stated that
there does not appear to be any research that explicitly investigates
to what extent cost barriers preclude access to kidney disease patient
education services, the identified relationship between household
income or poverty status and prevalence of CKD suggests that cost is an
important factor when considering a beneficiary's access to kidney
disease patient education services.
---------------------------------------------------------------------------
\276\ Table 1.2 in United States Renal Data System, 2020 Annual
Report, Chronic Kidney Disease: Chapter 1, CKD in the General
Population, available at https://adr.usrds.org/2020/chronic-kidney-disease/1-ckd-in-the-general-population (indicating that the
prevalence of CKD in those above the poverty line is 14.4 percent
while the prevalence of CKD in those below the poverty line is 17.4
percent. See also McClellan, W.M., et al., Poverty and Racial
Disparities in Kidney Disease: The REGARDS Study, Am. J Nephrol,
2010, Volume 32, Issue 1, pages 38-46, available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2914392/ (providing data
suggesting that lower household income is associated with higher
prevalence of CKD).
\277\ Morton, R.L, et al., Impact of CKD on Household Income,
Kidney International Reports, Volume 3, Issue 3, 2018, pages 610-
618, available at https://www.sciencedirect.com/science/article/pii/S2468024917304795?via%3Dihub.
---------------------------------------------------------------------------
Under section 1833 of the Act, the amounts paid by Medicare for
kidney disease patient education services are equal to 80 percent of
the applicable payment amount; beneficiaries are thus subject to a 20
percent coinsurance for kidney disease patient education services.
Kidney disease patient education services can be billed under G0420 for
an individual session, or under G0421 for a group session. The current
national unadjusted payment for G0420 under the CY 2021 Physician Fee
Schedule is $114.10; for G0421, it is $27.22. As such, a beneficiary
would be required to pay $22.82 for an individual session of kidney
disease patient education services or $5.44 for kidney disease patient
education services furnished to a group, which may be higher or lower
depending on certain factors, such as the geographic location of the
beneficiary. Medicare covers up to six kidney disease patient education
services for an individual beneficiary during that beneficiary's
lifetime, meaning that a beneficiary may be required to pay $136.92 if
six individual kidney disease patient education services are clinically
appropriate for that beneficiary, or $32.64 if six group kidney disease
patient education services are clinically appropriate for that
beneficiary.
In the CY 2022 ESRD PPS proposed rule, we stated that we believe
that it is necessary, for purposes of testing the ETC Model, to permit
ETC Participants the flexibility to reduce or waive the 20 percent
coinsurance requirement for kidney disease patient education services.
We also stated that we believe this patient incentive would increase
the provision of kidney disease patient education services to
beneficiaries, given the relationship between income or poverty and
prevalence of CKD, and the relationship between kidney disease patient
education services and progression of CKD. In the CY 2022 ESRD PPS
proposed rule, we stated that CMS had determined that, if this proposal
were finalized, this CMS-sponsored patient incentive would advance the
ETC Model's goal of increasing access to kidney disease patient
education services, and to making beneficiaries more aware of their
choices in preparing for kidney treatment, including the choice of
receiving home dialysis, self-dialysis, or nocturnal in-center
dialysis, rather than traditional in-center dialysis.
Accordingly, we proposed at Sec. 512.397(c) to permit, beginning
January 1, 2022, ETC Participants to reduce or waive the beneficiary
coinsurance obligations for kidney disease patient education services
furnished to an eligible beneficiary who does not have secondary
insurance on the date the kidney disease patient education services are
furnished if
[[Page 61989]]
certain conditions are satisfied. We refer to this patient incentive
herein as the ``kidney disease patient education services coinsurance
patient incentive.'' We stated in the CY 2022 ESRD PPS proposed rule
that we expected to make a determination that the anti-kickback statute
safe harbor for CMS-sponsored model patient incentives (42 CFR
1001.952(ii)(2)) would be available to protect cost-sharing support
that is furnished in compliance with ETC Model requirements with
respect to kidney disease patient education services. We noted that if
CMS were to make such a determination, the safe harbor for CMS-
sponsored model patient incentives would protect an ETC Participant, as
that term is defined at Sec. 512.310, who offers a reduction or waiver
of coinsurance for kidney disease patient education services to
beneficiaries who are eligible to receive kidney disease patient
education services, including those eligible pursuant to the waiver
described in Sec. 512.397(b)(2), and who do not have secondary
insurance on the date that the kidney disease patient education
services were furnished.
We proposed that the kidney disease patient education services
coinsurance patient incentive would be available to the ETC Participant
for kidney disease patient education services furnished by an
individual or entity who is qualified staff. We stated that this
proposal would align with the individuals who may furnish kidney
disease patient education services under Sec. 512.397(b) of this
subpart, which are we replacing in its entirety to standardize certain
terms and add clarity, as described in greater detail in the CY 2022
ESRD PPS proposed rule and in section VIII.b.3 of this final rule.
We proposed to limit the kidney disease patient education services
coinsurance patient incentive to beneficiaries who do not have
secondary insurance, because secondary insurance typically provides
cost-sharing support of the type CMS proposed in the CY 2022 ESRD PPS
proposed rule. In the CY 2022 ESRD PPS proposed rule, we stated that we
also believe that limiting the kidney disease patient education
services coinsurance patient incentive to beneficiaries without
secondary insurance would better ensure that only beneficiaries who
need cost-sharing support would receive it, rather than permitting
cost-sharing support for all beneficiaries for whom kidney disease
patient education services are clinically appropriate.
We also proposed that the kidney disease patient education services
coinsurance patient incentive would be available only for kidney
disease patient education services that were furnished in compliance
with the applicable provisions of Sec. 410.48 of our regulations,
which includes a requirement that a beneficiary obtain a referral from
the physician (as defined in section 1861(r)(1) of the Act) managing
the beneficiary's kidney condition in order for the beneficiary to be
eligible to receive kidney disease patient education services. We
proposed to include this requirement because we waived some but not all
provisions of Sec. 410.48, and because, as stated in the CY 2022 ESRD
PPS proposed rule, we believe that the requirement that the beneficiary
receive a referral from their physician is important for ensuring that
kidney disease patient education services are furnished only to
beneficiaries for whom it is clinically appropriate.
We proposed that such coinsurance support would be permitted for
the kidney disease patient education services offered either in-person
or via telehealth, and that it would be permitted for both individual
sessions and group sessions. However, in the CY 2022 ESRD PPS proposed
rule we considered limiting the coinsurance support to kidney disease
patient education services that are furnished to an individual
beneficiary, rather than allowing the coinsurance support for such
services furnished either individually or to a group. We noted that the
cost burden on beneficiaries who receive kidney disease patient
education services in a group setting is much lower than it is on
beneficiaries who receive kidney disease patient education services
individually. However, as we stated in the CY 2022 ESRD PPS proposed
rule, we are concerned that any cost barrier to kidney disease patient
education services, even if low, represents a meaningful barrier to
some beneficiaries who would otherwise elect to receive such services.
We solicited comments on this issue.
We proposed that an ETC Participant that offers coinsurance support
for kidney disease patient education services would be required to
maintain records of certain information. Specifically, we proposed that
an ETC Participant that offers the kidney disease patient education
services coinsurance patient incentive would be required to maintain
records of the following: The identity of the qualified staff who
furnished the kidney disease patient education services for which the
coinsurance was reduced or waived; the date the kidney disease patient
education services coinsurance patient incentive was provided; the
identity of the beneficiary to whom the kidney disease patient
education services coinsurance patient incentive was provided; evidence
that the beneficiary who received the kidney disease patient education
services coinsurance patient incentive was eligible to receive the
kidney disease patient education services and did not have secondary
insurance; and the amount of the kidney disease patient education
services coinsurance patient incentive reduced or waived by the ETC
Participant. We proposed to require an ETC Participant that offers this
kidney disease patient education services coinsurance patient incentive
to maintain and provide the government with access to these records in
accordance with 42 CFR 512.135(b) and (c).
We further proposed in proposed 42 CFR 512.160(b)(6)(ii) that, for
the ETC Model only, CMS could suspend or terminate the ability of an
ETC Participant to offer the kidney disease patient education services
coinsurance patient incentive if CMS determined that any grounds for
remedial action exist pursuant to Sec. 512.160(a).
We stated in the CY 2022 ESRD PPS proposed rule that, in lieu of a
waiver of certain fraud and abuse provisions in sections 1128A and
1128B of the Act, CMS may determine that the anti-kickback statute safe
harbor CMS-sponsored model patient incentives (42 CFR 1001.952(ii)(2))
is available to protect the reduction or waiver of coinsurance for
kidney disease patient education services permitted under the ETC Model
final rule, if issued. We stated in the CY 2022 ESRD PPS proposed rule
that we expect to determine that the CMS-sponsored model safe harbor
will be available to protect the reduction or waiver of coinsurance
that satisfies the requirements of such safe harbor and the provisions
of proposed Sec. 512.397(c)(1). We proposed that, if we make this
determination, we would specify in regulation text at Sec.
512.397(c)(4) that the safe harbor is available.
We also considered, in the CY 2022 ESRD PPS proposed rule,
prohibiting on an ESRD facility or other entity from providing
qualified staff or the ETC Participant with financial support to enable
such qualified staff or ETC Participant to provide the kidney disease
patient education services coinsurance patient incentive. As we stated
in the CY 2022 ESRD PPS proposed rule, CMS is concerned that permitting
such financial support may encourage unlawful or abusive
[[Page 61990]]
arrangements designed to induce or reward referrals for Federal health
care program business. We solicited comments on whether this
prohibition is necessary to safeguard against fraud and abuse or if
other laws effectively provide sufficient protection.
We also considered waiving Medicare payment requirements such that
CMS would pay the full amount of the kidney disease patient education
services furnished to a beneficiary who does not have secondary
insurance, rather than just 80 percent of the amount. Under section
1115A(d)(1) of the Act, the Secretary may waive such requirements of
titles XI and XVIII and of sections 1902(a)(1), 1902(a)(13),
1903(m)(2)(A)(iii) of the Act, and certain provisions of section 1934
of the Act as may be necessary solely for purposes of carrying out
section 1115A of the Act respect to testing models described in section
1115A(b) of the Act. As we stated in the CY 2022 ESRD PPS proposed
rule, this is the authority under which we would waive such Medicare
payment requirements. We stated that, under such a policy, Medicare
would pay 100 percent of the payment amount for kidney disease patient
education services furnished by Managing Clinicians who are ETC
Participants to beneficiaries who do not have secondary insurance, and
such beneficiaries would have no cost-sharing obligation for that
benefit. However, in the CY 2022 ESRD PPS proposed rule, we determined
that this policy would likely represent too large an impact to the ETC
Model's savings estimates, and thus would potentially jeopardize our
ability to continue to test the ETC Model, if such a policy were
finalized.
Given the proposed policies related to programmatic waivers and
additional flexibilities available under the ETC Model, we proposed to
modify the title of Sec. 512.397 from ``ETC Model Medicare program
waivers'' to ``ETC Model Medicare program waivers and additional
flexibilities.'' We proposed this change so that the section title
would more accurately reflect the contents of the section if our
proposed kidney disease patient education services coinsurance patient
incentive is finalized.
We solicited public comments on our proposal to allow qualified
staff, as we proposed to define the term under Sec. 512.310, to offer
coinsurance support for kidney disease patient education services to
beneficiaries who are eligible for such services, including those
eligible under Sec. 512.397(b)(2), and who do not have secondary
insurance on the date the kidney disease patient education services are
furnished. We also solicited comment on our proposal to require the ETC
Participant to maintain and provide the government with access to
records regarding the use of the kidney disease patient education
services coinsurance patient incentive.
The following is a summary of the comments received on our proposal
to allow qualified staff to offer coinsurance support for kidney
disease patient education services to beneficiaries who do not have
secondary insurance and our responses.
Comment: Many commenters expressed that cost is a barrier for at
least some beneficiaries in accessing kidney disease patient education
services.
We also received many comments expressing support for our proposal
to allow an ETC Participant to reduce or waive a beneficiary's
coinsurance for kidney disease patient education services furnished by
qualified staff, in accordance with Sec. 512.397(b)(1), under the ETC
Model. One commenter expressed support for the proposal noting that
many kidney patients have limited resources, and may choose to forgo
education to dedicate such resources to obtaining medications and
medical care. Another commenter similarly expressed support because
they believe the proposed coinsurance patient incentive would increase
access to kidney disease patient education services by removing cost
barriers. Yet another commenter expressed support for the proposal,
noting that coinsurance payments can burden beneficiaries, particularly
those in the most underserved communities. The same commenter also
expressed a belief that the proposal will advance the ETC Model's goal
of increasing access to kidney disease patient education services, and
of making beneficiaries more aware of their choices in preparing for
kidney treatment, including the choice to receive home dialysis, self-
dialysis, or nocturnal in-center dialysis, rather than traditional in-
center dialysis.
Response: We agree with the reasons the commenters provided for
their support, which is why we proposed and are now finalizing a policy
allowing an ETC Participant to reduce or waive a beneficiary's
coinsurance for kidney disease patient education services furnished by
qualified staff, in accordance with Sec. 512.397(b)(1), under the ETC
Model.
Comment: A few commenters expressed opposition to our proposal to
limit the proposed coinsurance patient incentive to beneficiaries
without secondary insurance. One such commenter expressed that offering
the coinsurance patient incentive to more beneficiaries would improve
uptake of kidney disease patient education services, which is important
given both the historically low percentage of eligible beneficiaries
who have been provided kidney disease patient education services, and
the important of pre-dialysis education to help beneficiaries make
informed treatment decisions. Another commenter stated that, unless CMS
can guarantee that Medicaid would cover the coinsurance amount for
dually-eligible beneficiaries, the coinsurance patient incentive should
be broadened to cover dual-eligible and LIS-eligible beneficiaries,
reasoning that such a proposal would ensure these groups' access to
appropriate education.
Response: We proposed to restrict the coinsurance patient incentive
to only those beneficiaries without secondary insurance because
secondary insurance typically covers this type of cost sharing. That
is, providing cost sharing support would be redundant for beneficiaries
with secondary coverage. Because a beneficiary's secondary insurance
will likely cover cost sharing for kidney disease patient education
services, we believe our proposed policy would generally succeed in
increasing access to beneficiaries by removing cost barriers for those
who are obligated to pay cost sharing because it is not covered by
their insurance. However, the commenter who expressed concern that
Medicaid may not necessarily provide cost-sharing support for kidney
disease patient education services raises an important point.
Medicaid will not necessarily cover the coinsurance amount for
dual-eligible beneficiaries' kidney disease patient education services,
because not all Medicare Savings Programs cover Medicare coinsurance
and Medicaid coverage of cost sharing generally varies by State. In
some states, Medicaid would cover the cost sharing for kidney disease
patient education services, while in other states it would not. In
light of this State variation, and to further our stated goal of
providing cost sharing support to beneficiaries who are obligated to
pay cost sharing because it is not covered by their insurance, we are
finalizing a policy that restricts the coinsurance patient incentive to
only those beneficiaries without secondary insurance that provides cost
sharing support for kidney disease patient education services.
Comment: Two commenters suggested that CMS include both individual
and group kidney disease patient education services sessions in the
coinsurance patient incentive. One such commenter
[[Page 61991]]
reasoned that, while group kidney disease patient education services
sessions have minimal costs, even nominal costs can quickly add up for
beneficiaries with a chronic condition, especially for beneficiaries
with kidney disease, who often see multiple providers and fill multiple
prescriptions each month.
Response: We agree with the commenters that, even if the
coinsurance amount for group kidney disease patient education services
sessions is minimal, these costs can indeed present meaningful barriers
to some beneficiaries, including the beneficiaries with multiple
chronic conditions and beneficiaries with kidney disease. In light of
these comments, we are finalizing our proposed kidney disease patient
education services coinsurance patient incentive policy to permit cost
sharing support for individual or group kidney disease patient
education services sessions alike.
Comment: A few commenters requested clarification relating to our
statement in the CY 2022 ESRD PPS proposed rule that we are considering
prohibiting an ESRD facility or other entity from providing the ETC
Participant with qualified staff or financial support that the ETC
Participant would use in furnishing kidney disease patient education
services and the proposed cost sharing support. Two such commenters
requested clarification specifically on whether ESRD facilities or
other entities could enter into arrangements with ETC Participants to
provide certain services at fair market value, and proposed that CMS
permit such arrangements so long as the services were indeed provided
at fair market value. These commenters reasoned that ESRD facilities
sometimes provide physician practices with clinical staff under a
personal services or other similar arrangement that complies with the
Anti-Kickback Statute, the physician self-referral law, and other
requirements. The commenters noted that such arrangements often occur
when the dialysis facility maintains staff with pertinent expertise,
such as expertise with educating patients about chronic kidney disease.
These comments expressed a belief that a dialysis facility providing
staffing at fair market value would not constitute providing
``financial support'' as CMS expressed concern about in the CY 2022
ESRD PPS proposed rule, so long as the arrangement complies with all
applicable fraud and abuse requirements.
Another commenter asserted that the CY 2022 ESRD PPS proposed rule
did not clarify whether CMS is considering prohibiting ESRD facilities
from providing qualified staff to ETC Participants without
compensation, or whether CMS is considering prohibiting dialysis
facilities from entering into a payment contract with ETC Participants
to provide such services. The commenter expressed the belief that
providing staff without compensation would be inappropriate and
inconsistent with current fraud and abuse laws, but suggested that a
prohibition on contractual payment arrangements between dialysis
facilities and ETC Participants for the purpose of providing qualified
staff to deliver kidney disease patient education services runs counter
to CMS's goals in proposing the kidney disease patient education
services coinsurance patient incentive. The commenter expressed the
belief that current fraud and abuse rules, combined with the
requirements CMS currently imposes relating to kidney disease patient
education services, offer sufficient protection against potentially
problematic arrangements.
Response: We thank the commenters for their feedback and
information. We understand that ESRD facilities and other entities
sometimes enter into arrangements with clinicians or other parties to
provide certain services. We recognize that some ETC Participants may
wish to furnish kidney disease patient education services using staff
or other resources furnished under a contractual arrangement with an
ESRD facility or other entity. We are concerned, however, that even if
such arrangements are structured to comply with all applicable fraud
and abuse laws, they could nevertheless result in program abuse.
Specifically, such arrangements could operate to circumvent the
statutory prohibition against dialysis facilities furnishing kidney
disease patient education services. For example, the staff or resources
furnished to the ETC Participant from an ESRD facility or related
entity could be used to market a specific ESRD facility or chain of
ESRD facilities to beneficiaries who may need to choose a dialysis
facility in the future.
We do not believe ETC Participants should obtain safe harbor
protection for the reduction or waiver of cost-sharing on kidney
disease patient education services if such services were furnished by
personnel leased from an ESRD facility or related entity. Accordingly,
we are adding a provision at Sec. 512.397(c)(1)(ii) to require that
the qualified staff furnishing the kidney disease patient education
services for which an ETC Participant reduces or waives cost sharing
must not be leased from or otherwise provided by an ESRD facility or
related entity. For purposes of this provision, a related entity would
include any entity that is directly or indirectly owned in whole or in
part by an ESRD facility. We believe this aligns with the statutory
intent to prohibit ESRD facilities from furnishing kidney disease
patient education services.
Comment: Two commenters advocated that CMS should prohibit ESRD
facilities from effectively making up the financial difference an ETC
Participant would experience by waiving or reducing a beneficiary's
coinsurance amount for kidney disease patient education services. One
commenter recommended that CMS not finalize a prohibition on an ESRD
facility or other entity from providing financial support to enable ETC
Participants to reduce or eliminate cost sharing for kidney disease
patient education services. This commenter believed that such financial
support arrangements should be permitted as long as they comply with
all applicable law.
Response: We agree that ESRD facilities should not be permitted to
pay ETC Participants in an effort to offset the financial impact of the
ETC Participant's lost cost-sharing revenues. We question whether the
receipt of any such remuneration could comply with applicable fraud and
abuse laws. Such arrangements, including those in which an entity other
than an ESRD facility reimburses the ETC Participant for lost cost-
sharing revenues, could result in inappropriate referrals of Federal
health care program business, patient steering, corruption of medical
judgment, and other abuses. Indeed, the receipt of any such
remuneration could implicate and potentially violate the Federal Anti-
Kickback statute (42 U.S.C. 1320a-7b(b)), and by extension the False
Claims Act (31 U.S.C. 3729-3733 and 42 U.S.C. 1320a-7b(g)).
Moreover, we do not believe that permitting such arrangements is
necessary to test the model. We are testing a narrowly-tailored
exception to the usual prohibition against the reduction or waiver of
beneficiary cost-sharing obligations. Permitting any individual or
entity other than the ETC Participant to finance cost-sharing support
is beyond the scope of the policy we are testing. Accordingly, we are
persuaded that safe harbor protection for cost-sharing support
furnished by ETC Participants to beneficiaries for kidney disease
patient education services should be contingent
[[Page 61992]]
on the ETC Participant bearing the full cost of the copayment reduction
or waiver. That is, the copayment reduction or waiver may not be
financed by a third party, including but not limited to an ESRD
facility or related entity. Therefore, we are finalizing at Sec.
512.397(c)(1)(v) a new safeguard that requires the ETC Participant to
bear the full cost of any cost-sharing reduction or waiver for kidney
disease patient education services.
We note that we did not propose and are not finalizing any
provision that would offer safe harbor protection for any arrangement
between an ETC Participant and an ESRD facility or other entity. Under
this final rule, the only arrangements that may qualify for protection
under the safe harbor for CMS-sponsored model patient incentives are
arrangements between the ETC Participant and the beneficiary for whom
the ETC Participant reduced or waived the kidney disease patient
education services coinsurance amount, provided that the arrangements
comply with the requirements of the safe harbor as set forth at 42 CFR
1001.952(ii)(2) and the provisions of 512.397(c)(1).
Comment: Several commenters, including some commenters who
expressed support for CMS's proposed coinsurance patient incentive
policy, suggested that CMS instead waive Medicare payment requirements
such that CMS would pay the full amount of the kidney disease patient
education services furnished to a beneficiary who does not have
secondary insurance, rather than just 80 percent of the amount. One
such commenter expressed concern that ETC Participants will not have
the financial resources to forgo all or a portion of a beneficiary's
coinsurance and will therefore be unable to use the flexibility
afforded under this patient incentive to reduce the financial burden of
beneficiaries. Two such commenters expressed concern that while waiving
coinsurance would serve to increase beneficiary use of kidney disease
patient education services, ETC Participants and their qualified staff
may lack willingness to provide kidney disease patient education
services at a rate that, according to the commenters, would not
adequately cover their costs, and that this would diminish the
availability of kidney disease education to beneficiaries. Further,
these commenters suggested that CMS providing the full payment amount
for kidney disease patient education services would alleviate CMS's
stated concern that the proposed coinsurance patient incentive could
incentivize improper financial assistance from ESRD facilities and
other entities. These commenters suggested that, to counterbalance
CMS's stated concern that such payment waivers would result in
additional Medicare costs under the ETC Model, CMS could exclude the 20
percent coinsurance amounts that CMS would cover under this alternative
proposal from ETC cost calculations during the ETC Model period to
determine whether this limited additional investment results in
improved beneficiary quality of care and an overall cost of care
reduction. Two commenters stated that CMS should pay the full amount of
the kidney disease patient education services furnished to a
beneficiary who does not have secondary insurance because, according to
the commenters, the requirements needed to qualify for the coinsurance
patient incentive are overly onerous and may present an additional
barrier to access to kidney disease patient education services.
Response: We considered this alternative policy in the CY 2022 ESRD
PPS proposed rule, but concluded that it would represent too large an
impact to the ETC Model's potential savings (86 FR 36394-36395). We
believe that the policy we are finalizing, wherein an ETC Participant
may reduce or waive cost sharing for kidney disease patient education
services, strikes the appropriate balance in providing a new tool for
ETC Participants to engage beneficiaries while also helping support the
success of the Model. While a policy under which Medicare pays the full
amount of the kidney disease patient education services amount, rather
than 80 percent of the amount, may result in the highest number of
beneficiaries receiving kidney disease patient education services, we
believe that the kidney disease patient education services coinsurance
patient incentive will result in more beneficiaries receiving kidney
disease patient education services compared to the status quo, and will
do so without detracting from the savings estimates of the ETC Model.
Moreover, we disagree with the commenters who suggested that CMS
could exclude the 20 percent coinsurance payment paid by CMS from the
Model's cost calculations. We cannot exclude the 20 percent coinsurance
payment paid by CMS from the Model's cost calculations. If we
implemented the payment waiver as recommended by the commenters, CMS
would need to account for these costs when determining the Model's
overall impact on Medicare program expenditures. However, CMS may
consider implementing a payment waiver like the alternative we
considered in the CY 2022 ESRD PPS proposed rule in a future model or
initiative to determine whether such an investment results in improved
beneficiary quality of care and an overall cost of care reduction.
Finally, we understand the commenters' concern that the proposed
kidney disease patient education services coinsurance patient incentive
imposes an administrative burden on ETC Participants who choose to
furnish the patient incentive, but we believe that the benefits of
reducing cost barriers to kidney disease patient education services
through furnishing the kidney disease patient education services
coinsurance patient incentive will outweigh this administrative burden.
Commenters have expressed that beneficiaries who undergo kidney disease
education are more likely to choose home dialysis, and to the extent
this is the case, an ETC Participant that furnishes the coinsurance
patient incentive might recover the direct and indirect
(administrative) costs associated with cost-sharing waivers for such
services if the ETC Participant qualifies for a positive PPA. In
addition, while we agree that the alternative policy considered in the
CY 2022 ESRD PPS proposed rule would alleviate the fraud and abuse
concerns we articulated in that rule, we have concluded that existing
law and the safeguards finalized in this rule provide sufficient
protection against such fraud and abuse.
Final Rule Action: After considering public comments, we are
finalizing with modification our proposal to add Sec. 512.397(c)
regarding an ETC Participant's ability to reduce or waive the 20
percent coinsurance obligation for kidney disease patient education
services. Specifically, we are adding Sec. 512.390(c)(1), which
permits ETC Participants to reduce or waive beneficiary cost sharing
for kidney disease patient education services furnished on or after
January 1, 2022 if the following conditions are satisfied: (i) The
individual or entity that furnished the kidney disease patient
education services is qualified staff; (ii) the qualified staff are not
leased from or otherwise provided by an ESRD facility or related
entity; (iii) the kidney disease patient education services were
furnished to a beneficiary described in Sec. 410.48(b) or Sec.
512.397(b)(2) who did not have secondary insurance that provides cost-
sharing support for kidney disease patient education services on the
date the services were furnished; (iv) the kidney disease patient
education services were furnished in compliance with the applicable
provisions of Sec. 410.48 and Sec. 512.397(b); and (v) the
[[Page 61993]]
ETC Participant bears the full cost of the waiver or reduction of the
20 percent coinsurance requirement under section 1833 of the Act and
such reduction or waiver is not financed by a third party, including
but not limited to an ESRD facility or related entity.
Under new Sec. 512.397(c)(2), we are finalizing with modification
our proposed requirements regarding documentation retention and
government access to records regarding the reduction or waiver of
beneficiary cost-sharing obligations for kidney disease patient
education services furnished under the ETC model. Specifically, we are
modifying Sec. 512.397(c)(2)(iii) to read, ``Evidence that the
beneficiary who received the kidney disease patient education services
coinsurance waiver was eligible to receive the kidney disease patient
education services under the ETC Model and did not have secondary
insurance that provides cost-sharing support for kidney disease patient
education services on the date the services were furnished.''
Lastly, we are finalizing without change our proposal to include at
Sec. 512.397(c)(3) a provision stating that the Federal anti-kickback
statute safe harbor for CMS-sponsored model patient incentives is
available to protect kidney disease patient education coinsurance
waivers that satisfy the requirements of such safe harbor and the
conditions set forth in Sec. 512.397(c)(1).
(3) Revising Language Providing Other ETC Model Medicare Program
Waivers
We proposed to revise Sec. 512.397(b)(1) through (4) in their
entirety to accomplish a few goals (86 FR 36395). First, we proposed to
make conforming changes throughout Sec. 512.397(b) to the manner in
which CMS discusses kidney disease patient education services.
Currently, Sec. 512.397(b) includes references to ``KDE services,''
``the KDE benefit,'' ``KDE sessions,'' and, simply, ``KDE.'' CMS would
change all of these references to ``kidney disease patient education
services'' for clarity and to conform with the term used elsewhere in
our regulations.
In addition, we proposed to make conforming changes through Sec.
512.397(b) to the manner in which CMS discusses the individuals who are
permitted to furnish kidney disease patient education services under
the ETC model programmatic waivers. Specifically, as discussed
previously, CMS proposed to add definitions for ``clinical staff'' and
``qualified staff'' in the CY 2022 ESRD PPS proposed rule, as CMS
believes clarifying how CMS discusses these individuals in Sec.
512.397(b) will enhance clarity. Finally, we proposed to remove the
``clinic/group practice'' from the list of individuals or entities that
are permitted to furnished kidney disease patient education services
under the ETC Model programmatic waivers, and to remove the waiver of
42 CFR 410.48(c)(2)(i) from Sec. 512.397(b)(1) of this part. We stated
in the CY 2022 ESRD PPS proposed rule that we believe that its
inclusion of clinic/group practices previously was in error, and we
noted that a clinic/group practice is not able to furnish or bill for
kidney disease patient education services under existing law and that
CMS did not intend for the waiver described in Sec. 512.397(b) to
permit anyone other than a clinician to furnish kidney disease patient
education services. Because the waiver of the requirements under 42 CFR
410.48(c)(2)(i) was implemented only to broaden the ``qualified
person'' that could furnish kidney disease patient education services
pursuant to Sec. 512.397(b)(1) to include a clinic/group practice, we
proposed to remove references to 42 CFR 410.48(c)(2)(i) in Sec.
512.397(b)(1) of this part.
We solicited public comments on these proposed changes to Sec.
512.397(b) to make conforming and clarifying changes to the manner in
which CMS discusses kidney disease patient education services and the
individuals who are permitted to furnish kidney disease patient
education services under the ETC Model waivers described in Sec.
512.397(b), and to our proposed removal of ``clinic/group practice''
from the list of individuals or entities who may, under the ETC Model
waivers described in Sec. 512.397(b), furnish kidney disease patient
education services.
CMS did not receive any comments regarding the proposed conforming
and clarifying changes to Sec. 512.397(b) of our regulations. However,
we did receive some comments suggesting that CMS make additional
changes to the kidney disease patient education services waivers in
Sec. 512.397(b). The following is a summary of those comments and our
responses.
Comment: We received a few comments asking CMS to further increase
the scope of the kidney disease patient education services waivers,
specifically in order to allow additional clinicians and healthcare
sites to furnish kidney disease patient education services, including
ESRD facilities, home dialysis nurses, and Certified Nephrology Nurses
(CNNs).
Response: While we understand the commenters' interest in
increasing even further the types of clinicians and entities that may
furnish kidney disease patient education services under the ETC Model,
we believe that our current policy provides sufficient flexibility to
test the Model. Accordingly, we are not updating Sec. 512.397(b) at
this time to add additional types of clinicians and entities that may
furnish kidney disease patient education services under the Model.
Comment: We received several comments urging CMS not to grant a
waiver to allow ESRD facilities to be able to bill for kidney disease
patient education services, due to concerns about potential quality of
education and the entrenchment of the existing dialysis market
structure.
Response: We do not believe that a waiver of the requirement
preventing ESRD facilities from billing for kidney disease patient
education services is necessary for testing the model. ESRD facilities
are already required to provide information to beneficiaries about
their treatment modality options in the ESRD facility conditions for
coverage at Sec. 494.70(a)(7) and to develop and implement a plan of
care that addresses the patient's modality of care, at Sec.
494.90(a)(7), and the costs for doing so are already included in the
payment for the ESRD PPS bundled payment. Accordingly, we are not
modifying Sec. 512.397(b) to permit ESRD facilities to furnish kidney
disease patient education services under the Model at this time.
Comment: We received a few comments expressing concern about the
quality of education that beneficiaries receive as part of kidney
disease patient education services and urging that CMS create
accredited curricula to ensure consistent education.
Response: We appreciate this feedback and are monitoring
utilization of kidney disease patient education services to see
potential effects on care. We believe that the required content for
kidney disease patient education services, as set forth in 42 CFR
410.48(d), shows the minimum of what must be covered but urge
interested stakeholders to consider creating a curriculum that could be
used by Managing Clinicians and other qualified staff to administer
kidney disease patient education services.
Comment: A few commenters suggested that CMS use its waiver
authority to authorize referrals for kidney disease patient education
services issued by nurse practitioners. Two such commenters also
proposed that CMS use its waiver authority to additionally authorize
physician assistants and clinical nurse specialists
[[Page 61994]]
to issue referrals for kidney disease patient education services.
Response: As required under 42 CFR 410.48(b)(2), Medicare Part B
covers kidney disease patient education services only if the
beneficiary obtains a referral from the physician managing the
beneficiary's kidney condition. We did not consider issuing a waiver to
broaden the categories of clinicians who could issue referrals for
kidney disease patient education services in the CY 2022 ESRD PPS
proposed rule. Moreover, we currently have no evidence to suggest that
the waiver suggested by the commenters would be necessary solely for
purposes of testing the model, as would be required to issue such a
waiver under section 1115A(d)(1) of the Act. In addition, we do not
currently have, and no commenter provided, evidence that broadening the
categories of clinicians who could issue a referral for kidney disease
patient education services would continue to ensure clinical
appropriateness. As such, we will continue to require that the
physician managing the beneficiary's kidney condition refer a
beneficiary for kidney disease patient education services in order for
Medicare to pay for such services as required under 42 CFR
410.48(b)(2). However, we will continue to consider the commenters'
suggestions, and we may consider broadening the categories of
clinicians who may issue a referral for kidney disease patient
education services in future rulemaking.
Final Rule Action: After considering public comments, we are
finalizing our proposal to make conforming and clarifying changes to
our regulation at Sec. 512.397(b), without modification. After
considering public comments, we will not be altering the curriculum for
kidney disease patient education services or allowing any additional
types of Medicare providers or suppliers to furnish and bill kidney
disease patient education services beyond clinical staff and qualified
staff at this time.
C. Requests for Information on Topics Relevant to the ETC Model
1. Peritoneal Dialysis Catheter Placement--Request for Information
(RFI)
Through the CY 2022 ESRD PPS proposed rule (86 FR 36395), we sought
input on how we can test and use Medicare payment policy, under the ETC
Model, to promote placement of PD catheters. Specifically, we sought
feedback on the following questions:
a. What are the key barriers to increased placement of PD
catheters?
b. How can CMS promote placement of PD catheters in a more timely
manner?
c. Should the Innovation Center use its authority to test
alternative payment structures to address the barriers to PD catheter
placement as a part of the ETC Model? If so, why and how?
For the complete discussion of this RFI, see the CY 2022 ESRD PPS
proposed rule, 86 FR 39395 through 39396.
Comments: Commenters expressed general concern that CMS continues
to address barriers to home dialysis one provider type at a time rather
than holistically as an extended series of barriers and decision points
that patients face beginning when they are in earlier stages of kidney
disease.
Most commenters agreed with the main barriers to PD catheter
placement described in the RFI, including the lack of availability of
hospital-based catheter insertion teams to perform PD catheter
placements, lack of appropriate operating room time, and a lack of
training on PD catheter placement for vascular surgeons. But the
commenters suggested additional barriers for CMS's consideration.
First, commenters noted that the COVID-19 pandemic has limited the
ability of health care providers to perform elective procedures on a
timely basis. According to the commenters, hospital operating rooms
effectively halted PD catheter implantation in many hospitals for
several months. Rural facilities were particularly hit because these
communities rely on surgeons who travel in from larger communities and
have limited availability. One commenter noted that incentivizing, or
disincentivizing, providers through payment changes or Innovation
Center models would not fix the core issue for rural dialysis
facilities unless there are enough scheduled patients to make a trip
financially feasible. This commenter suggested that as an alternative,
CMS should consider methods to reduce the prevalence of ESRD in the
long term with a specific focus on rural areas. While this approach may
not create immediate savings, reducing the rate of ESRD would
significantly benefit CMS in the years to come.
A commenter noted that many of the candidates for prospective PD
catheter placement are either not yet eligible for Medicare or are
uninsured, and that there is little incentive for hospitals or other
facility settings to address the lack of availability of vascular
surgeons to perform PD catheter placements, lack of appropriate
operating room time, and a lack of training on PD catheter placement
for vascular surgeons. Another commenter noted a concern regarding the
number of physicians trained to perform PD catheter placement as many
of the more experienced PD catheter physician providers are in the
later stages of their careers and there are not replacement providers
in the pipeline when they retire.
The majority of commenters mentioned the largest barrier for PD
catheter placement is low reimbursement, making it difficult to
encourage new surgeons and other physicians to become adept at PD
catheter implantation. One commenter specifically mentioned that many
of the standalone vascular access centers have closed because of the
reduction of CMS payments to vascular access surgeons. Unlike the
transplant surgeons, who may be incentivized to increase rates of
transplantation through increased revenue resulting directly from
increasing the number of transplants performed, there are no other
direct or indirect incentives for vascular surgeons or vascular access
centers to increase rates of, PD catheter placements that can work
outside the model to address these concerns. Accordingly, commenters
suggested that it would be appropriate to create a separate PD catheter
placement incentive under the ETC Model.
As the ETC Model currently seeks to change payment incentives only
for ETC Participants (ESRD facilities and Managing Clinicians in
Selected Geographic Areas) and, doesn't provide direct incentives for
vascular access surgeons to work with ETC Participants, commenters
strongly urged CMS to thoughtfully consider to what extent ETC
Participants can influence increased rates of PD catheter placement.
Despite the importance of dialysis access procedures to patients,
commenters noted that ETC Participants currently have little influence
on surgeons and hospitals performing dialysis access procedures in a
fee-for-service structure. This factor limits the ability of ETC
Participants to increase home dialysis utilization, which is contingent
on timely and high-quality PD catheter placement. Commenters also urged
CMS to consider establishing an incentive payment of at least $360.62
to surgeons and other access specialists in the ETC Model to achieve
this goal.
Several commenters suggested that a voluntary track or option could
be added to the ETC Model under which ETC Participants would receive a
payment increase per PD placement (of at least an additional $360.62
per PD catheter procedure) to equalize the
[[Page 61995]]
reimbursement between PD catheter insertion and vascular placement
within the Model. A voluntary track would allow participants to opt-in
to further test broader and more comprehensive incentive payments. This
track would allow for comparison of rates of PD catheter placement
within and outside the model, to evaluate whether the payment increase
within the Model increased the rate of PD catheter placement. Others
didn't think the incentive could be tested in the current model because
ETC Participants have no ability to influence the behavior of surgeons
or interventionalists who place PD catheters. However, these commenters
noted they would be supportive of the incentive in another context.
Several commenters suggested that the Innovation Center should
pilot bonus or increased payments for PD catheter placement outside of
the ESRD PPS and MCP. These commenters recommended that the Innovation
Center consider testing a bonus incentive payment for vascular
surgeons, hospitals, and surgical centers that would increase
reimbursement for PD catheter placement commensurate with reimbursement
provided for AV Fistula reimbursement. According to the commenters,
this incentive payment should not be budget neutral to the ESRD PPS or
the MCP, but instead should be viewed in the broader context of
physician, hospital, and outpatient surgical center reimbursement
systems.
Other commenters suggested financial options with less detail. One
commenter suggested that CMS can encourage the placement of PD
catheters by not only maintaining the reimbursement levels for office
based placed catheters but increasing the reimbursement to levels that
are on par with Ambulatory Surgery Center settings. Another commenter
suggested paying PD catheter placement over time--that is, adding
longevity payments so the surgeon gets payments for patients staying on
PD at 90 days and 180 days--to align interests across nephrologists and
PD providers. Another commenter suggested a bonus payment per
diagnostic related group (DRG) of new ESRD dialysis starts in the
hospital who are leaving with a PD catheter, including urgent PD.
Lastly, another commenter suggested that PD catheter placement be
designed as an urgent procedure to be prioritized by the hospital under
emergent procedures.
There were also several comments related to use of Innovation
Center authority. The first such comment suggested that CMS propose
including as ETC Participants those surgeons who bill for dialysis
vascular access procedures including PD catheter placement identified
based on certain CPT codes (for example, 36818, 36819, 36820, 36821,
36825, 36830, 36831, 36832, 36833, 36838, 49324, 49418, 49421).
According to the commenter, including these surgeons in the model would
provide an incentive for the surgeons to partner with other providers
to ensure the timely placement, repair, and revision of vascular
accesses for patients with ESRD. The second such comment had concerns
with RVUs in the PFS and suggested the Innovation Center has authority
to supplement, beyond the PFS, payments to surgeons that increase
access to and availability of procedures that are ``gateways.'' Another
such comment urged the Innovation Center to address PD catheter
placement and consider possible alternate payment structures such as
retroactive payment for successful placement of PD catheters that are
proven to have been successful over time or establishment of a bonus
structure similar to the Kidney Transplant Bonus under the KCC Model;
the commenter also suggested that such innovations should include
pediatric patients. The same commenter also urged CMS to not exclude
pediatric patients from innovative policies to promote PD catheter
placement.
Response: We plan to continue working with other agencies and
stakeholders to coordinate and to inform our decisions regarding the
potential for incorporating peritoneal dialysis into the ETC Model and
any related quality measurement and reporting requirements. While we
stated that we would not be responding to specific comments submitted
in response to this RFI in the CY 2022 ESRD PPS final rule, we will
actively consider all input as we continue testing the ETC Model. Any
updates to specific program requirements related to peritoneal dialysis
and quality measurement and reporting provisions would be addressed
through separate and future notice-and-comment rulemaking, as
necessary.
2. Beneficiary Experience Measure--Request for Information
While a beneficiary experience measure is not currently included in
the ETC Model, in the CY 2022 ESRD PPS proposed rule (86 FR 36396), we
sought comment on the inclusion of a measure to capture the beneficiary
experience of home dialysis care. We invited public comment on any
aspect of a patient experience measure. We noted that questions to
consider include the following:
a. What domains of a patient experience of care with home dialysis
would be the most useful to assess and why?
b. Would you prefer the measure to be newly developed or an update
to an existing measure? If an update, which existing measure should be
updated?
c. How would a patient experience measure be best used to further
the purpose of the ETC Model?
d. How should CMS use a patient experience measure to assess the
quality of care of beneficiaries?
e. How should CMS use a patient experience measure to incentivize
improved quality of care in the ETC Model and/or for other CMS
programs?
CMS also considered publishing the quality outcomes for the ETC
Model. We invited public comment on any aspect of reporting quality
data, and specifically sought input on the following:
f. What is the frequency with which CMS should disseminate the
results?
g. What should be the unit of analysis for the reporting data?
For the complete discussion of this RFI, see the CY 2022 ESRD PPS
proposed rule, 86 FR 39396.
Comments: Commenters were appreciative that CMS solicited feedback
and there was overwhelming support for inclusion of a measure assessing
beneficiary experience on home dialysis in the ETC Model. In general,
the commenters thought the inclusion of a measure to assess beneficiary
perceptions of the care they receive would be useful to inform changes
that can improve the patient's health and well-being. Commenters
concurred with CMS that the current ICH CAHPS is not sufficient to
capture the beneficiary experience of home dialysis patients and
strongly encouraged CMS to work with the kidney community to develop a
useful measure that is endorsed by the National Quality Forum (NQF).
A few commenters continued to recommend that CMS continue to
develop and improve the ICH CAHPS, with a particular focus on adding a
home dialysis survey to allow the patient experience to be compared
across settings.
However, more commenters recommended that the agency not update an
existing measure, such as ICH CAHPS or the Patient Activation Measure
(PAM), and instead develop an entirely new instrument and include
questions that are most meaningful to patients. A commenter noted that
measuring the patient experience of dialysis in a home setting includes
components of in-center dialysis, home
[[Page 61996]]
health, and home medical equipment, in addition to topics that are
unique to this care setting and patient population. No existing survey
touches on all aspects of this distinctive experience. Commenters asked
CMS to consider including topics specific to dialysis care at home,
such as patient training on equipment, supplies, and safety, and
communication with and access to the patient's care team. According to
commenters, CMS could convene a Technical Expert Panel (TEP) to develop
and test a tool to measure the patient voice in their treatment with
home dialysis that would include satisfaction, patient activation,
quality of life and economic impact of the treatment at home.
Several commenters commented there are already private-sector
efforts to develop a survey tool to measure home dialysis patient
experience. Commenters encouraged CMS to work closely with these
efforts, and to actively support the psychometric testing and
validation necessary to ensure that there is a valid and reliable
instrument that can be utilized broadly across providers in assessing
the experience of home dialysis patients. Commenters specifically
mentioned that any Innovation Center effort should complement and not
replicate potential efforts to leverage the Home Dialysis Care
Experience (Home-DCE) instrument developed and initially tested by the
University of Washington. Commenters further expressed hope that this
measure will eventually be tested more broadly and be submitted to NQF
for endorsement and use in the CMS ESRD QIP.
Several commenters mentioned that the survey response rate for ICH
CAHPS has declined significantly in recent years. Therefore, the
commenters recommended that any patient experience measure CMS uses
should impose minimal burden on patients and providers. In addition,
commenters noted that there is a critical need to develop and implement
a patient experience tool that does not further health inequities.
Lastly, commenters recommended that any home dialysis patient
experience measure CMS implements should be relevant to other CMS
programs, such as the ESRD QIP.
Some commenters suggested that a new measure should address the
following areas: Ease of use of their modality/device; patient/provider
burden in self administration or helping support a loved one; sense of
support from the care team.; sense of respect and value from the care
team; and communication with the care team. One commenter recommended
including three specific questions in a new home dialysis patient
experience measure. The first is ``if the patient previously received
in-center dialysis, does the patient have better quality of life on
home dialysis?'' The second is ``is the patient on home dialysis more
able to engage in activities of daily living (ADLs)?'' The final
question is ``are dialysis facility staff supportive for patients on
home dialysis?''
Some commenters suggested additional mandatory measures in the ETC
Model. Commenters suggested an advance care planning measure
specifically because it is critical for patients and clinicians to
define goals of care. Commenters also suggested measures regarding
palliative care access and utilization because there is mounting
evidence that ESRD patients who have access to or are enrolled in
palliative care programs have better outcomes and have more support for
treatment choices. Lastly, commenters suggested a measure specific to
timely and appropriate referral to hospice to encourage timely and
appropriate referral to hospice. The commenters recommended that this
measure should also provide documentation of include evidence of goals
of care and advance care planning.
With regard to reporting quality outcomes, commenters supported
transparency for beneficiaries attributed to ETC Participants.
Commenters suggested that reporting of quality outcomes occur annually
in order to be consistent with the ESRD QIP timeline. Commenters also
recommended the quality outcomes be available via a website, as well as
posted at each facility in the ETC Participant's aggregation group.
Specifically, because the ETC Model is focused on aggregation at the
HRR level, commenters recommended that the data should be at that
aggregated level rather than at the individual ETC Participant level.
Response: We appreciate all the comments and interest in this topic
and believe that this input is very valuable in the continuing
development of the quality measurement efforts for the ETC Model. We
will continue to take all concerns, comments, and suggestions into
consideration.
VI. Requests for Information
A. Informing Payment Reform Under the ESRD PPS
Over the last several years, CMS, in conjunction with its
contractor, has been conducting research, including holding three
technical expert panels (TEPs), to explore possible improvements to the
ESRD payment model. Additionally, in the CY 2020 ESRD PPS proposed rule
(84 FR 38398 through 38400), CMS invited further comment on a number of
topics, including expanding the outlier policy to include composite
rate drugs, laboratory tests and supplies; reporting the length of each
dialysis session directly on the ESRD claim; patient characteristics
which contribute significantly to the cost of dialysis care; and
improving the quality of facility-level data as reflected in the
Medicare cost report. Stakeholders have asked CMS to explore a refined
case-mix adjustment model for the ESRD PPS, stating that the existing
case mix adjustors may not correlate well with the current cost of
dialysis treatment.
Accordingly, in the CY 2022 ESRD PPS proposed rule (86 FR 36398
through 36409), CMS included a detailed request for information (RFI)
on several topics in order to inform payment reform under the ESRD PPS.
Those topics included six focal areas: (1) The LVPA payment
methodology; (2) calculations for the case-mix adjustment; (3) the
calculation for the outlier payment adjustment; (4) the current
pediatric dialysis payment model; (5) modifications to the pediatric,
the ESRD PPS and the hospital cost report; and (6) payment for home
dialysis for Medicare beneficiaries with acute kidney injury. For each
topic, we provided background information, reviewed current issues and
stakeholder concerns, described suggestions that we received, and
included specific requests for information. Although we are not
presenting that information again in this final rule, we refer readers
to the complete discussion in the CY 2022 ESRD PPS proposed rule, 86 FR
36396 through 36409.
We received numerous public comments in response to our RFI on
payment reform under the ESRD PPS, including from large, small, and
non-profit dialysis organizations; an advocacy organization; a
coalition of dialysis organizations; a large non-profit health system;
an independent commenter; and MedPAC. A high level description of these
comments is included below. We will provide more detailed information
about the commenters' recommendations in a future posting on the CMS
website located at the following link: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ESRDpayment/Educational_Resources.
[[Page 61997]]
1. Calculation of the Low-Volume Payment Adjustment (LVPA)
Of the fourteen responses to the LVPA RFI, all commenters supported
either eliminating or revising the current LVPA or rural adjustment.
One small dialysis organization within a large non-profit health system
responded that they are reliant upon the LVPA and the rural adjustment,
and support both adjustments, albeit with modifications. Several
commenters agreed with MedPAC's suggestion for the low volume and
isolated (LVI) adjustment. Several commenters opposed the census tract
methodology with some stating that it is complex and lacks
transparency.
2. Calculation of the Case-Mix Adjustments
In response to the RFI for current case-mix methodology, several
commenters recommended changes or removal of the case-mix adjusters,
including refinement of the age and weight (BSA and BMI) adjustments
and removal of the comorbidity adjustments, based on declining
frequency of claims containing comorbidities. Commenters expressed
their belief that the comorbidity categories no longer protect
beneficiary access and no longer correlate with increased costs.
Numerous commenters expressed support for the current onset of dialysis
adjustment. Most commenters did not support the collection of time on
machine data on claims or cost reports to allocate composite rate
costs. MedPAC recommended that CMS develop a one-equation regression
model in place of the current two-equation model currently used as the
basis for the ESRD PPS.
3. Calculation of the Outlier Adjustment
In response to the current RFI for the calculation of the outlier
payment adjustment, several commenters recommended changes to the
outlier policy, expressing concerns about the current outlier policy
because it continues to achieve less than the target amount of outlier
payments equal to 1.0 percent of total PPS payments. They suggested
various strategies for addressing the outlier policy, including
reducing the outlier threshold, and excluding TDAPA and TPNIES payments
in the outlier calculation methodology. Several commenters supported
the use of the FDL trend using historical utilization data. Commenters
also recommended the creation of a mechanism to return unpaid outlier
amounts to the ESRD PPS.
4. Calculation of the Pediatric Dialysis Payment Adjustment
In the response to RFI for calculation of pediatric dialysis
payment adjustment, all the commenters expressed that the total costs
of ESRD care delivered to pediatric dialysis patients are not covered
by the current ESRD bundled payment and existing pediatric multipliers.
Several commenters stated that they did not believe that using duration
of treatment is a valid proxy for composite rate costs. Some commenters
recommended that a combination of age, weight and pediatric-specific
comorbidities be used as a proxy for composite rate costs for pediatric
patients. A few commenters recommended streamlining the reporting for
claims and cost reports.
5. Modifying the Pediatric Dialysis, ESRD PPS and Hospital Cost Reports
In the responses to RFI for modifying the pediatric cost report,
commenters supported updating the pediatric cost report to allow
facilities to include costs that cannot be currently reported on the
cost report. Specific recommendations included breakdown of patient age
groups, pediatric-specific dialysis supplies, additional overhead at
hospital outpatient dialysis facilities, psychosocial support,
specialized pharmacy needs and costs unique to the pediatric population
for home dialysis.
Several commenters noted that, despite best efforts to educate
reporting and billing staff, hospitals often triage their cost
reporting obligations, focusing on those that affect payment over those
that do not; they stated that this is particularly true with pediatric
dialysis costs. In order to improve reporting, the commenters
recommended streamlining the reporting required and making it more
consistent with reporting required from the State Medicaid programs or
the private payers.
In the responses to RFI for modifying the ESRD PPS and Hospital
Cost Reports, we received input from ten commenters consisting of
large, small, and non-profit dialysis organizations; an advocacy
organization; a coalition of dialysis organizations; a large non-profit
health system; an independent commenter; and MedPAC. All the commenters
expressed support for making improvements to the cost report that will
streamline reporting and improve accuracy of information collected that
informs payment policy. Additionally, commenters recommended CMS
consider modifying hospital cost report reporting instructions to
ensure complete, consistent, and accurate data reporting as well as
make timely updates to reflect changes to payment policies, including
the TDAPA and TPNIES. These commenters cautioned CMS that prior to
making changes, CMS should weigh the burden of data collection against
the benefit to the system in collecting it.
6. Modifying Site of Services Provided to Medicare Beneficiaries With
Acute Kidney Injury (AKI)
The responses to the RFI for modifying site of service provided to
Medicare beneficiaries included numerous requests to allow payment for
home dialysis for patients with AKI. Of the 16 total comments received
on this topic, 15 discussed modification of the site of service
requirements, with commenters supporting payment for AKI patients
receiving dialysis in home settings, including skilled nursing
facilities. Several commenters favored modification of the site of
service requirements in concert with payment of home dialysis for AKI
patients when deemed appropriate by health care providers.
7. CMS Response to Public Comments
We appreciate the public input and comments on suggested
refinements to the ESRD PPS in response to our RFI in the CY 2022 ESRD
PPS proposed rule. We will take all of these comments into
consideration for possible future rulemaking.
VII. Collection of Information Requirements
A. Legislative Requirement for Solicitation of Comments
Under the Paperwork Reduction Act of 1995, we are required to
provide 60-day notice in the Federal Register and solicit public
comment before a collection of information requirement is submitted to
the Office of Management and Budget (OMB) for review and approval. In
order to fairly evaluate whether an information collection requirement
should be approved by OMB, the Paperwork Reduction Act of 1995 (44
U.S.C. 3506(c)(2)(A)) requires that we solicit comment on the following
issues:
The need for the information collection and its usefulness
in carrying out the proper functions of our agency.
The accuracy of our estimate of the information collection
burden.
The quality, utility, and clarity of the information to be
collected.
Recommendations to minimize the information collection
burden on the affected public, including automated collection
techniques.
We solicited public comment on each of these issues for the
following sections
[[Page 61998]]
of this document that contain information collection requirements
(ICRs):
B. Requirements in Regulation Text
In sections V through V.B of this final rule, we are revising the
regulatory text for the ETC Model. However, the changes do not impose
any new information collection requirements.
C. Additional Information Collection Requirements
This final rule does not impose any new information collection
requirements in the regulation text, as specified above. However, there
are changes in some currently approved information collections. The
following is a discussion of these information collections.
1. ESRD QIP--Wage Estimates (OMB Control Numbers 0938-1289 and 0938-
1340)
To derive wages estimates, we used data from the U.S. Bureau of
Labor Statistics' May 2020 National Occupational Employment and Wage
Estimates. In the CY 2016 ESRD PPS final rule (80 FR 69069), we stated
that it was reasonable to assume that Medical Records and Health
Information Technicians, who are responsible for organizing and
managing health information data, are the individuals tasked with
submitting measure data to CROWNWeb (now EQRS) and NHSN, as well as
compiling and submitting patient records for the purpose of data
validation studies, rather than a Registered Nurse, whose duties are
centered on providing and coordinating care for patients. We stated
that the median hourly wage of a Medical Records and Health Information
Technician is $21.20 per hour.\278\ We also stated that fringe benefit
and overhead are calculated at 100 percent. Therefore, using these
assumptions, we estimated an hourly labor cost of $42.40 as the basis
of the wage estimates for all collections of information calculations
in the ESRD QIP. We adjusted these employee hourly wage estimates by a
factor of 100 percent to reflect current HHS department-wide guidance
on estimating the cost of fringe benefits and overhead. We stated that
these are necessarily rough adjustments, both because fringe benefits
and overhead costs vary significantly from employer to employer and
because methods of estimating these costs vary widely from study to
study. Nonetheless, we stated that there is no practical alternative
and we believe that these are reasonable estimation methods.
---------------------------------------------------------------------------
\278\ https://www.bls.gov/oes/current/oes292098.htm. Accessed on
June 7, 2021.
---------------------------------------------------------------------------
We used this updated wage estimate, along with updated facility and
patient counts to re-estimate the total information collection burden
in the ESRD QIP for PY 2024 that we discussed in the CY 2021 ESRD QIP
final rule (85 FR 71473 through 71474) and to estimate the total
information collection burden in the ESRD QIP for PY 2025. We provided
the re-estimated information collection burden associated with the PY
2024 ESRD QIP and the newly estimated information collection burden
associated with the PY 2025 ESRD QIP in section VII.C.3 of the proposed
rule.
2. Estimated Burden Associated With the Data Validation Requirements
for PY 2024 and PY 2025 (OMB Control Numbers 0938-1289 and 0938-1340)
In the CY 2020 ESRD PPS final rule, we finalized a policy to adopt
the CROWNWeb data validation methodology that we previously adopted for
the PY 2016 ESRD QIP as the methodology we would use to validate
CROWNWeb data for all payment years, beginning with PY 2021 (83 FR
57001 through 57002). Although, as noted in section IV.B.2. of the
proposed rule, we are now using EQRS to report data that was previously
reported in CROWNWeb, the data validation methodology remains the same.
Under this methodology, 300 facilities are selected each year to submit
10 records to CMS, and we reimburse these facilities for the costs
associated with copying and mailing the requested records. The burden
associated with these validation requirements is the time and effort
necessary to submit the requested records to a CMS contractor. In the
proposed rule, we updated these estimates using a newly available wage
estimate of a Medical Records and Health Information Technician. In the
CY 2020 ESRD PPS final rule, we estimated that it would take each
facility approximately 2.5 hours to comply with this requirement. If
300 facilities are asked to submit records, we estimated that the total
combined annual burden for these facilities would be 750 hours (300
facilities x 2.5 hours). Since we anticipate that Medical Records and
Health Information Technicians or similar administrative staff would
submit these data, we estimate that the aggregate cost of the EQRS data
validation each year would be approximately $31,800 (750 hours x
$42.40), or an annual total of approximately $106.00 ($31,800/300
facilities) per facility in the sample. The burden cost increase
associated with these requirements will be revised in the information
collection request (OMB control number 0938-1289).
In the CY 2021 ESRD PPS final rule, we finalized our policy to
reduce the number of records that a facility selected to participate in
the NHSN data validation must submit to a CMS contractor, beginning
with PY 2023 (85 FR 71471 through 71472). Under this finalized policy,
a facility is required to submit records for 20 patients across any two
quarters of the year, instead of 20 records for each of the first two
quarters of the year. The burden associated with this policy is the
time and effort necessary to submit the requested records to a CMS
contractor. Applying our policy to reduce the number of records
required from each facility participating in the NHSN validation, we
estimated that it would take each facility approximately 5 hours to
comply with this requirement. If 300 facilities are asked to submit
records each year, we estimated that the total combined annual burden
hours for these facilities per year would be 1,500 hours (300
facilities x 5 hours). Since we anticipate that Medical Records and
Health Information Technicians or similar staff would submit these
data, using the newly available wage estimate of a Medical Records and
Health Information Technician, we estimate that the aggregate cost of
the NHSN data validation each year would be approximately $63,600
(1,500 hours x $42.40), or a total of approximately $212 ($63,600/300
facilities) per facility in the sample. While the burden hours estimate
will not change, the burden cost updates associated with these
requirements will be revised in the information collection request (OMB
control number 0938-1340).
3. EQRS Reporting Requirements for PY 2024 and PY 2025 (OMB Control
Number 0938-1289)
To determine the burden associated with the EQRS reporting
requirements (previously known as the CROWNWeb reporting requirements),
we look at the total number of patients nationally, the number of data
elements per patient-year that the facility would be required to submit
to EQRS for each measure, the amount of time required for data entry,
the estimated wage plus benefits applicable to the individuals within
facilities who are most likely to be entering data into EQRS, and the
number of facilities submitting data to EQRS. In the CY 2021 ESRD PPS
final rule, we estimated that the burden associated with CROWNWeb (now
[[Page 61999]]
EQRS) reporting requirements for the PY 2024 ESRD QIP was approximately
$208 million (85 FR 71400).
As discussed in section IV.C. and section IV.D. of this final rule,
we are finalizing our proposed measure suppressions that would apply
for PY 2022 and updates to the scoring methodology and payment
reductions for the PY 2022 ESRD QIP. In the proposed rule, we also
announced an extension of EQRS reporting requirements for facilities
due to systems issues. However, we believe that none of the policies
finalized in this final rule would affect our estimates of the annual
burden associated with the Program's information collection
requirements, as facilities are still expected to continue to collect
measure data during this time period. We are not finalizing any changes
that would affect the burden associated with EQRS reporting
requirements for PY 2024 or PY 2025. However, we have re-calculated the
burden estimate for PY 2024 using updated estimates of the total number
of dialysis facilities, the total number of patients nationally, and
wages for Medical Records and Health Information Technicians or similar
staff as well as a refined estimate of the number of hours needed to
complete data entry for EQRS reporting. Consistent with our approach in
the CY 2021 ESRD PPS final rule (85 FR 71474), in the proposed rule we
estimated that the amount of time required to submit measure data to
EQRS was 2.5 minutes per element and did not use a rounded estimate of
the time needed to complete data entry for EQRS reporting. We are
further updating these estimates in this final rule. There are 229 data
elements for 532,931 patients across 7,717 facilities. At 2.5 minutes
per element, this yields approximately 658.94 hours per facility.
Therefore, the PY 2024 burden is 5,085,050 hours (658.94 hours x 7,717
facilities). Using the wage estimate of a Medical Records and Health
Information Technician, we estimate that the PY 2024 total burden cost
is approximately $215 million (5,085,050 hours x $42.40). There is no
net incremental burden change from PY 2024 to PY 2025 because we are
not changing the reporting requirements for PY 2025.
VIII. Regulatory Impact Analysis
A. Impact Analysis
1. Introduction
We have examined the impacts of this rule as required by Executive
Order 12866 on Regulatory Planning and Review (September 30, 1993),
Executive Order 13563 on Improving Regulation and Regulatory Review
(January 18, 2011), the Regulatory Flexibility Act (RFA) (September 19,
1980; Pub. L. 96-354), section 1102(b) of the Social Security Act,
section 202 of the Unfunded Mandates Reform Act of 1995 (March 22,
1995; Pub. L. 104-4), Executive Order 13132 on Federalism (August 4,
1999), and the Congressional Review Act (5 U.S.C. 801(2)).
Executive Orders 12866 and 13563 direct agencies to assess all
costs and benefits of available regulatory alternatives and, if
regulation is necessary, to select regulatory approaches that maximize
net benefits (including potential economic, environmental, public
health and safety effects, distributive impacts, and equity). Section
3(f) of Executive Order 12866 defines a ``significant regulatory
action'' as an action that is likely to result in a rule: (1) Having an
annual effect on the economy of $100 million or more in any 1 year, or
adversely and materially affecting a sector of the economy,
productivity, competition, jobs, the environment, public health or
safety, or State, local or tribal governments or communities (also
referred to as ``economically significant''); (2) creating a serious
inconsistency or otherwise interfering with an action taken or planned
by another agency; (3) materially altering the budgetary impacts of
entitlement grants, user fees, or loan programs or the rights and
obligations of recipients thereof; or (4) raising novel legal or policy
issues arising out of legal mandates, the President's priorities, or
the principles set forth in the Executive Order.
A regulatory impact analysis (RIA) must be prepared for major rules
with economically significant effects ($100 million or more in any 1
year). Based on our estimates, OMB's Office of Information and
Regulatory Affairs has determined that this rulemaking is
``economically significant'' as measured by the $100 million threshold,
and hence also a major rule under Subtitle E of the Small Business
Regulatory Enforcement Fairness Act of 1996 (also known as the
Congressional Review Act). Accordingly, we have prepared a Regulatory
Impact Analysis that to the best of our ability presents the costs and
benefits of the rulemaking. We solicit comments on the regulatory
impact analysis provided.
2. Statement of Need
a. ESRD PPS
As required by section 1881(b)(14) of the Social Security Act (the
Act), as added by section 153(b) of the Medicare Improvements for
Patients and Providers Act of 2008 (MIPPA) (Pub. L. 110-275). Section
1881(b)(14)(F) of the Act, as added by section 153(b) of MIPPA, and
amended by section 3401(h) of the Patient Protection and Affordable
Care Act (the Affordable Care Act) (Pub. L. 111-148), established that
beginning calendar year (CY) 2012, and each subsequent year, the
Secretary of the Department of Health and Human Services (the
Secretary) shall annually increase payment amounts by an ESRD market
basket increase factor, reduced by the productivity adjustment
described in section 1886(b)(3)(B)(xi)(II) of the Act.
This rule finalizes updates to the ESRD PPS for CY 2022, as
required by section 1881(b)(14)(F) of the Act. The routine updates
include the CY 2022 wage index values, the wage index budget-neutrality
adjustment factor, and outlier payment threshold amounts. Failure to
publish this final rule will result in ESRD facilities not receiving
appropriate payments in CY 2022 for renal dialysis services furnished
to ESRD beneficiaries, as required by section 1881(b)(14)(F) of the
Act.
b. AKI
This rule also finalizes updates to the payment for renal dialysis
services furnished by ESRD facilities to individuals with AKI, as
required by section 1834(r) of the Act, as added by section 808(b) of
the Trade Preferences Extension Act of 2015 (TPEA) (Pub. L. 114-27)
enacted on June 29, 2015. Failure to publish this final rule will
result in ESRD facilities not receiving appropriate payments in CY 2022
for renal dialysis services furnished to patients with AKI in
accordance with section 1834(r) of the Act.
c. ESRD QIP
Section 1881(h)(1) of the Act requires a payment reduction of up to
2 percent for eligible dialysis facilities that do not meet or exceed
the mTPS established with respect to performance standards for the ESRD
QIP each year. This final rule finalizes updates for the ESRD QIP,
including the adoption of a measure suppression policy and the
suppression of several ESRD QIP measures under that measure suppression
policy, updates regarding the scoring methodology and payment
reductions for the PY 2022 ESRD QIP, an update to the SHR measure, and
an update to the PY 2024 performance standards.
d. ETC Model
The ETC Model is a mandatory Medicare payment model tested under
the authority of section 1115A of the
[[Page 62000]]
Act, which authorizes the Innovation Center to test innovative payment
and service delivery models expected to reduce Medicare, Medicaid, and
CHIP expenditures while preserving or enhancing the quality of care
furnished to the beneficiaries of such programs.
This final rule will refine the methodology for setting and
updating achievement and improvement benchmarks for participating ESRD
facilities and Managing Clinicians serving the ESRD population over the
remaining years of the ETC Model, among other changes. As described in
detail in section V.B of this final rule, we believe it is necessary to
adopt certain changes to the ETC Model. Notwithstanding the changes, we
continue to anticipate improvement in quality of care for beneficiaries
and reduced expenditures under the ETC Model inasmuch as the Model is
designed to create incentives for Managing Clinicians and ESRD
facilities to support beneficiaries, along with their families and
caregivers, in choosing the optimal kidney replacement modality.
B. Overall Impact
1. ESRD PPS
We estimate that the final revisions to the ESRD PPS will result in
an increase of approximately $290 million in payments to ESRD
facilities in CY 2022, which includes the amount associated with
updates to the outlier thresholds, payment rate update, updates to the
wage index, and TPNIES payment.
2. AKI
We estimate that the updates to the AKI payment rate will result in
an increase of approximately $1 million in payments to ESRD facilities
in CY 2022.
C. Detailed Economic Analysis
In this section, we discuss the anticipated benefits, costs, and
transfers associated with the changes in this final rule. Additionally,
we estimate the total regulatory review costs associated with reading
and interpreting this final rule.
1. Benefits for ESRD PPS and AKI
Under the CY 2022 ESRD PPS and AKI payment, ESRD facilities will
continue to receive payment for renal dialysis services furnished to
Medicare beneficiaries under a case-mix adjusted PPS. We continue to
expect that making prospective payments to ESRD facilities will enhance
the efficiency of the Medicare program. Additionally, we expect that
updating ESRD PPS and AKI payments by 1.9 percent based on the final CY
2022 ESRD PPS market basket update less the final CY 2022 productivity
adjustment will improve or maintain beneficiary access to high quality
care by ensuring that payment rates reflect the best available data on
the resources involved in delivering renal dialysis services.
2. Costs
a. ESRD PPS and AKI
We do not anticipate the provisions of this final rule regarding
ESRD PPS and AKI rates-setting will create additional cost or burden to
ESRD facilities.
b. ESRD QIP
For PY 2024 and PY 2025, we have re-estimated the costs associated
with the information collection requirements under the ESRD QIP with
updated estimates of the total number of dialysis facilities. We note
that the estimated total number of patients nationally, wages for
Medical Records and Health Information Technicians or similar staff,
and the estimated number of hours needed to complete data entry for
EQRS reporting are the same as they were in the proposed rule. We have
made no changes to our methodology for calculating the annual burden
associated with the information collection requirements for the EQRS
validation study (previously known as the CROWNWeb validation study),
the NHSN validation study, and EQRS reporting. As discussed in section
IV.C. and section IV.D. of this final rule, we are finalizing our
proposed measure suppressions that would apply for PY 2022 and updates
to the scoring methodology and payment reductions for the PY 2022 ESRD
QIP. We also announced an extension of EQRS reporting requirements for
facilities due to systems issues in the proposed rule. However, we
believe that none of the policies finalized in this final rule would
affect our estimates of the annual burden associated with the Program's
information collection requirements, as facilities are still expected
to continue to collect measure data during this time period.
We also finalized the payment reduction scale using more recent
data for the measures in the ESRD QIP measure set. We estimate
approximately $215 million in information collection burden, which
includes the cost of complying with this rule, and an additional $17
million in estimated payment reductions across all facilities for PY
2024.
For PY 2025, we estimate that the proposed revisions to the ESRD
QIP would result in $215 million in information collection burden, and
$17 million in estimated payment reductions across all facilities, for
an impact of $232 million as a result of the policies we have
previously finalized and the policies we have finalized in this final
rule.
c. ETC Model
We estimate that the changes to the ETC Model will increase the
Model's projected direct savings from payment adjustments alone by $5
million over the duration of the Model. We estimate that the Model will
generate $28 million in direct savings related to payment adjustments
over 6.5 years with the adopted changes, and would generate $23 million
in savings in the absence of the finalized changes.
3. Transfers for ESRD PPS and AKI
We estimate that the finalized updates to the ESRD PPS and AKI
payment rate will result in a total in increase of approximately $290
million in payments to ESRD facilities in CY 2022, which includes the
amount associated with updates to the outlier thresholds, and updates
to the wage index. This estimate includes an increase of approximately
$1 million in payments to ESRD facilities in CY 2022 due to the
finalized updates to the AKI payment rate, of which approximately 20
percent is increased beneficiary co-insurance payments. We estimate
approximately $230 million in transfers from the Federal Government to
ESRD facilities due to increased Medicare program payments and
approximately $60 million in transfers from beneficiaries to ESRD
facilities due to increased beneficiary co-insurance payments as a
result of this final rule.
4. Regulatory Review Cost Estimation
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 rule in detail, and it is possible
that some reviewers chose not to comment on the proposed rule. For
these reasons, we thought that the number of past commenters would be a
fair estimate of the number of reviewers of this rule. We welcome any
comments on the approach in estimating the number of entities, which
will review
[[Page 62001]]
this final rule. We also recognize that different types of entities are
in many cases affected by mutually exclusive sections of this final
rule, and therefore for the purposes of our estimate we assume that
each reviewer reads approximately 50 percent of the rule. We seek
comments on this assumption.
Using the May, 2020 mean (average) wage information from the BLS
for medical and health service managers (Code 11-9111), we estimate
that the cost of reviewing this rule is $114.24 per hour, including
overhead and fringe benefits https://www.bls.gov/oes/current/oes119111.htm. Assuming an average reading speed of 250 words per
minute, we estimate that it will take approximately 300 minutes (5
hours) for the staff to review half of this final rule, which is
approximately 75,000 words. For each entity that reviews the rule, the
estimated cost is $571.20 (5 hours x $114.24). Therefore, we estimate
that the total cost of reviewing this regulation is $163,363.20
($571.20 x 286).
5. Impact Statement and Table
a. CY 2022 End-Stage Renal Disease Prospective Payment System
(1) Effects on ESRD Facilities
To understand the impact of the changes affecting payments to
different categories of ESRD facilities, it is necessary to compare
estimated payments in CY 2021 to estimated payments in CY 2022. To
estimate the impact among various types of ESRD facilities, it is
imperative that the estimates of payments in CY 2021 and CY 2022
contain similar inputs.
Therefore, we simulated payments only for those ESRD facilities for
which we are able to calculate both current payments and new payments.
For this final rule, we used CY 2020 data from the Part A and Part
B Common Working Files as of February 12, 2021, as a basis for Medicare
dialysis treatments and payments under the ESRD PPS. We updated the
2020 claims to 2021 and 2022 using various updates. The updates to the
ESRD PPS base rate are described in section II.B.1.d of this final
rule. Table 9 shows the impact of the estimated CY 2022 ESRD PPS
payments compared to estimated payments to ESRD facilities in CY 2021.
BILLING CODE 4120-01-P
[[Page 62002]]
[GRAPHIC] [TIFF OMITTED] TR08NO21.008
[[Page 62003]]
[GRAPHIC] [TIFF OMITTED] TR08NO21.009
BILLING CODE 4120-01-C
Column A of the impact table indicates the number of ESRD
facilities for each impact category and column B indicates the number
of dialysis treatments (in millions). The overall effect of the changes
to the outlier payment policy described in section II.B.1.c of this
final rule is shown in column C. For CY 2022, the impact on all ESRD
facilities as a result of the changes to the outlier payment policy
will be a 0.6 percent increase in estimated payments. All ESRD
facilities are anticipated to experience a positive effect in their
estimated CY 2022 payments as a result of the outlier policy changes.
Column D shows the effect of the annual update to the wage index,
as described in section II.B.1.b of this final rule. That is, this
column reflects the update from the CY 2021 ESRD PPS wage index using
2018 OMB delineations as finalized in the CY 2021 ESRD PPS final rule,
with a basis of the FY 2022 pre-floor, pre-reclassified IPPS hospital
wage index data in a budget neutral manner. The total impact of this
change is 0.0 percent; however, there are distributional effects of the
change among different categories of ESRD facilities. The categories of
types of facilities in the impact table show changes in estimated
payments ranging from a 0.7 percent decrease to a 0.5 percent increase
due to the annual update to the ESRD PPS wage index.
Column E shows the effect of the final CY 2022 ESRD PPS payment
rate update as described in section II.B.1.a of this final rule. The
ESRD PPS payment rate update is 1.9 percent, which reflects the ESRDB
market basket percentage increase factor for CY 2022 of 2.4 percent and
the productivity adjustment of 0.5 percent.
Column F reflects the overall impact, that is, the effects of the
outlier policy changes, the updated wage index, and the payment rate
update. We expect that overall ESRD facilities will experience a 2.5
percent increase in estimated payments in CY 2022. The categories of
types of facilities in the impact table show impacts ranging from a 1.6
percent increase to a 3.3 percent increase in their CY 2022 estimated
payments.
(2) Effects on Other Providers
Under the ESRD PPS, Medicare pays ESRD facilities a single bundled
payment for renal dialysis services, which may have been separately
paid to other providers (for example, laboratories, durable medical
equipment suppliers, and pharmacies) by Medicare prior to the
implementation of the ESRD PPS. Therefore, in CY 2022, we estimate that
the ESRD PPS will have zero impact on these other providers.
(3) Effects on the Medicare Program
We estimate that Medicare spending (total Medicare program
payments) for ESRD facilities in CY 2022 will be approximately $8.8
billion. This estimate considers a projected decrease in fee-for-
service Medicare dialysis beneficiary enrollment of 5.8 percent in CY
2022.
(4) Effects on Medicare Beneficiaries
Under the ESRD PPS, beneficiaries are responsible for paying 20
percent of the ESRD PPS payment amount. As a result of the projected
2.5 percent overall increase in the CY 2022 ESRD PPS payment amounts,
we estimate that there will be an increase in beneficiary co-insurance
payments of 2.5 percent in CY 2022, which translates to approximately
$60 million.
(5) Alternatives Considered
CY 2022 Impacts: 2019 Versus 2020 Claims Data
Each year CMS uses the latest available ESRD claims to update the
outlier threshold, budget neutrality factor, and payment rates. Due to
the COVID-19 PHE, we compared the impact of using CY 2019 claims
against CY 2020 claims to determine if there was any substantial
difference in the results that would justify potentially deviating from
our longstanding policy to use the latest available data. Analysis
suggested that ESRD utilization did not change substantially during the
pandemic, likely due to the patients' vulnerability and need for these
services. Consequently, we finalized our proposal to use the CY 2020
data because it does not negatively impact ESRD facilities and keeps
with our longstanding policy to make updates using the latest available
ESRD claims data (86 FR 36414).
Transitional Add-On Payment Adjustment for New and Innovative Equipment
and Supplies (TPNIES) Application: The Tablo[supreg] System--Home
Dialysis Machine
As discussed in section II.C.1.a. of the preamble of this final
rule, we are approving 1 technology for TPNIES for CY 2022, the
Tablo[supreg] System. We have provided an estimated impact for the
purposes of the Regulatory Impact Analysis, as follows. A Tablo[supreg]
System that was priced at $40,000 and amortized over 5 useful life
years using straight line depreciation would equal $8,000 per year
($40,000/5 = $8,000). Sixty-five percent of the annual cost would equal
$5,200 per year ($8,000 * .65 = $5,200 per year). The pre-adjusted per
treatment payment amount would equal $33.33 per treatment ($5,200/156 =
$33.33 per treatment). The TPNIES amount would therefore equal an
estimated $23.92 per treatment ($33.33-the CY 2022 average per
treatment offset amount of $9.50 = $23.83).
Based on February 2021 Shared Systems Data, there were
approximately 6,600 Medicare beneficiaries receiving home hemodialysis
treatment. If we estimated that this entire population were to use the
Tablo[supreg] System in CY2022, there would be 1,029,600 treatments
(6,600 Medicare beneficiaries * 156 treatments per year = 1,029,600
treatments). Applying the estimated $23.83 per treatment TPNIES amount
to the estimated 1,029,600 treatments would result in approximately $25
million in spending ($23.83 * 1,029,600 = $24,535,368). If, for
example, 1 percent of this population were to use the Tablo[supreg]
System in CY 2022, there would be 10,296 treatments (66 Medicare
beneficiaries * 156 treatments per year = 10,296 treatments). Applying
the $23.83 per treatment TPNIES amount to the 10,296 treatments would
result in approximately $246,280 in
[[Page 62004]]
spending ($23.83 * 10,296 = $245,354). We believe that 10 percent of
this population is a more reasonable estimate. If the estimated 10
percent were to use the Tablo[supreg] System in CY 2022, there would be
102,960 treatments (660 Medicare beneficiaries * 156 treatments per
year = 102,960 treatments). Applying the estimated $23.83 per treatment
TPNIES amount to the 102,960 treatments would result in approximately
$2.5 million in spending ($23.83 * 102,960 = $2,453,537), of which,
approximately $490,000 would be attributed to beneficiary coinsurance
amounts.
b. Payment for Renal Dialysis Services Furnished to Individuals With
AKI
(1) Effects on ESRD Facilities
To understand the impact of the changes affecting payments to
different categories of ESRD facilities for renal dialysis services
furnished to individuals with AKI, it is necessary to compare estimated
payments in CY 2021 to estimated payments in CY 2022. To estimate the
impact among various types of ESRD facilities for renal dialysis
services furnished to individuals with AKI, it is imperative that the
estimates of payments in CY 2021 and CY 2022 contain similar inputs.
Therefore, we simulated payments only for those ESRD facilities for
which we are able to calculate both current payments and new payments.
For this final rule, we used CY 2020 data from the Part A and Part
B Common Working Files as of February 12, 2021, as a basis for Medicare
for renal dialysis services furnished to individuals with AKI. We
updated the 2020 claims to 2021 and 2022 using various updates. The
updates to the AKI payment amount are described in section III.B of
this final rule. Table 10 shows the impact of the estimated CY 2022
payments for renal dialysis services furnished to individuals with AKI
compared to estimated payments for renal dialysis services furnished to
individuals with AKI in CY 2021.
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Column A of the impact table indicates the number of ESRD
facilities for each impact category and column B indicates the number
of AKI dialysis
[[Page 62006]]
treatments (in thousands). Column C shows the effect of the final CY
2022 wage indices. Column D shows the effect of the CY 2022 ESRD PPS
payment rate update. The ESRD PPS payment rate update is 1.9 percent,
which reflects the ESRDB market basket percentage increase factor for
CY 2022 of 2.4 percent and the productivity adjustment of 0.5 percent.
Column E reflects the overall impact, that is, the effects of the
updated wage index and the payment rate update. We expect that overall
ESRD facilities will experience a 1.9 percent increase in estimated
payments in CY 2022. The categories of types of facilities in the
impact table show impacts ranging from an increase of 0.0 percent to
2.5 percent in their CY 2022 estimated payments.
(2) Effects on Other Providers
Under section 1834(r) of the Act, as added by section 808(b) of
TPEA, we are updating the payment rate for renal dialysis services
furnished by ESRD facilities to beneficiaries with AKI. The only two
Medicare providers and suppliers authorized to provide these outpatient
renal dialysis services are hospital outpatient departments and ESRD
facilities. The patient and his or her physician make the decision
about where the renal dialysis services are furnished. Therefore, this
change will have zero impact on other Medicare providers.
(3) Effects on the Medicare Program
We estimate approximately $60 million will be paid to ESRD
facilities in CY 2022 as a result of patients with AKI receiving renal
dialysis services in the ESRD facility at the lower ESRD PPS base rate
versus receiving those services only in the hospital outpatient setting
and paid under the outpatient prospective payment system, where
services were required to be administered prior to the TPEA.
(4) Effects on Medicare Beneficiaries
Currently, beneficiaries have a 20 percent co-insurance obligation
when they receive AKI dialysis in the hospital outpatient setting. When
these services are furnished in an ESRD facility, the patients will
continue to be responsible for a 20 percent coinsurance. Because the
AKI dialysis payment rate paid to ESRD facilities is lower than the
outpatient hospital PPS's payment amount, we expect beneficiaries to
pay less co-insurance when AKI dialysis is furnished by ESRD
facilities.
(5) Alternatives Considered
As we discussed in the CY 2017 ESRD PPS proposed rule (81 FR
42870), we considered adjusting the AKI payment rate by including the
ESRD PPS case-mix adjustments, and other adjustments at section
1881(b)(14)(D) of the Act, as well as not paying separately for AKI
specific drugs and laboratory tests. We ultimately determined that
treatment for AKI is substantially different from treatment for ESRD
and the case-mix adjustments applied to ESRD patients may not be
applicable to AKI patients and as such, including those policies and
adjustment is inappropriate. We continue to monitor utilization and
trends of items and services furnished to individuals with AKI for
purposes of refining the payment rate in the future. This monitoring
will assist us in developing knowledgeable, data-driven proposals.
c. ESRD QIP
(a). Effects of the PY 2022 ESRD QIP on ESRD Facilities
The ESRD QIP is intended to prevent reductions in the quality of
ESRD dialysis facility services provided to beneficiaries. Although the
general methodology that we use to determine a facility's TPS is
described in our regulations at 42 CFR 413.178(e), we are finalizing
our proposal to codify special scoring policies for PY 2022 at 42 CFR
413.178(h). Under these finalized regulations, we will calculate
measure rates for all measures but will not calculate achievement and
improvement points for any measures. We will also not calculate or
award a TPS for any facility. Finally, we will not reduce payment to
any facility for PY 2022.
We believe there will be no effects of the PY 2022 ESRD QIP on ESRD
Facilities resulting from these finalized policies because no
facilities will receive a TPS or payment reductions for PY 2022.
(b). Effects of the PY 2024 ESRD QIP on ESRD Facilities
Any reductions in the ESRD PPS payments as a result of a facility's
performance under the PY 2024 ESRD QIP will apply to the ESRD PPS
payments made to the facility for services furnished in CY 2024, as
codified in our regulations at 42 CFR 413.177.
For the PY 2024 ESRD QIP, we estimate that, of the 7,717 dialysis
facilities (including those not receiving a TPS) enrolled in Medicare,
approximately 24.3 percent or 1,788 of the facilities that have
sufficient data to calculate a TPS would receive a payment reduction
for PY 2024. We are presenting an estimate for the PY 2024 ESRD QIP to
update the estimated impact that was provided in the CY 2021 ESRD PPS
final rule (85 FR 71481 through 71483). As a result of our finalized
policies, the total estimated payment reductions for all the 1,788
facilities expected to receive a payment reduction in PY 2024 would
decrease from $18,247,083.76 to approximately $17,104,030.59.
Facilities that do not receive a TPS do not receive a payment
reduction.
Table 11 shows the overall estimated distribution of payment
reductions resulting from the PY 2024 ESRD QIP.
[GRAPHIC] [TIFF OMITTED] TR08NO21.011
To estimate whether a facility would receive a payment reduction
for PY 2024, we scored each facility on achievement and improvement on
several clinical measures we have previously finalized and for which
there
[[Page 62007]]
were available data from EQRS and Medicare claims. Payment reduction
estimates are calculated using the most recent data available
(specified in Table 12) in accordance with the policies finalized in
this final rule. Measures used for the simulation are shown in Table
12.
[GRAPHIC] [TIFF OMITTED] TR08NO21.012
For all measures except the SHR clinical measure, the Standardized
Readmission Ratio (SRR) clinical measure, and the STrR reporting
measure, measures with less than 11 patients for a facility were not
included in that facility's TPS. For the SHR clinical measure and the
SRR clinical measure, facilities were required to have at least 5
patient-years at risk and 11 index discharges, respectively, in order
to be included in the facility's TPS. For the STrR reporting measure,
facilities were required to have at least 10 patient-years at risk in
order to be included in the facility's TPS. Each facility's TPS was
compared to an estimated mTPS and an estimated payment reduction table
that were consistent with the finalized polices outlined in sections
IV.E. and IV.F. of this final rule. Facility reporting measure scores
were estimated using available data from CY 2019. Facilities were
required to have at least one measure in at least two domains to
receive a TPS.
To estimate the total payment reductions in PY 2024 for each
facility resulting from this final rule, we multiplied the total
Medicare payments to the facility during the 1-year period between
January 2019 and December 2019 by the facility's estimated payment
reduction percentage expected under the ESRD QIP, yielding a total
payment reduction amount for each facility.
Table 13 shows the estimated impact of the finalized ESRD QIP
payment reductions to all ESRD facilities for PY 2024. The table also
details the distribution of ESRD facilities by size (both among
facilities considered to be small entities and by number of treatments
per facility), geography (both rural and urban and by region), and
facility type (hospital based and freestanding facilities). Given that
the performance period used for these calculations differs from the
performance period we are using for the PY 2024 ESRD QIP, the actual
impact of the PY 2024 ESRD QIP may vary significantly from the values
provided here.
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BILLING CODE 4120-01-C
(c). Effects of the PY 2025 ESRD QIP on ESRD Facilities
For the PY 2025 ESRD QIP, we estimate that, of the 7,717 dialysis
facilities (including those not receiving a TPS) enrolled in Medicare,
approximately 24.3 percent or 1,788 of the facilities that have
sufficient data to calculate a TPS would receive a payment reduction
for PY 2025. The total payment reductions for all the 1,788 facilities
expected to receive a payment reduction is approximately
$17,104,030.59. Facilities that do not receive a TPS do not receive a
payment reduction. Table 14 shows the overall estimated distribution of
payment reductions resulting from the PY 2025 ESRD QIP.
[[Page 62009]]
[GRAPHIC] [TIFF OMITTED] TR08NO21.014
To estimate whether a facility would receive a payment reduction in
PY 2025, we scored each facility on achievement and improvement on
several clinical measures we have previously finalized and for which
there were available data from EQRS and Medicare claims. Payment
reduction estimates were calculated using the most recent data
available (specified in Table 14) in accordance with the policies
finalized in this final rule. Measures used for the simulation are
shown in Table 15.
[GRAPHIC] [TIFF OMITTED] TR08NO21.015
For all measures except the SHR clinical measure, the SRR clinical
measure, and the STrR reporting measure, measures with less than 11
patients for a facility were not included in that facility's TPS. For
SHR and SRR, facilities were required to have at least 5 patient-years
at risk and 11 index discharges, respectively, in order to be included
in the facility's TPS. For the STrR reporting measure, facilities were
required to have at least 10 patient-years at risk in order to be
included in the facility's TPS. Each facility's TPS was compared to an
estimated mTPS and an estimated payment reduction table that
incorporates the policies outlined in section IV.E. and IV.F. of this
final rule. Facility reporting measure scores were estimated using
available data from CY 2019. Facilities were required to have at least
one measure in at least two domains to receive a TPS.
To estimate the total payment reductions in PY 2025 for each
facility resulting from this proposed rule, we multiplied the total
Medicare payments to the facility during the 1-year period between
January 2019 and December 2019 by the facility's estimated payment
reduction percentage expected under the ESRD QIP, yielding a total
payment reduction amount for each facility.
Table 16 shows the estimated impact of the finalized ESRD QIP
payment reductions to all ESRD facilities for PY 2025. The table
details the distribution of ESRD facilities by size (both among
facilities considered to be small entities and by number of treatments
per facility), geography (both rural and urban and by region), and
facility type (hospital based and freestanding facilities). Given that
the performance period used for these calculations differs from the
performance period we are using for the PY 2025 ESRD QIP, the actual
impact of the PY 2025 ESRD QIP may vary significantly from the values
provided here.
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[[Page 62010]]
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BILLING CODE 4120-01-C
(d). Effects on Other Providers
The ESRD QIP is applicable to dialysis facilities. We are aware
that several of our measures impact other providers. For example, with
the introduction of the SRR clinical measure in PY 2017 and the SHR
clinical measure in PY 2020, we anticipate that hospitals may
experience financial savings as dialysis facilities work to reduce the
number of unplanned readmissions and hospitalizations. We are exploring
various methods to assess the impact these measures have on hospitals
and other facilities, such as through the impacts of the Hospital
Readmissions Reduction Program and the Hospital-Acquired Condition
Reduction Program, and we intend to continue examining the interactions
between our quality programs to the greatest extent feasible.
(e). Effects on the Medicare Program
For PY 2025, we estimate that the ESRD QIP would contribute
approximately $17,104,030.59 in Medicare savings. For comparison, Table
17 shows the payment reductions that we estimate will be applied by the
ESRD QIP from PY 2018 through PY 2025. This includes our finalized PY
2022 scoring and payment proposals as described in section IV.D. of
this final rule.
[[Page 62011]]
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(f). Effects on Medicare Beneficiaries
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\279\ As discussed in section IV.D of this final rule, we are
finalizing our proposed special scoring methodology and payment
policy for PY 2022. Under this policy, we will not apply any payment
reductions to ESRD facilities for PY 2022.
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The ESRD QIP is applicable to dialysis facilities. Since the
Program's inception, there is evidence on improved performance on ESRD
QIP measures. As we stated in the CY 2018 ESRD PPS final rule, one
objective measure we can examine to demonstrate the improved quality of
care over time is the improvement of performance standards (82 FR
50795). As the ESRD QIP has refined its measure set and as facilities
have gained experience with the measures included in the Program,
performance standards have generally continued to rise. We view this as
evidence that facility performance (and therefore the quality of care
provided to Medicare beneficiaries) is objectively improving. We are in
the process of monitoring and evaluating trends in the quality and cost
of care for patients under the ESRD QIP, incorporating both existing
measures and new measures as they are implemented in the Program. We
will provide additional information about the impact of the ESRD QIP on
beneficiaries as we learn more. However, in future years we are
interested in examining these impacts through the analysis of available
data from our existing measures.
(g). Alternatives Considered
In section IV.D. of this final rule, we are finalizing a special
rule to modify the scoring methodology such that no facility will
receive a payment reduction for PY 2022. Under this special rule for PY
2022, we will calculate measure rates for all measures for that payment
year, but will not use those measure rates to generate an achievement
or improvement score, domain scores, or a TPS. We considered retaining
our current scoring policy for PY 2022. However, we concluded that this
was not feasible because of the EQRS system issues described in section
IV.B.2., and additionally, due to the impact of the COVID-19 PHE on
some of the PY 2022 ESRD QIP measures, as described more fully in
section IV.C. of this final rule. This approach will help to ensure
that a facility would not be penalized due to extraordinary
circumstances beyond the facility's control.
d. ETC Model
(1). Overview
Under the ESRD PPS under Medicare Part B, a single per-treatment
payment is made to an ESRD facility for all of the renal dialysis
services defined in section 1881(b)(14)(B) of the Act and furnished to
individuals for the treatment of ESRD in the ESRD facility or in a
patient's home. Under the Physician Fee Schedule, medical management of
an ESRD beneficiary receiving dialysis by a physician or other
practitioner is paid through the MCP. The ETC Model is a mandatory
payment model designed to test payment adjustments to certain dialysis
and dialysis-related payments, as discussed in the Specialty Care
Models final rule (85 FR 6114), for ESRD facilities and for Managing
Clinicians for claims with dates of service from January 1, 2021 to
June 30, 2027. The requirements for the ETC Model are set forth in 42
CFR part 512, subpart C. The changes in this final rule (discussed in
detail in section V.B of this final rule) will impact model payment
adjustments for PPA Period 3, starting in July 1, 2023.
Under the current ETC Model, there are two payment adjustments
designed to increase rates of home dialysis and kidney transplant
waitlisting through financial incentives. The HDPA is an upward payment
adjustment on certain home dialysis claims for ESRD facilities, as
described in the final rule in Sec. Sec. 512.340 and 512.350, and to
certain home dialysis-related claims for Managing Clinicians, as
described in the final rule in Sec. Sec. 512.345 and 512.350, during
the initial 3 years of the ETC Model.
The PPA is an upward or downward payment adjustment on certain
dialysis and dialysis-related claims submitted by ETC Participants, as
described in the final rule in Sec. Sec. 512.375(a) and 512.380 for
ESRD facilities and Sec. Sec. 512.375(b) and 512.380 for Managing
Clinicians, which will apply to claims with claim service dates
beginning on July 1, 2022 and increase in magnitude over the duration
of the Model. We will assess each ETC Participant's home dialysis rate,
as described in the final rule in Sec. 512.365(b), and ETC transplant
waitlist rate, as described in Sec. 512.365(c), for each Measurement
Year (MY). The ETC Participant's transplant waitlist rate, will be
aggregated, as described in Sec. 512.365(e), and the ETC Participant's
home dialysis rate will be aggregated, as described in Sec.
512.365(e). The ETC Participant will receive a Modality Performance
Score (MPS) based on the weighted sum of the higher of the ETC
Participant's achievement score or improvement score for the home
dialysis rate and the higher of the ETC Participant's achievement score
or improvement score for the transplant waitlist rate, as described in
Sec. 512.370(d).
For MY1 and MY2 (January 1, 2021 through July 6, 2022), the
achievement scores will be calculated in relation to a set of
benchmarks based on the historical rates of home dialysis and inclusion
on the transplant waitlist among ESRD facilities and Managing
Clinicians located in Comparison Geographic Areas. The improvement
scores will be calculated in relation to a set of benchmarks based on
the ETC Participant's own historical performance. The ETC Participant's
MPS for a MY will determine the magnitude of its PPA during the
corresponding 6-month PPA Period, which will begin 6 months after the
end of the MY. An ETC Participant's MPS will be updated on a rolling
basis every 6 months.
As mentioned in section IV.C.2.b(1) of the Specialty Care Models
final rule (85 FR 61351), the intention was to increase achievement
benchmarks over time through subsequent notice and
[[Page 62012]]
comment rulemaking. In the CY 2022 ESRD PPS proposed rule, the changes
listed with bullets were proposed for MY3 (beginning January 1, 2022)
through the final MY of ETC Model (MY10).
Include nocturnal in-center dialysis in the home dialysis
rate calculation for Managing Clinicians and ESRD facilities not owned
in whole or in part by an ETC LDO.
Modify the PPA achievement benchmarking methodology:
++Stratify the home dialysis and transplant rate benchmark by the
proportion of beneficiaries who are dual-eligible for Medicare and
Medicaid, or, receive the Low-Income Subsidy (LIS), resulting in two
strata.
++Increase the home dialysis and transplant rate benchmarks by 10
percent for each MY couplet (that is, 1.10 for MY3 and MY4, 1.20 for
MY5 and MY6, 1.30 for MY7 and MY8, and 1.40 for MY9 and MY10).
Modify the PPA improvement benchmarking methodology:
++Health Equity Incentive: Participants can earn 0.5 improvement
points in addition to their improvement score for a 5 percentage point
increase in the home dialysis rate or transplant rate among dual
eligible or LIS recipient beneficiaries.
++Modify improvement calculation to ensure that the Benchmark Year
rate cannot be zero, such that improvement is calculable for all
participants.
In this final rule, we finalized all of the changes proposed in the
CY 2022 ESRD PPS proposed rule, with certain modifications. The two
such modifications most likely to affect the impact estimate for the
ETC Model are:
Modify the home dialysis rate calculation by including
nocturnal dialysis in the numerator of the home dialysis rate
calculation for all ESRD facilities, rather than only those ESRD
facilities not owned in whole or in part by an ETC LDO.
Modify the methodology for the Health Equity Incentive by
reducing the threshold to earn the additional 0.5 improvement points
from a 5-percentage point increase to a 2.5-percentage point increase
from the Benchmark Year to the MY.
More detail on these changes are provided in sections V.B.3.c and
V.B.6.c.(2) of this final rule. The ETC Model is not a total cost of
care model. ETC Participants will still bill FFS Medicare, and items
and services not subject to the ETC Model's payment adjustments will
continue to be paid as they will in the absence of the Model.
(2). Data and Methods
A stochastic simulation was created to estimate the financial
impacts of the changes to the ETC Model relative to baseline
expenditures, where baseline expenditures were defined as data from CYs
2018 and 2019 without the changes applied. The simulation relied upon
statistical assumptions derived from retrospectively constructed ESRD
facilities' and Managing Clinicians' Medicare dialysis claims,
transplant claims, and transplant waitlist data reported during 2018
and 2019, the most recent years with complete data available. Both
datasets and the risk-adjustment methodologies for the ETC Model were
developed by the CMS Office of the Actuary (OACT).
The ESRD facilities and Managing Clinicians datasets were
restricted to the following eligibility criteria. Beneficiaries must be
residing in the United States, 18 years of age or older, and enrolled
in Medicare Part B. Beneficiaries enrolled in Medicare Advantage or
other cost or Medicare managed care plans, who have elected hospice,
are receiving dialysis for acute kidney injury (AKI) only, with a
diagnosis of dementia, who are receiving dialysis in a nursing
facility, or reside in a skilled nursing facility were excluded. In
addition, beneficiaries who have a diagnosis of and are receiving
treatment with chemotherapy or radiation for a vital solid organ cancer
were excluded from the transplant rate calculations. Diagnosis of a
vital solid organ cancer was defined as a beneficiary that had a claim
with any of 39 ICD-10-CM codes ranging from C22.0 through C79.02.
Treatment of a vital solid organ cancer was defined as a beneficiary
with a claim with any of 2,087 radiation administration ICD-10-PCS
codes, 19 chemotherapy administration CPT codes, or 41 radiation
administration CPT codes. Last, the HRR was matched to the claim
service facility ZIP Code\TM\ or the rendering physician ZIP Code for
ESRD facility and Managing Clinician, respectively.\280\
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\280\ ZIP Code is a trademark owned by the United States Postal
Service.
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For the modeling exercise used to estimate changes in payment to
providers and suppliers and the resulting savings to Medicare, OACT
maintained the previous method to identify ESRD facilities with common
ownership, the low-volume exclusion threshold, and the aggregation
assumptions as CMS is not making changes to these model policies. To
clarify OACT's methodology, the ESRD facilities' data were aggregated
to the CMS Certification Number (CCN) level for beneficiaries on
dialysis identified by outpatient claims with Type of Bill 072X to
capture all dialysis services furnished at or through ESRD facilities.
Beneficiaries receiving home dialysis services were defined as
condition codes 74 and 76 (Sec. 512.340). Condition code 75 was
removed from the home dialysis definition because that billing code is
no longer in use. Condition code 80 was removed because we want to
exclude beneficiaries who received home dialysis furnished in a SNF or
nursing facility. Beneficiaries receiving in-center dialysis services
were defined using condition code 71. Two new variables were created:
In-center self-dialysis, condition code 72 (Sec. 512.365) and in-
center nocturnal dialysis, based on any of the claims' lines 1-5 HCPCS
codes equal to the ``UJ'' modifier. Self-care in training and ESRD
self-care retraining, condition codes 73 and 87, respectively, were
only included in the denominator for the home dialysis rate
calculation. For consistency with the exclusion in Sec. 512.385(a),
after grouping within each HRR, aggregated ESRD facilities with less
than 132 total attributed beneficiary months during a given MY were
excluded. When constructing benchmarks, for consistency with the
methodology for aggregating performance for purposes of the PPA
calculation, we aggregated all ESRD facilities owned in whole or in
part by the same dialysis organization located in the same HRR.
The Managing Clinicians' performance data were aggregated to the
Tax Identification Number (TIN) level (for group practices) and the
individual National Provider Identifier (NPI) level (for solo
practitioners). For purposes of calculating the home dialysis rate,
beneficiaries on home dialysis were identified using outpatient claims
with CPT[supreg] codes 90965 and 90966 (Sec. 512.345). Beneficiaries
receiving in-center dialysis were identified by outpatient claims with
CPT[supreg] codes 90957, 90958, 90959, 90960, 90961, and 90962 (Sec.
512.360). Last, following the low-volume threshold described in Sec.
512.385(b), after grouping within each HRR, Managing Clinicians with
less than 132 total attributed beneficiary months during a given MY
were excluded.
The Scientific Registry of Transplant Recipients (SRTR) transplant
waitlist data were obtained from the Center for Clinical Standards and
Quality (CCSQ). To construct the transplant waitlist rate, the
numerator was based on per-patient counts and included every addition
to the waitlist for a patient in any past year. The waitlist counts for
the
[[Page 62013]]
numerator included waitlists for kidney transplants, alone or with
another organ, active and inactive records, multi-organ listings, and
patients that have subsequently been removed from the waitlist. The
denominator was a unique count of prevalent dialysis patients as of the
end of the year. Only patients on dialysis as of December 31st for the
selected year were included. Facility attribution was based on the
facility the patient was admitted to on the last day of the year.
For MY1 and MY2, the home dialysis score and transplant score for
the PPA were calculated using the following methodology for the ESRD
facilities and Managing Clinicians. ETC Participant behavior for each
year was simulated by adjusting the ETC Participant's baseline home
dialysis (or transplant) rate for a simulated statistical fluctuation
and then summing with the assumed increase in home dialysis (or
transplant) rate multiplied by a randomly generated improvement scalar.
The achievement and improvement scores were assigned by comparing the
ETC Participant's simulated home dialysis (or transplant) rate for the
MY to the percentile distribution of home dialysis (or transplant)
rates in the prior year. Last, the MPS was calculated using the
weighted sum of the higher of the achievement or improvement score for
the home dialysis rate and the transplant waitlist rate. The home
dialysis rate constituted two-thirds of the MPS, and the transplant
rate one-third of the MPS.
For MY3 through MY10, the home dialysis rate calculation accounts
for modifications in this final rule compared to the CY 2022 ESRD PPS
proposed rule. The revisions include changing the numerator for the
home dialysis rate from the home dialysis beneficiary months to the
home dialysis beneficiary months + 0.5 (in-center self-dialysis
beneficiary months) + 0.5* (nocturnal in-center dialysis beneficiary
months), such that 1-beneficiary year is comprised of 12-beneficiary
months for all ETC Participants.
The number of beneficiaries on in-center self-dialysis who met the
eligibility criteria for the ETC Model was very small, ranging from 102
to 277 over the period 2012-2019 and decreasing 89.9 percent to 22
beneficiaries in 2020 (based on preliminary 2020 data at CMS). With
such a small sample size, the growth rate vacillated significantly. In
addition, the in-center nocturnal dialysis UJ modifier code did not
become effective until January 1, 2017; therefore, there were
insufficient data to generate growth rate assumptions. The in-center
nocturnal dialysis beneficiary growth rate decreased by 91.3 percent in
2020. As a solution to these data limitations, to simulate the impact
of incorporating in-center self-dialysis and in-center nocturnal
dialysis for the purpose of the savings to Medicare estimate, the
simulation assumed any given ESRD facility or Managing Clinician will
have a one percent chance of receiving an increased achievement score
due to this policy.
The overall process for generating achievement and improvement
scoring followed modeling from section VI.C.2 of the Specialty Care
Models final rule (85 FR 61352), with the exception of the following
changes proposed in the CY 2022 ESRD PPS proposed rule, which we are
finalizing in this final rule.
Beginning for MY3 and beyond, the achievement benchmarking
methodology included two modifications. First, the home dialysis rate
and transplant waitlist rate benchmarks were increased by a total of 10
percent relative to ESRD facilities and Managing Clinicians not
selected for participation, every two MYs. To clarify, no changes to
the achievement benchmarking methodology were made to MYs 1 and 2. The
latter MY couplets' achievement benchmarking included the following
preset benchmark updates:
MYs 3 and 4: Comparison Geographic Area percentiles*1.10,
MYs 5 and 6: Comparison Geographic Area percentiles*1.20,
MYs 7 and 8: Comparison Geographic Area percentiles*1.30,
and
MYs 9 and 10: Comparison Geographic Area percentiles*1.40.
The percentiles represented the 30th, 50th, 75th, and 90th
percentile of the home dialysis rate and transplant rate for ESRD
facilities and Managing Clinicians not selected for participation. The
preset benchmark updates method provides greater certainty to ETC
Participants than the rolling updates described in section IV.C.2.b(3)
of the Specialty Care Models final rule (85 FR 61353).
Second, we incorporated two proxies for socioeconomic status, dual
eligibility status or receipt of the Low Income Subsidy (LIS), as part
of the achievement benchmarking starting for MY3 and beyond. Dual
eligibility status was defined as a Medicare beneficiary with any of
the following full-time dual type codes: 02 = Eligible is entitled to
Medicare Qualified Medicare Beneficiary (QMB) and Medicaid coverage
including prescription drugs, 04 = Eligible is entitled to Medicare
Specified Low-Income Medicare Beneficiary (SLMB) and Medicaid coverage
including prescription drugs, or 08 = Eligible is entitled to Medicare
Other dual eligible with Medicaid coverage including prescription
drugs. Separately, a yes/no indicator was created for any beneficiary
that was either deemed or determined by the Social Security
Administration (SSA) to be receiving the LIS. The home dialysis rate
and transplant waitlist rate achievement benchmarks were then
stratified by the proportion of attributed beneficiaries who are dual-
eligible or receive the LIS. Two strata were created with a cutpoint of
approximately 50 percent for participants with any dual-eligible or LIS
recipient beneficiaries and those who do not have beneficiaries meeting
these two socioeconomic status proxies.
Third, a Health Equity Incentive was added to improvement scoring
starting in MY3. For the purpose of the estimates in this Regulatory
Impact Analysis, we incorporated a random variable to simulate each ETC
Participant's baseline variation and behavioral improvement for each
MY. If the participant's simulated improvement behavior in MY3 through
MY10 was greater than 2.5 percent, then the participant received a 0.5-
point increase on their improvement score, allowing for a maximum of
2.0 total points. The threshold for receiving the Health Equity
Incentive was reduced from the 5-percentage point threshold proposed in
the CY 2022 ESRD PPS proposed rule to a 2.5-percentage point threshold
in this final rule.
For all MYs, the transplant waitlist benchmarks were annually
inflated by approximately 3-percentage points growth. This was a
modification from section VI.C.2 of the Specialty Care Models final
rule (85 FR 61352), where the waitlist benchmarks were annually
inflated by approximately 2-percentage points growth observed during
years 2017 through 2019 in the CCSQ data, to project rates of growth.
The additional 1 percentage point growth in this final rule was
included to account for uncertainty from the COVID-19 PHE disruption
and section 17006 of the 21st Century Cures Act (Cures Act) (Pub. L.
114-255), which amended the Act to increase enrollment options for
individuals with ESRD into Medicare Advantage. To clarify, applying the
3-percentage point annual growth from the median transplant waitlist
rate across HRR condensed facilities grew from 8 percent in 2017 to 11
percent in 2018 to 14 percent in 2019 (that is, not a growth rate of
1.03 percent per year).
To assess the impact of the COVID-19 PHE on the kidney transplant
waitlist, we analyzed data from the
[[Page 62014]]
United Network for Organ Sharing (UNOS).\281\ The UNOS data suggest
that the number of new patients added to the kidney transplant waitlist
steadily decreased between the weeks of March 15, 2020 through May 10,
2020, when between 16 to 81 percent of patients listed on the weekly
kidney transplant waitlist became inactive due to COVID-19 precautions.
During July through December 2020, the number of new patients added to
the kidney transplant waitlist increased to near pre-pandemic levels
with an average of less than 3 percent of patients listed as inactive
due to COVID-19. Anomalous dips in the number of new patients added to
the kidney transplant waitlist were observed during the weeks of
November 22, 2020 and December 27, 2020, which correspond with Federal
holidays in addition to a period that Americans were asked to social
distance to slow the spread of COVID-19. Continuing into the first
quarter of 2021, new additions to the kidney transplant waitlist
remained at approximately pre-pandemic rates. Therefore, we assume that
the number of new patients added to the waitlist will not decrease as a
result of the pandemic and the linear 2-percentage point growth rate
for the transplant waitlist calculated using years 2017 through 2019
CCSQ data remains a reasonable assumption for baseline growth going
forward. In the final rule, we also included a 1 percent increase to
the standard error to account for a new variation assumption to address
how year-over-year changes could fluctuate at the ESRD facility or
Managing Clinician level, which was potentially exacerbated by the
exclusion criteria (that is, residents of a nursing facility, receiving
dialysis in a skilled nursing facility, dialysis for AKI only) applied
to the updated model data source used for estimates in this final rule.
---------------------------------------------------------------------------
\281\ UNOS. 2021. COVID-19 and Solid Organ Transplants.
Transplant and Waitlist Data Visualizations. https://unos.org/covid/.
---------------------------------------------------------------------------
No changes were made to the payment structure for the HDPA
calculation in the final rule (Sec. 512.350). As such, the HDPA was
calculated using the home dialysis and home dialysis-related payments
adjusted by decreasing amounts (3, 2, and 1 percent) during each of the
first 3 years of the Model.
The kidney disease patient education services utilization and cost
data were identified by HCPCS codes G0420 and G0421, to capture face-
to-face individual and group training sessions for chronic kidney
disease beneficiaries on treatment modalities. The home dialysis
training costs for incident beneficiaries on home dialysis for
Continuous Ambulatory Peritoneal Dialysis (CAPD) or Continuous Cycler-
Assisted Peritoneal Dialysis (CCPD) were defined using CPT[supreg]
codes 90989 and 90993 for complete and incomplete training sessions,
respectively.
Data from CY 2019 were used to project baseline expenditures (that
is, expenditures before the proposed changes were applied) and the
traditional FFS payment system billing patterns were assumed to
continue under current law.
(3). Medicare Estimate--Primary Specification, Assume Preset Benchmark
Updates
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Table 18 summarizes the estimated impact of the ETC Model when
assuming preset benchmark updates where the achievement benchmarks for
each year are set using the average of the home dialysis rates for year
t-1 and year t-2 for the HRRs randomly selected for participation in
the ETC Model. We estimate the Medicare program will save a net total
of $43 million from the PPA and HDPA between January 1, 2021 and June
30, 2027, less $15 million in increased training and education
expenditures. Therefore, the net impact to Medicare spending is
estimated to be $28 million in savings. In Table 18 and Table 19,
negative spending reflects a reduction in Medicare spending, while
positive spending reflects an increase. The results for both tables
were generated from an average of 400 simulations under the assumption
that benchmarks are rolled forward with a 1.5-year lag.
Table 19 is provided to isolate the total impact of the changes in
this final rule for years 2023 going forward by calculating the
difference from our final estimates in Table 18 less totals from the
[[Page 62016]]
estimates reported in Table 18 of the CY 2022 ESRD PPS proposed rule
(86 FR 36425) that used the same years of data, but without the changes
from the CY 2022 ESRD PPS proposed rule to this final rule. To clarify,
the CY 2022 ESRD PPS proposed rule estimates are not the estimates
reported in Table 19 of the Specialty Care Models final rule (85 FR
61354); the final rule used data from CYs 2016 and 2017 and this final
rule used the most recent data available, from CYs 2018 and 2019. There
was no impact reported in years 2021 and 2022 since the payment
adjustments were not effective until MY3. In addition, the changes did
not apply to the HDPA or the Kidney Disease Patient Education Services
Costs and HD Training Costs. As expected, Table 19 shows that the
changes had a small effect on Medicare savings; a reduction of $10
million in savings for the net impact to Medicare spending over the
4.5-year period can be attributed to the changes in this final rule
from the CY 2022 ESRD PPS proposed rule.
As was the case in the Specialty Care Models final rule (85 FR
61353), the projections do not include the Part B premium revenue
offset because the payment adjustments under the ETC Model will not
affect beneficiary cost-sharing. Any potential effects on Medicare
Advantage capitation payments were also excluded from the projections.
This approach is consistent with how CMS has previously conveyed the
primary FFS effects anticipated for an uncertain model without also
assessing the potential impact on Medicare Advantage rates.
Returning to Table 18, as anticipated, the expected Medicare
program savings were driven by the net effect of the Facility PPA; a
reduction in Medicare spending of $65 million over the period from July
1, 2022 through June 30, 2027. In comparison, the net effect of the
Clinician PPA was only $8 million in Medicare savings. This estimate
was based on an empirical study of historical home dialysis utilization
and transplant waitlist rates for Medicare FFS beneficiaries that CMS
virtually attributed to ESRD facilities and to Managing Clinicians
based on the plurality of associated spending at the beneficiary level.
We analyzed the base variation in those facility/practice level
measures and simulated the effect of the payment policy assuming
providers and suppliers respond by marginally increasing their share of
patients utilizing home dialysis. Random variables were used to vary
the effectiveness that individual providers and suppliers might show in
such progression over time and to simulate the level of year-to-year
variation already noted in the base multi-year data that was analyzed.
The uncertainty in the projection was illustrated in sections
VII.C.2.b.(3)(a) and VII.C.2.b.(3)(b) of the Specialty Care Models
final rule (85 FR 61354), respectively, through alternate scenarios
assuming that the benchmarks against which ETC Participants are
measured were to not be updated. In those sensitivity analyses, we
analyzed a modified version of the model that included a fixed
benchmark for the home dialysis and transplant waitlist rates as well
as a separate sensitivity analysis that assumed a rolling benchmark for
the home dialysis rate and a fixed benchmark for the transplant
waitlist rate.
For this final rule, we are continuing with the approach applied in
the CY 2022 ESRD PPS proposed rule by modeling a preset benchmark
growth rate in this rule but continue to incorporate sensitivity to a
range of potential behavioral changes for the home dialysis rate and
transplant waitlist rate for ETC facilities and Managing Clinicians
assumed to participate in the model. Kidney disease patient education
services on treatment modalities and home dialysis (HD) training for
incident dialysis beneficiaries are relatively small outlays and were
projected to represent only relatively modest increases in Medicare
spending each year.
The key assumptions underlying the impact estimate are that each
aggregation group's share of total maintenance dialysis provided in the
home setting was assumed to grow by up to an assumed maximum growth
averaging 3-percentage points per year. Factors underlying this
assumption about the home dialysis growth rate include: known
limitations that may prevent patients from being able to dialyze at
home, such as certain common disease types that make peritoneal
dialysis impractical (for example, obesity); current equipment and
staffing constraints; and the likelihood that a patient new to
maintenance dialysis starts dialysis at home compared to the likelihood
that a current dialysis patient who dialyzes in center switches to
dialysis at home. In any given trial of the simulation, the maximum
growth rate was chosen from a uniform distribution of 0 to 5-percentage
points per year. Preliminary data from CMS show that the growth rate
for home dialysis was 3.9 percent in CY 2020 for beneficiaries meeting
the eligibility criteria for the ETC Model. This growth rate is within
range to what was observed prior to the establishment of the Advancing
American Kidney Health initiative in 2019 and it also shows that the
COVID-19 PHE did not cause the home dialysis growth assumption to
become invalid. The 3-percentage point per year average max growth rate
will, in effect, move the average market peritoneal dialysis rate
(about 10 percent) to the highest market baseline peritoneal dialysis
rate (for example, Bend, Oregon HRR at about 25 percent), which we
believe is a reasonable upper bound on growth over the duration of the
ETC Model for the purposes of this actuarial model.
Aggregation groups were assumed to achieve anywhere from zero to
100 percent of such maximum growth in any given year. Thus, the average
projected growth for the share of maintenance dialysis provided in the
home was 1.5-percentage points per year (expressed as the percentage of
total dialysis). In contrast, we do not include an official assumption
that the overall number of kidney transplants will increase and provide
justification for this assumption in sections VI.C.2.b.(4) and
VI.C.2.b.(5) of the Specialty Care Models final rule (85 FR 61355).
However, as part of the sensitivity analysis for the savings
calculations for the model, we laid out a different savings scenario if
the ETC Learning Collaborative described in VI.C.2.b.(6) of the
Specialty Care Models final rule (85 FR 61355) were to be successful in
decreasing the discard rate of deceased donor kidneys and increasing
the utilization rate of deceased donor kidneys that have been
retrieved.
(4). Sensitivity Analysis: Medicare Savings Estimate--Results for the
10th and 90th Percentiles
Using the primary specification for the Medicare estimate with
preset benchmark updates for home dialysis and transplant waitlist
rates, we compared the results for the top 10th and 90th percentiles of
the 400 individual simulations to the average of all simulation results
reported in Table 18. Since the impact on Medicare spending for the ETC
Model using the present benchmark updates is estimated to be in savings
rather than losses, the top 10th and 90th percentiles represent the
most optimistic and conservative projections, respectively. The overall
net PPA and HDPA for the top 10th and 90th percentiles using the
present benchmark updates method are $102 million in savings and $9
million in losses (encompassing the mean estimate of $43 million in
savings in Table 18). The overall uncertainty of the impact of the
model is further illustrated in Table 19, the change from the CY 2022
ESRD
[[Page 62017]]
PPS proposed rule, where the mean $10 million dollars in savings
reported for the Overall PPA Net & HDPA has $64 million in savings and
$97 million in losses, for the top 10th and 90th percentiles,
respectively.
(5). Effects on the Home Dialysis Rate
The two changes in this final rule have the potential to increase
ETC Participants' home dialysis rate, therefore reducing the overall
savings to Medicare estimate. First, this final rule modifies the home
dialysis rate equation by adding 0.5 multiplied by the sum of the self-
dialysis beneficiary months and the in-center nocturnal dialysis
beneficiary months to the numerator such that 1-beneficiary year is
comprised of 12-beneficiary months for Managing Clinicians and all ESRD
facilities, regardless of ownership.
However, less than 1 percent of beneficiaries eligible for
attribution into the ETC Model were receiving either self-dialysis or
nocturnal in-center dialysis in CY 2019. In addition, in CY 2020, the
annual growth rate decreased by 89.9 and 91.3 percent for beneficiaries
receiving self-dialysis or in-center nocturnal dialysis, respectively.
The sharp decline in these dialysis modalities is potentially in
response to the COVID-19 pandemic. The low historical take-up for self-
dialysis and shortage of historical years for in-center nocturnal
dialysis (that is, a nocturnal dialysis claims line instruction became
effective in 2017) result in these modifications having an
insignificant impact on the savings to Medicare.
The second change in this final rule that has the potential to
generate higher PPA scores for a limited subset of providers and
therefore a small negative impact on estimated savings for the Model is
the Health Equity Incentive. The Health Equity Incentive proposed in
the CY 2022 ESRD PPS proposed rule (86 FR 36427) would have rewarded
ETC Participants with an additional 0.5 points to their improvement
score who improved the home dialysis rate (or transplant rate) among
their attributed beneficiaries who are dual eligible or receive the LIS
by at least 5 percentage points between the Benchmark Year to the MY.
In this final rule, the threshold to earn the 0.5 improvement points
was reduced to a 2.5-percentage point increase from the Benchmark Year
to the MY. The $10 million decrease in the savings to Medicare estimate
in this final rule relative to the CY 2022 ESRD PPS proposed rule was
primarily due to the change in the Health Equity Incentive threshold.
(6). Effects on Kidney Transplantation
Kidney transplantation is considered the optimal treatment for most
ESRD beneficiaries. The PPA includes a one-third weight on the ESRD
facilities' or Managing Clinician's transplant waitlist rate, with the
ultimate goal of increasing the rate of kidney transplantation.
However, the changes in this final rule do not impact our decision in
the CY 2022 ESRD PPS proposed rule or the Specialty Care Models final
rule to not include an assumption that the overall number of kidney
transplants will increase. The number of ESRD patients on the kidney
transplant waitlist has for many years far exceeded the annual number
of transplants performed. Transplantation rates have not increased to
meet such demand because of the limited supply of deceased donor
kidneys. The U.S. Renal Data System \282\ reported 22,393 kidney
transplants in 2018 compared to a kidney transplant waiting list \283\
of over 98,000. Refer to section VI.C.2.b(4) in the Specialty Care
Models final rule (85 FR 61355) for a detailed justification for our
assumption that the overall number of kidney transplants will not
increase in response to ESRD facilities and Managing Clinicians
participating in the ETC Model.
---------------------------------------------------------------------------
\282\ United States Renal Data System. 2020. ``ADR Reference
Table E6 Renal Transplants by Donor Type.'' https://adr.usrds.org/2020/reference-tables.
\283\ Organ Procurement and Transplantation Network. 2021.
``Current US Waiting List, Overall by Organ.'' https://optn.transplant.hrsa.gov/data/view-data-reports/national-data/#.
---------------------------------------------------------------------------
(7). Effects of the Transplant Rate
The ETC Model continues to include the transplant rate described in
the Specialty Care Models final rule (Sec. 512.365).
The change in this final rule that has the potential to generate
higher scores for a limited subset of ETC Participants and therefore a
small reduction in the estimated savings for the Model relative to the
CY 2022 ESRD PPS proposed rule is the modification to the Health Equity
Incentive threshold. By lowering the threshold for earning the Health
Equity Incentive threshold in this final rule relative to the threshold
proposed in the CY 2022 ESRD PPS proposed rule, more ETC Participants
have the potential to earn the additional 0.5 points to their
improvement score.
(8). Effects on Kidney Disease Patient Education Services and HD
Training Add-Ons
The changes to the ETC Model finalized in this final rule relative
to the Specialty Care Models final rule do not impact the findings
reported for the effects of the ETC Model on the Kidney Disease Patient
education services and HD training add-ons described in section
VI.C.2.b(6) in the Specialty Care Models final rule (85 FR 61356-57).
(9). Effects on Medicare Beneficiaries
The changes in this final rule relative to the CY 2022 ESRD PPS
proposed rule could incentivize ESRD facilities and Managing Clinicians
serving dual eligible or LIS recipient Medicare beneficiaries to
potentially improve access to care for those beneficiaries. The final
rule's changes could also marginally improve uptake of the in-center
nocturnal dialysis treatment modality since this dialysis method was
not directly incentivized (that is, accounted for in the home dialysis
rate for all ESRD facilities) under the ETC Model. The changes made to
the final rule may have marginally increased uptake of in-center
nocturnal dialysis for ESRD facilities owned in whole or in part by an
ETC LDO relative to the CY 2022 ESRD PPS proposed rule, which had
proposed to exclude ESRD facilities owned in whole or in part by an ETC
LDO from the in-center nocturnal dialysis policy.
As noted in section VI.C.3.B of the Specialty Care Models final
rule (85 FR 61357), we continue to anticipate that the ETC Model will
have a negligible impact on the cost to beneficiaries receiving
dialysis. Under current policy, Medicare FFS beneficiaries are
generally responsible for 20 percent of the allowed charge for services
furnished by providers and suppliers. This policy will remain the same
for most beneficiaries under the ETC Model. However, we will waive
certain requirements of title XVIII of the Act as necessary to test the
PPA and HDPA under the ETC Model and to hold beneficiaries harmless
from any effect of these payment adjustments on cost sharing. In
addition, the Medicare beneficiary's quality of life has the potential
to improve if the beneficiary elects to have home dialysis, or
nocturnal in-center dialysis, as opposed to in-center dialysis. Studies
have found that home dialysis patients experienced improved quality of
life as a result of their ability to continue regular work schedules or
life plans;[thinsp]as well as better overall, physical, and
psychological health in comparison to other dialysis options.
(10). Alternatives Considered
Throughout this final rule, we have identified our policies and
alternatives that we have considered, and provided information as to
the likely effects of
[[Page 62018]]
these alternatives and the rationale for each of our policies.
This final rule addresses a model specific to ESRD. It provides
descriptions of the requirements that we will waive, identifies the
performance metrics and payment adjustments to be tested, and presents
rationales for our changes, and where relevant, alternatives that we
considered. We carefully considered the alternatives to this final
rule, including the degree that benchmark targets should be
prospectively updated to provide greater transparency to ETC
Participants while preserving the expectation for model net savings for
the program. For context related to alternatives previously considered
when establishing the ETC Model we refer readers to the Specialty Cares
Models final rule (85 FR 61114) for more information on policy-related
stakeholder comments, our responses to those comments, and statements
of final policy preceding the limited modifications proposed here.
D. Accounting Statement
As required by OMB Circular A-4 (available at https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/circulars/A4/a-4.pdf), in Table 20, we have prepared an accounting statement showing
the classification of the transfers and costs associated with the
various provisions of this final rule.
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In accordance with the provisions of Executive Order 12866, this
final rule was reviewed by the Office of Management and Budget.
E. Regulatory Flexibility Act Analysis (RFA)
The Regulatory Flexibility Act (RFA) requires agencies to analyze
options for regulatory relief of small entities, if a rule has a
significant impact on a substantial number of small entities. For
purposes of the RFA, small entities include small businesses, nonprofit
organizations, and small governmental jurisdictions. Approximately 11
percent of ESRD dialysis facilities are considered small entities
according to the Small Business Administration's (SBA) size standards,
which classifies small businesses as those dialysis facilities having
total revenues of less than $41.5 million in any 1 year. Individuals
and states are not included in the definitions of a small entity. For
more information on SBA's size standards, see the Small Business
Administration's website at http://www.sba.gov/content/small-business-size-standards (Kidney Dialysis Centers are listed as 621492 with a
size standard of $41.5 million).
When viewed as individual entities, as opposed to being a part of a
LDO, there are approximately 1,295 (~17 percent of total number of ESRD
facilities) ESRD facilities that provide fewer than 4,000 treatments
per year. With a low volume payment adjustment, each facility generates
revenue from dialysis treatments of ~$1.26 million per year per
facility. This is shown in the Table 21.
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We do not believe ESRD facilities are operated by small government
entities such as counties or towns with populations of 50,000 or less,
and therefore, they are not enumerated or included in this estimated
RFA analysis. Individuals and states are not included in the definition
of a small entity.
For purposes of the RFA, we estimate that approximately 11 percent
of ESRD facilities are small entities as that term is used in the RFA
(which includes small businesses, nonprofit organizations, and small
governmental jurisdictions). This amount is based on the number of ESRD
facilities shown in the ownership category in Table 9. Using the
definitions in this ownership category, we consider 515 facilities that
are independent and 378 facilities that are shown as hospital-based to
be small entities. The ESRD facilities that are owned and operated by
LDOs and regional chains would have total revenues of more than $41.5
million in any year when the total revenues for all locations are
combined for each business (LDO or regional chain), and are not,
therefore, included as small entities.
For the ESRD PPS updates proposed in this rule, a hospital-based
ESRD facility (as defined by type of ownership, not by type of dialysis
facility) is estimated to receive a 1.3 percent increase in payments
for CY 2022. An independent facility (as defined by ownership type) is
estimated to receive a 1.1 percent increase in payments for CY 2022.
For AKI dialysis, we are unable to estimate whether patients would
go to ESRD facilities, however, we have estimated there is a potential
for $52 million in payment for AKI dialysis treatments that could
potentially be furnished in ESRD facilities.
For the ESRD QIP, we estimate that of the 1,788 ESRD facilities
expected to receive a payment reduction as a result of their
performance on the PY 2024 ESRD QIP, 331 are ESRD small entity
facilities. We present these findings in Table 11 (``Estimated
Distribution of PY 2024 ESRD QIP Payment Reductions'') and Table 13
(``Estimated Impact of QIP Payment Reductions to ESRD Facilities for PY
2024'').
For ETC Model, this final rule includes as ETC Participants
Managing Clinicians and ESRD facilities required to participate in the
Model pursuant to Sec. 512.325(a). We assume for the purposes of the
regulatory impact analysis that the great majority of Managing
Clinicians are small entities and that the greater majority of ESRD
facilities are not small entities. Throughout the final rule we
describe how the adjustments to certain payments for dialysis services
and dialysis-related services furnished to ESRD beneficiaries may
affect Managing Clinicians and ESRD facilities participating in the ETC
Model. The great majority of Managing Clinicians are small entities by
meeting the SBA definition of a small business (having minimum revenues
of less than $8 million to $41.5 million in any 1 year, varying by type
of provider and highest for hospitals) with a minimum threshold for
small business size of $41.5 million (https://www.sba.gov/document/support--table-size-standards http://www.sba.gov/content/small-businesssize-standards). The great majority of ESRD facilities are not
small entities, as they are owned, partially or entirely by entities
that do not meet the SBA definition of small entities.
The HDPA in the ETC Model is a positive adjustment on payments for
specified home dialysis and home dialysis-related services. The PPA in
the ETC Model, which includes both positive and negative adjustments on
payments for dialysis services and dialysis-related services, excludes
aggregation groups with fewer than 132 attributed beneficiary-months
during the relevant year.
The aggregation methodology groups ESRD facilities owned in whole
or in part by the same dialysis organization within a Selected
Geographic Area and Managing Clinicians billing under the same TIN
within a Selected Geographic Area. This aggregation policy increases
the number of beneficiary months, and thus statistical reliability, of
the ETC Participant's home dialysis and transplant rate for ESRD
facilities that are owned in whole or in part by the same dialysis
organization and for Managing Clinicians that share a TIN with other
Managing Clinicians.
Taken together, the low volume threshold exclusions and aggregation
policies previously described, coupled with the fact that the ETC Model
will affect Medicare payment only for select services furnished to
Medicare FFS beneficiaries; we have determined that the provisions of
the final rule will not have a significant impact on spending for a
substantial number of small entities (defined as greater than 5 percent
impact).
Therefore, the Secretary has determined that this final rule will
not have a significant economic impact on a substantial number of small
entities. The economic impact assessment is based on estimated Medicare
payments (revenues) and HHS's practice in interpreting the RFA is to
consider effects economically ``significant'' only if greater than 5
percent of providers reach a threshold of 3 to 5 percent or more of
total revenue or total costs.
In addition, section 1102(b) of the Act requires us to prepare a
RIA 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
[[Page 62020]]
located outside of a metropolitan statistical area and has fewer than
100 beds. We do not believe this final rule will have a significant
impact on operations of a substantial number of small rural hospitals
because most dialysis facilities are freestanding. While there are 122
rural hospital-based dialysis facilities, we do not know how many of
them are based at hospitals with fewer than 100 beds. However, overall,
the 122 rural hospital-based dialysis facilities will experience an
estimated 1.0 percent increase in payments.
Therefore, the Secretary has determined that this final rule will
not have a significant impact on the operations of a substantial number
of small rural hospitals.
F. Unfunded Mandates Reform Act Analysis (UMRA)
Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also
requires that agencies assess anticipated costs and benefits before
issuing any rule whose mandates require spending in any 1 year of $100
million in 1995 dollars, updated annually for inflation. In 2021, that
threshold is approximately $158 million. This final rule does not
mandate any requirements for State, local, or tribal governments in the
aggregate, or by the private sector. Moreover, HHS interprets UMRA as
applying only to unfunded mandates. We do not interpret Medicare
payment rules as being unfunded mandates, but simply as conditions for
the receipt of payments from the Federal Government for providing
services that meet Federal standards. This interpretation applies
whether the facilities or providers are private, State, local, or
tribal.
G. Federalism
Executive Order 13132 establishes certain requirements that an
agency must meet when it promulgates a proposed rule (and subsequent
final rule) that imposes substantial direct requirement costs on State
and local governments, preempts State law, or otherwise has federalism
implications. We have reviewed this final rule under the threshold
criteria of Executive Order 13132, Federalism, and have determined that
it will not have substantial direct effects on the rights, roles, and
responsibilities of states, local or Tribal governments.
H. Congressional Review Act
This final rule 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.
IX. Files Available to the Public via the Internet
The Addenda for the annual ESRD PPS proposed and final rulemakings
will no longer appear in the Federal Register. Instead, the Addenda
will be available only through the internet and is posted on the CMS
website at http://www.cms.gov/ESRDPayment/PAY/list.asp. In addition to
the Addenda, limited data set files are available for purchase at
http://www.cms.gov/Research-Statistics-Data-and-Systems/Files-for-Order/LimitedDataSets/EndStageRenalDiseaseSystemFile.html. Readers who
experience any problems accessing the Addenda or LDS files, should
contact [email protected].
Chiquita Brooks-LaSure, Administrator of the Centers for Medicare &
Medicaid Services, approved this document on October 28, 2021.
List of Subjects
42 CFR Part 413
Diseases, Health facilities, Medicare, Puerto Rico, Reporting and
recordkeeping requirements.
42 CFR Part 512
Administrative practice and procedure, 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 follows:
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
1. 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
2. Section 413.177 is amended by revising paragraph (a) introductory
text to read as follows:
Sec. 413.177 Quality incentive program payment.
(a) With respect to renal dialysis services as defined under Sec.
413.171, except for those renal dialysis services furnished during
payment year 2022, in the case of an ESRD facility that does not earn
enough points under the program described at Sec. 413.178 to meet or
exceed the minimum total performance score (as defined at Sec.
413.178(a)(8)) established by CMS for a payment year (as defined at
Sec. 413.178(a)(10)), payments otherwise made to the facility under
Sec. 413.230 for renal dialysis services during the payment year will
be reduced by up to 2 percent as follows:
* * * * *
0
3. Section 413.178 is amended by adding paragraph (h) to read as
follows:
Sec. 413.178 ESRD quality incentive program.
* * * * *
(h) Special rule for payment year 2022. (1) CMS will calculate a
measure rate for all measures specified by CMS under paragraph (c) of
this section for the PY 2022 ESRD QIP but will not score facility
performance on any of those measures or calculate a TPS for any
facility under paragraph (e) of this section.
(2) CMS will not establish a mTPS for PY 2022.
PART 512--RADIATION ONCOLOGY MODEL AND END STAGE RENAL DISEASE
TREATMENT CHOICES MODEL
0
4. The authority citation for part 512 continues to read as follows:
Authority: 42 U.S.C. 1302, 1315(a), and 1395hh.
0
5. Section 512.160 is amended by adding paragraph (a)(9) and revising
paragraph (b)(6) to read as follows:
Sec. 512.160 Remedial action.
(a) * * *
(9) For the ETC Model only, has misused or disclosed the
beneficiary-identifiable data in a manner that violates any applicable
statutory or regulatory requirements or that is otherwise non-compliant
with the provisions of the applicable data sharing agreement.
(b) * * *
(6) In the ETC Model only:
(i) Terminate the ETC Participant from the ETC Model.
(ii) Suspend or terminate the ability of the ETC Participant,
pursuant to Sec. 512.397(c), to reduce or waive the coinsurance for
kidney disease patient education services.
* * * * *
0
6. Section 512.310 is amended by adding definitions for ``Clinical
staff'', ``Health Equity Incentive'', and
[[Page 62021]]
``Qualified staff'' in alphabetical order to read as follows:
Sec. 512.310 Definitions.
* * * * *
Clinical staff means a licensed social worker or registered
dietician/nutrition professional who furnishes services for which
payment may be made under the physician fee schedule under the
direction of and incident to the services of the Managing Clinician who
is an ETC Participant.
* * * * *
Health Equity Incentive means the amount added to the ETC
Participant's improvement score, calculated as described in Sec.
512.370(c)(1), if the ETC Participant's aggregation group demonstrated
sufficient improvement on the home dialysis rate or transplant rate for
attributed beneficiaries who are dual eligible or Medicare Low Income
Subsidy (LIS) recipients between the Benchmark Year and the MY.
* * * * *
Qualified staff means both clinical staff and any qualified person
(as defined at Sec. 410.48(a) of this chapter) who is an ETC
Participant.
* * * * *
0
7. Section 512.360 is amended by revising paragraph (c)(2)(ii)
introductory text and adding paragraph (c)(2)(iii) to read as follows:
Sec. 512.360 Beneficiary population and attribution.
* * * * *
(c) * * *
(2) * * *
(ii) For MY1 and MY2, a Pre-emptive LDT Beneficiary who is not
excluded based on the criteria in paragraph (b) of this section is
attributed to the Managing Clinician with whom the beneficiary has had
the most claims between the start of the MY and the month in which the
beneficiary received the transplant for all months between the start of
the MY and the month of the transplant.
* * * * *
(iii) For MY3 through MY10, a Pre-emptive LDT Beneficiary who is
not excluded based on the criteria in paragraph (b) of this section is
attributed to the Managing Clinician who submitted the most claims for
services furnished to the beneficiary in the 365 days preceding the
date in which the beneficiary received the transplant.
(A) If no Managing Clinician has had the most claims for a given
Pre-emptive LDT Beneficiary such that multiple Managing Clinicians each
had the same number of claims for that beneficiary in the 365 days
preceding the date of the transplant, the Pre-emptive LDT Beneficiary
is attributed to the Managing Clinician associated with the latest
claim service date at the claim line through date during the 365 days
preceding the date of the transplant.
(B) If no Managing Clinician had the most claims for a given Pre-
emptive LDT Beneficiary such that multiple Managing Clinicians each had
the same number of claims for that beneficiary in the 365 days
preceding the date of the transplant, and more than one of those
Managing Clinicians had the latest claim service date at the claim line
through date during the 365 days preceding the date of the transplant,
the Pre-emptive LDT Beneficiary is randomly attributed to one of these
Managing Clinicians.
(C) The Pre-emptive LDT Beneficiary is considered eligible for
attribution under this paragraph (c)(2)(iii) if the Pre-emptive LDT
Beneficiary has at least 1-eligible month during the 12-month period
that includes the month of the transplant and the 11 months prior to
the month of the transplant. An eligible month refers to a month during
which the Pre-emptive LDT Beneficiary not does not meet exclusion
criteria in paragraph (b) of this section.
0
8. Section 512.365 is amended by revising paragraphs (b)(1)(ii),
(b)(2)(ii), (c)(1)(i)(A), (c)(1)(ii)(A), (c)(2)(i)(A), and
(c)(2)(ii)(A)(1) and (2) to read as follows:
Sec. 512.365 Performance assessment.
* * * * *
(b) * * *
(1) * * *
(ii) For MY1 and MY2, the numerator is the total number of home
dialysis treatment beneficiary years plus one half the total number of
self dialysis treatment beneficiary years for attributed ESRD
Beneficiaries during the MY. For MY3 through MY10, the numerator is the
total number of home dialysis treatment beneficiary years, plus one
half the total number of self dialysis treatment beneficiary years,
plus one half the total number of nocturnal in center dialysis
beneficiary years for attributed ESRD Beneficiaries during the MY.
(A) Home dialysis treatment beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received maintenance dialysis at home, such that 1-
beneficiary year is comprised of 12-beneficiary months. Months in which
an attributed ESRD Beneficiary received maintenance dialysis at home
are identified by claims with Type of Bill 072X and condition codes 74
or 76.
(B) Self dialysis treatment beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received self dialysis in center, such that 1-beneficiary
year is comprised of 12-beneficiary months. Months in which an
attributed ESRD Beneficiary received self dialysis are identified by
claims with Type of Bill 072X and condition code 72.
(C) Nocturnal in center dialysis beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received nocturnal in center dialysis, such that 1-
beneficiary year is comprised of 12-beneficiary months. Months in which
an attributed ESRD Beneficiary received nocturnal in center dialysis
are identified by claims with Type of Bill 072X and modifier UJ.
* * * * *
(2) * * *
(ii) For MY1 and MY2, the numerator is the total number of home
dialysis treatment beneficiary years for attributed ESRD Beneficiaries
during the MY plus one half the total number of self dialysis treatment
beneficiary years. For MY3 through MY10, the numerator is the total
number of home dialysis treatment beneficiary years, plus one half the
total number of self dialysis treatment beneficiary years, plus one
half the total number of nocturnal in center dialysis beneficiary years
for attributed ESRD Beneficiaries during the MY.
(A) Home dialysis treatment beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received maintenance dialysis at home, such that 1-
beneficiary year is comprised of 12-beneficiary months. Months in which
an attributed ESRD Beneficiary received maintenance dialysis at home
are identified by claims with CPT codes 90965 or 90966.
(B) Self-dialysis treatment beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received self dialysis in center, such that 1-beneficiary
year is comprised of 12-beneficiary months. Months in which an
attributed ESRD Beneficiary received self dialysis are identified by
claims with Type of Bill 072X and condition code 72.
(C) Nocturnal in center dialysis beneficiary years included in the
numerator are composed of those months during which attributed ESRD
Beneficiaries received nocturnal in center dialysis, such that 1-
beneficiary year is comprised of 12-beneficiary
[[Page 62022]]
months. Months in which an attributed ESRD Beneficiary received
nocturnal in center dialysis are identified by claims with Type of Bill
072X and modifier UJ.
* * * * *
(c) * * *
(1) * * *
(i) * * *
(A) The denominator is the total dialysis treatment beneficiary
years for attributed ESRD Beneficiaries during the MY. Dialysis
treatment beneficiary years included in the denominator are composed of
those months during which an attributed ESRD beneficiary received
maintenance dialysis at home or in an ESRD facility, such that 1-
beneficiary year is comprised of 12-beneficiary months. For MY1 and
MY2, months during which an attributed ESRD Beneficiary received
maintenance dialysis are identified by claims with Type of Bill 072X,
excluding claims for beneficiaries who were 75 years of age or older at
any point during the month. For MY3 through MY10, months during which
an attributed ESRD Beneficiary received maintenance dialysis are
identified by claims with Type of Bill 072X, excluding claims for
beneficiaries who were 75 years of age or older at any point during the
month, or had a vital solid organ cancer diagnosis and were receiving
treatment with chemotherapy or radiation for vital solid organ cancer
during the MY.
(1) An attributed ESRD Beneficiary had a diagnosis of vital solid
organ cancer in an MY if the beneficiary had any of the following
diagnosis codes on any claim during the MY or the 6 months prior to the
start of the MY: C22.0, C22.1, C22.2, C22.3, C22.4, C22.7, C22.8,
C22.9, C34.10-C34.12, C34.2, C34.30-C34.32, C34.80-C34.82, C34.90-
C34.92, C38.0, C38.8, C46.50-C46.52, C64.1, C64.2, C64.2, C78.00-
C78.02, C78.7, C79.00-C79.02, C7A.090, C7A.093, or C7B.02.
(2) An attributed ESRD Beneficiary received treatment with
chemotherapy or radiation for vital solid organ cancer during the MY if
the beneficiary had a claim with any of the following procedure codes
on any claim during the MY or the 6 months prior to the start of the
MY:
(i) CPT[supreg] 96401-96402, 96405-96406, 96409, 96411, 96413,
96415-96417, 96420, 96422-26423, 96425, 96440, 96446, 96549, 77373,
77401-77402, 77407, 77412, 77423, 77424-77425, 77520, 77522-77523,
77525, 77761-77763, 77770-77772, 77778, 77789, 77799, 79005, 79101,
79200, 79300, 79403, 79440, 79445, 79999.
(ii) ICD-10-PCS[supreg] DB020ZZ, DB021ZZ, DB022ZZ, DB023Z0,
DB023ZZ, DB024ZZ, DB025ZZ, DB026ZZ, DB1297Z, DB1298Z, DB1299Z, DB129BZ,
DB129CZ, DB129YZ, DB12B6Z, DB12B7Z, DB12B8Z, DB12B9Z, DB12BB1, DB12BBZ,
DB12BCZ, DB12BYZ, DB22DZZ, DB22HZZ, DB22JZZ, DBY27ZZ, DBY28ZZ, DBY2FZZ,
DBY2KZZ, DB070ZZ, DB071ZZ, DB072ZZ, DB073Z0, DB073ZZ, DB074ZZ, DB075ZZ,
DB076ZZ, DB1797Z, DB1798Z, DB1799Z, DB179BZ, DB179CZ, DB179YZ, DB17B6Z,
DB17B7Z, DB17B8Z, DB17B9Z, DB17BB1, DB17BBZ, DB17BCZ, DB17BYZ, DB27DZZ,
DB27HZZ, DB27JZZ, DBY77ZZ, DBY78ZZ, DBY7FZZ, DBY7KZZ, DF000ZZ, DF001ZZ,
DF002ZZ, DF003Z0, DF003ZZ, DF004ZZ, DF005ZZ, DF006ZZ, DF1097Z, DF1098Z,
DF1099Z, DF109BZ, DF109CZ, DF109YZ, DF10B6Z, DF10B7Z, DF10B8Z, DF10B9Z,
DF10BB1, DF10BBZ, DF10BCZ, DF10BYZ, DF20DZZ, DF20HZZ, DF20JZZ, DFY07ZZ,
DFY08ZZ, DFY0CZZ, DFY0FZZ, DFY0KZZ, DT000ZZ, DT001ZZ, DT002ZZ, DT003Z0,
DT003ZZ, DT004ZZ, DT005ZZ, DT006ZZ, DT1097Z, DT1098Z, DT1099Z, DT109BZ,
DT109CZ, DT109YZ, DT10B6Z, DT10B7Z, DT10B8Z, DT10B9Z, DT10BB1, DT10BBZ,
DT10BCZ, DT10BYZ, DT20DZZ, DT20HZZ, DT20JZZ, DTY07ZZ, DTY08ZZ, DTY0CZZ,
DTY0FZZ, DW020ZZ, DW021ZZ, DW022ZZ, DW023Z0, DW023ZZ, DW024ZZ, DW025ZZ,
DW026ZZ, DW1297Z, DW1298Z, DW1299Z, DW129BZ, DW129CZ, DW129YZ, DW12B6Z,
DW12B7Z, DW12B8Z, DW12B9Z, DW12BB1, DW12BBZ, DW12BCZ, DW12BYZ, DW22DZZ,
DW22HZZ, DW22JZZ, DWY27ZZ, DWY28ZZ, DWY2FZZ, DW030ZZ, DW031ZZ, DW032ZZ,
DW033Z0, DW033ZZ, DW034ZZ, DW035ZZ, DW036ZZ, DW1397Z, DW1398Z, DW1399Z,
DW139BZ, DW139CZ, DW139YZ, DW13B6Z, DW13B7Z, DW13B8Z, DW13B9Z, DW13BB1,
DW13BBZ, DW13BCZ, DB13BYZ, DW23DZZ, DW23HZZ, DW23JZZ, DWY37ZZ, DWY38ZZ,
DWY3FZZ, DW050ZZ, DW051ZZ, DW052ZZ, DW053Z0, DW053ZZ, DW054ZZ, DW055ZZ,
DW056ZZ, DWY57ZZ, DWY58ZZ, DWY5FZZ, DWY5GDZ, DWY5GFZ, DWY5GGZ, DWY5GHZ,
DWY5GYZ.
* * * * *
(ii) * * *
(A) The denominator is the total dialysis treatment beneficiary
years for attributed ESRD Beneficiaries during the MY. Dialysis
treatment beneficiary years included in the denominator are composed of
those months during which an attributed ESRD Beneficiary received
maintenance dialysis at home or in an ESRD facility, such that 1-
beneficiary year is comprised of 12-beneficiary months. For MY1 and
MY2, months during which an attributed ESRD Beneficiary received
maintenance dialysis are identified by claims with Type of Bill 072X,
excluding claims for beneficiaries who were 75 years of age or older at
any point during the month. For MY3 through MY10, months during which
an attributed ESRD Beneficiary received maintenance dialysis are
identified by claims with Type of Bill 072X, excluding claims for
beneficiaries who were 75 years of age or older at any point during the
month, or had a vital solid organ cancer diagnosis and were receiving
treatment with chemotherapy or radiation for vital solid organ cancer
during the MY. Months in which an attributed ESRD Beneficiary had a
diagnosis of vital solid organ cancer are identified as described in
paragraph (c)(1)(i)(A)(1) of this section. Months in which an
attributed ESRD Beneficiary received treatment with chemotherapy or
radiation for vital solid organ cancer are identified as described in
paragraph (c)(1)(i)(A)(2) of this section.
* * * * *
(2) * * *
(i) * * *
(A) The denominator is the total dialysis treatment beneficiary
years for attributed ESRD Beneficiaries during the MY. Dialysis
treatment beneficiary years included in the denominator are composed of
those months during which an attributed ESRD Beneficiary received
maintenance dialysis at home or in an ESRD facility, such that 1-
beneficiary year is comprised of 12-beneficiary months. For MY1 and
MY2, months during which an attributed ESRD Beneficiary received
maintenance dialysis are identified by claims with CPT codes 90957,
90958, 90959, 90960, 90961, 90962, 90965, or 90966, excluding claims
for beneficiaries who were 75 years of age or older at any point during
the month. For MY3 through MY10, months during which an attributed ESRD
Beneficiary received maintenance dialysis are identified by claims with
CPT codes 90957, 90958, 90959, 90960, 90961, 90962, 90965, or 90966,
excluding claims for beneficiaries who were 75 years of age or older at
any point during the month, or had a vital solid organ cancer diagnosis
and were receiving treatment with chemotherapy or radiation for vital
solid organ cancer during the MY. Months in which an attributed ESRD
[[Page 62023]]
Beneficiary had a diagnosis of vital solid organ cancer are identified
as described in paragraph (c)(1)(i)(A)(1) of this section. Months in
which an attributed ESRD Beneficiary received treatment with
chemotherapy or radiation for vital solid organ cancer are identified
as described in paragraph (c)(1)(i)(A)(2) of this section.
* * * * *
(ii) * * *
(A) * * *
(1) Dialysis treatment beneficiary years included in the
denominator are composed of those months during which an attributed
ESRD Beneficiary received maintenance dialysis at home or in an ESRD
facility, such that 1-beneficiary year is comprised of 12-beneficiary
months. For MY1 and MY2, months during which an attributed ESRD
Beneficiary received maintenance dialysis are identified by claims with
CPT codes 90957, 90958, 90959, 90960, 90961, 90962, 90965, or 90966,
excluding claims for beneficiaries who were 75 years of age or older at
any point during the month. For MY3 through MY10, months during which
an attributed ESRD Beneficiary received maintenance dialysis are
identified by claims with CPT codes 90957, 90958, 90959, 90960, 90961,
90962, 90965, or 90966, excluding claims for beneficiaries who were 75
years of age or older at any point during the month, or had a vital
solid organ cancer diagnosis and were receiving treatment with
chemotherapy or radiation for vital solid organ cancer during the MY.
Months in which an attributed ESRD Beneficiary had a vital solid organ
cancer diagnosis are identified as described in paragraph
(c)(1)(i)(A)(1) of this section. Months in which an attributed ESRD
Beneficiary received treatment with chemotherapy or radiation for vital
solid organ cancer are identified as described in paragraph
(c)(1)(i)(A)(2) of this section.
(2) MY1 and MY2, Pre-emptive LDT beneficiary years included in the
denominator are composed of those months during which a Pre-emptive LDT
Beneficiary is attributed to a Managing Clinician, from the beginning
of the MY up to and including the month of the living donor transplant.
For MY3 through MY10, Pre-emptive LDT beneficiary years included in the
denominator are composed of those months during which a Pre-emptive LDT
Beneficiary is attributed to a Managing Clinician, from the beginning
of the MY up to and including the month of the living donor transplant,
excluding beneficiaries who had a vital solid organ cancer diagnosis
and were receiving treatment with chemotherapy or radiation for vital
solid organ cancer during the MY. Months in which an attributed ESRD
Beneficiary had a vital solid organ cancer diagnosis are identified as
described in paragraph (c)(1)(i)(A)(1) of this section. Months in which
an attributed ESRD Beneficiary received treatment with chemotherapy or
radiation for vital solid organ cancer are identified as described in
paragraph (c)(1)(i)(A)(2) of this section. Pre-emptive LDT
Beneficiaries are identified using information about living donor
transplants from the SRTR Database and Medicare claims data.
* * * * *
0
9. Section 512.370 is amended by revising paragraphs (b), (c), and (d)
to read as follows:
Sec. 512.370 Benchmarking and scoring.
* * * * *
(b) Achievement scoring. CMS assesses ETC Participant performance
at the aggregation group level on the home dialysis rate and transplant
rate against achievement benchmarks constructed based on the home
dialysis rate and transplant rate among aggregation groups of ESRD
facilities and Managing Clinicians located in Comparison Geographic
Areas during the Benchmark Year. Achievement benchmarks are calculated
as described in paragraph (b)(1) of this section and, for MY3 through
MY10, are stratified as described in paragraph (b)(2) of this section.
(1) Achievement benchmarks. CMS uses the following scoring
methodology to assess an ETC Participant's achievement score.
Table 1 to Sec. 512.370(b)(1)--ETC Model Schedule of PPA Achievment Benchmarks by Measurement Year
----------------------------------------------------------------------------------------------------------------
MY1 and MY2 MY3 and MY4 MY5 and MY6 MY7 and MY8 MY9 and MY10 Points
----------------------------------------------------------------------------------------------------------------
90th+ Percentile of benchmark 1.1 * (90th+ 1.2 * (90th+ 1.3 * (90th+ 1.4 * (90th+ 2
rates for Comparison Percentile of Percentile of Percentile of Percentile of
Geographic Areas during the benchmark rates benchmark rates benchmark rates benchmark rates
Benchmark Year. for Comparison for Comparison for Comparison for Comparison
Geographic Geographic Geographic Geographic
Areas during Areas during Areas during Areas during
the Benchmark the Benchmark the Benchmark the Benchmark
Year). Year). Year). Year).
75th+ Percentile of benchmark 1.1 * (75th+ 1.2 * (75th+ 1.3 * (75th+ 1.4 * (75th+ 1.5
rates for Comparison Percentile of Percentile of Percentile of Percentile of
Geographic Areas during the benchmark rates benchmark rates benchmark rates benchmark rates
Benchmark Year. for Comparison for Comparison for Comparison for Comparison
Geographic Geographic Geographic Geographic
Areas during Areas during Areas during Areas during
the. the Benchmark the Benchmark the Benchmark
Benchmark Year). Year). Year). Year).
50th+ Percentile of benchmark 1.1 * (50th+ 1.2 * (50th+ 1.3 * (50th+ 1.4 * (50th+ 1
rates for Comparison Percentile of Percentile of Percentile of Percentile of
Geographic Areas during the benchmark rates benchmark rates benchmark rates benchmark rates
Benchmark Year. for Comparison for Comparison for Comparison for Comparison
Geographic Geographic Geographic Geographic
Areas during Areas during Areas during Areas during
the Benchmark the Benchmark the Benchmark the Benchmark
Year). Year). Year). Year).
30th+ Percentile of benchmark 1.1 * (30th+ 1.2 * (30th+ 1.3 * (30th+ 1.4 * (30th+ 0.5
rates for Comparison Percentile of Percentile of Percentile of Percentile of
Geographic Areas during the benchmark rates benchmark rates benchmark rates benchmark rates
Benchmark Year. for Comparison for Comparison for Comparison for Comparison
Geographic Geographic Geographic Geographic
Areas during Areas during Areas during Areas during
the Benchmark the Benchmark the Benchmark the Benchmark
Year). Year). Year). Year).
<30th Percentile of benchmark 1.1 * (<30th 1.2 * (<30th 1.3 * (<30th 1.4 * (<30th 0
rates for Comparison Percentile of Percentile of Percentile of Percentile of
Geographic Areas during the benchmark rates benchmark rates benchmark rates benchmark rates
Benchmark Year. for Comparison for Comparison for Comparison for Comparison
Geographic Geographic Geographic Geographic
Areas during Areas during Areas during Areas during
the Benchmark the Benchmark the Benchmark the Benchmark
Year). Year). Year). Year).
----------------------------------------------------------------------------------------------------------------
(2) Stratifying achievement benchmarks. For MY3 through MY10, CMS
stratifies achievement benchmarks based on the proportion of
beneficiary years attributed to the aggregation group for which
attributed beneficiaries are dual eligible or LIS recipients during the
MY. An ESRD Beneficiary or Pre-emptive LDT Beneficiary is considered to
be dual eligible or a LIS recipient for a given month if at any point
during the month the beneficiary was dual eligible
[[Page 62024]]
or an LIS recipient based on Medicare administrative data. CMS
stratifies the achievement benchmarks into the following two strata:
(i) Stratum 1: 50 percent or more of attributed beneficiary years
during the MY are for beneficiaries who are dual eligible or LIS
recipients.
(ii) Stratum 2: Less than 50 percent of attributed beneficiary
years during the MY are for beneficiaries who are dual eligible or LIS
recipients.
(c) Improvement scoring. CMS assesses ETC Participant improvement
on the home dialysis rate and transplant rate against benchmarks
constructed based on the ETC Participant's aggregation group's
historical performance on the home dialysis rate and transplant rate
during the Benchmark Year to calculate the ETC Participant's
improvement score, as specified in paragraph (c)(1) of this section.
For MY3 through MY10, CMS assesses ETC Participant improvement on the
home dialysis rate and transplant rate for ESRD Beneficiaries and, if
applicable, Pre-emptive LDT Beneficiaries, who are dual eligible or LIS
recipients to determine whether to add the Health Equity Incentive to
the ETC Participant's improvement score, as specified in paragraph
(c)(2) of this section.
(1) Improvement score calculation. CMS uses the following scoring
methodology to assess an ETC Participant's improvement score.
(i) Greater than 10 percent improvement relative to the Benchmark
Year rate: 1.5 points
(ii) Greater than 5 percent improvement relative to the Benchmark
Year rate: 1 point
(iii) Greater than 0 percent improvement relative to the Benchmark
Year rate: 0.5 points
(iv) Less than or equal to the Benchmark Year rate: 0 points
(v) For MY3 through MY10, when calculating improvement benchmarks
constructed based on the ETC Participant's aggregation group's
historical performance on the home dialysis rate and transplant rate
during the Benchmark Year, CMS adds one beneficiary month to the
numerator of the home dialysis rate and adds one beneficiary month to
the numerator of the transplant rate, such that the Benchmark Year
rates cannot be equal to zero.
(2) Health Equity Incentive. CMS calculates the ETC Participant's
aggregation group's home dialysis rate and transplant rate as specified
in Sec. Sec. 512.365(b) and 512.365(c), respectively, using only
attributed beneficiary years comprised of months during the MY in which
ESRD Beneficiaries and, if applicable, Pre-emptive LDT Beneficiaries,
are dual eligible or LIS recipients. CMS also calculates the threshold
for earning the Health Equity Incentive based on the ETC Participant's
aggregation group's historical performance on the home dialysis rate
and transplant rate during the Benchmark Year, using only attributed
beneficiary years comprised of months during the Benchmark Year in
which ESRD Beneficiaries and, if applicable, Pre-emptive LDT
Beneficiaries, are dual eligible or LIS recipients. An ESRD Beneficiary
or Pre-emptive LDT Beneficiary is considered to be dual eligible or a
LIS recipient for a given month if at any point during the month the
beneficiary was dual eligible or a LIS recipient. CMS determines
whether a beneficiary was dual eligible or a LIS recipient based on
Medicare administrative data.
(i) The ETC Participant earns the Health Equity Incentive for the
home dialysis rate improvement score if the home dialysis rate for the
MY, calculated as specified in this paragraph (c)(2), is at least 2.5-
percentage points higher than the home dialysis rate for the Benchmark
Year, calculated as specified in this paragraph (c)(2). If the ETC
Participant earns the Health Equity Incentive for the home dialysis
rate improvement score, CMS adds 0.5 points to the ETC Participant's
home dialysis rate improvement score, calculated as specified in
paragraph (c)(1) of this section, unless the ETC Participant is
ineligible to receive the Home Equity Incentive as specified in
paragraph (c)(2)(iii) of this section.
(ii) The ETC Participant earns the Health Equity Incentive for the
transplant rate improvement score if the home dialysis rate for the MY,
calculated as specified in this paragraph (c)(2), is at least 2.5-
percentage points higher than the transplant rate for the Benchmark
Year, calculated as specified in this paragraph (c)(2). If the ETC
Participant earns the Health Equity Incentive for the transplant rate
improvement score, CMS adds 0.5 points to the ETC Participant's
transplant rate improvement score, calculated as specified in paragraph
(c)(1) of this section, unless the ETC Participant is ineligible to
receive the Home Equity Incentive as specified in paragraph (c)(2)(iii)
of this section.
(iii) An ETC Participant in an aggregation group with fewer than
11-attributed beneficiary years comprised of months in which ESRD
Beneficiaries and, if applicable, Pre-emptive LDT Beneficiaries, are
dual eligible or LIS recipients, during either the Benchmark Year or
the MY is ineligible to earn the Health Equity Incentive.
(d) Modality Performance Score. (1) For MY1 and MY2, CMS calculates
the ETC Participant's MPS as the higher of ETC Participant's
achievement score or improvement score for the home dialysis rate,
together with the higher of the ETC Participant's achievement score or
improvement score for the transplant rate, weighted such that the ETC
Participant's score for the home dialysis rate constitutes \2/3\ of the
MPS and the ETC Participant's score for the transplant rate constitutes
\1/3\ of the MPS. CMS uses the following formula to calculate the ETC
Participant's MPS for MY1 and MY2:
Modality Performance Score = 2 x (Higher of the home dialysis
achievement or improvement score) + (Higher of the transplant
achievement or improvement score)
(2) For MY3 through MY10, CMS calculates the ETC Participant's MPS
as the higher of the ETC Participant's achievement score for the home
dialysis rate or the sum of the ETC Participant's improvement score for
the home dialysis rate calculated as specified in paragraph (c)(1) of
this section and, if applicable, the Health Equity Incentive,
calculated as described in paragraph (c)(2)(i) of this section,
together with the higher of the ETC Participant's achievement score for
the transplant rate or the sum of the ETC Participant's improvement
score for the transplant rate calculated as specified in paragraph
(c)(1) of this section and, if applicable, the Heath Equity Incentive,
calculated as described in paragraph (c)(2)(ii) of this section,
weighted such that the ETC Participant's score for the home dialysis
rate constitutes \2/3\ of the MPS and the ETC Participant's score for
the transplant rate constitutes \1/3\ of the MPS. CMS uses the
following formula to calculate the ETC Participant's MPS for MY3
through MY10:
Modality Performance Score = 2 x (Higher of the home dialysis
achievement or (home dialysis improvement score + Health Equity Bonus
[dagger])) + (Higher of the transplant achievement or (transplant
improvement score + Health Equity Bonus[dagger]))
[dagger] The Health Equity Incentive is applied to the home dialysis
improvement score or transplant improvement score only if earned by the
ETC Participant.
0
10. Section 512.390 is amended by revising the section heading,
redesignating paragraph (b) as (c) and adding new paragraph (b).
The revision and addition read as follows:
[[Page 62025]]
Sec. 512.390 Notification, data sharing, and targeted review.
* * * * *
(b) Data sharing with ETC Participants. CMS shares certain
beneficiary-identifiable data as described in paragraph (b)(1) of this
section and certain aggregate data as described in paragraph (b)(2) of
this section with ETC Participants regarding their attributed
beneficiaries and performance under the ETC Model.
(1) Beneficiary-identifiable data. CMS shares beneficiary-
identifiable data with ETC Participants as follows:
(i) CMS will make available certain beneficiary-identifiable data
for retrieval by ETC Participants no later than one month before the
start of each PPA Period, in a form and manner specified by CMS. ETC
Participants may retrieve this data at any point during the relevant
PPA Period.
(ii) This beneficiary-identifiable data includes, when available,
the following information for each PPA Period:
(A) The ETC Participant's attributed beneficiaries' names, Medicare
Beneficiary Identifiers, dates of birth, dual eligible status, and LIS
recipient status.
(B) Data regarding the ETC Participant's performance under the ETC
Model, including, for each attributed beneficiary, as applicable: the
number of months the beneficiary was attributed to the ETC Participant,
home dialysis months, self-dialysis months, nocturnal in-center
dialysis months, transplant waitlist months, and months following a
living donor transplant.
(iii) CMS shares this beneficiary-identifiable data on the
condition that the ETC Participants observe all relevant statutory and
regulatory provisions regarding the appropriate use of data and the
confidentiality and privacy of individually identifiable health
information as would apply to a covered entity under the regulations
found at 45 CFR parts 160 and 164 promulgated under the Health
Insurance Portability and Accountability Act of 1996 (HIPAA), as
amended, and comply with the terms of the data sharing agreement
described in paragraph (b)(1)(iv) of this section.
(iv) If an ETC Participant wishes to retrieve the beneficiary-
identifiable data specified in paragraph (b)(1)(ii) of this section,
the ETC Participant must complete and submit, on at least an annual
basis, a signed data sharing agreement, to be provided in a form and
manner specified by CMS, under which the ETC Participant agrees:
(A) To comply with the requirements for use and disclosure of this
beneficiary-identifiable data that are imposed on covered entities by
the HIPAA regulations and the requirements of the ETC Model set forth
in this part.
(B) To comply with additional privacy, security, breach
notification, and data retention requirements specified by CMS in the
data sharing agreement.
(C) To contractually bind each downstream recipient of the
beneficiary-identifiable data that is a business associate of the ETC
Participant to the same terms and conditions to which the ETC
Participant is itself bound in its data sharing agreement with CMS as a
condition of the business associate's receipt of the beneficiary-
identifiable data retrieved by the ETC Participant under the ETC Model.
(D) That if the ETC Participant misuses or discloses the
beneficiary-identifiable data in a manner that violates any applicable
statutory or regulatory requirements or that is otherwise non-compliant
with the provisions of the data sharing agreement, CMS may deem the ETC
Participant ineligible to retrieve beneficiary-identifiable data under
paragraph (b)(1)(i) of this section for any amount of time, and the ETC
Participant may be subject to additional sanctions and penalties
available under the law.
(2) Aggregate data. CMS shares aggregate performance data with ETC
Participants as follows:
(i) CMS will make available certain aggregate data for retrieval by
the ETC Participant, in a form and manner to be specified by CMS, no
later than one month before each PPA Period.
(ii) This aggregate data includes, when available, the following
information for each PPA Period, de-identified in accordance with 45
CFR 164.514(b):
(A) The ETC Participant's performance scores on the home dialysis
rate, transplant waitlist rate, living donor transplant rate, and the
Health Equity Incentive.
(B) The ETC Participant's aggregation group's scores on the home
dialysis rate, transplant waitlist rate, and living donor transplant
rate, and the Health Equity Incentive.
(C) Information on how the ETC Participant's and ETC Participant's
aggregation group's scores relate to the achievement benchmark and
improvement benchmark.
(D) The ETC Participant's MPS and PPA for the corresponding PPA
Period.
* * * * *
0
11. Section 512.397 is amended by revising the section heading and
paragraph (b) and adding paragraph (c) to read as follows:
Sec. 512.397 ETC Model Medicare program waivers and additional
flexibilities.
* * * * *
(b) CMS waives the following requirements of title XVIII of the Act
solely for purposes of testing the ETC Model:
(1) CMS waives the requirement under section 1861(ggg)(2)(A)(i) of
the Act and Sec. 410.48(a) of this chapter that only doctors,
physician assistants, nurse practitioners, and clinical nurse
specialists can furnish kidney disease patient education services to
allow kidney disease patient education services to be provided by
clinical staff (as defined at Sec. 512.310) under the direction of and
incident to the services of the Managing Clinician who is an ETC
Participant. The kidney disease patient education services may be
furnished only by qualified staff (as defined at Sec. 512.310).
(2) CMS waives the requirement that kidney disease patient
education services are covered only for Stage IV chronic kidney disease
(CKD) patients under section 1861(ggg)(1)(A) of the Act and Sec.
410.48(b)(1) of this chapter to permit beneficiaries diagnosed with CKD
Stage V or within the first 6 months of starting dialysis to receive
kidney disease patient education services.
(3) CMS waives the requirement that the content of kidney disease
patient education services include the management of co-morbidities,
including for the purpose of delaying the need for dialysis, under
Sec. 410.48(d)(1) of this chapter when such services are furnished to
beneficiaries with CKD Stage V or ESRD, unless such content is relevant
for the beneficiary.
(4) CMS waives the requirement that an outcomes assessment designed
to measure beneficiary knowledge about CKD and its treatment be
performed as part of a kidney disease patient education service under
Sec. 410.48(d)(5)(iii) of this chapter, provided that such outcomes
assessment is performed by qualified staff within one month of the
final kidney disease patient education service.
(5) Beginning the upon the expiration of the Public Health
Emergency (PHE) for the COVID-19 pandemic, CMS waives the geographic
and site of service originating site requirements in sections
1834(m)(4)(B) and 1834(m)(4)(C) of the Act and Sec. 410.78(b)(3) and
(4) of this chapter for purposes of kidney disease patient education
services furnished by qualified staff via telehealth in accordance with
this section, regardless of the location of the beneficiary or
[[Page 62026]]
qualified staff. Beginning the upon the expiration of the Public Health
Emergency (PHE) for the COVID-19 pandemic, CMS also waives the
requirement in section 1834(m)(2)(B) of the Act and Sec. 414.65(b) of
this chapter that CMS pay a facility fee to the originating site with
respect to telehealth services furnished to a beneficiary in accordance
with this section at an originating site that is not one of the
locations specified in Sec. 410.78(b)(3) of this chapter.
(c)(1) For kidney disease patient education services furnished on
or after January 1, 2022, an ETC Participant may reduce or waive the 20
percent coinsurance requirement under section 1833 of the Act if all of
the following conditions are satisfied:
(i) The individual or entity that furnished the kidney disease
patient education services is qualified staff.
(ii) The qualified staff are not leased from or otherwise provided
by an ESRD facility or related entity.
(iii) The kidney disease patient education services were furnished
to a beneficiary described in Sec. 410.48(b) or Sec. 512.397(b)(2)
who did not have secondary insurance that provides cost-sharing support
for kidney disease patient education services on the date the services
were furnished.
(iv) The kidney disease patient education services were furnished
in compliance with the applicable provisions of Sec. 410.48 and Sec.
512.397(b).
(v) The ETC Participant bears the full cost of the reduction or
waiver of the 20 percent coinsurance requirement under section 1833 of
the Act. The reduction or waiver of the 20 percent coinsurance
requirement under section 1833 of the Act shall not be financed by a
third party, including but not limited to an ESRD facility or related
entity.
(2) The ETC Participant must maintain and provide the government
with access to records of the following information in accordance with
Sec. 512.135(b) and (c):
(i) The identity of the qualified staff who furnished the kidney
disease patient education services for which the coinsurance was
reduced or waived and the date such services were furnished.
(ii) The identity of the beneficiary who received the kidney
disease patient education services for which the coinsurance was
reduced or waived.
(iii) Evidence that the beneficiary who received the kidney disease
patient education services coinsurance waiver was eligible to receive
the kidney disease patient education services under the ETC Model and
did not have secondary insurance that provides cost-sharing support for
kidney disease patient education services.
(iv) The amount of the kidney disease patient education coinsurance
reduction or waiver provided by the ETC Participant.
(3) The Federal anti-kickback statute safe harbor for CMS-sponsored
model patient incentives (42 CFR 1001.952(ii)(2)) is available to
protect the kidney disease patient education coinsurance waivers that
satisfy the requirements of such safe harbor and paragraph (c)(1) of
this section.
Dated: October 28, 2021.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2021-23907 Filed 10-29-21; 4:15 pm]
BILLING CODE 4120-01-P