[Federal Register Volume 89, Number 97 (Friday, May 17, 2024)]
[Proposed Rules]
[Pages 43518-43634]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2024-09989]



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Vol. 89

Friday,

No. 97

May 17, 2024

Part II





Department of Homeland Security





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Cybersecurity and Infrastructure Security Agency





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42 CFR Part 512





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

  Federal Register / Vol. 89 , No. 97 / Friday, May 17, 2024 / Proposed 
Rules  

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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Part 512

[CMS-5535-P]
RIN 0938-AU51


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

AGENCY: Centers for Medicare & Medicaid Services (CMS), Department of 
Health and Human Services (HHS).

ACTION: Proposed rule.

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SUMMARY: This proposed rule describes a new mandatory Medicare payment 
model, the Increasing Organ Transplant Access Model (IOTA Model), that 
would test whether performance-based incentive payments paid to or owed 
by participating kidney transplant hospitals increase access to kidney 
transplants for patients with end-stage renal disease (ESRD) while 
preserving or enhancing the quality of care and reducing Medicare 
expenditures. This proposed rule also includes standard provisions that 
would apply to Innovation Center models whose first performance period 
begins on or after January 1, 2025, and also would apply, in whole or 
part, to any Innovation Center model whose first performance period 
begins prior to January 1, 2025 should such model's governing 
documentation incorporate the provisions by reference in whole or in 
part. The proposed standard provisions relate to beneficiary 
protections; cooperation in model evaluation and monitoring; audits and 
records retention; rights in data and intellectual property; monitoring 
and compliance; remedial action; model termination by CMS; limitations 
on review; miscellaneous provisions on bankruptcy and other 
notifications; and the reconsideration review process.

DATES: To be assured consideration, comments must be received at one of 
the addresses provided below, by July 16, 2024.

ADDRESSES: In commenting, please refer to file code CMS-5535-P.
    Comments, including mass comment submissions, must be submitted in 
one of the following three ways (please choose only one of the ways 
listed):
    1. Electronically. You may submit electronic comments on this 
regulation to http://www.regulations.gov. Follow the ``Submit a 
comment'' instructions.
    2. By regular mail. You may mail written comments to the following 
address ONLY: Centers for Medicare & Medicaid Services, Department of 
Health and Human Services, Attention: CMS-5535-P, P.O. Box 8013, 
Baltimore, MD 21244-8013.
    Please allow sufficient time for mailed comments to be received 
before the close of the comment period.
    3. By express or overnight mail. You may send written comments to 
the following address ONLY: Centers for Medicare & Medicaid 
Services,Department of Health and Human Services, Attention: CMS-5535-
P, Mail Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-
1850.
    For information on viewing public comments, see the beginning of 
the SUPPLEMENTARY INFORMATION section.

FOR FURTHER INFORMATION CONTACT: [email protected] for 
questions related to the Increasing Organ Transplant Access Model.
    [email protected] for questions related to the 
Standard Provisions for Innovation Center Models.

SUPPLEMENTARY INFORMATION: 
    Inspection of Public Comments: All comments received before the 
close of the comment period are available for viewing by the public, 
including any personally identifiable or confidential business 
information that is included in a comment. We post all comments 
received before the close of the comment period on the following 
website as soon as possible after they have been received: http://www.regulations.gov. Follow the search instructions on that website to 
view public comments. CMS will not post on Regulations.gov public 
comments that make threats to individuals or institutions or suggest 
that the commenter will take actions to harm an individual. CMS 
encourages individuals not to submit duplicative comments. We will post 
acceptable comments from multiple unique commenters even if the content 
is identical or nearly identical to other comments.

Current Procedural Terminology (CPT) Copyright Notice

    Throughout this proposed 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. All Rights Reserved. CPT[supreg] is a registered trademark 
of the American Medical Association (AMA). Applicable Federal 
Acquisition Regulations (FAR) and Defense Federal Acquisition 
Regulations (DFAR) apply.

I. Executive Summary

A. Purpose

    Section 1115A of the Social Security Act (the Act) gives the 
Secretary of Health and Human Services the authority to test innovative 
payment and service delivery models to reduce program expenditures in 
Medicare, Medicaid, and the Children's Health Insurance Program (CHIP) 
while preserving or enhancing the quality of care furnished to 
individuals covered by such programs. This proposed rule describes a 
new mandatory Medicare payment model to be tested under section 1115A 
of the Act--the Increasing Organ Transplant Access Model (IOTA Model)--
which would begin on January 1, 2025 and end on December 31, 2030. In 
this proposed rule, we propose payment policies, participation 
requirements, and other provisions to test the IOTA Model. We propose 
to test whether performance-based incentives (including both upside and 
downside risk) for participating kidney transplant hospitals can 
increase the number of kidney transplants (including both living donor 
and deceased donor transplants) furnished to End Stage Renal Disease 
(ESRD) patients, encourage investments in care processes and patterns 
with respect to patients who need kidney transplants, encourage 
investments in value-based care and improvement activities, and promote 
kidney transplant hospital accountability by tying payments to value. 
The IOTA Model is also intended to advance health equity by improving 
equitable access to the transplantation ecosystem through design 
features such as a proposed health equity plan requirement to address 
health outcome disparities and a health equity performance adjustment.
    This proposed rule also includes proposed standard provisions that 
would apply to Innovation Center models whose first performance periods 
begin on or after January 1, 2025, unless otherwise specified in a 
model's governing documentation, as well as to Innovation Center models 
whose first performance periods begin prior to January 1, 2025, 
provided the standard provisions are incorporated into such models' 
governing documentation. The proposed standard provisions address 
beneficiary protections; cooperation in model evaluation and 
monitoring; audits and record retention; rights in data and 
intellectual property; monitoring and compliance; remedial action; 
model termination by CMS; limitations on review; miscellaneous 
provisions on bankruptcy and other

[[Page 43519]]

notifications; and the reconsideration review process.
    We seek public comment on these proposals, the alternatives 
considered, and the request for information (RFI) in section III.D. of 
this proposed rule.

B. Summary of the Proposed Provisions

1. Standard Provisions for Innovation Center Models
    The proposed standard provisions for Innovation Center models would 
be applicable to all Innovation Center models whose first performance 
periods begin on or after January 1, 2025, subject to any limitations 
specified in a model's governing documentation. The proposed standard 
provisions also would apply to all Innovation Center models whose first 
performance periods begin prior to January 1, 2025, provided the 
standard provisions are incorporated into such models' governing 
documentation.
    We are proposing to codify these standard provisions to increase 
transparency, efficiency, and clarity in the operation and governance 
of Innovation Center models, and to avoid the need to restate the 
provisions in each model's governing documentation. The proposed 
standard provisions include terms that have been repeatedly 
memorialized, with minimal variation, in existing models' governing 
documentation. The proposed standard provisions are not intended to 
encompass all of the terms and conditions that would apply to each 
Innovation Center model, because each model embodies unique design 
features and implementation plans that may require additional, more 
tailored provisions, including with respect to payment methodology, 
care delivery and quality measurement, that would continue to be 
included in each model's governing documentation. Model-specific 
provisions applicable to the IOTA Model proposed herein are described 
in section III of this proposed rule.
2. Model Overview--Proposed Increasing Organ Transplant Access Model
a. Proposed IOTA Model Overview
    End-Stage Renal Disease (ESRD) is a medical condition in which a 
person's kidneys cease functioning on a permanent basis, leading to the 
need for a regular course of long-term dialysis or a kidney transplant 
to maintain life.\1\ The best treatment for most patients with kidney 
failure is kidney transplantation. Nearly 808,000 people in the United 
States are living with ESRD, with about 69 percent on dialysis and 31 
percent with a kidney transplant.\2\ For ESRD patients, regular 
dialysis sessions or a kidney transplant is required for survival. 
Relative to dialysis, a kidney transplant can improve survival, reduce 
avoidable health care utilization and hospital acquired conditions, 
improve quality of life, and lower Medicare expenditures.\3\ \4\ 
However, despite these benefits, evidence shows low rates of ESRD 
patients placed on kidney transplant hospitals' waitlists, a decline in 
living donors over the past 20 years, and underutilization of available 
donor kidneys, coupled with increasing rates of donor kidney discards, 
and wide variation in kidney offer acceptance rates and donor kidney 
discards by region and across kidney transplant hospitals.\5\ \6\ 
Further, there are substantial disparities in both deceased and living 
donor transplantation rates among structurally disadvantaged 
populations. Strengthening and improving the performance of the organ 
transplantation system is a priority for the Department of Health and 
Human Services (HHS). Consistent with this priority, and through joint 
efforts with HHS' Health Resources and Services Administration (HRSA), 
the proposed IOTA Model would aim to reduce Medicare expenditures and 
improve performance and equity in kidney transplantation by creating 
performance-based incentive payments for participating kidney 
transplant hospitals tied to access and quality of care for ESRD 
patients on the hospitals' waitlists.
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    \1\ End-Stage Renal Disease (ESRD) [verbar] CMS. (n.d.). https://www.cms.gov/medicare/coordination-benefits-recovery/overview/end-stage-renal-disease-esrd.
    \2\ United States Renal Data System. 2022 USRDS Annual Data 
Report: Epidemiology of kidney disease in the United States. 
National Institutes of Health, National Institute of Diabetes and 
Digestive and Kidney Diseases, Bethesda, MD, 2022.
    \3\ Tonelli, M., Wiebe, N., Knoll, G., Bello, A., Browne, S., 
Jadhav, D., Klarenbach, S., & Gill, J. (2011). Systematic review: 
kidney transplantation compared with dialysis in clinically relevant 
outcomes. American Journal of Transplantation: Official Journal of 
the American Society of Transplantation and the American Society of 
Transplant Surgeons, 11(10), 2093-2109. https://doi.org/10.1111/j.1600-6143.2011.03686.xhttps://doi.org/10.1111/j.1600-6143.2011.03686.
    \4\ Cheng, X. S., Han, J., Braggs-Gresham, J. L., Held, P. J., 
Busque, S., Roberts, J. P., Tan, J. C., Scandling, J. D., Chertow, 
G. M., & Dor, A. (2022). Trends in Cost Attributable to Kidney 
Transplantation Evaluation and Waitlist Management in the United 
States, 2012-2017. JAMA network open, 5(3), e221847. https://doi.org/10.1001/jamanetworkopen.2022.184.
    \5\ Al Ammary, F., Bowring, M. G., Massie, A. B., Yu, S., 
Waldram, M. M., Garonzik-Wang, J., Thomas, A. G., Holscher, C. M., 
Qadi, M. A., Henderson, M. L., Wiseman, A. C., Gralla, J., Brennan, 
D. C., Segev, D. L., & Muzaale, A. D. (2019). The changing landscape 
of live kidney donation in the United States from 2005 to 2017. 
American journal of transplantation: official journal of the 
American Society of Transplantation and the American Society of 
Transplant Surgeons, 19(9), 2614-2621. https://doi.org/10.1111/ajt.15368.
    \6\ Mohan, S., Yu, M., King, K. L., & Husain, S. A. (2023). 
Increasing Discards as an Unintended Consequence of Recent Changes 
in United States Kidney Allocation Policy. Kidney international 
reports, 8(5), 1109-1111. https://doi.org/10.1016/j.ekir.2023.02.1081.
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    The proposed IOTA Model would be a mandatory model that would begin 
on January 1, 2025 and end on December 31, 2030, resulting in a 6-year 
model performance period (``model performance period'') comprised of 6 
individual performance years (each a ``performance year'' or ``PY''). 
The proposed IOTA Model would test whether performance-based incentives 
paid to, or owed by, participating kidney transplant hospitals can 
increase access to kidney transplants for patients with ESRD, while 
preserving or enhancing quality of care and reducing Medicare 
expenditures. CMS would select kidney transplant hospitals to 
participate in the IOTA Model through the methodology proposed in 
section III.C.3.d of this proposed rule. As this would be a mandatory 
model, the selected kidney transplant hospitals would be required to 
participate. CMS would measure and assess the participating kidney 
transplant hospitals' performance during each PY across three 
performance domains: achievement, efficiency, and quality.
    The achievement domain would assess each participating kidney 
transplant hospital on the overall number of kidney transplants 
performed during a PY, relative to a participant-specific target. The 
efficiency domain would assess the kidney organ offer acceptance rates 
of each participating kidney transplant hospital relative to the 
national rate. The quality domain would assess the quality of care 
provided by the participating kidney transplant hospitals across a set 
of proposed outcome metrics and quality measures. Each participating 
kidney transplant hospital's performance score across these three 
domains would determine its final performance score and corresponding 
amount for the performance-based incentive payment that CMS would pay 
to, or the payment that would be owed by, the participating kidney 
transplant hospital. The proposed upside risk payment would be a lump 
sum payment paid by CMS after the end of a PY to a participating kidney 
transplant hospital with a final performance score of 60 or greater. 
Conversely, beginning after PY 2, the downside risk payment would be a 
lump sum payment paid to CMS by any participating kidney transplant 
hospital

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with a final performance score of 40 or lower. We are not proposing a 
downside risk payment for PY 1 of the model.
b. Model Scope
    We propose that participation in the IOTA Model would be mandatory 
for 50 percent of all eligible kidney transplant hospitals in the 
United States. We anticipate that a total of approximately 90 kidney 
transplant hospitals will be selected to participate in the IOTA Model. 
As discussed in section III.C.3.b. of this proposed rule, we believe 
that mandatory participation is necessary to minimize the potential for 
selection bias and to ensure a representative sample size nationally, 
thereby guaranteeing that there will be adequate data to evaluate the 
model test.
    We propose that eligible kidney transplant hospitals would be those 
that: (1) performed at least eleven kidney transplants for patients 18 
years of age or older annually regardless of payer type during the 
three-year period ending 12 months before the model's start date; and 
(2) furnished more than 50 percent of the hospital's annual kidney 
transplants to patients 18 years of age or older during that same 
period. We propose to select the kidney transplant hospitals that will 
be required to participate in the IOTA Model from the group of eligible 
kidney transplant hospitals using a stratified random sampling of 
donation service areas (``DSAs'') to ensure that there is a fair 
selection process and representative group of participating kidney 
transplant hospitals. For the purposes of this proposed rule, a DSA has 
the same meaning given to that term at 42 CFR 486.302.
c. Performance Assessment
    We propose to assess each IOTA participants' performance across 
three performance domains during each PY of the model, with a maximum 
possible final performance score of 100 points. The three performance 
domains would include: (1) an achievement domain worth up to 60 points, 
(2) an efficiency domain worth up to 20 points, and (3) a quality 
domain worth up to 20 points.
    The achievement domain would assess the number of kidney 
transplants performed by each IOTA participant for attributed patients, 
with performance on this domain worth up to 60 points. The final 
performance score would be heavily weighted on the achievement domain 
to align with the IOTA Model's goal to increase access to kidney 
transplants. The IOTA Model theorizes that improvement activities, 
including those aimed at reducing unnecessary deceased donor discards 
and increasing living donors, may help increase access to kidney 
transplants.
    We propose that CMS would set a target number of kidney transplants 
for each IOTA participant for each PY to measure the IOTA participant's 
performance in the achievement domain (the ``transplant target''), as 
described in section III.C.5.c of this proposed rule. Each IOTA 
participant's transplant target for a given PY would be based on the 
IOTA participant's historical volume of deceased and living donor 
transplants furnished to attributed patients in the relevant baseline 
years, adjusted by the national trend rate in the number of kidney 
transplants performed and further adjusted by the proportion of 
transplants furnished by the IOTA participant to attributed patients 
who are low income. Section III.C.5.c. of this proposed rule describes 
the variation in the number of kidney transplants performed across 
kidney transplant hospitals, which would make it challenging to set 
transplant targets on a regional or national basis. The IOTA Model 
would therefore set a transplant target that is specific to each IOTA 
participant to address this concern, while still accounting for the 
national trend rate in the number of kidney transplants performed. It 
is expected that IOTA participants' transplant targets may change from 
PY to PY because of the way in which the transplant target would be 
calculated.
    The efficiency domain would assess the kidney organ offer 
acceptance rate ratio for each IOTA participant. The kidney organ offer 
acceptance rate ratio measures the number of kidneys an IOTA 
participant accepts for transplant over the expected value, based on 
variables such as kidney quality. Points for the kidney organ offer 
acceptance rate ratio would be determined relative to either the kidney 
organ offer acceptance rate ratio across all kidney transplant 
hospitals, or the IOTA participant's own past kidney organ offer 
acceptance rate ratio, with performance on the efficiency domain being 
worth up to 20 points.
    Finally, the quality domain would assess IOTA participants' 
performance on post-transplant outcomes in addition to three quality 
measures--the CollaboRATE Shared Decision-Making Score, Colorectal 
Cancer Screening, and the 3-Item Care Transition Measure, with 
performance on this domain being worth up to 20 points.
    Each IOTA participant's final performance score would be the sum of 
the points earned for each domain: achievement, efficiency, and 
quality. The final performance score in a PY would be determinative of 
whether the IOTA participant would be eligible to receive an upside 
risk payment from CMS, fall into the neutral zone where no upside or 
downside risk payment would apply, or owe a downside risk payment to 
CMS for the PY as described in section III.C.6. of this proposed rule.
d. Performance-Based Incentive Payment Formula
    Each IOTA participant's final performance score would determine 
whether: (1) CMS would pay an upside risk payment to the IOTA 
participant; (2) the IOTA participant would fall into a neutral zone, 
in which case no performance-based incentive payment would be paid to 
or owed by the IOTA participant; or (3) the IOTA participant would owe 
a downside risk payment to CMS. For a final performance score above 60, 
CMS would apply the formula for the upside risk payment, which we 
propose would be equal to the IOTA participant's final performance 
score minus 60, then divided by 60, then multiplied by $8,000, then 
multiplied by the number of kidney transplants furnished by the IOTA 
participant to attributed patients with Medicare as their primary or 
secondary payer during the PY. Final performance scores below 60 in PY 
1 and final performance scores of 41 to 59 in PYs 2-6 would fall in the 
neutral zone where there would be no payment owed to the IOTA 
participant or CMS.
    We propose to phase-in the downside risk payment beginning in PY2. 
We explain in section III.C.5.b. of this proposed rule that new 
entrants to value-based payment models may need a ramp up period before 
they are able to accept downside risk. Thus, the IOTA Model proposes an 
upside risk-only approach for PY 1 as an incentive in each of the three 
performance domains. This would give IOTA participants time to 
consider, invest in, and implement value-based care and quality 
improvement initiatives before downside risk payments would begin. 
Beginning in PY 2, for a final performance score of 40 and below, CMS 
would apply the formula for the downside risk payment, which would be 
equal to the IOTA participant's final performance score minus 40, then 
divided by 40, then multiplied by -$2,000, then multiplied by the 
number of kidney transplants furnished by the IOTA participant to 
attributed patients with Medicare as their primary or secondary payer 
during the PY.
    CMS would pay the upside risk payment in lump sum to the IOTA 
participant after the PY. The IOTA participant would pay the downside

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risk payment to CMS in a lump sum after the PY.
e. Data Sharing
    We propose to collect certain quality, clinical, and administrative 
data from IOTA participants for model monitoring and evaluation 
activities under the authority in 42 CFR 403.1110(b). We would also 
share certain data with IOTA participants upon request as described in 
section III.C.3.a. of this proposed rule and as permitted by the Health 
Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy 
Rule and other applicable law. We propose to offer each IOTA 
participant the opportunity to request certain beneficiary-identifiable 
data for their attributed Medicare beneficiaries for treatment, case 
management, care coordination, quality improvement activities, and 
population-based activities relating to improving health or reducing 
health care costs, as permitted by 45 CFR 164.506(c). The data uses and 
sharing would be allowed only to the extent permitted by the HIPAA 
Privacy Rule and other applicable law and CMS policies. We also propose 
to share certain aggregate, de-identified data with IOTA participants.
f. Other Requirements
    We propose several other model requirements for selected transplant 
hospitals, including transparency requirements, public reporting 
requirements, and a health equity plan requirement which would be 
optional for PY1 and required for PY 2 through PY 6, as described in 
section III.C.8. of this proposed rule.
(1) Transparency Requirements
    Patients are often unsure whether they qualify for a kidney 
transplant at a given kidney transplant hospital. We propose that IOTA 
participants would be required to publish on a public facing website 
the criteria they use when determining whether or not to add a patient 
to the kidney transplant waitlist. We also propose to add requirements 
to facilitate increased transparency for patients regarding the organ 
offers received on the patient's behalf while the patient is on the 
waitlist. Specifically, we propose that IOTA participants would be 
required to inform patients on the waitlist, on a monthly basis, of the 
number of times an organ was declined on each patient's behalf and the 
reason(s) why each organ was declined. We believe that notifying 
patients of the organs declined on their behalf would encourage 
conversations between patients and their providers regarding a 
patient's preferences for transplant and facilitate better shared 
decision-making.
(2) Health Equity Requirements
    We propose that during the model's first PY, each IOTA participant 
would have the option to submit a health equity plan (``HEP'') to CMS. 
We propose that each IOTA participant would then be required to submit 
a HEP to CMS for PY 2 and to update its HEP for each subsequent PY. We 
propose that the IOTA participant's HEP would identify health 
disparities within the IOTA participant's population of attributed 
patients and outline a course of action to address them.
    We also considered proposing to require IOTA participants to 
collect and report patient-level health equity data to CMS. 
Specifically, we considered proposing that IOTA participants would be 
required to conduct health related social needs screening for at least 
three core areas--food security, housing, and transportation. We 
recognize these areas as some of the most common barriers to kidney 
transplantation and the most pertinent health related social needs for 
the IOTA patient population.\7\ We have included an RFI in this 
proposed rule to solicit feedback and comment on such a requirement.
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    \7\ Venkataraman, S., & Kendrick, J. (2020). Barriers to kidney 
transplantation in ESKD. Seminars in Dialysis, 33(6), 523-532. 
https://doi.org/10.1111/sdi.12921.
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g. Medicare Payment Waivers and Additional Flexibilities
    We believe it is necessary to waive certain requirements of title 
XVIII of the Act solely for purposes of carrying out the testing of the 
IOTA Model under section 1115A of the Act. We propose to issue these 
waivers using our waiver authority under section 1115A(d)(1) of the 
Act. Each of the proposed waivers is discussed in detail in section 
III.C.10. of this proposed rule.
h. Overlaps With Other Innovation Center Models and CMS Programs
    We expect that there could be situations where a Medicare 
beneficiary attributed to an IOTA participant is also assigned, 
aligned, or attributed to another Innovation Center model or CMS 
program. Overlap could also occur among providers and suppliers at the 
individual or organization level, such as where an IOTA participant or 
one of their providers would participate in multiple Innovation Center 
models. We believe that the IOTA Model would be compatible with 
existing models and programs that provide opportunities to improve care 
and reduce spending. The IOTA Model would not be replacing any covered 
services or changing the payments that participating hospitals receive 
through the inpatient prospective payment system (IPPS) or outpatient 
prospective payment system (OPPS). Rather, the IOTA Model proposes 
performance-based payments separate from what participants would be 
paid by CMS for furnishing kidney transplants to Medicare 
beneficiaries. Additionally, we would work to resolve any potential 
overlaps between the IOTA Model and other Innovation Center models or 
CMS programs that could result in duplicative payments for services, or 
duplicative counting of savings or other reductions in expenditures. 
Therefore, we propose to allow overlaps between the IOTA Model and 
other Innovation Center models and CMS programs.
i. Monitoring
    We propose to closely monitor the implementation and outcomes of 
the IOTA Model throughout its duration consistent with the monitoring 
requirements proposed in the Standard Provisions for Innovation Center 
models in section II of this proposed rule and the proposed 
requirements in section III.C.13. of this proposed rule. The purpose of 
this monitoring would be to ensure that the IOTA Model is implemented 
safely and appropriately, that the quality and experience of care for 
beneficiaries is not harmed, and that adequate patient and program 
integrity safeguards are in place.
j. Beneficiary Protections
    As proposed in section III.C.10. of this proposed rule, CMS would 
not allow beneficiaries or patients to opt out of attribution to an 
IOTA participant; however, the IOTA Model would not restrict a 
beneficiary's freedom to choose another kidney transplant hospital, or 
any other provider or supplier for healthcare services, and IOTA 
participants would be subject to the Standard Provisions for Innovation 
Center Models outlined in section II. of this proposed rule protecting 
Medicare beneficiary freedom of choice and access to medically 
necessary services. We also would require that IOTA participants notify 
Medicare beneficiaries of the IOTA participant's participation in the 
IOTA Model by, at a minimum, prominently displaying informational 
materials in offices or facilities where beneficiaries receive care. 
Additionally, IOTA participants would be subject to the proposed 
Standard Provisions for Innovation Center Models regarding descriptive 
model materials and activities in section II. of this proposed rule.

[[Page 43522]]

C. Summary of Costs and Benefits

    The IOTA Model aims to incentivize transplant hospitals to overcome 
system-level barriers to kidney transplantation. The chronic shortfall 
in kidney transplants results in poorer outcomes for patients and 
increases the burden on Medicare in terms of payments for dialysis and 
dialysis-based enrollment in the program. There is reasonable evidence 
that the savings to Medicare resulting from an incremental growth in 
transplantation would potentially exceed the payments projected under 
the model's proposed incentive structure.

II. Standard Provisions for Innovation Center Models

A. Introduction

    Section 1115A of the Act authorizes the Center for Medicare and 
Medicaid Innovation (the ``Innovation Center'') to test innovative 
payment and service delivery models expected to reduce Medicare, 
Medicaid, and CHIP expenditures, while preserving or enhancing the 
quality of care furnished to such programs' beneficiaries. We have 
designed and tested both voluntary Innovation Center models--governed 
by participation agreements, cooperative agreements, and model-specific 
addenda to existing contracts with CMS--and mandatory Innovation Center 
models that are governed by regulations. Each voluntary and mandatory 
model features its own specific payment methodology, quality metrics, 
and certain other applicable policies, but each model also features 
numerous provisions of a similar or identical nature, including 
provisions regarding cooperation in model evaluation; monitoring and 
compliance; and beneficiary protections.
    On September 29, 2020, we published in the Federal Register a final 
rule titled ``Medicare Program; Specialty Care Models To Improve 
Quality of Care and Reduce Expenditures'' (85 FR 61114) (hereinafter 
the ``Specialty Care Models final rule''), in which we adopted General 
Provisions Related to Innovation Center models at 42 CFR part 512 
subpart A that apply to the End-Stage Renal Disease Treatment Choices 
(ETC) Model and the Radiation Oncology (RO) Model.\8\ The Specialty 
Care Models final rule codified general provisions regarding 
beneficiary protections, cooperation in model evaluation and 
monitoring, audits and record retention, rights in data and 
intellectual property, monitoring and compliance, remedial action, 
model termination by CMS, limitations on review, and bankruptcy and 
other notifications. These general provisions were adopted only for the 
ETC and RO Models (and, in practice, applied only to the ETC Model). 
However, we now believe the general provisions should apply to 
Innovation Center models more broadly. As we note, the Innovation 
Center models share numerous similar provisions, and codifying the 
general provisions into law to expand their applicability across 
models, except where otherwise explicitly specified in a model's 
governing documentation, would, we believe, promote transparency, 
efficiency, clarity, and ensure consistency across models to the extent 
appropriate, while avoiding the need to restate the provisions in each 
model's governing documentation.
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    \8\ In the autumn of 2020, due to the Secretary of Health and 
Human Services' Determination that a Public Health Emergency Exists 
for the Coronavirus disease 2019 (COVID-19) (https://aspr.hhs.gov/legal/PHE/Pages/2019-nCoV.aspx), CMS revised the RO Model's 
performance period to begin on July 1, 2021, and to end on December 
31, 2025, in the CY 2021 Hospital Outpatient Prospective Payment 
(OPPS) and Ambulatory Surgical Center (ASC) Payment Systems and 
Quality Reporting Programs final rule with comment period (85 FR 
85866). Section 133 of the Consolidated Appropriations Act (CAA), 
2021 (Pub. L. 116-260) (hereinafter referred to as ``CAA, 2021''), 
enacted on December 27, 2020, included a provision that prohibited 
implementation of the RO Model before January 1, 2022. This 
congressional action superseded the July 1, 2021, start date that we 
had established in the CY 2021 OPPS/ASC IFC. To align the RO Model 
regulations with the requirements of the CAA, 2021, we proposed to 
modify the definition of ``model performance period'' in 42 CFR part 
512.205 to provide for a 5-year model performance period starting on 
January 1, 2022, unless the RO Model was prohibited by law from 
starting on January 1, 2022, in which case the model performance 
period would begin on the earliest date permitted by law that is 
January 1, April 1, or July 1. We also proposed other modifications 
both related and unrelated to the timing of the RO Model in the 
proposed rule that appeared in the August 4, 2021, Federal Register 
titled ``Medicare Program: Hospital Outpatient Prospective Payment 
and Ambulatory Surgical Center Payment Systems and Quality Reporting 
Programs; Price Transparency of Hospital Standard Charges; Radiation 
Oncology Model; Request for Information on Rural Emergency 
Hospitals'' (86 FR 42018). These provisions were finalized in a 
final rule with comment period titled ``Medicare Program: Hospital 
Outpatient Prospective Payment and Ambulatory Surgical Center 
Payment Systems and Quality Reporting Programs; Price Transparency 
of Hospital Standard Charges; Radiation Oncology Model'' that 
appeared in the November 16, 2021 Federal Register (86 FR 63458) 
(hereinafter referred to as the ``CY 2022 OPPS/ASC FC'').
    On December 10, 2021, the Protecting Medicare and American 
Farmers from Sequester Cuts Act (Pub. L. 117-71) was enacted, which 
included a provision that prohibits implementation of the RO Model 
prior to January 1, 2023. The CY 2022 OPPS/ASC final rule with 
comment period specified that if the RO Model was prohibited by law 
from beginning on January 1, 2022, the model performance period 
would begin on the earliest date permitted by law that is January 1, 
April 1, or July 1. As a result, under the current definition for 
model performance period at Sec.  512.205, the RO Model would have 
started on January 1, 2023, because that date is the earliest date 
permitted by law. However, given the multiple delays to date, and 
because both CMS and RO participants must invest operational 
resources in preparation for implementation of the RO Model, we have 
considered how best to proceed under these circumstances. In a final 
rule titled ``Radiation Oncology (RO) Model,'' which appeared in the 
Federal Register on August 29, 2022 (87 FR 52698), we delayed the 
start date of the RO Model to a date to be determined through future 
rulemaking, and modified the definition of the model performance 
period at Sec.  512.205 to provide that the start and end dates of 
the model performance period for the RO Model would be established 
in future rulemaking. We have not undertaken rulemaking to determine 
the start date for the RO Model and, thus, the model is not active 
at this time.
---------------------------------------------------------------------------

    We also propose a new provision pertaining to the reconsideration 
review process that would apply to Innovation Center models that waive 
the appeals processes provided under section 1869 of the Act.

B. General Provisions Codified in the Code of Federal Regulations That 
Would Apply to Innovation Center Models

    Each Innovation Center model features many unique aspects that must 
be memorialized in its governing documentation, but each model also 
includes certain provisions that are common to most or all models. We 
believe that codifying these common provisions would facilitate their 
uniform application across models (except where the governing 
documentation for a particular model dictates otherwise) and promote 
program efficiency and consistency that would benefit CMS' program 
administration and model participants.
    As such, we propose to expand the applicability of the 42 CFR part 
512 subpart A ``General Provisions Related to Innovation Center 
Models'' to all Innovation Center models whose first performance 
periods begin on or after January 1, 2025, unless otherwise specified 
in the models' governing documentation, and also to any Innovation 
Center models whose first performance periods begin prior to January 1, 
2025 if incorporated by reference into the models' governing 
documentation. To accomplish this, we propose that the provisions 
codified at 42 CFR part 512 subpart A for the ETC and RO Models, 
including those with respect to definitions, beneficiary protections, 
cooperation in model evaluation and monitoring, audits and record 
retention, rights in data and intellectual property, monitoring and 
compliance, remedial action, Innovation Center model termination by 
CMS, and limitations on review, would be designated as the newly 
defined ``standard provisions for Innovation Center models'' and would 
apply to all Innovation Center models as described

[[Page 43523]]

above. We propose specific revisions that would be necessary to expand 
the scope of several of the current general provisions, but otherwise 
propose that the general provisions (which would be referred to as the 
``standard provisions for Innovation Center models'') would not change. 
In particular, we propose that the substance of the following 
provisions would not change, except that they would apply to all 
Innovation Center Models as opposed to just the ETC and RO Models: 
Sec.  512.120 Beneficiary protections; Sec.  512.130 Cooperation in 
model evaluation and monitoring; Sec.  512.135 Audits and record 
retention; Sec.  512.140 Rights in data and intellectual property: 
Sec.  512.150 Monitoring and compliance; Sec.  512.160 Remedial action; 
Sec.  512.165 Innovation center model termination by CMS; Sec.  512.170 
Limitations on review; and Sec.  512.180 Miscellaneous provisions on 
bankruptcy and other notifications.

C. Proposed Revisions to the Titles, Basis and Scope Provision, and 
Effective Date

    We propose to amend the title of part 512 to read ``Standard 
Provisions for Innovation Center Models and Specific Provisions for the 
Radiation Oncology Model and the End Stage Renal Disease Model'' so 
that it more closely aligns with the other changes proposed herein and 
to ensure that the title indicates that part 512 includes both standard 
provisions for Innovation Center models and specific provisions for the 
RO and ETC Models. We also propose to amend the title of subpart A to 
read ``Standard Provisions for Innovation Center Models'' to use the 
term we propose to define the provisions codified at 42 CFR part 512 
subpart A.
    Additionally, we propose to amend Sec.  512.100(a) and (b) so that 
the standard provisions would take effect on January 1, 2025, and would 
apply to each Innovation Center model where that model's first 
performance period begins on or after January 1, 2025, unless the 
model's governing documentation indicates otherwise, as well as any 
Innovation Center model that begins testing its first performance 
period prior to January 1, 2025, if the model's governing documentation 
incorporates the provisions by reference in whole or in part. We 
propose to determine on a case-by-case basis, based on each model's 
unique features and design, whether the standard provisions would apply 
to a particular model, or whether we would specify alternate terms in 
the model's governing documentation.
    We believe that these standard provisions are necessary for the 
testing of the IOTA model, regardless of whether they are finalized as 
proposed for all Innovation Center models. As such, as an alternative 
to the previous proposal, we would propose making these standard 
provisions for Innovation Center models applicable to, and effective 
for, the IOTA Model beginning on January 1, 2025, absent extending the 
standard provisions to all Innovation Center models. Under such an 
alternative, the general provisions in the Specialty Care Models final 
rule would also still be applicable to the ETC Model and the RO Model.
    These proposed standard provisions would not, except as 
specifically noted in this section II. of this proposed rule, affect 
the applicability of other provisions affecting providers and suppliers 
under Medicare fee-for-service (FFS).
    We invite public comment on these proposed changes.

D. Provisions Revising Certain Definitions

    We propose to amend the definition of ``Innovation Center model'' 
at 42 CFR 512.110 by replacing the specific references to the RO and 
ETC Models with a definition consistent with section 1115A of the Act 
and intended to encompass all Innovation Center models. We propose to 
amend the definition for ``Innovation Center model'' to read as 
follows: ``an innovative payment and service delivery model tested 
under the authority of section 1115A(b) of the Act, including a model 
expansion under section 1115A(c) of the Act.''
    We propose to add a new definition of the term ``governing 
documentation'' at Sec.  512.110 to mean, ``the applicable Federal 
regulations, and the model-specific participation agreement, 
cooperative agreement, and any addendum to an existing contract with 
CMS, that collectively specify the terms of the Innovation Center 
model.'' We propose to add a new definition, ``standard provisions for 
Innovation Center models,'' at Sec.  512.110 to mean, ``the provisions 
codified in 42 CFR 512 Subpart A.'' We propose to add a new definition, 
``performance period,'' at Sec.  512.110 to mean, ``the period of time 
during which an Innovation Center model is tested and model 
participants are held accountable for cost and quality of care; the 
performance period for each Innovation Center model is specified in the 
governing documentation.''
    Further, we propose to amend the definitions of ``Innovation Center 
model activities,'' ``model beneficiary,'' and ``model participant'' to 
pertain to all ``Innovation Center models,'' as we propose to define 
that term, instead of just the models previously implemented under part 
512. As such, we propose to define ``Innovation Center model 
activities'' to mean ``any activities affecting the care of model 
beneficiaries related to the test of the Innovation Center model.'' We 
propose to define ``model beneficiary'' to mean ``a beneficiary 
attributed to a model participant or otherwise included in an 
Innovation Center model.'' We propose to define ``model participant'' 
to mean ``an individual or entity that is identified as a participant 
in the Innovation Center model.''
    We invite public comment on these proposed changes to the 
definitions of ``Innovation Center model,'' ``Innovation Center model 
activities,'' ``model beneficiary,'' and ``model participant'' and the 
proposed definitions of ``governing documentation,'' ``standard 
provisions for Innovation Center models,'' and ``performance period.''

E. Proposed Reconsideration Review Process

    We propose to add a new Sec.  512.190 to part 512 subpart A to 
codify a reconsideration review process, based on processes implemented 
under current Innovation Center models. The process would enable model 
participants to contest determinations made by CMS in certain 
Innovation Center models, where model participants would not otherwise 
have a means to dispute determinations made by CMS. We propose at Sec.  
512.190(a)(1) that such a reconsideration process would apply only to 
Innovation Center models that waive section 1869 of the Act, which 
governs determinations and appeals in Medicare, or where section 1869 
would not apply because model participants are not Medicare-enrolled. 
We propose at Sec.  512.190(a)(2) that only model participants may 
utilize the dispute resolution process, unless the governing 
documentation for the Innovation Center model states otherwise. Such 
limitations with respect to such models are, we believe, appropriate, 
because with respect to such models, model participants do not have 
another means to dispute determinations made by CMS. We propose to 
codify a reconsideration review process in regulation in order to have 
a transparent and consistent method of reconsideration for model 
participants participating in models that do not utilize the standard 
reconsideration process outlined in section 1869 of the Act.
    This proposed reconsideration review process would be utilized 
where a model-specific determination has been made and the affected 
model participant

[[Page 43524]]

disagrees with, and wishes to challenge, that determination. Each 
Innovation Center model features a unique payment and service delivery 
model, and, as such, requires its own model-specific determination 
process. Each Innovation Center model's governing documentation details 
the model-specific determinations made by CMS, which may include, but 
are not limited to, model-specific payments, beneficiary attribution, 
and determinations regarding remedial actions. Each Innovation Center 
model's governing documentation also includes specific details about 
when a determination is final and may be disputed through the model's 
reconsideration review processes.
    We propose at Sec.  512.190(b) that model participants may request 
reconsideration of a determination made by CMS in accordance with an 
Innovation Center model's governing documentation only if such 
reconsideration is not precluded by section 1115A(d)(2) of the Act, 
part 512 subpart A, or the model's governing documentation. A model 
participant may challenge, by requesting review by a CMS 
reconsideration official, those final determinations made by CMS that 
are not precluded from administrative or judicial review. We propose at 
Sec.  512.190(b)(i) that the CMS reconsideration official would be 
someone who is authorized to receive such requests and was not involved 
in the initial determination issued by CMS or, if applicable, the 
timely error notice review process. We propose at Sec.  512.190(b)(ii) 
that the reconsideration review request would be required to include a 
copy of CMS's initial determination and contain a detailed written 
explanation of the basis for the dispute, including supporting 
documentation. We propose at Sec.  512.190(b)(iii) that the request for 
reconsideration would have to be made within 30 days of the date of 
CMS' initial determination for which reconsideration is being requested 
via email to an address as specified by CMS in the governing 
documentation. At Sec.  512.190(b)(2), we propose that requests that do 
not meet the requirements of paragraph (b)(1) would be denied.
    We propose at Sec.  512.190(b)(3) that the reconsideration official 
would send a written acknowledgement to CMS and to the model 
participant requesting reconsideration within 10 business days of 
receiving the reconsideration request. The acknowledgement would set 
forth the review procedures and a schedule that would permit each party 
an opportunity to submit position papers and documentation in support 
of its position for consideration by the reconsideration official.
    We propose to codify at Sec.  512.190(b)(4) that, to access the 
reconsideration process for a determination concerning a model-specific 
payment where the Innovation Center model's governing documentation 
specifies an initial timely error notice process, the model participant 
must first satisfy those requirements before submitting a 
reconsideration request under this process. Should a model participant 
fail to timely submit an error notice with respect to a particular 
model-specific payment, we propose that the reconsideration review 
process would not be available to the model participant with regard to 
that model-specific payment.
    We propose to codify standards for reconsideration at Sec.  
512.190(c). First, during the course of the reconsideration, we propose 
that both CMS and the party requesting the reconsideration must 
continue to fulfill all responsibilities and obligations under the 
governing documentation during the course of any dispute arising under 
the governing documentation. Second, the reconsideration would consist 
of a review of documentation timely submitted to the reconsideration 
official and in accordance with the standards specified by the 
reconsideration official in the acknowledgement at Sec.  512.190(b)(3). 
Finally, we propose that the model participant would bear the burden of 
proof to demonstrate with clear and convincing evidence to the 
reconsideration official that the determination made by CMS was 
inconsistent with the terms of the governing documentation.
    We propose to codify at Sec.  512.190(d) that the reconsideration 
determination would be an on-the-record review. By this, we mean a 
review that would be conducted by a CMS reconsideration official who is 
a designee of CMS who is authorized to receive such requests under 
proposed Sec.  512.190(b)(1)(i), of the position papers and supporting 
documentation that are timely submitted and in accordance with the 
schedule specified under proposed Sec.  512.190(b)(3)(ii) and that meet 
the standards of submission under proposed Sec.  512.190(b)(1) as well 
as any documents and data timely submitted to CMS by the model 
participant in the required format before CMS made the initial 
determination that is the subject of the reconsideration request. We 
propose at Sec.  512.190(d)(2) that the reconsideration official would 
issue to the parties a written reconsideration determination. Absent 
unusual circumstances, in which the reconsideration official would 
reserve the right to an extension upon written notice to the model 
participant, the reconsideration determination would be issued within 
60 days of CMS's receipt of the timely filed position papers and 
supporting documentation in accordance with the schedule specified 
under proposed Sec.  512.190(b)(3)(ii). Under proposed Sec.  
512.190(d)(3), the determination made by the CMS reconsideration 
official would be final and binding 30 days after its issuance, unless 
the model participant or CMS were to timely request review of the 
reconsideration determination by the CMS Administrator in accordance 
with Sec. Sec.  512.190(e)(1) and (2).
    We propose to codify at Sec.  512.190(e) a process for the CMS 
Administrator to review reconsideration determinations made under Sec.  
512.190(d). We propose that either the model participant or CMS may 
request that the CMS Administrator review the reconsideration 
determination. The request to the CMS Administrator would have to be 
made via email, within 30 days of the reconsideration determination, to 
an email address specified by CMS. The request would have to include a 
copy of the reconsideration determination, as well as a detailed 
written explanation of why the model participant or CMS disagrees with 
the reconsideration determination. The CMS Administrator would promptly 
send the parties a written acknowledgement of receipt of the request 
for review. The CMS Administrator would send the parties notice of 
whether the request for review was granted or denied. If the request 
for review is granted, the notice would include the review procedures 
and a schedule that would permit each party to submit a brief in 
support of the party's positions for consideration by the CMS 
Administrator. If the request for review is denied, the reconsideration 
determination would be final and binding as of the date of denial of 
the request for review by the CMS Administrator. If the request for 
review by the CMS Administrator is granted, the record for review would 
consist solely of timely submitted briefs and evidence contained in the 
record of the proceedings before the reconsideration official and 
evidence as set forth in the documents and data described in proposed 
Sec.  512.190(d)(1)(ii); the CMS Administrator would not consider 
evidence other than information set forth in the documents and data 
described in proposed Sec.  512.190(d)(1)(ii). The CMS

[[Page 43525]]

Administrator would review the record and issue to the parties a 
written determination that would be final and binding as of the date 
the written determination is sent.
    We invite public comment on the proposed reconsideration review 
process for Innovation Center models.

III. Proposed Increasing Organ Transplant Access (IOTA) Model

A. Introduction

    In this proposed rule, we are proposing to test the IOTA Model, a 
new mandatory Medicare alternative payment model under the authority of 
the Innovation Center, that would begin on January 1, 2025, and end on 
December 31, 2030. The IOTA Model would test whether using performance-
based incentive payments in the form of upside risk payments and 
downside risk payments to and from select transplant hospitals 
increases the number of kidney transplants furnished to patients with 
ESRD, thereby reducing Medicare expenditures while preserving or 
enhancing quality of care.
    The goal of the proposed performance-based payments is: to increase 
the number of kidney transplants furnished to ESRD patients placed on a 
kidney transplant hospital's waitlist; encourage investments in value-
based care and quality improvement activities, particularly those that 
promote an equitable kidney transplant process prior to, during, and 
post transplantation for all patients; encourage better use of the 
current supply of deceased donor organs and greater provider and 
community collaborations to address medical and non-medical needs of 
patients; and increased awareness, education, and support for living 
donations. The IOTA Model payment structure would also promote IOTA 
participant accountability by linking performance-based payments to 
quality. We theorize that increasing the number of kidney transplants 
furnished to ESRD patients on the participating hospitals' waitlists 
would reduce Medicare expenditures by reducing dialysis expenditures 
and avoidable health care service utilization and would improve the 
quality of life for patients with ESRD.
    As discussed in section III.B of this proposed rule, studies show 
that kidney transplant hospitals are underutilizing donor kidneys and 
have become more conservative in accepting organs for transplantation, 
with notable variation by region and across transplant hospitals.\9\ 
The IOTA Model aims to address these access and equity problems through 
financial incentives that reward IOTA participants that improve their 
kidney organ offer acceptance rate ratios over time or hold them 
financially accountable for not doing so. The IOTA Model's proposed 
payment structure would include upside or downside performance-based 
incentive payments (``upside risk payment'' or ``downside risk 
payment'') for kidney transplant hospitals selected to participate in 
the IOTA Model (``IOTA participant''), with these payments being tied 
to performance on achievement, efficiency, and quality domains.
---------------------------------------------------------------------------

    \9\ Mohan, S., Chiles, M.C., Patzer, R.E., Pastan, S.O., Husain, 
S.A., Carpenter, D.J., Dube, G.K., Crew, R.J., Ratner, L.E., & 
Cohen, D.J. (2018). Factors leading to the discard of deceased donor 
kidneys in the United States. Kidney International, 94(1), 187-198. 
https://doi.org/10.1016/j.kint.2018.02.016.
---------------------------------------------------------------------------

    The achievement domain would assess the number of kidney 
transplants performed relative to a participant-specific target, with 
performance on this domain being worth up to 60 points. The efficiency 
domain would assess kidney organ offer acceptance rate ratios relative 
to a national rate for all kidney transplant hospitals, including those 
not selected to participate in the model, with performance on this 
domain being worth up to 20 points. The quality domain would assess 
performance based on post-transplant outcomes at one-year after 
transplant and a proposed set of quality measures, with performance on 
this domain being worth up to 20 points. The achievement domain would 
be weighted more heavily than the other two domains because increasing 
the number of transplants is a key goal of the model and would be a 
primary factor in determining the amount of the performance-based 
payment.
    The final performance score for each IOTA participant would be the 
sum of the points earned across the achievement domain, efficiency 
domain, and quality domain. The final performance score would determine 
whether an upside risk payment or downward risk payment would be owed 
and the amount of such payment. Specifically:
     For PY 1, if an IOTA participant has a final performance 
score between 60 and 100 points, it would qualify for the upside risk 
payment in accordance with the proposed calculation methodology 
described in section III.C.6.c(a) of this proposed rule (final 
performance score minus 60, then divided by 60, then multiplied by 
$8,000, then multiplied by the number of kidney transplants furnished 
by the IOTA participant to beneficiaries with Medicare as a primary or 
secondary payer during the PY).
     For PY 1, if an IOTA participant has a final performance 
score below 60, it would fall into a neutral zone where no upside risk 
payment and no downside risk payment would apply.
     For PY 2 and each subsequent PY (PYs 2-6) if an IOTA 
participant achieves a final performance score of 41 to 59 points, it 
would fall into a neutral zone where no upside risk payment and no 
downside risk payment would apply.
     For PY 2 and each subsequent PY, if an IOTA participant 
achieves a final performance score of 40 points or below, it would 
qualify for the downside risk payment in accordance with the proposed 
calculation methodology described in section III.C.6.c.(b). of this 
proposed rule (final performance score minus 40, then divided by 40, 
then multiplied by -$2,000, then multiplied by the number of kidney 
transplants furnished by the IOTA participant to beneficiaries with 
Medicare as a primary or secondary payer during the PY).
    We recognize the complexity of the transplant ecosystem, which 
requires coordination between transplant hospitals, other health care 
providers, organ procurement organizations (OPOs), patients, potential 
donors, and their families. The proposed IOTA Model does not prescribe 
or require specific processes or policy approaches that each selected 
IOTA participant must implement for purposes of the model test.
    We believe the IOTA Model would complement other efforts in 
relation to the transplant ecosystem to enhance health and safety 
outcomes, increase transparency, increase the number of transplants, 
and reduce disparities. We also believe that the proposed payment 
methodology would act in concert with measures that are currently under 
development by HRSA to increase the numbers of both deceased and living 
donor organ transplants.
    This proposed model falls within a larger framework of activities 
initiated by the Federal Government during the past several years and 
planned for the upcoming year to enhance the donation, procurement, and 
transplantation of solid organs. This Federal collaborative, called the 
Organ Transplantation Affinity Group (OTAG), is a coordinated group 
working together to strengthen accountability, equity, and performance 
in organ donation, procurement, and transplantation.\10\
---------------------------------------------------------------------------

    \10\ Moody-Williams, J.D., & Nair, S. (2023, September 15). 
Organ Transplantation Affinity Group (OTAG): Strengthening 
accountability, equity, and performance  CMS. BLOG. https://www.cms.gov/blog/organ-transplantation-affinity-group-otag-strengthening-accountability-equity-and-performance.

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

[[Page 43526]]

B. Background

    A review of the literature on kidney transplantation shows that the 
increasing numbers of kidney transplants is unable to keep pace with 
the increasing need for organs.\11\ While more people die waiting for a 
kidney transplant, the short- and long-term outcomes of patients who 
undergo kidney transplantation have improved, despite both recipients 
and donors increasing in age and adverse health conditions.\12\ Recent 
studies show that transplant hospitals have become more conservative in 
accepting organs for transplantation when offered for specific 
patients, avoiding the use of less-than-ideal organs on account of 
perceived risk.\13\ Wide variation among geographic regions and 
transplant hospitals in rates of kidney transplantation, along with 
access and equity issues, raises the need to hold kidney transplant 
hospitals accountable for performance.\14\ The IOTA Model proposes a 
two-sided performance-based payment structure that rewards IOTA 
participants for high performance in the achievement, efficiency, and 
quality domains, and imposes financial accountability on IOTA 
participants that perform poorly on those domains. We propose the IOTA 
Model as a complement to wider efforts aimed at transplant ecosystem 
performance and equity improvements. Ultimately, we seek a set of 
interventions that focus on ESRD patients in need of a kidney 
transplant. In this section of the proposed rule, we summarize the 
transplant ecosystem and HHS oversight within CMS and HRSA related to 
kidney transplantation, highlight related initiatives and priorities 
nationally, and outline our rationale for the proposed IOTA Model 
informed by literature, data, and studies.
---------------------------------------------------------------------------

    \11\ Too Many Donor Kidneys Are Discarded in U.S. Before 
Transplantation--Penn Medicine. (2020, December 16). 
www.pennmedicine.org. https://www.pennmedicine.org/news/news-releases/2020/december/too-many-donor-kidneys-are-discarded-in-us-before-transplantation.
    \12\ Hariharan, S., Israni, A.K., & Danovitch, G. (2021). Long-
Term Survival after Kidney Transplantation. New England Journal of 
Medicine, 385(8), 729-743. https://doi.org/10.1056/nejmra2014530.
    \13\ Stewart, D.E., Garcia, V.C., Rosendale, J.D., Klassen, 
D.K., & Carrico, B.J. (2017). Diagnosing the Decades-Long Rise in 
the Deceased Donor Kidney Discard Rate in the United States. 
Transplantation, 101(3), 575-587. https://doi.org/10.1097/tp.0000000000001539.
    \14\ Mohan, S., Chiles, M.C., Patzer, R.E., Pastan, S.O., 
Husain, S.A., Carpenter, D.J., Dube, G.K., Crew, R.J., Ratner, L.E., 
& Cohen, D.J. (2018). Factors leading to the discard of deceased 
donor kidneys in the United States. Kidney International, 94(1), 
187-198. https://doi.org/10.1016/j.kint.2018.02.016.
---------------------------------------------------------------------------

1. The Transplant Ecosystem
    Kidney transplantation occurs within an overall organ donation and 
transplantation system (also known and referred to as the transplant 
ecosystem) that comprises a vast network of institutions dedicated to 
ensuring that patients are evaluated and, if appropriate, placed onto 
the organ transplant waitlist, and that those on the organ transplant 
waitlist receive lifesaving organ transplants. Transplantation of 
livers, hearts, lungs, and other organs is also well established within 
the U.S. health care system. The transplant ecosystem includes the 
Organ Procurement and Transplantation Network (OPTN); Organ Procurement 
Organizations (OPOs); transplant hospitals and providers; 
histocompatibility laboratories that provide blood, tissue, and 
antibody testing for the organ matching process; and patients, 
including ESRD patients in need of a transplant, their families, and 
caregivers.\15\ For kidney transplantation, it also includes ESRD 
facilities, commonly known as dialysis facilities.
---------------------------------------------------------------------------

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

    The National Organ Transplant Act of 1984, referred to herein as 
NOTA, established the OPTN, with HHS oversight, to manage and operate 
the national organ transplantation system (42 U.S.C. 274). The OPTN 
coordinates the nation's organ procurement, distribution, and 
transplantation systems. The OPTN is a network of clinical experts, 
patients, donor families, and community stakeholders who work 
collectively to develop, implement, and monitor organ allocation policy 
and performance of the organ transplant ecosystem.
    Organ Procurement Organizations (OPOs) are non-profit organizations 
operating under contract with the Federal Government that are charged, 
under section 371(b) of the Public Health Service Act (PHS Act, 42 
U.S.C. 273(b)) with activities including, but not limited to, 
identifying potential organ donors, providing for the acquisition and 
preservation of donated organs, the equitable allocation of donated 
organs, and the transportation of donated organs to transplant 
hospitals. Section 371(b) of the Public Health Services Act requires 
that an OPO must have a defined service area, a concept that is defined 
at 42 CFR part 486 subpart G as the Donation Service Area (DSA). 
Section 1138(b) of the Act states that the Secretary may not designate 
more than one OPO to serve each DSA. There are currently 56 OPOs that 
serve the United States and Puerto Rico.
    Section 1138(b) of the Act lays out the requirements that an OPO 
must meet to have its costs reimbursed by the Secretary. CMS sets out 
the components of allowable Medicare organ acquisition costs at 42 CFR 
413.402(b). Allowable organ acquisition costs are those costs incurred 
in the acquisition of organs intended for transplant, and include, but 
are not limited to: costs associated with special care services, the 
surgeon's fee for excising the deceased donor organ from the donor 
patient (limited to $1,250 for kidneys), operating room and other 
inpatient ancillary services provided to the living or deceased donor, 
organ preservation and perfusion costs, donor and beneficiary 
evaluation, and living donor complications. OPOs and transplant 
hospitals may incur organ acquisition costs and include these and some 
additional administrative and general costs on the Medicare cost 
report.
    The CMS conditions for coverage for OPOs at 42 CFR 486.322 require 
an OPO to have written agreements with 95 percent of the Medicare and 
Medicaid certified hospitals and critical access hospitals in its DSA 
that have a ventilator and an operating room and have not been granted 
a waiver to work with another OPO. These hospitals, known as donor 
hospitals, are required by the CMS conditions of participation for 
hospitals at 42 CFR 482.45 to have an agreement with an OPO under which 
the donor hospital must notify the OPO of patients who are expected to 
die imminently and of patients who have died in the hospital. (Under 
the hospital conditions of participation, such an agreement is required 
of all hospitals that participate in Medicare.) Also, under the 
hospital conditions of participation, donor hospitals are responsible 
for informing donor patient families of the option to donate organs, 
tissues, and eyes, or to decline to donate; and to work collaboratively 
with the OPO to educate hospital staff on donation, improve its 
identification of potential donors, and work with the OPO to manage the 
potential donor patient while testing and placement of the potential 
donor organ occurs.
    At 42 CFR 482.70, CMS defines a transplant hospital as ``a hospital 
that furnishes organ transplants and other medical and surgical 
specialty services

[[Page 43527]]

required for the care of transplant patients,'' and a transplant 
program as ``an organ-specific transplant program within a transplant 
hospital,'' as so defined. In accordance with 42 CFR 482.98, a 
transplant program must have a primary transplant surgeon and a 
transplant physician with the appropriate training and experience to 
provide transplantation services, who are immediately available to 
provide transplantation services when an organ is offered for 
transplantation. The transplant surgeon is responsible for providing 
surgical services related to transplantation, and the transplant 
physician is responsible for providing and coordinating transplantation 
care.
    In accordance with CMS' Conditions for Coverage (CfC) for ESRD 
Facilities at 42 CFR part 494, ESRD facilities are charged with 
delivering safe and adequate dialysis to ESRD patients, and, among 
other requirements, informing patients of their treatment modalities, 
including dialysis and kidney transplantation. The CfCs require ESRD 
facilities to conduct a patient assessment that includes evaluation of 
suitability for referral for transplantation, based on criteria 
developed by the prospective transplantation center and its surgeon(s). 
General nephrologists refer patients for evaluation for kidney 
transplants.\16\ Candidates for kidney transplant undergo a rigorous 
evaluation by a transplant program prior to placement on a waitlist, 
involving evaluation by a multidisciplinary team for conditions 
pertaining to the potential success of the transplant, the possibility 
of recurrence, and surgical issues including frailty, obesity, diabetes 
and other causes of ESRD, infections, malignancies, cardiac disease, 
pulmonary disease, peripheral arterial disease, neurologic disease, 
hematologic conditions, and gastrointestinal and liver disease and an 
immunological assessment; a psychosocial assessment; assessment of 
adherence behaviors; and tobacco counseling.\17\
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    \16\ Virmani, S., & Asch, W.S. (2020). The Role of the General 
Nephrologist in Evaluating Patients for Kidney Transplantation: Core 
Curriculum 2020. American Journal of Kidney Diseases, 76, 567-579. 
https://doi.org/10.1053/j.ajkd.2020.01.001.
    \17\ Chadban, S.J., Ahn, C., Axelrod, D.A., Foster, B.J., 
Kasiske, B.L., Kher, V., Kumar, D., Oberbauer, R., Pascual, J., 
Pilmore, H.L., Rodrigue, J.R., Segev, D.L., Sheerin, N.S., Tinckam, 
K.J., Wong, G., & Knoll, G.A. (2020). KDIGO Clinical Practice 
Guideline on the Evaluation and Management of Candidates for Kidney 
Transplantation. Transplantation, 104(4S1), S11. https://doi.org/10.1097/TP.0000000000003136.
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    Once placed on the waitlist, potential recipients must maintain 
active status to be eligible to receive a deceased donor 
transplant.\18\ An individual may receive a status of `inactive' if 
they are missing lab results, contact information, or any of the other 
requirements that would be necessary for them to receive an organ 
transplant if offered. An individual may only receive an organ offer if 
they have a status of `active'.\19\ Each transplant hospital has its 
own waitlist, and patients can attempt to be placed on multiple 
waitlists; OPTN maintains a national transplant waiting list that 
encompasses the waitlists for all kidney transplant 
hospitals.20 21 Individuals already on dialysis continue to 
receive regular dialysis treatments while waiting for an organ to 
become available. After surgery, a transplant nephrologist manages the 
possible outcomes of organ rejection and infection, and other medical 
complications.\22\
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    \18\ National kidney Foundation. (2017, February 10). The Kidney 
Transplant Waitlist--What You Need to Know. National Kidney 
Foundation. https://www.kidney.org/atoz/content/transplant-waitlist.
    \19\ The kidney transplant waitlist. (n.d.). Transplant Living. 
https://transplantliving.org/kidney/the-kidney-transplant-waitlist/.
    \20\ National kidney Foundation. (2019, June 12). Understanding 
the transplant waitlist. National Kidney Foundation. https://www.kidney.org/content/understanding-transplant-waitlist.
    \21\ National kidney Foundation. (2016, August 4). Multiple 
Listing for Kidney Transplant. National Kidney Foundation. https://www.kidney.org/atoz/content/multiple-listing.
    \22\ Transplant Nephrology Fellowship. (n.d.). 
Www.hopkinsmedicine.org. Retrieved May 30, 2023, from https://
www.hopkinsmedicine.org/nephrology/education/
transplant_fellowship.html#:~:text=Diagnose%20and%20manage%20acute%20
and.
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2. HHS Oversight and Priorities
    HRSA, which oversees the OPTN, and CMS play a vital role in 
protecting the health and safety of Americans as they engage with the 
U.S. health care system.\23\ The OPTN operates a complex network of 
computerized interactions whereby specific deceased donor organs get 
matched to individual patients on the national transplant waiting list. 
The Scientific Registry of Transplant Recipients (SRTR), operated under 
contract with HRSA, is responsible for providing statistical and 
analytic support to the OPTN. Section 373 of the PHS Act requires the 
operation of the SRTR to support ongoing evaluation of the scientific 
and clinical status of solid organ transplantation.\24\
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    \23\ On March 22, 2023, HRSA announced an initiative that 
included several actions to strengthen accountability and 
transparency in the OPTN. These actions include modernization of the 
OPTN information technology system. HRSA also intends to issue 
contract solicitations for multiple awards to support the OPTN.
    \24\ Mission, Vision, and Values. (n.d.). Www.srtr.org. https://www.srtr.org/about-srtr/mission-vision-and-values/.
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    CMS oversees and evaluates OPO performance. OPOs must meet 
performance measures and participate in, and abide by certain rules of, 
the OPTN.\25\ The PHS Act requires the Secretary to establish outcome 
and process performance measures to recertify OPOs (Part H section 371; 
42 U.S.C. 273). CMS has promulgated the OPO CfCs at 42 CFR part 486 
subpart G.
---------------------------------------------------------------------------

    \25\ U.S. Congress. (1934) United States Code: Social Security 
Act, 42 U.S.C. 301-Suppl. 4 1934.
---------------------------------------------------------------------------

    Additionally, the OPTN Bylaws specify that OPOs whose observed 
organ yield rates fall below the expected rates by more than a 
specified threshold would be reviewed by the OPTN Membership 
Professional Standards Committee (MPSC).\26\ CMS also conducts 
oversight of transplant programs, located within transplant hospitals, 
which must abide by both the hospital and the transplant program 
conditions of participation (CoPs). CMS contracts with quality 
improvement entities such as the ESRD Networks and Quality Improvement 
Organizations to provide technical support to providers and patients 
seeking improvements in the transplant ecosystem.
---------------------------------------------------------------------------

    \26\ Bylaws--OPTN. (n.d.). Optn.transplant.hrsa.gov. Retrieved 
May 30, 2023, from https://optn.transplant.hrsa.gov/policies-bylaws/bylaws/.
---------------------------------------------------------------------------

    Medicare covers certain transplant-related services when provided 
at a Medicare-approved facility. Medicare Part A covers the costs 
associated with a Medicare kidney transplant procedure received in a 
Medicare-certified hospital and any additional inpatient hospital care 
needed following the procedure, and organ acquisition costs including 
kidney registry fees and laboratory tests associated with the 
evaluation of a Medicare transplant candidate. The evaluation or 
preparation of a living donor, the living donor's donation of the 
kidney, and postoperative recovery services directly related to the 
living donor's kidney donation are covered under Medicare. In addition, 
deductible and coinsurance requirements do not apply to living donors 
for services furnished to an individual in connection with the donation 
of a kidney for transplant surgery. Medicare Part B coverage includes 
the surgeon's fees for performing the kidney transplant procedure and 
perioperative care. Medicare Part B also covers physician services for 
the living kidney donor without regard to whether the service would 
otherwise be covered by

[[Page 43528]]

Medicare. Part A and Part B share responsibility for covering blood, 
including packed red blood cells, blood components and the cost of 
processing and receiving blood.
    Medicare Part B covers immunosuppressive drugs following an organ 
transplant for which payment is made under Title XVIII. 
Immunosuppressive drugs following an organ transplant are covered by 
Part D when an individual did not have Part A at the time of the 
transplant. Beneficiaries who have Medicare due to ESRD alone lose 
Medicare coverage 36 months following a successful kidney transplant. 
Section 402(a) of the Consolidated Appropriations Act (CAA) of 2021 
added section 1836(b) of the Act to provide coverage for 
immunosuppressive drugs beginning January 1, 2023, for eligible 
individuals whose eligibility for Medicare based on ESRD ends by reason 
of section 226A(b)(2) of the Act for those three-years post kidney 
transplant. Under section 1833 of the Act, the amounts paid by Medicare 
for immunosuppressive drugs are equal to 80 percent of the applicable 
payment amount; beneficiaries are thus subject to a 20 percent 
coinsurance for immunosuppressive drugs covered by both Part B and the 
Medicare Part B Immunosuppressive Drug Benefit (Part B-ID).
3. Federal Government Initiatives To Enhance Organ Transplantation
a. CMS Regulatory Initiatives To Enhance Organ Transplantation
    On September 30, 2019, we published the final rule, ``Medicare and 
Medicaid Programs; Regulatory Provisions To Promote Program Efficiency, 
Transparency, and Burden Reduction; Fire Safety Requirements for 
Certain Dialysis Facilities; Hospital and Critical Access Hospital 
(CAH) Changes To Promote Innovation, Flexibility, and Improvement in 
Patient Care'' (84 FR 51732). The rulemaking, in part, aimed to address 
the concern that too many organs are being discarded that could be 
transplanted successfully, including hearts, lungs, livers, and 
kidneys. This rule implemented changes to the transplant program 
regulations, eliminating requirements for re-approval of transplant 
programs pertaining to data submission, clinical experience, and 
outcomes. We believed that the removal of these requirements aligned 
with our goal of increasing access to kidney transplants by increasing 
the utilization of organs from deceased donors and reducing the organ 
discard rate (84 FR 51749). We sought improved organ procurement, 
greater organ utilization, and reduction of burden for transplant 
hospitals, while still maintaining the importance of safety in the 
transplant process.
    On December 2, 2020, we issued a final rule titled, ``Medicare and 
Medicaid Programs; Organ Procurement Organizations Conditions for 
Coverage: Revisions to the Outcome Measure Requirements for Organ 
Procurement Organizations'' (85 FR 77898), which revised the OPO CfCs 
by replacing the previous outcome measures with new transparent, 
reliable, and objective outcome measures. In modifying the metrics used 
for assessing OPO performance, we sought to promote greater utilization 
of organs that might not otherwise be recovered or used due to 
perceived organ quality.\27\
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    \27\ The Organ Procurement Organizations Annual Public 
Aggregated Performance Report for 2023 is available at https://www.cms.gov/files/document/opo-annual-public-performance-report-2023.pdf.
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    While these regulatory changes recently went into effect with the 
goal of improving the performance of transplant hospitals and OPOs and 
to promote the procuring of organs and delivering them to prospective 
transplant recipients, we acknowledged the need for improvements in 
health, safety, and outcomes across the transplant ecosystem, including 
in transplant programs, OPOs, and ESRD facilities.28 29 In 
particular, we recognize that further action must be taken to address 
disparities and inequities observed across transplant hospitals.
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    \28\ One study--Doby, B.L., Ross-Driscoll, K., Shuck, M., 
Wadsworth, M., Durand, C.M., & Lynch, R.J. (2021). Public discourse 
and policy change: Absence of harm from increased oversight and 
transparency in OPO Performance. American Journal of 
Transplantation, 21(8), 2646-2652. https://doi.org/10.1111/ajt.16527--showed that deceased donor organ donation increased 
during 2019, that is., during the period of public debate about 
regulating OPO performance.
    \29\ In addition, CMS finalized a policy in the final rule for 
FY 2023 for the Medicare Physician Fee Schedule that Medicare Part A 
and Part B payment can be made for dental or oral examinations, 
including necessary treatment, performed as part of a necessary 
workup prior to organ transplant surgery. In the final rule, CMS 
describes certain dental services as inextricably linked and 
integral to the clinical success of organ transplantation. (87 FR 
69671-69675).
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    We published a request for information in the Federal Register on 
December 3, 2021, titled ``Request for Information: Health and Safety 
Requirements for Transplant Programs, Organ Procurement Organizations, 
and End-Stage Renal Facilities'' (86 FR 68594) (hereafter known as the 
``Transplant Ecosystem RFI''). This RFI solicited public comments on 
potential changes to the requirements that transplant programs, OPOs, 
and ESRD facilities must meet to participate in the Medicare and 
Medicaid programs. Specifically, we solicited public comments on ways 
to:
     Continue to improve systems of care for all patients in 
need of a transplant;
     Increase the number of organs available for transplant for 
all solid organ types;
     Encourage the use of dialysis in alternate settings or 
modalities over in-center hemodialysis where clinically appropriate and 
advantageous;
     Ensure that the CMS and HHS policies appropriately 
incentivize the creation and use of future new treatments and 
technologies; and
     Harmonize requirements across government agencies to 
facilitate these objectives and improve quality across the organ 
donation and transplantation ecosystem.
    We also solicited information related to opportunities, 
inefficiencies, and inequities in the transplant ecosystem and what can 
be done to ensure all segments of our healthcare systems are invested 
and accountable in ensuring improvements to organ donation and 
transplantation rates (86 FR 68596). The Transplant Ecosystem RFI 
focused on questions in the areas of transplantation, kidney health and 
ESRD facilities, and OPOs. For transplant programs, specific topics 
included transplant program CoPs, patient rights, and equity in organ 
transplantation and organ donation (86 FR 68596). For kidney health and 
ESRD facilities, topics included maintaining and improving health of 
patients, ways to identify those at risk of developing chronic kidney 
disease (CKD), improving detection rates of CKD, and ways to close the 
CKD detection, education, and care health equity gap (86 FR 68599). 
Other topics included home dialysis, dialysis in alternative settings 
such as nursing homes and mobile dialysis, and alternate models of care 
(86 FR 68600). For OPOs, specific topics included assessment and 
recertification, organ transport and tracking, the donor referral 
process, organ recovery centers, organ discards, donation after cardiac 
death, tissue banks, organs for research, and vascular composite 
organs. (86 FR 68601 through 68606)
    The Transplant Ecosystem RFI followed three executive orders 
addressing health equity that were issued by President Biden on January 
20 and January 21, 2021--
     Executive Order on Advancing Racial Equity and Support for 
Underserved Communities Through the Federal Government (E.O. 13985, 86 
FR 7009, January 20, 2021);

[[Page 43529]]

     Executive Order on Preventing and Combating Discrimination 
on the Basis of Gender Identity or Sexual Orientation (E.O. 13988, 86 
FR 7023, January 25, 2021); and
     Executive Order on Ensuring an Equitable Pandemic Response 
and Recovery (E.O. 13995, 86 FR 7193, January 26, 2021).
    The RFI was among several issued by CMS in 2021 to request public 
comment on ways to advance health equity and reduce disparities in our 
policies and programs.
    CMS's regulatory initiatives since 2018 pertaining to organ 
donation and transplantation have included final rules modifying CoPs 
and CfCs for transplant programs (84 FR 51732) and OPOs (85 FR 77898), 
respectively, and our recent RFI on transplant program CoPs, OPO CfCs, 
and the ESRD facility CfCs (86 FR 68594). These regulations and RFIs 
have sought to foster greater health and safety for patients, greater 
transparency for all patients, increases in organ donation and 
transplantation, and reduced disparities in organ donation and 
transplantation. Through these regulations, we are working to attain 
these goals by designing and implementing policies that improve health 
for all people affected by the transplant ecosystem.
b. CMS Innovation Center Payment Models
    The Innovation Center is currently pursuing complementary 
alternative payment model tests--the ESRD Treatment Choices (ETC) Model 
and the Kidney Care Choices (KCC) Model--aimed at enhancing kidney 
transplantation and improving health-related outcomes for patients with 
late-stage CKD and ESRD, thereby reducing costs to the Medicare 
program. The impetus for the ETC and KCC Models originated with 
evaluation findings for the earlier Comprehensive ESRD Care (CEC) 
Model, which ran from October 2015 through March 2021, that showed 
large dialysis organizations achieving positive clinical and financial 
outcomes relating to services to Medicare beneficiaries receiving 
dialysis, though the CEC Model did not achieve net savings to 
Medicare.\30\ The CEC Model focused on patients being treated in ESRD 
facilities, with no explicit incentives to encourage increases in 
kidney transplantation.
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    \30\ The results of the CMS-sponsored evaluation of the CEC 
Model are available at https://innovation.cms.gov/innovation-models/comprehensive-esrd-care. The 5-year model test reduced Medicare 
expenses by $217 million, or 1.3 percent relative to the pre-CEC 
period. These results do not account for shared savings payments to 
the model participants. There was a 3 percent decrease in the number 
of hospitalizations and a 0.4 percent increase in the number of 
outpatient dialysis sessions for Medicare beneficiaries in CEC 
compared to non-CEC beneficiaries. In addition, the CEC Model 
improved key quality outcomes.
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    The ETC and KCC Models have engaged a broader range of health care 
providers beyond ESRD facilities, including nephrology professionals 
and transplant providers, and address transplantation. Each model 
includes direct financial incentives for increasing the number of 
kidney transplants.
    The ETC Model, which began January 1, 2021, and which is scheduled 
to end on June 30, 2027, is a mandatory model that tests whether 
greater use of home dialysis and kidney transplantation for Medicare 
beneficiaries with ESRD reduces Medicare expenditures while preserving 
or enhancing the quality of care furnished to those beneficiaries. We 
established requirements for the ETC Model in the Medicare Program; 
Specialty Care Models to Improve Quality of Care and Reduce 
Expenditures final rule (85 FR 61114 through 61381). These requirements 
are codified at 42 CFR subpart C. The ETC Model tests the effects of 
certain Medicare payment adjustments to participating ESRD facilities 
and Managing Clinicians (clinicians who manage ESRD beneficiaries and 
bill the Monthly Capitation Payment (MCP)). The payment adjustments are 
designed to encourage greater utilization of home dialysis and kidney 
transplantation, support beneficiary modality choice, reduce Medicare 
expenditures, and preserve or enhance quality of care. Under the ETC 
Model, CMS makes upward adjustments to certain payments under the ESRD 
Prospective Payment System (PPS) to certain dialysis facilities on home 
dialysis claims, and upward adjustments to the MCP paid to certain 
Managing Clinicians on home dialysis-related claims (85 FR 61117). In 
addition, CMS makes upward and downward adjustments to PPS payments to 
participating ESRD facilities and to the MCP paid to participating 
Managing Clinicians based on the Participant's home dialysis rate and 
transplant waitlisting and living donor transplant rate (85 FR 61117). 
The ETC Model's objectives, as described in the final rule, include 
supporting paired donations and donor chains, and reducing the 
likelihood that potentially viable organs are discarded (85 FR 61128). 
The ETC Model was updated by the final rule dated November 8, 2021, 
titled ``Medicare Program; End-Stage Renal Disease Prospective Payment 
System, Payment for Renal Dialysis Services Furnished to Individuals 
With Acute Kidney Injury, End-Stage Renal Disease Quality Incentive 
Program, and End-Stage Renal Disease Treatment Choices Model'' and the 
final rule dated November 7, 2022, titled ``Medicare Program; End-Stage 
Renal Disease Prospective Payment System, Payment for Renal Dialysis 
Services Furnished to Individuals With Acute Kidney Injury, End-Stage 
Renal Disease Quality Incentive Program, and End-Stage Renal Disease 
Treatment Choices Model'' (87 FR 67136). We finalized further 
modifications to the ETC Model related to the availability of 
administrative review of an ETC Participant's targeted review request 
in the final rule issued on November 6, 2023, titled ``Medicare 
Program; End-Stage Renal Disease Prospective Payment System, Payment 
for Renal Dialysis Services Furnished to Individuals With Acute Kidney 
Injury, End-Stage Renal Disease Quality Incentive Program, and End-
Stage Renal Disease Treatment Choices Model'' (88 FR 76345).
    CMS is also operating the ETC Learning Collaborative, which is 
focused on increasing the availability of deceased donor organs for 
transplantation.\31\ The ETC Learning Collaborative regularly convenes 
ETC Participants, transplant hospitals, OPOs, and large donor 
hospitals, with the goal of using learning and quality improvement 
techniques to systematically spread the best practices of the highest 
performing organizations. CMS is employing quality improvement 
approaches to improve performance by collecting and analyzing data to 
identify the highest performers, and to help others to test, adapt and 
spread the best practices of these high performers throughout the 
entire national organ recovery system (85 FR 61346).
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    \31\ Centers for Medicare & Medicaid Services. https://innovation.cms.gov/innovation-models/esrd-treatment-choices-model.
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    The KCC Model, which began its performance period on January 1, 
2022, and is scheduled to end on December 31, 2026, is a voluntary 
model that also builds upon the CEC Model structure to encourage health 
care providers to better manage the care for Medicare beneficiaries 
with CKD stages 4 and 5 and ESRD, delay the onset of dialysis, and 
incentivize kidney transplantation. Various entities are participating 
in the KCC Model, including nephrologists and nephrology practices, 
dialysis facilities, and other health care providers. The participating 
entities receive a bonus payment for each aligned beneficiary who 
receives a

[[Page 43530]]

kidney transplant, so long as the transplant remains successful over a 
certain time period. CMS plans to continue to evaluate the 
effectiveness of the ETC and KCC Models in achieving clinical goals, 
improving quality of care, and reducing Medicare costs.\32\
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    \32\ The evaluation report for the first two years (2021, 2022) 
of the ETC Model is available at https://www.cms.gov/priorities/innovation/data-reports.
---------------------------------------------------------------------------

    The IOTA Model proposes to complement the ETC and KCC Models and 
expand kidney model participation to kidney transplant hospitals, which 
are a key player in the transplant ecosystem, to test whether two-sided 
risk payments based on performance increase access to kidney 
transplants for ESRD patients placed on the waitlists of participating 
transplant hospitals.
c. HRSA Initiatives Involving Kidney Transplants
    NOTA established the OPTN almost 40 years ago to coordinate and 
operate the nation's organ procurement, allocation, and transplantation 
system. There are about 400 member organizations that comprise the 
OPTN. Section 372(b)(2)(A) of the PHS Act charges the OPTN with 
establishing a national list of individuals who need organs and a 
national computer system to match organs with individuals on the 
waitlist. HRSA has also undertaken efforts in alignment with CMS 
efforts and Federal Government initiatives to improve accountability in 
OPTN functions. On March 22, 2023, HRSA launched the OPTN Modernization 
Initiative to strengthen accountability, equity, and performance in the 
organ donation and transplantation system through a focus on five key 
areas: technology, data transparency, governance, operations, and 
quality improvement and innovation.\33\ The OPTN Modernization 
Initiative was further supported by the Securing the U.S. Organ 
Procurement and Transplantation Network Act (Pub. L. 118-14), which 
included several key provisions proposed in the President's Fiscal Year 
2024 Budget and was signed into law on September 22, 2023.\34\ The new 
law expressly authorizes HHS to make multiple awards to different 
entities, which could enable the OPTN to benefit from best-in-class 
vendors and provide a more efficient system that strengthens oversight 
and improves patient safety.
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    \33\ HRSA Announces Organ Procurement and Transplantation 
Network Modernization Initiative [verbar] HRSA. (n.d.). 
Www.hrsa.gov. Retrieved August 20, 2023, from https://www.hrsa.gov/optn-modernization/march-2023.
    \34\ The White House. (2023, September 22). Bill Signed: H.R. 
2544. The White House. https://www.whitehouse.gov/briefing-room/
legislation/2023/09/22/bill-signed-h-r-2544/
#:~:text=On%20Friday%2C%20September%2022%2C%202023,Organ%20Procuremen
t%20and%20Transplantation%20Network.
---------------------------------------------------------------------------

    Effective July 14, 2022, revisions to the OPTN Bylaws were made 
related to the Transplant Program Performance to establish new criteria 
for identification of transplant programs that enter MPSC performance 
review based on the following criteria: \35\
---------------------------------------------------------------------------

    \35\ OPTN. (n.d.). Enhance Transplant Program Performance 
Monitoring System, Phase 1 (July 2022) Sponsoring Committee: 
Membership and Professional Standards Bylaws Affected. Retrieved 
August 20, 2023, from https://optn.transplant.hrsa.gov/media/hgkksfuu/phase-1_tx-prgm-performance-monitoring_dec-2021.pdf.
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     The transplant program's 90-day post-transplant graft 
survival hazard ratio is greater than 1.75 during the 2.5-year time 
period; or
     The transplant program's 1-year post-transplant graft 
survival conditional on 90-day post-transplant graft survival hazard 
ratio is greater than 1.75 during a 2.5-year period.
    Transplant programs that meet either of the criteria, as reported 
by the SRTR, must participate in the OPTN Membership and Professional 
Standards Committee (MPSC) performance review, which may require the 
member to take appropriate actions to determine if the transplant 
program has demonstrated sustainable improvement, including, but not 
limited to--
     Providing information about the program structure, 
procedures, protocols and quality;
     Review processes;
     Adopting and implementing a plan for improvement;
     Participating in an informal discussion with MPSC members; 
and
     Participating in a peer visit.
    The MPSC would continue to review the transplant program under the 
performance review until the MPSC determines that the transplant 
program has made sufficient and sustainable improvements to avoid risk 
to public health or patient safety. If the MPSC's review determines 
that a risk to patient health or public safety exists, the MPSC may 
request that a member inactivate or withdraw a designated transplant 
program, or a specific component of the program, to mitigate the risk. 
Transplant programs that do not participate in the MPSC performance 
review process or fail to act to improve their performance are subject 
to the policies described in Appendix L of the OPTN Bylaws, Reviews and 
Actions, including the declaration of ``Member Not in Good Standing.'' 
While being designated ``Member Not in Good Standing'' does not 
necessarily lead to the closure or removal of that program from 
receiving reimbursement from Federal health insurance programs, the 
Secretary can, based on a recommendation from the OPTN Board of 
Directors, revoke OPTN membership, close an OPTN member, or remove the 
ability of the member to receive Federal funding from Medicare or 
Medicaid. Additionally, numerous private payers align with the MPSC 
metrics and SRTR star rating system that evaluate transplant hospitals 
on post-transplant performance to create their Centers of Excellence 
programs. Therefore, MPSC reviews and performance on the MPSC 
monitoring measures are a powerful regulatory incentive for transplant 
programs.
    In the final rule, dated September 22, 2020, titled ``Removing 
Financial Disincentives to Living Organ Donation'' (85 FR 59438), HRSA 
expanded the scope of qualified reimbursable expenses incurred by 
living donors under the Living Organ Donation Reimbursement Program to 
include lost wages and dependent care (childcare and elder care) 
expenses to further the goal of reducing financial barriers to living 
organ donation. The program previously only allowed for reimbursement 
of travel, lodging, meals, and incidental expenses. In the final 
notice, dated September 22, 2020, titled, ``Reimbursement of Travel and 
Subsistence Expenses Toward Living Organ Donation Program Eligibility 
Guidelines,'' HRSA increased the income eligibility threshold under the 
Living Organ Donation Reimbursement Program from 300 percent to 350 
percent of the Federal Poverty Guidelines (85 FR 59531).
3. Rationale for the Proposed IOTA Model
a. Alignment With Federal Government Initiatives and Priorities
    For decades, patients and health care providers have confronted an 
imbalance in the number of transplant candidates and the supply of 
acceptable donor organs, including kidneys and other organs. Observed 
variation in access to organ transplantation by geography, race/
ethnicity, disability status, and socioeconomic status, as well as the 
overall performance of the organ transplantation ecosystem, raised the 
need to make performance improvements and address disparities.\36\ 
Strengthening and improving the

[[Page 43531]]

performance of the organ transplantation ecosystem is a priority for 
HHS. To that end, OTAG was established in 2021 by CMS and HRSA and has 
expanded interagency coordination and collaboration to ``drive 
improvements in donations, clinical outcomes, system improvement, 
quality measurement, transparency, and regulatory oversight.'' \37\ 
Collectively, CMS and HRSA seek to--
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    \36\ Moody-Williams, J.D., & Nair, S. (2023, December 13). Organ 
Transplantation Affinity Group (OTAG): Strengthening accountability, 
equity, and performance [verbar] CMS. BLOG. https://www.cms.gov/blog/organ-transplantation-affinity-group-otag-strengthening-accountability-equity-and-performance.
    \37\ Moody-Williams, J.D., & Nair, S. (2023, December 13). Organ 
Transplantation Affinity Group (OTAG): Strengthening accountability, 
equity, and performance [verbar] CMS. BLOG. https://www.cms.gov/blog/organ-transplantation-affinity-group-otag-strengthening-accountability-equity-and-performance.
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     Reduce variation of pre-transplant and referral practices; 
\38\
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    \38\ Pre-transplant/referral practices are inclusive of the 
referring physician's assessment criteria, patient education, and 
feedback to the referring physician from the transplant assessment.
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     Increase availability and use of donated organs;
     Increase accountability for organ procurement and 
matching;
     Promote equitable access to transplants; and
     Empower patients, families, and caregivers to actively 
engage in the transplant journey.
    We believe the proposed IOTA Model has the potential to 
substantially increase the number of kidney transplants in a way that 
enhances fairness for all affected individuals, regardless of 
socioeconomic status or other factors that limit access to care and 
negatively affect health outcomes, thereby improving quality of care, 
reducing costs to Medicare, and prolonging lives. The IOTA Model, as 
proposed, is complementary to the ETC and KCC Models, and to other CMS 
and HRSA initiatives, with the collective goal of achieving 
improvements in processes among transplant hospitals that would spur an 
increase in both deceased donor and living donor kidney transplantation 
and reduce population health disparities. Furthermore, although we are 
targeting our proposals to kidney transplant programs, we seek to test 
specific modifications for Medicare payment and other programmatic 
measures that would establish a framework for potential future 
interventions for transplantation relating to the other solid organ 
types.
    In the following sections of this proposed rule, we review 
scientific literature that outlines specific ways that kidney 
transplantation can be enhanced. Although not the focus of our 
analysis, we also present findings pertaining to the transplantation of 
other organs, especially livers. We aim to show how the types of 
interventions that we are proposing might also apply for any future 
efforts to increase transplant numbers for other organ types, and to 
continue to pursue the goal of greater equity. We also describe recent 
efforts from CMS and HRSA to enhance organ transplantation that 
complement our proposals to use payment incentives as a policy lever to 
increase the number of kidney transplants and achieve a fairer 
distribution.
b. End Stage Renal Disease Impact
    According to the United States Renal Data System (USRDS), in 2021 
about 808,536 people in the United States were living with ESRD, almost 
double the number in 2001.\39\ Prevalence of ESRD varied by Health 
Service Area (HSA) and ESRD Network.\40\ Stratified by age and race/
ethnicity, ESRD was consistently more prevalent among older people (65 
and older) and in Black people.\41\ Diabetes and hypertension are most 
often the primary cause of ESRD.\42\ According to the National Kidney 
Foundation, these diseases disproportionately affect minority 
populations, increasing the risk of kidney disease.\43\ Year-over-year, 
incidence of ESRD continues to increase, as the number of patients 
newly registered increased from 97,856 in 2001 to 134,837 in 2019 and 
135,972 in 2021.\44\ Studies show that people with kidney transplants 
live longer than those who remain on dialysis.\45\ Despite these 
positive outcomes, the percentage of prevalent ESRD patients with a 
functioning kidney transplant remained relatively stable over the past 
decade, increasing only slightly from 29.7 percent in 2011 to 30.51 
percent in 2021.\46\ In 2021, 72,864 patients with ESRD were on the 
kidney transplant waitlist, of which 27,413 were listed during that 
year.\47\ The IOTA Model proposes to focus on the ESRD patients who are 
on the kidney transplant waitlists of the kidney transplant hospitals 
that would be required to participate in this Model. ESRD patients 
represent a small portion of the U.S. population, but the disease 
burden to the patient and to CMS is great in terms of health outcomes, 
survival, quality of life, and cost. The ESRD population accounted for 
6.1% of total Medicare expenditures in 2020.\48\
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    \39\ United States Renal Data System. 2023.End Stage Renal 
Disease: Chapter 1. Figure 1.5.
    \40\ United States Renal Data System. 2023. End Stage Renal 
Disease: Chapter 1. Figure 1.7.
    \41\ United States Renal Data System. 2023. End Stage Renal 
Disease: Chapter 1. Figure 1.8.
    \42\ United States Renal Data System. 2023. End Stage Renal 
Disease. Chapter 1. Table 1.3.
    \43\ National Kidney Foundation. (2016, January 7). Race, 
Ethnicity and Kidney Disease. National Kidney Foundation. https://www.kidney.org/atoz/content/minorities-KD.
    \44\ United States Renal Data System. 2023. End Stage Renal 
Disease. Chapter 1. Figure 1.1.
    \45\ National Kidney Foundation. (2017, February 14). Kidney 
Transplant. National Kidney Foundation. https://www.kidney.org/atoz/content/kidney-transplant.
    \46\ United States Renal Data System. 2023. End Stage Renal 
Disease: Chapter 7. Figure 7.16.
    \47\ United States Renal Data System. 2023. End Stage Renal 
Disease: Chapter 7. Figures 7.1 and 7.2.
    \48\ United States Renal Data System. 2022. End Stage Renal 
Disease: Chapter 9.
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    Due to wide variability across eligible kidney transplant 
hospitals, we are unable to estimate the IOTA Model's attributed 
patient population until the IOTA participants are randomly selected.
c. Benefits of Kidney Transplantation
    ESRD, when a person's kidney function has declined to the point of 
requiring regular dialysis or a transplant for survival, as the 
person's kidneys are no longer able to perform life-sustaining 
functions, is the final stage of CKD. ESRD is a uniquely burdensome 
condition, with uncertain survival and poor quality of life for 
patients. The higher mortality and substantially greater expenditures 
and hospitalization rates for ESRD beneficiaries compared to the 
overall Medicare population suggest the need to explore policy 
interventions to enhance patients' survival and life experience, as 
well as to reduce the impact to Medicare. The IOTA Model proposes to 
improve patient outcomes by incentivizing increased access to kidney 
transplantation across IOTA participants. Access to this lifesaving 
treatment may delay or avert dialysis, reduce costs to the Medicare 
program and to patients, and enhance survival and quality of life.
    A kidney transplant involves surgically transplanting a kidney from 
a living or deceased donor to a kidney transplant recipient. The 
replacement organ is known as a graft. Most kidneys are transplanted 
alone, as kidneys transplanted along with other organs are very 
rare.\49\ Fewer than 1,000 patients each year receive a simultaneous 
kidney-pancreas transplant, which is generally conducted for patients 
who have kidney failure related to type 1 diabetes mellitus.\50\ The 
kidney in such

[[Page 43532]]

a simultaneous transplant may come from a living or deceased donor, but 
other organs mostly come from a deceased donor.
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    \49\ According to OPTN data, in 2022, there were 389 kidney-
heart transplants in the U.S, 789 kidney-liver transplants, 22 
kidney-lung transplants, and 3 kidney-intestine transplants. See 
https://optn.transplant.hrsa.gov/data/view-data-reports/national-data/.
    \50\ Health Resources and Services Administration. (2020). 
Scientific Registry for Transplant Recipients. OPTN/SRTR 2020 Annual 
Data Report: Pancreas. https://srtr.transplant.hrsa.gov/annual_reports/2020/Pancreas.aspx.
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    About three-quarters of kidney transplants in the U.S. are deceased 
donor kidney transplants.\51\ For deceased donor transplantation, a 
patient needs to contact a transplant hospital and arrange for an 
evaluation to assess the feasibility of surgery. The patient's name 
would then be added to a list of individuals who can receive organ 
offers. This is known as the kidney transplant hospital's kidney 
transplant waitlist. Living donation occurs when a living person 
donates an organ to a family member, friend, or other individual. 
People unknown to one another sometimes take part in paired exchanges, 
which allow the switching of recipients based on blood type and other 
biological factors. The numbers of deceased donor kidney donation have 
increased over the past decade, while living donor kidney donation has 
remained relatively constant, declining in 2020 with the COVID-19 
pandemic.\52\
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    \51\ United States Renal Data System. 2022. USRDS Annual Data 
Report. Volume 2. End-stage Renal Disease (ESRD) in the United 
States, Chapter 7: Transplantation. Figure 7.10b.
    \52\ United States Renal Data System. 2022. USRDS Annual Data 
Report. Volume 2. End-stage Renal Disease (ESRD) in the United 
States, Chapter 7: Transplantation. Figure 7.10b.
---------------------------------------------------------------------------

    Kidney transplantation is considered the optimal treatment option 
for most ESRD patients. Although not a cure for kidney disease, a 
transplant can help a person live longer and improve quality of life. 
On average, patients experience 14 to 16 years of function from a 
kidney from a living kidney donor, while few people survive more than a 
decade on dialysis.\53\ According to one source, the majority of 
deceased donor kidneys are expected to function for about 9 years, with 
high quality organs lasting longer.\54\ A systematic review of studies 
worldwide finds significantly lower mortality and risk of 
cardiovascular events associated with kidney transplantation compared 
with dialysis.\55\ Additionally, this review finds that patients who 
receive transplants experience a better quality of life than treatment 
with dialysis.\56\ The average dialysis patient is admitted to the 
hospital nearly twice a year, often as a result of infection, and more 
than 35 percent of dialysis patients who are discharged are re-
hospitalized within 30 days of being discharged.\57\ Among transplant 
recipients, there are lower rates of hospitalizations, emergency 
department visits, and readmissions compared to those still on 
dialysis.\58\ In general, from the standpoint of long-term survival and 
quality of life, a living donor kidney transplant is considered the 
best among all kidney transplant options for most people with 
CKD.59 60
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    \53\ Get the Facts on Kidney Transplantation Before You Start 
Dialysis--Penn Medicine. (2019, July 24). Www.pennmedicine.org. 
https://www.pennmedicine.org/updates/blogs/transplant-update/2019/july/kidney-transplant-facts-before-dialysis.
    \54\ Organ Procurement and Transplantation Network. Kidney Donor 
Profile Index (KDPI) Guide for Clinicians. https://
optn.transplant.hrsa.gov/professionals/by-topic/guidance/kidney-
donor-profile-index-kdpi-guide-for-clinicians/
#:~:text=Figure%201%20shows%20that%20a,function%20for%20about%209%20y
ears.
    \55\ Tonelli, M., Wiebe, N., Knoll, G., Bello, A., Browne, S., 
Jadhav, D., Klarenbach, S., & Gill, J. (2011). Systematic Review: 
Kidney Transplantation Compared With Dialysis in Clinically Relevant 
Outcomes. American Journal of Transplantation, 11(10), 2093-2109. 
https://doi.org/10.1111/j.1600-6143.2011.03686.x.
    \56\ Ibid.
    \57\ United States Renal Data System. 2022. USRDS Annual Data 
Report. 2022. Volume 2. End-stage Renal Disease (ESRD) in the United 
States, Chapter 5: Hospitalization. Figures 5.1a, 5.9.
    \58\ United States Renal Data System. 2021. USRDS Annual Data 
Report. Volume 2. End-Stage Renal Disease (ESRD) in the United 
States. Chapter 5: Hospitalization, Figures 5.1a, 5.6a, 5.8.
    \59\ Nemati, E., Einollahi, B., Lesan Pezeshki, M., Porfarziani, 
V., & Fattahi, M.R. (2014). Does Kidney Transplantation With 
Deceased or Living Donor Affect Graft Survival? Nephro-Urology 
Monthly, 6(4). https://doi.org/10.5812/numonthly.12182.
    \60\ United States Renal Data System. 2022. USRDS Annual Data 
Report. Volume 2. End-stage Renal Disease (ESRD) in the United 
States, Chapter 7: Hospitalization. Figure 7.20.b.
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    A cost advantage also arises with kidney transplantation. Per 
person per year Medicare FFS spending for beneficiaries with ESRD with 
a transplant is less than half that for either hemodialysis or 
peritoneal dialysis.\61\ While the benefits to patient survival and 
quality of life from living donor kidney transplantation are more 
pronounced, a recent literature review shows that deceased donor kidney 
transplantation generally produced better outcomes at a lower cost 
compared to dialysis, although old age and a high comorbidity load 
among kidney transplant patients may mitigate this advantage.\62\ An 
earlier study, based on a single hospital, showed rates of 
hospitalization, a substantial factor in health care costs, to be lower 
among kidney transplant patients than for those on dialysis.\63\
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    \61\ United States Renal Data System. 2022. USRDS Annual Report. 
Volume 2. End-stage Renal Disease (ESRD) in the United States, 
Chapter 9: Healthcare Expenditures for Persons with ESRD. Figure 
9.11.
    \62\ Fu, R., Sekercioglu, N., Berta, W., & Coyte, P.C. (2020). 
Cost-effectiveness of Deceased-donor Renal Transplant Versus 
Dialysis to Treat End-stage Renal Disease. Transplantation Direct, 
6(2), e522. https://doi.org/10.1097/txd.0000000000000974.
    \63\ Khan, S., Tighiouart, H., Kalra, A., Raman, G., Rohrer, 
R.J., & Pereira, B.J.G. (2003). Resource utilization among kidney 
transplant recipients. Kidney International, 64(2), 657-664. https://doi.org/10.1046/j.1523-1755.2003.00102.x.
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    Despite these outcomes, in 2020, only about 30 percent of prevalent 
ESRD patients--those with existing ESRD diagnoses--in the U.S. had a 
functioning kidney transplant, or graft.\64\ In 2016, only 2.8 percent 
of incident ESRD patients--meaning patients newly diagnosed with ESRD--
received a preemptive kidney transplant, allowing them to avoid 
dialysis.\65\ These rates are substantially below those of other 
developed nations. The U.S. was ranked 17th out of 42 reporting 
countries in kidney transplants per 1,000 dialysis patients in 2020, 
with 42 transplants per 1,000 dialysis patients in 2020.\66\ We seek to 
test policy approaches aimed at increasing the number of kidney 
transplants over current levels given these relatively low numbers and 
the overall benefit to patients from transplantation, as well as the 
potential savings to Medicare.
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    \64\ United States Renal Data System. 2022 Annual Data Report. 
Volume 2. End Stage Renal Disease Chapter 7 Transplantation Figure 
7.16.
    \65\ United States Renal Data System. 2018. Annual Data Report. 
Volume 2. Chapter 1: Incidence, Prevalence, Patient Characteristics, 
and Treatment Modalities. Figure 1.2. Retrieved from https://www.usrds.org/2018/view/v2_01.aspx.
    \66\ United States Renal Data System. 2022. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 11.17b.
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d. Kidney Transplant Rates and Unmet Needs
    Annually, more than one hundred thousand individuals in the U.S. 
begin treatment for ESRD.\67\ Despite transplantation being widely 
regarded as the optimal treatment for people with ESRD, as well as 
being more cost-effective in the long term compared to dialysis, only a 
minority of people with ESRD (13 percent) are added to the waitlist, 
and even fewer receive a transplant. To be added to the kidney 
transplant waitlist, a patient must complete an evaluation at a 
transplant hospital, and the patient must be found to be a good 
candidate for a transplant. Nearly 5,000 patients on the national 
kidney transplant waiting list die each year.68 69 70 These 
trends have persisted

[[Page 43533]]

for several decades despite increases in the number of kidney 
transplants from deceased donors and living donors.
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    \67\ United States Renal Data System. 2022. USRDS annual data 
report: Epidemiology of kidney disease in the United States. 
National Institutes of Health, National Institute of Diabetes and 
Digestive and Kidney Diseases, Bethesda, MD; 2022.Volume 2: End-
stage Renal Disease (ESRD) in the United States, Chapter 1: 
Incidence, Prevalence, Patient Characteristics.
    \68\ Scientific Registry of Transplant Recipients. Program 
Specific Reports. Www.srtr.org. Retrieved June 15, 2023, from 
https://www.srtr.org/reports/program-specific-reports/.
    \69\ Too Many Donor Kidneys Are Discarded in U.S. Before 
Transplantation--Penn Medicine. (2020, December 16). 
www.pennmedicine.org. https://www.pennmedicine.org/news/news-releases/2020/december/too-many-donor-kidneys-are-discarded-in-us-before-transplantation.
    \70\ United States Renal Data System. 2022 Annual Data Report. 
Volume 2. End Stage Renal Disease Chapter 7 Transplantation Figure 
7.4.
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    From 1996 to 2019, the number of kidneys made available for 
transplantation from deceased donors grew steadily, in part because of 
organs that became available as a result of the opioid 
epidemic.71 72 In 2018 and 2019, the total number of kidney 
transplants rose steadily as compared to previous years.\73\ In 2019, 
almost one third of patients received a transplant within one year of 
being placed on the waitlist (32.9 percent), and the rate reached 51.8 
percent within 5 years of being placed on the waitlist.\74\ The number 
of kidney transplants increased by 10.2 percent from 2018 to 2019, but 
fell by 2.7 percent from 2019 to 2020, from 24,511 to 23,853. The 
reduction was precipitated by a 23.6 percent decline in living donor 
transplants on account of the COVID-19 pandemic.\75\ The overall number 
of patients with a functioning graft continued its upward trend, 
reaching 245,846 in 2020, an increase of 2.7 percent from 2019.\76\ 
Nonetheless, these gains in kidney transplantation in the U.S. have 
fallen far short of the prevailing need among individuals with ESRD or 
facing the prospect of kidney failure. The number of individuals with 
ESRD added to the waitlist for a kidney transplant reached a high of 
28,533 in 2019, but dropped slightly to 25,136 in 2020, while rising to 
27,413 in 2021.\77\ At the end of 2021, 72,864 individuals were on the 
waitlist for a kidney transplant.\78\
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    \71\ Hariharan, S., Israni, A. K., & Danovitch, G. (2021). Long-
Term Survival after Kidney Transplantation. New England Journal of 
Medicine, 385(8), 729-743. https://doi.org/10.1056/nejmra2014530.
    \72\ Durand, C.M., Bowring, M.G., Thomas, A.G., Kucirka, L.M., 
Massie, A.B., Cameron, A., Desai, N.M., Sulkowski, M., & Segev, D.L. 
(2018). The Drug Overdose Epidemic and Deceased-Donor 
Transplantation in the United States: A National Registry Study. 
Annals of Internal Medicine, 168(10), 702-711. https://doi.org/10.7326/M17-2451.
    \73\ United States Renal Data System. 2021. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.11.
    \74\ United States Renal Data System. 2021. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.7.
    \75\ United States Renal Data System. 2022. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.10b.
    \76\ United States Renal Data System. 2022. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.16.
    \77\ United States Renal Data System. 2023. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.1.
    \78\ United States Renal Data System. 2023. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.2.
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    The increase in deceased donor kidney transplantation was 
accompanied by a gradual but steady decline in the number of living 
donor transplants as compared to patients undergoing dialysis. The 
total number of living donor transplants per year has risen moderately 
over the past two decades, from 5,048 in 2000 to 5,241 in 2020, and 
5,971 in 2021.79 80 With the overall dialysis population 
growing, the rate of living donor transplants per 100 patient-years on 
dialysis declined from 1.4 to 0.8 transplants from 2010 to 2020.\81\ A 
report states the proportion of patients undergoing living donor kidney 
donation to have decreased from 37 percent in 2010 to 29 percent in 
2019.\82\ A study in 2013 of OPTN data found that the decline in living 
donation appeared most prominent among men, Black/African Americans, 
and younger and lower income adults, potentially leading to longer 
waiting times for transplantation, greater dialysis exposure, higher 
death rates on the waitlist, lower graft and patient survival for 
recipients, and higher overall healthcare costs for the care of 
patients with ESRD.\83\
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    \79\ United States Renal Data System. 2012. Annual Data Report. 
Atlas ESRD. Table 7.1.
    \80\ United States Renal Data System. 2023. Annual Data report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.10a.
    \81\ United States Renal Data System. 2022. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.10a.
    \82\ Charnow, J.A. (2021, June 8). Living Donor Kidney 
Transplants Declined in the Last Decade. Renal and Urology News. 
https://www.renalandurologynews.com/home/conference-highlights/american-transplant-congress/living-donor-kidney-transplantation-decreased-after-2010-united-states-trends/.
    \83\ Rodrigue, J.R., Schold, J.D., & Mandelbrot, D.A. (2013). 
The Decline in Living Kidney Donation in the United States. 
Transplantation Journal, 96(9), 767-773. https://doi.org/10.1097/tp.0b013e318298fa61.
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e. Disparities
    Kidney transplantation research in the U.S. reveals disparities 
across a number of different axes including geography, race and 
ethnicity, disability, socioeconomic status, neighborhood factors, and 
availability of health insurance.84 85 86 87 88 Studies 
during the past decade have shown substantial disparities in kidney 
transplant rates among transplant programs at a national level, as well 
as both among and within donation service areas (DSAs).\89\ A 2020 
study examined data from a registry that included all U.S. adult kidney 
transplant candidates added to the waitlist in 2011 and 2015, 
comprising 32,745 and 34,728 individuals, respectively.\90\ Among 
transplant programs nationwide, in 2015, the study found that the 
probability of a deceased donor transplant within three years for the 
average patient to be up to 16 times greater in some transplant 
hospitals as compared to others.\91\ Substantial differences in 
probability of deceased donor transplantation were found even within 
DSAs, where all transplant programs utilize the same OPO and local 
organ supply. For the 2015 cohort, there was a median 2.3-fold 
difference between the highest and lowest hospital in each DSA in the 
43 of 58 DSAs with more than one transplant hospital. The largest 
absolute difference in probability of transplant occurred in a DSA with 
seven transplant programs, with a patient on the waitlist at the 
transplant program with the highest probability of

[[Page 43534]]

transplant being 9.8 times more likely to receive a transplant than a 
patient at the transplant program with the lowest probability of 
receiving a transplant.\92\ Factors such as local organ supply, the 
characteristics of individuals on the waitlist of a given transplant 
program, the size of the waitlist, and the transplant program's volume 
of transplants may account for the differences observed nationally 
across DSAs. However, the variation among transplant programs across 
DSAs is significantly associated with organ offer acceptance patterns 
at individual transplant hospitals.\93\ This underscores the need to 
address geographic disparities and for more transparency on how 
transplant programs make decisions on organ offers for their waitlist 
patients.
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    \84\ King, K.L., Husain, S.A., Schold, J.D., Patzer, R.E., 
Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., Pastan, S.O., & 
Mohan, S. (2020). Major Variation across Local Transplant Centers in 
Probability of Kidney Transplant for Wait-Listed Patients. Journal 
of the American Society of Nephrology, 31(12), 2900-2911. https://doi.org/10.1681/ASN.2020030335.
    \85\ Melanson T., Basu M., Plantiga L., Pastan S., Mohan S., 
Patzer R. (2017). Variation in Living Donor Kidney Transplantation 
among U.S. Transplant Centers. American Journal of Transplantation, 
17 (suppl 3).
    \86\ United States Renal Data System. 2022. Annual Data Report. 
Supplements: COVID-19, Racial and Ethnic Disparities Figures 14-4 
and 14.15.
    \87\ Wesselman, H., Ford, C.G., Leyva, Y., Li, X., Chang, C.-
C.H., Dew, M.A., Kendall, K., Croswell, E., Pleis, J.R., Ng, Y.H., 
Unruh, M.L., Shapiro, R., & Myaskovsky, L. (2021). Social 
Determinants of Health and Race Disparities in Kidney Transplant. 
Clinical Journal of the American Society of Nephrology, 16(2), 262-
274. https://doi.org/10.2215/cjn.04860420.
    \88\ Ng, Y.-H., Pankratz, V.S., Leyva, Y., Ford, C.G., Pleis, 
J.R., Kendall, K., Croswell, E., Dew, M.A., Shapiro, R., Switzer, 
G.E., Unruh, M.L., & Myaskovsky, L. (2019). Does Racial Disparity in 
Kidney Transplant Wait-listing Persist After Accounting for Social 
Determinants of Health? Transplantation, 1. https://doi.org/10.1097/tp.0000000000003002.
    \89\ With the enactment of NOTA, CMS designated donation service 
areas (DSAs); generally, each DSA includes an OPO within its 
geographic area. Until March 2021, when OPTN implemented the current 
policy for allocation of deceased donor kidneys, the priority for 
organs acquired by an OPO was based, among other factors, on an 
individual's residence within the DSA extending around the OPO.
    \90\ King, K.L., Husain, S.A., Schold, J.D., Patzer, R.E., 
Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., Pastan, S.O., & 
Mohan, S. (2020). Major Variation across Local Transplant Centers in 
Probability of Kidney Transplant for Wait-Listed Patients. Journal 
of the American Society of Nephrology, 31(12), 2900-2911. https://doi.org/10.1681/ASN.2020030335.
    \91\ King et al. 2020. 2903.
    \92\ King et al., 2020. 2903.
    \93\ King et al. 2020. 2903-2904.
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    Living donor kidney donation also varies widely among transplant 
hospitals. A 2018 report using OPTN data from 2015 showed that while 
most transplant hospitals perform few living donor kidney transplants, 
certain transplant hospitals have substantially higher rates for their 
waitlist patients than the median rate. Differences among transplant 
hospitals were correlated with geographic region and the number of 
deceased donor kidney transplantations performed.\94\ This underscores 
the need for initiatives and processes among transplant hospitals to 
encourage living donations to reduce geographic disparities.
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    \94\ Melanson T., Basu M., Plantiga L., Pastan S., Mohan S., 
Patzer R. (2017). Variation in Living Donor Kidney Transplantation 
among U.S. Transplant Centers. American Journal of Transplantation, 
17 (suppl 3).
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    Disparities in kidney transplantation rates for various populations 
in the U.S. have long been documented. Literature over the past two 
decades has focused on Non-Hispanic Black patients, who experience 
lower rates of deceased and living donor kidney transplantation as 
compared to Non-Hispanic White patients, while being four times more 
likely to have kidney failure. Black/African Americans and Hispanics/
Latinos with kidney failure experience lower rates of kidney 
transplantation compared with White patients.\95\ Additionally, Black/
African Americans and Hispanics/Latinos, along with Asians, American 
Indian/Alaskan Natives, and other minorities, are at a higher risk of 
illnesses that may eventually lead to kidney failure, such as diabetes 
and high blood pressure.\96\
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    \95\ United States Renal Data System. 2022. Annual Data Report. 
Supplements: COVID-19, Racial and Ethnic Disparities Figures 14-4 
and 14.15.
    \96\ National Kidney Foundation. (2016, January 7). Race, 
Ethnicity, & Kidney Disease. National Kidney Foundation. https://
www.kidney.org/atoz/content/minorities-
KD#:~:text=Black%20or%20African%20Americans%20are.
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    The literature over several decades has also addressed the effect 
of differences in age, gender, socioeconomic status (SES), and cultural 
aspects.\97\ Recent studies have emphasized poverty and income 
differentials in analyzing the interplay of these and other factors 
among populations referred for kidney transplantation at several large 
transplant hospitals.98 99 100 101 This research extends in 
time prior to the Kidney Allocation System (KAS) of 2014, which aimed 
to lessen the impact of racial differences on access to kidney 
transplantation.
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    \97\ Patzer, R.E., & Pastan, S.O. (2020). Policies to promote 
timely referral for kidney transplantation. Seminars in Dialysis, 
33(1), 58-67. https://doi.org/10.1111/sdi.12860.
    \98\ Patzer, R. Perryman, J. Schrager, J. Pastan, S. Amaral, S. 
Gazmararian, J. Klein, M. Kutner, N. McClellan, W. 2012. Patzer, 
R.E., Perryman, J.P., Schrager, J.D., Pastan, S., Amaral, S., 
Gazmararian, J.A., Klein, M., Kutner, N., & McClellan, W.M. (2012). 
The Role of Race and Poverty on Steps to Kidney Transplantation in 
the Southeastern United States. American Journal of Transplantation, 
12(2), 358-368. https://doi.org/10.1111/j.1600-6143.2011.03927.x.
    \99\ Wesselman, H., Ford, C.G., Leyva, Y., Li, X., Chang, C.-
C.H., Dew, M.A., Kendall, K., Croswell, E., Pleis, J.R., Ng, Y.H., 
Unruh, M.L., Shapiro, R., & Myaskovsky, L. (2021). Social 
Determinants of Health and Race Disparities in Kidney Transplant. 
Clinical Journal of the American Society of Nephrology, 16(2), 262-
274. https://doi.org/10.2215/cjn.04860420.
    \100\ Ng, Y.-H., Pankratz, V.S., Leyva, Y., Ford, C.G., Pleis, 
J.R., Kendall, K., Croswell, E., Dew, M.A., Shapiro, R., Switzer, 
G.E., Unruh, M.L., & Myaskovsky, L. (2019). Does Racial Disparity in 
Kidney Transplant Wait-listing Persist After Accounting for Social 
Determinants of Health? Transplantation, 1. https://doi.org/10.1097/tp.0000000000003002.
    \101\ Schold, J.D., Gregg, J.A., Harman, J.S., Hall, A.G., 
Patton, P.R., & Meier-Kriesche, H.-U. (2011). Barriers to Evaluation 
and Wait Listing for Kidney Transplantation. Clinical Journal of the 
American Society of Nephrology, 6(7), 1760-1767. https://doi.org/10.2215/cjn.08620910.
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    Research findings support the proposition that a broad 
interpretation of social determinants of health (SDOH) may 
substantially explain racial disparities in both deceased and living 
donor kidney transplantation.\102\ Recently, a comprehensive survey of 
the literature on disparities in transplantation for kidneys and other 
organs found that socioeconomic factors may substantially explain 
disproportionately lower transplant rates and longer wait times.\103\ 
As described in recent literature, a person's SDOH may contribute to 
inequities in their prospects for waitlist registration and receipt of 
transplantation.104 105 106 SDOH is defined more broadly 
than socioeconomic status, to include those conditions in the places 
where people live, learn, work, and play that affect a wide range of 
health and quality of life risks and outcomes.\107\ More specifically, 
SDOH include variations in employment, neighborhood factors, education, 
social support systems, and healthcare coverage that impact health 
outcomes.
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    \102\ Reed, R.D., & Locke, J.E. (2020). Social Determinants of 
Health: Going Beyond the Basics to Explore Racial Disparities in 
Kidney Transplantation. Transplantation, 104, 1324-1325. https://doi.org/10.1097/tp.0000000000003003.
    \103\ National Academies of Science, Engineering, and Medicine. 
2022. ``Realizing the Promise of Equity in the Organ Transplantation 
System. National Academies Press. Washington DC. 88-93.
    \104\ Centers for Disease Control and Prevention. Social 
Determinants of Health at CDC. Retrieved June 13, 2023, from https://www.cdc.gov/about/sdoh/index.html.
    \105\ Wesselman et al., 2021.
    \106\ Ng et al., 2020.
    \107\ Centers for Disease Control and Prevention.
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    Salient among recent analyses are those of a cohort of patients 
initially referred for evaluation for a kidney transplant at a large 
urban transplant hospital between 2010 and 2012. These studies showed 
lower waitlist registration and transplant rates for Black/African 
Americans, regardless of SDOH. However, after the introduction of the 
KAS in 2014, racial difference showed weaker associations with rates of 
waitlist registration and receipt of a deceased donor transplant, when 
controlling for SDOH.108 109 This finding is consistent with 
reports showing a decrease nationally in differences in rates of 
deceased donor kidney transplants among White patients as compared to 
Black/African American patients and Hispanic/Latino patients on 
dialysis, following the introduction of the KAS.110 111 The 
studies of this patient cohort showed Black/African American race to be 
associated with a decrease in probability of kidney transplant, while 
still according influence to clinical, social, demographic and cultural 
factors. These factors included older age, lower income, public 
insurance, having more comorbidities, being transplanted pre-KAS, less 
social support, and less transplant knowledge.\112\ Similarly, an 
earlier study of a population at a single

[[Page 43535]]

transplant hospital found that socioeconomic factors attenuated the 
association between racial difference and placement on the waitlist for 
a kidney transplant.\113\ This underscores the need to consider 
initiatives and improvement activities aimed at addressing SDOH for 
ESRD patients to remove barriers to access to kidney transplantations.
---------------------------------------------------------------------------

    \108\ Ng Y et al. 2020. 8.
    \109\ Wesselman et al., 2021. 271.
    \110\ United States Renal Data System. 2022. Annual Data Report. 
End Stage Renal Disease Chapter 7 Transplantation. Figures 7.10a, 
7.10b.
    \111\ OPTN Two Year Analysis shows effects of Kidney Allocation 
System https://optn.transplant.hrsa.gov/news/two-year-analysis-shows-effects-of-kidney-allocation-system/.
    \112\ Wesselman et al. 2021. 267.
    \113\ Schold et al., 2021.
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    Living donor transplantation has demonstrated the enduring 
influence of racial disparities, but also the importance of SES and 
neighborhood factors. The cohort of patients identified previously, 
initially referred for evaluation at a large urban hospital between 
2010 and 2012, showed that for living donor transplantation, Black/
African American race and lower income held a stronger association with 
a lower probability of living donor transplant than for deceased donor 
donation.\114\ These results accord with findings nationwide that White 
patients are more likely to receive a living donor transplant, followed 
by Asian and Hispanic/Latino patients. Black/African American patients 
have had lower rates of living donor transplants than other racial or 
ethnic groups.\115\ Explanations for these differences have included 
disparate rates of diabetes, obesity, and hypertension observed among 
minority populations that may contraindicate living donation by a 
relative; cultural differences in willingness to donate or ask for a 
living donation; concerns about costs among potential donors; and lack 
of knowledge about living donor transplantation on the part of 
patients, their families, and health care providers.116 117
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    \114\ Wesselman et al., 2021. 270.
    \115\ United States Renal Data System. 2022. Annual Data Report. 
End Stage Renal Disease Chapter 7 Transplantation Figure 7.10a.
    \116\ Purnell, T.S., Hall, Y.N., & Boulware, L.E. (2012). 
Understanding and Overcoming Barriers to Living Kidney Donation 
Among Racial and Ethnic Minorities in the United States. Advances in 
Chronic Kidney Disease, 19(4), 244-251. https://doi.org/10.1053/j.ackd.2012.01.008.
    \117\ Rodrigue, J.R., Kazley, A.S., Mandelbrot, D.A., Hays, R., 
LaPointe Rudow, D., & Baliga, P. (2015). Living Donor Kidney 
Transplantation: Overcoming Disparities in Live Kidney Donation in 
the US--Recommendations from a Consensus Conference. Clinical 
Journal of the American Society of Nephrology, 10(9), 1687-1695. 
https://doi.org/10.2215/cjn.00700115.
---------------------------------------------------------------------------

    Research over several decades confirms the relation between health 
care access and SES factors and disparities in living donor kidney 
transplantation receipt for Black/African American and Hispanic/Latino 
patients, and, additionally, that these disparities have increased over 
time.118 119 120 121 According to one study, between 1995 
and 2014, disparities in the receipt of living donor kidney 
transplantation grew more for Black/African Americans and Hispanics/
Latinos: (1) living in poorer (versus wealthier) neighborhoods; (2) 
without (versus with) a college degree; and (3) with Medicare (versus 
private insurance).\122\ The study suggests that delays in the receipt 
of kidney care may contribute to reported racial and ethnic differences 
in the quality and timing of discussions among patients, families, and 
clinicians about living donor kidney transplantation as a treatment 
option.\123\
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    \118\ Purnell, T.S., Luo, X., Cooper, L.A., Massie, A.B., 
Kucirka, L.M., Henderson, M.L., Gordon, E.J., Crews, D.C., Boulware, 
L.E., & Segev, D.L. (2018). Association of Race and Ethnicity With 
Live Donor Kidney Transplantation in the United States From 1995 to 
2014. JAMA, 319(1), 49. https://doi.org/10.1001/jama.2017.19152.
    \119\ Hall, E.C., James, N.T., Garonzik Wang, J.M., Berger, 
J.C., Montgomery, R.A., Dagher, N.N., Desai, N.M., & Segev, D.L. 
(2012). Center-Level Factors and Racial Disparities in Living Donor 
Kidney Transplantation. American Journal of Kidney Diseases, 59(6), 
849-857. https://doi.org/10.1053/j.ajkd.2011.12.021.
    \120\ Gore, J.L., Danovitch, G.M., Litwin, M.S., Pham, P-T.T., & 
Singer, J.S. (2009). Disparities in the Utilization of Live Donor 
Renal Transplantation. American Journal of Transplantation, 9(5), 
1124-1133. https://doi.org/10.1111/j.1600-6143.2009.02620.x.
    \121\ Rodrigue et al. 2015.
    \122\ Purnell et al. 2015. 58.
    \123\ Purnell et al. 2015. 59.
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    One study also established associations between rates of living 
donor kidney transplantation for Black/African Americans and transplant 
hospital characteristics. While recognizing the potential effect of 
clinical factors, the study found that hospitals with high overall 
rates of living donor kidney transplantation showed significantly 
decreased racial disparities. The authors suggest that such high rates 
reveal commitment to living donor kidney transplantation, possibly 
shown in better education programs, more formalized procedures to 
reduce failure to complete transplant evaluations, increased use of 
medically complex and unrelated donors, and more success in reducing 
financial barriers to living donor kidney donation.\124\ The study also 
notes that hospitals with higher percentages of Black/African American 
candidates experience greater racial disparities. The authors surmise 
that such a high percentage might indicate an urban setting exhibiting 
greater differences in access to health care between Black/African 
Americans and other populations.\125\
---------------------------------------------------------------------------

    \124\ Hall et al. 2012. 855.
    \125\ Hall et al. 2012. 855.
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    Studies have also shown discrimination on the basis of disability 
with regard to organ transplantation, particularly for individuals with 
intellectual and developmental disabilities, who are often assumed by 
transplant providers to be unable to manage post-transplantation care 
requirements.\126\ Discrimination occurs even though individuals' 
disabilities that are not related to the need for an organ transplant 
generally have little or no impact on the likelihood that the 
transplant would be successful.\127\ The American Society of Transplant 
Surgeons has recommended that no patient be discriminated against or 
precluded from transplant listing solely due to the presence of a 
disability, whether physical or psychological.\128\
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    \126\ See, for example., Nat'l Council on Disability, Organ 
Transplants Discrimination against People with Disabilities: Part of 
the Bioethics and Disability Series (2019), https://ncd.gov/sites/default/files/NCD_Organ_Transplant_508.pdf.
    \127\ Id. at 38-40.
    \128\ Am. Soc'y of Transplant Surgeons, Statement Concerning 
Eligibility for Solid Organ Transplant Candidacy (Feb. 12, 2021), 
https://asts.org/advocacy/position-statements.
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    CMS has kept these concerns in mind when developing the IOTA Model 
proposals. The IOTA Model proposes performance-based payments that hold 
transplant hospitals selected as the IOTA participants financially 
accountable for improvements in access to both deceased and living 
donor kidney transplantations. To reduce disparities and promote health 
equity, CMS is proposing that the IOTA participants would be required 
to develop and submit a Health Equity Plan to CMS in PYs 2 through 6. 
This proposed model design feature is aimed at encouraging IOTA 
participants to reassess their processes and policies around living and 
deceased donor kidneys and promote investments in performance and 
quality improvement activities that address barriers to care, including 
SDOH. The sequence of steps that patients need to undertake to gain 
access to kidney transplantation is complex, and the challenge posed by 
this process for potential recipients may be compounded by racial, 
socioeconomic and neighborhood factors. Thus, we believe that a unified 
framework of interventions to address the distinct social contexts 
underlying differences among racial groups in deceased donor kidney 
transplantation and living donor kidney transplantation may result in 
the desired outcomes of greater overall kidney transplant numbers and 
equity.

[[Page 43536]]

f. Post-Transplant Outcomes
    While the need for kidney transplants has grown, the rates of 
patient and graft survival have increased. Between 2001 and 2020, graft 
survival rates at 1 and 5 years showed an increasing trend.\129\ 
Patient survival at 1 year increased from 97.5 percent in 2001 to 99.2 
percent in 2018, but then declined to 98.9 percent in 2019 and 98.4 
percent in 2020; patient survival at 5 years rose from 89.8 percent in 
2001 to an all-time high of 93.6 percent in 2013, dropping slightly to 
93.2 percent in 2016.\130\ For living donor kidney transplants, the 
rate of graft failure at 3 years decreased from 3.0 per 100 person 
years in 2010 to 2.1 per 100 person years in 2018. The rate of death at 
3 years with a functioning graft also decreased from 1.2 to 1.0 per 100 
person-years.\131\ For deceased donor kidney transplants, the rate of 
graft failure at 3 years decreased from 2010 (6.3 per 100 patient 
years) to 2014 (4.9 per 100 patient years), but increased to 5.3 per 
100 patient years in 2018. The same pattern was observed for death with 
a functioning graft, except that the rate in the 2018 cohort (2.8 per 
100 patient years) exceeded that of the 2010 cohort (2.6 per 100 
patient years).\132\
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    \129\ United States Renal Data System. 2023. Annual Data Report. 
Volume 2. End Stage Renal Disease. Transplantation. Figures 7.19a 
and 7.19b.
    \130\ United States Renal Data System. 2023. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figures 7.20a and 720.b.
    \131\ United States Renal Data System. 2023. Annual Data Report. 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 7.21a.
    \132\ United States Renal Data System. 2023. Annual Data Report 
Volume 2. End Stage Renal Disease. Chapter 7. Transplantation. 
Figure 721.b.
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    A study published in the New England Journal of Medicine in 2021 
shows the advantage of transplantation using deceased donor organs over 
long-term dialysis, even with an increasing trend of adverse conditions 
among recipients and donors. Notably, patient survival improved between 
the 1990s and the period from 2008 to 2011, despite increases in both 
(a) recipients' age, body-mass index (BMI), frequency of diabetes, and 
length of time undergoing dialysis, as well as a higher proportion of 
recipients with a previous kidney transplant; and (b) donors' age and 
in the percentage of donations after circulatory death.\133\ Early 
referral of patients for transplants, kidney exchange programs, better 
diagnostic tools to identify early acute rejection, innovative 
therapies for countering rejection and infection, and optimization of 
immunosuppressive medications may be opportunities to enhance kidney 
graft survival.\134\
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    \133\ Hariharan S, Israni AK, Danovitch G. Long-Term Survival 
after Kidney Transplantation. N Engl J Med. 2021 Aug 19;385(8):729-
743. doi: 10.1056/NEJMra2014530. PMID: 34407344.
    \134\ Hariharan, S., Israni, A. K., & Danovitch, G. (2021). 
Long-Term Survival after Kidney Transplantation. New England Journal 
of Medicine, 385(8), 729-743. https://doi.org/10.1056/nejmra2014530.
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g. Non-Acceptance and Discards in Kidney Transplantation
    Studies have documented the substantial extent of deceased donor 
kidney non-utilization in the U.S. relative to other countries 
(although methods of defining these rates differ among countries), as 
well as a steady increase in that trend over the past two 
decades.135 136 137 138 139 A study in 2018 described donor-
specific factors, such as biopsy findings and donor history, along with 
an increasing selectivity among transplant hospitals in accepting 
organs for transplant and inability to locate a recipient as 
contributing to this increase in non-utilization.\140\ Within the 
context of the COVID-19 pandemic, the non-utilization of deceased donor 
kidneys in 2020 rose to the highest level up to that time, 21.3 
percent, despite the decline in discard of organs from hepatitis C-
positive donors.141 142 An analysis found that the donor 
kidney discard rate peaked at 27 percent during the fourth quarter of 
2021.\143\
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    \135\ Mohan, S., Chiles, M. C., Patzer, R. E., Pastan, S. O., 
Husain, S. A., Carpenter, D. J., Dube, G. K., Crew, R. J., Ratner, 
L. E., & Cohen, D. J. (2018). Factors leading to the discard of 
deceased donor kidneys in the United States. Kidney International, 
94(1), 187-198. https://doi.org/10.1016/j.kint.2018.02.016.
    \136\ Aubert, O. Reese. P. Audry, B. Bouatou, B. Raynaud, M. 
Viglietti, D. Legendre, C. Glotz, D. Empana, J. Jouben, X. 
Lefaucheur, C. Jacquelinet, C. Loupy, A. (2019). Disparities in 
Acceptance of Deceased Donor Kidneys Between the United States and 
France and Estimated Effects of Increased US Acceptance. JAMA 
Internal Medicine, 179(10), 1365-1374. https://doi.org/10.1001/jamainternmed.2019.2322.
    \137\ Ibrahim, M., Vece, G., Mehew, J., Johnson, R., Forsythe, 
J., Klassen, D., Callaghan, C., & Stewart, D. (2019). An 
international comparison of deceased donor kidney utilization: What 
can the United States and the United Kingdom learn from each other? 
American Journal of Transplantation, 20(5), 1309-1322. https://doi.org/10.1111/ajt.15719.
    \138\ Stewart, D. E., Garcia, V. C., Rosendale, J. D., Klassen, 
D. K., & Carrico, B. J. (2017). Diagnosing the Decades-Long Rise in 
the Deceased Donor Kidney Discard Rate in the United States. 
Transplantation, 101(3), 575-587. https://doi.org/10.1097/tp.0000000000001539.
    \139\ Health Resources and Services Administration. OPTN. 
(2017). Two year analysis shows effects of kidney transplantation 
system. Optn.transplant.hrsa.gov. Retrieved May 30, 2023, from 
https://optn.transplant.hrsa.gov/news/two-year-analysis-shows-effects-of-kidney-allocation-system/.
    \140\ Mohan, Chiles et al. (2018).
    \141\ Lentine, K. Smith, J. Hart, A. Miller, J. Skeans, M. 
Larkin, L. Robinson, A. Gauntt, K. Israni, A. Hirose, R. Snyder, J. 
(2022). OPTN/SRTR 2020 Annual Data Report: Kidney. American Journal 
of Transplantation 22(Suppl 2) 21-136.
    \142\ Following upon the introduction of certain anti-viral 
drugs, transplanting kidneys from donors infected with Hepatitis C 
has shown promising outcomes in recent studies. See Penn Medicine 
News ``Penn Researchers Continue to Advance Transplantation of 
Hepatitis C Virus-infected kidneys into HCV-Negative Recipients'' 
August 31, 2020 https://www.pennmedicine.org/news/news-releases/2020/august/penn-researchers-advance-transplantation-hepatitis-c-virus-infected-kidneys-hcv-negative-recipients.
    \143\ Cron, D. Husain, S. Adler, J. (2022). The new distance-
based kidney allocation system: Implications for patients, 
transplant centers, and Organ Procurement Organizations. Current 
Transplantation Reports, 9(4), 304. https://doi.org/10.1007/s40472-022-00384-z.
---------------------------------------------------------------------------

    Since 2014, when the KAS went into effect, OPTN has aimed to 
address the high rate of kidneys going unused. The new kidney 
allocation system was developed in response to higher than necessary 
discard rates of kidneys, variability in access to transplants for 
candidates who are harder to match due to biologic reasons, inequities 
resulting from the way waiting time was calculated, and a matching 
system that results in unrealized life years and high re-transplant 
rates.\144\ The KAS also revised the system that matched waitlisted 
individuals with available organs.\145\ As part of the KAS, the Kidney 
Donor Profile Index (KDPI) was implemented to assess the quality of 
kidneys procured for kidney transplants. The KDPI is based on a 
preliminary measurement, the Kidney Donor Risk Index (KDRI), which 
estimates the relative risk of post-transplant kidney graft failure 
based on scores for the deceased donor on a set of 10 demographic and 
clinic characteristics, including age, height, weight, ethnicity, 
history of hypertension, history of diabetes, cause of death, serum 
creatinine, hepatitis C virus status, and donation after circulatory 
death status.\146\ This relative risk is determined in relation to the 
overall distribution of a grouping of these scores across the overall 
deceased donor population for the previous year. The KDPI transforms 
the KDRI to a zero-to-100 scale. Lower KDPI scores are associated with 
greater expected post-transplant longevity, while higher KDPI

[[Page 43537]]

scores are associated with a worse expected outcome in this 
regard.\147\
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    \144\ OPTN Kidney Transplantation Committee. (n.d.). The New 
Kidney Allocation System (KAS) Frequently Asked Questions. Retrieved 
December 6, 2023, from https://optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. p. 4.
    \145\ OPTN. (n.d.) The New Kidney Allocation System (KAS) 
Frequently Asked Questions. https://optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. p. 4.
    \146\ OPTN. (n.d.). The New Kidney Allocation System Frequently 
Asked Questions. https://optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. pp. 8-9.
    \147\ OPTN. (n.d.). The New Kidney Allocation System Frequently 
Asked Questions . https://optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. p. 4.
---------------------------------------------------------------------------

    According to these new allocation rules, the KDPI of an available 
organ was to be assessed, with donor kidneys with low KDPI scores being 
offered to patients scoring high in terms of expected longevity. New 
revisions to the KAS also included an individual's time on dialysis 
prior to waitlisting to assess waiting time used for determining 
priority for an available organ, and new rules that allowed for greater 
access for candidates with blood type B to donor kidneys with other 
blood types.\148\
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    \148\ OPTN. (n.d.). The New Kidney Allocation System Frequently 
Asked Questions. https://optn.transplant.hrsa.gov/media/1235/kas_faqs.pdf. p. 4.
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    An OPTN data analysis from 2014 to 2016, the first two years after 
KAS implementation, showed that despite substantial increases in both 
deceased kidney donor transplants and deceased kidney donation, the 
kidney discard rate increased to 19.9 percent in 2016.\149\ OPTN linked 
the discard rates to KDPI scores, with fewer than 3 percent of donor 
kidneys with KDPI between zero and 20 percent discarded, compared with 
60 percent of donor kidneys with KDPI between 86 and 100 percent being 
discarded.\150\
---------------------------------------------------------------------------

    \149\ OPTN. (2017, July 9). Two Year Analysis shows effects of 
Kidney Allocation System. Retrieved June 9, 2023, from https://optn.transplant.hrsa.gov/news/two-year-analysis-shows-effects-of-kidney-allocation-system/.
    \150\ OPTN. (2017, July 9). Two Year Analysis shows effects of 
Kidney Allocation System. Retrieved June 9, 2023, from https://optn.transplant.hrsa.gov/news/two-year-analysis-shows-effects-of-kidney-allocation-system/.
---------------------------------------------------------------------------

    In March 2021, OPTN finalized a newer allocation policy, which 
eliminated the use of DSAs and regions from kidney and pancreas donor 
distribution. These measures were part of a framework announced in 2019 
that also applied to heart, lung, and liver donor distribution, with 
the goal of reducing the importance of geography in patients' access to 
organs, and, instead, emphasizing medical urgency.151 152 
The new system instituted a point system with up to 2 points (equal to 
2 years on the wait list) for patients listed at transplant hospitals 
within 250 nautical miles of the donor hospital, and the points 
decreasing linearly from the donor hospital to the circle perimeter. 
The more points an individual has, the higher their position on the 
waitlist and the more likely they are to receive an organ offer. If 
there is no candidate within the designated radius, the kidney is 
offered to patients listed at hospitals outside the fixed circle, based 
on separate proximity points that decrease linearly as the location of 
a patient approaches 2,500 nautical miles from the donor hospital.\153\
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    \151\ Potluri, V. S., & Bloom, R. D. (2021). Effect of Policy on 
Geographic Inequities in Kidney Transplantation. American Journal of 
Kidney Diseases, 79(6), 897-900. https://doi.org/10.1053/j.ajkd.2021.11.005.
    \152\ Penn Medicine. (2021, November 17). Update: Change in 
Organ Allocation Designed to Increase Equity in US Kidney and 
Pancreas Transplantation. Penn Medicine Physician Blog. https://www.pennmedicine.org/updates/blogs/penn-physician-blog/2021/november/change-in-organ-allocation-designed-to-increase-equity-in-us-kidney-and-pancreas-transplantation.
    \153\ Potluri, Bloom. (2021). 897-898.
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    Interested parties within the transplant ecosystem commented that 
the new policy might further contribute to the increasing rate of donor 
organ non-acceptance. According to one review, sharing kidneys over a 
broader geographic region means that OPOs would need to work with 
transplant hospitals with which there was no prior relationship.\154\ 
Concern was also expressed about increased transportation time and 
procurement costs, risk associated with air transport, and a greater 
number of interactions between transplant hospitals and 
OPOs.155 156 157 One study notes that policymakers would 
need to assess the extent to which the new kidney allocation policy 
might affect organ offer acceptance patterns, organ recovery and 
utilization rates, and wait times both for the transplant hospital and 
broader geographic areas.\158\ Another report cited unpublished SRTR 
data, saying that preliminary results suggest an increase in transplant 
rate overall, but a trend toward higher donor kidney discard and 
increased cold ischemia time.\159\ A study at a single transplant 
hospital showed that the number of organ offers--for livers and 
kidneys--grew by 140 percent between May 1, 2019, and July 31, 2021, 
while the number of transplanted organs remained stable, suggesting 
less efficient allocation of organs after the new change in allocation 
policy.\160\
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    \154\ Potluri, Bloom. (2021) 898.
    \155\ Gentry, S.E., Chow, E.K.H., Wickliffe, C.E., Massie, A.B., 
Leighton, T., & Segev, D.L. (2014). Impact of broader sharing on the 
transport time for deceased donor livers. Liver Transplantation, 
20(10), 1237-1243. https://doi.org/10.1002/lt.23942.
    \156\ Chow, E.M., DiBrito, S.R., Luo, X., Wickliffe, C., Massie, 
A.B., Locke, J.E., Gentry, S.E., Garonzik-Wang, J., & Segev, D.L. 
(2018). Long Cold Ischemia Times in Same Hospital Deceased Donor 
Transplants. Transplantation, 102(3), 471-477. https://doi.org/10.1097/tp.0000000000001957.
    \157\ Adler, J.T., Husain, S.A., King, K.L., & Mohan, S. (2021). 
Greater complexity and monitoring of the new Kidney Allocation 
System: Implications and unintended consequences of concentric 
circle kidney allocation on network complexity. American Journal of 
Transplantation, 21(6), 2007-2013. https://doi.org/10.1111/ajt.16441.
    \158\ Adler et al., 2021. 2012.
    \159\ Cron, D.C., S. Ali Husain, & Adler, J. T. (2022). The New 
Distance-Based Kidney Allocation System: Implications for Patients, 
Transplant Centers, and Organ Procurement Organizations. Current 
Transplantation Reports, 9(4), 302-307. https://doi.org/10.1007/s40472-022-00384-z.
    \160\ Reddy, V., Briget da Graca, Martinez, E., Ruiz, R., 
Asrani, S.K., Testa, G., & Wall, A. (2022). Single-center analysis 
of organ offers and workload for liver and kidney allocation. 
American Journal of Transplantation, 22(11), 2661-2667. https://doi.org/10.1111/ajt.17144.
---------------------------------------------------------------------------

    A similar study assessing deceased donor kidney discards from 2000 
to 2015 found that 17.3 percent of 212,305 procured deceased donor 
kidneys were discarded, representing a 91.5 percent increase in 
deceased donor kidney discards during the same time period. The 
increase in donor kidney discards outpaced the number of organs 
recovered for transplantation, adversely impacting transplantation 
rates and waitlist times. Kidneys with higher KDPIs and from donors 
with more disadvantageous characteristics were more likely to be 
discarded. The estimated 5-year graft survival for even the lowest 
quality kidneys substantially exceeds the average 5-year dialysis 
survival rate, making discard patterns concerning.\161\ The study 
indicates a significant overlap in the quality of discarded and 
transplanted deceased donor kidneys, and substantial geographical 
variation in the odds of donor kidney discards, which, as seen 
previously, would continue to be observed in SRTR data for following 
years.\162\ The study also found patterns that indicate factors beyond 
organ quality, including biopsy findings, donor history and poor organ 
function, and inability to locate a kidney donor recipient, may factor 
into deceased organ acceptance decisions. Other factors may be driving 
the deceased donor organ discard rates, as the study found that 
``discarded organs were more likely to come from older, heavier donors 
who were Black, female, diabetic, hypertensive, with undesirable social 
behavior and higher terminal creatinine.'' \163\ This finding accords 
with observed discard patterns from earlier studies whereby recipients 
of marginal kidneys, in terms of advanced donor age, hypertension, 
diabetes, or greater cold ischemia time, showed lower mortality and 
greater survival benefit for many candidates as

[[Page 43538]]

compared to staying on the transplant wait list.164 165 166
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    \161\ Mohan, Chiles et al. 2018. p. 192.
    \162\ Mohan et al. 2018. p. 195.
    \163\ Mohan et al. 2018. 192.
    \164\ Ojo, A.O., Hanson, J.A., Herwig Ulf Meier-Kriesche, Chike 
Nathan Okechukwu, Wolfe, R.R., Leichtman, A.B., Agodoa, L.Y., 
Kaplan, B., & Port, F.K. (2001). Survival in Recipients of Marginal 
Cadaveric Donor Kidneys Compared with Other Recipients and Wait-
Listed Transplant Candidates. Journal of the American Society of 
Nephrology, 12(3), 589-597. https://doi.org/10.1681/asn.v123589.
    \165\ Massie, A.B., Luo, X., Chow, E.K.H., Alejo, J.L., Desai, 
N.M., & Segev, D.L. (2014). Survival Benefit of Primary Deceased 
Donor Transplantation With High-KDPI Kidneys. American Journal of 
Transplantation, 14(10), 2310-2316. https://doi.org/10.1111/ajt.12830.
    \166\ Cohen, J.B., Eddinger, K.C., Locke, J.E., Forde, K.A., 
Reese, P.P., & Sawinski, D. (2017). Survival Benefit of 
Transplantation with a Deceased Diabetic Donor Kidney Compared with 
Remaining on the Waitlist. Clinical Journal of the American Society 
of Nephrology, 12(6), 974-982. https://doi.org/10.2215/cjn.10280916.
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    Research at this time suggests that CMS regulatory requirements and 
OPTN policies may have been contributing to transplant hospitals 
growing more selective in choosing organs for their waitlisted 
patients. A study from 2017 examined OPTN registry data for deceased 
donors from 1987 to 2015, showing that changes in the donor pool and 
certain clinical practices explained about 80 percent of the increase 
in non-utilization of deceased donor kidneys.\167\ However, according 
to the study, the remainder of kidney discards, not accounted for by 
these factors, suggests that increased risk aversion was leading 
transplant hospitals to be more selective about the kidneys they 
accept, regardless of the actual risk profile. Furthermore, increasing 
reliance on the part of OPTN, CMS, and private insurers on program-
specific reports that assessed the performance of transplant hospitals 
on transplant graft and recipient survival rates might have been 
contributing to the overall trend of organs going unused.\168\
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    \167\ Stewart et al. (2017). 575.
    \168\ Stewart et al. (2017). 585.
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    The finding of high rates of non-use of organs that could 
potentially be transplanted with positive outcomes has led to closer 
examination of trends among transplant hospitals in declining the 
possible use of organs for specific patients. Information on each organ 
that is recovered by an OPO is shared with the OPTN, which runs the 
matching system that determines which organ should be offered to which 
recipient. If an organ is determined to be a good match for a 
particular patient, then OPTN would offer that organ to the transplant 
hospital at which the patient is waitlisted on the patient's 
behalf.\169\ A transplant hospital can decline an offer without 
informing the candidate of the offer or the reason it was 
declined.\170\ A study in 2019 focused on patient outcomes associated 
with declines in offers of organs by transplant hospitals. Using OPTN 
data, the study identified a cohort of 280,041 adults on the kidney 
transplant waitlist (out of 367,405 candidates on the waitlist from 
2008 through 2015, the study period) who received one or more offers 
for a deceased donor kidney during that period. More than 80 percent of 
deceased donor kidneys were declined on behalf of one or more 
candidates before being accepted for transplant, and a mean of 10 
candidates who previously received an offer died every day during the 
study period.\171\ As reported by transplant hospitals, organ or donor 
quality concerns accounted for 92.6 percent of all declined offers, 
whereas 2.6 percent of offers were refused because of patient-related 
factors, and an even smaller number for logistical limitations or other 
concerns. While organ or donor quality concerns remained the primary 
reason for declined offers across all KDPI ranges, the study observed 
marked State-level variability in the interval between first offer and 
death or transplant and in the likelihood of dying while having 
remained on the wait list after receiving an offer.\172\
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    \169\ National Kidney Foundation. (2017, February 10). The 
Kidney Transplant Waitlist--What You Need to Know. National Kidney 
Foundation. https://www.kidney.org/atoz/content/transplant-waitlist.
    \170\ Husain, S.A., King, K.L., Pastan, S., Patzer, R.E., Cohen, 
D.J., Radhakrishnan, J., & Mohan, S. (2019). Association Between 
Declined Offers of Deceased Donor Kidney Allograft and Outcomes in 
Kidney Transplant Candidates. JAMA Network Open, 2(8), e1910312. 
https://doi.org/10.1001/jamanetworkopen.2019.10312.
    \171\ Husain et al. 2019.
    \172\ Husain et al. 2019.
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    The methodology and findings of this study are notable since they 
draw a correlation between the specific patterns among transplant 
hospitals of organ non-acceptance and the longevity of patients on the 
wait list. The tendency among certain hospitals to choose to not use 
kidneys for specific patients is shown apart from the distinct finding 
of organs going unused and being discarded. The study shows the 
potential for a similar effect on patient survival from organ offer 
non-acceptance as for organ non-use. The authors of an earlier study 
commented that low acceptance rates of organ offers lead to 
inefficiency, longer ischemia time, unequal access to donated kidneys, 
and perhaps to higher rates of discarded organs.\173\ The findings in 
the 2019 study of a wide range of organ offer acceptance rates among 
transplant hospitals nationwide, as well as of the relation between 
organ offer declines and patient deaths, suggest the need for 
incentives for transplant hospitals to accept earlier offers for their 
patients, which, in turn, could reduce cold ischemia time, and, on the 
whole, increase patient survival.
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    \173\ Wolfe, R.A., Laporte, F., Rodgers, A.M., Roys, E., Fant, 
G., & Leichtman, A.B. (2007). Developing Organ Offer and Acceptance 
Measures: When ``Good'' Organs Are Turned Down. American Journal of 
Transplantation, 7, 1404-1411. https://doi.org/10.1111/j.1600-6143.2007.01784.x.
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h. Non-Acceptance and Discards in Transplantation for Other Solid Organ 
Types
    SRTR has also tracked the non-use, or discard rate, of other solid 
organ types. In 2020, 9.5 percent of livers recovered were not 
transplanted, with livers from older donors less likely to be 
transplanted.\174\ The discard rate for pancreases was 23.4 percent in 
2020; organs from obese donors were highly likely not to be 
transplanted.\175\ The discard rate for hearts in 2020 was one percent, 
having stayed similar over the previous decade.\176\
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    \174\ OPTN/SRTR 2020 Annual Data Report. 2020. Liver. Figures LI 
49, 50.
    \175\ OPTN/SRTR 2021 Annual Data Report. Pancreas. Figures PA 
39, 43.
    \176\ OPTN/SRTR 2021 Annual Data Report. Heart. Figure HR 52.
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    Liver transplantation shows survival benefits for individuals with 
chronic liver disease, but liver transplantation suffers from a severe 
shortage of donor organs.177 178 A study from 2012 shows 
organ offer non-acceptance on the part of transplant programs to affect 
mortality for individuals with end-stage liver disease in a similar 
manner as for ESRD patients. According to the study, most candidates 
for a liver transplant who died or were removed from the wait list had 
received at least one organ offer, suggesting that a substantial 
portion of waitlist mortality results in part from declined organ 
offers.\179\ As we propose for kidney transplantation, understanding 
and addressing why livers, and possibly other organs, are not chosen 
for specific patients also has the

[[Page 43539]]

potential to lead to improved outcomes and longer lives.
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    \177\ Merion, R.M., Schaubel, D.E., Dykstra, D.M., Freeman, 
R.B., Port, F.K., & Wolfe, R.A. (2005). The Survival Benefit of 
Liver Transplantation. American Journal of Transplantation, 5(2), 
307-313. https://doi.org/10.1111/j.1600-6143.2004.00703.x.
    \178\ Ross, K., Patzer, R.E., Goldberg, D.S., & Lynch, R.J. 
(2017). Sociodemographic Determinants of Waitlist and Posttransplant 
Survival Among End-Stage Liver Disease Patients. American Journal of 
Transplantation, 17(11), 2879-2889. https://doi.org/10.1111/ajt.14421.
    \179\ Lai, J.C., Feng, S., & Roberts, J.P. (2012). An 
Examination of Liver Offers to Candidates on the Liver Transplant 
Wait-List. Gastroenterology, 143(5), 1261-1265. https://doi.org/10.1053/j.gastro.2012.07.105.
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i. Organ Transplant Affinity Group
    On September 15, 2023, CMS published a blog post entitled ``Organ 
Transplantation Affinity Group (OTAG): Strengthening accountability, 
equity, and performance.'' \180\ This blog discussed the formation of 
OTAG, a Federal collaborative with staff from CMS and HRSA working 
together to strengthen accountability, equity, and performance to 
improve access to organ donation, procurement, and transplantation for 
patients, donors, families and caregivers, and providers. The proposed 
IOTA Model is a part of this coordinated effort from the OTAG and 
relies on input from across CMS and HRSA.
---------------------------------------------------------------------------

    \180\ Moody-Williams, J, Nair, S. Organ Transplantation Affinity 
Group (OTAG): Strengthening accountability, equity, and performance. 
CMS Blog, September 15, 2023. https://www.cms.gov/blog/organ-transplantation-affinity-group-otag-strengthening-accountability-equity-and-performance.
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C. Provisions of the Proposed Regulation

1. Proposal To Implement the IOTA Model
    In this section of the proposed rule, we propose our policies for 
the IOTA Model, including model-specific definitions and the general 
framework for implementation of the IOTA Model. The proposed upside 
risk payment to the IOTA participants and the proposed downside risk 
payment from IOTA participants to CMS, are designed to increase access 
to kidney transplants for patients with ESRD on the IOTA participant's 
waitlist. As described in section I of this proposed rule, access to 
kidney transplants widely varies by region and across transplant 
hospitals and disparities by demographic characteristics are pervasive, 
raising the need to strengthen and improve performance. We theorize 
that the IOTA Model financial structure would promote improvement 
activities across selected transplant hospitals that address access 
barriers, including SDOH, thereby increasing the number of transplants, 
quality of care, and cost-effective treatment. Selected transplant 
hospitals may be motivated to revisit processes and policies around 
deceased and living donor organ acceptance to identify opportunities 
for improvement. The IOTA model payments may also require selected 
transplant hospitals to engage in care delivery transformation to 
better coordinate and manage patient care and needs, invest in 
infrastructure, improve the patient, family, and caregiver experience, 
and engage a care delivery team that is tasked with holistic patient 
care.
a. Proposal for Model Performance Period
    We are proposing a 6-year ``model performance period.'' We are 
proposing to define the model performance period as the 72-month period 
from the model start date, comprised of 6 individual PYs. During the 
model performance period, the IOTA participants' performance would be 
measured and assessed for purposes of determining their performance-
based payments, as proposed in this rule. We propose to define the 
``performance year'' (PY) as a 12-month calendar year during the model 
performance period. We are proposing to define the start of the model 
performance period as the ``model start date,'' and we propose a model 
start date of January 1, 2025, meaning that PY 1 would be January 1, 
2025 to December 31, 2025, and the model performance period would end 
on December 31, 2030. We are proposing a 6-year model performance 
period to allow sufficient time for selected transplant hospitals to 
invest in care delivery transformation and realize returns on 
investments.
    We alternatively considered a 3- or 5-year model performance 
period; however, we believe that a 3-year model performance period 
would be too short to allow adequate time for selected transplant 
hospitals to invest in care delivery transformations. Additionally, our 
analyses detailed in section III.D. of this proposed rule project that 
considerable savings to Medicare would be achieved after the fifth PY, 
which is another reason why we are proposing a 6-year model performance 
period. We also considered a 10-year model performance period similar 
to some more recent Innovation Center models; however, given that this 
would be a mandatory model, we believe it important to limit the 
duration of the initial test to a shorter period.
    We alternatively considered proposing to begin the IOTA Model on 
April 1, 2025 or July 1, 2025, to allow selected transplant hospitals 
more time to prepare to implement the model and to better align the 
model performance periods with that of our data sources, as detailed in 
section III.C. of this proposed rule. However, we are proposing a 
January 1, 2025 start date because we believe that there will be 
sufficient time for IOTA participants to prepare for the model. A 
proposed start date of January 1st also aligns with other CMS calendar 
year rules. We propose that in the event the model start date is 
delayed from the proposed start date, the model performance period for 
the entire model would be 6 PYs with each PY being a 12-month period 
that begins on the model start date. For example, if the IOTA Model 
were to begin April 1, 2025, ``performance year'' would still be 
defined as a 12-month period beginning on the model start date, meaning 
April 1, 2025, to March 31, 2026. As a result, the model performance 
period end date would also shift to include a 72-month period from the 
model start date In the previous example, the model performance period 
would be April 1, 2025, to March 31, 2031.
    We seek comment on the proposed model performance period of 6 years 
and the proposed model start date. We also seek comment on the 
alternative model performance periods that we considered of 3, 5, and 
10 years. We also seek comment on the alternative start dates (April 1, 
2025, and July 1, 2025), and the subsequent adjustments to the model 
performance period if the model start date were to change.
b. Other Proposals
    We are also proposing additional policies for the IOTA Model, 
including the following: (1) the method for selecting transplant 
hospitals for participation; (2) the schedule and methodologies for the 
performance-based payments, and waivers of certain Medicare payment 
requirements solely as necessary to test these payment methodologies 
under the model; (3) the performance assessment methodology for 
selected transplant hospitals, including the proposed methodologies for 
patient attribution, target setting and scoring, and calculation of 
performance across the achievement domain, efficiency domain, and 
quality domain; (4) monitoring and evaluation; and (5) overlap with 
other Innovation Center models and CMS programs.
    We propose that IOTA participants would be subject to the general 
provisions for Innovation Center models specified in 42 CFR part 512 
subpart A and in 42 CFR part 403 subpart K, effective January 1, 2025. 
The general provisions at subpart A of part 512 are also the subject of 
proposed revisions in this proposed rule. As described in section II.B. 
of this proposed rule, we are proposing to expand the applicability of 
the general provisions for Innovation Center models to provide a set of 
standard provisions for Innovation Center models that are applicable 
more broadly across Innovation Center models. We believe that this 
approach would promote transparency, efficiency, and clarity in 
Innovation Center models and avoid the need to restate the provisions 
in each

[[Page 43540]]

model's governing documentation. We believe that applying these 
provisions to the IOTA Model would promote these purposes.
    We seek comment on our proposal to apply the general provisions for 
Innovation Center models, or the proposed standard provisions for 
Innovation Center models, to the IOTA Model.
2. Definitions
    We propose at Sec.  512.402 to define certain terms for the IOTA 
Model. We describe these proposed definitions in context throughout 
section III. of this proposed rule. We propose to codify the 
definitions and policies of the IOTA Model at 42 CFR part 512 subpart D 
(proposed Sec. Sec.  512.400 through 512.460). In addition, we propose 
that the definitions contained in the general provision related to 
Innovation Center models at subpart A of part 512, and the revisions to 
those provisions proposed in this notice of proposed rulemaking, would 
also apply to the IOTA Model. We seek comment on these proposed 
definitions for the IOTA Model.
3. IOTA Participants
a. Proposed Participants
    We propose to define ``IOTA participant'' as a kidney transplant 
hospital, as defined at Sec.  512.402, that is required to participate 
in the IOTA Model pursuant to Sec.  512.412. In addition, we note that 
the definition of ``model participant'' contained in 42 CFR part 
512.110, as well as the proposed revisions to that definition, would 
include an IOTA participant.
    We propose to define ``transplant hospital'' as a hospital that 
furnishes organ transplants as defined in 42 CFR 121.2. We propose this 
definition to align with the definition used by Medicare. We propose to 
define ``kidney transplant hospital'' as a transplant hospital with a 
Medicare approved kidney transplant program. Under Sec.  482.70, a 
transplant program is ``an organ-specific transplant program within a 
transplant hospital (as defined in this section).'' Kidney transplants 
are the most common form of transplants, but not all transplant 
hospitals have a kidney transplant program. As the focus of the IOTA 
Model is kidney transplants, we propose this definition of kidney 
transplant hospital to refer specifically to transplant hospitals that 
perform kidney transplants. We propose to define ``kidney transplant'' 
as the procedure in which a kidney is surgically transplanted from a 
living or deceased donor to a transplant recipient, either alone or in 
conjunction with any other organ(s). As described in section III.B.4.b. 
of this proposed rule, the vast majority of kidney transplants are 
performed alone. However, we believe that it is necessary to include in 
the definition of kidney transplant those kidney transplants that occur 
in conjunction with other organ transplants to avoid creating a 
disincentive for multi-organ transplants within the IOTA Model.
    Kidney transplant hospitals are the focus of the proposed IOTA 
Model because they are the entities that furnish kidney transplants to 
ESRD patients on the waitlist and ultimately decide to accept donor 
recipients as transplant candidates. Kidney transplant hospitals play a 
key role in managing transplant waitlists and patient, family, and 
caregiver readiness. They are also responsible for the coordination and 
planning of kidney transplantation with the OPO and donor facilities, 
staffing and preparation for kidney transplantation, and oversight of 
post-transplant patient care, and they are largely responsible for 
managing the living donation process. The proposed model is intended to 
promote improvement activities across selected transplant hospitals 
that reduce access barriers, including SDOH, thereby increasing the 
number of transplants, quality of care, and cost-effective treatment. 
The IOTA Model would also aim to improve quality of care for ESRD 
patients on the waitlist pre-transplant, during transplant, and during 
post-transplant care. As described in section III.B.4.e. of this 
proposed rule, kidney transplant access and acceptance rates vary 
nationally across kidney transplant hospitals by geography and other 
demographic and socioeconomic factors. The Innovation Center has 
implemented models targeting dialysis facilities and nephrology 
providers, including in the CEC, ETC, and KCC Models. CMS has also 
implemented changes to the OPO CfCs to strengthen performance 
accountability for OPOs. However, kidney transplant hospitals have not 
been the principal focus of any Innovation Center models to date. 
Expanding accountability to kidney transplant hospitals, key players in 
the transplantation ecosystem for ESRD patients, aligns with the larger 
efforts across CMS and HRSA to improve performance and address 
disparities in kidney transplantation.
    We alternatively considered having the IOTA participants be 
accountable care organizations (ACOs), such as a kidney transplant 
ACOs, instead of individual kidney transplant hospitals. In this 
alternative conception, a kidney transplant ACO would form as a 
separate legal entity, potentially including kidney transplant 
hospitals, OPOs, transplant surgeons, and other provider types. The 
kidney transplant ACO would assume accountability for the number of 
kidney transplants, equity in the distribution of transplants, and the 
quality of transplant services from the point of a patient being 
waitlisted to after a transplant recipient's condition stabilizes 
following transplantation. This alternative would potentially carry 
some advantages in the potential for improved coordination among 
individual providers and suppliers in the kidney transplant ACO, but we 
believe that it would be administratively burdensome, as it would 
require the formation of an ACO governing board distinct from the 
governing boards of individual providers. In addition, such an ACO 
arrangement possibly would be subject to additional Federal, State, and 
tribal laws with respect to grievance, licensure, solvency, and other 
regulations, as well as considerable overlap with other ACO-based 
Innovation Center models. We therefore believe that the ``IOTA 
participant'' should be defined as a kidney transplant hospital, as 
defined at Sec.  512.402, that is required to participate in the IOTA 
Model pursuant to Sec.  512.412.
    We further alternatively considered requiring OPO participation in 
the IOTA Model as the entity charged with identifying eligible donors 
and securing organs from deceased donors. However, in 2020, CMS issued 
a final rule that updated OPO CfC requirements to receive Medicare and 
Medicaid payment. This final rule focuses on holding OPOs in the 
transplant ecosystem accountable for improving performance, and the 
Innovation Center does not plan further interventions regarding OPOs at 
this time.
    We seek public comment on the proposal that the IOTA Model 
participants would be kidney transplant hospitals.
b. Proposed Mandatory Participation
    We propose that all kidney transplant hospitals that meet the 
eligibility requirements as discussed in section III.C.3.c. of this 
proposed rule, and that are selected through the participation 
selection process discussed in section III.C.3.d. of this proposed 
rule, must participate in the IOTA Model. We believe that a mandatory 
model is necessary to ensure that a sufficient number of kidney 
transplant hospitals participate in the IOTA Model such that CMS will 
be able to conduct a sound evaluation of the model's effects on cost 
and quality of care in accordance with

[[Page 43541]]

section 1115A(b)(4) of the Act. A mandatory model would also minimize 
the potential for selection bias, thereby ensuring that the model 
participants are a representative sample of kidney transplant 
hospitals. We believe a mandatory model is necessary to obtain relevant 
information about the effects of the model's proposed policies on 
Medicare savings, kidney transplant volume, kidney transplant 
acceptance rates, health equity, and quality of care.
    Nationally, kidney transplant hospitals serve diverse patient 
populations, operate in varied organizational and market contexts, and 
differ in size, staffing, and capability. There is also wide variation 
across kidney transplant hospitals on performance on kidney transplant 
access and organ offer acceptance rate ratios by geography and other 
demographic and socioeconomic factors. We believe that selection bias 
would be a challenge in a voluntary model because we are proposing that 
the IOTA Model would include financial accountability on performance on 
access to kidney transplants and quality of care, and downside risk for 
poor performers. A mandatory model would address these selection bias 
concerns and ensure that our model reaches ESRD patients residing in 
underserved communities.
    We alternatively considered making participation in the IOTA Model 
voluntary. However, we would be concerned that a voluntary model would 
not be evaluable, would result in insufficient numbers of kidney 
transplant hospital participants, and would not be representative of 
kidney transplant hospitals and ESRD patients nationally. These 
concerns reflect our expectation that the proposed payment approach 
would disproportionately attract kidney transplant hospitals already 
performing well in kidney transplant volume, organ offer acceptance 
rate ratios, and quality of care pre- and post-transplantation. Kidney 
transplant hospitals already positioned to score high in the IOTA 
Model's achievement, efficiency, and quality domains may be more likely 
to join the model than other kidney transplant hospitals, as they would 
expect to receive upside risk payments. This may be especially true for 
kidney transplant hospitals that would stand the most to benefit from a 
model that rewards an increase in the number of kidney transplants. We 
believe that selection bias in a voluntary model would also limit our 
ability to assess systematic differences in the IOTA Model's effects on 
kidney transplant disparities, and may further widen disparity gaps for 
underserved communities that stand to lose if the model does not reach 
them. We therefore propose that the IOTA Model would be mandatory for 
all eligible kidney transplant hospitals selected for participation in 
the model, as we believe this would minimize the risk of potential 
distortions in the model's effects on outcomes resulting from hospital 
self-selection.
    We seek public comment on our proposal to make participation in the 
IOTA Model mandatory.
c. Participant Eligibility
    We are proposing kidney transplant hospital participant eligibility 
criteria that would increase the likelihood that: (1) individual kidney 
transplant hospitals selected as IOTA participants represent a diverse 
array of capabilities across the performance domains as discussed in 
section III.C.5. of this proposed rule; and (2) the results of the 
model test would be statistically valid, reliable, and generalizable to 
kidney transplant hospitals nationwide should the model test be 
successful and considered for expansion under section 1115A(c) of the 
Act.
    We are proposing that eligible kidney transplant hospitals would be 
those that: (1) performed 11 or more transplants for patients aged 18 
years or older annually, regardless of payer type, each of the baseline 
years (the ``low volume threshold''); and (2) furnished more than 50 
percent of its kidney transplants annually to patients over the age of 
18 during each of the baseline years. We propose to define ``baseline 
year'' as a 12-month period within a 3-year historical baseline period 
that begins 48 months (or 4 years) before the start of each model PY 
and ends 12 months (or 1 year) before the start of each model PY. For 
example, if the IOTA Model were to start on January 1, 2025, the 
baseline years for PY 1 would be the 12-month period that begins 
January 1, 2021, and ends on December 31, 2023. We propose to define 
``non-pediatric facility'' as a kidney transplant hospital that 
furnishes over 50 percent of their kidney transplants annually to 
patients 18 years of age or older. CMS would select approximately half 
of all DSAs nationwide using a stratified sampling methodology, and all 
eligible kidney transplant hospitals in the selected DSAs would be 
required to participate in the IOTA Model.
    The proposed low volume threshold of 11 or more kidney transplants 
for ESRD patients aged 18 years or older during each of the three 
baseline years (as described in section I.B.2.b. of this proposed rule) 
would exclude low volume kidney transplant hospitals from the IOTA 
Model. We believe that these kidney transplant hospitals should be 
excluded from the model because they may not have the capacity to 
comply with the model's policies, and because the inclusion of this 
group of kidney transplant hospitals in the model would be unlikely to 
significantly alter the overall rates of kidney transplantation. We are 
also proposing a low volume threshold of 11 adult kidney transplants 
because it is consistent with the minimum thresholds for the display of 
CMS data to protect the confidentiality of Medicare and Medicaid 
beneficiaries by avoiding the release of information that can be used 
to identify individual beneficiaries. We alternatively considered using 
a higher threshold, such as 30 adult kidney transplants or 50 adult 
kidney transplants during each of the three baseline years. However, we 
have found that many kidney transplant hospitals consistently perform 
between 11 and 50 transplants per year. We further believe that using a 
higher threshold would decrease the number, size and location of kidney 
transplant hospitals eligible to be selected for participation in the 
IOTA Model, thereby limiting the generalizability of the model test. We 
also recognize that the number of kidney transplants performed by a 
kidney transplant hospital may fluctuate from year to year, and looking 
back three years would help determine if a kidney transplant hospital 
has the capacity to consistently perform 11 or more transplants per 
year. We seek feedback on this approach for determining which kidney 
transplant hospitals would be eligible for selection under the model.
    We considered including pediatric kidney transplant hospitals as 
eligible participants in the IOTA Model. However, pediatric kidney 
transplantation has significantly different characteristics, 
considerations, and processes from adult kidney transplantation. The 
number of pediatric kidney transplants performed each year is also 
exceedingly small, which would present difficulties in reliably 
determining the effects to the model in the pediatric population. 
Additionally, a much larger proportion of pediatric kidney transplants 
are living donor transplants than in the adult population. As such, we 
do not believe the proposed IOTA Model would function in the same way 
for both kidney transplant hospitals serving primarily adults and those 
serving primarily children, and we believe it is necessary to include 
only non-pediatric

[[Page 43542]]

kidney transplant hospitals in the IOTA Model.
    We seek comment on our proposed participant eligibility criteria 
for kidney transplant hospitals, including the requirement that a 
kidney transplant hospital perform 11 or more kidney transplants 
annually on patients aged 18 years or older during the baseline years. 
We also seek comment on the proposal to include only kidney transplant 
hospitals that meet the proposed definition for a non-pediatric 
facility during the baseline years.
d. Participant Selection
(1) Overview and Process for Participant Selection
    We propose to select eligible kidney transplant hospitals for 
participation in the IOTA Model using a stratified sampling of 
approximately half of all DSAs nationwide. All kidney transplant 
hospitals that meet the proposed participant eligibility criteria 
described in section III.C.3.c. of this proposed rule and are located 
in the selected DSAs would be required to participate in the IOTA 
Model. As defined in 42 CFR 486.302, a ``Donation Service Area (DSA)'' 
means a geographical area of sufficient size to ensure maximum 
effectiveness in the procurement and equitable distribution of organs 
and that either includes an entire metropolitan statistical area (MSA) 
or does not include any part of such an area and that meets the 
standards of subpart G. A DSA is designated by CMS, is served by one 
OPO, contains one or more transplant hospitals, and one or more donor 
hospitals. There are currently 56 DSAs as of January 1, 2024. A map of 
the DSAs can be found on the SRTR website.\181\ CMS would use the list 
of DSAs as it appears on January 1, 2024 to select the DSAs, and 
therefore the eligible kidney transplant hospitals that would be 
required to participate in the IOTA Model.
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    \181\ https://www.srtr.org/reports/opo-specific-reports/interactive-report.
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    We propose this approach for selecting IOTA participants to obtain 
a group of eligible kidney transplant hospitals that is representative 
of kidney transplant hospitals from across the country in terms of 
geography and kidney transplant volume. We propose to stratify the DSAs 
into groups based on each DSA's Census Division and the total number of 
adult kidney transplants performed annually across all eligible kidney 
transplant hospitals in each DSA during the baseline years for the 
first PY. Selecting eligible kidney transplant hospitals from these 
groups of DSAs would ensure that the IOTA participants are 
representative of eligible kidney transplant hospitals from across the 
nation in terms of geography and the volume of adult kidney 
transplants.
    A second aim of our proposal to select eligible kidney transplant 
hospitals from stratified groups of DSAs is to prevent distortions on 
the effects of the model's policies and features on outcomes. Our 
analysis of kidney transplant hospital data shows that selecting only 
some eligible kidney transplant hospitals within a selected DSA to 
participate in the IOTA Model may shift the supply of deceased donor 
organs from non-IOTA participants to IOTA participants within the same 
DSA. The resulting distortions would make it difficult to attribute 
changes in outcomes to the model and would limit its evaluability.
    Our proposed approach for selecting IOTA participants would involve 
stratifying DSAs into groups based on the average number of adult 
kidney transplants performed by all eligible transplant hospitals 
located in the DSA during the baseline years of PY 1. We propose using 
this variable to stratify the DSAs into groups because increasing the 
total number of adult kidney transplants is the primary metric that we 
propose to use to evaluate the IOTA participants' performance in the 
model.
    The proposed approach for IOTA participant selection is as follows:
     Assign all DSAs to a Census Division.\182\ The Census 
Bureau subdivides the United States into four Census Regions 
(Northeast, Midwest, South, and West) which are in turn divided into 
nine Census Divisions. CMS would assign each DSA to a single Census 
Division. Due to the New England region being both a DSA and a Census 
Division, CMS would combine the Middle Atlantic and New England Census 
Divisions for a total of eight Census Divisions. If CMS were to keep 
the New England Census Division separate, the New England DSA would be 
guaranteed participation in the model in subsequent steps. As such, we 
are proposing to combine the Middle Atlantic and New England Census 
Divisions for the purposes of this selection methodology. Some DSAs may 
span several Census Divisions, but most DSAs will be assigned to the 
Census Division where the majority of the DSA's population resides 
according to the 2020 Census data. Puerto Rico is the only DSA which 
exists outside of a Census Division. This DSA would be assigned to the 
South Atlantic Census Division as it is the closest geographically. 
This step would create eight Census Division groups, one for each 
Census Division (with the exception of the combined Middle Atlantic and 
New England Census Divisions, which would be grouped together to create 
one Census Division group).
---------------------------------------------------------------------------

    \182\ A complete list of DSAs in the United States as of 2022-
2023 can be obtained using the data reporting tool found on the SRTR 
website (https://optn.transplant.hrsa.gov/data/view-data-reports/build-advanced/).
---------------------------------------------------------------------------

     Determine the kidney transplant hospitals located within 
each DSA. CMS would list out the kidney transplant hospitals located 
within each DSA and assigned Census Division group.
     Identify the eligible kidney transplant hospitals located 
within each DSA. CMS would use the criteria noted in section III.C.3.c. 
of this proposed rule to identify the eligible kidney transplant 
hospitals within each DSA. This step is expected to yield approximately 
180 to 200 eligible kidney transplant hospitals total across the eight 
Census Division Groups.
     For each DSA, determine the average number of adult kidney 
transplants performed annually across all eligible kidney transplant 
hospitals during the baseline years for PY 1. CMS would use data from 
the baseline years for PY 1 (2021-2023) to determine the average number 
of adult kidney transplants performed annually across all of the 
eligible transplant hospitals located in each DSA. CMS would sum the 
number of adult kidney transplants performed by all of the eligible 
kidney transplant hospitals in a DSA during each of the baseline years 
for PY 1 and divide each DSA's sum by three to determine the average 
number of adult kidney transplants furnished annually during the 
baseline years by the eligible kidney transplant hospitals located 
within each DSA.
     Within each Census Division group, create two mutually 
exclusive groups of DSAs using the average number of adult kidney 
transplants performed annually across the baseline years for PY 1. CMS 
would separate DSAs assigned to a Census Division group into two 
mutually exclusive groups of DSAs based on the average number of adult 
kidney transplants performed annually across the baseline years for PY 
1. The two groups within each Census Division group would be: (1) DSAs 
having higher numbers of adult kidney transplants across the baseline 
years; and (2) DSAs having lower numbers of adult kidney transplants 
across the baseline years. Since the average number of adult kidney 
transplants will be different across each DSA, each Census Division 
group will have a different cut off to create these two groups. To 
ensure each DSA has a 50 percent chance of being chosen in step 7, each 
DSA group

[[Page 43543]]

within a Census Division group should have the same number of DSAs. 
However, in the event of an odd number of DSAs within a Census Division 
group, CMS would proceed to step six.
     For groups within a Census Division group that contain an 
odd number of DSAs, CMS would randomly select one DSA from the group. 
Each of these individual selected DSAs would have a 50 percent 
probability of being selected for the IOTA Model. For groups within a 
Census Division group that contain an odd number of DSAs, CMS would 
randomly select one DSA from the group and determine that individual 
DSA's chance of selection for inclusion in the IOTA Model with 50 
percent probability. Following this step, each group within a Census 
Division group would have an even number of DSAs.
     Randomly select 50 percent of remaining DSAs in each 
group. CMS would then take a random sample, without replacement, of 50 
percent of the remaining DSAs in each group (the groups being DSAs 
having higher numbers of adult kidney transplants across the baseline 
years and DSAs having lower numbers of adult kidney transplants across 
the baseline years) within each Census Division group. All of the 
eligible transplant hospitals located within the selected DSAs would be 
required to participate in the IOTA Model.
    We propose that CMS would notify IOTA participants of their 
selection to participate in the IOTA Model in a form and manner chosen 
by CMS, such as public notice and email, at least 3 months prior to the 
start of the model performance period. As described in section 
III.C.3.b. of this proposed rule, we are proposing that participation 
in the IOTA Model would be mandatory. As such, if an IOTA eligible 
transplant hospital is located within one of the DSAs that CMS randomly 
selects for the IOTA Model, the eligible kidney transplant hospital 
would not be able to decline participation in this model, nor would it 
be able to terminate its participation in the model once selected. 
Model termination policies are further discussed in section III.C.16. 
of this proposed rule.
(2) Consideration of Alternatives to Proposed Participant Selection 
Approach
    We considered using other geographic units for stratified random 
sampling to choose IOTA participants, such as Core Based Statistical 
Areas (CBSAs), Metropolitan Statistical Areas (MSAs), Hospital Referral 
Regions (HRRs), or States. CBSAs, MSAs, HRRs, and States are commonly 
known geographic units, and have been used as part of participant 
selection for other Innovation Center models. We believe selecting 
participants by DSA significantly mitigates behavior that would 
artificially inflate the model's effects on kidney transplant volume 
for the reasons described in the preceding section. OPOs associated 
with selected DSAs would be expected to benefit from consistency in 
rules across most or all of their transplant hospitals. The Innovation 
Center found that selecting participants by DSA improved the ability to 
detect changes in kidney transplant volume to a level consistent with 
the anticipated change in kidney transplant volume associated with the 
model's payment rules. Participants from the same DSA are, for the most 
part, subject to similar levels of kidney supply, and, with the 
exception of kidneys from another DSA, the same rules for kidney 
allocation apply. While OPTN recently updated its organ allocation 
methodology to allow organs to go outside of the DSA in which an organ 
was procured, many kidney transplant hospitals still receive a 
plurality of kidneys from the local OPO in their DSA, ensuring that 
this is still a meaningful method to group kidney transplant hospitals. 
Using alternative geographic units would negate these advantages.
    We also considered other random sampling techniques, including 
simple random sampling of transplant hospitals, simple random sampling 
of DSAs, and cluster sampling of DSAs. Simple random sampling of 
hospitals risks oversampling regions of the country where transplant 
hospitals are concentrated and under sampling areas with fewer eligible 
transplant hospitals. Using simple random sampling of DSAs may result 
in an unrepresentative sample of DSAs with a greater risk of 
oversampling regions where DSAs cover small geographic areas. We 
considered cluster random sampling where half of all DSAs would be 
sampled in a first step and half of eligible kidney transplant 
hospitals within selected DSAs would be sampled. However, because this 
approach would retain half of eligible kidney transplant hospitals in 
selected DSAs, we expect the model's effects on kidney transplant 
volume would be overstated because kidney supply flowing towards non-
participant hospitals prior to the start of the model would be 
redirected towards IOTA participants. In addition, CMS's analyses of 
these alternative sampling approaches indicated the model would not be 
evaluable because these approaches were associated with lower precision 
in detecting changes in kidney transplant volumes due to the model 
compared to the increase in transplant volume anticipated from the 
model's payment rules.
    As an alternative we also considered other variables to create DSA 
groups for stratified sampling of DSAs. Specifically, after assigning 
each DSA to a Census Division, we considered stratifying DSAs using the 
following DSA level variables:
     Number of eligible transplant hospitals in DSA.
     Annual adult kidney transplants per eligible transplant 
hospital in DSA.
     Average organ/offer acceptance rate ratio across eligible 
kidney transplant hospitals in DSA.
     Average percent of Medicare kidney transplant recipients 
dually eligible for Medicare and Medicaid or who are LIS recipients.
     Percent of eligible transplant hospitals in DSA 
participating in the Kidney Care Choices or ESRD Treatment Choices 
Models.
     Average percent of kidney transplants from a living donor 
among eligible kidney transplant hospitals in DSA.
    These variables were given consideration in the stratified 
selection approach because their use would create groups of DSAs whose 
eligible transplant hospitals are more similar to each other on the 
listed characteristics instead of only adult kidney transplant volume 
and Census Division. However, we opted to use the simpler stratified 
participant selection approach to provide greater transparency in the 
model's participant selection approach.
    We also considered stratified random sampling of individual kidney 
transplant hospitals using similar variables as those described in the 
preceding paragraph. Although this approach provided representativeness 
of sampled transplant hospitals along dimensions important for the 
model, it would be expected to result in a subset of eligible kidney 
transplant hospitals in at least a portion of DSAs being designated as 
participants. As we have described previously, we expect that allowing 
a portion of DSA kidney transplant hospitals to be model participants 
would result in an overstatement of the model's effects on kidney 
transplant volume and other outcomes of interest. As with the sampling 
approaches considered in the preceding paragraph, CMS's analyses 
indicated the IOTA Model would not be evaluable if stratified sampling 
of individual kidney transplant hospitals were used in participant 
selection for the reasons described previously.

[[Page 43544]]

    CMS expects that no additional participant selections would be made 
for the IOTA Model after its start date unless 10 percent or more of 
selected participants are terminated from the model during the model 
performance period. If this were to occur, we would address the 
selection of new participants in future rulemaking.
    We seek comment on our proposed approach for selecting IOTA 
participants and on the alternative approaches considered, including 
perceived advantages and disadvantages of our proposed participant 
selection approach relative to alternatives.
4. Patient Population and Attribution
a. Proposed Attributed Patient Population
    We propose that the following patients who are alive at the time 
CMS conducts attribution would be attributed to an IOTA participant: 
(1) A kidney transplant waitlist patient, as defined in section 
III.C.4.a. of this proposed rule, regardless of payer type and waitlist 
status, who is alive, 18 years of age or older, and is registered on a 
waitlist, as defined in section III.C.4.a. of this proposed rule, to 
one or more IOTA participants, as identified by the OPTN computer match 
program (``IOTA waitlist patient,''); and (2) A kidney transplant 
patient who receives a kidney transplant at the age of 18 years or 
older from an IOTA participant at any time during the model performance 
period (``IOTA transplant patient''). These patients would be referred 
to as IOTA waitlist patients and IOTA transplant patients, 
respectively, for purposes of assessing each IOTA participant's 
performance across the achievement domain, efficiency domain, and 
quality domain as discussed in section III.C.5. of this proposed rule. 
IOTA waitlist patients and IOTA transplant patients would factor into 
the model's performance-based payments to IOTA participants.
    For the purpose of this model, we propose to define ``waitlist'' as 
a list of transplant candidates, as defined in 42 CFR 121.2, registered 
to the waiting list, as defined in Sec.  121.2, and maintained by a 
transplant hospital in accordance with 42 CFR 482.94(b). We propose to 
define ``kidney transplant waitlist patient'' as a patient who is a 
transplant candidate, as defined in Sec.  121.2, and who is registered 
to a waitlist for a kidney at one or more kidney transplant hospitals.
    We understand that many patients on the waiting list are registered 
at multiple transplant hospitals. Therefore, we propose attributing 
each of these waitlisted patients to every IOTA participant where they 
are registered on a waitlist during a given month in the applicable 
quarter. However, ``kidney transplant patient,'' defined as a patient 
who is a transplant candidate, as defined in Sec.  121.2, and received 
a kidney transplant furnished by a kidney transplant hospital, 
regardless of payer type, would be attributed to the IOTA participant 
that furnished the kidney transplant.
    We propose attributing kidney transplant waitlist patients and 
kidney transplant recipients to IOTA participants for two reasons. 
First, we believe that by attributing these patients to IOTA 
participants it would ensure the full population of potential and 
actual kidney transplant candidates is represented when measuring 
participant performance. The waiting list captures most candidates 
except some living donor recipients. Transplant recipients include 
those who received deceased or living donor transplants. Second, 
because CMS is proposing to hold IOTA participants accountable for 
furnishing kidney organ transplants; focusing on kidney transplant 
waitlist patients and kidney transplant patients, and attributing them 
to IOTA participants, aligns with the model's goals of improving access 
to, and quality of, kidney transplantation, including post-transplant.
    CMS is proposing to determine an IOTA participant's performance 
across the achievement domain, efficiency domain, and quality domain 
based on all IOTA waitlist patients and IOTA transplant patients, 
regardless of payer type, as described in section III.C.5. of this 
proposed rule. That is, an IOTA participant's performance in terms of 
both Medicare beneficiaries and non-Medicare patients would be used to 
determine whether the IOTA participant would receive an upside risk 
payment from CMS, or owe a downside risk payment to CMS. As described 
in section III.C.5. of this proposed rule, demand for kidney 
transplants far exceeds supply, raising concerns that if the IOTA Model 
were limited to Medicare beneficiaries only, the model may 
inadvertently incentivize inappropriate diversion of donor organs to 
Medicare beneficiaries to improve their performance in the model, 
thereby limiting access to non-Medicare beneficiaries and potentially 
disincentivizing pre-emptive kidney transplants for patients not 
already covered by Medicare because their CKD has not progressed to 
ESRD. We believe that the change in care patterns that IOTA 
participants may undertake to be successful in the IOTA Model are 
unlikely to apply solely to Medicare beneficiaries under their care.
    We considered limiting IOTA waitlist patients and IOTA transplant 
patients to Medicare beneficiaries only, as Medicare covers more than 
50 percent of all kidney transplants from both deceased and living 
donors. However, we believe it is necessary to include all patients, 
regardless of payer type, in the IOTA participant's performance 
calculations to protect against unintended consequences and problematic 
financial incentives. Moreover, the group of eligible waitlist and 
transplant patients that would be attributed to each IOTA participant 
is already relatively small, both in terms of transplant candidates and 
transplant recipients. Limiting the IOTA Model performance assessment, 
as described in section III.C.5. of this proposed rule, to Medicare 
beneficiaries would further limit the patient sample size, potentially 
affecting our ability to detect changes in performance due to model 
payments. Therefore, we are proposing that the IOTA Model reflect both 
Medicare beneficiaries and non-Medicare patients for performance 
assessment, with Medicare beneficiaries just being a subset of the 
patient population attributed to each model participant.
    We seek public comment on our proposals to include: (1) all kidney 
transplant waitlist patients, regardless of payer type and waitlist 
status, who are alive, 18 years of age or older, and registered on a 
waitlist to an IOTA participant, as identified by the OPTN computer 
match program; and (2) all kidney transplant patients who receive a 
kidney transplant, at 18 years of age or older, from an IOTA 
participant at any time during the model performance period, in each 
IOTA participant's population of attributed patients. We also seek 
public comment on our proposal to attribute IOTA waitlist patients and 
IOTA transplant patients, respectively, to IOTA participants for the 
purposes of assessing each IOTA participant's performance across the 
achievement domain, efficiency domain, and quality domain, and to 
determine performance-based payments to and from IOTA participants.
b. Patient Attribution Process
    As described in section III.C.4.a. of this proposed rule, we 
propose to define ``attribution'' as the process by which CMS 
identifies patients for whom each IOTA participant is accountable 
during the model performance period. CMS would identify and assign a 
set of Medicare and non-Medicare patients to the IOTA participant 
through attribution. We propose to define

[[Page 43545]]

``attributed patient'' as an IOTA waitlist patient or an IOTA 
transplant patient, as described in section III.C.4.a. of this proposed 
rule. We propose that a patient may not opt out of attribution to an 
IOTA participant under the model.
    Section III.C.4.b.(1). of this proposed rule outlines in more 
detail the attribution criteria to identify attributable kidney 
transplant waitlist patients and kidney transplant patients during 
initial attribution, quarterly attribution, and at annual attribution 
reconciliation using Medicare claims data, Medicare administrative 
data, and OPTN data. In advance of the model start date, we propose to 
attribute patients to IOTA participants through an initial attribution 
process described in section III.C.4.b.(2). of this proposed rule; 
quarterly attribution would be conducted thereafter to update the 
patient attribution list as described in section III.C.4.b.(3). of this 
proposed rule, to include the dates in which patient attribution 
changes occur. After the fourth quarter of each PY, we propose to 
finalize each IOTA participant's annual attribution reconciliation list 
for that PY, including removing certain attributed patients, as 
described in section III.C.4.b(4) of this proposed rule. We propose 
that once a patient is attributed to an IOTA participant, that 
attributed patient would remain attributed to the IOTA participant for 
the duration of the model, unless the patient is removed from the IOTA 
participant's list of attributed patients during the annual attribution 
reconciliation process, as described in section III.C.4.b.(4). of this 
proposed rule.
    We also considered proposing that once a patient is attributed to 
an IOTA participant, either through the initial attribution process or 
through quarterly attribution, that the patient would remain attributed 
only through the end of the PY. Initial attribution would then occur 
prior to the beginning of each PY. However, we choose to align with the 
attribution processes of our other kidney models to simplify 
operations.
    We propose to identify kidney waitlist patients and kidney 
transplant patients using SRTR data, OPTN data, Medicare claims data, 
and Medicare administrative data.
    We seek comment on our patient attribution process proposals and 
alternatives considered.
(1) Attribution and De-attribution Criteria
(i) IOTA Waitlist Patient Attribution
    We propose that kidney transplant waitlist patients would be 
attributed as IOTA waitlist patients to one or more IOTA participants 
based on where the patient is registered on a kidney transplant 
waitlist, regardless of payer type and waitlist status, as identified 
by the OPTN computer match program. We propose that CMS would conduct 
attribution on a quarterly basis, before each quarter of the model 
performance period. CMS is proposing to attribute a kidney transplant 
waitlist patient as an IOTA waitlist patient to an IOTA participant if 
the patient meets all of the following criteria:
     The patient is registered to one or more IOTA 
participant's kidney transplant waitlist during a month in the 
applicable quarter.
     The patient is 18 years or older at the time of 
attribution.
     The patient is alive at the time of attribution.
    For purposes of attributing IOTA waitlist patients to IOTA 
participants, the proposed criteria must be met on the date that CMS 
runs attribution, as described in section III.C.4.b.(1).(i). of this 
proposed rule.
    As described in section III.C.4.b.(1). of this proposed rule, a 
kidney transplant waitlist patient may be registered to more than one 
waitlist, which is why we propose to attribute kidney transplant 
waitlist patients as IOTA waitlist patients to IOTA participants in a 
way that accurately reflects their waitlist registrations. A kidney 
transplant hospital should be actively engaged in coordinating the 
transplant process for kidney transplant waitlist patients on their 
waitlist, as they are responsible for accepting donor organs and 
furnishing transplants. As such, if a kidney transplant waitlist 
patient is registered on the waitlist of multiple IOTA participants, 
CMS would attribute that kidney transplant waitlist patient as an IOTA 
waitlist patient to all of the IOTA participants that have the kidney 
transplant waitlist patient on their waitlists.
    We alternatively considered limiting IOTA waitlist patient 
attribution to only one IOTA participant based on ``active'' waitlist 
status. That is, the IOTA waitlist patient would be attributed to each 
IOTA participant where the patient is registered to a kidney transplant 
waitlist with an ``active'' status in a given quarter. A kidney 
transplant hospital designates patients on its waitlist with an 
``active'' status to signal their readiness to receive a donor kidney 
offer when one becomes available. However, we anticipate that there 
would be operational challenges if CMS were to base patient attribution 
on waitlist ``active'' status, as doing so would require real-time and 
accurate information regarding each patient's waitlist status. There 
may be a time delay when changing a waitlist status from provisionally 
inactive to active once minor issues have been resolved. A kidney 
transplant waitlist patient may be made inactive or ineligible to 
receive an organ offer if, for example, they have an incomplete 
transplant evaluation to assess medical readiness, their BMI exceeds 
the transplant hospital's established threshold, due to infection or 
patient choice, or because of complications presented by other medical 
issues. Additionally, due to our inability to recognize differences in 
the contributions between kidney transplant hospitals in maintaining a 
patient's transplant readiness, we believe attributing kidney 
transplant waitlist patients as IOTA waitlist patients to all the IOTA 
participants where a kidney transplant waitlist patient is registered 
is the most appropriate approach to IOTA waitlist patient attribution, 
regardless of waitlist status.
    As indicated in section III.C.3.c. of this proposed rule, we are 
only proposing to include non-pediatric facilities as eligible 
participants in the IOTA Model. In alignment with this proposal, we 
propose to exclude pediatric patients under 18 years of age from the 
population of attributed patients. According to national data from the 
OPTN, children under the age of 18 make up a small proportion of the 
kidney transplant candidates registered on the waiting list. However, 
pediatric patients have greater access to both deceased and living 
donor kidney transplant relative to adults and are more likely to 
receive a kidney transplant than adults over the age of 18. Pediatric 
patients under 18 years of age are also more likely to receive a living 
donor transplant than adults over the age of 18, and are infrequently 
the recipient of organs at high risk for non-use.\183\ Thus, CMS is not 
proposing to include pediatric patients under the age of 18 as part of 
the population that would be identified and attributed to IOTA 
participants. We alternatively considered including pediatric patients 
under the age of 18 in the IOTA model patient population, but believe 
focusing on adults, given their unique challenges

[[Page 43546]]

accessing kidney transplants, is a priority.
---------------------------------------------------------------------------

    \183\ Lentine, K. L., Smith, J. M., Miller, J. M., Bradbrook, 
K., Larkin, L., Weiss, S., Handarova, D. K., Temple, K., Israni, A. 
K., & Snyder, J. J. (2023). OPTN/SRTR 2021 Annual Data Report: 
Kidney. American journal of transplantation: official journal of the 
American Society of Transplantation and the American Society of 
Transplant Surgeons, 23(2 Suppl 1), S21-S120. https://doi.org/10.1016/j.ajt.2023.02.004.
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    The waiting list often has a delay between when a patient's 
waitlist status changes and when that change is reflected in the data. 
For example, patients who have died are ineligible for transplant and 
must be removed from the waiting list, but there may be a time delay 
between a patient's death and their removal. Thus, we are proposing to 
limit IOTA waitlist patient attribution to patients who are alive at 
the time of attribution.
    We seek comments on our proposed criteria for identifying and 
attributing kidney transplant waitlist patients to one or more IOTA 
participants and alternatives considered.
(ii) IOTA Transplant Patient Attribution
    We propose that kidney transplant patients would be attributed as 
IOTA transplant patients to the IOTA participant that furnished a 
kidney transplant during the model performance period, if they meet the 
following criteria:
     The patient was 18 years of age or older at the time of 
their transplant; and
     The patient was alive at the time of attribution.
    We note that an IOTA transplant patient who experiences transplant 
failure and is then de-attributed from an IOTA participant, as 
described in section III.C.4.b.(1).(iii). of this proposed rule, could 
become attributed to an IOTA participant again at any point during the 
model performance period if they rejoined a kidney transplant waitlist 
for, or received a kidney transplant from, any IOTA participant and 
satisfied all of the criteria for attribution as described in section 
III.C.4.b.(1).(i). or section III.C.4.b.(1).(ii). of this proposed 
rule.
    We propose to attribute kidney transplant patients to the IOTA 
participant that furnished the transplant to hold the IOTA participant 
accountable for patient transplant and post-transplant outcomes. We 
alternatively considered attributing kidney transplant patients based 
on the plurality of post-transplant services, as identified in Medicare 
claims, because it would still result in attributing kidney transplant 
patients to only one IOTA participant and would base attribution on 
where the majority of services were furnished. We recognize that 
patients may choose to receive their pre-and post-transplant care from 
multiple IOTA participants in addition to the IOTA participant that 
performed their kidney transplant. However, the model's incentives do 
not support shifting accountability for post-transplant outcomes away 
from the IOTA participant that furnished the transplant. We believe 
that the IOTA participant that performed the transplant should remain 
accountable for any surgery related outcomes, both successes and 
failures.
    We propose not to attribute patients who are younger than 18 years 
of age at the time of their kidney transplant or who are deceased at 
the time of attribution due to the same reasons described in section 
III.C.4.b.(1).(i). of this proposed rule.
    We seek comments on our proposed criteria for identifying and 
attributing kidney transplant patients as IOTA transplant patients to 
the IOTA participant that furnished their kidney transplant during the 
model performance period. We also seek comment on the alternative 
considered.
(iii) De-Attribution Criteria
    We propose that CMS would only de-attribute attributed patients 
from an IOTA participant during annual attribution reconciliation, as 
described in section III.C.4.b.(4). of this proposed rule. We propose 
that CMS would de-attribute any attributed patient from an IOTA 
participant that meets any of the following criteria as of the last day 
of the PY being reconciled, in accordance with the annual attribution 
reconciliation list as described in section III.C.4.c. of this proposed 
rule:
     The IOTA waitlist patient was not registered on an IOTA 
participant's kidney transplant waitlist on the last day of the PY 
being reconciled.
     The IOTA waitlist patient died at any point during the PY. 
We propose that an IOTA waitlist patient who has died during the PY 
would be removed from the list of attributed IOTA waitlist patients 
effective on the last day of the PY that the death occurred.
     The IOTA transplant patient has died at any point during 
the PY. We propose that an IOTA transplant patient who has died during 
the PY would be de-attributed from the list of attributed IOTA 
transplant patients effective on the last day of the PY that the death 
occurred.
     The IOTA transplant patient's kidney failed during the PY, 
and the patient is not included on the IOTA participant's waitlist. We 
propose that an IOTA transplant patient who experiences transplant 
failure at any point during the PY and does not rejoin an IOTA 
participant's kidney transplant waitlist or receive another transplant 
from an IOTA participant before the last day of the same PY would be 
listed as de-attributed in the annual attribution reconciliation list. 
This IOTA transplant patient would no longer be attributed to the IOTA 
participant effective the last day of the PY in which the IOTA 
transplant patient's kidney transplant has failed.
    We seek comment on our proposed methodology and criteria for 
identifying and de-attributing attributed patients from an IOTA 
participant.
(2) Initial Attribution
    We propose that before the model start date, CMS would conduct an 
``initial attribution'' to identify and prospectively attribute 
waitlist patients to an IOTA participant pursuant to Sec.  512.414. The 
list of IOTA waitlist patients identified through initial attribution, 
namely the initial attribution list, would prospectively apply to the 
first quarter of PY 1, effective on the model start date. The purpose 
of this initial attribution list would be to prospectively provide IOTA 
participants with a list of their IOTA waitlist patients for the 
upcoming quarter.
    We considered attributing patients to IOTA participants at 
different points in time, such as the day that a kidney transplant 
waitlist patient was added to the IOTA participant's kidney transplant 
waitlist, or the day that a kidney transplant patient received their 
kidney transplant. This approach would be more precise than considering 
all attributed patients to be attributed as of the start of the 
quarter. However, due to the limitations of data sources and the 
frequency with which these data are updated, we did not see this as a 
viable alternative.
    We seek comment on our proposal to conduct initial attribution 
before the model start date and alternatives considered.
(3) Quarterly Attribution
    We propose that CMS would attribute patients to IOTA participants 
in advance of each quarter, after initial attribution, and distribute a 
``quarterly attribution list'' to each IOTA participant that includes 
all their attributed patients, including newly attributed patients, on 
a quarterly basis throughout the model performance period, except in 
the event of termination as described in section III.C.16.(b). of this 
proposed rule.
    We considered monthly attribution for more frequent updates to the 
initial attribution list, but believe it would be operationally 
burdensome. We also considered annual attribution for less frequent 
updates to the initial attribution list, which would be less 
operationally burdensome than monthly or quarterly attribution. Annual

[[Page 43547]]

attribution is common in other Innovation Center models and CMS 
programs where the participant is managing total cost of care for a 
population. The benefits of annual attribution would include 
prospectively providing participants a stable list of patients for whom 
they would be held accountable, and, as the process would occur only 
once a year, would be associated with lower administrative burden. The 
downside of annual attribution, however, is that IOTA participants 
would have less frequent updates and understanding of their attributed 
population, potentially making it hard to plan and budget accordingly. 
We do not believe annual attribution would be appropriate for the IOTA 
Model's goal of improving access to kidney transplants and quality of 
care for a patient population that changes frequently. For example, 
kidney transplant hospitals add patients to their kidney transplant 
waitlist throughout the year. Were we to limit attribution to once a 
year, kidney transplant waitlist patients added during the year would 
not be attributed to an IOTA participant until the following year, 
delaying our ability to meet the minimum number of patients required to 
evaluate a model test. As such, we believe more frequent attribution 
would be necessary.
    We seek comment on our proposal to conduct attribution on a 
quarterly basis during the model performance period and on the 
alternatives considered.
(4) Annual Attribution Reconciliation
    We propose that after the end of each PY, CMS would conduct annual 
attribution reconciliation. We propose to define ``annual attribution 
reconciliation'' as the yearly process by which CMS would: (1) create 
each IOTA participant's final list of attributed patients for the PY 
being reconciled by retrospectively de-attributing from each IOTA 
participant any attributed patients that satisfied a criterion for de-
attribution pursuant to Sec.  512.414(c); and (2) create a final list 
of each IOTA participant's attributed patients who would remain 
attributed for the PY being reconciled, subject to the attribution 
criteria in Sec.  512.414(b)(1) and (2). For the purposes of this 
model, we propose to define ``annual attribution reconciliation list'' 
as the final cumulative record of attributed patients that would be 
generated annually for whom each IOTA participant was accountable for 
during the applicable PY.
    For example, after PY 1, CMS would rerun attribution for the entire 
PY to finalize the list of attributed patients that met the criteria 
specified in sections III.C.4.b.(1). and (2). of this proposed rule. 
Once the fourth quarter is complete, CMS would use the fourth quarter 
attribution list to determine and de-attribute any attributed patients 
that meet a criterion for de-attribution, as described in section 
II.C.4.b.(1).(iii). of this proposed rule, from the IOTA participant, 
as described in section III.C.4.b.(1).(iii). of this proposed rule, and 
remove those attributed patients from the quarterly attribution list to 
create the annual attribution reconciliation list. Before the second 
quarter of the following PY, CMS would distribute the annual 
attribution reconciliation list to IOTA participants. We propose that 
these lists, at a minimum, would identify each attributed patient, 
identify reasons for de-attribution in the previous PY, and the dates 
in which attribution began, changed, or ended, where applicable.
    We seek comment on our proposal to conduct annual attribution 
reconciliation.
c. IOTA Patient Attribution Lists
    We propose that no later than 15 days prior to the start of the 
first model performance period, CMS would provide the IOTA participant 
the ``initial attribution list.'' For the purposes of the model, we 
propose to define ``days'' as calendar days, as defined in 42 CFR 
512.110, unless otherwise specified by CMS. On a quarterly basis 
thereafter, CMS would provide the IOTA participant the ``quarterly 
attribution list'' no later than 15 days prior to the start of the next 
quarter. The annual attribution reconciliation list for a given PY 
would be provided to the IOTA participants after the conclusion of the 
PY, before the second quarter of the following PY.
    We propose that the initial, quarterly, and annual attribution 
reconciliation lists would be provided in a form and manner determined 
by CMS.
    We seek comment on our proposed attribution list policies.
5. Performance Assessment
a. Goals and Proposed Data Sources
    As described in section III.B. of this proposed rule, CMS and the 
OPTN each have roles in assessing the performance of kidney transplant 
hospitals. CMS' regulations in 42 CFR part 482 subpart E require 
certain conditions of participation for kidney transplant hospitals to 
receive approval to perform Medicare transplant services. Under 42 CFR 
part 121, the OPTN is required to implement a peer review process by 
which OPOs and transplant hospitals are periodically reviewed for 
compliance with the bylaws of the OPTN and the OPTN final rule (63 FR 
16332). The OPTN MPSC is charged with performing these evaluations; 
including the identification of threats to patient safety and public 
health.\184\
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    \184\ https://optn.transplant.hrsa.gov/about/committees/membership-professional-standards-committee-mpsc/.
---------------------------------------------------------------------------

    CMS and the OPTN have each acknowledged the limitations of 
transplant hospital performance assessment based on the one-year 
patient and transplant survival measure alone. In 2018, CMS eliminated 
its assessment of one year patient and transplant survival for the 
purposes of transplant hospital re-approval in the final rule, 
``Medicare and Medicaid Programs; Regulatory Provisions To Promote 
Program Efficiency, Transparency, and Burden Reduction; Fire Safety 
Requirements for Certain Dialysis Facilities; Hospital and Critical 
Access Hospital (CAH) Changes To Promote Innovation, Flexibility, and 
Improvement in Patient Care'' (84 FR 51732), leaving assessment of the 
one year patient and transplant survival measure only for initial 
Medicare approval, due to concerns that the measure was causing 
conservative behavior in transplant hospitals.\185\ In 2021, the OPTN 
disseminated a proposal to enhance the MPSC's performance monitoring 
process by expanding the number of measures used to identify transplant 
hospital underperformance.\186\ In that proposal, the OPTN acknowledged 
the potential for transplant hospital risk aversion due to the MPSC's 
evaluations of performance based on the one year patient and transplant 
survival metric alone and proposed transplant hospital assessment based 
on a holistic set of measures encompassing aspects of care across the 
transplant journey.\187\
---------------------------------------------------------------------------

    \185\ Medicare and Medicaid Programs; Regulatory Provisions To 
Promote Program Efficiency, Transparency, and Burden Reduction. 
Federal Register. https://www.federalregister.gov/d/2018-19599/p-215.
    \186\ https://optn.transplant.hrsa.gov/media/4777/transplant_program_performance_monitoring_public_comment_aug2021.pdf.

    \187\ Ibid.
---------------------------------------------------------------------------

    Strengthening and improving the performance of the organ 
transplantation system is a priority for HHS, including CMS and HRSA. 
In accordance with this priority and joint efforts with HRSA, the IOTA 
Model would aim to improve performance and equity in kidney 
transplantation by testing whether performance-based payments to IOTA 
participants increases access to kidney transplants for kidney 
transplant waitlist and kidney transplant patients attributed to

[[Page 43548]]

IOTA participants in the model, thereby reducing Medicare program 
expenditures while preserving or enhancing quality of care. For the 
IOTA Model, we are proposing a broader set of metrics which aligns with 
the trends that we believe would encourage IOTA participants to meet 
the model goals as described in section III.A of this proposed rule.
    The IOTA Model would assess performance on a broad set of metrics 
that were selected to align with all of the following model goals:
     Increase number of, and access to, kidney transplants.
     Improve utilization of available deceased donor organs.
     Support more donors through the living donation process.
     Improve quality of care and equity.
    We propose using Medicare claims and administrative data about 
beneficiaries, providers, suppliers, and data from the OPTN, which 
contains comprehensive information about transplants that occur 
nationally, to measure IOTA participant performance in the three model 
domains: (1) achievement domain; (2) efficiency domain; and (3) quality 
domain. Medicare administrative data refers to non-claims data that 
Medicare uses as part of regular operations. This includes information 
about beneficiaries, such as enrollment information, eligibility 
information, and demographic information. Medicare administrative data 
also refers to information about Medicare-enrolled providers and 
suppliers, including Medicare enrollment and eligibility information, 
practice and facility information, and Medicare billing information.
    We solicit comment on our proposal for selecting performance 
metrics and performance domains. We also solicit comment on our 
proposed use of Medicare claims data, Medicare administrative data, and 
OPTN data to calculate the performance across the three proposed 
domains, as described in section III.C.5. of this proposed rule.
b. Method and Scoring Overview
    In accordance with our proposed goals of the IOTA performance 
assessment, as described in section III.C.5.a. of this proposed rule, 
we propose to assess performance across three domains: (1) achievement 
domain; (2) efficiency domain; and (3) quality domain. We propose to 
use one or more metrics within each domain to assess IOTA participant 
performance. We propose that CMS would assign each set of metrics 
within a domain a maximum point value, with the total possible points 
awarded to an IOTA participant being 100 points. We propose to define 
``final performance score'' as the sum total of the scores earned by 
the IOTA participant across the achievement domain, efficiency domain, 
and quality domain for a given PY. We also propose that the combined 
sum of total possible points would determine whether and how the IOTA 
Model performance-based payments, as described in section III.C.6.c. of 
this proposed rule, would apply and be calculated. We propose the 
following point allocations for each of these three domains:
     The achievement domain would make up 60 of 100 maximum 
points. The achievement domain would measure the number of kidney 
transplants performed relative to a participant-specific target, as 
described in section III.C.5.c. of this proposed rule. The achievement 
domain would represent a large portion (60 percent) of the maximum 
total performance score. We weighted the achievement domain performance 
score more than the efficiency and quality domain because we believe it 
aligns with the primary goal of the IOTA Model, to increase the overall 
number of kidney transplants. Additionally, because increasing the 
number of kidney transplants performed is the primary goal of the 
model, we believe weighing performance on this measure more than the 
efficiency domain and quality domain is necessary to directly 
incentivize participants to meet their target.
     The efficiency domain would make up 20 of 100 maximum 
points. The efficiency domain would measure performance on a kidney 
organ offer acceptance rate ratio.
     The quality domain would make up 20 of 100 maximum points. 
As described in section III.C.5.e. of this proposed rule, the quality 
domain would measure performance on a set of quality metrics, including 
post-transplant outcomes, and on three proposed quality measures--
CollaboRATE Shared Decision-Making Score, Colorectal Cancer Screening, 
and 3-Item Care Transition Measure.
    We believe that many prospective IOTA participants may already be 
familiar with the approach of assigning points up to a maximum in 
multiple domains. This structure is similar to other CMS programs, 
including the Merit-based Incentive Payment System (MIPS) track of the 
Quality Payment Program. For MIPS, we assess the performance of MIPS 
eligible clinicians (as defined in 42 CFR 414.1305) across four 
performance categories--one of which is quality--and then determine a 
positive, neutral, or negative MIPS payment adjustment factor that 
applies to the clinician's Medicare Part B payments for professional 
services. Similar to MIPS, we are proposing that the IOTA Model would 
use a performance scoring scale from zero to 100 points across 
performance domains, and apply a specific weight for each domain. We 
believe using wider scales of 0 to 100 points would allow us to 
calculate more granular performance scores for IOTA participants and 
provide greater differentiation between IOTA participants' performance. 
In the future, we believe this methodology for assessing performance 
could be applied with minimal adaptation to future IOTA participants if 
CMS adds other types of organs transplants to the model through 
rulemaking. We believe that the approach of awarding points in the 
achievement, efficiency, and quality domains for a score out of 100 
points represents the best combination of flexibility and comparability 
that would allow us to assess participant performance in the IOTA 
Model.
    The proposed performance domains and scoring structure would also 
allow us to combine more possible metric types within a single 
framework. We believe that this approach allows for more pathways to 
success than performance measurement based on relative or absolute 
quintiles, which were also alternatively considered, as it would reward 
efforts made towards achievable targets.
    We considered more than three domains to assess performance, which 
would potentially offer IOTA participants more opportunity to succeed 
due to the ability to maximize points in different combinations of 
domains. The more domains there are, the more the maximum points 
possible in each domain are spread out. However, we limited the number 
of domains to three to ensure the model is focused and goal-oriented, 
thus promoting, encouraging, and driving improvement activity and care 
delivery transformation across IOTA participants that evidence suggest 
may help achieve desired outcomes. Desired outcomes include delaying or 
avoiding dialysis, improving access to kidney transplantation by 
reducing barriers and disparities, reducing unnecessary deceased donor 
discards, increasing living donors, and improving care coordination and 
quality of care pre and post transplantation. We believe that the three 
domains and the proposed performance scoring structure would offer IOTA 
participants multiple paths to succeed in the proposed IOTA Model due 
to the ability to maximize points in different combinations of domains.

[[Page 43549]]

    We also considered not using the three performance domains and 
scoring structure, instead opting for alternative methods. We 
considered a performance assessment methodology in which an IOTA 
participant's performance on a metric would be divided by an expected 
value for each metric, which would indicate whether an IOTA participant 
is performing better or worse on a given measure than expected. We 
would then calculate a weighted average of all performance scores to 
reach a final score. However, we believe that setting appropriate 
targets of expected performance for each IOTA participant for each 
metric would be unrealistic to implement. The additional methodological 
complexity necessary for this approach would be difficult for an IOTA 
participant to incorporate into its operations and data systems, 
thereby limiting an IOTA participant's ability to understand the care 
practice changes it would need to make to succeed in the IOTA Model.
    We also considered assessing IOTA participant performance solely on 
magnitude of increased transplants over expected transplants. Under 
this approach, an IOTA participant's number of transplants furnished in 
a given PY subtracted from expected transplants would show a numeric 
net gain or loss in total transplants. This net value would be 
multiplied by an IOTA participant's kidney transplant survival rate to 
generate a total score for each IOTA participant. This option would 
reward successfully completed transplants. This methodology reflects 
the goals of the IOTA Model and acknowledges that kidney transplant 
failures are an undesirable outcome. In addition, the methodology is 
simple to evaluate and understand, requiring only two inputs and a 
simple calculation. However, this approach does not account for 
efficiency and quality domain metrics, as proposed in section 
III.C.5.d. and e. of this proposed rule, which we believe to be 
important goals of the model. Thus, we are not proposing this method to 
assess IOTA participant performance.
    We also considered directly translating the benefits of a kidney 
transplant by measuring the net effect of increased transplants and 
post-transplant care at the IOTA participant level. In a performance 
scoring methodology focused on the net effect of increased transplants 
and post-transplant care, the number of kidney transplants performed in 
a given PY would be compared to a benchmark year for the IOTA 
participant. Each additional kidney transplant would then be multiplied 
by the expected number of years of dialysis treatment the transplant 
averted, based on organ quality. Post-transplant care would analyze 
observed versus expected kidney transplant failures. For IOTA 
participants that achieved fewer kidney transplant failures than 
expected, the difference in volumes would be translated into life-
years. Each marginal additional year of averted dialysis care would be 
used to determine the performance-based payment. Because calculating 
expected transplant failures is a complicated calculation with 
assumptions based on organ quality, donor age, and donor health 
conditions, a scoring system of this type would require us to make 
multiple broad assumptions about individual transplants or average 
scores across all transplants performed by the IOTA participant to 
create an accurate estimate of the total number of years of dialysis 
treatment the kidney transplant averted. This level of complexity would 
also introduce operational risks and burden. This approach would be 
aligned with the goals of the IOTA Model as it relates to increasing 
the number and access to kidney transplants but would still require CMS 
to separately assess performance on proposed performance measures for 
the IOTA Model, as discussed in section III.C.5.c., d., and e. of this 
proposed rule.
    We are soliciting feedback from the public on our proposal to 
assess IOTA participant performance in three domains: (1) achievement 
domain; (2) efficiency domain; and (3) quality domain. We are also 
seeking feedback on our proposed performance scoring approach that 
would weigh the achievement domain higher than the efficiency and 
quality domain, and our proposed use of a 0 to 100 performance scoring 
approach to determine if and how performance-based payments would 
apply. Additionally, we invite feedback on the alternatives considered.
c. Achievement Domain
    As stated in section III.C.5.b. of this proposed rule, we propose 
measuring IOTA participant performance across three domains, one of 
which is the achievement domain. We propose to define ``achievement 
domain'' as the performance assessment category in which CMS assesses 
the IOTA participant's performance based on the number of transplants 
performed on patients 18 years of age or older, relative to a target, 
subject to a health equity performance adjustment, as described in 
section III.C.5.c.(3). of this proposed rule, during a PY. We propose 
to use OPTN data, regardless of payer, and Medicare claims data to 
calculate the number of kidney transplants performed during a PY by an 
IOTA participant on patients 18 years of age or older at the time of 
transplant, as described in section III.C.5.c.(2). of this proposed 
rule.
    We propose to set the participant-specific target for the 
achievement domain based on each IOTA participant's historic number of 
transplants. A central goal of the proposed IOTA Model test is to 
increase the number of kidney transplants furnished by IOTA 
participants, which we believe would be possible via care delivery 
transformation and improvement activities, including donor acceptance 
process improvements to reduce underutilization and discards of donor 
kidneys. We believe IOTA participants may also increase the number of 
kidney transplants furnished to patients by improving or implementing 
greater education and support for living donors.
    We considered constructing and using a transplant waitlisting rate 
measure or using SRTR's transplant rate \188\ rather than measuring 
number of transplants performed relative to a participant-specific 
target for the achievement domain. Research has suggested that 
including such a metric could demonstrate the need for both living and 
deceased donor organs for a particular transplant hospital and be less 
reliant on organ availability for a particular geographical area.\189\ 
Research also suggests that the inclusion of a pretransplant measure, 
such as waitlisting rate, may allow for a more complete assessment of 
transplant hospital performance and provide essential information for 
patient decision-making.\190\ However, for the IOTA Model, we propose 
to test the effectiveness of the model's incentives to change outcomes, 
rather than on processes. The relevant outcome for purposes of the IOTA 
Model is the

[[Page 43550]]

receipt of a kidney transplant, not getting on and remaining on the 
kidney transplant waitlist. Additionally, the SRTR transplant rate 
measure calculates the number of those transplanted as a share of the 
kidney transplant hospital's waitlist, which we believe does not 
reflect the variety of ways that kidney transplant hospitals construct 
their waitlist practices. For example, for some kidney transplant 
hospitals, the number of kidneys transplanted as a share of their 
``active'' waitlist transplant candidates may be a more accurate 
representation of their waitlist practices. Thus, we did not believe 
this was appropriate to propose for the IOTA Model.
---------------------------------------------------------------------------

    \188\ For additional information on SRTR's transplant rate 
measure, please see https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports#figurea2.
    \189\ Paul, S., Melanson, T., Mohan, S., Ross-Driscoll, K., 
McPherson, L., Lynch, R., Lo, D., Pastan, S.O., & Patzer, R.E. 
(2021). Kidney transplant program waitlisting rate as a metric to 
assess transplant access. American Journal of Transplantation: 
Official Journal of the American Society of Transplantation and the 
American Society of Transplant Surgeons, 21(1), 314-321. https://doi.org/10.1111/ajt.16277.
    \190\ Paul, S., Melanson, T., Mohan, S., Ross-Driscoll, K., 
McPherson, L., Lynch, R., Lo, D., Pastan, S.O., & Patzer, R.E. 
(2021). Kidney transplant program waitlisting rate as a metric to 
assess transplant access. American Journal of Transplantation: 
Official Journal of the American Society of Transplantation and the 
American Society of Transplant Surgeons, 21(1), 314-321. https://doi.org/10.1111/ajt.16277.
---------------------------------------------------------------------------

    We seek comment on our proposed achievement domain performance 
metric and alternative methodologies considered for assessing 
transplant rates.
(1) Calculation of Transplant Target
    We propose that for each model PY, CMS would calculate a 
``transplant target'' for each IOTA participant, which would determine 
performance in the achievement domain. For the purposes of the model, 
we propose to define ``transplant target'' as the target number of 
transplants set for each IOTA participant to measure performance in the 
achievement domain as described in section III.C.5.c. of this proposed 
rule. We propose that CMS would notify each IOTA participant of their 
transplant target by the first day of each PY, in a form and manner 
determined by CMS.
    For each PY, we propose that CMS would calculate the transplant 
target for the achievement domain by first determining the highest 
number of deceased donor kidney transplants and living donor kidney 
transplants furnished to patients 18 years of age or older in a single 
year during the baseline years, as defined in section III.C.3.c. of 
this proposed rule. CMS would then sum the highest number of deceased 
donor kidney transplants and living donor kidney transplants furnished 
in a single year during the baseline years calculate the transplant 
target for an IOTA participant, even if those transplant numbers were 
achieved during different baseline years. We believe that choosing the 
highest transplant numbers during the baseline years would illustrate 
the capabilities and capacities of the IOTA participant, and, when 
combined, would be an appropriate target for number of transplants 
performed during the PY. We also understand that living donation and 
deceased donor donation involve different processes by the IOTA 
participant, so we are choosing each of those numbers separately to 
recognize the potential capacity for each IOTA participant for both 
living and deceased donor transplantation.
    We propose that the sum of the highest number of deceased donor and 
living donor transplants across the baseline years of the IOTA 
participant would then be projected forward by the national growth 
rate, as described in section III.C.5.c.(1). of this proposed rule, or 
zero should the national growth rate be negative, resulting in the 
transplant target for a given PY. We propose to define ``national 
growth rate'' as the percentage increase or decrease in the number of 
kidney transplants performed over a twelve-month period by all kidney 
transplant hospitals except for pediatric kidney transplant hospitals 
and kidney transplant hospitals that fall below the low volume 
threshold described in section III.C.3. of this proposed rule. We 
propose to define ``pediatric kidney transplant hospitals'' as a kidney 
transplant hospital that performs 50 percent or more of its transplants 
in a 12-month period on patients under the age of 18. We are also 
proposing that the low volume threshold to be 11 kidney transplants 
performed for the purposes of calculating the national growth rate. We 
also propose this approach for calculating the national growth rate to 
account for and reflect the growth in organ procurement by OPOs that 
has occurred, indicating potential growth in the number of available 
organs.
    We propose that CMS would calculate the national growth rate by 
determining the percent increase or decrease of all kidney transplants 
furnished to patients 18 years of age or older from two years prior to 
the PY to one year prior to the PY. Because the proposed national 
growth rate includes IOTA participants and non-IOTA participant kidney 
transplant hospitals, we acknowledge that it could make achieving the 
transplant target number harder. This is why, if the national growth 
rate becomes negative for a PY, we propose treating it as zero and CMS 
would not apply the national growth rate to project forward the sum of 
the highest number of deceased and living donor kidney transplants 
furnished in a single year during the baseline years. In other words, 
an IOTA participant's transplant target would equal the sum of its own 
highest deceased and living donor transplants furnished across the 
baseline years if the national growth rate were to be negative for a 
PY. We also want to be able to share model performance targets with 
IOTA participants before the start of each PY and are prioritizing 
ensuring prospectivity over ensuring the most up-to-date trend figures. 
We also propose that if the model begins on an any date after January 
1, 2025, the trend would also be adjusted.
    For example, to calculate the national growth rate for PY 1 using 
the proposed model start date of January 1, 2025, CMS would first 
subtract the total number of kidney transplants furnished to patients 
18 years of age or older in 2022 from the total number of kidney 
transplants furnished to patients 18 years of age or older in 2023. 
Next, CMS would then divide that number by the total number of kidney 
transplants furnished to patients 18 years of age or older in 2022 to 
determine national growth rate. To create the transplant target for 
each IOTA participant for PY 1 CMS would do the following:
     If the national growth rate is positive, CMS would trend 
the national growth rate forward for an IOTA participant by multiplying 
the national growth rate by the sum of the highest number of deceased 
donor and living donor transplants furnished to patients 18 years of 
age or older across the baseline years for the IOTA participant.
     CMS would take the product of step 1 and add it to the sum 
of the highest living donor and deceased donor kidney transplants 
furnished to patients 18 years of age or old across the baseline years 
for an IOTA participant.
     The sum of step 2 would be the transplant target for an 
IOTA participant. However, if the national growth rate were negative, 
CMS would not trend the growth rate forward for PY 1 and the transplant 
target would be the sum of the highest living donor and deceased donor 
kidney transplants across the baseline years.
    We propose that when calculating the national growth rate for each 
PY, CMS would look to the relevant baseline years for that PY, as 
depicted in Table 1. This approach would mitigate our concern that a 
static baseline may reward a one-time investment, rather than 
continuous improvement. The model PYs, as proposed, would not factor 
into an IOTA participant's transplant target calculation until PY 3 of 
the model (January 1, 2027, to December 31, 2027) and the baseline 
years would not be based exclusively on PYs until PY 5 of the model 
(January 1, 2029, to December 31, 2029), which may represent an 
effective phase-in approach to drive improved performance and savings 
for the Medicare trust fund. We believe that using baseline years to 
calculate the transplant targets would also account for kidney 
transplant hospitals that experience changes in strategy or staffing 
that may affect their

[[Page 43551]]

capacity to perform transplants at the level that they did in previous 
years.
[GRAPHIC] [TIFF OMITTED] TP17MY24.000

    Should we finalize a model start date other than January 1, 2025, 
we propose that the baseline years, as defined in section III.B.2.c. of 
this proposed rule, would shift accordingly, as illustrated in Table 2.
[GRAPHIC] [TIFF OMITTED] TP17MY24.001

    We believe that IOTA participants could improve on this metric in 
several ways. For example, IOTA participants could increase the number 
of kidney organ offers they accept, which would also potentially lead 
to greater efficiency domain scores. IOTA participants could also 
invest in a living donation program or modify their OR schedules to 
facilitate fewer discards due to physician scheduling.
    We considered basing the transplant target on the total number of 
all organ transplants performed by the IOTA participant over the 
baseline years. However, we did not believe this was appropriate 
because the total would not reflect the specific capabilities of the 
IOTA participant's kidney transplant program. We also considered 
adjusting the transplant target by IOTA participant revenue from 
hospital cost reports. In this scenario, our consideration was to look 
at historical kidney transplant data as the best predictor, since this 
reveals the demonstrated capacity for each IOTA

[[Page 43552]]

participant to complete kidney transplants.
    We also considered setting each IOTA participant's transplant 
target by determining the IOTA participant's average total kidney 
transplant volume from the three previous years instead of using the 
sum of the highest living and deceased donor kidney transplant volumes 
during the baseline years. We believe this methodology would be simpler 
and result in a transplant target that is potentially more attainable 
for IOTA participants, assuming that the average kidney transplant 
volume is lower than the sum of the highest volumes of deceased and 
living donor kidney transplants. However, we do not believe that this 
would reflect the potential highest capacity for transplant that we 
would otherwise like the target to reflect.
    We alternatively considered a static or fixed baseline approach for 
purposes of determining the transplant target for each IOTA 
participant, as it would minimize operational burden for CMS due to 
less frequent updates to the transplant target and ensure that the 
model does not set a moving target year-over-year. However, we believe 
that a fixed baseline may reward a one-time investment, rather than 
continuous improvement, and may not account for kidney transplant 
hospitals that experience changes in strategy or staffing that may 
affect their capacity to perform transplants at the level that they did 
in historical years. The rolling baseline approach we are instead 
proposing uses historical kidney transplant volumes pre-dating the 
model start date through the first two model PYs, ensuring a phased-in 
approach before any improvements made during the model performance 
period are accounted for in the baseline.
    We also considered setting the transplant target for IOTA 
participants based on two baseline years, rather than the proposed 
methodology of three. For the proposed model start date of January 1, 
2025, this approach would look at the highest living and deceased 
volumes from 2022 and 2023, trended by the national growth rate from 
2024, to set the transplant target for PY 1. We believe this 
methodology would be more reflective of recent transplantation volume 
and account for the changes to the kidney allocation system that were 
implemented in 2021. However, we believe that using two baseline years 
to set a transplant target would be more susceptible to temporary 
market disruptions or fluctuations that may impact IOTA participants 
capability or capacity to furnish kidney transplants, such as: if the 
transplant hospital experiences a shortage in transplant surgeons or 
other critical staff; if the transplant hospital is acquired; or, the 
occurrence of a natural disaster, pandemic, or other public health 
emergency or other extreme and uncontrollable circumstance that would 
require the transplant hospital to temporarily suspend operations. Any 
of these disruptions or fluctuations could result in an inaccurate 
transplant target that would not accurately reflect an IOTA 
participant's volume capability.
    We considered determining the national growth rate by calculating 
separately; (1) the growth rate of the deceased donor target number by 
the growth in organs procured, and (2) the living donor target number 
by the national growth rate in living donor transplants. However, 
procurement rates vary nationally depending on variables unique to each 
geography and local OPO policies.\191\ Because we want the model to 
inspire kidney transplant hospitals to expand living donor programs, 
not just match national growth rates, we did not believe this 
alternative methodology was appropriate to propose.
---------------------------------------------------------------------------

    \191\ Potluri, V.S., & Bloom, R.D. (2021). Effect of Policy on 
Geographic Inequities in Kidney Transplantation. https://doi.org/10.1053/j.ajkd.2021.11.005; Hanaway, M.J., MacLennan, P.A., & Locke, 
J.E. (2020). Exacerbating Racial Disparities in Kidney Transplant. 
JAMA Surgery, 155(8), 679. https://doi.org/10.1001/jamasurg.2020.1455.
---------------------------------------------------------------------------

    We also considered determining the national growth rate using the 
following information: (1) the total growth rate in kidney transplants; 
(2) the change in rate of organs procured by OPOs; (3) the growth rate 
in kidney transplants in the non-selected portions of the country; and 
(4) calculating the average growth rate across multiple baseline years. 
However, we believe that the national growth rate in kidney transplants 
makes the most sense to use as the basis for the model's growth factor 
because it best reflects volume trends in the kidney transplant 
ecosystem overall, as it considers all kidney transplant hospitals, not 
just IOTA participants.
    Finally, we also considered a performance assessment methodology 
for IOTA participants already achieving higher rates of kidney 
transplantation by assessing each such IOTA participant's total 
transplant volume as compared to all IOTA participants, rather than on 
an IOTA participant specific transplant target. We believe this 
methodology is both easy to understand and simple to administer because 
it rewards IOTA participants for the total number of transplants 
performed. However, we believe this methodology would not be fair to 
IOTA participants that are smaller in size or achieving lower rates of 
kidney transplantation.
    We solicit comment on our proposal to set unique transplant targets 
for each IOTA participant, the methodology for setting transplant 
targets, and any alternatives considered.
(2) Calculation of Points
    We propose that the achievement domain would be worth 60 points. We 
chose this domain for the highest number of points because we believe 
that driving an increase in the number of transplants should be the 
main incentive for change in the model. We considered allocating fewer 
points to this domain, such as 50 points, but we believe that 
performance in this domain should impact the overall performance score 
more than the other domains given its centrality to the model.
    We propose that an IOTA participant's performance would be assessed 
relative to their transplant target, with those performing at less than 
75 percent of the transplant target receiving no points and those 
performing at 150 percent of the transplant target or above receiving 
the maximum number of points (60 points). That is, at the highest end 
of the scale, IOTA participants performing at or above 150 percent of 
the transplant target would earn the maximum 60 points, while at the 
lowest end of the scale, IOTA participants performing at less than 75 
percent of the transplant target would earn no points for the 
achievement domain; performance that falls in between 75 percent and 
150 percent of the transplant target may earn the IOTA participant 45, 
30, or 15 points in the achievement domain. Table 3 illustrates our 
proposal for how an IOTA participant's performance would be assessed 
against its transplant target. We chose 150 percent as the maximum 
performance level based on the theoretical capability of growth in one 
year and analysis in trends of transplant over time. We recognize that 
an IOTA participant might exceed 150 percent of its transplant target, 
but this is not expected given the investment needed for substantiable 
transplant infrastructure to consistently support that number of 
transplants over time.

[[Page 43553]]

[GRAPHIC] [TIFF OMITTED] TP17MY24.002

    We believe that a methodology based on performance improvement 
relative to historical performance is important and would allow us to 
test whether the model's performance based payments drive increased 
behavior from IOTA participant, as opposed to just rewarding IOTA 
participants based on the status quo. IOTA participants that are 
achieving a high rate of kidney transplantation, and already have 
robust transplant programs at the start, can more easily scale up to 
achieve the additional growth required for excellent performance under 
the model. Also, given our statutory requirements to achieve savings, 
the CMS Office of the Actuary (OACT) estimates, as described in section 
VI of this proposed rule, suggest that savings would be driven by the 
effects of increased transplants. We believe that the model's 
performance based payments need to be tied to a policy that aims to 
create and drive Medicare savings.
    We considered offering differential credit for transplants by type. 
With this methodology, IOTA participants would receive bonus points and 
score higher for transplants that fit into categories that lead to more 
savings, such as living donor kidney transplants (LDK), high KDPI 
donors, or pre-emptive transplants, compared to other transplants. 
However, we believe that counting all transplants the same, except for 
transplants furnished to underserved populations, would maximize 
flexibility for IOTA participants in meeting their targets and minimize 
the potential harm and unintended consequences the alternative system 
would create.
    As an alternative, we considered including gradient points instead 
of points based on bands (that is, between X and Y). Scoring closer to 
a performance minimum would result in increased points rather than 
remaining static throughout the band. We considered the following 
formula: Percent Performance Relative to Transplant Target * (100/2.5), 
not to exceed 60 points. However, we decided that a narrower range of 
results would better differentiate performance among IOTA participants 
and allow for easier comparison across IOTA participants.
    We also considered smaller point brackets of improvement, requiring 
IOTA participants to achieve a flat number increase of kidney 
transplants, such as to a 140 percent, 125 percent, or 120 percent, to 
achieve the highest performance in this category, and asymmetric point 
brackets that would make the magnitude of performance required to 
achieve the highest performance rate a flat number increase in addition 
to a percentage increase. However, we wanted the percentage of the 
transplant target necessary to achieve the highest number of points to 
be large enough to incentivize behavior while still being achievable.
    We also considered improvement-only scoring, based on year-over-
year IOTA participant transplant growth, without inclusion of national 
rates. In this methodology, positive improvement rates less than 5 
percent would be scored 15 points, rates over 5 percent would be scored 
30 points, rates over 20 percent would be scored 45 points, and rates 
over 50 percent would be scored 60 points. We also considered using 
combinations of potential transplant target or scoring methods, with 
the final score being whichever score was highest to ensure low-volume 
IOTA participants are not penalized and to mitigate unrealistic 
transplant targets. We considered an improvement-only scoring 
methodology to reflect the historical performance of each IOTA 
participant. However, because we want a methodology that sets more of a 
national standard for expected growth rate to assess volume trends in 
the transplant space overall, we chose not to propose improvement-only 
scoring. As organ supply continues to increase year-over-year, we wish 
to set the expectation for IOTA participants to grow their transplant 
volumes at least at the cadence of the national growth rate.
    We solicit comment on our proposed achievement domain scoring 
methodology and alternative methodologies considered.
(3) Health Equity Performance Adjustment
    Socioeconomic factors impact patient access to kidney transplants. 
Patients with limited resources or access to care may require more 
assistance from kidney transplant hospitals to overcome barriers to 
transplantation. To incentivize IOTA participants to decrease 
disparities in the overall transplant rate among patients of various 
income levels, we propose to include a health equity performance 
adjustment in the methodology for calculating the overall number of 
transplants furnished to patients attributed to an IOTA participant 
during the PY. We propose to define the ``health equity performance 
adjustment'' as the multiplier applied to each kidney transplant 
furnished to a low-income population IOTA transplant patient when 
calculating the transplant target as described in Sec.  512.424). For 
purposes of the model, we propose to define the ``low-income 
population'' to mean an IOTA transplant patient in one or more of the 
following groups:
     The uninsured.
     Medicaid beneficiaries.
     Medicare-Medicaid dually eligible beneficiaries.
     Recipients of the Medicare LIS.
     Recipients of reimbursements from the Living Organ 
Donation Reimbursement Program administered by the National Living 
Donor Assistance Center (NLDAC).
    We propose to apply a health equity performance adjustment, a 1.2 
multiplier, to each kidney transplant furnished by an IOTA participant 
to a patient, 18 years of age or older at the time of transplant, that 
meets the low-income population definition. That is, each kidney 
transplant that is furnished to a patient who meets the low-income 
population definition would be multiplied by 1.2, thus counting that 
transplant as 1.2 instead of 1. The resulting count of the overall 
number of

[[Page 43554]]

kidney transplants performed during the PY, after the health equity 
performance adjustment is applied, would then be compared to the 
transplant target. In effect, the health equity performance adjustment 
would be a reward-only adjustment to the performance score in the 
achievement domain. We also considered basing the multiplier on the 
difference between rates of transplantation for Medicare beneficiaries 
with ESRD who are dual eligible and those who are not. In 2019, 47 
percent of Medicare beneficiaries with ESRD were dually eligible for 
Medicare. However, only 41 percent of Medicare transplants recipients 
were dually eligible, which would yield a multiplier of 1.1.\192\
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    \192\ Gillen, E.M., Ganesan, N., Kyei-Baffour, B., & Gooding, M. 
(2021, August 30). Avalere analysis of disparities in Kidney Care 
Service Utilization. Avalere Health. https://avalere.com/insights/avalere-analysis-of-disparities-in-kidney-care-service-utilization.
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    We chose 1.2 as the health equity performance adjustment multiplier 
because, according to USRDS data, 78.6 percent of patients living with 
ESRD have some form of Medicare and or Medicaid coverage; however only 
65.1 percent of patients who received transplants in 2020 were on 
Medicare, Medicaid, or both.193 194 The 1.2 multiplier 
represents the ratio of those living with ESRD and those who received 
transplants. We theorize that providing this incentive for IOTA 
participants to increase their transplant rate among low-income 
populations would ultimately reduce disparities in access to kidney 
transplants, as it would encourage IOTA participants to address access 
barriers low-income patients often face, such as transportation, 
remaining active on the kidney transplant waiting list, and making 
their way through the living donation process.
---------------------------------------------------------------------------

    \193\ United States Renal Data System. (2020). 2020 USRDS Annual 
Data Report: Epidemiology of kidney disease in the United States. 
National Institutes of Health, National Institute of Diabetes and 
Digestive and Kidney Diseases. Bethesda, MD.
    \194\ Lentine, K. L., Smith, J. M., Hart, A., Miller, J., 
Skeans, M. A., Larkin, L., Robinson, A., Gauntt, K., Israni, A. K., 
Hirose, R., & Snyder, J. J. (2022). OPTN/SRTR 2020 Annual Data 
Report: Kidney. American Journal of Transplantation, 22(S2), 21-136. 
https://doi.org/10.1111/ajt.16982 https://doi.org/10.1111/ajt.16982.
---------------------------------------------------------------------------

    We believe the health equity performance adjustment would be a 
strong incentive to promote health equity, as the multiplier earned 
would help IOTA participants meet or exceed their kidney transplant 
target, thereby potentially resulting in upside risk payments given the 
heavy weighted scoring applied to the achievement domain. We also 
believe it would ensure IOTA participants that serve disproportionately 
high numbers of low-income populations are not penalized in the 
achievement performance scoring.
    We considered not applying a health equity performance adjustment 
to the achievement performance scoring, which would ensure all kidney 
transplants, regardless of the low-income status of individual 
patients, are counted as one transplant. The concern with the health 
equity performance adjustment may be that it may incentivize shifting 
of kidney transplants from one type of patient to another. However, we 
believe the incentive is to promote improvement activities that would 
increase access to all patients while recognizing that low-income 
patients may face more barriers to care outside of the IOTA 
participants' control. It also recognizes that disparities already 
exist in access to kidney transplants for low-income patients, so, by 
addressing inequities, IOTA participants would focus efforts on 
tackling inequities for patients outside the Medicare population.
    For purposes of the health equity performance adjustment, we also 
considered using the area deprivation index (ADI) to define the low-
income population. ADI ranks neighborhoods based on socioeconomic 
disadvantage in the areas of income, education, employment, and housing 
quality. Areas with greater disadvantage are ranked higher, and they 
correlate with worse health outcomes in measures such as life 
expectancy.\195\ The areas used in the ADI are defined by Census Block 
Group, which presents a number of challenges.\196\ However, because 
address information for Medicare beneficiaries may be incomplete, and 
not available at all for patients who have private insurance or the 
uninsured, we opted to not use ADI to define the low-income population. 
We believe that this would leave an incomplete picture of the 
transplant population for a given IOTA participant. Furthermore, the 
socioeconomic status of individuals within a given ADI can vary 
greatly. Those that are underserved in a Census Block Group with a low 
ADI may be overlooked.
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    \195\ Neighborhood Atlas--Home. (2018). Wisc.edu. https://www.neighborhoodatlas.medicine.wisc.edu/.
    \196\ https://www2.census.gov/geo/pdfs/reference/GARM/Ch11GARM.pdf.
---------------------------------------------------------------------------

    We also considered including ``rural resident'' as one of the 
groups that define a low-income population in the IOTA Model, as rural 
transplant patients face numerous barriers to care, including 
transportation, food, housing, and income insecurity, and no or limited 
access to kidney transplant hospitals within or close to their rural 
communities. We considered defining rural beneficiaries consistent with 
the criteria used for identifying a rural area when determining CAH 
eligibility at 42 CFR part 485.610(b)(1)(i), that is beneficiaries 
living outside an MSA. However, we were unsure if it was appropriate to 
include this group to define a low-income population to determine if a 
health equity adjustment would apply to the achievement performance 
score, particularly as the proposed low-income definition may already 
capture the majority of rural kidney transplant patients.
    We seek comment on our proposed health equity performance 
adjustment, including on the adjustment multiplier and calculation 
method, the definition of low-income population and alternatives 
considered, including consideration of ADI as an alternative 
definition, or including rural resident in the low-income population 
definition.
d. Efficiency Domain
    We propose to define the ``efficiency domain'' as the performance 
assessment category in which CMS assesses the IOTA participant's 
performance a metric intended to improve the transplant process, as 
described in section III.C.5.d.(1). of this proposed rule, during a PY. 
The efficiency domain is focused on improving the overall efficiency of 
the transplant ecosystem.
    We propose including OPTN's organ offer acceptance rate measure in 
the efficiency domain. The organ offer acceptance rate ratio measure is 
a ratio of observed organ offer acceptances versus expected organ offer 
acceptances, as described in section III.C.5.d.(1). of this proposed 
rule.
(1) Organ Offer Acceptance Rate Ratio
    With over 90,000 unique patients on the waitlist for a kidney 
transplant, the need to effectively use every available donor organ is 
critical. However, despite the new allocation system introduced in 
2021, and more organs being offered over a wider geographic area, the 
kidney discard rate has risen to over 24.6 percent and continues to 
trend upwards.\197\ There is a significant shortage of organs available 
for transplantation, and many patients die waiting for a kidney 
transplant. Moreover, there are large disparities in organ offer 
acceptance ratio performance. A 2020 national registry

[[Page 43555]]

study found that the probability of receiving a deceased donor kidney 
transplant within three years of placement on the waiting list varied 
16-fold between different kidney transplant hospitals across the 
U.S.\198\ The study also found that large variations were still present 
between kidney transplant hospitals that utilized the same OPO and that 
the probability of transplant was significantly associated with 
transplant hospitals' offer acceptance rates.\199\ By incentivizing 
kidney organ offer acceptance, we aim to optimize the use of available 
organs, thereby reducing underutilization and discards of quality donor 
organs.
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    \197\ MN, 1Scientific R. of T. R., Hennepin Healthcare Research 
Institute, Minneapolis. (n.d.). Kidney. Srtr.transplant.hrsa.gov. 
Retrieved June 19, 2023, from https://srtr.transplant.hrsa.gov/annual_reports/2021/Kidney.aspx.
    \198\ King, K. L., Husain, S. A., Schold, J. D., Patzer, R. E., 
Reese, P. P., Jin, Z., Ratner, L. E., Cohen, D. J., Pastan, S. O., & 
Mohan, S. (2020). Major Variation across Local Transplant Centers in 
Probability of Kidney Transplant for Wait-Listed Patients. Journal 
of the American Society of Nephrology, 31(12), 2900-2911. https://doi.org/10.1681/ASN.2020030335.
    \199\ King, K. L., Husain, S. A., Schold, J. D., Patzer, R. E., 
Reese, P. P., Jin, Z., Ratner, L. E., Cohen, D. J., Pastan, S. O., & 
Mohan, S. (2020). Major Variation across Local Transplant Centers in 
Probability of Kidney Transplant for Wait-Listed Patients. Journal 
of the American Society of Nephrology, 31(12), 2900-2911. https://doi.org/10.1681/ASN.2020030335.
---------------------------------------------------------------------------

    For purposes of assessing the performance of IOTA participants in 
the achievement domain, we propose to include the organ offer 
acceptance rate ratio as one of the two metrics of performance. We 
believe that including this measure in the efficiency domain would 
encourage IOTA participants to increase the utilization of available 
organs. We also believe that this measure would encourage IOTA 
participants to improve efficiency in the organ offer process, improve 
acceptance practices for offers received, and allow for maximal 
utilization of available organs. We believe that the organ offer 
acceptance rate ratio is an important system-wide metric, as improved 
performance by an IOTA participant would also improve opportunities for 
other kidney transplant hospitals that would not have to wait as long 
for an available donor kidney. We recognize that all kidney transplant 
hospitals are already assessed on the organ offer acceptance rate ratio 
metric under the OPTN, however, we believe that the IOTA Model sets a 
higher bar for performance, as discussed in section III.C.5.d.(1).(a). 
of this proposed rule, rather than clearing the threshold that the OPTN 
sets at 0.30.\200\
---------------------------------------------------------------------------

    \200\ Enhance Transplant Program Performance Monitoring System 
OPTN Membership and Professional Standards Committee. (n.d.). 
https://optn.transplant.hrsa.gov/media/4777/transplant_program_performance_monitoring_public_comment_aug2021.pdf.

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    In the United States, kidney transplant waitlist candidates face 
considerable disparities in access to kidney transplant, such as in who 
is referred and placed on the waiting list, who remains ``active'' on 
the waiting list, and how waitlisted patients are managed by kidney 
transplant hospitals.\201\ Additionally, kidney transplant hospital 
performance is commonly measured by post-transplant outcomes. We 
recognize that including pre-transplant measures could allow for a more 
thorough evaluation of transplant hospital performance and provide 
insight for patient decision-making.
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    \201\ Schold, J.D., Gregg, J.A., Harman, J.S., Hall, A.G., 
Patton, P.R., & Meier-Kriesche, H.U. (2011). Barriers to Evaluation 
and Wait Listing for Kidney Transplantation. Clinical Journal of the 
American Society of Nephrology, 6(7), 1760-1767. https://doi.org/10.2215/cjn.08620910; Hod, T., & Goldfarb-Rumyantzev, A.S. (2014). 
The role of disparities and socioeconomic factors in access to 
kidney transplantation and its outcome. Renal Failure, 36(8), 1193-
1199. https://doi.org/10.3109/0886022x.2014.934179; Stolzmann, K.L., 
Bautista, L.E., Gangnon, R.E., McElroy, J.A., Becker, B.N., & 
Remington, P.L. (2007). Trends in kidney transplantation rates and 
disparities. Journal of the National Medical Association, 99(8), 
923-932. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2574300/; 
Paul, S., Melanson, T., Mohan, S., Ross-Driscoll, K., McPherson, L., 
Lynch, R., Lo, D., Pastan, S.O., & Patzer, R.E. (2021). Kidney 
transplant program waitlisting rate as a metric to assess transplant 
access. American Journal of Transplantation: Official Journal of the 
American Society of Transplantation and the American Society of 
Transplant Surgeons, 21(1), 314-321. https://doi.org/10.1111/ajt.16277; Cheng, X.S., Busque, S., Lee, J., Discipulo, K., Hartley, 
C., Tulu, Z., Scandling, J. ., & Tan, J.C. (2018). A new approach to 
kidney wait-list management in the kidney allocation system era: 
Pilot implementation and evaluation. Clinical Transplantation, 
32(11), e13406. https://doi.org/10.1111/ctr.13406.
---------------------------------------------------------------------------

    We considered several waitlist management metrics for assessing 
performance in the efficiency domain, such as the number of patients 
registered to a waitlist, the number or percentage of attributed 
patients registered on a waitlist with an active waitlist status, or 
the number or percentage of attributed patients on a waitlist with 
active waitlist status to inactive waitlist status. Metrics focused on 
the waitlist could help assess how effectively kidney transplant 
hospitals are managing their kidney transplant waitlist patients. Organ 
offers to waitlist kidney transplant patients are made directly to the 
kidney transplant hospital where they are waitlisted. Once a kidney 
transplant hospital receives an organ offer for one of their kidney 
transplant waitlist patients, it is ultimately its decision to accept 
or decline an organ offer on the patient's behalf. Kidney transplant 
hospitals are not required to inform kidney transplant waitlist 
patients for whom an offer was received when an organ offer was 
received or why an organ offer was declined. While we understand the 
importance of a transplant surgeon's clinical decision-making and 
respect the clinical judgement of transplant surgeons, declining an 
offer without involving the affected patient in the decision-making can 
be detrimental to the patient, as additional time on the waitlist can 
negatively impact the patient's quality of life.\202\
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    \202\ Husain, S.A., King, K.L., Pastan, S., Patzer, R.E., Cohen, 
D.J., Radhakrishnan, J., & Mohan, S. (2019). Association Between 
Declined Offers of Deceased Donor Kidney Allograft and Outcomes in 
Kidney Transplant Candidates. JAMA Network Open, 2(8), e1910312. 
https://doi.org/10.1001/jamanetworkopen.2019.10312.
---------------------------------------------------------------------------

    We also considered including a waitlist mortality metric for 
assessing efficiency domain performance, so as to incentivize 
improvements in mortality outcomes of attributed patients on a 
waitlist. On average, as many as 20 patients on the waitlist for a 
kidney transplant die each day waiting for a kidney transplant in the 
United States.\203\ While a waitlist mortality metric may help assess 
patient outcomes and experience while waiting for an organ offer,\204\ 
and provide insight into differences in waitlist management practices 
across kidney transplant hospitals, we recognize that waitlist 
mortality rate is also influenced by the insufficient supply of 
available donor organs available for transplantation. We also recognize 
that IOTA participants may not have a direct effect on, or ability to 
improve, mortality metrics, as nephrologists are also closer to the 
direct care of waitlist patients and would have a greater ability to 
affect their care and mortality rate. Furthermore, we believe that we 
are already testing the ability of nephrologists to manage care for 
Medicare beneficiaries with ESRD or CKD via the KCC Model.
---------------------------------------------------------------------------

    \203\ Delmonico, F.L., & McBride, M.A. (2008). Analysis of the 
Wait List and Deaths Among Candidates Waiting for a Kidney 
Transplant. Transplantation, 86(12), 1678-1683. https://doi.org/10.1097/tp.0b013e31818fe694.
    \204\ Shepherd, S., & Formica, R.N. (2021). Improving Transplant 
Program Performance Monitoring. 8(4), 293-300. https://doi.org/10.1007/s40472-021-00344-z; Wey, A., Gustafson, S.K., Salkowski, N., 
Kasiske, B.L., Skeans, M., Schaffhausen, C.R., Israni, A.K., & 
Snyder, J.J. (2019). Association of pretransplant and posttransplant 
program ratings with candidate mortality after listing. 19(2), 399-
406. https://doi.org/10.1111/ajt.15032.
---------------------------------------------------------------------------

    We also considered several other metrics for assessing efficiency 
domain performance related to time to transplant, such as--
     Time from initial evaluation to transplant;

[[Page 43556]]

     Time from initial referral to transplant;
     Time from initial placement on a waitlist to transplant; 
and
     Time from when a patient was initially referred to time of 
initial evaluation to time of initial placement on a waitlist to time 
to transplant.
    Before a patient can be considered for, and placed on, the waiting 
list for a kidney transplant, they must first be referred by either a 
nephrologist or dialysis facility, at which point they undergo a 
comprehensive evaluation process by a transplant hospital.\205\ Studies 
have shown long-standing barriers and disparities to access to 
transplantation by patient demographics, such as racial/ethnic, sex, 
socioeconomic, and insurance factors.\206\ Disparities are driven by 
various factors, but we recognize that delays or lack of referrals for 
evaluation, evaluation criteria that may unintentionally deem a patient 
not eligible to be placed on a waitlist, and organ acceptance rate 
variations across kidney transplant hospitals, may exacerbate 
disparities. Thus, measuring time to transplant was considered an 
appropriate potential performance metric that could incentivize IOTA 
participants to improve. However, we chose not to propose this type of 
measure due to concerns about how to properly measure start and end 
points and unintended consequences that may harm patients, as it may 
create opportunities for kidney transplant hospitals to manipulate 
average times by only adding patients to the waitlist when they are 
certain of imminent transplant, which could exacerbate waitlist 
inequities.
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    \205\ Paul, S., Plantinga, L.C., Pastan, S.O., Gander, J.C., 
Mohan, S., & Patzer, R.E. (2018). Standardized Transplantation 
Referral Ratio to Assess Performance of Transplant Referral among 
Dialysis Facilities. Clinical Journal of the American Society of 
Nephrology, 13(2), 282-289. https://doi.org/10.2215/cjn.04690417; 
Redeker, S., Massey, E.K., van Merweland, R.G., Weimar, W., Ismail, 
S.Y., & Busschbach, J.J.V. (2022). Induced demand in kidney 
replacement therapy. Health Policy, 126(10), 1062-1068. https://doi.org/10.1016/j.healthpol.2022.07.011; Knight, R.J., Teeter, L.D., 
Graviss, E.A., Patel, S.J., DeVos, J.M., Moore, L.W., & Gaber, A.O. 
(2015). Barriers to Preemptive Renal Transplantation. 
Transplantation, 99(3), 576-579. https://doi.org/10.1097/tp.0000000000000357; Schold, J.D., Patzer, R.E., Pruett, T.L., & 
Mohan, S. (2019). Quality Metrics in Kidney Transplantation: Current 
Landscape, Trials and Tribulations, Lessons Learned, and a Call for 
Reform. American Journal of Kidney Diseases, 74(3), 382-389. https://doi.org/10.1053/j.ajkd.2019.02.020.
    \206\ Shepherd, S., & Formica, R.N. (2021). Improving Transplant 
Program Performance Monitoring. 8(4), 293-300. https://doi.org/10.1007/s40472-021-00344-z; Ernst, Z., Wilson, A., Pe[ntilde]a, A., 
Love, M., Moore, T., & Vassar, M. (2023). Factors associated with 
health inequities in access to kidney transplantation in the USA: A 
scoping review. Transplantation Reviews, 100751. https://doi.org/10.1016/j.trre.2023.100751.
---------------------------------------------------------------------------

    We also considered including a transplantation referral to 
evaluation conversion rate measure. For patients with ESRD, access to 
transplantation is influenced by both referral patterns of pre-
transplantation providers and transplant hospital processes of care and 
evaluation criteria.\207\ Additionally, some studies found considerable 
variation in referral rates to transplantation by dialysis facilities, 
proposing significant regional and facility-level variation in 
care.\208\ However, because dialysis facilities are often the primary 
referrer and are not IOTA participants, we did not propose this 
measure. We also have concerns about how this data would be collected.
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    \207\ Schold, J.D., Patzer, R.E., Pruett, T.L., & Mohan, S. 
(2019). Quality Metrics in Kidney Transplantation: Current 
Landscape, Trials and Tribulations, Lessons Learned, and a Call for 
Reform. American Journal of Kidney Diseases, 74(3), 382-389. https://doi.org/10.1053/j.ajkd.2019.02.020.
    \208\ Ibid; Alexander, G. Caleb., & Sehgal, A.R. (2002). 
Variation in access to kidney transplantation across dialysis 
facilities: Using process of care measures for quality improvement. 
American Journal of Kidney Diseases, 40(4), 824-831. https://doi.org/10.1053/ajkd.2002.35695; Patzer, R.E., Plantinga, L.C., 
Paul, S., Gander, J., Krisher, J., Sauls, L., Gibney, E.M., Mulloy, 
L., & Pastan, S.O. (2015). Variation in Dialysis Facility Referral 
for Kidney Transplantation Among Patients With End-Stage Renal 
Disease in Georgia. JAMA, 314(6), 582. https://doi.org/10.1001/jama.2015.8897.
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    Finally, we also considered a living donor rate as one of the 
metrics used to assess performance in the efficiency domain to measure 
percentage of potential living donors who are evaluated to donate a 
kidney and that actually donated a kidney. This metric could help 
assess success towards addressing living donor concerns and 
improvements in education on the living donor process. However, we did 
not propose this metric because we have concerns about our ability to 
access data needed for measurement.
    Ultimately, we chose not to propose to include waitlist management 
metrics when assessing IOTA participant performance in the efficiency 
domain because we believe that costs are already accounted for in the 
Medicare cost report. Transplant waitlist measures also do not capture 
living donation, which is an additional path to a successful kidney 
transplant that CMS already incentivizes living donations in the ETC 
Model. Moreover, studies have shown that organ acquisition costs have 
been rising and were not solely attributable to the cost of 
procurement, suggesting that an increased focus on the waiting list 
could further increase Medicare expenditures.\209\ Also, for some of 
the measures considered (that is, waitlist mortality, transplantation 
referral to evaluation rate), nephrologists and dialysis facilities 
play large roles in maintaining the patient's health, and we do not 
believe it is appropriate to include a measure that would depend 
largely upon the behavior and actions of physicians and facilities 
other than the IOTA participant. We also believe this type of measure 
could distract from increasing rates of transplant and provide false 
expectations for time to transplant for kidney transplant waitlist 
patients. We are also concerned that a waitlist measure could have 
unintended consequences and potentially lead to those most in need of 
transplant not being listed to receive a transplant.
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    \209\ Cheng, X.S., Han, J., Braggs-Gresham, J.L., Held, P.J., 
Busque, S., Roberts, J.P., Tan, J.C., Scandling, J.D., Chertow, 
G.M., & Dor, A. (2022). Trends in Cost Attributable to Kidney 
Transplantation Evaluation and Waitlist Management in the United 
States, 2012-2017. JAMA Network Open, 5(3), e221847. https://doi.org/10.1001/jamanetworkopen.2022.1847.
---------------------------------------------------------------------------

    We solicit comment on our proposed organ offer acceptance rate 
ratio metric for purposes of assessing performance in the efficiency 
domain, and the alternatives considered.
(a) Calculation of Metric
    We propose calculating organ offer acceptance rates for an IOTA 
participant using OPTN's offer acceptance rate ratio performance metric 
(see Equation 1). Per OPTN's new offer acceptance rate ratio, a rate 
ratio for a kidney transplant hospital that is greater than 1 indicates 
that the kidney transplant hospital usually accepts more offers than 
expected. A rate ratio that is less than 1 conveys a kidney transplant 
hospital's tendency to accept fewer offers than expected compared to 
national offer acceptance practices.\210\ The OPTN MPSC has reported 
that this metric assesses kidney transplant hospitals' rate of observed 
organ offer acceptances to expected acceptances and is intended to 
answer the following question: Given the types of offers received to 
the specific candidates, does this program accept offers at a rate 
higher/lower than national experience for similar offers to similar 
candidates.\211\
---------------------------------------------------------------------------

    \210\ OPTN. (2022). OPTN Enhanced Transplant Program Performance 
Metrics. https://optn.transplant.hrsa.gov/media/r5lmmgcl/mpsc_performancemetrics_3242022b.pdf.
    \211\ Mpsc-enhance-transplant-program-performance-monitoring-
system_srtr-metrics.pdf. (n.d.). Retrieved December 28, 2022, from 
https://optn.transplant.hrsa.gov/media/qfuj3osi/mpsc-enhance-transplant-program-performance-monitoring-system_srtr-metrics.pdf.

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[[Page 43557]]

    Expected acceptances are based solely on kidneys that are accepted 
and transplanted by a kidney transplant hospital, so unsuitable kidneys 
are excluded from this measure, and are calculated using logistic 
regression models to determine the probability that a given organ offer 
will be accepted. The measure, as specified by SRTR methodology, is 
inherently risk adjusted as it only counts organs that are ultimately 
accepted by a kidney transplant hospital.\212\ We propose to use SRTR 
data to calculate the OPTN organ offer acceptance rate ratio, as 
described in section III.C.5.d.(1).(b). of this proposed rule.
---------------------------------------------------------------------------

    \212\ Scientific Registry of Transplant Recipients. (n.d.). Risk 
Adjustment Model: Offer Acceptance. Offer acceptance. https://www.srtr.org/tools/offer-acceptance/.
---------------------------------------------------------------------------

    Per the SRTR measure, we propose dividing the number of kidney 
transplant organs accepted by each IOTA participant (numerator) by the 
risk-adjusted number of expected organ offer acceptances 
(denominator).\213\ This measure utilizes a logistic regression and 
risk adjusts for the following: donor quality and recipient 
characteristics; donor-candidate interactions, such as size and age 
differences; number of previous offers; and, distance of potential 
recipient from the donor.\214\ We propose to use SRTR's adult kidney 
model strata risk adjustment methodology and most recently available 
set of coefficients to calculate the number of expected organ offer 
acceptances.
---------------------------------------------------------------------------

    \213\ Ibid.
    \214\ SRTR. (2023). Srtr.org. https://tools.srtr.org/OAModelApp_2205/; Ibid.
---------------------------------------------------------------------------

    For example, suppose we have a model for predicting the probability 
a kidney offer will be accepted, and this model adjusts for the number 
of years the candidate has been on dialysis, whether the kidney was 
biopsied, and the distance between the donor hospital and the 
candidate's transplant center. Consider the offer of a biopsied kidney 
150 nautical miles (NM) away to a candidate who has been on dialysis 
for 2 years. To calculate the probability of acceptance, we would first 
multiply these values by their respective model coefficients and then 
sum up those products with the model's intercept, as illustrated in 
Table 4.\215\
---------------------------------------------------------------------------

    \215\ CMS notes that some risk adjustment factors in the SRTR 
models may only apply in certain ranges of a continuous variable. 
For example, a term that applies if the patient's age at the time of 
listing is >35 may be named 
``can_age_at_listing_right_spline_knot_35''. In these cases, obtain 
the product using this formula if the patient's age at listing was 
>35: product = (Age-35)*(model coefficient). Others may apply if the 
value is less than (<) a specified value. For example, for a term 
like ``can_age_at_listing_left_spline_knot_18'', obtain the product 
for a patient younger than 18 as: product = (18-Age)*(model 
coefficient).
[GRAPHIC] [TIFF OMITTED] TP17MY24.003

    We would then plug that total into the following equation (see 
Equation 2) to get that the probability of acceptance is approximately 
0.119 (that is, 11.9% chance of acceptance).
Equation 2: Probability of Organ Offer Acceptance
[GRAPHIC] [TIFF OMITTED] TP17MY24.004

    To determine the number of offers a transplant program was expected 
to accept, we would add up the probability of acceptance for every 
offer that transplant program received The final organ offer acceptance 
rate ratio (OAR) is then constructed from the observed (O) number of 
acceptances and the expected (e) number of acceptances using equation 1 
to paragraph (b)(1) of Sec.  512.426. In this example we showed a 
simple logistic regression model that only included three risk-
adjusters. The actual models used by the SRTR adjust for many more 
variables, but the process demonstrated here is the same.
    A kidney may be transplanted into a candidate who did not appear on 
the match run, usually to avoid discard if the intended recipient is 
unable to undergo transplant. If the eventual recipient was not a 
multi-organ transplant candidate and was blood type compatible per 
kidney allocation policy, then these transplants would be included in 
the organ offer acceptance rate. For purposes of the IOTA Model, we 
propose to define ``match run'' as a computerized ranking of transplant 
candidates based upon donor and candidate medical compatibility and 
criteria defined in OPTN policies.
    Per OPTN's new organ offer acceptance rate ratio, Table 5 
summarizes the types of organ offers that we propose be included and 
excluded in the calculation of this metric. For the purposes of organ 
offers excluded from the organ offer acceptance rate ratio, we propose 
to define ``missing responses'' as organ offers that the kidney 
transplant hospital received from the OPO but did not submit a response 
(accepting or rejecting) in the allotted time frame from the time the 
offer was made per OPTN policy 5.6.B.\216\ For purposes of organ offers 
excluded from the organ offer acceptance rate ratio measure, we

[[Page 43558]]

propose to define ``bypassed response'' as an organ offer not received 
due to expedited placement \217\ or a decision by a kidney transplant 
hospital to have all of its waitlisted candidates skipped during the 
organ allocation process based on a set of pre-defined filters matching 
the characteristics of the potential organ to be transplanted.\218\
---------------------------------------------------------------------------

    \216\ OPTN. (2023). OPTN Policies. https://optn.transplant.hrsa.gov/media/eavh5bf3/optn_policies.pdf.
    \217\ Expedited placement has the potential to minimize delays 
in organ allocation by directing organs that may not be ideal to 
transplant centers that have demonstrated a willingness to utilize 
such organs. Currently, expedited placement, also known as 
``accelerated placement'' or ``out-of-sequence'' allocation, permits 
OPOs to deviate from the standard match run, which determines the 
priority of patients on the waiting list for organ offers, under 
exceptional circumstances. This discretionary tool of expedited 
placement is employed by OPOs when there are suboptimal donor 
characteristics associated with donor disease or recovery-related 
issues, in order to prevent the organ from going unused. For 
numerous years, expedited organ placement has played a crucial role 
in organ allocation, enabling OPOs to promptly allocate organs that 
they believe are at risk of not being utilized for transplantation.
    \218\ King, K.L., S Ali Husain, Cohen, D.J., Schold, J.D., & 
Mohan, S. (2022). The role of bypass filters in deceased donor 
kidney allocation in the United States. American Journal of 
Transplantation, 22(6), 1593-1602. https://doi.org/10.1111/ajt.16967; Transplant Quality Corner [verbar] The New MPSC Metric. 
(n.d.). The Organ Donation and Transplantation Alliance. Retrieved 
February 23, 2024, from https://www.organdonationalliance.org/insights/quality-corner/new-mpsc-metric/.
[GRAPHIC] [TIFF OMITTED] TP17MY24.005

    We believe that IOTA participants could improve on the organ offer 
acceptance rate ratio metric in at least two ways. First, IOTA 
participants could increase the number of organ offers they accept, 
which would also potentially lead to greater performance scores in the 
achievement domain. Second, IOTA participants could also decrease the 
number of expected acceptances by adding better filters so that they 
are only receiving offers that they are likely to accept. Stricter 
filters may help ensure that an IOTA participant is not delaying the 
allocation of organs that they are uninterested in that could otherwise 
be accepted by another kidney transplant hospital. Since there are 
multiple ways to improve the offer acceptance ratio, the model is not 
requiring increased utilization of higher KDPI kidneys that some 
centers may not want to use due to their clinical protocols. 
Additionally, the IOTA Model is not prescribing or requiring specific 
care delivery transformation or improvement activities of IOTA 
participants, so as to allow for flexibility and innovation.
---------------------------------------------------------------------------

    \219\ OPTN. (2022). OPTN Enhanced Transplant Program Performance 
Metrics. https://optn.transplant.hrsa.gov/media/r5lmmgcl/mpsc_performancemetrics_3242022b.pdf; For Transplant Center 
Professionals. (n.d.). Www.srtr.org. Retrieved February 22, 2023, 
from https://www.srtr.org/faqs/for-transplant-center-professionals/#oaconsideration.
---------------------------------------------------------------------------

    We considered calculating the organ offer acceptance rate by 
dividing the number of organs each IOTA participant accepts by the 
number offered to that transplant hospital's patients that are 
ultimately accepted elsewhere; however, the lack of risk adjustment in 
this metric may be unfair to some IOTA participants.
    We considered calculating the organ offer acceptance rate by 
dividing the number of organs each IOTA participant accepts by the 
number offered to that transplant hospital's patients that are 
ultimately accepted elsewhere; however, the lack of risk adjustment in 
this metric may be unfair to some IOTA participants.
    We also considered updating the calculation for organ offer 
acceptance rate ratio to account for the benefits of living donation by 
increasing the number of organs in the system because the proposed 
organ offer acceptance rate ratio only shows improvement in deceased 
donor utilization. This modification would add a single 1 in the 
numerator and a single 1 in the denominator for each living donation a 
transplant hospital completes. However, we did not propose updating the 
organ offer acceptance rate ratio because we decided to focus on 
deceased donor acceptance to remain aligned with the SRTR calculation. 
We also did not believe this was appropriate to propose because we 
believe that IOTA participants with an established or high performing 
living donation program would be able to gain points more easily in the 
achievement domain, which has a larger percent of overall points, which 
we believe may be unfair to IOTA participants that do not.
    We seek comment on our proposal to use and calculate the OPTN organ 
offer acceptance rate ratio in accordance with OPTN's measure 
specifications and SRTR's methodology as the metrics that would 
determine IOTA participants' performance on the efficiency domain. We 
also seek comments on the alternatives we considered. Additionally, we 
seek comment on our proposed definitions.
(b) Calculation of Points
    As described in section III.C.5.b. of this proposed rule, we 
propose that performance on the efficiency domain would be worth up to 
20 points of 100 maximum points. As indicated in section III.C.5.c(2) 
of this proposed rule, the efficiency domain is weighted lower than the 
achievement domain but equal to the quality domain to ensure 
performance measurement is primarily

[[Page 43559]]

focused on increasing number of kidney transplants, while still 
incentivizing efficiency and quality. Within the efficiency domain, we 
propose that the OPTN organ offer acceptance rate ratio would account 
for the entirety of the 20 allocated points in that domain.
    We propose applying a two-scoring system to award up to 20 points 
to the IOTA participant based on its performance on the OPTN organ 
offer acceptance rate ratio. Under this two-scoring system, we would 
determine two separate scores for an IOTA participant: an ``achievement 
score'' reflecting its current level of performance, and an 
``improvement score'' reflecting changes in its performance over time. 
We propose that the IOTA participant would be awarded points equal to 
the higher of the two scores, up to a maximum of 20 points. We believe 
that this approach would recognize both high achievement among high 
performing IOTA participants as well as IOTA participants that make 
marked improvement in their performance. We believe that average or 
low-performing IOTA participants would likely require multiple years of 
transformation to catch up with those who have a high organ offer 
acceptance rate ratio.
    For achievement scoring, we propose that points earned would be 
based on the IOTA participants' performance on the organ offer 
acceptance rate ratio ranked against a national target, inclusive of 
all eligible kidney transplant hospitals, both those selected and not 
selected as IOTA participants. Currently, there is a large disparity in 
organ offer acceptance ratio performance. As previously noted, a 2020 
national registry study found that the probability of receiving a 
deceased donor kidney transplant within 3 years of waiting list 
placement varied 16-fold between different kidney transplant hospitals 
across the U.S.\220\ Large variations were still present between kidney 
transplant hospitals that utilized the same OPO.\221\ The probability 
of transplant was significantly associated with transplant hospitals' 
offer acceptance rates.\222\
---------------------------------------------------------------------------

    \220\ King, K.L., Husain, S.A., Schold, J.D., Patzer, R.E., 
Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., Pastan, S.O., & 
Mohan, S. (2020). Major Variation across Local Transplant Centers in 
Probability of Kidney Transplant for Wait-Listed Patients. Journal 
of the American Society of Nephrology, 31(12), 2900-2911. https://doi.org/10.1681/ASN.2020030335.
    \221\ King, K.L., Husain, S.A., Schold, J.D., Patzer, R.E., 
Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., Pastan, S.O., & 
Mohan, S. (2020). Major Variation across Local Transplant Centers in 
Probability of Kidney Transplant for Wait-Listed Patients. Journal 
of the American Society of Nephrology, 31(12), 2900-2911. https://doi.org/10.1681/ASN.2020030335.
    \222\ Ibid.
---------------------------------------------------------------------------

    We propose that achievement scoring points be awarded based on the 
national quintiles, as outlined in Table 6. Utilizing quintiles aligns 
with the calculation of the upside and downside risk payments in 
relation to the final performance score, as detailed in section 
III.C.6.c.(2). of this proposed rule, where average performance yields 
half the number of points. The scoring is normalized, meaning an 
average performing IOTA participant earns 10 points out of 20, 50 
percent of the total possible points. We recognize that there is an 
upper limit to the benefits of efficiency, and quintiles combine the 
highest 20 percent of performers in a point band. Due to the current 
disparity among kidney transplant hospitals on this metric, we do not 
expect every IOTA participant to reach top-level performance.
    We propose the following Organ Offer Acceptance Rate Achievement 
point allocation for IOTA participants, as illustrated in Table 6:
     IOTA participants in the 80th percentile and above, 20 
points.
     IOTA participants in the 60th to below the 80th percentile 
of performers, 15 points.
     IOTA participants in the 40th to the 60th percentile of 
performers, 10 points.
     IOTA participants in the 20th to below the 40th percentile 
of performers, 6 points.
     IOTA participants who are below the 20th percentile of 
performers, 0 points.
[GRAPHIC] [TIFF OMITTED] TP17MY24.006

    We considered the approach used by the MPSC, that would yield 
maximum points if transplant hospitals have at least a .35 organ offer 
acceptance rate ratio. However, we do not believe that this approach 
fits with the IOTA Model's goals. MPSC metrics are more focused on 
highlighting and improving performance for the lowest performers, 
whereas the model seeks to improve performance across the board, not 
just avoid poor performance.
    For improvement scoring, we propose that points earned would be 
based on the IOTA participants' performance on organ offer acceptance 
rate ratio during a PY relative to their performance during the third 
baseline year for the PY that is being measured. We propose to use the 
same baseline year definition used for participant eligibility, as 
described in section III.C.3 of this proposed rule, including the 
rationale for doing so. We separately propose to calculate an 
``improvement benchmark rate,'' defined as 120 percent of the IOTA 
participants' performance on the organ offer acceptance rate ratio 
during the third baseline year for each PY. We would award points by 
comparing the IOTA participant's organ offer acceptance rate ratio 
during the PY to the IOTA participant's improvement benchmark rate to 
determine the improvement scoring points earned. Specifically:
     IOTA participants whose organ offer acceptance rate ratio 
during a PY

[[Page 43560]]

is at or above the improvement benchmark rate would receive 12 points.
     IOTA participants whose organ offer acceptance rate ratio 
during a PY is at or below the organ offer acceptance rate ratio during 
the third baseline year for that respective PY would receive no points.
     IOTA participants whose organ offer acceptance rate ratio 
during a PY is greater than the organ offer acceptance rate ratio 
during the third baseline year for that respective PY, but less than 
the improvement benchmark rate, would earn a maximum of 12 points in 
accordance with equation 1 to paragraph (c)(1)(ii)(B)(1) of Sec.  
512.426.
    We propose using equation 1 to paragraph (c)(1)(ii)(B)(1) of Sec.  
512.426 to mirror the methodology used in the Hospital Value Based 
Purchasing (VBP) Program, with the only modification being the number 
of points available for this metric. Equation 3 would also allow for a 
maximum of 12 points to be earned by IOTA participants whose organ 
offer acceptance rate ratio during the PY is greater than the baseline 
year organ offer acceptance rate ratio but less than the improvement 
benchmark rate. We did not want the improvement score to be worth more 
than, or equal to, the achievement score, as proposed for the organ 
offer acceptance rate ratio performance scoring, so as to reserve the 
highest number of points (15 points) for top performers in the metric.
    Once both the achievement score and the improvement score are 
calculated, we propose comparing the two scores and applying the higher 
of the two values as the performance score or points earned (of 20 
possible points) for the organ offer acceptance rate ratio metric 
within the efficiency domain.
    We considered setting the improvement benchmark rate to be 200 
percent of the IOTA participant's third baseline year for a given PY to 
measure performance on the organ offer acceptance rate ratio. The 
scoring structure would be the same, with 12 or 0 points to be awarded 
depending on whether the benchmark is met. However, we believed this 
would be too strict and risk penalizing already high-achieving IOTA 
participants.
    We considered simplifying the performance scoring for the organ 
offer acceptance rate ratio metric within the efficiency domain by only 
awarding performance points based on the proposed achievement scoring 
methodology, rather than also calculating an improvement score for the 
IOTA participant and comparing the scores. However, given the variation 
that is present amongst kidney transplant hospitals, we believed it 
might be difficult for some IOTA participants to achieve top tier 
points for the first two model PYs. Thus, incorporating an improvement 
scoring method would ensure that IOTA participants are still rewarded 
for improvements made towards the efficiency domain goal.
    We considered using the scoring method proposed for the post-
transplant outcomes metric within the quality domain, as described in 
section III.C.5.e.(1).(b). of this proposed rule, as it would award 
full points if the hazard ratio or confidence interval of the metric 
includes the number one or higher. We believe this scoring method would 
honor the intent of the organ offer acceptance rate ratio metric, which 
is to determine if an IOTA participant is accepting more organs than 
expected. However, given the variation in performance on this metric 
across all kidney transplant hospitals, we believe improvement 
opportunities exist in this metric. We also believe that our proposed 
approach rewards both achievement and improvements and is a more 
rigorous scoring methodology.
    We considered a continuous scoring range from zero to 15, where 
IOTA participants may earn a score of any point value instead of bands. 
We believe a continuous scoring range could provide more flexibility 
for IOTA participants and greater variety of scores. However, we 
believe grading using bands provides a more favorable scoring system 
for IOTA participants by grouping performance. We also recognize there 
is diminishing marginal efficiency for higher and higher organ offer 
acceptance rate ratios.
    We considered using the lower and upper bounds of the offer 
acceptance odds ratio within a confidence interval, like we are 
proposing in the quality domain for post-transplant outcomes, as 
described in section III.C.5.e.(1).(b). of this proposed rule. However, 
the organ offer acceptance rate ratio metric, unlike post-transplant 
outcomes, has wider disparity in performance than in post-transplant 
outcomes. We believe that there is a clear benefit to patients and the 
transplantation ecosystem overall by continuing to increase performance 
on this metric and promoting better performance than the national 
average. Under this alternative, IOTA participants would be evaluated 
based on whether the lower bound, acceptance ratio, and upper bound all 
crossed 1. Doing so would indicate the IOTA participant's true offer 
acceptance ratio with 95 percent probability. We are not proposing this 
approach, however, as our analyses using SRTR data indicate that the 
majority of kidney transplant hospitals had either all three bounds 
cross 1 or all three never cross 1. Thus, scoring would largely not 
have differed from utilizing the offer acceptance ratio alone.
    Finally, we also considered stratifying offer acceptance by KDRI 
status, with different score targets based on KDRI status ranges, such 
as KDRI of less than 1.05, between 1.05 and 1.75, and more than 1.75. 
We believe this scoring method may potentially prevent IOTA 
participants from narrowing their criteria to only receive selected 
offers. However, we believe that it is already risk adjusted for organ 
status inherently in the measure because only organs that are 
ultimately transplanted are counted in the denominator.
    We seek comment on our proposed organ offer acceptance rate ratio 
performance scoring methodology for purposes of assessing efficiency 
domain performance for each IOTA participant, including on the 
achievement and improvement score calculation and point allocation 
method. We also seek comments on alternatives considered.
e. Quality Domain
    We propose to define ``quality domain'' as the performance 
assessment category in which CMS assesses the IOTA participant's 
performance using a performance measure and quality measure set focused 
on improving the quality of transplant care, as described in section 
III.C.5.e. of this proposed rule. We propose that performance on the 
quality domain would be worth up to 20 points out of the proposed 100 
points. The quality domain is focused on monitoring post-transplant 
care and quality of life for IOTA transplant patients.
    Our goal for the quality domain within the IOTA Model is to achieve 
acceptable post-transplant outcomes while incentivizing increased 
kidney transplant volume. We believe that transplant hospital 
accountability for patient-centricity and clinical outcomes continues 
post-transplantation. While transplant outcomes have historically 
received the most attention, often at the exclusion of other factors, 
we seek to encourage a better balance in the system to offer the 
benefits of transplant to more patients. Therefore, we are proposing to 
include one post-transplant outcome measure, as described in section 
III.C.5.e.(1). of this proposed rule, and a quality measure set that 
includes two patient-reported outcome-based performance measures (PRO-
PM) and one process measure, as described in section III.C.5.e.(2). of 
this proposed rule.

[[Page 43561]]

(1) Post-Transplant Outcomes
    We propose using an unadjusted rolling ``composite graft survival 
rate,'' defined as the total number of functioning grafts relative to 
the total number of adult kidney transplants performed, as described in 
section III.C.5.e.(1).(a). of this proposed rule, to assess IOTA 
participant performance on post-transplant outcomes. In this measure, 
the numerator (observed functioning grafts) and denominator (number of 
kidney transplants completed) would increase each PY of the IOTA Model 
to include a cumulative total.
    Over the past few decades, advances in immunosuppressive therapies, 
surgical techniques, and organ preservation methods have resulted in 
significant improvements in kidney transplantation outcomes.\223\ 
According to the OPTN, the overall 1-year survival rate for kidney 
transplantation recipients in the United States is over 90 percent, and 
the 5-year survival rate is around 75 percent. However, even with the 
advances that have been made to improve kidney outcomes, the success of 
kidney transplantation is still dependent upon factors such as the age 
and health of the donor and recipient, the presence of comorbidities 
(for example, diabetes), and the effectiveness of the immunosuppressive 
regimen. Kidney transplant outcomes can also be affected by possible 
post-transplant complications, including infection, cardiovascular 
disease, and kidney failure.\224\
---------------------------------------------------------------------------

    \223\ Stewart, D.E., Garcia, V.C., Rosendale, J.D., Klassen, 
D.K., & Carrico, B.J. (2017). Diagnosing the Decades-Long Rise in 
the Deceased Donor Kidney Discard Rate in the United States. 
Transplantation, 101(3), 575-587. https://doi.org/10.1097/tp0000000000001539;. Vinson, A., Kiberd, B.A., & Karthik Tennankore. 
(2021). In Search of a Better Outcome: Opting Into the Live Donor 
Paired Kidney Exchange Program. 8, 205435812110174-205435812110174. 
https://doi.org/10.1177/20543581211017412; Shepherd, S., & Formica, 
R. N. (2021). Improving Transplant Program Performance Monitoring. 
8(4), 293-300. https://doi.org/10.1007/s40472-021-00344-z.
    \224\ Gioco, R., Sanfilippo, C., Veroux, P., Corona, D., 
Privitera, F., Brolese, A., Ciarleglio, F., Volpicelli, A., & 
Veroux, M. (2021). Abdominal wall complications after kidney 
transplantation: A clinical review. Clinical Transplantation, 
35(12), e14506. https://doi.org/10.1111/ctr.14506; Wei, H., Guan, 
Z., Zhao, J., Zhang, W., Shi, H., Wang, W., Wang, J., Xiao, X., Niu, 
Y., & Shi, B. (2016). Physical Symptoms and Associated Factors in 
Chinese Renal Transplant Recipients. Transplantation Proceedings, 
48(8), 2644-2649. https://doi.org/10.1016/j.transproceed.2016.06.052; Mehrabi, A., Fonouni, H., Wente, M., 
Sadeghi, M., Eisenbach, C., Encke, J., Schmied, B.M., Libicher, M., 
Zeier, M., Weitz, J., Buchler, M.W., & Schmidt, J. (2006). Wound 
complications following kidney and liver transplantation. Clinical 
Transplantation, 20(s17), 97-110. https://doi.org/10.1111/j.1399-0012.2006.00608.x.
---------------------------------------------------------------------------

    More recently, CMS received feedback from transplant hospitals, 
patient advocacy groups, and transplant societies, including on the 
recent rule making (``Medicare and Medicaid Programs; Regulatory 
Provisions To Promote Program Efficiency, Transparency, and Burden 
Reduction,'' 83 FR 47686), that the 1-year measure was causing 
transplant centers to be risk averse about the patients and organs they 
would transplant while being simultaneously topped out (83 FR 
47706).\225\ Notably, even the lowest ranked programs, as measured by 
the SRTR, achieved a result of 90 percent of transplanted patients have 
a functioning graft at one year.\226\
---------------------------------------------------------------------------

    \225\ Medicare and Medicaid Programs; Regulatory Provisions To 
Promote Program Efficiency, Transparency, and Burden Reduction 
(September, 20, 2018) https://www.federalregister.gov/documents/2018/09/20/2018-19599/medicare-and-medicaid-programs-regulatory-provisions-to-promote-program-efficiency-transparency-and.
    \226\ Scientific Registry of Transplant Recipients. Request for 
Information. Requested on 05/02/2023. https://www.srtr.org./.
---------------------------------------------------------------------------

    To safeguard patient outcomes under the IOTA Model, we are 
proposing to include this measure as a checkpoint. Because there is 
significant variation in post-transplant outcomes across kidney 
transplant hospitals, we believe the IOTA Model should promote 
improvement in outcomes for the benefit of attributed patients. We also 
believe that this measure would build upon, and complement, existing 
OPTN and SRTR measures to the maximum extent possible. Additionally, we 
believe that this approach could be applied with minimal adaptation to 
other organs were they to be added to the model through future 
rulemaking. Furthermore, we believe that this measure would enhance 
patient understanding of clinically important post-transplant outcomes 
beyond existing 90-day, 1-year and 3-year post transplant outcomes.
    We considered measuring post-transplant outcomes using SRTR's 
methodology at 90 days,\227\ and constructing 5-year and 10-year post-
transplant measures. However, we did not select these measures because 
post-transplant outcomes are already measured at 90-days by SRTR. 
Additionally, because the IOTA Model as proposed spans only 6 years, we 
did not believe we could appropriately measure post-transplant outcomes 
at 5 or 10 years.
---------------------------------------------------------------------------

    \227\Mpsc-enhance-transplant-program-performance-monitoring-
system_srtr-metrics.pdf (n.d.). Retrieved December 28, 2022, from 
https://optn.transplant.hrsa.gov/media/qfuj3osi/mpsc-enhance-transplant-program-performance-monitoring-system_srtr-metrics.pdf.
---------------------------------------------------------------------------

    We considered constructing an ongoing post-transplant outcome 
measure that would continuously evaluate post-transplant outcomes at 1-
year throughout the model performance period of the IOTA Model. In this 
measure the numerator (observed graft failures) and denominator (number 
of transplants completed) would increase each PY of the model to a 
cumulative total. For example, in PY 1 of the model an IOTA participant 
could have five 1-year observed graft failures and complete 20 
transplants, resulting in a graft failure rate of 0.25. In PY 2 of the 
model, the same IOTA participant could have eight 1-year observed graft 
failures and complete 30 transplants. To calculate the IOTA 
participant's graft failure rate for PY 2 of the model, we would divide 
the cumulative total of 13 1-year observed graft failures by the 
cumulative total of 50 completed transplants. However, we believed it 
was important to measure post-transplant outcomes in terms of graft 
survival rather than in terms of graft failure. We acknowledge that for 
the purposes of measuring graft survival using OPTN data, use of either 
concept would generate the same outcome measurement because OPTN data 
identify graft status as either functioning or failed. However, we aim 
to convey the importance of ongoing management to preserve the health 
of the transplanted graft and the health and quality of life of the 
attributed patients.
    We considered constructing a continuous patient survival measure 
that would evaluate patient survival throughout the entirety of the 
IOTA Model. Similar to the considered measure mentioned in the previous 
paragraph, the numerator (number of patients alive) and denominator 
(number of received kidney organ offers) would increase each PY of the 
model to a cumulative total. For the denominator, we considered only 
including organ offers where the sequence number was less than 100 or 
less than 50. In other words, under that rationale we would only 
include offers that came within a certain point of time that could have 
potentially benefited the patient or should not have been turned down. 
We believe that this type of measure would not disincentivize 
waitlisting and could potentially increase equity within this 
population. Additionally, we believe that this type of measure would 
indirectly encourage living donor transplants because those would only 
hit the numerator (number of people alive) but not the denominator 
(number of kidney organ offers received). However, we believe this 
measure

[[Page 43562]]

would be somewhat duplicative of other parts of the model where we are 
already evaluating organ offer acceptance. We also chose not to propose 
this measure due to logistical concerns, and believed it could be 
difficult to determine how many people were offered a specific organ 
and determining what an appropriate sequence number cutoff should be.
    We considered measuring estimated glomerular filtration rate (eGFR) 
at the 1-year anniversary of the date of transplant. Glomerular 
filtration rate (GFR) is a way to assess renal function, and eGFR is 
the test used to assess renal function in primary clinical care.\228\ 
Despite the fact that studies indicate eGFR's potential as a reliable 
predictor of long-term post-transplant prognosis, our goal is to adopt 
a measure that resonates more with the transplant community's 
evaluation of post-transplant outcomes.\229\ We recognize that the 
equation for calculating eGFR was revised in 2021 to not include race, 
but we still have some concerns over the potential for bias and 
inaccurate results and the limitations that still exist with the 
updated equation and did not feel it was appropriate to propose.\230\
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    \228\ Mayne, T.J., Nordyke, R.J., Schold, J.D., Weir, M.R., & 
Mohan, S. (2021). Defining a minimal clinically meaningful 
difference in 12-month estimated glomerular filtration rate for 
clinical trials in deceased donor kidney transplantation. Clinical 
Transplantation, 35(7), e14326. https://doi.org/10.1111/ctr.14326.
    \229\ Ibid; Wu, J., Li, H., Huang, H., Wang, R., Wang, Y., He, 
Q., & Chen, J. (2010). Slope of changes in renal function in the 
first year post-transplantation and one-yr estimated glomerular 
filtration rate together predict long-term renal allograft survival. 
Clinical Transplantation, 24(6), 862-868. https://doi.org/10.1111/j.1399-0012.2009.01186.x; Schold, J.D., Nordyke, R.J., Wu, Z., 
Corvino, F., Wang, W., & Mohan, S. (2022). Clinical events and renal 
function in the first year predict long-term kidney transplant 
survival. Kidney360, 10.34067/KID.0007342021. https://doi.org/10.34067/kid.0007342021; Hariharan, S., Mcbride, M.A., Cherikh, 
W.S., Tolleris, C.B., Bresnahan, B.A., & Johnson, C.P. (2002). Post-
transplant renal function in the first year predicts long-term 
kidney transplant survival. Kidney International, 62(1), 311-318. 
https://doi.org/10.1046/j.1523-1755.2002.00424.x.
    \230\ Majerol, M., & Hughes, D.L. (2022, July 5). CMS Innovation 
Center Tackles Implicit Bias. Health Affairs. Retrieved January 16, 
2024, from https://www.healthaffairs.org/content/forefront/cms-innovation-center-tackles-implicit-bias.
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    We considered constructing several hospital-based post-transplant 
outcome measures such as those that measure: the number of days spent 
out of the hospital post-transplant, how many days spent at home post-
transplant before returning to work, and number of hospital 
readmissions post-transplant. However, we do not want to penalize the 
use of moderate-to-high KDPI kidneys, as we recognize that utilizing 
these organs carries an increased risk of transplant recipient 
hospitalizations. Additionally, we had concerns over how we would 
assess and measure this type of metric.
    We considered proposing a phased-in approach to measuring post-
transplant outcomes, in which no post-transplant outcome metrics would 
be included until PY 3 of the model. In this alternative methodology, 
the quality domain for the first two PYs would only include our 
proposed quality measure set, as described in section III.C.5.e.(2). of 
this proposed rule. Starting PY 3 of the model, IOTA participants would 
be evaluated on two post-transplant outcome measures (SRTR's 1-year 
post-transplant outcome conditional on 90-day survival measure and 3-
year post-transplant outcome measure) in addition to our proposed 
quality measure set. This approach incorporates a time delay, allowing 
us to assess the post-transplant outcomes of IOTA participants using 
SRTR's measures. Because we believed it was critical to include a post-
transplant measure from the onset of the model to check for unintended 
consequences throughout the entirety of the model performance period, 
we did not believe this alternative was appropriate to propose.
    We also considered using SRTR's new ``1-year post-transplant 
outcome conditional on 90-day graft survival'' measure and including a 
3-year post-transplant outcome measure, such as the one currently used 
by SRTR. We also considered constructing our own 3-year post-transplant 
outcome measure conditional on 1-year survival. However we chose not to 
propose SRTR's conditional 1-year or 3-year post-transplant outcome 
measures or our own measure for the following reasons: (1) because 
SRTR's conditional 1-year metric has a 2.5 year lookback period, it 
would require us to evaluate IOTA participants on post-transplant 
outcomes prior to starting the model for at least the first two PYs; 
(2) because SRTR does not currently have a 3-year conditional post-
transplant outcome measure, we would not be in alignment with SRTR if 
we constructed our own; (3) including SRTR's 3-year post-transplant 
outcome measure would include time outside of the model for at least 
the first three PYs and we want to evaluate IOTA participants based on 
their performance within the model; and (4) we recognize there may be 
some logistical issues and difficulty in measuring performance in that 
time. We may consider incorporating a 3-year post-transplant outcome 
measure into the model in the future, through rulemaking.
    We seek public comment on our proposal to evaluate IOTA 
participants on post-transplant outcomes using our new composite graft 
survival rate metric, as well as on the alternatives we considered. We 
are also interested in public comment on how we may be able to use OPTN 
data to characterize different clinical manifestations of graft 
survival, as we understand that not all surviving grafts are clinically 
equivalent or have the same impact on the patient and graft health. We 
would further be interested to hear from the public on which factors 
involved in graft survival are modifiable by the care team.
(a) Calculation of Metric
    We propose that for each model PY, CMS would calculate a composite 
graft survival rate for each IOTA participant, as defined in section 
III.C.5.e.(1). of this proposed rule, to measure performance in the 
quality domain as described in section III.C.5.e. of this proposed 
rule.
    We propose to use our own unadjusted composite graft survival rate 
equation to evaluate post-transplant outcomes. We propose to calculate 
the composite graft survival rate by taking the total number of 
functioning grafts an IOTA participant has and dividing that by the 
total number of kidney transplants furnished to patients 18 years of 
age or older at the time of the transplant in PY 1 and all subsequent 
PYs as specified in Equation 1 to paragraph (b)(1) of Sec.  512.428 to 
evaluate post-transplant outcomes during the IOTA Model performance 
period.
    For example, if in PY 1 of the model, an IOTA participant had 20 
observed functioning grafts and furnished 25 kidney transplants to 
patients 18 years of age or older at the time of transplant, the 
composite graft survival rate for that IOTA participant would be 0.8 
(20 from PY 1 divided by 25 from PY 1). Continuing this example, for 
PY2 of the model if the same IOTA participant had 30 observed 
functioning grafts and furnished 35 kidney transplants to patients 18 
years of age or older at the time of transplant, and two functioning 
kidney grafts failed from PY 1, CMS would calculate its composite graft 
survival rate for PY 2 as follows. CMS would divide the cumulative 
total of 48 observed functioning grafts (30 from PY 2 + 20 from PY 1-2 
from PY 1) by the cumulative total of 60 completed kidney transplants 
(35 from PY 2 + 25 from PY 1), resulting in a composite graft survival 
rate of 0.8 (48 divided by 60).
    In the proposed equation, the numerator (number of functioning 
grafts) is defined as the total number of living adult kidney 
transplant patients with a functioning graft. The numerator,

[[Page 43563]]

functioning grafts, would exclude grafts that have failed, as defined 
by SRTR. SRTR counts a graft as failed when follow-up information 
indicates that one of the following occurred before the reporting time 
point: (1) graft failure (except for heart and liver, when re-
transplant dates are used instead); (2) re-transplant (for all 
transplants except heart-lung and lung); or 3) death.\231\ OPTN follow-
up forms are used to identify graft failure and re-transplant 
dates.\232\ We also propose to use OPTN adult kidney transplant 
recipient follow-up forms \233\ to identify graft failure and re-
transplant dates for all transplant furnished to kidney transplant 
patients 18 years of age or older at the time of the transplant. In the 
proposed equation, we note that the numerator and denominator would not 
be limited to the attributed IOTA transplant patients. By this, we mean 
that it could include IOTA transplant patients who have been de-
attributed from an IOTA participant due to transplant failure. We 
believe that IOTA participants could improve on this metric by working 
with IOTA collaborators to coordinate post-transplant care.
---------------------------------------------------------------------------

    \231\ Technical Methods for the Program-Specific Reports. 
(n.d.). Www.srtr.org. Retrieved December 3, 2022, from https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/; OPTN. (2022). OPTN Enhanced Transplant Program 
Performance Metrics. https://optn.transplant.hrsa.gov/media/r5lmmgcl/mpsc_performancemetrics_3242022b.pdf.
    \232\ Technical Methods for the Program-Specific Reports. 
(n.d.). Www.srtr.org. Retrieved December 3, 2022, from https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/ reports/.
    \233\ https://unos.org/wp-content/uploads/Adult-TRF-Kidney.pdf.
---------------------------------------------------------------------------

    We considered incorporating a risk adjustment methodology to our 
proposed composite graft survival equation, such as the one used by 
SRTR for 1-year post-transplant outcomes conditional on 90-day survival 
or constructing our own. While we recognize that risk adjustment 
methodologies may help account for patient and donor traits, we could 
not find a risk adjustment approach that has consensus agreement within 
the kidney transplant community. We also believe that our proposed 
measure is inherently risk adjusted as it only counts organs that are 
ultimately transplanted to patients 18 years of age or older by a 
kidney transplant hospital.
    We invite public comment on our proposed methodology to calculate 
post-transplant outcomes in the IOTA Model, and on alternatives 
considered. Although we are proposing an unadjusted composite graft 
survival rate to measure post-transplant outcomes, we are interested in 
comments on whether risk risk-adjustments are necessary, and which 
ones, such as donor demographic characteristics (race, gender, age, 
disease condition, geographic location), would be significant and 
clinically appropriate in the context of our proposed approach.
(b) Calculation of Points
    As described in section III.C.5.e. of this proposed rule, 
performance on the quality domain would be worth up to 20 points. 
Within the quality domain, we propose that the composite graft survival 
rate would account for 10 of the 20 allocated points. We propose that 
the points earned would be based on the IOTA participants' performance 
on the composite graft survival rate metric ranked against a national 
target, inclusive of all eligible kidney transplant hospitals, both 
those selected and not selected as IOTA participants. We believe that 
using percentiles would create even buckets of scores among the 
continuum of IOTA participants.
    We propose that points would be awarded based on the national 
quintiles, as outlined in Table 7, such that IOTA participants that 
perform--
     At or above the 80th percentile would earn 10 points;
     In the 60th percentile to below the 80th percentile would 
earn 8 points;
     In the 40th to below the 60th percentile would earn 5 
points;
     In the 20th percentile to below the 40th percentile would 
earn 3 points; and
     Below the 20th percentile would receive no points for the 
composite graft survival rate.
[GRAPHIC] [TIFF OMITTED] TP17MY24.007

    Utilizing quintiles aligns with the calculation of the upside and 
downside risk payments in relation to the final performance score as 
detailed in section III.C.6.c.(2). of this proposed rule, where average 
performance yields half the number of points. The scoring is 
normalized, meaning an average performing IOTA participant earns 5 
points out of 10, or about 50 percent of possible points. We recognize 
that there is an upper limit to the benefits of efficiency, and 
quintiles combine the highest 20 percent of performers in a point band. 
Due to the current disparity among kidney transplant hospitals, we do 
not expect every IOTA participant to reach top-level performance on 
this metric.
    We considered a strategy similar to the proposed organ offer 
acceptance methodology which would apply a two-scoring system in which 
we would determine an achievement score and improvement score and award 
the point equivalent to the higher value between the two scores. We 
also considered proposing just an improvement score, in which we would 
evaluate IOTA participants' performance on composite graft survival 
during a PY relative to their performance the previous CY. We 
considered both approaches because we recognize that if an IOTA 
participant does not do well one year in our proposed methodology, that 
it may be difficult for it to improve during the model performance 
period. However, we chose not to propose either of these other 
methodologies (achievement and improvement or just improvement scoring) 
because we had concerns over

[[Page 43564]]

our ability to measure improvement year over year due to potentially 
small numbers.
    We seek public comment on the proposed point allocation and 
calculation methodology for post-transplant outcomes within the quality 
domain for the IOTA Model and alternatives considered.
(2) Quality Measure Set
    We propose to select and use quality measures to assess IOTA 
participant performance in the quality domain. Performance on the 
proposed IOTA Model quality measure set would be used to assess the 
performance of an IOTA participant on aspects of care that we believe 
contribute to a holistic and patient-centered journey to receiving a 
kidney transplant.
    We propose the following three measures for inclusion in the IOTA 
Model quality measure set: (1) CollaboRATE Shared Decision-Making Score 
(CBE ID: 3327), (2) Colorectal Cancer Screening (COL) (CBE ID: 0034), 
and (3) the 3-Item Care Transition Measure (CTM-3) (CBE ID: 
0228).234 235 236 The quality measures that we are proposing 
share common features. We are proposing measures that have been or are 
currently endorsed by the CMS Consensus-Entity (CBE) through the CMS 
Consensus-Based Process. This ensures that the measures proposed have 
been assessed against established evaluation criteria of importance, 
acceptability of measure properties, feasibility, usability, and 
competing measures.\237\ Our proposed measure set is patient-centered, 
reflecting areas that we have heard from patients are important and for 
which there is significant variation in performance among transplant 
hospitals. We are proposing measures that would incentivize 
improvements in care that we would otherwise not expect to improve 
based on the financial incentives in the model alone. We are also 
proposing a measure set that would allow us to make a comprehensive 
assessment of post-transplant outcomes. The composite graft survival 
rate that we are proposing in section III.C.5.e.(1). of this proposed 
rule would provide an essential, albeit limited, assessment of the 
success of a kidney transplant. Finally, we are proposing measures that 
we believe would incentivize improvement in aspects of post-transplant 
care that are important to patients and modifiable by IOTA 
participants.
---------------------------------------------------------------------------

    \234\ collaboRATE. (2019). Glyn Elwyn. http://www.glynelwyn.com/collaborate.html.
    \235\ Colorectal Cancer Screening--NCQA. (2018). NCQA. https://www.ncqa.org/hedis/measures/colorectal-cancer-screening/ https://www.ncqa.org/hedis/measures/colorectal-cancer-screening/.
    \236\ THE NATIONAL QUALITY FORUM Specifications for the Three-
Item Care Transition Measure-CTM-3. (n.d.). Retrieved May 28, 2023, 
from https://mhdo.maine.gov/_pdf/NQF_CTM_3_%20Specs_FINAL.pdf.
    \237\ Supplemental Material to the CMS Measures Management 
System (MMS) Hub CMS Consensus-Based Entity (CBE) Endorsement and 
Maintenance. (2022). https://www.cms.gov/files/document/blueprint-nqf-endorsement-maintenance.pdf.
---------------------------------------------------------------------------

    On March 2, 2023, Jacobs et al. published Aligning Quality Measures 
across CMS--The Universal Foundation, which describes CMS leadership's 
vision for a set of foundational quality measures known as the 
Universal Foundation. This measure set would be used by as many CMS 
value-based and quality programs as possible, with other measures added 
based on the population or healthcare setting.\238\ CMS selected 
measures for the Universal Foundation that are meaningful to a broad 
population, reduce burden by aligning measures, advance equity, support 
automatic and digital reporting, and have minimal unintended 
consequences.\239\
---------------------------------------------------------------------------

    \238\ Jacobs, D. B., Schreiber, M., Seshamani, M., Tsai, D., 
Fowler, E., & Fleisher, L.A. (2023). Aligning quality measures 
across CMS--the Universal Foundation. New England Journal of 
Medicine, 388(9), 776-779. https://doi.org/10.1056/nejmp2215539.
    \239\ Jacobs, D.B., Schreiber, M., Seshamani, M., Tsai, D., 
Fowler, E., & Fleisher, L.A. (2023). Aligning quality measures 
across CMS--the Universal Foundation. New England Journal of 
Medicine, 388(9), 776-779. https://doi.org/10.1056/nejmp2215539.
---------------------------------------------------------------------------

    We considered only including two measures in the initial quality 
measure set and pre-measure development because we were concerned about 
the potential added reporting burden placed on IOTA participants. 
However, we chose to propose three measures and pre-measure development 
because we want to use them to incentivize and improve patient care. We 
seek additional feedback on which of the proposed measures have the 
highest potential to impact changes in behavior, while minimizing 
provider burden.
    We also considered only including COL in the quality measure set 
and allotting this measure 4 points, with the remaining 16 points 
allotted to the composite graft survival rate. It is worth noting that 
if we choose fewer measures, then we propose allocating the points 
accordingly within the remaining measures.
    We considered several alternative measures for the quality domain 
performance assessment. We considered the Hospital Consumer Assessment 
of Healthcare Providers and Systems (HCAHPS) survey because hospitals 
are already required to report that survey in the Hospital VBP Program, 
thereby reducing or limiting burden to IOTA participants burden since 
it is already in use. We are not proposing the HCAHPS measure for the 
IOTA Model because HCAHPS data is based on survey results from a random 
sample of adult patients across medical conditions. We believe that the 
HCAHPS would present sample size issues for purposes of calculation.
    We considered the Gains in Patient Activation Measure (PAM[supreg]) 
(CBE ID: 2483). The PAM[supreg] measure is being used in the voluntary 
KCC Model and was included on the 2022 Measures Under Consideration 
(MUC) List for the ESRD Quality Incentive Program (QIP) and MIPS.\240\ 
We considered whether the PAM[supreg] Measure could encourage IOTA 
participants and IOTA Collaborators, as defined in section III.C.11.d. 
of this proposed rule, to activate IOTA waitlist patients to work in 
collaboration with IOTA participants to complete requirements to 
maintain active waitlist status; however, we were unable to locate any 
peer-reviewed literature to support this hypothesis.
---------------------------------------------------------------------------

    \240\ Pre-Rulemaking [verbar] The Measures Management System. 
(n.d.). Mmshub.cms.gov. Retrieved May 12, 2023, from https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/overview.
---------------------------------------------------------------------------

    We also considered the Depression Remission at 12 Months measure 
(CBE ID: 0710e). Studies have shown that depression and anxiety are 
common amongst people on dialysis and suggested that incorporating 
patient reported outcome measures (PROs) that focus on depression can 
improve health-related quality of life in patients with ESRD.\241\ One 
study found that, at the time of kidney evaluation, over 85 percent of 
patients exhibited at least minimal depressive symptoms and that 
patients with depressive symptoms were less likely to gain access to 
the waitlist.\242\ Although the waitlist offers

[[Page 43565]]

some hope to patients, being waitlisted for a kidney transplant is also 
psychologically distressing, with patients reporting disillusionment, 
moral distress, unmet expectations, increasing vulnerability, and 
deprivation.\243\ These factors are likely contributors to high rates 
of stress and anxiety observed among waitlisted patients.\244\ The 
conditions of participation (CoPs) for transplant hospitals require 
that prospective transplant candidates receive a psychosocial 
evaluation prior to placement on a waitlist (42 CFR part 482.90(a)(1)), 
if possible, and OPTN bylaws specify that transplant hospitals must 
include team members to coordinate a transplant candidate's 
psychosocial needs; however, neither the CoP nor the OPTN bylaws 
require specific assessment of, or intervention into, patients' 
behavioral health. The ESRD QIP measure set includes the Clinical 
Depression Screening and Follow-Up measure; however, performance on the 
measure requires only documentation that an attempt at screening and 
follow up was made.\245\ Additionally, this measure is already being 
used in the KCC Model.
---------------------------------------------------------------------------

    \241\ Feroze, U., Martin, D., Kalantar-Zadeh, K., Kim, J.C., 
Reina-Patton, A., & Kopple, J.D. (2012). Anxiety and depression in 
maintenance dialysis patients: Preliminary data of a cross-sectional 
study and brief literature review. Journal of Renal Nutrition, 
22(1), 207-210. https://doi.org/10.1053/j.jrn.2011.10.009; Mclaren, 
S., Jhamb, M., & Unruh, M. (2021). Using Patient-Reported Measures 
to Improve Outcomes in Kidney Disease. Blood Purification, 1-6. 
https://doi.org/10.1159/000515640; Cukor, D., Donahue, S., 
Tummalapalli, S.L., Bohmart, A., & Silberzweig, J. (2022). Anxiety, 
comorbid depression, and dialysis symptom burden. Clinical Journal 
of the American Society of Nephrology, 17(8), 1216-1217. https://doi.org/10.2215/cjn.01210122.
    \242\ Chen, X., Chu, N.M., Basyal, P.S., Vihokrut, W., Crews, 
D., Brennan, D.C., Andrews, S.R., Vannorsdall, T.D., Segev, D.L., & 
McAdams-DeMarco, M. A. (2022). Depressive symptoms at kidney 
transplant evaluation and access to the kidney transplant waitlist. 
Kidney International Reports, 7(6), 1306-1317. https://doi.org/10.1016/j.ekir.2022.03.008.
    \243\ Tong, A., Hanson, C.S., Chapman, J.R., Halleck, F., Budde, 
K., Josephson, M.A., & Craig, J.C. (2015). `suspended in a paradox'-
patient attitudes to wait-listing for Kidney Transplantation: 
Systematic review and thematic synthesis of qualitative studies. 
Transplant International, 28(7), 771-787. https://doi.org/10.1111/tri.12575.
    \244\ Ibid.
    \245\ CMS ESRD Measures Manual for the 2023 Performance Period. 
(2022). https://www.cms.gov/files/document/esrd-measures-manual-v81.pdf.
---------------------------------------------------------------------------

    While we understand the importance of including measures focused on 
depression, we believe that IOTA participants may have limited 
experience diagnosing and treating depression and may struggle to make 
referrals due to limited behavioral health providers. We also believe 
that this measure may be duplicative with other policies in this model 
that strive to improve the health and post-transplant outcomes of 
attributed patients. Additionally, based on the KCC Model experience, 
the Depression Remission measure is operationally complex due to the 
10-month reporting period and novel collection and reporting processes. 
We believe that IOTA participants would experience similar challenges 
due to the mandatory nature of the model and unfamiliarity with 
reporting quality measure data to the Innovation Center.
    We considered the Depression Remission at 12 Months measure (CBE 
ID: 0710e) because major depression is prevalent in the dialysis 
population and most kidney transplant recipients spend some time on a 
dialysis modality.\246\ Depression measures are included in the 
Universal Foundation because successfully treating depression can 
improve physical health outcomes, in addition to behavioral health 
outcomes.\247\ A depression measure would align with the behavioral 
health domain of Meaningful Measures 2.0. We considered a depression 
remission measure over a depression screening measure because we 
believed a depression remission measure would incentivize IOTA 
participants to work with the other clinicians and providers involved 
in the care of attributed patients to resolve or improve the depressive 
symptoms rather than only identifying them. Our review of the 
literature found that presence of behavioral health symptoms affected 
the ability of patients to get on the kidney transplant waitlist, but 
did not affect likelihood of receiving a kidney transplant.\248\ We are 
not proposing the Depression Remission at 12 Months Measure because we 
were unable to locate any publications that found depression remission 
affected access to a kidney transplant. We also chose not to propose 
this type of measure because the IOTA Model does not target pre-
waitlist patients for attribution to model participants. We also 
believe that IOTA participants may have limited experience in diagnosis 
and treating depression and may struggle to make referrals due to 
limited behavioral health providers. Additionally, behavioral health 
management is not under the purview of a kidney transplant hospital 
that might see a kidney transplant waitlist patient perhaps only a 
handful of times, but may be more appropriate for the patient's 
nephrologist or dialysis center.
---------------------------------------------------------------------------

    \246\ Cukor, D., Donahue, S., Tummalapalli, S.L., Bohmart, A., & 
Silberzweig, J. (2022). Anxiety, comorbid depression, and dialysis 
symptom burden. Clinical Journal of the American Society of 
Nephrology, 17(8), 1216-1217. https://doi.org/10.2215/cjn.01210122 
https://doi.org/10.2215/cjn.01210122.
    \247\ Jacobs, D.B., Schreiber, M., Seshamani, M., Tsai, D., 
Fowler, E., & Fleisher, L.A. (2023). Aligning quality measures 
across CMS--the Universal Foundation. New England Journal of 
Medicine, 388(9), 776-779. https://doi.org/10.1056/nejmp2215539.
    \248\ Szeifert, L., Bragg-Gresham, J.L., Thumma, J., Gillespie, 
B.W., Mucsi, I., Robinson, B.M., Pisoni, R.L., Disney, A., Combe, 
C., & Port, F.K. (2011). Psychosocial variables are associated with 
being wait-listed, but not with receiving a kidney transplant in the 
dialysis outcomes and Practice Patterns Study (dopps). Nephrology 
Dialysis Transplantation, 27(5), 2107-2113. https://doi.org/10.1093/ndt/gfr568; Chen, X., Chu, N.M., Basyal, P.S., Vihokrut, W., Crews, 
D., Brennan, D.C., Andrews, S.R., Vannorsdall, T.D., Segev, D.L., & 
McAdams-DeMarco, M.A. (2022). Depressive symptoms at kidney 
transplant evaluation and access to the kidney transplant waitlist. 
Kidney International Reports, 7(6), 1306-1317. https://doi.org/10.1016/j.ekir.2022.03.008.
---------------------------------------------------------------------------

    We seek comment on our proposed quality measure set that includes 
two PRO-PMs (CollaboRATE Shared Decision-Making Score and 3-Item Care 
Transition Measure) and one process measure (Colorectal Cancer 
Screening) for purposes of measuring performance in the quality domain. 
We also seek comment on alternative quality measures considered.
(a) Quality Measure Set Selection, Reporting and Changes
    As proposed in section III.C.5.e.(2). of this proposed rule, we are 
proposing that CMS select and use quality measures to assess IOTA 
participant performance in the quality domain. We propose that each PY, 
IOTA participants would be required to report quality measure data 
during survey and reporting windows to CMS in a form and manner, and at 
times, established by CMS. We also propose that, where applicable, IOTA 
participants would be required to administer any surveys or screenings 
relevant to the quality measures selected for inclusion in the IOTA 
Model to attributed patients. We propose to define ``survey and 
reporting windows'' as two distinct periods where IOTA participants 
would be required to administer a quality measure-related survey or 
screening to attributed patients or submit attributed patient responses 
to CMS pursuant to Sec.  512.48(b)(2)(ii). We propose that CMS would 
notify, in a form and manner as determined by CMS, IOTA participants of 
the survey and reporting window for applicable quality measures by the 
first day of each PY.
    We propose that CMS would use future rulemaking to make 
substantiative updates to the specifications of any of the quality 
measures in the IOTA Model. Additionally, we propose that the quality 
measures finalized for inclusion in the IOTA Model would remain in the 
quality measure set unless CMS, through future rulemaking, removed or 
replaced them.
    We propose that CMS could remove or replace a quality measure based 
on one of the following factors:
     A quality measure does not align with current clinical 
guidelines or practice.
     Performance on a quality measure among IOTA participants 
is so high and unvarying that meaningful distinctions and improvement 
in performance can no longer be made (``topped out'' measure), as 
defined in 42 CFR 412.140(g)(3)(i)(A).

[[Page 43566]]

     Performance or improvement on a quality measure does not 
result in better patient outcomes.
     The availability of a more broadly applicable quality 
measure (across settings or populations) or the availability of a 
quality measure that is more proximal in time to desired patient 
outcomes for the particular topic.
     The availability of a quality measure that is more 
strongly associated with desired patient outcomes for the particular 
topic.
     Collection or public reporting of a quality measure leads 
to negative unintended consequences other than patient harm.
     It is not feasible to implement the quality measure 
specifications.
     The costs associated with a quality measure outweigh the 
benefit of its continued use in the IOTA Model.
    We propose that CMS would assess the benefits of removing or 
replacing a quality measure from the IOTA Model on a case-by-case 
basis. We propose that CMS would use the future rulemaking process to 
add, remove, suspend, or replace quality measures in the IOTA Model to 
allow for public comment, unless a quality measure raises specific 
safety concerns. We propose that if CMS determines that the continued 
requirement for IOTA participants to submit data on a quality measure 
raises specific patient safety concerns, CMS could elect to immediately 
remove the quality measure from the IOTA Model quality measure set. 
Finally, we propose that CMS would, upon removal of a quality measure, 
and in a form and manner determined by CMS, do the following:
     Provide notice to IOTA participants and the public at the 
time CMS removes the quality measure, along with a statement of the 
specific patient safety concerns that would be raised if IOTA 
participants continued to submit data on the quality measure.
     Provide notice of the removal in the Federal Register.
    We seek comment on the requirement that IOTA participants report 
quality measure data to CMS. We additionally seek comment on our 
proposed process for adding, removing, or replacing quality measures in 
the IOTA Model.
(b) CollaboRATE Shared Decision-Making Score
    The CollaboRATE Shared Decision-Making Score is a patient-reported 
measure of shared decision-making. The measure provides a performance 
score representing the percentage of adults 18 years of age and older 
who experience a high degree of shared decision making. The CollaboRATE 
Shared Decision-Making Score is based on three questions that assess 
the degree to which effort was made to inform the patient of his or her 
health issues, to listen to the patient's priorities, and the extent to 
which the patient's priorities were included in determining next steps. 
The measure is generic and applies to all clinical encounters, 
irrespective of the condition or the patient group. We propose that 
IOTA participants would be required to administer the CollaboRATE 
Shared Decision-Making Score to attributed patients once per PY, at 
minimum, and report quality measure data to CMS during survey and 
reporting windows, as defined in section III.C.5.e.(2).(a). of this 
proposed rule, that would be established by CMS.
    We believe that incentivizing shared decision-making is critical to 
ensuring the model centers the patient experience and treatment choice 
to meet the IOTA desired goals of improving equity, increasing the 
number of kidney transplants, and reducing kidney non-utilization. 
Patients needing a kidney transplant often face many challenges when 
making healthcare decisions, as they must first decide between 
treatment options (such as dialysis versus transplantation, living 
donor versus deceased-donor transplantation) and where they wish to be 
evaluated for transplantation. Research findings demonstrate the 
importance and impact of shared decision-making throughout the entire 
transplant process for patients because of the types of complex 
decisions they must make, and the dynamic factors involved in each 
patient's decision.\249\ Research studies have found that shared 
decision-making shifts the patient-physician relationship past 
traditional practices and contributes to better health outcomes, 
increased quality of life, increased patient knowledge and medication 
adherence, and lower healthcare expenditures.\250\ Furthermore, 
research findings support that shared decision-making with the patient 
could reduce kidney non-utilization, improve equity,

[[Page 43567]]

and increase the number of kidney transplants.\251\
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    \249\ Jones, E.L., Shakespeare, K., McLaughlin, L., & Noyes, J. 
(2023). Understanding people's decisions when choosing or declining 
a kidney transplant: a qualitative evidence synthesis. BMJ Open, 
13(8), e071348. https://doi.org/10.1136/bmjopen-2022-071348; 
Stephenson, M.D., & Bradshaw, W. (2018). Shared decision making in 
chronic kidney disease. Renal Society of Australasia Journal, 14(1), 
26-32. http://mutex.gmu.edu/login?url=https://www.proquest.com/scholarly-journals/shared-decision-making-chronic-kidney-disease/docview/2283078287/se-2; Gordon, E.J., Butt, Z., Jensen, S.E., Lok-
Ming Lehr, A., Franklin, J., Becker, Y., Sherman, L., Chon, W.J., 
Beauvais, N., Hanneman, J., Penrod, D., Ison, M.G., & Abecassis, 
M.M. (2013). Opportunities for Shared Decision Making in Kidney 
Transplantation. American Journal of Transplantation, 13(5), 1149-
1158. https://doi.org/10.1111/ajt.12195; Salter, M.L., Babak Orandi, 
McAdams-DeMarco, M.A., Law, A., Meoni, L.A., Jaar, B.G., Sozio, 
S.M., Hong, W., Parekh, R.S., & Segev, D.L. (2014). Patient- and 
Provider-Reported Information about Transplantation and Subsequent 
Waitlisting. Journal of the American Society of Nephrology, 25(12), 
2871-2877. https://doi.org/10.1681/asn.2013121298; Schold, J.D., 
Huml, A.M., Poggio, E.D., Reese, P.P., & Mohan, S. (2022). A tool 
for decision-making in kidney transplant candidates with poor 
prognosis to receive deceased donor transplantation in the United 
States. Kidney International. https://doi.org/10.1016/j.kint.2022.05.025; Schaffhausen, C.R., Bruin, M.J., McKinney, W.T., 
Snyder, J.J., Matas, A.J., Kasiske, B.L., & Israni, A.K. (2019). How 
patients choose kidney transplant centers: A qualitative study of 
patient experiences. 33(5), e13523-e13523. https://doi.org/10.1111/ctr.13523; Hart, A., Bruin, M., Chu, S., Matas, A., Partin, M.R., & 
Israni, A.K. (2019). Decision support needs of kidney transplant 
candidates regarding the deceased donor waiting list: A qualitative 
study and conceptual framework. Clinical Transplantation, 33(5), 
e13530. https://doi.org/10.1111/ctr.13530; S. Ali Husain, Brennan, 
C., Michelson, A., Tsapepas, D., Patzer, R.E., Schold, J.D., & 
Mohan, S. (2018). Patients prioritize waitlist over posttransplant 
outcomes when evaluating kidney transplant centers. 18(11), 2781-
2790. https://doi.org/10.1111/ajt.14985; Patzer, R.E., McPherson, 
L., Basu, M., Mohan, S., Wolf, M., Chiles, M., Russell, A., Gander, 
J.C., Friedewald, J.J., Ladner, D., Larsen, C.P., Pearson, T., & 
Pastan, S. (2018). Effect of the iChoose Kidney decision aid in 
improving knowledge about treatment options among transplant 
candidates: A randomized controlled trial. American Journal of 
Transplantation: Official Journal of the American Society of 
Transplantation and the American Society of Transplant Surgeons, 
18(8), 1954-1965. https://doi.org/10.1111/ajt.14693.
    \250\ Stephenson, M.D., & Bradshaw, W. (2018). Shared decision 
making in chronic kidney disease. Renal Society of Australasia 
Journal, 14(1), 26-32. http://mutex.gmu.edu/login?url=https://www.proquest.com/scholarly-journals/shared-decision-making-chronic-kidney-disease/docview/2283078287/se-2; Gordon, E.J., Butt, Z., 
Jensen, S.E., Lok-Ming Lehr, A., Franklin, J., Becker, Y., Sherman, 
L., Chon, W.J., Beauvais, N., Hanneman, J., Penrod, D., Ison, M.G., 
& Abecassis, M.M. (2013). Opportunities for Shared Decision Making 
in Kidney Transplantation. American Journal of Transplantation, 
13(5), 1149-1158. https://doi.org/10.1111/ajt.12195; Schold, J.D., 
Huml, A.M., Poggio, E.D., Reese, P.P., & Mohan, S. (2022). A tool 
for decision-making in kidney transplant candidates with poor 
prognosis to receive deceased donor transplantation in the United 
States. Kidney International. https://doi.org/10.1016/j.kint.2022.05.025; Schaffhausen, C.R., Bruin, M.J., McKinney, W.T., 
Snyder, J.J., Matas, A.J., Kasiske, B.L., & Israni, A.K. (2019). How 
patients choose kidney transplant centers: A qualitative study of 
patient experiences. 33(5), e13523-e13523. https://doi.org/10.1111/ctr.13523; Hart, A., Bruin, M., Chu, S., Matas, A., Partin, M.R., & 
Israni, A.K. (2019). Decision support needs of kidney transplant 
candidates regarding the deceased donor waiting list: A qualitative 
study and conceptual framework. Clinical Transplantation, 33(5), 
e13530. https://doi.org/10.1111/ctr.13530; Patzer, R.E., McPherson, 
L., Basu, M., Mohan, S., Wolf, M., Chiles, M., Russell, A., Gander, 
J.C., Friedewald, J.J., Ladner, D., Larsen, C.P., Pearson, T., & 
Pastan, S. (2018). Effect of the iChoose Kidney decision aid in 
improving knowledge about treatment options among transplant 
candidates: A randomized controlled trial. American Journal of 
Transplantation: Official Journal of the American Society of 
Transplantation and the American Society of Transplant Surgeons, 
18(8), 1954-1965. https://doi.org/10.1111/ajt.14693.
    \251\ Kucirka, L.M., Grams, M.E., Balhara, K.S., Jaar, B.G., & 
Segev, D.L. (2011). Disparities in Provision of Transplant 
Information Affect Access to Kidney Transplantation. American 
Journal of Transplantation, 12(2), 351-357. https://doi.org/10.1111/j.1600-6143.2011.03865.x; Patzer, R.E., Retzloff, S., Buford, J., 
Gander, J., Browne, T., Jones, H., Ellis, M., Canavan, K., Berlin, 
A., Mulloy, L., Gibney, E., Sauls, L., Muench, D., Reeves-Daniel, 
A., Zayas, C., DuBay, D., Mutell, R., & Pastan, S.O. (2021). 
Community Engagement to Improve Equity in Kidney Transplantation 
from the Ground Up: the Southeastern Kidney Transplant Coalition. 
Current Transplantation Reports, 8(4), 324-332. https://doi.org/10.1007/s40472-021-00346-x; Schold, J.D., Huml, A.M., Poggio, E.D., 
Reese, P.P., & Mohan, S. (2022). A tool for decision-making in 
kidney transplant candidates with poor prognosis to receive deceased 
donor transplantation in the United States. Kidney International. 
https://doi.org/10.1016/j.kint.2022.05.025; Patzer, R.E., McPherson, 
L., Basu, M., Mohan, S., Wolf, M., Chiles, M., Russell, A., Gander, 
J.C., Friedewald, J.J., Ladner, D., Larsen, C.P., Pearson, T., & 
Pastan, S. (2018). Effect of the iChoose Kidney decision aid in 
improving knowledge about treatment options among transplant 
candidates: A randomized controlled trial. American Journal of 
Transplantation: Official Journal of the American Society of 
Transplantation and the American Society of Transplant Surgeons, 
18(8), 1954-1965. https://doi.org/10.1111/ajt.14693.
---------------------------------------------------------------------------

    By pairing the CollaboRATE Shared Decision-Making Score measure 
with the proposed achievement domain number of kidney transplants 
metric, as described in section III.C.5.c. of this proposed rule, and 
the proposed quality domain post-transplant outcomes metrics, as 
described in section III.C.5.e.(1). of this proposed rule, we aim to 
incentivize care delivery transformation and improvement activity 
across IOTA participants that would center attributed patients and 
their family and caregiver as a critical decision-maker in treatment 
choices that align with their preferences and values. This may include 
greater transparency on donor organ offers and reasons for non-
acceptance, and increased education and support on the living donor 
process. We also believe that this would support attributed patients in 
receiving a kidney that may be at higher risk of non-use, but that may 
offer a survival and quality of life advantage over remaining on 
dialysis, dying while waitlisted, or being de-listed.\252\
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    \252\ Massie, A.B., Luo, X., Chow, E.K.H., Alejo, J.L., Desai, 
N.M., & Segev, D.L. (2014). Survival benefit of primary deceased 
donor transplantation with high-KDPI kidneys. American Journal of 
Transplantation, 14(10), 2310-2316. https://doi.org/10.1111/ajt.12830.
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    We acknowledge that the instrument used for the CollaboRATE Shared 
Decision-Making Score is generic; however, we have not been able to 
identify alternative measures of shared decision-making that are 
specific to kidney transplant that have been endorsed by the CBE. 
Similarly, while there may be value in an instrument that measures 
shared decision-making regarding the types of kidney organ offers 
attributed patients are willing to accept, no such measure exists. We 
believe the CollaboRATE Shared Decision-Making Score would capture 
variation in the presence and quality of shared decision-making among 
IOTA participants and that the instrument need not be specific to 
kidney transplant to incentivize meaningful improvements in patient-
centricity and the patient experience, equity, and reducing kidney non-
use.
    We seek comment on our proposal to include the CollaboRATE Shared 
Decision-Making Score as a quality measure for purposes of quality 
domain performance assessment.
(c) Colorectal Cancer Screening
    The Colorectal Cancer Screening (COL) measure identifies the 
percentage of patients 50-75 years of age who had guideline concordant 
screening for colorectal cancer. Kidney transplant recipients are at 
higher risk for cancer than the general population, due in part to 
long-term immunosuppression.\253\ Kidney transplant recipients have a 
higher incidence of colorectal cancer and advanced adenomas and may 
have worse prognoses than the general population, both of which support 
improved screening and prophylactic care for kidney transplant 
recipients.254 255 256
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    \253\ Rama, I., & Griny[oacute], J.M. (2010). Malignancy after 
renal transplantation: The role of immunosuppression. Nature Reviews 
Nephrology, 6(9), 511-519. https://doi.org/10.1038/nrneph.2010.102.
    \254\ Komaki, Y., Komaki, F., Micic, D., Ido, A., & Sakuraba, A. 
(2018). Risk of colorectal cancer in chronic kidney disease. Journal 
of Clinical Gastroenterology, 52(9), 796-804. https://doi.org/10.1097/mcg.0000000000000880.
    \255\ Privitera, F., Gioco, R., Civit, A.I., Corona, D., 
Cremona, S., Puzzo, L., Costa, S., Trama, G., Mauceri, F., Cardella, 
A., Sangiorgio, G., Nania, R., Veroux, P., & Veroux, M. (2021). 
Colorectal cancer after Kidney Transplantation: A screening 
colonoscopy case-control study. Biomedicines, 9(8), 937. https://doi.org/10.3390/biomedicines9080937.
    \256\ Farrugia, D., Mahboob, S., Cheshire, J., Begaj, I., 
Khosla, S., Ray, D., & Sharif, A. (2014). Malignancy-related 
mortality following kidney transplantation is common. Kidney 
International, 85(6), 1395-1403. https://doi.org/10.1038/ki.2013.458.
---------------------------------------------------------------------------

    The COL measure is a Universal Foundation measure in the CMS 
Meaningful Measures 2.0 Wellness and Prevention Domain. By nature of 
its inclusion in the Universal Foundation measure set, the COL measure 
addresses a condition associated with significant morbidity and 
mortality and incentivizes action on high-value preventive care.\257\ 
The COL measure is also aligned with the goals of the President's 
Cancer Moonshot to reduce the death rate from cancer by 50 percent over 
the next 25 years and improve the experience of people living with 
cancer and those who have survived it.\258\
---------------------------------------------------------------------------

    \257\ Jacobs, D.B., Schreiber, M., Seshamani, M., Tsai, D., 
Fowler, E., & Fleisher, L.A. (2023). Aligning quality measures 
across CMS--the Universal Foundation. New England Journal of 
Medicine, 388(9), 776-779. https://doi.org/10.1056/nejmp2215539.
    \258\ Cancer Moonshot. (n.d.). The White House. https://www.whitehouse.gov/cancermoonshot/.
---------------------------------------------------------------------------

    We are proposing the COL measure for inclusion in our assessment of 
quality domain performance in the model because we believe it would 
provide a signal of the importance of ongoing post-transplant care and 
reduce variation in the screening and prophylactic care of kidney 
transplant recipients by transplant hospital. We propose that IOTA 
participants would be required to administer the COL measure yearly to 
all attributed IOTA transplant patients who are Medicare beneficiaries. 
The COL measure would work in concert with the proposed composite graft 
survival metric to increase the likelihood that attributed patients in 
the IOTA Model would receive comprehensive post-transplant care that 
would account not only for the attributed patient and graft survival, 
but also complications and comorbidities associated with receiving a 
kidney transplant.
    We seek comment on our proposal to include the COL measure as a 
quality measure for purposes of quality domain performance assessment.
(d) 3-Item Care Transition Measure (CTM-3)
    The 3-Item Care Transition Measure (CTM-3) is a hospital-level, 
patient-reported measure of readiness for self-care at time of 
discharge from an acute care hospital. The CTM-3 is based on data from 
a three-question instrument that assesses whether the patient and 
family's preferences were accounted for in the care plan; whether 
patients understood their role in self-management; and, whether 
appropriate medication education was provided. A higher score on the 
CTM-3 reflects a higher quality transition of care. We propose that 
IOTA participants would be required to administer the CTM-3 to 
attributed patients once per PY, at minimum, and report quality measure 
data to CMS during survey and reporting windows, as defined in section 
III.C.5.e.(2).(a). of this proposed rule, that would be established by 
CMS.

[[Page 43568]]

    Transitions of care after kidney transplant are common and indicate 
elements of modifiable transplant hospital quality. One study found 
that 30-day hospital readmissions after an organ transplant were 
significantly associated with graft loss and death.\259\ Poor 
understanding of and adherence to immunosuppressive drugs were 
identified as key elements associated with an increased risk for early 
hospital readmission.\260\ Mitigating readmission risk may be of 
special importance given that IOTA participants may choose to increase 
their number of transplants by transplanting more kidneys that may have 
clinical value to patients. Simultaneously, there may also be increased 
healthcare utilization needs due to delayed graft function (DGF), which 
could require longer hospital stays, readmissions, and more complex 
care coordination.\261\ We have also heard from interested parties 
about the need for patient-reported measures to contribute to the 
assessment of post-transplant outcomes.
---------------------------------------------------------------------------

    \259\ Covert, K.L., Fleming, J.N., Staino, C., Casale, J.P., 
Boyle, K.M., Pilch, N.A., Meadows, H.B., Mardis, C.R., McGillicuddy, 
J.W., Nadig, S., Bratton, C.F., Chavin, K.D., Baliga, P.K., & Taber, 
D.J. (2016). Predicting and preventing readmissions in Kidney 
Transplant Recipients. Clinical Transplantation, 30(7), 779-786. 
https://doi.org/10.1111/ctr.12748.
    \260\ Covert, K.L., Fleming, J.N., Staino, C., Casale, J.P., 
Boyle, K.M., Pilch, N.A., Meadows, H.B., Mardis, C.R., McGillicuddy, 
J.W., Nadig, S., Bratton, C.F., Chavin, K.D., Baliga, P.K., & Taber, 
D.J. (2016). Predicting and preventing readmissions in Kidney 
Transplant Recipients. Clinical Transplantation, 30(7), 779-786. 
https://doi.org/10.1111/ctr.12748.
    \261\ Jadlowiec, C.C., Frasco, P., Macdonough, E., Wagler, J., 
Das, D., Budhiraja, P., Mathur, A.K., Katariya, N., Reddy, K., 
Khamash, H., & Heilman, R. (2022). Association of DGF and early 
readmissions on outcomes following Kidney Transplantation. 
Transplant International, 35. https://doi.org/10.3389/ti.2022.10849.
---------------------------------------------------------------------------

    The CTM-3 is a patient-reported measure and would measure 
transplant hospital performance on an aspect of care that we understand 
to be important to the patient experience, modifiable by transplant 
hospitals, and that may not otherwise improve based on the financial 
incentives in the model targeted towards 1- and 3-year outcomes, but 
not directly at perioperative transitions of care and readmission risk. 
The CTM-3 is a domain of the HCAHPS (CBE ID: 0166). We believe that 
IOTA participants would have some familiarity with the HCAHPS survey 
and that the hospital systems of which IOTA participants would be a 
part would have an infrastructure in place for the administration of 
HCAHPS that could be leveraged to support administration of the CTM-3.
    We seek comment on our proposal to include the CTM-3 measure as a 
quality measure as a quality measure for purposes of quality domain 
performance assessment.
(e) Calculation of Points
    We propose that the IOTA participant would receive up to 10 points 
for performance on our three proposed measures within the quality 
domain--the CollaboRATE Shared Decision-Making Score, COL, and CTM-3 
measures. For purposes of quality measure set performance scoring, we 
propose that IOTA participants may receive up to 4 points for 
performance on the CollaboRATE Shared Decision-Making Score measure, up 
to 2 points on the COL measure, and up to 4 points on the CTM-3 
measure. Lower weight in terms of scoring points was given to the COL 
measure because it is a claims-based measure that does not require 
reporting from IOTA participants. Because the CTM-3 and CollaboRATE are 
PRO-PMs we believe it is important to allot more points to them, to 
recognize the additional operational activities necessary for IOTA 
participants.
    We propose to phase-in quality performance benchmarks for the three 
quality measures selected for the IOTA quality measure set, such that 
we would reward reporting for the first two years of the model 
performance period (``pay-for-reporting''), at minimum, before we 
reward performance against quality performance benchmarks for each 
measure (``pay-for-performance''). Thus, performance for each of these 
three quality measures would be measured against a ``response rate 
threshold'' applicable to our proposed ``pay-for-reporting'' method for 
PY 1-PY 2, while performance would be measured against quality 
performance benchmarks calculated by CMS applicable to our proposed 
``pay-for-performance'' method for PY 3-PY 6. Table 8 illustrates our 
proposed pay-for-reporting and pay-for-performance timeline. We note 
that we anticipate establishing a quality performance benchmarks and 
minimum attainment levels for quality measures in future rule making.
[GRAPHIC] [TIFF OMITTED] TP17MY24.008

    We propose that CMS would determine and share with IOTA 
participants the response rate threshold by the first day of each PY in 
a form and manner chosen by CMS. This approach to assessing IOTA 
participant quality performance would serve four key purposes. First, 
it would promote measure implementation, uptake, and data collection by 
IOTA participants through a rewards-only scoring system. Second, it 
would build experience over the first two model PYs, giving IOTA 
participants more time to prepare and build capacity to meet 
performance benchmarks. Third, it would allow CMS to collect data 
needed to develop measure benchmarks. Finally, it would focus model 
incentives on care delivery transformation and improvement activity 
directly aimed at meeting quality performance goals, as to ensure the 
patient is centered in this approach. Ultimately, we considered the 
pay-for-reporting approach to be a reasonable approach. We also believe 
that some IOTA participants may be familiar with this as it is similar 
to the format within the KCC Model. We recognize that these measures 
already exist, but, because they are used in a much broader population, 
there are no benchmarks that are applicable for the model.
    We propose to define the ``response rate threshold'' as the level 
of complete and accurate reporting for each quality measure, within the 
quality measure set of the quality domain, that the IOTA participant 
must meet to earn points on the quality domain during a performance 
year as described in Sec.  512.428(c) and (e). For the CTM-3 and 
CollaboRATE measures, we propose that

[[Page 43569]]

points be awarded based on response rate thresholds, as illustrated in 
Table 9, such that IOTA participants with a response rate threshold 
of--
     90-100 percent of attributed patients would receive 4 
points;
     50-89 percent of attributed patients would receive 2 
points; or
     Under 50 percent of attributed patients would receive 0 
points.
    We propose for the COL measure that a completion rate of 50 percent 
or greater would result in the IOTA participant receiving two points, 
and a completion rate of less than 50 percent would result in the IOTA 
participant receiving zero points, as illustrated in Table 9.
[GRAPHIC] [TIFF OMITTED] TP17MY24.009

    We recognize that the proposed response rate thresholds are high, 
but we want to make sure that we have enough data to set appropriate 
and meaningful benchmarks in PY 3 through PY 6. We considered setting a 
higher maximum measure completion rate; however, given that each IOTA 
participant may have different levels of engagement with kidney 
transplant waitlist patients, we believe a higher threshold may be 
difficult for IOTA participants to achieve. We also believe that a 
higher response rate would incentivize IOTA participants to collect the 
data. We considered the following variations to the response rate 
threshold for each of the proposed quality measure:
     Response rate threshold of 100 percent would receive 10 
points, if not 100 percent 0 points would be awarded.
     Response rate threshold of 80-100 percent would receive 10 
points, 50-79 percent would receive 5 points, and 49-0 percent would 
receive 0 points.
     50-100 percent would receive 10 points; under 50 percent 
would receive 0 points.
    We considered mirroring the point structure under which an IOTA 
participant would receive either all possible points, or, if data was 
not collected from all their attributed patients, none of the possible 
points. We believe this could incentivize IOTA participants to 
administer the surveys associated with the proposed quality measures, 
which would allow us to create meaningful benchmarks for future model 
years. However, because there would be some additional burden placed 
onto IOTA participants to administer the surveys associated with the 
proposed quality measures, we believe this point structure would be 
difficult for some and wanted to provide more attainable response rate 
thresholds. We also considered lowering the response rate thresholds 
for the same reasons mentioned earlier, but, because there are 
currently no benchmarks for these measures in this specific population, 
we believed the response rate threshold needed to be higher but still 
attainable.
    We also considered achievement and improvement scoring for the 
proposed quality measures. However, because none of the measures 
included in the proposed quality measure set, as described in section 
III.C.5.e.(2). of this proposed rule, currently have benchmarks, we did 
not believe it was appropriate to propose achievement and improvement 
scoring for the proposed quality measures at this time.
    We seek comment on our proposed calculation of points for the 
quality measure set, as well as the proposal to reward IOTA participant 
reporting for the first two PYs (``pay-for-reporting''), before 
rewarding IOTA participant performance against quality performance 
benchmarks. We seek comment on the proposed response rate thresholds 
and point allocations for measures included in the proposed quality 
measure set within the quality domain.
6. Payment
a. Purpose and Goals
    We believe that risk-based payment arrangements in Innovation 
Center models drive healthcare innovation and transform the healthcare 
payment system by rewarding value over volume. Risk-based payment 
models hold participants financially accountable, as these payments are 
structured to incentivize value-based care that improves quality and 
reduces total cost of care for beneficiaries. Risk-based payment models 
may be upside-risk only, or have two-sided, upside and downside, risk. 
Under these risk-based arrangements, model participants may receive a 
payment from CMS if performance goals are met or exceeded, and, if the 
model features downside risk, may owe a payment to CMS for failing to 
meet performance goals.\262\
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    \262\ https://www.cms.gov/priorities/innovation/key-concepts/risk-arrangements-health-care.
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    For the IOTA Model, we propose an alternative payment model (APM) 
structure that incorporates both upside and downside risk to existing 
Medicare fee-for-service (FFS) payments for kidney transplantations as 
described in section III.C.6.b. of this proposed rule.
    The IOTA Model would test whether performance-based payments, 
including an upside risk payment and downside risk payment, to IOTA 
participants increases access to kidney transplants for attributed 
patients while preserving or enhancing quality of care and reducing 
program expenditures. As described in section III.C.5. of this proposed 
rule, IOTA participants would be assessed against proposed metrics to 
assess performance for each PY relative to specified targets, 
threshold, or benchmarks proposed and determined by CMS. The final 
performance score, not to exceed a maximum of 100 points, would 
determine if and how upside and downside risk payments are applied, as 
described in section III.C.6.c. of this proposed rule. We believe this 
upside and downside risk approach would be a strong incentive to 
promote performance improvement.
    We seek comment on our proposed two-sided risk payment design to 
incentivize model performance goals.
b. Alternative Payment Design Overview
    There are two payment components in the current Medicare FFS 
program for organ transplantation. Under the

[[Page 43570]]

Medicare Inpatient Prospective Payment System (IPPS), kidney transplant 
hospitals are paid a prospective payment system rate based on the MS-
DRG for the organ transplant. Payment for organ acquisition costs as 
described at 42 CFR 413.402, which include costs associated with 
beneficiary and donor evaluation, is made on a reasonable cost basis. 
To remain active on the transplant waitlist, candidates must meet a 
variety of criteria, including annual screenings for cardiovascular 
diseases and cancers.
    In the IOTA Model, CMS is proposing two-sided performance-based 
payments for ``Medicare kidney transplants,'' defined as kidney 
transplants furnished to attributed patients whose primary or secondary 
insurance is Medicare FFS, as identified in Medicare FFS claims with 
MS-DRGs 008, 019, 650, 651 and 652, and as illustrated in Table 10. 
This APM design aligns with the Health Care Payment Learning & Action 
Network (LAN) Category 3 APM framework in which model participants 
continue to be paid on the basis of Medicare FFS, but a retrospective 
annual attribution reconciliation and performance assessment after the 
end of each model PY is conducted to determine performance-based 
payments.\263\
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    \263\ https://hcp-lan.org/workproducts/apm-refresh-whitepaper-final.pdf.
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    The IOTA Model's performance-based payments are linked to existing 
Medicare Part A and Part B services for kidney transplants, and align 
with other Innovation Center models' payment structure, including the 
ETC Model where upward and downward adjustments are made to certain 
Medicare payments under the ESRD Prospective Payment System and 
Physician Fee Schedule depending on a n ETC Participant's performance 
at the aggregation group level under the model. The difference between 
ETC and the IOTA Model, for example, is how these retrospective 
adjustments would be paid or recouped by CMS. CMS is not proposing to 
adjust existing Medicare IPPS payments for kidney transplants furnished 
to Medicare beneficiaries. Instead, CMS is proposing to make 
performance-based payments to IOTA participants separate from claims-
based payments.
[GRAPHIC] [TIFF OMITTED] TP17MY24.010

    We propose to base performance-based payments on increasing the 
number of transplants and other metrics of efficiency and quality 
because: (1) we believe it would be a strong proxy for total cost; (2) 
it directly aligns with the model's focused goal of increasing access 
and volume of kidney transplantations; (3) acknowledges kidney waitlist 
and transplant patients are high-cost and high-need, making performance 
based on total cost of care unfair for IOTA participants with lower 
volume and fewer capabilities and resources given increased opportunity 
for outliers; and (4) may safeguard against unintended consequences 
introduced by defining value based on cost for an attributed patient 
population already at high-risk, such as inappropriate cost shifting 
and widening access to care disparities. We theorize that increasing 
the number of, and access to, kidney transplants alone would result in 
better quality. As indicated in our estimates presented in section IV 
of this proposed rule, it would also result in savings to Medicare.
    While we propose to assess model performance for each IOTA 
participant for all attributed patients regardless of payer type, as 
described in section III.C.6.c of this proposed rule, we propose model 
performance-based payments that would only be based on kidney 
transplants furnished to attributed patients with Medicare FFS as the 
primary or secondary insurance.
    We considered also basing the model performance-based payments on 
kidney transplants furnished to attributed patients enrolled in 
Medicare Advantage (MA), as kidney transplants are a Medicare-covered 
service that MA plans must also cover. As these payments would be made 
to transplant hospitals, a potential waiver of section 1851(i)(2) of 
the Act, which provides that only the MA plan shall be entitled to 
payments for services furnished to the beneficiary, may have been 
necessary to apply the payments to attributed patients enrolled in MA. 
Because further consideration is needed for the implications of such a 
potential waiver, we are not proposing to apply model performance-based 
payments performed on attributed patients enrolled in MA.
    We believe that the benefits of applying model performance-based 
payments to transplants furnished to attributed patients enrolled in MA 
would be recognizing the growth in MA enrollment relative to Medicare 
FFS enrollment, strengthening the model test through aligned payment 
incentives across payers, and protecting against unintended 
consequences of incentivizing inappropriate organ offer acceptance 
based on payer type. However, we are not proposing to base payments on 
attributed patients enrolled in MA, because of concerns about 
potentially waiving section 1851(i)(2) of the Act. This provision 
states that only the MA plan is entitled to payments for services 
provided to the beneficiary. Waiving this requirement would be 
unprecedented and the effects are unknown. We do recognize that the 
proposed incentives in the IOTA Model would have a larger effect if 
transplant hospitals were receiving performance-based payments based on 
their entire panel of attributed beneficiaries who receive transplants, 
and not just based on transplants for attributed beneficiaries with 
Medicare FFS as their primary or secondary insurance. To that end, the 
IOTA Model would encourage multi-payer alignment with the goal of 
aligning on goals, incentives, and quality. CMS intends to engage with 
the payer community, including MA,

[[Page 43571]]

Medicaid, and commercial payers, to discuss opportunities and 
approaches for alignment.
    We request comment and feedback, especially from MA plans, on our 
decision not to calculate model performance-based payments to 
transplants furnished to attributed patients enrolled in MA. We are 
especially interested in comments that address how the Innovation 
Center should generally approach the growing MA population with the 
design of its models, which have traditionally been focused on the fee-
for-service Medicare population.
    While kidney transplant hospitals are subject to value-based 
payment programs, some IOTA participants may have limited APM 
experience, resources, and capacity to meet model goals. We considered 
an upside-risk payment only framework that would still base model 
payments on kidney transplant utilization and other metrics of 
efficiency and quality. However, we believed that two-sided risk 
payments would be stronger incentives to achieve desired goals. We also 
recognized this in the model design by proposing a phased-in approach 
to two-sided risk, with upside-only applied to the first model PY. We 
also considered other APM frameworks that would link performance to 
quality, such as pay-for-reporting and pay-for-performance. We did not 
propose these frameworks, as they did not align with our goals of 
establishing two-sided risk accountability for IOTA participants. 
Recognizing the benefits of a rewards-focused approach, particularly as 
it relates to quality performance, we did incorporate a rewards-focused 
performance scoring structure designed as pay-for-reporting and pay-
for-performance within the quality domain performance assessment.
    Another alternative we considered was a flat positive adjustment to 
the Medicare FFS payment for a kidney transplant based on the number of 
completed kidney transplants that an IOTA participant performs. 
Increasing the amount paid for completed kidney transplants through a 
FFS adjustment is the simplest policy and aligns with a main focus of 
the IOTA Model; that is, increasing the number of kidney transplants. 
Additionally, adjusting the FFS payment would directly incentivize an 
increase in the number of kidney transplants performed by IOTA 
participants. Under this approach, eligible claims would be identified 
utilizing Medicare claims data with Medicare Severity Diagnosis Related 
Groups (MS-DRGs) 008 (simultaneous pancreas-kidney transplant) and 652 
(kidney transplant); and claims with ICD-10 procedure codes 0TY00Z0 
(transplantation of right kidney, allogeneic, open approach), 0TY00Z1 
(transplantation of right kidney, syngeneic, open approach), 0TY00Z2 
(transplantation of right kidney, zooplastic, open approach) 0TY10Z0 
(transplantation of left kidney, allogeneic, open approach), 0TY10Z1 
(transplantation of left kidney, syngeneic, open approach), and 0TY10Z2 
(transplantation of left kidney, zooplastic, open approach).
    We are not proposing a performance methodology based solely on 
adjusting the DRG payment for a kidney transplant, because this option 
would not encourage IOTA participants to focus on issues other than 
transplant volume, including equity, increased utilization of donor 
kidneys, quality of care, and patient outcomes, all of which are all 
important parts of the transplant process where we believe performance 
is variable and can be improved. We further believe that the claims-
only approach would limit IOTA participant responsiveness to the model 
because IOTA participants that already have high kidney transplant 
volumes would be rewarded through increased reimbursements whether they 
improved year-over-year or not. Finally, we do not believe that this 
approach would provide any additional encouragement for IOTA 
participants to manage post-transplant care.
    We also considered establishing a payment for transplant waitlist 
management to encourage additional investment in the transplant 
process, but decided to focus more on the outcomes described in section 
III.C.5 of this proposed rule. Additionally, given that IOTA 
participants are already reimbursed at cost for efforts to manage 
beneficiaries on the waitlist, we did not believe an explicit 
additional payment would be necessary in this area.
    We seek feedback on our proposed alternative payment model design, 
data source to identify kidney transplants, and proposal to only apply 
model performance-based payments, both upside and downside, to Medicare 
kidney transplants. We also seek feedback on alternative approaches 
considered, including consideration of MA inclusion. We welcome input 
on how CMS may be able to work with multiple payers to ensure alignment 
with the IOTA Model.
c. Performance-Based Payment Method
    We are proposing that the final performance score as described in 
section III.C.5. of this proposed rule would determine if and how an 
IOTA participant qualifies for an upside risk payment, falls in the 
neutral zone, or qualifies for a downside risk payment, proposed using 
a two-step process. First, we would determine if an IOTA participant's 
final performance score qualifies the IOTA participant for upside risk 
payments, downside risk payments, or the neutral zone, as described in 
section III.C.6.c.(1). of this proposed rule. Second, we would apply 
the proposed calculation formula for each of type of payment, as 
described in section III.C.6.c.(2). of this proposed rule. Ultimately, 
we are proposing a performance-based payment method that prioritizes 
the following principles:
     Significant weight should be given to performance in the 
achievement domain, representing up to 60 points relative to a 100 
maximum performance score, in alignment with the primary goals of the 
model to increase number of kidney transplants.
     The magnitude of performance-based payments should be tied 
to relative number of kidney transplants, given significant 
differentials across kidney transplant hospitals nationally.
     The largest performance-based payments amount in total 
dollars should go to IOTA participants that perform the most 
transplants because they are removing the most people from dialysis and 
creating the largest quality improvement and cost savings for the 
Medicare Trust Fund.
     The payments need to be calibrated to provide an incentive 
to IOTA participants, but still ensure net savings to Medicare based on 
the analysis performed by OACT in section IV of this proposed rule.
     The mechanisms should recognize that CMS has not 
previously offered kidney transplant hospitals a value-based care 
payment model around transplantation and should provide a transition to 
any form of downside risk to allow for an opportunity to become 
familiar with the value-based care process.
     Limit operational complexity for both IOTA participants 
and CMS to avoid any potential for errors.
(1) Determine Final Performance Score Range Category
    We propose to establish three final performance score range 
categories, as illustrated in Table 11, that dictate which type of 
performance-based payment would apply to an IOTA participant for a 
given PY.
    We propose to define ``upside risk payment'' as a lump sum payment 
that CMS would make to an IOTA participant if the IOTA participant's 
final performance score for a PY falls

[[Page 43572]]

within the payment range specified in section III.C.6.c(2)(a) of this 
proposed rule. As proposed and indicated in Table 11, if in PY 1-6, an 
IOTA participant's final performance score is greater than or equal to 
60 points, the IOTA participant would qualify for an upside risk 
payment.
    We propose to define ``neutral zone'' as the final performance 
score range in which the IOTA participant would not owe a downside risk 
payment to CMS or receive an upside-risk payment from CMS if the IOTA 
participant's final performance score falls within the ranges specified 
in section III.C.6.c.(2).(c). of this proposed rule. In the first year 
of the model, we propose that the neutral zone would apply for final 
performance scores below 60. As such, only upside payments and the 
neutral zone would exist in PY 1. We are also proposing the neutral 
zone in PYs 2-6 would apply for final performance scores of 41-59 
(inclusive). We believe that average performance should yield no upside 
or downside risk payment.
    We propose to define ``downside risk payment'' as a lump sum 
payment the IOTA participant would be required to pay to CMS after a PY 
if the IOTA participant's final performance score falls within the 
ranges specified in section III.C.6.c.(2).(b). of this proposed rule. 
We propose that there will be no downside risk payment in the PY 1. We 
are proposing no downside risk payment in the first PY to allow IOTA 
participants time to implement changes to improve performance prior to 
facing downside risk. In PYs 2-6, we are proposing to introduce 
downside risk payments. We propose that an IOTA participant's final 
performance score of 40 or below in PYs 2-6, would result in a downside 
risk payment. We believe that below average performance should yield a 
downside risk payment.
    The performance assessment scoring method, as described in section 
III.C.5. of this proposed rule, was designed such that IOTA 
participants with limited experience in APMs would still be likely to 
achieve a sufficient final performance score that would result in no 
downside risk payment. For example, it is expected that most IOTA 
participants would earn around 30 of 60 possible points in the 
achievement domain. We believe that average performance should be 
neither rewarded nor penalized. We also considered eliminating the 
neutral zone and only applying upside and downside performance 
payments, narrowing the neutral zone score range (that is, 44-55), or 
applying a wider-to-narrower phased-in approach over the model 
performance period. We believed these alternative options would be less 
flexible and more penalty-focused, with some IOTA participants more 
likely to be penalized due to varying degrees of capabilities and 
capacity that would limit their ability to achieve performance targets 
as they progress and evolve over the model performance period. Thus, we 
are opting to propose a neutral zone that would allow for more 
opportunities and incentives to achieve improvements over time without 
a large probability of downside risk.
[GRAPHIC] [TIFF OMITTED] TP17MY24.011

    We seek feedback on the use of the final performance scores to 
determine the upside risk payment, the downside risk payment, and the 
neutral zone.
(2) Apply Payment Calculation Formula to Final Performance Score
    We propose that after determining if an IOTA participant's final 
performance score qualifies the IOTA participant for an upside risk 
payment, downside risk payment, or the neutral zone, as described in 
section III.C.6.c.(1). of this proposed rule, we would apply a 
calculation formula unique to each PY to the final performance score, 
as specified in sections III.C.6.c.(2).(a). through (c). of this 
proposed rule.
(a) Upside Risk Payment
    If, in PYs 1-6, an IOTA participant's final performance score is 
greater than or equal to 60 points, we propose that the IOTA 
participant would qualify for an upside risk payment. If an IOTA 
participant's final performance score would qualify them for the upside 
risk payment, we propose a methodology to calculate their upside risk 
payment using the formula in equation 2, where:
     $8,000 is a fixed, risk-based payment amount within the 
calculation formula, estimated to be about 33 percent of the average 
Medicare FFS kidney transplant MS-DRG cost. We aimed to create a strong 
financial incentive with significant earning opportunity for IOTA 
participants that meet or exceed model performance expectations. We 
believe this amount or proportion of the MS-DRG to be a large financial 
incentive to promote behavior changes while maintaining expectations of 
net savings to Medicare. We calibrated this based on projection of the 
incentive effects that would encourage the necessary support and 
infrastructure investment needed to achieve high performance and 
produce overall model savings and have the effects that we are looking 
for.
     The final performance score is the sum of points earned 
from the achievement domain, efficiency domain, and quality domain in a 
PY, as described in section III.C.5. of this proposed rule.
     Medicare kidney transplants is the number of Medicare 
kidney transplants furnished by the IOTA participant in a PY.
Equation 2: Proposed Upside Risk Payment Calculation Formula
Upside Risk Payment = $8,000 * ((Final Performance Score-60)/40) * 
Medicare Kidney Transplants

    We also considered calculating the maximum positive multiplier per 
Medicare kidney transplant claim based on the Kidney Transplant Bonus 
in the KCC Model. In 2019, the Kidney Transplant Bonus for entities 
participating in the KCC Model was set to $15,000. Adjusted for 
inflation, this is roughly $18,000, which would be the maximum 
allowable positive bonus payment per transplant. The Kidney Transplant 
Bonus was originally calculated based on the difference in spending 
between a beneficiary who went on to get a transplant and the average 
ESRD beneficiary cost.

[[Page 43573]]

However, we believe that the maximum positive adjustment may be too 
large in relation to current Medicare payments for kidney transplants 
for the model to yield net savings.
    We also considered using a system similar to the Hospital VBP 
Program under which CMS withholds 2 percent of participating's 
hospitals Medicare payments and uses the sum of these reductions to 
fund value-based incentive payments to hospitals based on their 
performance under the program. However, we wished to have equal upside 
and downside multipliers across IOTA participants.
    We also considered adjusting the maximum upside multiplier in PYs 
2-6; however, we felt making that decision prior to the start of the 
model would be premature and wish to understand IOTA participant 
performance before making such a decision.
    We seek comment on our proposed methodology to calculate the upside 
risk payment and alternatives considered.
(b) Downside Risk Payment
    If an IOTA participant's final performance score is at or below 40 
points in PYs 2--6, the IOTA participant would qualify for a downside 
risk payment. If an IOTA participant qualifies for a downside risk 
payment, we describe the methodology to calculate their downside risk 
payment risk using the formula in equation 3:
Equation 3: Proposed Downside Risk Payment Calculation Formula
Downside Risk Payment = $2,000 * ((40-Final Performance Score)/40) * 
Medicare Kidney Transplants

     $2,000 is a fixed, risk-based payment amount within the 
calculation formula, estimated to be about one-twelfth, or 8 percent, 
of the average Medicare FFS kidney transplant MS-DRG cost. We are 
proposing a lower downside-risk value relative to the upside-risk value 
proposed for the upside risk payments (about one-fourth lower) because 
we wanted to maintain a greater rewards approach, while still holding 
IOTA participants accountable for poor performance. We also believe 
that this approach is more flexible and accommodating to IOTA 
participants with no, or limited, APM experience, or that are more 
limited in terms of resources and capabilities.
     The final performance score is the sum of points earned 
from the achievement domain, efficiency domain, and quality domain, as 
described in section III.C.5. of this proposed rule.
     Medicare kidney transplants is the count of furnished 
Medicare kidney transplants during the PY.
    We also considered applying the same fixed amount to both the 
upside and downside risk payment ($8,000 or $2,000 in both) or having 
the downside risk payment be 50 percent of the fixed amount of the 
upside risk payment ($4,000) but opted against it to maintain lower 
levels of risk given the fact that this model would be mandatory for 
eligible kidney hospitals. As discussed in section III.C.6.b of this 
proposed rule, we considered an upside-risk only payment framework, 
thus eliminating the application of downside-risk payments. Recognizing 
the potential for volatility in performance year-over-year, we also 
considered requiring IOTA participants to owe downside-risk payments to 
CMS if their final performance score was at or below 40 for more than 
one PY, starting from PY 1, potentially giving IOTA participants a 
similar phased-in, or, rather, ramp-up, opportunity to adjust and 
improve before downside-risk payments kick in. We considered this 
option to be unnecessary and operationally complex, particularly as it 
would function in a similar way as our proposed approach from a 
phasing-in standpoint. We also considered adjusting the $2,000 fixed, 
risk-based payment amount for PYs 2--6; however, we believe a fixed 
amount would provide greater transparency to IOTA participants on 
financial risk and model implementation experience would better inform 
if this approach would be necessary.
    We seek comment on our proposed downside risk payment calculation 
formula, and alternatives considered.
(c) Neutral Zone
    If, in PY 1, an IOTA participant's final performance score was 
below 60 points, or if, in PYs 2-6, an IOTA participant's final 
performance score was between 41 and 59 (inclusive), we propose that 
the final performance score, as described in section III.C.6.c.(1). of 
this proposed rule, would qualify the IOTA participant for the neutral 
zone, where no upside risk payment or downside risk payment would 
apply. As such, in a PY where an IOTA participant's final performance 
score falls in the neutral zone, no money would be paid to the IOTA 
participant by CMS, nor would money be owed by the IOTA participant to 
CMS.
    We seek comment on our proposed neutral zone.
(3) Payments Operations and Timelines
    After the end of each PY, CMS would assess each IOTA participant's 
performance in accordance with section III.C.5. of this proposed rule 
and calculate performance-based payments in accordance with the 
methodology specified in section III.C.6.c. of this proposed rule. We 
propose to define this process as ``preliminary performance assessment 
and payment calculations.''
    We propose that CMS would conduct and calculate preliminary 
performance assessment and payment calculations at least 3 to 6 months 
after the end of each PY to allow for sufficient Medicare kidney 
transplant claims runout. We propose that CMS would notify IOTA 
participants of their preliminary model performance assessment, 
including the IOTA participant's score for each metric within the 
achievement domain, efficiency domain, and quality domain and the final 
performance score, and payment calculations with respect to any 
applicable upside risk payment or downside risk payment, at least 5 to 
9 months after the end of each PY, allowing for a two-to-three month 
period for CMS to conduct calculations after the claims runout period. 
We propose that a 30-day notification period between preliminary and 
final calculations would apply, giving IOTA participants 30 days to 
review preliminary data and calculations and request targeted reviews, 
as described in section III.C.6.c.(4). of this proposed rule. This 30-
day notification period would also be intended to provide IOTA 
participants with advance notice of forthcoming performance-based 
payments before upside risk payments or demand letters for downside 
risk payments would be issued by CMS. We also propose that CMS would 
notify IOTA participants of their model performance assessment and 
payment calculations in a form and manner determined by CMS, such as 
letters, email, or model dashboard. We propose that CMS would notify 
the IOTA participant of their final performance score and any 
associated upside risk payment or downside risk payment at least 30 
days after notifying the IOTA participant of their preliminary model 
performance assessment and payment calculations.
    We propose that after CMS notifies the IOTA participant of their 
final performance score and any associated upside risk payment and by a 
date determined by CMS, CMS would issue the upside risk payment to the 
tax identification number (TIN) on file for the IOTA participant in the 
Medicare Provider Enrollment, Chain, and Ownership System (PECOS).
    We propose that after CMS notifies the IOTA participant of their 
final

[[Page 43574]]

performance score and any associated downside risk payment and by a 
date determined by CMS, CMS would issue a demand letter to the TIN on 
file in PECOS for the IOTA participant for downside risk payments owed 
to CMS, with a payment due date of at least 60 days after the date on 
which the demand letter is issued. We propose that the demand letter 
would include details on model performance, the downside risk payment, 
and how payments would be made to CMS.
    Rather than the proposed lump-sum payment and demand letter 
approach, we also considered making the upside risk payments and 
downside risk payments to IOTA participants in the form of Medicare FFS 
claim adjustments. The benefit of this approach would be that upside 
risk payments and downside risk payments, which are retrospective, 
would be applied prospectively and spread out over a 12-month period, 
so that a transplant hospital would not need to pay back to CMS a large 
sum of monies owed all at once. However, we believe that this approach 
would delay model payments and collection of monies owed to CMS. We 
also consider this approach to be disruptive to standard claims 
processing systems and operationally complex, with more opportunities 
for error and less flexibility to correct errors in a timely manner.
    We seek comment on our proposed payment operations and timeline and 
alternative considered.
(4) Targeted Review
    We believe that CMS calculation errors are possible, and therefore 
IOTA participants should be able to dispute the results of 
calculations.
    Thus, upon receipt of CMS issued notifications of preliminary 
performance assessment and payment calculations, as described in 
section III.C.6.c.(3). of this proposed rule, we propose that IOTA 
participants may appeal via a ``targeted review process,'' defined as 
the process in which an IOTA participant could dispute performance 
assessment and payment calculations made, and issued, by CMS.
    We propose that an IOTA participant would be able to request a 
targeted review for one or more calculations made and issued by CMS 
within the preliminary performance assessment and payment calculations. 
We propose that an IOTA participant would be able to request a targeted 
review for CMS consideration if--
     The IOTA participant believes an error occurred in 
calculations due to data quality or other issues; or
     The IOTA participant believes an error occurred in 
calculations due to misapplication of methodology.
    We propose that an IOTA participant would be required to submit a 
targeted review request within 30 days, or another time period as 
specified by CMS, of receiving its preliminary performance assessment 
and payment calculations from CMS. We also propose the request would 
require supporting information from the IOTA participant, in a form and 
manner specified by CMS. The 30-day window to appeal generally aligns 
with the length of time we have finalized for submitting appeals in 
other CMS models, such as the ETC Model, as well as under the Hospital 
VBP Program, and we believe would allow ample time for IOTA 
participants to separately review CMS calculations.
    We propose that the targeted review process would not provide IOTA 
participants the ability to dispute policy and methodology, as it would 
be limited to the dispute of calculations. Specifically, we propose 
that CMS will not consider targeted review requests regarding, without 
limitation, the following:
     The selection of the kidney transplant hospital to be an 
IOTA participant.
     The attribution of IOTA waitlist patients and the 
attribution of IOTA transplant patients to the IOTA participant, or to 
any other kidney transplant hospital selected for participation in the 
IOTA Model, or to any kidney transplant hospital not selected for 
participation in the IOTA Model.
     The methodology used for determining the achievement 
domain, efficiency domain, and quality domain.
     The methodology used for calculating and assigning points 
for each metric within the achievement domain, efficiency domain, and 
quality domain.
     The methodology used for calculating the payment amount 
per Medicare kidney transplant paid to an IOTA participant.
    We propose that a targeted review request that includes one or more 
of the exclusions under Sec.  512.434(c)(1) could still be reviewed by 
CMS, given that all remaining considerations of the request meet all 
other criteria for consideration by CMS.
    Upon receipt of a targeted review request from an IOTA participant, 
we propose that CMS would conduct an initial assessment and final 
assessment of the targeted review. We believe that this proposal would 
be in line with other CMS models.
    The CMS targeted review initial assessment would determine if the 
targeted review request met the targeted review requirements and 
contained sufficient information to substantiate the request. If the 
request was not compliant with the requirements or required additional 
information, CMS would follow up with IOTA participants to request 
additional information in a form and manner determined by CMS. Any 
additional information that CMS requests from an IOTA participant would 
be due to CMS within 30 days of CMS's request, also in a form and 
manner determined by CMS. An IOTA participant's non-responsiveness to 
the request for additional information from CMS could result in the 
closure of the targeted review request.
    In a final assessment, CMS would determine whether it erred in a 
calculation, as disputed by the IOTA participant.
    CMS's correction of an error may delay the date of payment of an 
IOTA participant's upside risk payments or downside risk payments.
    Were a calculation error to be found as a result of an IOTA 
participant's targeted review request, we would notify the IOTA 
participant within 30 days of any findings in a form and manner 
determined by CMS and resolve and correct the error and discrepancy in 
the amount of the upside risk payment or downside risk payment in a 
time and manner as determined by CMS.
    We propose that targeted review decisions made by CMS would be 
final, unless submitted by the IOTA participant or CMS for a CMS 
Administrator review. We are also proposing to include the 
reconsideration determination process as outlined in proposed Sec.  
512.190 in the IOTA Model.
    We note that if an IOTA participant has regular Medicare FFS claims 
issues or decisions that it wishes to appeal (that is, issues during 
the model performance period with Medicare FFS that are unrelated to 
the model performance and payment calculations and payments), then the 
IOTA participant should continue to use the standard CMS procedures. 
Section 1869 of the Act provides for a process for Medicare 
beneficiaries, providers, and suppliers to appeal certain claims and 
decisions made by CMS.
    We seek comment on our proposals regarding the process by which an 
IOTA participant could request a targeted review of CMS calculations.

[[Page 43575]]

(5) Extreme and Uncontrollable Circumstances
    Events may occur outside the purview and control of the IOTA 
participant that may affect their performance in the model. In the 
event of extreme and uncontrollable circumstances, such as a public 
health emergency, we propose that CMS may reduce the downside risk 
payment, if any, prior to recoupment by an amount determined by 
multiplying the downside risk payment by the percentage of total months 
during the PY affected by an extreme and uncontrollable circumstance, 
by the percentage of attributed patients who reside in an area affected 
by the extreme and uncontrollable circumstance. We are proposing to 
address only the downside risk payment under this policy, as we wish to 
mitigate the harm to entities due to extreme and uncontrollable 
circumstances. We considered applying this policy to upside risk 
payments and final performance scores in the neutral zone, but we 
believe that IOTA participants that have been able to achieve model 
success do not need to be made whole by this policy.
    We propose to apply determinations made under the Quality Payment 
Program with respect to whether an extreme and uncontrollable 
circumstance has occurred, and the affected areas, during the PY. We 
chose the Quality Payment Program to align across Innovation Center 
models and CMS policy. We propose that CMS has the sole discretion to 
determine the time period during which an extreme and uncontrollable 
circumstance occurred and the percentage of attributed patients 
residing in affected areas for the IOTA participant.
    We request comment on our extreme and uncontrollable circumstances 
policy and whether the determinations by the Quality Payment Program 
that an extreme and uncontrollable circumstance has occurred should 
apply to IOTA participants.
7. Data Sharing
a. General
    We expect that IOTA participants would work toward independently 
identifying and producing their own data, through electronic health 
records, health information exchanges, or other means that they believe 
are necessary to best evaluate the health needs of their patients, 
improve health outcomes, and produce efficiencies in the provision and 
use of services.
    To assist IOTA participants in this process, we propose to provide 
IOTA participants with certain beneficiary-identifiable data for their 
Medicare beneficiaries who are attributed patients, upon request. We 
anticipate that IOTA participants would use this data to better assess 
transplant readiness and post-transplant outcomes. We also propose to 
provide certain aggregate data that has been de-identified in 
accordance with the HIPAA Privacy Rule, 45 CFR 164.514(b), as discussed 
below, for the purposes of helping IOTA participants understand their 
progress towards the model's performance metrics.
    Specifically, subject to the limitations discussed in this proposed 
rule, and in accordance with applicable law, including the HIPAA 
Privacy Rule, we propose that CMS may offer an IOTA participant an 
opportunity to request certain Medicare beneficiary-identifiable data 
and reports as discussed in section III.C.7.b of this proposed rule. We 
propose that CMS would share beneficiary identifiable data with IOTA 
participants on the condition that the IOTA participants, their IOTA 
collaborators, and other individuals or entities performing functions 
or services related to the IOTA participant's activities observe all 
relevant statutory and regulatory provisions regarding the appropriate 
use of data and the confidentiality and privacy of individually 
identifiable health information, and comply with the terms of the data 
sharing agreement described in this section of the proposed rule.
    We propose that the beneficiary-identifiable claims data described 
in section III.C.7.b of this proposed rule would omit individually 
identifiable data for Medicare beneficiaries who have opted out of data 
sharing with the IOTA participant, as described in section III.C.7.c of 
this proposed rule. We also note that, for the beneficiary-identifiable 
claims data, we would exclude information that is subject to the 
regulations governing the confidentiality of substance use disorder 
patient records (42 CFR part 2) from the data shared with an IOTA 
participant.
b. Beneficiary-Identifiable Data
(1) Legal Authority To Share Beneficiary-Identifiable Data
    We believe that an IOTA participant may need access to certain 
Medicare beneficiary-identifiable data for the purposes of evaluating 
its performance, conducting quality assessment and improvement 
activities, conducting population-based activities relating to 
improving health or reducing health care costs, or conducting other 
health care operations listed in the first or second paragraph of the 
definition of ``health care operations'' under the HIPAA Privacy Rule, 
45 CFR 164.501.
    We propose that, subject to providing the beneficiary with the 
opportunity to decline data sharing as described in section III.C.10.a 
of this proposed rule, and subject to having a valid data sharing 
agreement in place, an IOTA participant may request from CMS certain 
beneficiary identifiable claims for attributed patients who are 
Medicare beneficiaries.
    We recognize there are sensitivities surrounding the disclosure of 
individually identifiable (beneficiary-specific) health information, 
and several laws place constraints on the sharing of individually 
identifiable health information. For example, section 1106 of the Act 
generally bars the disclosure of information collected under the Act 
without consent unless a law (statute or regulation) permits the 
disclosure. Here, the HIPAA Privacy Rule would allow for the proposed 
disclosure of individually identifiable health information by CMS.
    Under the HIPAA Privacy Rule, covered entities (defined in 45 CFR 
160.103 as health care plans, health care providers that submit certain 
transactions electronically, and health care clearinghouses) are barred 
from using or disclosing individually identifiable health information 
(called ``protected health information'' or PHI) in a manner that is 
not explicitly permitted or required under the HIPAA Privacy Rule, 
without the individual's authorization. The Medicare FFS program, a 
``health plan'' function of the Department, is subject to the HIPAA 
Privacy Rule limitations on the disclosure of PHI without an 
individual's authorization. IOTA participants are also covered 
entities, provided they are health care providers as defined by 45 CFR 
160.103 and they or their agents electronically engage in one or more 
HIPAA standard transactions, such as for claims, eligibility or 
enrollment transactions. In light of these relationships, we believe 
that the proposed disclosure of the beneficiary-identifiable data under 
the IOTA model would be permitted by the HIPAA Privacy Rule under the 
provisions that permit disclosures of PHI for ``health care 
operations'' purposes. Under those provisions, a covered entity is 
permitted to disclose PHI to another covered entity for the recipient's 
health care operations purposes if both covered entities have or had a 
relationship with the subject of the PHI to be disclosed, the PHI 
pertains to that relationship, and the recipient will use the PHI for a 
``health care

[[Page 43576]]

operations'' function that falls within the first two paragraphs of the 
definition of ``health care operations'' in the HIPAA Privacy Rule (45 
CFR 164.506(c)(4)).
    The first paragraph of the definition of health care operations 
includes ``conducting quality assessment and improvement activities, 
including outcomes evaluation and development of clinical guidelines,'' 
and ``population-based activities relating to improving health or 
reducing health costs, protocol development, case management and care 
coordination.'' The second paragraph of the definition of health care 
operations includes ``evaluating practitioner and provider 
performance'' (45 CFR 164.501).
    Under our proposal, IOTA participants would be using the data on 
their patients to evaluate the performance of the IOTA participant and 
other providers and suppliers that furnished services to the patient, 
conduct quality assessment and improvement activities, and conduct 
population-based activities relating to improved health for their 
patients. When done by or on behalf of a covered entity, these are 
covered functions and activities that would qualify as ``health care 
operations'' under the first and second paragraphs of the definition of 
health care operations at 45 CFR 164.501. Hence, as previously 
discussed, we believe that this provision is extensive enough to cover 
the uses we would expect an IOTA participant to make of the 
beneficiary-identifiable data and would be permissible under the HIPAA 
Privacy Rule. Moreover, our proposed disclosures would be made only to 
HIPAA covered entities that have (or had) a relationship with the 
subject of the information, the information we would disclose would 
pertain to such relationship, and those disclosures would be for 
purposes listed in the first two paragraphs of the definition of 
``health care operations.'' Finally, the proposed disclosures would be 
limited to beneficiary-identifiable data that we believe would meet 
HIPAA requirements in 45 CFR 164.502(b) to limit PHI to the minimum 
necessary to accomplish the intended purpose of the use, disclosure, or 
request.
    The Privacy Act of 1974 also places limits on agency data 
disclosures. The Privacy Act applies when Federal agencies maintain 
systems of records by which information about an individual is 
retrieved by use of one of the individual's personal identifiers 
(names, Social Security numbers, or any other codes or identifiers that 
are assigned to the individual). The Privacy Act generally prohibits 
disclosure of information from a system of records to any third party 
without the prior written consent of the individual to whom the records 
apply (5 U.S.C. 552a(b)).
    ``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 believe that the proposed 
data disclosures are consistent with the purposes for which the data 
discussed in this rule was collected, and, thus, would not run afoul of 
the Privacy Act, provided we ensure that an appropriate Privacy Act 
system of records ``routine use'' is in place prior to making any 
disclosures. The systems of records from which CMS would share data are 
the Medicare Integrated Data Repository (IDR) and the Health Resources 
and Services Administration (HRSA) Organ Procurement and 
Transplantation Network (OPTN)/Scientific Registry of Transplant 
Recipients (SRTR) Data System. We believe that the proposed data 
disclosures are consistent with the purposes for which the data 
discussed in the proposed rule were collected and may be disclosed in 
accordance with the routine uses applicable to those records.
    We propose that CMS would share the following beneficiary-
identifiable lists and data with IOTA participants that have submitted 
a formal request for the data. Under our proposal, the request must be 
submitted on an annual basis in a manner and form and by a date 
specified by CMS. The request also would need to identify the data 
being requested and include an attestation that (A) the IOTA 
participant is requesting this beneficiary-identifiable data as a HIPAA 
covered entity or as a business associate, as those terms are defined 
at 45 CFR 160.103, to the IOTA participant's providers and suppliers 
who are HIPAA covered entities; and (B) the IOTA participant's request 
reflects the minimum data necessary for the IOTA participant to conduct 
health care operations work that falls within the first or second 
paragraph of the definition of health care operations at 45 CFR 
164.501. In addition, IOTA participants who request this data must have 
a valid and signed data sharing agreement in place, as described in 
more detail later in this section. We propose that we would make 
available beneficiary-identifiable data as described in section 
III.C.8.b. of this proposed rule for IOTA participants to request for 
purposes of conducting health care operations that falls within the 
first or second paragraph of the definition of health care operations 
at 45 CFR 164.501 on behalf of their attributed patients who are 
Medicare beneficiaries. We believe that access to beneficiary-
identifiable claims data would improve care coordination between IOTA 
participants and other health care providers. Patients can spend months 
in between their visits to the kidney transplant hospital at which they 
are listed, and the post-transplant period is critical to transplant 
success. We believe that improved care coordination would improve 
outcomes and keep patients engaged in their care.
    We also propose that IOTA participants limit the request for 
beneficiary-identifiable claims data to Medicare beneficiaries whose 
name appears on the quarterly attribution list who have been notified 
in compliance with section III.C.10.a. of this proposed rule, and who 
did not decline having their claims data shared with the IOTA 
participant, as proposed in section III.C.7.d. of this proposed rule. 
Finally, we propose that CMS would share beneficiary identifiable data 
with an IOTA participant on the condition that the IOTA participant, 
its IOTA collaborators, and other individuals or entities performing 
functions or services related to the IOTA participant's activities, 
observe all relevant statutory and regulatory provisions regarding the 
appropriate use of data and the confidentiality and privacy of 
individually identifiable health information and comply with the terms 
of the data sharing agreement described in section III.C.7.f. of this 
proposed rule.
(2) Quarterly Attribution Lists
    We propose that this data would include, for the relevant PY, a 
beneficiary attribution report, shared quarterly, that would include a 
list of attributed patients and patients who have been de-attributed 
from the IOTA participant. We propose that the report would include at 
least the following information for each attributed patient: the 
attribution year the attributed patient became attributed to the IOTA 
participant; the effective date of the attributed patient's attribution 
to the IOTA participant; the effective date of the patient's de-
attribution from the IOTA participant and the reason for such removal 
(if applicable); and the attributed patient's data sharing preferences 
made pursuant to section III.C.7.d. of this proposed rule. We propose 
that CMS may include additional information at its discretion in any of 
the quarterly attribution reports as data becomes available. Such

[[Page 43577]]

data may include information from the SRTR or OPTN on waitlist status 
or transplant status.
    We request comment on whether such additional information would be 
beneficial to IOTA participants or whether this information is best 
accessed by the IOTA participant through other means.
(3) Beneficiary-Identifiable Claims Data
    We propose to offer certain beneficiary-identifiable claims data to 
IOTA participants no later than 1 month after the start of each PY, in 
a form and manner specified by CMS. We propose that IOTA participants 
may retrieve this data at any point during the relevant PY and that it 
would include, at a minimum--
     Three years of historical Parts A, B, and D claims data 
files for attributed patients who are Medicare beneficiaries for 36 
months immediately preceding the effective date of the Medicare 
beneficiary's attribution to the IOTA participant;
     Monthly Parts A, B, and D claims data files specified for 
attributed patients who are Medicare beneficiaries; and
     Monthly Parts A, B, and D claims data files for Medicare 
beneficiaries who have been de-attributed from the IOTA participant for 
claims with a date of service prior to the date the Medicare 
beneficiary was removed from attribution to the IOTA participant.
    We propose that CMS would omit from the beneficiary-identifiable 
claims data any substance use disorder patient records subject to 42 
U.S.C. 290dd-2 and the implementing regulations at 42 CFR part 2.
    We believe these data elements would consist of the minimum data 
element necessary for IOTA participants to effectively manage the care 
of Medicare beneficiaries who are attributed patients. Specifically, 
this data would allow IOTA participants to coordinate care across the 
continuum as Medicare beneficiaries who are attributed patients 
transition from IOTA waitlist patients to IOTA transplant patients.
c. Minimum Necessary Data
    We propose IOTA participants must limit their beneficiary-
identifiable data requests to the minimum necessary to accomplish a 
permitted use of the data. We propose the minimum necessary Parts A and 
B data elements may include, but are not limited to, the following data 
elements:
     Beneficiary Identification (ID).
     Procedure code.
     Gender.
     Diagnosis code.
     Claim ID.
     The from and through dates of service.
     The provider or supplier ID.
     The claim payment type.
     Date of birth and death, if applicable.
     Tax Identification Number (TIN).
     National Provider Identification (NPI).
    We propose the minimum necessary Part D data elements may include, 
but are not limited to, the following data elements:
     Beneficiary ID.
     Prescriber ID.
     Drug service date.
     Drug product service ID.
     Quantity dispensed.
     Days supplied.
     Brand name.
     Generic name.
     Drug strength.
     TIN.
     NPI.
     Indication if on formulary.
     Gross drug cost.
    We request comment and feedback on the minimum beneficiary-
identifiable claims data necessary for IOTA participants to request for 
purposes of conducting permissible health care operations purposes 
under this model.
d. Medicare Beneficiary Opportunity To Decline Data Sharing
    As described in section III.C.10.a. of this proposed rule, we 
propose that Medicare beneficiaries must receive notification about the 
IOTA model. We also propose that Medicare beneficiaries must be given 
the opportunity to decline claims data sharing, and instructions on how 
to inform CMS directly of their preference.
    We propose that Medicare beneficiaries would be notified about the 
opportunity to decline claims data sharing through the notifications 
proposed in section III.C.10.a. of this proposed rule. We propose that 
these notifications must state that the IOTA participant may have 
requested beneficiary identifiable claims data about the Medicare 
beneficiary for purposes of its care coordination and quality 
improvement work and/or population-based activities relating to 
improving health or reducing health care costs, and inform the Medicare 
beneficiary how to decline having his or her claims information shared 
with the IOTA participant in the form and manner specified by CMS. We 
propose that Medicare beneficiary requests to decline claims data 
sharing would remain in effect unless and until a beneficiary 
subsequently contacts CMS to amend that request to permit claims data 
sharing with IOTA participants.
    We propose that Medicare beneficiaries may not decline to have the 
aggregate, de-identified data proposed in section III.C.7.f. of this 
proposed rule shared with IOTA participants. We also propose that 
Medicare beneficiaries may not decline to have the: initial attribution 
lists, quarterly attribution lists, and annual attribution 
reconciliation list as proposed in section III.C.4.b.(2)., b.(3). and 
b.(4). of this proposed rule shared with IOTA participants. We note 
that, in accordance with 42 U.S.C. 290dd-2 and its implementing 
regulations at 42 CFR part 2, CMS does not share beneficiary 
identifiable claims data relating to the diagnosis and treatment of 
substance use disorders under this model.
    We note that the proposed opt out provisions discussed in this 
section would relate only to the proposed sharing of beneficiary-
identifiable data between the Medicare program and the IOTA participant 
under the IOTA Model, and are in no way intended to impede existing or 
future data sharing under other authorities or models.
    We request comment and feedback on our proposed policies to enable 
Medicare beneficiaries to decline data sharing.
e. Data Sharing Agreement
(1) General
    As noted in section III.C.7.a. of this proposed rule, we propose 
that, prior to receiving any beneficiary-identifiable data, IOTA 
participants would be required to first complete, sign, and submit--and 
thereby agree to the terms of--a data sharing agreement with CMS. We 
propose that under the data sharing agreement, the IOTA participant 
would be required to comply with the limitations on use and disclosure 
that are imposed by HIPAA, the applicable data sharing agreement, and 
the statutory and regulatory requirements of the IOTA Model. We also 
propose that the data sharing agreement would include certain 
protections and limitations on the IOTA participant's use and further 
disclosure of the beneficiary-identifiable data and would be provided 
in a form and manner specified by CMS. Additionally, we propose that an 
IOTA Participant that wishes to retrieve the beneficiary-identifiable 
data would be required to complete, sign, and submit to CMS a signed 
data sharing agreement at least annually. We believe that it is 
important for the IOTA Participant to complete and submit a signed data 
sharing agreement at least annually so that CMS has up-to-date 
information that the IOTA participant wishes to retrieve the

[[Page 43578]]

beneficiary-identifiable data and information on the designated data 
custodian(s). As described in greater detail later in this section, we 
propose that a designated data custodian would be the individual(s) 
that an IOTA participant would identify as responsible for ensuring 
compliance with all privacy and security requirements and for notifying 
CMS of any incidents relating to unauthorized disclosures of 
beneficiary-identifiable data.
    CMS believes it is important for the IOTA participant to first 
complete and submit a signed data sharing agreement before it retrieves 
any beneficiary-identifiable data to help protect the privacy and 
security of any beneficiary-identifiable data shared by CMS with the 
IOTA participant. As noted previously in this section of the proposed 
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 IOTA participants would be further protected 
in an appropriate fashion.
    We solicit public comment on our proposal to require that the IOTA 
participant agree to comply with all applicable laws and terms of the 
data sharing agreement as a condition of retrieving beneficiary-
identifiable data, and on our proposal that the IOTA participant would 
need to submit the signed data sharing agreement at least annually if 
the IOTA participant wishes to retrieve the beneficiary-identifiable 
data.
(2) Content of the Data Sharing Agreement
    We propose that CMS would share the following beneficiary-
identifiable data with IOTA participants that have requested the data 
and have a valid data sharing agreement in place, as described in more 
detail later in this section. We propose that an IOTA participant that 
wishes to receive beneficiary-identifiable data for its attributed 
patients who are Medicare beneficiaries must also agree to certain 
terms, namely: (1) to comply with the requirements for use and 
disclosure of this beneficiary-identifiable data that are imposed on 
covered entities by the HIPAA regulations at 45 CFR part 160 and part 
164, subparts A and E, and the requirements of the proposed IOTA model; 
(2) to comply with additional privacy, security, breach notification, 
and data retention requirements specified by CMS in the data sharing 
agreement; (3) to contractually bind each downstream participant of the 
beneficiary-identifiable data that is a business associate of the IOTA 
participant, including all IOTA collaborators, to the same terms and 
conditions with the IOTA participant is itself bound in its data 
sharing agreement with CMS as a condition of the business associate's 
receipt of the beneficiary-identifiable data retrieved by the IOTA 
participant under the IOTA model; and (4) that if the IOTA participant 
misuses or discloses the beneficiary-identifiable data in a manner that 
violates any applicable statutory or regulatory requirements or that is 
otherwise non-compliant with the provisions of the data sharing 
agreement, CMS may: (A) deem the IOTA participant ineligible to 
retrieve the beneficiary-identifiable data under paragraph (b) of this 
section for any amount of time; (B) terminate the IOTA participant's 
participation in the IOTA model under Sec.  512.466; and (C) subject 
the IOTA participant to additional sanctions and penalties available 
under the law.
    CMS believes that these proposed terms for sharing beneficiary-
identifiable data with IOTA participants are appropriate and important, 
as CMS must ensure to the best of its ability that any beneficiary-
identifiable data that it shares with IOTA participants would be 
further protected by the IOTA participant, and any business associates 
of the IOTA participant, in an appropriate fashion.
    CMS seeks public comment on the additional privacy, security, 
breach notification, and other requirements that we would include in 
the data sharing agreement. CMS has these types of agreements in place 
as part of the governing documents of other models tested under section 
1115A of the Act and in the Medicare Shared Savings Program. In these 
agreements, CMS typically requires the identification of data 
custodian(s) and imposes certain requirements related to 
administrative, physical, and technical safeguards relating to data 
storage and transmission; limitations on further use and disclosure of 
the data; procedures for responding to data incidents and breaches; and 
data destruction and retention. These provisions would be imposed in 
addition to any restrictions required by law, such as those provided in 
the HIPAA privacy, security, and breach notification regulations. These 
data sharing agreement provisions would not prohibit the IOTA 
participant from making any disclosures of the data otherwise required 
by law.
    CMS also seeks public comment on what specific disclosures of the 
beneficiary identifiable data might be appropriate to permit or 
prohibit under the data sharing agreement. For example, CMS is 
considering prohibiting, in the data sharing agreement, any further 
disclosure, not otherwise required by law, of the beneficiary-
identifiable data to anyone who is not a HIPAA covered entity or 
business associate, as defined in 45 CFR 160.103, or to an individual 
practitioner in a treatment relationship with the attributed patient 
who is a Medicare beneficiary, or that practitioner's business 
associates. Such a prohibition would be similar to that imposed by CMS 
in other models tested under section 1115A of the Act in which CMS 
shares certain beneficiary-identifiable data with model participants 
for their health care operations.
    CMS is considering these possibilities because there exist 
important legal and policy limitations on the sharing of the 
beneficiary-identifiable data and CMS must carefully consider the ways 
in which and reasons for which we would provide access to this data for 
purposes of the IOTA model. CMS believes that some IOTA participants 
may require the assistance of business associates, such as contractors, 
to perform data analytics or other functions using this beneficiary-
identifiable data to support the IOTA participant's review of their 
care management and coordination, quality improvement activities, or 
clinical treatment of IOTA beneficiaries. CMS also believes that this 
beneficiary-identifiable data may be helpful for any HIPAA covered 
entities who are in a treatment relationship with the IOTA beneficiary.
    We seek public comment on how an IOTA participant might need to, 
and want to, disclose the beneficiary-identifiable data to other 
individuals and entities to accomplish the goals of the IOTA model, in 
accordance with applicable law.
    Under our proposal, the data sharing agreement would include other 
provisions, including requirements regarding data security, retention, 
destruction, and breach notification. For example, we are considering 
including, in the data sharing agreement, a requirement that the IOTA 
participant designate one or more data custodians who would be 
responsible for ensuring compliance with the privacy, security and 
breach notification requirements for the data set forth in the data 
sharing agreement; various security requirements like those found in 
participation agreements for other models tested under section 1115A of 
the Act, but no less restrictive than those provided in the relevant 
Privacy

[[Page 43579]]

Act system of records notices; how and when beneficiary-identifiable 
data could be retained by the IOTA participant or its downstream 
recipients of the beneficiary-identifiable data; procedures for 
notifying CMS of any breach or other incident relating to the 
unauthorized disclosure of beneficiary-identifiable data; and 
provisions relating to destruction of the data. These are only examples 
and are not the only terms CMS would potentially include in the data 
sharing agreement.
    We solicit public comment on this proposal to impose certain 
requirements in the IOTA data sharing agreement related to privacy, 
security, data retention, breach notification, and data destruction.
f. Aggregate Data
    We propose that CMS would share certain aggregate performance data 
with IOTA participants in a form and manner to be specified by CMS. 
This aggregate data would be de-identified in accordance with HIPAA 
requirements at 45 CFR 164.514(b) and would include, when available, 
transplant target data.
    We propose that, for the relevant PY, CMS would provide aggregate 
data to the IOTA participant detailing the IOTA participant's 
performance against the transplant target, as described in section 
III.C.5.c.(2). of this proposed rule.
    We seek comment and feedback on our proposal to share aggregate 
data with IOTA participants.
8. Other Requirements
a. Transparency Requirements
(1) Publication of Patient Selection Criteria for Kidney Transplant 
Evaluations
    Transplant hospitals are currently required to use written patient 
selection criteria in determining a patient's suitability for placement 
on the waitlist or a patient's suitability for transplantation per the 
CoP (see 42 CFR part 482.90). If the transplant hospital performs 
living donor transplants, the transplant hospital must use written 
donor selection criteria to determine the suitability of candidates for 
donation.\264\ The patient selection criteria must ensure fair and non-
discriminatory distribution of organs, and the program must document in 
the patient's medical record the patient selection criteria used.\265\ 
Prior to placement on the transplant hospital's waitlist, a prospective 
transplant candidate must receive a psychosocial evaluation, if 
possible.\266\ Before a transplant hospital places a transplant 
candidate on its waitlist, the candidate's medical record must contain 
documentation that the candidate's blood type has been determined.\267\ 
In addition, when a patient is placed on a hospital's waitlist or is 
selected to receive a transplant, the transplant hospital must document 
in the patient's medical record the patient selection criteria 
used.\268\ Currently, the transplant hospital must also provide a copy 
of its patient selection criteria to a transplant patient, or a 
dialysis facility, as requested by the patient or a dialysis facility. 
For living donor selection, the transplant hospital's living donor 
selection criteria must be consistent with the general principles of 
medical ethics.269 270 Transplant hospitals must also ensure 
that a prospective living donor receives a medical and psychosocial 
evaluation, document in the living donor's medical records the living 
donor's suitability for donation, and document that the living donor 
has given informed consent.\271\
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    \264\ https://www.ecfr.gov/current/title-42/section-482.90.
    \265\ Ibid.
    \266\ Ibid.
    \267\ Ibid.
    \268\ Ibid.
    \269\ OPTN. (n.d.). OPTN Policies--Living Donation, Chapter 14. 
https://optn.transplant.hrsa.gov/media/eavh5bf3/optn_policies.pdf.
    \270\ AMA Council on Ethical and Judicial Affairs. (2019). AMA 
Code of Medical Ethics' Opinions on Organ Transplantation. AMA 
Journal of Ethics, 14(3), 204-214. https://doi.org/10.1001/virtualmentor.2012.14.3.coet1-1203.
    \271\ https://www.ecfr.gov/current/title-42/section-482.90.
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    Available data and studies demonstrate that disparities exist for 
patients in underserved communities who seek or are referred for, or 
are evaluated for a transplant and who eventually are placed on a 
transplant waitlist and receive an organ transplant.\272\ For instance, 
the data has shown that White patients are more likely than Black 
patients to be referred for organ transplant, while Black patients are 
less likely than White patients to be referred for transplant 
evaluation.\273\ Racial disparities also exist in transplant wait 
listing, even after correcting for SDOH.\274\ In addition, there are 
sex and gender disparities in access to the kidney transplant waitlist, 
with men more likely to have access compared to women.\275\ Finally, a 
recent article in the Journal of the American Medical Association 
considers how transplant programs factor patient financial resources 
into waitlist decisions.\276\ The authors' review of several studies 
suggest that socioeconomically deprived patients were proportionally 
less likely to be selected for placement on a waitlist for an organ 
transplant. They suggest, based on the strong and consistent 
associations between race and poverty, that ``withholding transplants 
from those with inadequate financial resources equates to an example of 
structural racism in the health care system.'' We refer readers to the 
numerous additional studies regarding disparities in organ 
transplantation and organ donation that are cited throughout this 
proposed rule.
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    \272\ Park, C., Jones, M.-M., Kaplan, S., Koller, F.L., Wilder, 
J.M., Boulware, L.E., & McElroy, L.M. (2022). A scoping review of 
inequities in access to organ transplant in the United States. 
International Journal for Equity in Health, 21(1). https://doi.org/10.1186/s12939-021-01616-x.
    \273\ Epstein, A.M., Ayanian, J.Z., Keogh, J.H., Noonan, S.J., 
Armistead, N., Cleary, P.D., Weissman, J.S., David-Kasdan, J.A., 
Carlson, D., Fuller, J., Marsh, D., & Conti, R.M. (2000). Racial 
Disparities in Access to Renal Transplantation--Clinically 
Appropriate or Due to Underuse or Overuse? New England Journal of 
Medicine, 343(21), 1537-1544. https://doi.org/10.1056/nejm200011233432106.
    \274\ Ng, Y.-H., Pankratz, V.S., Leyva, Y., Ford, C.G., Pleis, 
J.R., Kendall, K., Croswell, E., Dew, M.A., Shapiro, R., Switzer, 
G.E., Unruh, M.L., & Myaskovsky, L. (2019). Does Racial Disparity in 
Kidney Transplant Wait-listing Persist After Accounting for Social 
Determinants of Health? Transplantation, 1. https://doi.org/10.1097/tp.0000000000003002.
    \275\ Ahern, Patrick et al. Sex Disparity in Deceased-Donor 
Kidney Transplant Access by Cause of Kidney Disease. 2021. Clinical 
Journal of the American Society of Nephrology. 16 (2) 241-250, 
https://cjasn.asnjournals.org/content/16/2/241.
    \276\ Wadhwani, S.I., Lai, J.C., & Gottlieb, L.M. (2022). 
Medical Need, Financial Resources, and Transplant Accessibility. 
JAMA, 327(15), 1445. https://doi.org/10.1001/jama.2022.5283.
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    To improve transparency for those looking to gain access to a 
transplant waitlist in the transplant program evaluation processes, we 
propose to require IOTA participants to publicly post, on a website, 
their patient selection criteria for evaluating patients for addition 
to their kidney transplant waitlist by the end of PY 1. We propose to 
finalize this requirement only if it is not redundant with other HHS 
guidance. We also considered requiring that IOTA participants update 
their selection criteria at a certain frequency to ensure that 
attributed patients have the most up to date information. However, we 
are unsure what cadence of update would be most appropriate.
    We solicit public comments on this proposal and on how often the 
selection criteria should be updated by the IOTA participant.
(2) Transparency Into Kidney Transplant Organ Offers
    Those active on a kidney transplant waitlist may receive organ 
offers at any time. However, there is currently no

[[Page 43580]]

requirement for providers to discuss organ offers with their patients. 
A provider may decline an organ offer for any number of reasons; 
however, declining without disclosing the rationale with the patient 
may miss an important opportunity for shared decision-making.
    We propose to add requirements to increase transparency for IOTA 
waitlist patients who are Medicare beneficiaries regarding the volume 
of organ offers received on their behalf while on the waitlist. 
Specifically, we propose that for each month an organ is offered for an 
IOTA waitlist patient who is a Medicare beneficiary, an IOTA 
participant must inform the Medicare beneficiary, on a monthly basis, 
of the number of times an organ is declined on the Medicare 
beneficiary's behalf and the reason(s) for the decline. We are not 
proposing to prescribe the method of this notification, but would 
require that the medical record reflect that the patient received this 
information and the method by which it was delivered (for example, 
mail, email, medical appointment, internet portal/dashboard, etc.). We 
propose that this information must be shared with the IOTA waitlist 
patient who is a Medicare beneficiary, and should be shared, where 
deemed appropriate, with their nephrologist or nephrology professional, 
to provide the opportunity for questions and clarification of 
information.
    Organ offer filters are a tool that transplant programs can use to 
bypass organ offers they would not accept. Offer filters were tested 
during two pilot programs and released nationally in January 2022.\277\ 
We propose that IOTA participants would be required to review 
transplant acceptance criteria and organ offer filters with their IOTA 
waitlist patients who are Medicare beneficiaries at least once every 6 
months that the Medicare beneficiary is on their waitlist. We propose 
that this review may be done on an individual basis in a patient visit, 
via phone, email, or mail. We believe that sharing this information 
with the patient would offer an opportunity for shared decision-making 
between the patient and IOTA participants and may increase the 
patient's quality of care. We propose that Medicare beneficiaries would 
be able to decline this review with the IOTA participant, as some may 
not wish to have this information. We anticipate that the Medicare 
beneficiary may decline this review during their next provider visit or 
over the phone.
---------------------------------------------------------------------------

    \277\ Optimizing Usage of Kidney Offer Filters--OPTN. (n.d.). 
Optn.transplant.hrsa.gov. Retrieved March 11, 2023, from https://optn.transplant.hrsa.gov/policies-bylaws/public-comment/optimizing-usage-of-kidney-offer-filters/.
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    We solicit public comment on whether an alternative frequency of 
sharing of organ offers with the Medicare beneficiary is more 
appropriate. We also solicit comment on whether there is a more 
suitable timeframe and frequency for addressing acceptance criteria 
with attributed patients. Per 42 CFR 482.94(c), and 482.102(a) and (c), 
kidney transplant hospitals currently review these criteria with 
patients upon patient request. Our goal is to provide a balance of 
transparency and patient engagement in this process without being 
overly prescriptive or burdensome. We also recognize that there are 
beneficiaries on the waitlist who may not be eligible to receive an 
organ offer for multiple years, so we seek feedback on whether this 
requirement should be limited to beneficiaries who have received or are 
likely to receive an organ offer in the next year.
(3) Publication of IOTA Participant Results
    In the Specialty Care Models final rule (85 FR 61114), CMS 
established certain general provisions in 42 CFR part 512 subpart A 
that apply to all Innovation Center models. One such general provision 
pertains to rights in data. Specifically, in the Specialty Care Models 
final rule, we stated that to enable CMS to evaluate the Innovation 
Center models as required by section 1115A(b)(4) of the Act and to 
monitor the Innovation Center models pursuant to Sec.  512.150, in 
Sec.  512.140(a) we would use any data obtained in accordance with 
Sec. Sec.  512.130 and 512.135 to evaluate and monitor the Innovation 
Center models (85 FR 61124). We also stated that, consistent with 
section 1115A(b)(4)(B) of the Act, CMS would disseminate quantitative 
and qualitative results and successful care management techniques, 
including factors associated with performance, to other providers and 
suppliers and to the public. We stated that the data to be disseminated 
would include, but would not be limited to, patient de-identified 
results of patient experience of care and quality of life surveys, as 
well as patient de-identified measure results calculated based upon 
claims, medical records, and other data sources. We finalized these 
policies in 42 CFR part 512.140(a).
    Consistent with these provisions, we propose to publish results 
from all PYs of the IOTA Model. Specifically, for each PY, we intend to 
post performance across the achievement domain, efficiency domain, and 
quality domain for each IOTA participant. We would also identify each 
IOTA participant for the PY. The results would be published on the IOTA 
Model website. Given that we have proposed that the IOTA Model would 
include a process for IOTA participants to request a targeted review of 
the calculation of performance score which is calculated based on the 
various rates we intend to publish, CMS anticipates that it would 
publish these rates only after they have been finalized and CMS has 
resolved any targeted review requests timely received from IOTA 
participants under section II.E. of this proposed rule. We believe that 
the release of this information would inform the public about the cost 
and quality of care and about IOTA participants' performance in the 
IOTA Model. This would supplement, not replace, the annual evaluation 
reports that CMS is required to conduct and release to the public under 
section 1115A(b)(4) of the Act.
    We considered requiring IOTA participants to publish their 
performance results on their own websites as well to increase 
transparency; however, we did not want to place additional reporting 
burden on IOTA participants, particularly because we propose that CMS 
would publish the performance results, which should be adequate.
    We seek comment on our intent to post this information to our 
website, as well as the information we intend to post and the manner 
and timing of the posting.
b. Health Equity Data Reporting
(1) Demographic Data Reporting
    As previously discussed in section III.B. of this proposed rule, 
and throughout this proposed rule, disparities exist throughout the 
transplant process. These circumstances highlight the importance of 
data collection and analysis that includes race, ethnicity, language, 
disability, sexual orientation, gender identity, and sex 
characteristics or other demographics by health care facilities. Such 
data are necessary for integration of health equity in quality 
programs, because the data permits stratification by patient 
subpopulation.278 279 Stratified data can produce meaningful 
measures that can be used to expose

[[Page 43581]]

health disparities, develop focused interventions to reduce them, and 
monitor performance to ensure interventions to improve care do not have 
unintended consequences for certain patients.\280\ Furthermore, quality 
programs are carried out with well-known and widely used standardized 
procedures, including but not limited to, root cause analysis, plan-do-
study-act (PDSA) cycles, health care failure mode effects analysis, and 
fish bone diagrams. These are common approaches in the health care 
industry to uncover the causes of problems, show the potential causes 
of a specific event, test a change that is being implemented, prevent 
failure by correcting a process proactively, and identify possible 
causes of a problem and sort ideas into useful categories, 
respectively.281 282 283 284 Adding a health equity prompt 
to these standardized procedures integrates a health equity lens within 
the quality structure and cues considerations of the patient 
subpopulations who receive care and services from a transplant 
hospital.\285\
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    \278\ IOM (Institute of Medicine). 2009. Race, Ethnicity, and 
Language Data: Standardization for Health Care Quality Improvement 
(p.287). The National Academies Press https://www.ahrq.gov/sites/default/files/publications/files/iomracereport.pdf.
    \279\ Sivashanker, K., & Gandhi, T.K. (2020). Advancing Safety 
and Equity Together. New England Journal of Medicine, 382(4), 301-
303. https://doi.org/10.1056/nejmp1911700.
    \280\ Weinick, R.M., & Hasnain-Wynia, R. (2011). Quality 
Improvement Efforts Under Health Reform: How To Ensure That They 
Help Reduce Disparities--Not Increase Them. Health Affairs, 30(10), 
1837-1843. https://doi.org/10.1377/hlthaff.2011.0617.
    \281\ American Society for Quality. (2019). What is root cause 
analysis (RCA)? Asq.org. https://asq.org/quality-resources/root-cause-analysis.
    \282\ Agency for Healthcare Research and Quality. (2020). Plan-
Do-Study-Act (PDSA) directions and examples. www.ahrq.gov. https://www.ahrq.gov/health-literacy/improve/precautions/tool2b.html.
    \283\ Failure Modes and Effects Analysis (FMEA) Tool [verbar] 
IHI--Institute for Healthcare Improvement. (2017). www.ihi.org. 
https://www.ihi.org/resources/Pages/Tools/FailureModesandEffectsAnalysisTool.aspx.
    \284\ Kane, R. (2014). How to Use the Fishbone Tool for Root 
Cause Analysis. https://www.cms.gov/medicare/provider-enrollment-and-certification/qapi/downloads/fishbonerevised.pdf.
    \285\ Sivashanker, K., & Gandhi, T.K. (2020). Advancing Safety 
and Equity Together. New England Journal of Medicine, 382(4), 301-
303. https://doi.org/10.1056/nejmp1911700.
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    To align with other Innovation Center efforts, we considered 
proposing that, beginning with the first PY and each PY thereafter, 
each IOTA participant would be required to collect and report to CMS 
demographic and SDOH data pursuant to 42 CFR part 403.1110(b) for the 
purposes of monitoring and evaluating the model. We considered 
proposing that, in conducting the collection required under this 
section, the IOTA participant would make a reasonable effort to collect 
demographic and social determinants of health data from all attributed 
patients but, in the case the IOTA participant attributed patient 
elects not to provide such data to the IOTA participant, the IOTA 
participant would indicate such election by the attributed patient in 
its report to CMS.
    We decided not to propose the collection of demographic data as 
this data is already collected by OPOs and the SRTR, thereby making 
such a requirement for purposes of this model potentially duplicative 
and unnecessarily burdensome. We wish to minimize reporting burden on 
IOTA participants where possible to ensure sufficient time and effort 
is spent adjusting to the requirements of a mandatory model.
    We solicit public comment on the decision not to propose the 
collection of this data and potential applications.
(2) Health Related Social Needs (HRSN) Data Reporting
    The Innovation Center is charged with testing innovations that 
improve quality and reduce the cost of health care. There is strong 
evidence that non-clinical drivers of health are the largest 
contributor to health outcomes and are associated with increased health 
care utilization and costs.286 287 These individual-level, 
adverse social conditions that negatively impact a person's health or 
healthcare are referred to as ``health-related social needs'' or 
HRSNs.\288\ CMS aims to expand the collection, reporting, and analysis 
of standardized HRSNs data in its efforts to drive quality improvement, 
reduce health disparities, and better understand and address the unmet 
social needs of patients. Standardizing HRSN Screening and Referral as 
a practice can inform larger, community-wide efforts to ensure the 
availability of and access to community services that are responsive to 
the needs of Medicare beneficiaries.
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    \286\ Booske, B.C., Athens, J.K., Kindig, D.A., Park, H., & 
Remington, P.L. (2010). County Health Rankings (Working Paper). 
https://www.countyhealthrankings.org/sites/default/files/differentPerspectivesForAssigningWeightsToDeterminantsOfHealth.pdf.
    \287\ ROI Calculator for Partnerships to Address the Social 
Determinants of Health Review of Evidence for Health-Related Social 
Needs Interventions. (2019). https://www.commonwealthfund.org/sites/default/files/2019-07/COMBINED-ROI-EVIDENCE-REVIEW-7-1-19.pdf.
    \288\ Medicare Program; End-Stage Renal Disease Prospective 
Payment System, Payment for Renal Dialysis Services Furnished to 
Individuals with Acute Kidney Injury, End-Stage Renal Disease 
Quality Incentive Program, and End- Stage Renal Disease Treatment 
Choices model NPRM (citing A Guide to Using the Accountable Health 
Communities Health-Related Social Needs Screening Tool) 87 FR 38554 
(June 28, 2022).
---------------------------------------------------------------------------

    HRSN screening is becoming increasingly common nationally, but 
implementation is not uniform across geography or health care setting. 
A literature review of national surveys measuring prevalence of social 
screening found that almost half of State Medicaid agencies have 
established managed care contracting requirements for HRSN screening in 
Medicaid.\289\ It also found that health care payers and/or delivery 
organizations reported a screening prevalence of 55-77 percent, with 
``the highest estimate reported among American Hospital Association 
member hospitals.'' \290\ Despite screening proliferation and generally 
positive views toward screening among both patients and health care 
providers, implementation of screening and referral policies for 
beneficiaries of CMS programs with similar health--and even 
demographic--profiles may be inconsistent, potentially exacerbating 
disparities in the comprehensiveness and quality of care.
---------------------------------------------------------------------------

    \289\ De Marchis, E., Brown, E., Aceves, B., Loomba, V., Molina, 
M., Cartier, Y., Wing, H., Ma, L., & Gottlieb. (n.d.). State of the 
Science of Screening in Healthcare Settings siren State of the 
Science on Social Screening in Healthcare Settings Summer 2022. 
https://sirenetwork.ucsf.edu/sites/default/files/2022-06/final%20SCREEN%20State-of-Science-Report%5B55%5D.pdf.
    \290\ Ibid.
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    One of the goals stated in the Innovation Center Strategy Refresh 
for advancing system transformation is to require all new models to 
collect and report demographic and SDOH data. Thus, in addition to the 
proposed health equity requirements in section III.C.8.b. of this 
proposed rule, we considered proposing a requirement that IOTA 
participants conduct HRSN screening for at least four core areas--food 
security, housing, transportation, and utilities. We recognize these 
areas as some of the most common barriers to kidney transplantation and 
the most pertinent for the IOTA participant patient population. 
However, given the need for a psychosocial evaluation prior to addition 
to the waitlist, we understand that such a requirement may be redundant 
given current clinical practices, we have refrained from making such a 
proposal.
    We seek comment on whether we should include a requirement for IOTA 
participants to conduct HRSN screening and report HRSN data in a form 
and manner specified by CMS each PY for their attributed patients. We 
are seeking input on following the questions in this section, and 
comment on any aspect of the psychosocial evaluation of waitlisted 
patients and how this compares to HRSN screenings for the four 
domains--food security, housing, transportation, and utilities. Even if 
CMS were to adopt an HRSN screening and reporting requirement in the 
final rule, CMS might consider delaying the implementation of such a 
requirement.

[[Page 43582]]

     When evaluating a patient for potential addition to the 
kidney transplant waitlist, what questions are asked as part of the 
psychosocial evaluation?
     How might a psychosocial evaluation compare to an HRSN 
screening? What HRSNs are identified as part of a psychosocial 
evaluation?
     What data is collected from the psychosocial evaluation on 
HRSNs?
     If HRSNs are identified as part of the evaluation process, 
what, if any, steps are taken to assist the patient in addressing these 
needs and improving their transplant readiness?
     If HRSNs are identified of a patient already on the 
transplant waitlist, how might this affect their status on the 
transplant waitlist? Could a patient be removed from the transplant 
waitlist if HRSNs are identified that may impact transplant readiness?
     What, if any, follow-up is conducted with waitlist 
patients that have identified HRSNs?
     Are there any concerns with HRSN screening and data 
collection requirements?
c. Health Equity Plans
    To further align with other Innovation Center models and promote 
health equity across the transplant process, we propose that, for PY 2 
through PY 6, each IOTA participant must submit to CMS, in a form and 
manner and by the date(s) specified by CMS, a health equity plan. Given 
that this would be a mandatory model, we propose that the health equity 
plan be voluntary in the first PY of the model to allow IOTA 
participants time to adjust to model requirements. We propose that the 
health equity plan must:
     Identify target health disparities. We propose to define 
``target health disparities'' as health disparities experienced by one 
or more communities within the IOTA participant's population of 
attributed patients that the IOTA participant would aim to reduce.
     Identify the data sources used to inform the 
identification of target health disparities.
     Describe the health equity plan intervention. We propose 
to define ``health equity plan intervention'' as the initiative(s) the 
IOTA participant would create and implement to reduce target health 
disparities.
     Include a resource gap analysis. We propose to define 
``resource gap analysis'' as the resources needed to implement the 
health equity plan interventions and identifies any gaps in the IOTA 
participant's current resources and the additional resources that would 
be needed.
     Include a health equity project plan. We propose to define 
``health equity project plan'' as the timeline for the IOTA participant 
to implement the IOTA participant's the health equity plan.
     Identify health equity plan performance measure(s). We 
propose to define ``health equity performance plan measure(s)'' as one 
or more quantitative metrics that the IOTA participant would use to 
measure the reductions in target health disparities arising from the 
health equity plan interventions.
     Identify health equity goals and describes how the IOTA 
participant would use the health equity goals to monitor and evaluate 
progress in reducing targeted health disparities. We propose to define 
``health equity goals'' as targeted outcomes relative to the health 
equity plan performance measures for the first PY and all subsequent 
PYs.
    We propose that once an IOTA participant submits their health 
equity plan to CMS, CMS will use reasonable efforts to approve or 
reject the health equity plan within 60 business days. We propose that 
if CMS approves the IOTA participant's health equity plan, the IOTA 
participant must engage in activities related to the execution of the 
IOTA participant's health equity plan, including implementing health 
equity plan interventions and monitoring and evaluating progress in 
reducing target health disparities. Discrimination on the basis of 
race, ethnicity, national origin, religion, or gender in activities 
related to the execution of the IOTA participant's health equity plan 
would be prohibited.
    Should CMS determine that the IOTA participant's health equity plan 
does not satisfy the proposed requirements and is inconsistent with the 
applicable CMS Health Equity Plan guidance, does not provide sufficient 
evidence or documentation to demonstrate that the health equity plan is 
likely to accomplish the IOTA participant's intended health equity 
goals, or is likely to result in program integrity concerns or 
negatively impact beneficiaries' access to quality care, we propose 
that CMS may reject the health equity plan or require amendment of the 
health equity plan at any time, including after its initial submission 
and approval.
    We propose that if CMS rejects the IOTA participant's health equity 
plan, in whole or in part, the IOTA participant must not, and must 
require its IOTA collaborators to not, conduct health equity activities 
identified in the health equity plan that have been rejected by CMS.
    We propose that in PY 3, and each subsequent PY, in a form and 
manner and by the date(s) specified by CMS, each IOTA participant would 
be required to submit to CMS an update on its progress in implementing 
its health equity plan. This update would be required to include all of 
the following:
     Updated outcomes data for the health equity plan 
performance measure(s).
     Updates to the resource gap analysis.
     Updates to the health equity project plan.
    We propose that if an IOTA participant fails to meet the 
requirements of the heath equity plan described in this section of the 
proposed rule, the IOTA participant would be subject to remedial action 
as specified in section III.C.16. of this proposed rule. Such remedial 
actions could include: corrective action such as recoupment of any 
upside risk payments; or termination from the model.
    We solicit feedback on these proposals. We also solicit comment on 
the potential impact of creation of a health equity plan, whether such 
plans should be voluntary, and whether health equity plans should only 
be a requirement in later PYs of the IOTA Model.
9. Overlap With Other Innovation Center Models, CMS Programs, and 
Federal Initiatives
a. Other Innovation Center Models and CMS Programs
    We propose that IOTA participants would be allowed to 
simultaneously participate in IOTA and other CMS programs and models. 
The IOTA Model would overlap with several other CMS programs and models 
and Departmental regulatory efforts, and we seek comment on our 
proposals to account for overlap.
    KCC Model--The KCC Model is a voluntary Innovation Center model for 
nephrologists, dialysis facilities, transplant providers, and other 
providers and suppliers that are focused on beneficiaries with CKD and 
beneficiaries with ESRD. The KCC Model performance period began on 
January 1, 2022, and is scheduled to end December 31, 2026. As such, 
the KCC Model would run concurrently for 2 years with the IOTA Model, 
which would have a proposed start date of January 1, 2025. The KCC 
Model includes a payment incentive called the Kidney Transplant Bonus 
(KTB). KCC participants are eligible for up to $15,000 for every 
aligned beneficiary

[[Page 43583]]

with CKD or ESRD who receives a kidney transplant, whether from a 
living or deceased donor, provided the transplant remains successful. 
Kidney Contracting Entities (KCEs) participating in the KCC Model are 
also required to include a transplant provider, defined as a transplant 
program that provides kidney transplants, a transplant hospital that 
provides kidney transplants, a transplant surgeon who provides kidney 
transplants, a transplant nephrologist, a transplant nephrology 
practice, an OPO, or another Medicare-enrolled provider or supplier 
that provides kidney transplant related covered services to Medicare 
beneficiaries.
    Though transplant hospitals are one of the types of health care 
provider eligible to serve as a transplant provider, CMS has found 
relatively low participation by transplant hospitals in the KCC Model. 
Across the 100 KCEs participating in the model in 2023, there were only 
10 kidney transplant hospitals participating in the model and serving 
as the transplant provider for the relevant KCE. In discussions with 
participants and with kidney transplant hospitals, CMS heard a few 
reasons for this relatively low rate of participation. CMS heard that 
it was difficult administratively for kidney transplant hospitals to 
participate as they are part of corporate entities that may have a 
larger organizational focus on broader shared savings efforts, rather 
than just for the kidney population.
    We propose that any providers or suppliers participating in the KCC 
Model that meet the proposed IOTA participant eligibility requirements 
would still be required to participate in the IOTA Model. We believe 
that granting an exemption to the IOTA Model for these providers or 
suppliers could disrupt the patterns of care being tested in the KCC 
Model. We also believe that a prohibition on dual participation could 
prevent enough KCEs from having a transplant provider and meeting model 
requirements, which could undermine participation in the KCC model.
    We considered proposing that any transplant hospitals participating 
in the IOTA Model would not be able to participate in the KCC Model and 
be able to receive any portion of a Kidney Transplant Bonus payment. 
However, we did not believe this was necessary given that there are 
currently only 10 transplant hospitals participating in the KCC Model, 
meaning that dual participation should not substantially affect the 
evaluation of either model. We also considered proposing that any 
kidney transplant for an aligned beneficiary that results in a Kidney 
Transplant Bonus being paid out in the KCC Model would not be counted 
for calculating an upside risk payment or downside risk payment in the 
IOTA Model. We decided not to propose this policy because of potential 
disruption to the KCC Model, which would be in its fourth performance 
year when the proposed IOTA Model would likely begin in 2025. 
Additionally, the Kidney Transplant Bonus payment in the KCC Model 
serves multiple functions within that model, as it also incentivizes 
post-transplant care for up to 3 years post-transplant.
    We believe that it is important to test both the IOTA Model and the 
KCC Model, to test the effectiveness of payment incentives for kidney 
transplants at different points of the care coordination process. The 
IOTA Model would test the effect of upside and downside risk payments 
for kidney transplant hospitals, while the KCC Model tests how 
nephrologists and other providers and suppliers can support 
transplantation in the overall care coordination process. Upside risk 
payment and downside risk payment from the IOTA Model would not be 
counted as expenditures for purposes of the KCC Model, as they would 
not be adjustments to claims for individual beneficiaries, but would be 
paid out in a lump sum based on aggregate performance directly tied to 
individual beneficiary level claims. Additionally, we do not want to 
potentially hurt KCC participants that have beneficiaries who could 
benefit from the KCC participant's potential high performance in the 
IOTA Model.
    Both the KCC Model and the IOTA Model would include explicit 
incentives for participants when aligned beneficiaries receive kidney 
transplants; and a transplant hospital participating in both models 
would be eligible to receive a portion of a Kidney Transplant Bonus 
from a KCE under the KCC Model and an upside risk payment or downside 
risk payment under the IOTA Model. Kidney transplants represent the 
most desired and cost-effective treatment for most beneficiaries with 
ESRD, but providers and suppliers may currently have insufficient 
financial incentives to assist beneficiaries through the transplant 
process because dialysis generally results in higher reimbursement over 
a more extended period of time than a transplant. As a result, CMS 
believes it would be appropriate to allow a transplant hospital to 
receive both an upside risk payment or downside risk payment from the 
IOTA Model and portion of a Kidney Transplant Bonus from the KCC Model 
and the IOTA Model simultaneously to assess their effects on the 
transplant rate.
    ETC Model--The ETC Model is a mandatory Innovation Center model 
that includes as participants certain clinicians who manage dialysis 
patients (referred to as Managing Clinicians) and ESRD facilities and 
provides incentives for increasing rates of home dialysis, transplant 
waitlisting, and living donor transplantation. The ETC Model began on 
January 1, 2021, and the model performance period is scheduled to end 
December 31, 2025, and it would have one year of overlap with the 
proposed model performance period of the IOTA Model beginning January 
1, 2025. The ETC Model includes an upward or downward payment 
adjustment called the Performance Payment Adjustment (PPA) that is 
calculated in part based on the rates of transplant waitlisting and 
living donor transplants for the population of beneficiaries aligned to 
a participating Managing Clinician or ESRD facility.
    We believe that the goals of the ETC Model and the goals of the 
proposed IOTA Model are aligned. As CMS described in the 2020 rule 
finalizing the ETC Model (85 FR 61114), ``[t]he ETC Model [is] a 
mandatory payment model focused on encouraging greater use of home 
dialysis and kidney transplants.'' We believe that the IOTA Model would 
then test a corresponding incentive on the transplant hospital side to 
further assist beneficiaries in moving through the transplant process 
to get a transplant. CMS believes it is appropriate to test both models 
as the ETC Model does not include direct incentives for transplant 
hospitals and we believe that transplant hospitals play a very 
important role in the transplant process.
    We note for the ETC Model, participants are selected based on their 
location in a Selected Geographic Area, which are randomly selected 
Hospital Referral Regions (HRR), stratified by census region, 
representing approximately one third of the country, as well as HRRs 
predominately comprised of ZIP codes in Maryland. This is a different 
randomization strategy than is being proposed for the IOTA Model. It is 
our intent to look at the effects of each model and its randomization 
strategy on the transplant rate as part of our model evaluation, which 
is discussed in section III.C.12 of this proposed rule.
    Additionally, we note that the ETC Model includes the ETC Learning 
Collaborative as part of its model test. This is further discussed in 
section III.C.13. of this proposed rule, where we seek feedback about 
the experience of

[[Page 43584]]

kidney transplant hospitals, OPOs, ETC Participants, and other 
interested parties engaged in the ETC Learning Collaborative, as we 
consider how to best promote shared learning in the IOTA Model.
    Other Medicare Alternative Payment Models (APMs)--For the Medicare 
Shared Savings Program (the Shared Savings Program) and the ACO 
Realizing Equity, Access, and Community Health (ACO REACH) Model, which 
focus on total cost of care, payment adjustments made under the IOTA 
Model would not be counted as program expenditures. The Medicare Shared 
Savings Program regulations address payments under a model, 
demonstration, or other time-limited program when defining program 
expenditures. Specifically, when calculating Shared Savings and Shared 
Losses for an ACO in the Shared Savings Program, CMS considers only 
``individually beneficiary identifiable final payments made under a 
demonstration, pilot, or time limited program'' to be a part of the 
ACO's Medicare Parts A and B fee-for-service expenditures (see, for 
example, 42 CFR 425.605(a)(5)(ii)). Similarly, in the ACO REACH Model, 
an ACO's performance year expenditure is defined to include the total 
payment that has been made by Medicare fee-for-service for services 
furnished to REACH Beneficiaries (see ACO REACH Model First Amended and 
Restated Participation Agreement (Dec. 1, 2023)). Payments under the 
IOTA Model are not directly tied to any specific beneficiary. Instead, 
they are made on a lump sum basis based on aggregate performance across 
transplant patients seen by the center during the performance year. 
IOTA Model payments, therefore, would not be considered by the Shared 
Savings Program as an amount included in Part A or B fee-for-service 
expenditures or by the ACO REACH Model as an amount included in payment 
for REACH Beneficiaries' Medicare fee-for-service services.
    Hospital VBP Program--CMS adjusts payments to hospitals under the 
Inpatient Prospective Payment System (IPPS) based on their performance 
under the Hospital VBP Program. However, the Hospital VBP Program does 
not currently include any measures related to transplant services. In 
addition, transplant services are only offered by a subset of 
hospitals. Given the different focuses between the Hospital VBP Program 
and the IOTA Model, we are not proposing any changes to the Hospital 
VBP Program and believe it is appropriate to test the IOTA Model 
alongside the existing Hospital VBP Program.
b. Overlap With Departmental Regulatory Efforts
    December 2020 OPO Conditions for Coverage--In December 2020, CMS 
issued a final rule entitled ``Organ Procurement Organizations 
Conditions for Coverage: Revisions to the Outcome Measure Requirements 
for Organ Procurement Organizations; Final Rule'' (85 FR 77898). The 
final rule revised the OPO CfCs and was intended to increase donation 
rates and organ transplantation rates by replacing the previous outcome 
measures. In general, the new outcome measures improve on the prior 
measures by using objective, transparent, and reliable data, rather 
than OPO self-reported data, to establish the donor potential in the 
OPO's DSA. The rule also permits CMS to begin decertifying 
underperforming OPOs beginning in 2026.
    We believe that the proposed IOTA Model supports the policies set 
out in that final rule. We note that we have received feedback from 
OPOs and other interested parties that OPOs are required to procure 
more organs, while there is not a corresponding incentive on the 
transplant hospital side to transplant more organs into beneficiaries. 
We also note that the number of discarded organs has risen from 21 
percent to 25 percent from 2018 to 2022.\291\ Though there have been 
other changes during that time, including the updated organ allocation 
system and the effects of the COVID-19 pandemic, this rise in discarded 
organs is highly concerning, and we believe that the IOTA Model can 
help to mitigate this troubling rise by giving transplant hospitals an 
incentive to accept more offers that they may not have accepted without 
that incentive.
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    \291\ Sumit Mohan, Miko Yu, Kristen L. King, S. Ali Husain, 
Increasing Discards as an Unintended Consequence of Recent Changes 
in United States Kidney Allocation Policy, Kidney International 
Reports, Volume 8, Issue 5, 2023, Pages 1109-1111, ISSN 2468-0249, 
https://doi.org/10.1016/j.ekir.2023.02.1081.
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    In September 2019, CMS finalized a rule entitled ``Medicare and 
Medicaid Programs; Regulatory Provisions to Promote Program Efficiency, 
Transparency, and Burden Reduction; Fire Safety Requirements for 
Certain Dialysis Facilities; Hospital and Critical Access Hospital 
(CAH) Changes To Promote Innovation, Flexibility, and Improvement in 
Patient Care'' (84 FR 51732). This rule was in part motivated by a 
commitment across CMS and HHS to ``the vision of creating an 
environment where agencies incorporate and integrate the ongoing 
retrospective review of regulations into Department operations to 
achieve a more streamlined and effective regulatory framework.''
    One of the major provisions finalized in this rule was the removal 
of data submission, clinical experience, and outcomes requirements for 
Medicare re-approval that were previously required of transplant 
hospitals participating in the Medicare program. As described in the 
rule, CMS had put in place additional CoPs in the March 2007 final rule 
(72 FR 15198) in an effort to increase the quality of care by 
specifying minimal health and safety standards for transplant 
hospitals. In addition, outcome metrics (1 year graft and patient 
survival) were included in the regulation and mirrored the OPTN 
outcomes metrics as calculated by the SRTR.
    CMS removed the outcomes requirements for a few key reasons. First, 
the concern was that transplant centers were also subject to OPTN 
policies, so parallel regulation on the CMS side was duplicative. 
Additionally, the concern was that ``increased emphasis on organ and 
patient survival rates, as key metrics of transplant performance, 
created incentives for transplant programs to select organs most likely 
to survive after transplant without rejection, and to select recipients 
most likely to survive after the transplant.'' This focus had the 
effect of creating ``performance standards that focused only on organ 
and patient survival rates for those who received a transplant, not on 
survival rates of patients awaiting transplant.'' \292\
---------------------------------------------------------------------------

    \292\ https://www.federalregister.gov/d/2019-20736/p-87.
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    In December 2021, CMS published an RFI entitled ``Health and Safety 
Requirements for Transplant Programs, Organ Procurement Organizations, 
and End-Stage Renal Disease Facilities'' (86 FR 68594).\293\ In this 
RFI, CMS asked questions about the overall transplant ecosystem, with 
goal of helping ``to inform potential changes that would create system-
wide improvements, which would further lead to improved organ donation, 
organ transplantation, quality of care in dialysis facilities, and 
improved access to dialysis services.''
---------------------------------------------------------------------------

    \293\ Request for Information; Health and Safety Requirements 
for Transplant Programs, Organ Procurement Organizations, and End-
Stage Renal Disease Facilities. https://www.federalregister.gov/documents/2021/12/03/2021-26146/request-for-information-health-and-safety-requirements-for-transplant-programs-organ-procurement.
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    We noted that we were seeking ways to harmonize policies across the

[[Page 43585]]

primary HHS agencies (CMS, HRSA, and the Food and Drug Administration 
(FDA)) that are involved in regulating stakeholders in the transplant 
ecosystem so that our requirements are not duplicative, conflicting, or 
overly burdensome. We asked if there any current requirements for 
transplant programs, ESRD facilities, or OPOs that are unnecessarily 
duplicative of, or in conflict with, OPTN policies or policies that are 
covered by other government agencies. We also asked about the impacts 
of these duplicative requirements on organ utilization and transplant 
program/ESRD facility/OPO quality and efficiency (86 FR 68596).
    Given the concerns described in these past efforts, the OPTN has 
been in part responsive to concerns from interested parties about their 
metrics and effects and has expanded which metrics they are evaluating 
transplant centers for their performance. In December 2021, the OPTN 
approved four new risk-adjusted metrics to be used to monitor 
transplant program performance, including 90-day graft survival hazard 
ratio, 1-year conditional graft survival hazard ratio, pre-transplant 
mortality rate ratio, and offer acceptance ratio.\294\ This added two 
new metrics for areas beyond simply looking at transplant survival, and 
looked at a more holistic view of patient care for beneficiaries on the 
transplant list. There is a critical role for both the Department and 
the OPTN with regard to the transplant ecosystem. The final rule 
governing the operation of the OPTN from 1996 (63 FR 16296) stated the 
following:
---------------------------------------------------------------------------

    \294\ OPTN Board adopts new transplant program performance 
metrics--OPTN. (2021, December 16). Optn.transplant.hrsa.gov. 
Retrieved May 30, 2023, from https://optn.transplant.hrsa.gov/news/optn-board-adopts-new-transplant-program-performance-metrics/.
---------------------------------------------------------------------------

    The Department believes that the transplantation network must be 
operated by professionals in the transplant community, and that both 
allocation and other policies of the OPTN should be developed by 
transplant professionals, in an open environment that includes the 
public, particularly transplant patients and donor families. It is not 
the desire or intention of the Department to interfere in the practice 
of medicine. This rule does not alter the role of the OPTN to use its 
judgment regarding appropriate medical criteria for organ allocation 
nor is it intended to circumscribe the discretion afforded to doctors 
who must make the difficult judgments that affect individual patients. 
At the same time, the Department has an important and constructive role 
to play, particularly on behalf of patients. Human organs that are 
given to save lives are a public resource and a public trust.
    We believe that the proposed IOTA Model recognizes the goals of the 
Department on behalf of the public and the medical judgment exhibited 
by the OPTN. We believe that constructing this as a model test would 
enable the Department to test out a different approach to incentivize 
certain behavior for transplant centers, while also acknowledging the 
role of the OPTN and transplant professionals in this area.
    We note the concern put forward by kidney transplant hospitals that 
they would not be able to increase their number of transplants without 
potentially affecting their performance 90 day and 1-year graft 
survival rate metrics used by the MPSC. However, we believe that there 
are several different ways that IOTA participants would ultimately be 
able to succeed under the IOTA Model and OPTN policies:
     The MPSC standard represents a standard far below the 
national average of performance that should be able to be met by member 
transplant centers. The MPSC describes this as meaning that to be 
identified for outcomes review in a document describing their 
Performance Reviews,\295\ ``[t]he adult criteria is based on the 
likelihood that the program's performance was at least 75 percent worse 
than an average program, accounting for differences in the types of 
recipients and donor organs transplanted. The pediatric criterion is 
based on the likelihood that the program's performance was at least 60 
percent worse than an average program, accounting for differences in 
the types of recipients and donor organs transplanted. Even if a 
program meets one or both of the criteria for graft survival, the MPSC 
may not send the program an inquiry based on various situations, such 
as recent release from review for outcomes or program membership 
status.'' This represents a minimum standard of care and only a small 
percentage were flagged for not meeting those standards.
---------------------------------------------------------------------------

    \295\ https://optn.transplant.hrsa.gov/media/5j5dov5s/what_to_expect_performance_reviews.pdf.
---------------------------------------------------------------------------

     The IOTA Model incentivizes investment in both living and 
deceased donor transplants. Living donor transplantation has rates that 
have been relatively flat for 20 years and has recipients of those 
organs with better post-transplant outcomes.
     MPSC outcomes metrics are risk adjusted based on organ 
quality and can account for the use of organs that are currently being 
discarded.
     Many organs currently being discarded are quality organs. 
Though the median KDRI of discarded kidneys was higher for discarded 
kidneys than transplanted kidneys, there is a large overlap in the 
quality of discarded and transplanted kidneys.\296\
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    \296\ Mohan, S., Chiles, M.C., Patzer, R.E., Pastan, S.O., 
Husain, S.A., Carpenter, D.J., Dube, G.K., Crew, R.J., Ratner, L.E., 
& Cohen, D.J. (2018). Factors leading to the discard of deceased 
donor kidneys in the United States. Kidney International, 94(1), 
187-198. https://doi.org/10.1016/j.kint.2018.02.016.
---------------------------------------------------------------------------

     Per 42 CFR 121.10(c)(1), the reviews conducted by the OPTN 
result in an advisory opinion to the Secretary of a recommended course 
of action. The Secretary then has the option under 42 CFR 121.10(c)(2) 
of requesting additional information, declining to accept the 
recommendation, accepting the recommendation, or taking such other 
action as the Secretary deems necessary. Given the enforcement 
discretion given to the Secretary, the Secretary may take into account 
performance on the metrics evaluated in the IOTA Model as part of a 
holistic evaluation of transplant hospital performance.
    Additionally, CMS also considered, but is not proposing, a limited 
waiver of section 1138(a)(1)(B) of the Act as part of the IOTA Model, 
which requires that a hospital be a member and abide by the rules and 
requirements of the OPTN. We considered retaining transplant hospitals' 
membership obligations to the OPTN with the exception of their required 
responsiveness to MPSC transplant hospital performance reviews and the 
potential for adverse actions that may risk a transplant hospital's 
operations and reimbursement by Federal health insurance programs. 
However, we do not believe that this waiver is necessary for testing 
the model, and that a transplant hospital can perform on both the 
metrics put forward by the MPSC and demonstrate successful performance 
in the IOTA Model.
    We invite public comments on our proposals to account for overlaps 
with other CMS programs and models.
10. Beneficiary Protections
a. Beneficiary Notifications
    We propose to require IOTA participants to provide notice to 
attributed patients that the IOTA participant is participating in the 
IOTA Model. We believe it would be important for IOTA participants to 
provide attributed patients with a standardized, CMS-developed, 
beneficiary notice to limit the potential for fraud and abuse, 
including patient steering. We intend to provide a notification 
template that IOTA

[[Page 43586]]

participants would be required to use. This template would, at minimum, 
indicate content that the IOTA participant would not be permitted to 
change and would indicate where the IOTA participant could insert its 
own content. It would also include information regarding the attributed 
patient's ability to opt-out of data sharing with IOTA participants and 
how they may opt out if they choose to do so.
    We propose requiring IOTA participants to display a notice 
containing these rights and protections prominently at each office or 
facility locations where an attributed patient may receive treatment, 
in a clear manner on its public facing website, and to each attributed 
patient in a paper format. This would increase the probability that the 
attributed patients would receive and take note of this information.
    We seek comment on the proposed requirements for beneficiary 
notifications.
b. Availability of Services and Beneficiary Freedom of Choice
    If finalized, we propose the Standard Provisions for Innovation 
Center Models relating to availability of services and beneficiary 
freedom of choice would apply to the IOTA Model. These provisions were 
originally finalized as general provisions in the Code of Federal 
Regulations (42 CFR part 512 subpart A) that applied to specific 
Innovation Center models, but are separately proposed in this proposed 
rulemaking in section II.B of this proposed rule for expansion to all 
Innovation Center Models with performance periods that begin on or 
after January 1, 2025. Consistent with these proposed provisions, IOTA 
participants would need to preserve beneficiary freedom of choice and 
continue to make medically necessary covered services available to 
beneficiaries to the extent required by applicable law.
11. Financial Arrangements and Attributed Patient Engagement Incentives
a. Background
    We believe it is necessary to provide IOTA participants with 
flexibilities that could support their performance in the IOTA Model 
and allow for greater support for the needs of attributed patients. 
These flexibilities are outlined in this section and include the 
ability to engage in financial arrangements to share IOTA upside risk 
payments and responsibility for paying Medicare for IOTA downside risk 
payments with providers and suppliers making contributions to the IOTA 
participants' performance against model metrics, and the availability 
of the provision of attributed patient engagement incentives. Such 
flexibilities would allow IOTA participants to share all or some of the 
payments they may be eligible to receive from CMS and to share the 
responsibility for the funds needed to pay CMS providers and suppliers 
engaged in caring for attributed patients, if those providers and 
suppliers have a role in the IOTA participant's spending or quality 
performance. Additionally, we believe that IOTA participants caring for 
attributed patients may want to offer attributed patient engagement 
incentives to encourage adherence to recommended treatment and active 
patient engagement in recovery. These incentives may help an IOTA 
participant reach their quality and efficiency goals for the model, 
while also benefitting beneficiaries' health and the Medicare Trust 
Fund if the IOTA participant improves the quality and efficiency of 
care that results in the Medicare beneficiary's reductions in hospital 
readmissions, complications, days in acute care, and mortality, while 
recovery continues uninterrupted or accelerates.
b. Overview of IOTA Model Financial Arrangements
    We believe that IOTA participants may wish to enter into financial 
arrangements with providers and suppliers caring for attributed 
patients to share model upside risk payments or downside risk payments, 
to align the financial incentives of those providers and suppliers with 
the IOTA Model goals of increasing the number of kidney transplants 
furnished to attributed patients to lower costs and to improve their 
quality of life. To do so, we expect that IOTA participants would 
identify key providers and suppliers caring for attributed patients in 
their communities and DSAs. The IOTA participants could establish 
partnerships with these providers and suppliers to promote 
accountability for the quality, cost, and overall care for attributed 
patients, including managing and coordinating care; encouraging 
investment in infrastructure, enabling technologies, and redesigning 
care processes for high quality and efficient service delivery; and 
carrying out other obligations or duties under the IOTA Model. These 
providers and suppliers may invest substantial time and other resources 
in these activities, yet they would neither be the direct recipients of 
any model upside risk payments from Medicare, nor directly responsible 
for paying to CMS any downside risk payments incurred. Therefore, we 
believe it is possible that an IOTA participant that may receive an 
upside risk payment from Medicare or may need to pay a downside risk 
payment to Medicare may want to enter into financial arrangements with 
other providers or suppliers to share these performance adjustments 
with the IOTA participant.
    We expect that all financial relationships established between IOTA 
participants and providers or suppliers for purposes of the IOTA Model 
would only be those permitted under applicable law and regulations, 
including the applicable fraud and abuse laws and all applicable 
payment and coverage requirements. As discussed in section III.C.3 of 
this proposed rule, CMS expects to finalize the proposal that the anti-
kickback statute safe harbor for CMS-sponsored model arrangements (42 
CFR 1001.952(ii)(1)) is available to protect the financial arrangements 
proposed in this section when arrangements with eligible providers and 
suppliers are in compliance with this policy and the conditions for use 
of the anti-kickback statute safe harbor set out at Sec.  
1001.952(ii)(1), if the proposed arrangements are finalized.
    We recognize that there are numerous arrangements that IOTA 
participants may wish to enter other than the financial arrangements 
described in the regulations for which safe harbor protection may be 
extended that could be beneficial to the IOTA participants. For 
example, IOTA participants may choose to engage with organizations that 
are neither providers nor suppliers to assist with matters such as data 
analysis; local provider and supplier engagement; care redesign 
planning and implementation; beneficiary outreach; beneficiary care 
coordination and management; monitoring IOTA participants' compliance 
with the model's terms and conditions; or other model-related 
activities. Such organizations may play important roles in an IOTA 
participant's plans to implement the model based on the experience 
these organizations may bring, such as prior experience with living 
donation initiatives, care coordination expertise, familiarity with a 
particular local community, or knowledge of SRTR data. We expect that 
all relationships established between IOTA participants and these 
organizations for purposes of the model would be those permitted only 
under existing law and regulation, including any relationships that 
would include

[[Page 43587]]

the IOTA participant's sharing of model upside risk payments or 
downside risk payments with such organizations. We would expect these 
relationships to be solely based on the level of engagement of the 
organization's resources to directly support the participants' model 
implementation.
c. IOTA Collaborators
    Given the financial incentives of the IOTA performance-based 
payments, as described in section III.C. of this proposed rule, an IOTA 
participant may want to engage in financial arrangements with providers 
and suppliers making contributions to the IOTA participant's 
performance across the achievement domain, efficiency domain, and 
quality domain. Such arrangements would allow the IOTA participant to 
share monies earned from the upside risk payments. Likewise, such 
arrangements could allow the IOTA participant to share the 
responsibility for the funds needed to repay CMS the downside risk 
payments. We propose to use the term ``IOTA collaborator'' to refer to 
these providers and suppliers.
    Because attributed patients include both those on the kidney 
transplant waitlist and those who have received a kidney transplant, as 
described in section III.C.4.a of this proposed rule, many providers 
and suppliers other than the IOTA participant would furnish related 
services to attributed patients during the model performance period. As 
such, for purposes of the anti-kickback statute safe harbor for CMS-
sponsored model arrangements (42 CFR part 1001.952(ii)), we propose 
that the following types of providers and suppliers that are Medicare-
enrolled and eligible to participate in Medicare may be IOTA 
collaborators:
     Nephrologist.
     ESRD Facility.
     Skilled Nursing Facility (SNF).
     Home Health Agency (HHA).
     Long-Term Care Hospital (LTCH).
     Inpatient Rehabilitation Facility (IRF).
     Physician.
     Nonphysician practitioner.
     Therapist in a private practice.
     Comprehensive Outpatient Rehabilitation Facility (CORF).
     Provider or supplier of outpatient therapy services.
     Physician Group Practice (PGP).
     Hospital.
     Critical Access Hospital (CAH).
     Non-physician provider group practice (NPPGP).
     Therapy Group Practice (TGP).
    We seek comment on the proposed definition of IOTA collaborators 
and any additional Medicare-enrolled providers or suppliers that should 
be included in this definition.
d. Sharing Arrangements
(1) General
    Similar to the Comprehensive Care for Joint Replacement Payment 
Model (CJR) (42 CFR part 510), we propose that certain financial 
arrangements between an IOTA participant and an IOTA collaborator be 
termed ``sharing arrangements.'' For purposes of the anti-kickback 
statute safe harbor for CMS-sponsored model arrangements (Sec.  
1001.952(ii)(1)), we propose that a sharing arrangement would be a 
financial arrangement to share only--(1) the upside risk payment; and 
(2) the downside risk payment.
    Where a payment from an IOTA participant to an IOTA collaborator is 
made pursuant to a sharing arrangement, we define that payment as a 
``gainsharing payment,'' which is discussed in section III.C.11.d.(3). 
of this proposed rule. Where a payment from an IOTA collaborator to an 
IOTA participant is made pursuant to a sharing arrangement, we define 
that payment as an ``alignment payment,'' which is discussed in section 
III.C.11.d.(3). of this proposed rule.
(2) Requirements
    We propose several requirements for sharing arrangements to help 
ensure that their sole purpose is to create financial alignment between 
IOTA participants and IOTA collaborators toward the goals of the model 
while maintaining adequate program integrity safeguards. An IOTA 
participant must not make a gainsharing payment or receive an alignment 
payment except in accordance with a sharing arrangement. We propose 
that a sharing arrangement must comply with the provisions of Sec.  
512.452 and all other applicable laws and regulations, including the 
applicable fraud and abuse laws and all applicable payment and coverage 
requirements.
    We propose that the IOTA participant must develop, maintain, and 
use a set of written policies for selecting providers and suppliers to 
be IOTA collaborators. To safeguard against potentially fraudulent or 
abusive practices, we propose that the selection criteria must include 
the quality of care delivered by the potential IOTA collaborator. We 
also propose that the selection criteria cannot be based directly or 
indirectly on the volume or value of referrals or business otherwise 
generated by, between, or among the IOTA participant, any IOTA 
collaborator, any collaboration agent, or any individual or entity 
affiliated with an IOTA participant, IOTA collaborator, or 
collaboration agent. Additionally, we propose that IOTA participants 
must consider the selection of IOTA collaborators based on criteria 
related to, and inclusive of, the anticipated contribution to the 
performance of the IOTA participant across the achievement domain, 
efficiency domain, and quality domain by the potential IOTA 
collaborator to ensure that the selection of IOTA collaborators takes 
into consideration the likelihood of their future performance.
    It is necessary that IOTA participants have adequate oversight over 
sharing arrangements to ensure that all arrangements meet the 
requirements of this section. Therefore, we propose that the board or 
other governing body of the IOTA participant have responsibility for 
overseeing the IOTA participant's participation in the model, 
including, but not limited to: its arrangements with IOTA 
collaborators, its payment of gainsharing payments, its receipt of 
alignment payments, and its use of beneficiary incentives (as discussed 
in III.C.11.h of this proposed rule).
    Finally, we propose that if an IOTA participant enters a sharing 
arrangement, its compliance program must include oversight of sharing 
arrangements and compliance with the applicable requirements of the 
model. Requiring oversight of sharing arrangements to be included in 
the compliance program provides a program integrity safeguard.
    We seek comment about all provisions described in the preceding 
discussion, including whether additional or different safeguards would 
be needed to ensure program integrity, protect against abuse, and 
ensure that the goals of the model are met.
    We propose that the sharing arrangement must be in writing, signed 
by the parties, and entered into before care is furnished to attributed 
patients during the PY under the sharing arrangement. In addition, 
participation in the sharing arrangement must require the IOTA 
collaborator to comply with the requirements of this model, as those 
pertain to their actions and obligations. Participation in a sharing 
arrangement must be voluntary and without penalty for nonparticipation. 
It is important that providers and suppliers rendering items and 
services to attributed patients during the model performance period 
have the freedom to provide medically necessary items and services to 
attributed patients without any requirement that they participate in a 
sharing arrangement to safeguard

[[Page 43588]]

beneficiary freedom of choice, access to care, and quality of care. The 
sharing arrangement must set out the mutually agreeable terms for the 
financial arrangement between the parties to guide and reward model 
care redesign for future performance across the achievement domain, 
efficiency domain, and quality domain, rather than reflect the results 
of model PYs that have already occurred and where the financial outcome 
of the sharing arrangement terms would be known before signing.
    We propose that the sharing arrangement must require the IOTA 
collaborator and its employees, contractors (including collaboration 
agents), and subcontractors to comply with certain requirements that 
are important for program integrity under the arrangement. We note that 
the terms contractors and subcontractors, respectively, include 
collaboration agents as defined later in this section. The sharing 
arrangement must require all of the individuals and entities in this 
group to comply with the applicable provisions of Sec. Sec.  512.450-
512.466 of this proposed rule, including requirements regarding 
beneficiary notifications, access to records, record retention, and 
participation in any evaluation, monitoring, compliance, and 
enforcement activities performed by CMS or its designees, because these 
individuals and entities all would play a role in model care redesign 
and be part of financial arrangements under the model. The sharing 
arrangement must also require all individuals and entities in the group 
to comply with the applicable Medicare provider enrollment requirement 
at Sec.  424.500 et seq., including having a valid and active TIN or 
NPI, during the term of the sharing arrangement. This is to ensure that 
these individuals and entities have the required enrollment 
relationship with CMS under the Medicare program, although we note that 
they are not responsible for complying with requirements that do not 
apply to them. Finally, the sharing arrangement must require these 
individuals and entities to comply with all other applicable laws and 
regulations.
    We propose that the sharing arrangement must not pose a risk to 
beneficiary access, beneficiary freedom of choice, or quality of care 
so that financial relationships between IOTA participants and IOTA 
collaborators do not negatively impact beneficiary protections under 
the model. The sharing arrangement must require the IOTA collaborator 
to have, or be covered by, a compliance program that includes oversight 
of the sharing arrangement and compliance with the requirements of the 
IOTA Model that apply to its role as an IOTA collaborator, including 
any distribution arrangements, just as we require IOTA participants to 
have a compliance program that covers oversight of the sharing 
arrangement for this purpose as a program integrity safeguard. We seek 
comment on the anticipated effect of the proposed compliance program 
requirement for IOTA collaborators, particularly with regard to 
individual physicians and nonphysician practitioners, small PGPs, 
NPPGPs, and TGPs and whether alternative compliance program 
requirements for all or a subset of IOTA collaborators should be 
adopted to mitigate any effect of the proposal that could make 
participation as an IOTA collaborator infeasible for any provider, 
supplier, or other entity on the proposed list of types of IOTA 
collaborators.
    For purposes of sharing arrangements under the model, we propose to 
define activities related to promoting accountability for the quality, 
cost, and overall care for attributed patients and performance across 
the achievement domain, efficiency domain, and quality domain, 
including managing and coordinating care; encouraging investment in 
infrastructure and redesigned care processes for high quality and 
efficient service delivery; the provision of items and services pre or 
post-transplant in a manner that reduces costs and improves quality; or 
carrying out any other obligation or duty under the model as ``IOTA 
activities.'' In addition to the quality of episodes of care, we 
believe the activities that would fall under this proposed definition 
could encompass the totality of activities upon which it would be 
appropriate for sharing arrangements to value the contributions of 
collaborators and collaboration agents toward meeting the performance 
goals of the model. We seek comment on the proposed definition of IOTA 
activities as an inclusive and comprehensive framework for capturing 
direct care and care redesign that contribute to performance across the 
achievement domain, efficiency domain, and quality domain.
    We propose that the written sharing arrangement agreement must 
specify the following parameters of the arrangement:
     The purpose and scope of the sharing arrangement.
     The identities and obligations of the parties, including 
specified IOTA activities and other services to be performed by the 
parties under the sharing arrangement.
     The date of the sharing arrangement.
     Management and staffing information, including type of 
personnel or contractors that would be primarily responsible for 
carrying out IOTA activities.
     The financial or economic terms for payment, including all 
of the following:
    ++ Eligibility criteria for a gainsharing payment.
    ++ Eligibility criteria for an alignment payment.
    ++ Frequency of gainsharing or alignment payment.
    ++ Methodology and accounting formula for determining the amount of 
a gainsharing payment that is substantially based on performance across 
the achievement domain, efficiency domain and quality domain, and the 
provision of IOTA Model activities.
    ++ Methodology and accounting formula for determining the amount of 
an alignment payment.
    Finally, we propose to require that the terms of the sharing 
arrangement must not induce the IOTA participant, IOTA collaborator, or 
any employees, contractors, or subcontractors of the IOTA participant 
or IOTA collaborator to reduce or limit medically necessary services to 
any attributed patient or restrict the ability of an IOTA collaborator 
to make decisions in the best interests of its patients, including the 
selection of devices, supplies, and treatments. These requirements are 
to ensure that the quality of care for attributed patients is not 
negatively affected by sharing arrangements under the model.
    The proposals for the requirements for sharing arrangements under 
the model are included in Sec.  512.452.
    We seek comment about all of the requirements set out in the 
preceding discussion, including whether additional or different 
safeguards would be needed to ensure program integrity, protect against 
abuse, and ensure that the goals of the model are met.
(3) Gainsharing Payments and Alignment Payments
    We propose several conditions and limitations for gainsharing 
payments and alignment payments as program integrity protections for 
the payments to and from IOTA collaborators. We propose to require that 
gainsharing payments be derived solely from upside risk payments; that 
they be distributed on an annual basis, not more than once per calendar 
year; that they not be a loan, advance payment, or payment for 
referrals or other business; and that they

[[Page 43589]]

be clearly identified as a gainsharing payment at the time they are 
paid.
    We believe that gainsharing payment eligibility for IOTA 
collaborators should be conditioned on two requirements--(1) 
contributing to performance across the achievement domain, efficiency 
domain or quality domain; and (2) rendering items and services to 
attributed patients during the model performance period--as safeguards 
to ensure that eligibility for gainsharing payments is solely based on 
aligning financial incentives for IOTA collaborators with the 
performance metrics of the model. With respect to the first 
requirement, we propose that to be eligible to receive a gainsharing 
payment, an IOTA collaborator must contribute to the performance of the 
IOTA participant across the achievement domain, efficiency domain or 
quality domain during the PY for which the IOTA participant earned the 
upside risk payment that comprises the gainsharing payment. We also 
propose that the contribution to performance across the achievement 
domain, efficiency domain, or quality domain criteria must be 
established by the IOTA participant and directly related to the care of 
attributed patients. With regard to the second requirement, to be 
eligible to receive a gainsharing payment, or to be required to make an 
alignment payment, an IOTA collaborator other than a PGP, NPPGP, or TGP 
must have directly furnished a billable item or service to an 
attributed patient during the same PY for which the IOTA participant 
earned the upside risk payment that comprises the gainsharing payment 
or incurred a downside risk payment. For purposes of this requirement, 
we consider a hospital, CAH or post-acute care provider to have 
``directly furnished'' a billable service if one of these entities 
billed for an item or service for an attributed patient in the same PY 
for which the IOTA participant earned the upside risk payment that 
comprises the gainsharing payment or incurred a downside risk payment. 
The phrase ``PY for which the IOTA participant earned the upside risk 
payment that comprises the gainsharing payment or incurred a downside 
risk payment'' does not mean the year in which the gainsharing payment 
was made. These requirements ensure that there is a required 
relationship between eligibility for a gainsharing payment and the 
direct care for attributed patients during PY for these IOTA 
collaborators. We believe the provision of direct care is essential to 
the implementation of effective care redesign, and the requirement 
provides a safeguard against payments to IOTA collaborators other than 
a PGP, NPPGP, or TGP that are unrelated to direct care for attributed 
patients during the model performance period.
    We propose to establish similar requirements for IOTA 
collaborator's that are PGPs, NPPGPs and TGPs that vary because these 
entities do not themselves directly furnish billable services. To be 
eligible to receive a gainsharing payment or required to make an 
alignment payment, a PGP, NPPGP or TGP must have billed for an item or 
service that was rendered by one or more members of the PGP, NPPGP or 
TGP to an attributed patient the same PY for which the IOTA participant 
earned an upside risk payment that comprises the gainsharing payment or 
incurred a downside risk payment. Like the proposal for IOTA 
collaborators that are not PGPs, NPPGPs or TGPs, these proposals also 
require a link between the IOTA collaborator that is the PGP, NPPGP or 
TGP and the provision of items and services to attributed patients 
during the PY by PGP, NPPGP or TGP members.
    Moreover, we further propose that, because PGPs, NPPGPs and TGPs do 
not directly furnish items and services to patients, to be eligible to 
receive a gainsharing payment or be required to make an alignment 
payment, the PGP, NPPGP or TGP must have contributed to IOTA activities 
and been clinically involved in the care of attributed patients during 
the same PY for which the IOTA participant earned the upside risk 
payment that comprises the gainsharing payment or incurred a downside 
risk payment. For example, a PGP, NPPGP, or TGP could have contributed 
to IOTA activities and been clinically involved in the care of 
attributed patients if they--
     Provided care coordination services to attributed patients 
during and after inpatient admission;
     Engaged with an IOTA participant in care redesign 
strategies, and performed a role in the implementation of such 
strategies, that were designed to improve the quality of care for 
attributed patients; or
     In coordination with other providers and suppliers (such 
as PGP members, NPPGP members, or TGP members; the IOTA participant; 
and post-acute care providers), implemented strategies designed to 
address and manage the comorbidities of attributed patients.
    We propose to limit the total amount of gainsharing payments for a 
PY to IOTA collaborators that are physicians, nonphysician 
practitioners, PGPs, NPPGPs or TGPs. For IOTA collaborators that are 
physicians or nonphysician practitioners, that limit is 50 percent of 
the Medicare-approved amounts under the PFS for items and services 
furnished by that physician or nonphysician practitioner to the IOTA 
participant's attributed patients during the same PY for which the IOTA 
participant earned the upside risk payment that comprises the 
gainsharing payment being made. For IOTA collaborators that are PGPs, 
NPPGPs or TGPs that limit is 50 percent of the Medicare-approved 
amounts under the PFS for items and services billed by the PGP, NPPGP 
or TGP and furnished to the IOTA participant's attributed patients by 
members of the PGP, NPPGP or TGP during the same PY for which the IOTA 
participant earned the upside risk payment that comprises the 
gainsharing payment being made. These limits are consistent with those 
in the CJR model.
    We propose that the amount of any gainsharing payments must be 
determined in accordance with a methodology that is substantially based 
on contribution to performance across the achievement domain, 
efficiency domain, and quality domain and the provision of IOTA 
activities. The methodology may take into account the amount of such 
IOTA activities provided by an IOTA collaborator relative to other IOTA 
collaborators. While we emphasize that financial arrangements may not 
be conditioned directly or indirectly on the volume or value of 
referrals or business otherwise generated by, between or among the IOTA 
participant, any IOTA collaborator, any collaboration agent, or any 
individual or entity affiliated with an IOTA participant, IOTA 
collaborator, or collaboration agent so that their sole purpose is to 
align the financial incentives of the IOTA participant and IOTA 
collaborators toward the model, we believe that accounting for the 
relative amount of IOTA activities by IOTA collaborators in the 
determination of gainsharing payments does not undermine this 
objective. Rather, the proposed requirement allows flexibility in the 
determination of gainsharing payments where the amount of an IOTA 
collaborator's provision of IOTA activities (including direct care) to 
attributed patients during the model performance period may contribute 
to the IOTA participant's upside risk payment that may be available for 
making a gainsharing payment. Greater contributions of IOTA activities 
by one IOTA collaborator versus that result in greater differences in 
the funds available for gainsharing payments may be

[[Page 43590]]

appropriately valued in the methodology used to make gainsharing 
payments to those IOTA collaborators to reflect these differences in 
IOTA activities among them. For example, a physician who is an IOTA 
collaborator who treats 20 attributed patients during the PY that 
result in high quality, less costly care could receive a larger 
gainsharing payment than a physician who is an IOTA collaborator who 
treats 10 attributed patients during episodes that similarly result in 
high quality, less costly care.
    However, we do not believe it would be appropriate to allow the 
selection of IOTA collaborators or the opportunity to make or receive a 
gainsharing payment or an alignment payment to take into the account 
the amount of IOTA activities provided by a potential or actual IOTA 
collaborator relative to other potential or actual IOTA collaborators 
because these financial relationships are not to be based directly or 
indirectly on the volume or value of referrals or business otherwise 
generated by, between, or among the IOTA participant, any IOTA 
collaborator, any collaboration agent, or any individual or entity 
affiliated with an IOTA participant, IOTA collaborator, or 
collaboration agent. Specifically, with respect to the selection of 
IOTA collaborators or the opportunity to make or receive a gainsharing 
payment or an alignment payment, we do not believe that the amount of 
model activities provided by a potential or actual IOTA collaborator 
relative to other potential or actual IOTA collaborators could be taken 
into consideration by the IOTA participant without a significant risk 
that the financial arrangement in those instances could be based 
directly or indirectly on the volume or value of referrals or business 
generated by, between or among the parties. Similarly, if the 
methodology for determining alignment payments was allowed to take into 
the account the amount of IOTA activities provided by an IOTA 
collaborator relative to other IOTA collaborators, there would be a 
significant risk that the financial arrangement could directly account 
for the volume or value of referrals or business generated by, between, 
or among the parties and, therefore, we propose that the methodology 
for determining alignment payments may not directly take into account 
the volume or value of referrals or business generated by, between or 
among the parties.
    We seek comment on this proposal for gainsharing payments, where 
the methodology could take into account the amount of IOTA activities 
provided by an IOTA collaborator relative to other IOTA collaborators. 
We are particularly interested in comments about whether this standard 
would provide sufficient additional flexibility in the gainsharing 
payment methodology to allow the financial reward of IOTA collaborators 
commensurate with their level of effort that achieves model goals. In 
addition, we are interested in comment on whether additional safeguards 
or a different standard is needed to allow for greater flexibility to 
provide certain performance-based payments consistent with the goals of 
program integrity, protecting against abuse and ensuring the goals of 
the model are met.
    We propose that for each PY, the aggregate amount of all 
gainsharing payments that are derived from an upside risk payment must 
not exceed the amount of the upside risk payment paid by CMS. In 
accordance with the prior discussion, no entity or individual, whether 
a party to a sharing arrangement or not, may condition the opportunity 
to make or receive gainsharing payments or to make or receive alignment 
payments, directly or indirectly, on the volume or value of referrals 
or business otherwise generated by, between, or among the IOTA 
participant, any IOTA collaborator, any collaboration agent, or any 
individual or entity affiliated with an IOTA participant, IOTA 
collaborator, or collaboration agent. We propose that an IOTA 
participant must not make a gainsharing payment to an IOTA collaborator 
that is subject to any action for noncompliance with this part or the 
fraud and abuse laws, or for the provision of substandard care to 
attributed patients or other integrity problems. Finally, the sharing 
arrangement must require the IOTA participant to recoup any gainsharing 
payment that contained funds derived from a CMS overpayment on an 
upside risk payment or was based on the submission of false or 
fraudulent data. These requirements provide program integrity 
safeguards for gainsharing under sharing arrangements.
    With respect to alignment payments, we propose that alignment 
payments from an IOTA collaborator to an IOTA participant may be made 
at any interval that is agreed upon by both parties. We propose that 
alignment payments must not be issued, distributed, or paid prior to 
the calculation by CMS of a payment amount reflected in a notification 
of the downside risk payment; loans, advance payments, or payments for 
referrals or other business; or assessed by an IOTA participant if the 
IOTA participant does not owe a downside risk payment. The IOTA 
participant must not receive any amounts under a sharing arrangement 
from an IOTA collaborator that are not alignment payments.
    We also propose certain limitations on alignment payments that are 
consistent with the CJR Model. For a PY, the aggregate amount of all 
alignment payments received by the IOTA participant must not exceed 50 
percent of the IOTA participant's downside risk payment. Given that the 
IOTA participant would be responsible for developing and coordinating 
care redesign strategies in response to its IOTA participation, we 
believe it is important that the IOTA participant retain a significant 
portion of its responsibility for payment to CMS. For example, upon 
receipt of a notification indicating that the IOTA participant owes a 
downside risk payment of $100 to CMS, the IOTA participant would be 
permitted to receive no more than $50 in alignment payments, in the 
aggregate, from its IOTA collaborators. In addition, the aggregate 
amount of all alignment payments from a single IOTA collaborator to the 
IOTA participant may not be greater than 25 percent of the IOTA 
participant's downside risk payment over the course of a single PY for 
an IOTA collaborator. We seek comment on our proposed aggregate and 
individual IOTA collaborator limitations on alignment payments.
    We propose that all gainsharing payments and any alignment payments 
must be administered by the IOTA participant in accordance with 
generally accepted accounting principles (GAAP) and Government Auditing 
Standards (The Yellow Book). Additionally, we propose that all 
gainsharing payments and alignment payments must be made by check, 
electronic funds transfer (EFT), or another traceable cash transaction. 
We seek comment on the effect of this proposal.
    The proposals for the conditions and restrictions on gainsharing 
payments and alignment payments under the model are included in Sec.  
512.452.
    We seek comment about all of the conditions and restrictions set 
out in the preceding discussion, including whether additional or 
different safeguards would be needed to ensure program integrity, 
protect against abuse, and ensure that the goals of the model are met.
(4) Documentation Requirements
    To ensure the integrity of the sharing arrangements, we propose 
that IOTA participants must meet a variety of documentation 
requirements for these arrangements. Specifically, the IOTA participant 
must--

[[Page 43591]]

     Document the sharing arrangement contemporaneously with 
the establishment of the arrangement;
     Maintain accurate current and historical lists of all IOTA 
collaborators, including IOTA collaborator names and addresses. 
Specifically, the IOTA participant must--
    ++ Update such lists on at least a quarterly basis; and
    ++ Publicly report the current and historical lists of IOTA 
collaborators and any written policies for selecting individuals and 
entities to be IOTA collaborators required by the IOTA participant on a 
web page on the IOTA participants website; and
     Maintain and require each IOTA collaborator to maintain 
contemporaneous documentation with respect to the payment or receipt of 
any gainsharing payment or alignment payment that includes at a minimum 
the--
    ++ Nature of the payment (gainsharing payment or alignment 
payment);
    ++ Identity of the parties making and receiving the payment;
    ++ Date of the payment;
    ++ Amount of the payment;
    ++ Date and amount of any recoupment of all or a portion of an IOTA 
collaborator's gainsharing payment; and
    ++ Explanation for each recoupment, such as whether the IOTA 
collaborator received a gainsharing payment that contained funds 
derived from a CMS overpayment of an upside risk payment, or was based 
on the submission of false or fraudulent data.
    In addition, we propose that the IOTA participant must keep records 
for all of the following:
     Its process for determining and verifying its potential 
and current IOTA collaborators' eligibility to participate in Medicare;
     A description of current health information technology, 
including systems to track upside risk payments and downside risk 
payments; and
     Its plan to track gainsharing payments and alignment 
payments.
    Finally, we propose that the IOTA participant must retain and 
provide access to, and must require each IOTA collaborator to retain 
and provide access to, the required documentation in accordance with 
Sec.  512.460 and Sec.  1001.952(ii).
    The proposals for the requirements for documentation of sharing 
arrangements under the model are included in Sec.  512.452(d).
    We seek comment about all of the requirements set out in the 
preceding discussion, including whether additional or different 
safeguards would be needed to ensure program integrity, protect against 
abuse, and ensure that the goals of the model are met.
e. Distribution Arrangements
(1) General
    Similar to the CJR Model, we propose that certain financial 
arrangements between IOTA collaborators and other individuals or 
entities called ``collaboration agents'' be termed ``distribution 
arrangements.'' For purposes of the anti-kickback statute safe harbor 
for CMS-sponsored model arrangements (Sec.  1001.952(ii)(1)), we 
propose to define ``distribution arrangement'' as a financial 
arrangement between an IOTA collaborator that is a PGP, NPPGP or TGP 
and a collaboration agent for the sole purpose of sharing a gainsharing 
payment received by the PGP, NPPGP or TGP. We propose to define 
``collaboration agent'' as an individual or entity that is not an IOTA 
collaborator and that is a member of a PGP, NPPGP, or TGP that has 
entered into a distribution arrangement with the same PGP, NPPGP, or 
TGP in which he or she is an owner or employee, and where the PGP, 
NPPGP, or TGP is an IOTA collaborator. Where a payment from an IOTA 
collaborator that is an PGP, NPPGP, or TGP is made to a collaboration 
agent, under a distribution arrangement, composed only of gainsharing 
payments, we propose to define that payment as a ``distribution 
payment.'' We propose that a collaboration agent could only make a 
distribution payment in accordance with a distribution arrangement that 
complies with the provisions of Sec.  512.454 and all other applicable 
laws and regulations, including the fraud and abuse laws.
    The proposals for the general provisions for distribution 
arrangements under the model are included in Sec.  512.454.
    We seek comment about all of the provisions set out in the 
preceding discussion, including whether additional or different 
safeguards would be needed to ensure program integrity, protect against 
abuse, and ensure that the goals of the model are met.
(2) Requirements
    We propose a number of specific requirements for distribution 
arrangements as a program integrity safeguard to help ensure that their 
sole purpose is to create financial alignment between IOTA 
collaborators and collaboration agents and performance across the 
achievement domain, efficiency domain, and quality domain. These 
requirements largely parallel those proposed in Sec.  512.452 for 
sharing arrangements and gainsharing payments based on similar 
reasoning for these two types of arrangements and payments. We propose 
that all distribution arrangements must be in writing and signed by the 
parties, contain the date of the agreement, and be entered into before 
care is furnished to attributed patients under the distribution 
arrangement. Furthermore, we propose that participation must be 
voluntary and without penalty for nonparticipation, and the 
distribution arrangement must require the collaboration agent to comply 
with all applicable laws and regulations.
    Like our proposal for gainsharing payments, we propose that the 
opportunity to make or receive a distribution payment must not be 
conditioned directly or indirectly on the volume or value of referrals 
or business otherwise generated by, between or among the IOTA 
participant, any IOTA collaborator, any collaboration agent, or any 
individual or entity affiliated with an IOTA participant, IOTA 
collaborator, or collaboration agent. We propose more flexible 
standards for the determination of the amount of distribution payments 
from PGPs, NPPGPs and TGPs for the same reasons we propose this 
standard for the determination of gainsharing payments.
    We note that for distribution payments made by a PGP to PGP 
members, by NPPGPs to NPPGP members, or TGPs to TGP members, the 
requirement that the amount of any distribution payments must be 
determined in accordance with a methodology that is substantially based 
on performance across the achievement domain, efficiency domain, and 
quality domain and the provision of IOTA Model activities may be more 
limiting in how a PGP pays its members than is allowed under existing 
law. Therefore, to retain existing flexibility for distribution 
payments by a PGP to PGP members, we propose that the amount of the 
distribution payment from a PGP to PGP members must be determined in a 
manner that complies with Sec.  411.352(g). This proposal would allow a 
PGP the choice either to comply with the general standard that the 
amount of a distribution payment must be substantially based on 
contribution to the performance across the achievement domain, 
efficiency domain, and quality domain and the provision of IOTA Model 
activities or to provide its members a financial benefit through the 
model without consideration of the PGP member's individual contribution 
to the performance across the achievement

[[Page 43592]]

domain, efficiency domain and quality domain. In the latter case, PGP 
members that are not collaboration agents (including those who 
furnished no services to attributed patients) would be able receive a 
share of the profits from their PGP that includes the monies contained 
in a gainsharing payment. We believe this is an appropriate exception 
to the general standard for determining the amount of distribution 
payment under the model from a PGP to a PGP member, because CMS has 
determined under the physician self-referral law that payments from a 
group practice as defined under Sec.  411.352 to its members that 
comply with Sec.  411.352(g) are appropriate.
    We seek comment on this proposal and specifically whether there are 
additional safeguards or a different standard is needed to allow for 
greater flexibility in calculating the amount of distribution payments 
that would avoid program integrity risks and whether additional or 
different safeguards are reasonable, necessary, or appropriate for the 
amount of distribution payments from a PGP to its members, a NPPGP to 
its members or a TGP to its members.
    Similar to our proposed requirements for sharing arrangements for 
those IOTA collaborators that furnish or bill for items and services, 
except for a distribution payment from a PGP to a PGP member that 
complies with Sec.  411.352(g), we propose that a collaboration agent 
is eligible to receive a distribution payment only if the collaboration 
agent furnished or billed for an item or service rendered to an 
attributed patients during the same PY for which the IOTA participant 
earned the upside risk payment. We note that all individuals and 
entities that fall within our proposed definition of collaboration 
agent may either directly furnish or bill for items and services 
rendered to attributed patients. This proposal ensures that, absent the 
alternative safeguards afforded by a PGP's distribution payments in 
compliance with Sec.  411.352(g), there is the same required 
relationship between direct care for attributed patients during the PY 
and distribution payment eligibility that we require for gainsharing 
payment eligibility. We believe this requirement provides a safeguard 
against payments to collaboration agents that are unrelated to direct 
care for attributed patients during the PY when the amount of the 
distribution payment is not determined in a manner that complies with 
Sec.  411.352(g).
    Except for a distribution payment from a PGP to a PGP member that 
complies with Sec.  411.352(g), we propose the same limitations on the 
total amount of distribution payments to physicians, nonphysician 
practitioners, PGPs, NPPGPs and TGPs as we propose for gainsharing 
payments. In the case of a collaboration agent that is a physician or 
nonphysician practitioner, we propose to limit the total amount of 
distribution payments paid for a PY to the collaboration agent to 50 
percent of the total Medicare-approved amounts under the PFS for items 
and services furnished by the collaboration agent to the IOTA 
participant's attributed patients during the same PY for which the IOTA 
participant earned the upside risk payment that comprises the 
gainsharing payment being distributed. In the case of a collaboration 
agent that is a group practice, we propose that the limit would be 50 
percent of the total Medicare-approved amounts under the PFS for items 
and services billed by the group practice for items and services 
furnished by members of the group practice to the IOTA participant's 
attributed patients during the same PY for which the IOTA participant 
earned the upside risk payment that comprises the gainsharing payment 
being distributed. We believe that, absent the alternative safeguards 
afforded by a group practice's distribution payments in compliance with 
Sec.  411.352(g), these proposed limitations on distribution payments, 
which are the same as those for gainsharing payments to physicians, 
nonphysician practitioners, and group practices, are necessary to 
eliminate any financial incentives for these individuals or entities to 
engage in a financial arrangement as an IOTA collaborator versus as a 
collaboration agent. Furthermore, we believe that group practices 
should be able to choose whether to engage in financial arrangements 
directly with IOTA participants as IOTA collaborators without having a 
different limit on their maximum financial gain from one arrangement 
versus another.
    We further propose that with respect to the distribution of any 
gainsharing payment received by a PGP, NPPGP or TGP, the total amount 
of all distribution payments must not exceed the amount of the 
gainsharing payment received by the IOTA collaborator from the IOTA 
participant. Like gainsharing and alignment payments, we propose that 
all distribution payments must be made by check, electronic funds 
transfer, or another traceable cash transaction. The collaboration 
agent must retain the ability to make decisions in the best interests 
of the patient, including the selection of devices, supplies, and 
treatments. Finally, the distribution arrangement must not induce the 
collaboration agent to reduce or limit medically necessary items and 
services to any Medicare beneficiary or reward the provision of items 
and services that are medically unnecessary.
    We propose that the IOTA collaborator must maintain contemporaneous 
documentation regarding distribution arrangements in accordance with 
Sec.  512.454, including--
     The relevant written agreements;
     The date and amount of any distribution payment(s);
     The identity of each collaboration agent that received a 
distribution payment; and
     A description of the methodology and accounting formula 
for determining the amount of any distribution payment.
    We propose that the IOTA collaborator may not enter into a 
distribution arrangement with any individual or entity that has a 
sharing arrangement with the same IOTA participant. This proposal 
ensures that the proposed separate limitations on the total amount of 
gainsharing payment and distribution payment to PGPs, NPPGPs, TGPs, 
physicians, and nonphysician practitioners that are substantially based 
on performance across the achievement domain, efficiency domain, and 
quality domain and the provision of IOTA activities are not exceeded in 
absolute dollars by a PGP, NPPGP, TGP, physician, or nonphysician 
practitioner's participation in both a sharing arrangement and 
distribution arrangement for the care of the same IOTA beneficiaries 
during the PY. Allowing both types of arrangements for the same 
individual or entity for care of the same attributed patients during 
the PY could also allow for duplicate counting of the individual or 
entity's same contribution to the achievement domain, efficiency 
domain, and quality domain and provision of IOTA Model activities in 
the methodologies for both gainsharing and distribution payments, 
leading to financial gain that is disproportionate to the contribution 
to the achievement domain, efficiency domain and quality domain and 
provision of IOTA Model activities by that individual or entity. 
Finally, we propose that the IOTA collaborator must retain and provide 
access to, and must require collaboration agents to retain and provide 
access to, the required documentation in accordance with Sec.  512.460.
    The proposals for requirements for distribution arrangements under 
the model are included in Sec.  512.454.
    We seek comment about all of the requirements set out in the 
preceding

[[Page 43593]]

discussion, including whether additional or different safeguards would 
be needed to ensure program integrity, protect against abuse, and 
ensure that the goals of the model are met. In addition, we seek 
comment on how the regulation of the financial arrangements under this 
proposal may interact with how these or similar financial arrangements 
are regulated under the Medicare Shared Savings Program.
f. Enforcement Authority
    OIG authority is not limited or restricted by the provisions of the 
model, including the authority to audit, evaluate, investigate, or 
inspect the IOTA participant, IOTA collaborators, collaboration agents, 
or any other person or entity or their records, data, or information, 
without limitations. Additionally, no model provisions limit or 
restrict the authority of any other Government Agency to do the same. 
The proposals for enforcement authority under the model are included in 
Sec.  512.455.
    We seek comment about all of the requirements set out in the 
preceding discussion, including whether additional or different 
safeguards would be needed to ensure program integrity, protect against 
abuse, and ensure that the goals of the model are met.
h. Attributed Patient Engagement Incentives
    We believe it is necessary and appropriate to provide additional 
flexibilities to IOTA participants for purposes of testing the IOTA 
Model to give IOTA participants additional access to the tools 
necessary to improve attributed patients' access to kidney transplants 
and ensure attributed patients receive comprehensive and patient-
centered post-transplant care. As discussed in section III.C.11.i. of 
this proposed rule, CMS expects to make a determination that the anti-
kickback statute safe harbor for CMS-sponsored model patient incentives 
is available to protect Part B and Part D immunosuppressive drug cost 
sharing support and attributed patient engagement incentives proposed 
in this section when the incentives are offered in compliance with this 
policy, specifically the conditions for use of the anti-kickback 
statute safe harbor set out at Sec.  1001.952(ii)(2), if the proposed 
Part B and Part D immunosuppressive drug cost sharing support policy 
and attributed patient engagement incentives are finalized.
(1) Part B and Part D Immunosuppressive Drug Cost Sharing Support
    The cost of immunosuppressive drugs is a financial burden for many 
transplant recipients, particularly those without sufficient health 
insurance coverage.\297\ A person's ability to pay for 
immunosuppressive drugs, among other services needed in the 
perioperative and postoperative periods, is a factor used by transplant 
hospitals to assess suitability for the transplant waitlist.\298\ 
Studies have found that low income status decreases the likelihood of 
waitlisting.\299\ One survey of a transplant programs found that 67.3 
percent of programs surveys reported frequent or occasional failure to 
list patients due to concerns regarding ability to pay for 
immunosuppressive medications.\300\ In assessing the financial 
implications of extending Medicare coverage of immunosuppressive drugs 
for the lifetime of the patient, the Assistant Secretary for Planning 
and Evaluation (ASPE) assumed a non-adherence graft failure rate of 
10.7 percent and assessed that factors outside of affordability had 
minimal impact on non-adherence to immunosuppressive drugs.\301\
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    \297\ James, A., & Mannon, R.B. (2015). The Cost of Transplant 
Immunosuppressant Therapy: Is This Sustainable? Current 
Transplantation Reports, 2(2), 113-121. https://doi.org/10.1007/s40472-015-0052-y.
    \298\ The kidney transplant waitlist. (n.d.). Transplant Living. 
https://transplantliving.org/kidney/the-kidney-transplant-waitlist/.
    \299\ Park, C., Jones, M.-M., Kaplan, S., Koller, F.L., Wilder, 
J.M., Boulware, L.E., & McElroy, L.M. (2022). A scoping review of 
inequities in access to organ transplant in the United States. 
International Journal for Equity in Health, 21(1). https://doi.org/10.1186/s12939-021-01616-x.
    \300\ Evans, R.W., Applegate, W.H., Briscoe, D.M., Cohen, D.J., 
Rorick, C.C., Murphy, B.T., & Madsen, J.C. (2010). Cost-related 
immunosuppressive medication nonadherence among kidney transplant 
recipients. Clinical Journal of the American Society of Nephrology, 
5(12), 2323-2328. https://doi.org/10.2215/cjn.04220510.
    \301\ Assessing the Costs and Benefits of Extending Coverage of 
Immunosuppressive Drugs under Medicare. (n.d.). ASPE. https://aspe.hhs.gov/reports/assessing-costs-benefits-extending-coverage-immunosuppressive-drugs-under-medicare.
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    Between 2016 and 2019, immunosuppressive drugs represented the 
greatest proportion of drug expenditures in the year following kidney 
transplant in Medicare Parts B and D.\302\ Between 2016 and 2019, the 
Per-Patient-Per-Year expenditure in the year following transplant in 
Medicare Parts B and D was $6,947.\303\ Medicare beneficiaries whose 
immunosuppressive drugs are covered by Part B are responsible for 20 
percent of these costs. The cost sharing obligation of Medicare 
beneficiaries whose immunosuppressive drugs are covered by Part D can 
vary depending on the benefit structure of the Part D plan.
---------------------------------------------------------------------------

    \302\ United States Renal Data System. (2022). 2022 USRDS Annual 
Data Report: Epidemiology of kidney disease in the United States. 
National Institutes of Health, National Institute of Diabetes and 
Digestive and Kidney Diseases, Bethesda, MD. https://usrds-adr.niddk.nih.gov/2022.
    \303\ Ibid.
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    We propose to allow IOTA participants to subsidize, in whole or in 
part, the cost sharing associated with immunosuppressive drugs covered 
by Part B, the Part B-ID benefit, and Part D (``Part B and Part D 
immunosuppressive drug cost sharing support'') incurred by attributed 
patients. As discussed in section III.C.11.i. of this proposed rule, if 
this rule is finalized, CMS expects to make a determination that the 
anti-kickback statute safe harbor for CMS-sponsored model patient 
incentives (Sec.  1001.952(ii)(2)) is available to protect the 
reduction of cost sharing obligations that are made in compliance with 
this policy and the conditions for use of the anti-kickback statute 
safe harbor set out at Sec.  1001.952(ii)(2).
    We expect that a large proportion of an IOTA participant's 
attributed patient population would be Medicare ESRD beneficiaries, 
covered either by traditional Medicare or by MA. Most ESRD 
beneficiaries covered by traditional Medicare receive immunosuppressive 
drug coverage through Part B. A proportion of ESRD beneficiaries who 
are not eligible for Part A at the time of the kidney transplant or who 
receive a kidney transplant in a non-Medicare approved facility receive 
immunosuppressive drugs through Medicare Part D. ESRD beneficiaries 
covered by MA receive Part B immunosuppressive drugs through the plan 
in which the beneficiary is enrolled.
    To be eligible for Part B and Part D immunosuppressive drug cost 
sharing support, we are proposing to define eligible attributed patient 
as an attributed patient that receives immunosuppressive coverage 
through Part B or Part D but that does not have secondary insurance 
that could provide cost sharing support. An IOTA participant's 
attributed patient population could include several subsets of eligible 
attributed patients. One subset of eligible attributed patients could 
be ESRD beneficiaries who are not able to purchase secondary insurance 
due to State laws that do not require insurers to sell Medigap plans to 
Medicare Beneficiaries under the age of 65. Another subset of eligible 
attributed

[[Page 43594]]

patients could, under certain conditions, be ESRD beneficiaries whose 
eligibility for Medicare only due to ESRD ends 36 months following a 
kidney transplant. Attributed patients whose eligibility for Medicare 
due to ESRD ends 36 months following a kidney transplant may be 
eligible for the Medicare Part B Immunosuppressive Drug Benefit (Part 
B-ID) depending on the availability of other health coverage options 
such as Medicaid, plans purchased via a State health exchange, or the 
TRICARE for Life program. Other attributed patients whose Medicare 
eligibility due to ESRD concludes 36 months following a transplant 
could choose to return to work and receive immunosuppressive drug 
coverage through an Employer Group Health Plan (EGHP), enroll in a 
Qualified health plan (QHP) under the Affordable Care Act as defined by 
45 CFR 155.20, or receive coverage through Medicaid. These attributed 
patients would not be eligible for Part B and Part D immunosuppressive 
drug cost sharing support. We believe that Part B and Part D 
immunosuppressive drug cost sharing support would have special value 
for attributed patients whose Medicare eligibility due only to ESRD 
ends after 36 months and who are eligible for Medicare Savings Programs 
(MSPs) but who live in States that have not expanded Medicaid 
eligibility for adults to include certain individuals with incomes up 
to 138 percent of the Federal Poverty Level (FPL). These individuals 
may have incomes that are too high to qualify for Medicaid, but too low 
to qualify for advance premium tax credits (APTCs) or cost-sharing 
reductions (CSRs) that would allow them to purchase a QHP. We are not 
proposing that Part B and Part D immunosuppressive drug cost sharing 
support would count towards an eligible attributed patients' Part D 
True Out-of-Pocket (TrOOP). Part B and Part D immunosuppressive drug 
cost sharing support would be reported on the Prescription Drug Event 
(PDE) record as Patient Liability Reduction due to Other Payer Amount 
(PLRO).
    We are proposing to allow IOTA participants to subsidize, in whole 
or in part, the cost sharing associated with immunosuppressive drugs 
covered by Part B, the Part B-ID benefit, and Part D because we believe 
cost sharing associated with medically necessary immunosuppressive 
drugs would represent a significant out-of-pocket cost burden to 
attributed patients who receive immunosuppressive coverage through Part 
B, the Part B-ID benefit, or Part D, and because we believe an IOTA 
participant's attributed patient population would include beneficiaries 
whose immunosuppressive drugs are covered through each of these avenues 
(that is, Part B, the Part B-ID benefit, and Part D).
    We are proposing several safeguards for the proposed Part B and 
Part D immunosuppressive drug cost sharing support policy. First, an 
attributed patient must be eligible to receive cost sharing support 
under the Part B and Part D cost sharing support policy. IOTA 
participants must provide a written policy for Part B and Part D 
immunosuppressive drug cost sharing support in a form and manner 
determined by CMS that is approved by CMS prior to the PY in which the 
cost sharing support would be available and prior to offering 
attributed patients the incentive. An IOTA participant would be 
required to revalidate the written policy with CMS in a form and manner 
determined by CMS prior to each PY in which Part B and Part D 
immunosuppressive drug cost sharing support would be offered 
subsequently. The initial written policy and the policy that would be 
revalidated by CMS must establish and justify the criteria that qualify 
an eligible attributed patient to receive Part B and Part D 
immunosuppressive drug cost sharing support. In providing the written 
policy and the revalidation of the written policy for Part B and Part D 
immunosuppressive drug cost sharing support, the IOTA participant must 
attest that the IOTA participant will not, in providing Part B and Part 
D immunosuppressive drug cost sharing support, take into consideration 
the type, cost, generic status, or manufacturer of the 
immunosuppressive drug(s) or limit an eligible attributed patient's 
choice of pharmacy. We believe these policies are necessary to ensure 
that an IOTA participant would have a sound basis for determining 
eligibility requirements for Part B and Part D immunosuppressive drug 
cost sharing support.
    We are proposing safeguards to protect against an IOTA participant 
preferentially providing cost sharing support for certain 
immunosuppressive drugs. An IOTA participant must not take into 
consideration the type, cost, generic status, or manufacturer of the 
immunosuppressive drug(s) or limit an eligible attributed patients' 
choice of pharmacy when providing Part B and Part D immunosuppressive 
drug cost sharing support. In addition, IOTA participant must not 
accept financial or operational support for the Part B and Part D 
immunosuppressive drug cost sharing support from pharmacies and 
pharmaceutical manufacturers. Immunosuppressive drug regimens are 
adjusted to an individual's unique clinical characteristics to achieve 
a balance between preserving the health of the transplanted organ and 
reducing morbidity associated with long-term immunosuppression. We do 
not believe that the anti-kickback statute safe harbor for CMS-
sponsored model patient incentives should be used to protect 
arrangements that could limit or influence attributed patients' access 
to the most clinically appropriate immunosuppressive drugs. Finally, to 
facilitate compliance monitoring, we are proposing that IOTA 
participants must maintain documentation regarding this beneficiary 
incentive. At minimum, the IOTA participant must maintain 
contemporaneous documentation that includes the identity of the 
eligible attributed patient to whom Part B and Part D immunosuppressive 
drug cost sharing support was provided, the date or dates on which Part 
B and Part D immunosuppressive drug cost sharing support was provided, 
and the amount or amounts of Part B and Part D immunosuppressive drug 
cost sharing support that was provided. IOTA participants must retain 
and provide access to the required documentation consistent with 
section III.C.12 of this proposed rule and Sec.  1001.952(ii)(2).
    We considered alternative safeguards for the Part B and Part D 
immunosuppressive drug cost sharing support policy. We considered 
requiring that an IOTA participant that wishes to offer Part B and Part 
D immunosuppressive drug cost sharing support must offer it to every 
attributed patient whose immunosuppressive drugs are covered by Part B 
or Part D and who does not have secondary insurance. Ultimately, we 
believe such a policy would run counter to our intention to offer IOTA 
participants flexibility to meet the needs of their attributed patient 
populations.
    We also considered alternatives to the entirety of the proposed 
Part B and Part D immunosuppressive cost sharing support policy. We 
considered waiving Medicare payment requirements such that CMS would 
pay the full amount of the Part B or Part B-ID coinsurance for 
immunosuppressive drugs that are medically necessary for preventing or 
treating the rejection of a transplanted organ or tissue. If we were to 
pay 100 percent of the cost of immunosuppressive drugs for attributed 
patients who are Medicare beneficiaries whose immunosuppressive drugs 
are covered by Part B and attributed patients whose immunosuppressive 
drugs are covered by the Part B-ID

[[Page 43595]]

benefit, such attributed patients would have no cost sharing 
obligation. However, we believed that this policy would represent too 
large an impact to the IOTA Model savings estimates, and thus would 
potentially jeopardize our ability to continue to test the IOTA Model, 
if such a policy were finalized.
    We also considered waiving the premium for the Part B-ID benefit. 
Under section 402(d) of the CAA and the implementing regulations at 42 
CFR part 407 subpart D 408.20(f), the Secretary determines and 
promulgates a monthly premium rate for individuals enrolled in the Part 
B-ID benefit that is 15 percent of the monthly actuarial rate for 
beneficiaries who are age 65 and older. The Part B premium for 2024 for 
individuals enrolled in the Part B-ID benefit who file individual or 
joint tax returns with a modified adjusted gross income of less than or 
equal to $103,000 or $206,000 respectively, is $103.00. The Part B-ID 
premium is subject to income-related adjustments based on modified 
adjusted gross income. We believe the Part B-ID benefit monthly premium 
may represent a substantial out-of-pocket expenditure for individuals 
enrolled in the benefit given that it is prudent for the individual to 
acquire additional health insurance to cover other necessary health 
care services outside of immunosuppressive drugs. A premium waiver for 
the Part B-ID benefit is authorized by section 1115A(d)(1) of the Act, 
under which the Secretary may waive provisions of Title XVIII of the 
Act, including provisions of section 1836(b) of the Act, as may be 
necessary solely for purposes of carrying out section 1115A of the Act. 
We believe, however, that waiving the premium for the Part B-ID benefit 
would have too significant an impact on the IOTA Model savings 
estimates; therefore, we are not proposing to waive it for purposes of 
the IOTA Model.
    We seek feedback on the proposal to allow an IOTA participant to 
subsidize the 20 percent coinsurance on immunosuppressive drugs covered 
by Part B or the Part B-ID benefit and the cost sharing associated with 
immunosuppressive drugs covered by Part D, when an attributed patient 
is eligible, meaning the attributed patient does not have secondary 
insurance and meets the eligibility criteria defined by the IOTA 
participant and approved by CMS prior to the PY in which the cost 
sharing support is provided. We are also soliciting input from 
interested parties on additional patient-centered safeguards that we 
may consider to protect cost sharing subsidies made under the proposed 
Part B and Part D immunosuppressive drug cost sharing support policy, 
if finalized.
(2) Attributed Patient Engagement Incentives
    We believe that providing additional flexibilities under the IOTA 
Model would allow IOTA participants to support attributed patients in 
overcoming challenges associated with remaining active on the kidney 
transplant waitlist and adhering to comprehensive post-transplant care. 
Thus, we propose that IOTA participants may offer the following 
attributed patient engagement incentives under certain circumstances:
     Communication devices and related communication services 
directly pertaining to communication with an IOTA participant or IOTA 
collaborator to improve communication between an attributed patient and 
an IOTA participant or IOTA collaborator;
     Transportation to and from a transplant hospital that is 
an IOTA participant and between other providers and suppliers involved 
in the provision of ESRD care;
     Mental health services to address an attributed patient's 
behavioral health symptoms pre- and post-transplant; and
     In-home care to support the health of the attributed 
patient or the kidney transplant in the post-transplant period.
    For the purposes of the proposed attributed patient engagement 
incentives, we are defining post-transplant period to mean the 90-day 
period following an attributed patient's receipt of a kidney 
transplant. We are proposing a 90-day post-transplant period because it 
may take up to 3 months for many individuals to fully recover from a 
kidney transplant.\304\ We are proposing that attributed patient 
engagement incentives that are communication devices and related 
communication services, transportation to and from an IOTA participant 
and between other providers and suppliers involved in the provision of 
ESRD care, and mental health services to address an attributed 
patient's behavioral health symptoms could, under certain circumstances 
described in this section, be offered while an attributed patient is on 
a waitlist, after an attributed patient receives a transplant, or both. 
In-home care to support the health of the attributed patient or the 
kidney transplant may only be offered in the post-transplant period.
---------------------------------------------------------------------------

    \304\ Recovery after transplant surgery [verbar] American Kidney 
Fund. (2021, December 14). Www.kidneyfund.org. https://www.kidneyfund.org/kidney-donation-and-transplant/life-after-transplant-rejection-prevention-and-healthy-tips/recovery-after-transplant-surgery.
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    A mixed methods study of transplant providers' assessment of 
barriers to accessing a kidney transplant found that transportation was 
the most reported impediment to transplant.\305\ Interested parties 
have informed us that transportation to medical appointments pre- and 
post-transplant, as well as to and from the dialysis center for 
treatments pre-transplant, is an important factor in maintaining active 
status on the list and the health of an individual and the graft after 
the transplant. Interested parties have also communicated with us about 
the importance of communication with waitlisted patients. We understand 
it can be common for an individual to not receive important information 
about the kidney transplant process when transplant hospitals and 
dialysis facilities do not communicate with one another about a 
patient's status. We believe we may be able to overcome this challenge 
by providing IOTA participants with greater flexibility to communicate 
directly with attributed patients about their status in the kidney 
transplant process.306 307 We understand that attributed 
patients who face communication and transportation barriers while on 
the kidney transplant waitlist may be inactivated, meaning that the 
attributed patient cannot receive organ offers. An attributed patient 
that cannot receive organ offers is misaligned with the IOTA Model's 
proposed performance assessment methodology, which would encourage an 
IOTA participant to increase its number of transplants. An attributed 
patient that cannot receive organ offers represents a missed 
opportunity for transplant, which is inconsistent with the goals of the 
proposed IOTA Model. Accordingly, we are interested in providing a 
framework under which an IOTA participant would be able to offer 
attributed patient engagement incentives in the form of communication 
devices and related communication services may increase the number of 
attributed patients who achieve and maintain active status on

[[Page 43596]]

the kidney transplant waitlist. We believe the availability of 
transportation to and from an IOTA participant and between other 
providers and suppliers involved in the provision of ESRD care and 
mental health services to address an attributed patient's behavioral 
health symptom may also act in service of assisting more attributed 
patients in overcoming barriers to achieving or maintaining active 
status on a waitlist, among other challenges in the kidney transplant 
process prior to and after receiving a kidney transplant.
---------------------------------------------------------------------------

    \305\ Browne, T., McPherson, L., Retzloff, S., Darius, A., Wilk, 
A.S., Cruz, A., Wright, S., Pastan, S.O., Gander, J.C., Berlin, 
A.A., & Patzer, R.E. (2021). Improving access to kidney 
transplantation: Perspectives from Dialysis and Transplant Staff in 
the Southeastern United States. Kidney Medicine, 3(5). https://doi.org/10.1016/j.xkme.2021.04.017.
    \306\ Ibid.
    \307\ Gillespie, A. (2021). Communication breakdown: Improving 
communication between transplant centers and dialysis facilities to 
improve access to kidney transplantation. Kidney Medicine, 3(5), 
696-698. https://doi.org/10.1016/j.xkme.2021.08.003.
---------------------------------------------------------------------------

    For example, we are also interested in providing greater 
flexibility to IOTA participants to support improved adherence to 
processes of care pre- and post-transplant that may support the ability 
of an attributed patient to accept an organ offer and the outcomes of 
the attributed patient and the graft after receiving a kidney 
transplant. Anxiety and depression may increase as attributed patients 
spend time on the kidney transplant waitlist.\308\ Prevalence of 
depression is reported to decrease after kidney transplant, but may 
still exceed 20 percent.\309\ Interested parties have reported that 
behavioral health symptoms interfere with adherence to care 
recommendations, including activities that support remaining active on 
the transplant waitlist and behaviors that support positive clinical 
outcomes for the patient and the graft after the kidney transplant 
procedure. Interested parties have also informed us of the importance 
of a transplant recipient having the support of another person in the 
home for a short period in the post-transplant period to enhance 
recovery.
---------------------------------------------------------------------------

    \308\ Corruble, E., Durrbach, A., Charpentier, B., Lang, P., 
Amidi, S., Dezamis, A., Barry, C., & Falissard, B. (2010). 
Progressive increase of anxiety and depression in patients waiting 
for a kidney transplantation. Behavioral Medicine, 36(1), 32-36. 
https://doi.org/10.1080/08964280903521339.
    \309\ Szeifert, L., Molnar, M.Z., Ambrus, C., Koczy, A.B., 
Kovacs, A.Z., Vamos, E.P., Keszei, A., Mucsi, I., & Novak, M. 
(2010). Symptoms of depression in kidney transplant recipients: A 
cross-sectional study. American Journal of Kidney Diseases, 55(1), 
132-140. https://doi.org/10.1053/j.ajkd.2009.09.022.
---------------------------------------------------------------------------

    We also believe providing the option for flexibility to offer 
attributed patient engagement incentives under the auspices of the IOTA 
Model would allow IOTA participants to provide attributed patients with 
tools to overcome barriers in the process of receiving a kidney 
transplant, thereby increasing adherence to the kidney transplant 
process, improving post-transplant outcomes, and supporting patient-
centricity in the IOTA Model. As stated in section III.C.11.i. of this 
proposed rule, we expect to make the determination that the anti-
kickback statute safe harbor for CMS-sponsored model patient incentives 
(Sec.  1001.952(ii)(2)) is available to protect the attributed patient 
engagement incentives proposed in this section when the incentives are 
offered or given to the attributed patient solely when the remuneration 
is exchanged between an IOTA participant and an attributed patient in 
compliance with this proposed rule and the conditions of the safe 
harbor for CMS-sponsored model patient incentives.
    We are proposing programmatic requirements for the attributed 
patient engagement incentives. First, an IOTA participant must provide 
a written policy in a form and manner determined by CMS for the 
provision of attributed patient engagement incentives. The IOTA 
participant's written policy must be approved by CMS before the PY in 
which an attributed patient engagement incentive is first made 
available, and must be revalidated by CMS, in a form and manner 
specified by CMS, prior to each PY in which an IOTA participant wishes 
to offer an attributed patient engagement incentive subsequently. The 
IOTA participant's written policy must describe the items or services 
the IOTA participant plans to provide, an explanation of how each item 
or service that would be an attributed patient engagement incentive has 
a reasonable connection to, at minimum, one of the following: (1) 
achieving or maintaining active status on a kidney transplant waitlist; 
(2) accessing the kidney transplant procedure; or (3) the health of the 
attributed patient or the kidney transplant in the post-transplant 
period, and a justification for the need for the attributed patient 
engagement incentives that is specific to the IOTA participant's 
attributed patient population. The IOTA participant's written policy 
must also include an attestation that items that are attributed patient 
engagement incentives would be provided directly to an attributed 
patient, meaning that third parties would be precluded from providing 
an item that is an attributed patient engagement incentive to an 
attributed patient. We are not requiring an IOTA participant to provide 
any such attestation pertaining to services that are attributed patient 
engagement incentives because we acknowledge that services such as 
communication services, mental health services and in-home care 
services are generally provided by third parties. The IOTA participant 
would, however, be required to attest in its written policy that the 
IOTA participant would pay the service provider directly for services. 
Finally, the IOTA participant's written policy must also include an 
attestation that any items or services acquired by the IOTA participant 
that would be furnished as attributed patient engagement incentives 
would be acquired for the minimum amount necessary to for an attributed 
patient to achieve or maintain active status on the waitlist, access 
the kidney transplant procedure, or support the health of the 
attributed patient or the kidney transplant in the post-transplant 
period.
    We are proposing the following restrictions on the provision of 
attributed patient engagement incentives. An IOTA participant must 
include in the written policy approved by CMS prior to offering an 
attributed patient engagement incentive, items that are attributed 
patient engagement incentives must be provided directly to an 
attributed patient and an IOTA participant must pay a service provider 
directly for any services that are offered as attributed patient 
engagement incentives. An IOTA participant must not offer attributed 
patient engagement incentives that are tied to the receipt of items of 
services from a particular provider or supplier or advertise or promote 
items or services that are attributed patient engagement incentives, 
except to make an attributed patient aware of the availability of the 
items or services at the time an attributed patient could reasonably 
benefit from them. An IOTA participant must not receive donations 
directly or indirectly to purchase attributed patient engagement 
incentives. Finally, items that are attributed patient engagement 
incentives must be retrieved from the attributed patient when the 
attributed patient is no longer eligible for that item or at the 
conclusion of the IOTA Model, whichever is earlier. Documented, 
diligent, good faith attempts to retrieve items that are attributed 
patient engagement incentives are deemed to meet the retrieval 
requirement.
    We are proposing the following, additional restrictions pertaining 
to attributed patient engagement incentives that are communication 
devices, because we believe that such items may be especially 
susceptible to abuse. An IOTA participant's purchase of items that are 
communication devices must not exceed $1000 in retail value for any one 
attributed patient in any one PY. Items that are communication devices 
must remain the property of the IOTA participant. An IOTA participant 
must retrieve the item that is a communication device either when the 
attributed patient is no longer eligible for the communication device 
or at the conclusion of the IOTA Model,

[[Page 43597]]

whichever is earlier. Items that are communication devices must be 
retrieved from an attributed patient before another communication 
device may be provided to the same attributed patient. This restriction 
applies across PYs. In other words, an IOTA participant may not offer 
another communication device to the same attributed patient across all 
IOTA model years until the first communication device has been 
retrieved. We believe these additional restrictions on communication 
devices that are offered under the attributed patient engagement 
incentive policy are necessary to ensure that IOTA participants are not 
providing communication devices for purposes that are not aligned with 
the goals of the IOTA Model.
    We are also proposing documentation requirements that pertain to 
the provision of attributed patient engagement incentives. The IOTA 
participant must maintain contemporaneous documentation of items and 
services furnished as attributed patient engagement incentives that 
includes, at minimum, the date an attributed patient engagement 
incentive is provided and the identity of the attributed patient to 
whom the item or service was provided. In accordance with the retrieval 
requirements for items that attributed patient engagement incentives, 
IOTA participants must document all retrieval attempts of items that 
are attributed patient engagement incentives, including the ultimate 
date of retrieval. IOTA participants must retain all records pertaining 
to the furnishing of attributed patient engagement incentives and make 
those records available to the Federal Government in accordance with 
section III.C.12. of this proposed rule.
    Taken together, we believe the safeguards described in this section 
are necessary to ensure that attributed patient engagement incentives 
offered by an IOTA participant are provided in compliance with the 
intent of the proposed policy and the anti-kickback statute safe harbor 
for CMS-sponsored model patient incentives (Sec.  1001.952(ii)(2)).
    We considered not allowing IOTA participants to offer attributed 
patient engagement incentives for attributed patients in the IOTA 
Model, which would simplify the IOTA Model. Further, having no 
attributed patient engagement incentive policy would allow IOTA 
participants to direct available resources to the proposed Part B and 
Part D immunosuppressive drug cost sharing support policy described in 
section III.C.h.(2). of this proposed rule. We took these 
considerations into account; however, we believe allowing for the 
maximum amount of flexibility possible for IOTA participants to meet 
the needs of attributed patients that relate to accessing a kidney 
transplant is consistent with the model's goals. In addition, we were 
unable to find any literature to suggest that one type of item or 
service, for example, cost sharing subsidies under Part B and Part D 
immunosuppressive drug cost sharing, is of greater value to an 
individual waiting for a kidney transplant or having received a kidney 
transplant than another, for example, an attributed patient engagement 
incentive. We also considered including dental services as a service 
that may be offered as an attributed patient engagement incentive. 
Sources of oral infection must be resolved before an individual can 
receive a kidney transplant because post-transplant immunosuppression 
puts a kidney transplant recipient at greater risk for oral infections 
that can spread to the rest of the body.\310\ We did not include dental 
services as an allowable attributed patient engagement incentive 
because we understand that sources of oral infection must be resolved 
before an individual can be waitlisted for a kidney transplant; in 
other words, prior to the ability of an individual to be attributed to 
the IOTA Model. We are interested in receiving comments on the extent 
to which dental issues emerge once an individual has been listed for a 
kidney transplant and whether we should consider dental services as an 
attributed patient engagement incentive under the auspices of the IOTA 
Model.
---------------------------------------------------------------------------

    \310\ Kwak, E.-J., Kim, D.-J., Choi, Y., Joo, D.J., & Park, W. 
(2020). Importance of oral health and dental treatment in organ 
transplant recipients. International Dental Journal, 70(6), 477-481. 
https://doi.org/10.1111/idj.12585.
---------------------------------------------------------------------------

    We are soliciting feedback on our proposal to allow IOTA 
participants to offer attributed patient engagement incentives in a 
manner that complies with the restrictions and safeguards in this 
section. We are further soliciting feedback on other barriers to 
remaining active on the kidney transplant waitlist, receiving organ 
offers, and adhering to pre- and post-transplant care that we may be 
able to address by expanding the attributed patient engagement 
incentives available to attributed patients through future rulemaking.
i. Fraud and Abuse Waiver and OIG Safe Harbor Authority
    Under section 1115A(d)(1) of the Act, the Secretary may waive such 
requirements of Titles XI and XVIII and of sections 1902(a)(1), 
1902(a)(13), 1903(m)(2)(A)(iii) of the Act, and certain provisions of 
section 1934 of the Act as may be necessary solely for purposes of 
carrying out section 1115A of the Act with respect to testing models 
described in section 1115A(b) of the Act.
    For this model and consistent with the authority under section 
1115A(d)(1) of the Act, the Secretary may consider issuing waivers of 
certain fraud and abuse provisions in sections 1128A, 1128B, and 1877 
of the Act. No fraud or abuse waivers are being issued in this 
document; fraud and abuse waivers, if any, would be set forth in 
separately issued documentation. Any such waiver would apply solely to 
the IOTA Model and could differ in scope or design from waivers granted 
for other programs or models. Thus, notwithstanding any provision of 
this proposed rule, IOTA participants and IOTA collaborators must 
comply with all applicable laws and regulations, except as explicitly 
provided in any such separately documented waiver issued pursuant to 
section 1115A(d)(1) of the Act specifically for the IOTA Model.
    In addition to or in lieu of a waiver of certain fraud and abuse 
provisions in sections 1128A and 1128B of the Act, CMS proposes to 
waive sections 1881(b) and 1833(a) and 1833(b) of the Act only to the 
extent necessary to make payments under the IOTA Model. CMS further 
expects to make a determination, if this rule is finalized, that the 
anti-kickback statute safe harbor for CMS-sponsored model arrangements 
and CMS-sponsored model patient incentives (Sec.  1001.952(ii)(1) and 
(2)) is available to protect remuneration exchanged pursuant to certain 
financial arrangements and patient incentives that may be permitted 
under the final rule, if issued. Specifically, we expect to determine 
that the CMS-sponsored models safe harbor would be available to protect 
the following financial arrangements and incentives: the IOTA Model 
Sharing Arrangement's gainsharing payments and alignment payments, the 
Distribution Arrangement's distribution payments, the Part B and Part D 
immunosuppressive drug cost sharing support policy and attributed 
patient engagement incentives.
    We considered not allowing use of the safe harbor provisions. 
However, we determined that use of the safe harbor would encourage the 
goals of the model. We believe that a successful model requires 
integration and coordination among IOTA participants and other health 
care providers and suppliers. We believe the use of the safe harbor 
would encourage and improve beneficiary experience of care and 
coordination of

[[Page 43598]]

care among providers and suppliers. We also believe these safe harbors 
offer flexibility for innovation and customization. The safe harbors 
allow for emerging arrangements that reflect up-to-date understandings 
in medicine, science, and technology.
    We seek comment on this proposal, including that the anti-kickback 
safe harbor for CMS-sponsored model arrangements (Sec.  
1001.952(ii)(1)) be available to IOTA participants and IOTA 
collaborators.
12. Audit Rights and Record Retention
    By virtue of their participation in an Innovation Center model, 
IOTA participants and IOTA collaborators may receive model-specific 
payments, access to Medicare payment waivers, or some other model-
specific flexibility, such as the ability to provide cost sharing 
support to eligible attributed patients for the proposed Part B and 
Part D immunosuppressive drug cost sharing support policy. It is 
therefore necessary and appropriate for CMS to audit, inspect, 
investigate, and evaluate records and other materials related to 
participation in the IOTA Model. CMS must be able to audit, inspect, 
investigate, and evaluate records and materials related to 
participation in the IOTA Model to allow us to ensure that IOTA 
participants are in no way denying or limiting the coverage or 
provision of benefits for beneficiaries as part of their participation 
in the IOTA Model. We propose to define ``model-specific payment'' to 
mean a payment made by CMS only to IOTA participants, or a payment 
adjustment made only to payments made to IOTA participants, under the 
terms of the IOTA Model that is not applicable to any other providers 
or suppliers; the term ``model-specific payment'' would include, unless 
otherwise specified, the model upside risk payment and downside risk 
payment, described in section III.C.6 of this proposed rule. It is 
necessary to propose this definition to distinguish payments and 
payment adjustments applicable to IOTA participants as part of their 
participation in the IOTA Model, from payments and payment adjustments 
applicable to IOTA participants as well as other providers and 
suppliers, as certain provisions of proposed part 512 would apply only 
to the former category of payments and payment adjustments.
    There are audit and record retention requirements under the 
Medicare Shared Savings Program (see 42 CFR 425.314) and in other 
models being tested under section 1115A of the Act (see, for example, 
42 CFR 510.110 and Sec.  512.135).
    We are proposing to adopt audit and record retention requirements 
for the IOTA Model. Specifically, as a result of our proposal to revise 
the scope of the general provisions of 42 CFR Part 512 Subpart A to 
include the IOTA Model, see proposed 42 CFR 512.100, we are proposing 
to apply Sec.  512.135(a) through (c) to each IOTA participant and its 
IOTA collaborators. In applying Sec.  512.135(a) to the IOTA Model, the 
Federal Government, including, but not limited to, CMS, HHS, and the 
Comptroller General, or their designees, would have a right to audit, 
inspect, investigate, and evaluate any documents and other evidence 
regarding implementation of an Innovation Center model. In applying 
existing Sec.  512.135(b) and (c) to the IOTA model, an IOTA 
participant and its IOTA collaborators would be required to:
     Maintain and give the Federal Government, including, but 
not limited to, CMS, HHS, and the Comptroller General, or their 
designees, access to all documents (including books, contracts, and 
records) and other evidence sufficient to enable the audit, evaluation, 
inspection, or investigation of the IOTA Model, including, without 
limitation, documents and other evidence regarding all of the 
following:
    ++ Compliance by the IOTA participant and its IOTA collaborators 
with the terms of the IOTA Model, including proposed new subpart A of 
proposed part 512.
    ++ The accuracy of model-specific payments made under the IOTA 
Model.
    ++ The IOTA participant's downside risk payments owed to CMS under 
the IOTA Model.
    ++ Quality measure information and the quality of services 
performed under the terms of the IOTA Model, including proposed new 
subpart A of proposed part 512.
    ++ Utilization of items and services furnished under the IOTA 
Model.
    ++ The ability of the IOTA participant to bear the risk of 
potential losses and to repay any losses to CMS, as applicable.
    ++ Where cost sharing support is furnished under the Part B and 
Part D immunosuppressive drug cost sharing support policy, the IOTA 
participant must maintain contemporaneous documentation that includes 
the identity of the eligible attributed patient to whom Part B and Part 
D immunosuppressive drug cost sharing support was provided, the date or 
dates on which Part B and Part D immunosuppressive drug cost sharing 
support was provided, and the amount or amounts of Part B and Part D 
immunosuppressive drug cost sharing support that was provided.
    ++ Contemporaneous documentation of items and services furnished as 
attributed patient engagement incentives in accordance with Sec.  
512.458 that includes, at minimum, the date the attributed patient 
engagement incentive is provided and the identity of the attributed 
patient to whom the item or service was provided.
    ++ Patient safety.
    ++ Any other program integrity issues.
     Maintain the documents and other evidence for a period of 
6 years from the last payment determination for the IOTA participant 
under the IOTA Model or from the date of completion of any audit, 
evaluation, inspection, or investigation, whichever is later, unless--
    ++ CMS determines there is a special need to retain a particular 
record or group of records for a longer period and notifies the IOTA 
participant at least 30 days before the normal disposition date; or
    ++ There has been a termination, dispute, or allegation of fraud or 
similar fault against the IOTA participant or its IOTA collaborators, 
in which case the records must be maintained for an additional 6 years 
from the date of any resulting final resolution of the termination, 
dispute, or allegation of fraud or similar fault.
    If CMS notifies the IOTA participant of a special need to retain a 
record or group of records at least 30 days before the normal 
disposition date, the IOTA participant would be required to maintain 
the records for such period of time determined by CMS. If CMS notifies 
the IOTA participant of a special need to retain records or there has 
been a termination, dispute, or allegation of fraud or similar fault 
against the IOTA participant or its IOTA collaborators, the IOTA 
participant would be required to notify its IOTA collaborators of the 
need to retain records for the additional period specified by CMS. This 
provision would ensure that that the government has access to the 
records.
    We note that we previously adopted a rule at 42 CFR 512.110 
defining the term ``days,'' as used in 42 CFR 512.135, to mean calendar 
days.
    We invite public comment on these proposed provisions regarding 
audits and record retention.
13. Monitoring
a. General
    We propose that CMS, or its approved designees, would conduct 
compliance

[[Page 43599]]

monitoring activities to ensure compliance by the IOTA participant and 
IOTA collaborators with the terms of the IOTA Model, including to 
understand IOTA participants' use of model-specific payments and to 
promote the safety of attributed patients and the integrity of the IOTA 
Model. Such monitoring activities would include, but not be limited 
to--
     Documentation requests sent to the IOTA participant and 
its IOTA collaborators, including surveys and questionnaires;
     Audits of claims data, quality measures, medical records, 
and other data from the IOTA participant and its IOTA collaborators;
     Interviews with the IOTA participant, including leadership 
personnel, medical staff, other associates and its IOTA collaborators;
     Interviews with attributed patients and their caregivers;
     Site visits to the IOTA participant, which would be 
performed in accordance with Sec.  512.462, described below in section 
b of this proposed rule;
     Monitoring quality outcomes and attributed patient data;
     Tracking beneficiary complaints and appeals;
     Monitor the definition of and justification for the 
subpopulation of the IOTA participant's eligible attributed patients 
that may receive Part B and Part D Immunosuppressive Drug Cost Sharing 
Support in accordance with Sec.  512.456; and
     Monitor the provision of attributed patient engagement 
incentives provided in accordance with Sec.  512.458.
    Additionally, CMS is concerned about IOTA participants bypassing 
the match run, as defined in section III.C.5.d.(1).(a). of this 
proposed rule, the rank order list of transplant candidates to be 
offered an organ. This practice, known as ``list diving,'' can improve 
efficiency in placing organs, but may undermine the mechanisms 
promoting fairness in rationing this scarce resource, if overused. We 
propose that CMS would monitor out of sequence allocation of kidneys by 
assessing how often top-ranked attributed patients receive the organ 
that was offered to them and if they did not receive it, what the 
reason for that was.
    We believe these specific monitoring activities, which align with 
those currently used in other models being tested by the Innovation 
Center, are necessary to ensure compliance with the terms of the IOTA 
Model and can protect attributed patients from potential harm that may 
result from the activities of the IOTA participant or its IOTA 
collaborators, such as attempts to reduce access to or the provision of 
medically necessary covered services.
    We propose that when CMS is conducting compliance monitoring and 
oversight activities, CMS or its designees would be authorized to use 
any relevant data or information, including without limitation Medicare 
claims submitted for items or services furnished to attributed patients 
who are Medicare beneficiaries. We believe that it is necessary to have 
all relevant information available to CMS during compliance monitoring 
and oversight activities, including any information already available 
to CMS through the Medicare program.
    IOTA participants would remain subject to all existing requirements 
and conditions for Medicare participation as set out in Federal 
statutes and regulations and provider and supplier agreements, unless 
waived under the authority of section 1115A(d)(1) of the Act solely for 
purposes of testing the IOTA Model.
    We seek feedback on how CMS should implement this monitoring 
proposal and any additional concerns regarding the overall monitoring 
approach.
b. Site Visits
    We propose that IOTA participants would be required to cooperate in 
periodic site visits conducted by CMS or its designee. Such site visits 
would be conducted to facilitate the model evaluation performed 
pursuant to section 1115A(b)(4) of the Act and to monitor compliance 
with the IOTA Model requirements. We further propose that CMS or its 
designee would provide the IOTA participant with no less than 15 days 
advance notice of a site visit, to the extent practicable. Furthermore, 
we propose that, to the extent practicable, CMS would attempt to 
accommodate a request that a site visit be conducted on a particular 
date, but that the IOTA participant would be prohibited from requesting 
a date that was more than 60 days after the date of the initial site 
visit notice from CMS. We believe the 60-day period would reasonably 
accommodate IOTA participant schedules while not interfering with the 
operation of the IOTA Model. Further, we propose to require the IOTA 
participant to ensure that personnel with the appropriate 
responsibilities and knowledge pertaining to the purpose of the site 
visit be available during any and all site visits. We believe this 
proposal is necessary to ensure an effective site visit and prevent the 
need for unnecessary follow-up site visits.
    Further, we propose that nothing in the previous sections would 
limit CMS from performing other site visits as allowed or required by 
applicable law. We believe that CMS must retain the ability to timely 
investigate concerns related to the health or safety of attributed 
patients or program integrity issues, and to perform functions required 
or authorized by law. In particular, we believe that it is necessary 
for CMS to monitor, and for IOTA participants to be compliant with our 
monitoring efforts, to ensure that they are not denying or limiting the 
coverage or provision of medically necessary covered services to 
attributed patients in an attempt to change model results or their 
model-specific payments, including discrimination in the provision of 
services to at-risk patients (for example, due to eligibility for 
Medicare based on disability).
    In the alternative, we considered allowing unannounced site visits 
for any reason. However, we determined that giving advanced notice for 
site visits for routine monitoring would allow the IOTA participant to 
ensure that the personnel with the applicable knowledge is available 
and would allow the IOTA participant the flexibility to arrange these 
site visits around their operations. However, we propose that if there 
is a concern regarding issues that may pose risks to the health or 
safety of attributed patients or to the integrity of the IOTA Model, 
unannounced site visits would be warranted. We believe this would allow 
us to address any potential concerns in a timely manner without a delay 
that may increase those potential risks.
c. Reopening of Payment Determinations
    To protect the financial integrity of the IOTA Model, we propose in 
Sec.  512.462(d) that if CMS discovers that it has made or received a 
request from the IOTA participant about an incorrect model payment, CMS 
may make payment to, or demand payment from, the IOTA participant.
    CMS' interests include ensuring the integrity and sustainability of 
the IOTA Model and the underlying Medicare program, from both a 
financial and policy perspective, as well as protecting the rights and 
interests of Medicare beneficiaries. For these reasons, CMS or its 
designee needs the ability to monitor IOTA participants to assess 
compliance with model terms and with other applicable Medicare program 
laws and policies. We believe our monitoring efforts help ensure that 
IOTA participants are furnishing medically necessary covered services 
and are not

[[Page 43600]]

falsifying data, increasing program costs, or taking other actions that 
compromise the integrity of the IOTA Model or are not in the best 
interests of the IOTA Model, the Medicare program, or Medicare 
beneficiaries.
    We invite public comment on these proposed provisions regarding 
monitoring of the IOTA Model and alternatives considered.
14. Evaluation
    Section 1115A(b)(4) of the Act requires the Secretary to evaluate 
each model tested under the authority of section 1115A of the Act and 
to publicly report the evaluation results in a timely manner. The 
evaluation must include an analysis of the quality of care furnished 
under the model and the changes in program spending that occurred due 
to the model. Models tested by the Innovation Center are rigorously 
evaluated. For example, when evaluating models tested under section 
1115A of the Act, we require the production of information that is 
representative of a wide and diverse group of model participants and 
includes data regarding potential unintended or undesirable effects. 
The Secretary must take the evaluation into account if making any 
determinations regarding the expansion of a model under section 
1115A(c) of the Act. In addition to model evaluations, the CMS 
Innovation Center regularly monitors model participants for compliance 
with model requirements.
    For the reasons described in section III.C.11. of this proposed 
rule, these compliance monitoring activities are an important and 
necessary part of the model test. Therefore, we note that IOTA 
participants and their IOTA collaborators must comply with the 
requirements of 42 CFR 403.1110(b) (regarding the obligation of 
entities participating in the testing of a model under section 1115A of 
the Act to report information necessary to monitor and evaluate the 
model), and must otherwise cooperate with CMS' model evaluation and 
monitoring activities as may be necessary to enable CMS to evaluate the 
Innovation Center model in accordance with section 1115A(b)(4) of the 
Act. This participation in the evaluation may include, but is not 
limited to, responding to surveys and participating in focus groups.
15. Learning
    In the Specialty Care Models final rule (85 FR 61114), we 
established the voluntary ETC Learning Collaborative (ETCLC). The goals 
of the ETCLC are to increase the supply and use of deceased donor 
kidneys by convening OPOs, transplant hospitals, donor hospitals, and 
patients and families to reduce the variation in OPO and transplant 
hospital performance and reduce kidney non-use.\311\ The ETCLC is 
addressing three national aims over a 5-year period: (1) achieve a 28 
percent absolute increase in the number of deceased donor kidneys with 
a KDPI greater than or equal to 60 recovered for transplant from the 
2021 OPTN/SRTR baseline of 11,284; (2) decrease the current national 
non-use rate of all procured kidneys with a KDPI >=60 by 20 percent; 
and (3) decrease the current national discard rate of all procured 
kidneys with a KDPI <60 by 4 percent. The ETCLC has developed Quality 
Improvement (QI) Teams that are identifying and implementing best 
practices based on the ETCLC Kidney Donation and Utilization Change 
Package. As of June 2023, 54 OPOs and 181 transplant hospitals were 
enrolled in ETCLC.\312\
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    \311\ End Stage Renal Disease Treatment Choices Learning 
Collaborative--End Stage Renal Disease Treatment Choices Learning 
Collaborative--QualityNet Confluence. (n.d.). 
Qnetconfluence.cms.gov. Retrieved May 30, 2023, from https://qnetconfluence.cms.gov/display/ETCLC/End+Stage+Renal+Disease+Treatment+Choices+Learning+Collaborative.
    \312\ Ibid.
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    While we considered continuing the ETCLC under the auspices of the 
IOTA Model, we are proposing to conclude the ETCLC at the end of the 
ETC Model test and implement a learning system specific to the IOTA 
Model. An IOTA Model learning system would deal only with issues 
specific to the IOTA Model and would have neither national aims nor 
include other providers in the transplant ecosystem such as OPOs or 
donor hospitals as regular participants. The advantages of this 
approach are that CMS could provide a forum for IOTA participants to 
discuss elements of the model, share experiences implementing IOTA 
Model provisions, and solicit support from peers in overcoming 
challenges that may arise. Since most transplant hospitals have less 
experience with Innovation Center models than other provider types, we 
believe an independent learning system would provide unique value to 
IOTA participants.
    We also considered continuing ETCLC under the aegis of the IOTA 
Model. We believe many IOTA participants would already be enrolled in 
the ETCLC and dedicating staff and time to participating in QI Teams 
and engaging with the Kidney Donation and Utilization Change Package. 
We also believe that there may be overlap between the QI work being 
undertaken by ETCLC participants and the issues that would be of 
interest to IOTA participants. We further considered whether the ETCLC 
needs more time to achieve its national aims that could be provided by 
continuing the ETCLC under the IOTA Model.
    We are soliciting feedback on our proposal to conclude the ETCLC 
with the ETC Model and implement a new learning system specific to the 
IOTA Model. We are also seeking feedback on the following questions:
     What are specific examples of how ETCLC is supporting 
transplant hospital QI to increase access to kidney transplant?
     What features of a new learning system would be important 
for IOTA participants?
     Could the ETCLC meet IOTA participants' need for QI 
support to succeed in the model?
16. Remedial Action and Termination
a. Remedial Action
    We propose the Standard Provisions for Innovation Center Models 
relating to remedial actions, originally finalized as general 
provisions in the Code of Federal Regulations (42 CFR part 512 subpart 
A) that applied to specific Innovation Center models but that we are 
proposing for expansion to all Innovation Center Models with model 
performance periods that begin on or after January 1, 2025, in section 
II.B. of this proposed rule would apply to the IOTA Model. We propose 
that CMS could impose one or more remedial actions on the IOTA 
participant if CMS determines that--
     The IOTA participant has failed to furnish 11 or more 
transplants during the PY or any baseline years;
     The IOTA participant or its IOTA collaborator has failed 
to comply with any of the terms of the IOTA Model;
     The IOTA participant has failed to comply with 
transparency requirements as listed in section III.C.8.a. of this 
proposed rule;
     The IOTA participant or its IOTA collaborator has failed 
to comply with any applicable Medicare program requirement, rule, or 
regulation;
     The IOTA participant or its IOTA collaborator has taken 
any action that threatens the health or safety of an attributed 
patient;
     The IOTA participant or its IOTA collaborator has 
submitted false data or made false representations, warranties, or 
certifications in connection with any aspect of the IOTA Model;
     The IOTA participant or its IOTA collaborator has 
undergone a Change in Control, as described in section III.C.17.b of 
this proposed rule, that presents a program integrity risk;

[[Page 43601]]

     The IOTA participant or its IOTA collaborator is subject 
to any sanctions of an accrediting organization or a Federal, State, or 
local government agency;
     The IOTA participant or its IOTA collaborator is subject 
to investigation or action by HHS (including the HHS-OIG or CMS) or the 
Department of Justice due to an allegation of fraud or significant 
misconduct, including being subject to the filing of a complaint or 
filing of a criminal charge, being subject to an indictment, being 
named as a defendant in a False Claims Act qui tam matter in which the 
Federal Government has intervened, or similar action;
     The IOTA participant or its IOTA collaborator has failed 
to demonstrate improved performance following any remedial action 
imposed by CMS; or
     The IOTA participant has misused or disclosed 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 propose that CMS may take one or more of the following remedial 
actions if CMS determines that one or more of the grounds for remedial 
action described in section III.C.16.a. of this proposed rule had taken 
place:
     Notify the IOTA participant and, if appropriate, require 
the IOTA participant to notify its IOTA collaborators of the violation;
     Require the IOTA participant to provide additional 
information to CMS or its designees;
     Subject the IOTA participant to additional monitoring, 
auditing, or both;
     Prohibit the IOTA participant from distributing model-
specific payments, as applicable;
     Require the IOTA participant to terminate, immediately or 
by a deadline specified by CMS, its sharing arrangement with an IOTA 
collaborator with respect to the IOTA Model;
     Terminate the IOTA participant from the IOTA Model;
     Suspend or terminate the ability of the IOTA participant 
to provide cost sharing support for Part B and Part D immunosuppressive 
drugs, or attributed patient engagement incentives in accordance with 
III.C.11.h(1).
     Require the IOTA participant to submit a corrective action 
plan (CAP) in a form and manner and by a deadline specified by CMS;
     Discontinue the provision of data sharing and reports to 
the IOTA participant;
     Recoup model-specific payments;
     Reduce or eliminate a model specific payment otherwise 
owed to the IOTA participant, as applicable; or
     Such other action as may be permitted under the terms of 
the IOTA Model.
    As part of the Innovation Center's monitoring and assessment of the 
impact of models tested under the authority of section 1115A of the 
Act, CMS has a special interest in ensuring that these model tests do 
not interfere with the program integrity interests of the Medicare 
program. For this reason, CMS monitors actions of IOTA participants for 
compliance with model terms, as well as other Medicare program rules. 
When CMS becomes aware of noncompliance with these requirements, it is 
necessary for CMS to have the ability to impose certain administrative 
remedial actions on a noncompliant model participant.
    In the alternative, we considered a policy where the IOTA 
participant would remain in the IOTA Model regardless of any 
noncompliance. However, if there are circumstances in which the IOTA 
participant has engaged, or is engaged in, egregious actions, we are 
proposing that CMS may terminate the IOTA participant, as further 
described in section III.C.16.b. of this proposed rule. In addition, we 
considered allowing IOTA participants access to their data and reports 
regardless of their compliance with the requirements of the IOTA Model 
however we are proposing to discontinue data sharing and reports as a 
potential remedial action if there are grounds for doing so.
    We seek comment on these proposed provisions regarding the proposed 
grounds for remedial actions, remedial actions generally, and whether 
additional types of remedial action would be appropriate.
b. Termination of IOTA Participant From the IOTA Model by CMS
    We propose that CMS may immediately or with advance notice 
terminate an IOTA participant from participation in the IOTA Model if:
     CMS determines that it no longer has the funds to support 
the IOTA Model;
     CMS modifies or terminates the model pursuant to section 
1115A(b)(3)(B) of the Act;
     CMS determines that the IOTA participant--
    ++ Has failed to comply with any model requirement or any other 
Medicare program requirement, rule, or regulation;
    ++ Has failed to comply with a monitoring or auditing plan or both;
    ++ Has failed to submit, obtain approval for, implement or fully 
comply with the terms of a CAP;
    ++ Has failed to demonstrate improved performance following any 
remedial action;
    ++ Has taken any action that threatens the health or safety of a 
Medicare beneficiary or other patient;
    ++ Has submitted false data or made false representations, 
warranties, or certifications in connection with any aspect of the IOTA 
Model; or
    ++ Assigns or purports to assign any of the rights or obligations 
under the model, voluntarily or involuntarily, whether by merger, 
consolidation, dissolution, operation of law, or any other manner, 
without the written consent of CMS;
     Poses significant program integrity risks, including but 
not limited to:
    ++ Is subject to sanctions or other actions of an accrediting 
organization or a Federal, State or local government agency; or
    ++ Is subject to investigation or action by HHS (including OIG or 
CMS) or the Department of Justice due to an allegation of fraud or 
significant misconduct, including being subject to the filing of a 
complaint, filing of a criminal charge, being subject to an indictment, 
being named as a defendant in a False Claims Act qui tam matter in 
which the government has intervened, or similar action.
    We request comment and feedback on the proposal for termination of 
an IOTA participant from participating in the IOTA Model.
c. Termination of Model Participation by IOTA Participant
    Given the mandatory nature of this model, we propose that an IOTA 
participant would not be able to terminate its own participation in the 
model. Maintaining a cohort of participants as close to 50 percent of 
eligible kidney transplant hospitals across the country is critical to 
evaluation of IOTA Model. As such, while we are proposing CMS may 
terminate an IOTA participant for reasons such as failure to meet 
eligibility criteria or change in kidney transplant hospital status, as 
described in section III.C.16.b. of this proposed rule, we are not 
proposing voluntary termination by the IOTA participant.
    We considered allowing an IOTA participant to voluntarily terminate 
their participation in the model; however, we believe this went against 
the mandatory nature of the model and jeopardized our ability to 
evaluate model success and savings.

[[Page 43602]]

    We solicit comment and feedback on our proposal not to allow IOTA 
participants to terminate their participation in the IOTA Model.
d. Financial Settlement Upon Termination
    We propose that if CMS terminates the IOTA participant's 
participation in the IOTA Model or CMS terminates the IOTA Model, CMS 
would calculate the final performance score and any upside risk payment 
or downside risk payment, if applicable, for the entire PY in which the 
IOTA participant's participation in the model or the IOTA Model was 
terminated.
    We propose that if CMS terminates an IOTA participant for any 
reason listed in section III.C.16.b of this proposed rule, CMS shall 
not make any payments of upside risk payment for the PY in which the 
IOTA participant was terminated and the IOTA participant shall remain 
liable for payment of any downside risk payment up to and including the 
PY in which termination becomes effective. We propose that CMS would 
determine the IOTA participant's effective date of termination.
    We considered that in the event of termination, CMS would not pay 
any upside risk payments for the year in which the IOTA participant was 
terminated, but also only keep the IOTA participant liable for paying 
CMS any downside risk payments for completed PYs and not the year in 
which the IOTA participant is terminated. However, to deter poor or 
non-compliant performance, we believe it necessary to also keep the 
IOTA participant liable for paying to CMS any downside risk payment for 
the PY in which the IOTA participant is terminated.
    We solicit comment on this proposal and alternative considered.
e. Termination of the IOTA Model
    We are proposing that the general provisions relating to 
termination of the model by CMS in 42 CFR 512.165 would apply to the 
IOTA Model. Consistent with these provisions, in the event we terminate 
the IOTA Model, we would provide written notice to IOTA participants 
specifying the grounds for termination and the effective date of such 
termination or ending. As provided by section 1115A(d)(2) of the Act 
and Sec.  512.170(e), termination of the model under section 
1115A(b)(3)(B) of the Act would not be subject to administrative or 
judicial review. We propose that in the event of termination of the 
model, financial settlement terms would be the same as those proposed 
in section III.C.16.d. of this proposed rule.
17. Miscellaneous Provisions on Bankruptcy and Other Notifications
a. Notice of Bankruptcy
    We propose that if an IOTA participant has filed a bankruptcy 
petition, whether voluntary or involuntary, the IOTA participant must 
provide written notice of the bankruptcy to CMS and to the U.S. 
Attorney's Office in the district where the bankruptcy was filed, 
unless final payment has been made by either CMS or the IOTA 
participant under the terms of each model tested under section 1115A of 
the Act in which the IOTA participant is participating or has 
participated and all administrative or judicial review proceedings 
relating to any payments under such models have been fully and finally 
resolved. We propose the notice of bankruptcy must be sent by certified 
mail no later than 5 days after the petition has been filed and must 
contain a copy of the filed bankruptcy petition (including its docket 
number), and a list of all models tested under section 1115A of the Act 
in which the IOTA participant is participating or has participated. 
This list would not need to identify a model tested under section 1115A 
of the Act in which the IOTA participant participated if final payment 
has been made under the terms of the model and all administrative or 
judicial review proceedings regarding model-specific payments between 
the IOTA participant and CMS have been fully and finally resolved with 
respect to that model. The notice to CMS would be addressed to the CMS 
Office of Financial Management, Mailstop C3-01-24, 7500 Security 
Boulevard, Baltimore, Maryland 21244 or to such other address as may be 
specified on the CMS website for purposes of receiving such notices.
b. Change in Control
    We propose that CMS could terminate an IOTA participant from the 
model if the IOTA participant undergoes a Change in Control. We propose 
that the IOTA participant shall provide written notice to CMS at least 
90 days before the effective date of any Change in Control. For 
purposes of this rule, we propose a ``Change in Control'' would mean at 
least one of the following: (1) the acquisition by any ``person'' (as 
such term is used in Sections 13(d) and 14(d) of the Securities 
Exchange Act of 1934) of beneficial ownership (within the meaning of 
Rule 13d-3 promulgated under the Securities Exchange Act of 1934), 
directly or indirectly, of voting securities of the IOTA participant 
representing more than 50 percent of the IOTA participant's outstanding 
voting securities or rights to acquire such securities; (2) the 
acquisition of the IOTA participant by any individual or entity; (3) 
any merger, division, dissolution, or expansion of the IOTA participant 
(4) the sale, lease, exchange or other transfer (in one transaction or 
a series of transactions) of all or substantially all of the assets of 
the IOTA participant; or (5) the approval and completion of a plan of 
liquidation of the IOTA participant, or an agreement for the sale or 
liquidation of the IOTA participant.
c. Prohibition on Assignment
    We propose that except with the prior written consent of CMS, an 
IOTA participant shall not transfer, including by merger (whether the 
IOTA participant is the surviving or disappearing entity), 
consolidation, dissolution, or otherwise: (1) any discretion granted it 
under the model; (2) any right that it has to satisfy a condition under 
the model; (3) any remedy that it has under the model; or (4) any 
obligation imposed on it under the model. We propose that the IOTA 
participant provide CMS 90 days advance written notice of any such 
proposed transfer. We propose this obligation remains in effect after 
the expiration or termination of the model or the IOTA participant's 
participation in the model and until final payment by the IOTA 
participant under the model has been made. We propose CMS may condition 
its consent to such transfer on full or partial reconciliation of 
upside risk payments and downside risk payments. We propose that any 
purported transfer in violation of this requirement is voidable at the 
discretion of CMS.

D. Requests for Information (RFIs) on Topics Relevant to the IOTA Model

    This section includes several requests for information (RFIs). In 
responding to the RFIs, the public is encouraged to provide complete, 
but concise responses. These RFIs are issued solely for information and 
planning purposes; RFIs do not constitute a Request for Proposal (RFP), 
application, proposal abstract, or quotation. The RFIs do not commit 
the U.S. Government to contract for any supplies or services or make a 
grant award. Further, CMS is not seeking proposals through these RFIs 
and would not accept unsolicited proposals. Respondents are advised 
that the U.S. Government would not pay for any information or 
administrative costs incurred in response to this RFI; all costs 
associated with responding to these RFIs would be solely at the 
respondent's expense. Failing to

[[Page 43603]]

respond to any of the RFIs would not preclude participation in any 
future procurement, if conducted.
    Please note that CMS would not respond to questions about the 
policy issues raised in these RFIs. CMS may or may not choose to 
contact individual respondents. Such communications would only serve to 
further clarify written responses. Contractor support personnel may be 
used to review RFI responses. Responses to these RFIs are not offers 
and cannot be accepted by the U.S. Government to form a binding 
contract or issue a grant. Information obtained because of this RFI may 
be used by the U.S. Government for program planning on a non-
attribution basis. Respondents should not include any information that 
might be considered proprietary or confidential. All submissions become 
U.S. Government property and would not be returned. CMS may publicly 
post the comments received, or a summary thereof.
1. Patient-Reported Outcome Performance Measures (PRO-PM)
    Chronic kidney disease is both complex and multifaceted and demands 
inclusive and thorough medical management, even after transplantation. 
Thus, when taking into consideration the lasting impact of CKD, symptom 
burden, and its correlation to mental health and psychosocial 
difficulties, it is important that the patient perspective and voice be 
included through the use of patient-reported outcome measures (PROMs) 
to truly grasp how CKD impacts their lives.\313\
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    \313\ Schick-Makaroff, K., Thummapol, O., Thompson, S., Flynn, 
R., Karimi-Dehkordi, M., Klarenbach, S., Sawatzky, R., & Greenhalgh, 
J. (2019). Strategies for incorporating patient-reported outcomes in 
the care of people with chronic kidney disease (PRO kidney): a 
protocol for a realist synthesis. Systematic Reviews, 8(1). https://doi.org/10.1186/s13643-018-0911-6; Brett, K.E., Ritchie, L.J., 
Ertel, E., Bennett, A., & Knoll, G.A. (2018). Quality Metrics in 
Solid Organ Transplantation. Transplantation, 102(7), e308-e330. 
https://doi.org/10.1097/tp.0000000000002149; Mendu, M.L., 
Tummalapalli, S.L., Lentine, K.L., Erickson, K.F., Lew, S.Q., Liu, 
F., Gould, E., Somers, M., Garimella, P.S., O'Neil, T., White, D.L., 
Meyer, R., Bieber, S.D., & Weiner, D.E. (2020). Measuring Quality in 
Kidney Care: An Evaluation of Existing Quality Metrics and Approach 
to Facilitating Improvements in Care Delivery. Journal of the 
American Society of Nephrology, 31(3), 602-614. https://doi.org/10.1681/ASN.2019090869; Tang, E., Bansal, A., Novak, M., & Mucsi, I. 
(2018). Patient-Reported Outcomes in Patients with Chronic Kidney 
Disease and Kidney Transplant--Part 1. Frontiers in Medicine, 4. 
https://doi.org/10.3389/fmed.2017.00254; Anderson, N.E., Calvert, 
M., Cockwell, P., Dutton, M., Aiyegbusi, O.L., & Kyte, D. (2018). 
Using patient-reported outcome measures (PROMs) to promote quality 
of care in the management of patients with established kidney 
disease requiring treatment with haemodialysis in the UK (PROM-HD): 
a qualitative study protocol. BMJ Open, 8(10), e021532. https://doi.org/10.1136/bmjopen-2018-021532.
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    Patient-reported measures are those measures where data comes 
directly from the patient. Broadly, patient-reported data includes 
patient-reported outcomes (PROs) and ePROs, which is the electronic 
capture of this data; patient-reported outcome measures (PROMs), which 
is the structure of how the PRO data is reported (for example, a survey 
instrument); and patient-reported outcome-based performance measures 
(PRO-PMs), which are reliable and valid quality measures of aggregated 
PRO data reported through a PROM and potentially used for performance 
assessment. PROMs include aspects pertaining health-related quality of 
life (HRQOL) and symptoms, both of which are essential measures in 
renal care. HRQOL can vary over time and course of an illness and these 
types of measures seek to examine the functioning and well-being in 
physical, mental, and social dimensions of life. It is also impacted by 
a variety of factors such as treatment, level of health, condition, 
culture, age, and psychosocial elements.\314\
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    \314\ Pagels, A.A., Stendahl, M., & Evans, M. (2019). Patient-
reported outcome measures as a new application in the Swedish Renal 
Registry: Health-related quality of life through Rand-36. Clinical 
Kidney Journal, 13(7), 442-449. https://doi.org/10.1093/ckj/sfz084; 
Broadbent, E., Petrie, K.J., Main, J., & Weinman, J. (2006). The 
Brief Illness Perception Questionnaire. Journal of Psychosomatic 
Research, 60(6), 631-637. https://doi.org/10.1016/j.jpsychores.2005.10.020; Mclaren, S., Jhamb, M., & Unruh, M. 
(2021). Using patient-reported measures to improve outcomes in 
kidney disease. Blood Purification, 50(4-5), 649-654. https://doi.org/10.1159/000515640.
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    Using PROMs or PRO-PMs are two ways to include the patient 
experience and has been acknowledged as a way for patients to provide 
critical insight about their symptoms, patient experience and quality 
of life.\315\ In spite of the growing recognition over the past two 
decades that this is paramount to advancing the quality of care at both 
the patient and policy levels, there remains significant information 
gaps in understanding how PROMs are, and can be utilized across 
different domains, especially within nephrology to enrich patient-
centered care, and measure other important quality components, such as 
access to transplantation, shared-decision making and quality of life 
post-transplantation, to provide a comprehensive understanding.\316\
---------------------------------------------------------------------------

    \315\ Schick-Makaroff, K., Thummapol, O., Thompson, S., Flynn, 
R., Karimi-Dehkordi, M., Klarenbach, S., Sawatzky, R., & Greenhalgh, 
J. (2019). Strategies for incorporating patient-reported outcomes in 
the care of people with chronic kidney disease (PRO kidney): a 
protocol for a realist synthesis. Systematic Reviews, 8(1). https://doi.org/10.1186/s13643-018-0911-6; Brett, K.E., Ritchie, L.J., 
Ertel, E., Bennett, A., & Knoll, G.A. (2018). Quality Metrics in 
Solid Organ Transplantation. Transplantation, 102(7), e308-e330. 
https://doi.org/10.1097/tp.0000000000002149; Mendu, M.L., 
Tummalapalli, S.L., Lentine, K.L., Erickson, K.F., Lew, S.Q., Liu, 
F., Gould, E., Somers, M., Garimella, P.S., O'Neil, T., White, D.L., 
Meyer, R., Bieber, S.D., & Weiner, D.E. (2020). Measuring Quality in 
Kidney Care: An Evaluation of Existing Quality Metrics and Approach 
to Facilitating Improvements in Care Delivery. Journal of the 
American Society of Nephrology, 31(3), 602-614. https://doi.org/10.1681/ASN.2019090869; Tang, E., Bansal, A., Novak, M., & Mucsi, I. 
(2018). Patient-Reported Outcomes in Patients with Chronic Kidney 
Disease and Kidney Transplant--Part 1. Frontiers in Medicine, 4. 
https://doi.org/10.3389/fmed.2017.00254; Anderson, N.E., Calvert, 
M., Cockwell, P., Dutton, M., Aiyegbusi, O.L., & Kyte, D. (2018). 
Using patient-reported outcome measures (PROMs) to promote quality 
of care in the management of patients with established kidney 
disease requiring treatment with haemodialysis in the UK (PROM-HD): 
a qualitative study protocol. BMJ Open, 8(10), e021532. https://doi.org/10.1136/bmjopen-2018-021532.
    \316\ Ibid.
---------------------------------------------------------------------------

    In addition to the proposed measures the IOTA Model proposes would 
be used, as described in section III.C.5.e.(2) of this proposed rule, 
we would consider incorporating a measure of HRQOL and access to 
waitlist.
    We seek comments on the inclusion of a HRQOL patient-reported 
outcome measure in the IOTA Model, as well as on the inclusion of an 
access to waitlist measure. We are seeking input to the questions later 
in this section, and comment on any aspect of a kidney transplant 
recipient patient experience measure that should be included in a new 
measure or existing and validated measurement tools and instruments 
appropriate for use in the IOTA Model.
     For a meaningful evaluation of transplant program outcomes 
from the recipient point of view, are there currently any validated 
PROMs of quality of life that are appropriate for use in the IOTA 
Model?
     Are there specific aspects of quality of life (QOL) that 
are particularly important to include for these populations? Why are 
these aspect(s) of QOL a high priority for inclusion in a survey? What 
should these metrics be (that is, measurement tools, instruments, 
concepts)? How should they be measured?
     For kidney transplant recipients: What other topic area(s) 
should be included in a new patient-reported outcome measure or 
performance measure assessing quality of life?
     For kidney transplant recipients: What domains of HRQOL 
can be influenced or improved by actions taken by transplant hospital 
and thus may be appropriate for performance measurement?
    In addition, we are seeking input on the questions later in this 
section on

[[Page 43604]]

existing PROMs and quality measures that are currently being used by 
transplant hospitals.
     Which patient-reported outcomes measure(s) that assess 
quality of life in kidney transplant recipients are currently being 
used?
    ++ What information is collected in these PROMs? How well do these 
surveys perform? What are the strengths of the survey(s) currently in 
use?
    ++ What content area(s) are missing from these survey(s) that are 
currently in use?
    ++ Which content area(s) are low priority or not useful in these 
currently used survey(s)? Why are they not useful?
    ++ How are the results and findings of these current survey(s) used 
to evaluate and improve quality of life/care? Are the results and 
findings of these current survey(s) used for other purposes?
     Are there any other PROMs or PRO-PMs that CMS should 
consider using to measure a transplant program's performance?
     Are there any other quality measures in general that CMS 
should consider using to measure a transplant program's performance?
     For transplant hospitals: Can PROs be effectively used to 
assess performance?
     For transplant hospitals: Does a reporting requirement 
effectively incentivize a transplant hospital to improve patient 
quality of life without tying payment to performance?
    The integration and implementation of PROMs can be challenging for 
transplant hospitals as it requires additional resources (that is, 
appropriate infrastructure with regard to technological capability or 
data security), time, and there may be uncertainty about how to 
interpret and use the data to improve patient care.\317\ We are also 
seeking information on implementation challenges and support.
---------------------------------------------------------------------------

    \317\ Ju, A., Cazzolli, R., Howell, M., Scholes-Robertson, N., 
Wong, G., & Jaure, A. (n.d.). Novel Endpoints in Solid Organ 
Transplantation: Targeting Patient-reported Outcome Measures. 
Transplantation, 10.1097/TP.0000000000004537. https://doi.org/10.1097/TP.0000000000004537; Aiyegbusi, O.L., Kyte, D., Cockwell, 
P., Anderson, N., & Calvert, M. (2017). A patient-centred approach 
to measuring quality in kidney care. Current Opinion in Nephrology 
and Hypertension, 26(6), 442-449. https://doi.org/10.1097/mnh.0000000000000357; MacLean, C.H., Antao, V.C., Fontana, M.A., 
Sandhu, H.S., & McLawhorn, A.S. (2021). PROMs: Opportunities, 
Challenges, and Unfinished Business. NEJM Catalyst, 2(11). https://doi.org/10.1056/cat.21.0280.
---------------------------------------------------------------------------

     When is the appropriate time to measure HRQOL post-
transplantation?
     For transplant hospitals: What, if any, challenge(s) are 
there to collecting information about patient quality of life?
     For kidney transplant recipients: What, if any, 
challenge(s) are there to reporting information about patient quality 
of life?
     For transplant hospitals: What actions or approaches by 
transplant hospitals would facilitate the collection of quality of life 
information?
    ++ What data collection approach(es) would be most likely to 
promote participation by transplant recipients to a survey (for 
example, web-based; paper-and-pencil; etc.)?
    ++ How much time would transplant hospitals need to build processes 
to collect and use data in a meaningful way?
     For transplant hospitals: How could CMS support transplant 
hospitals in introducing a measure like this into the model?
2. Access to Waitlist Measure
    The kidney transplant waitlist is a list of individuals with ESRD 
who need a kidney transplant. To be placed on the wait list for a 
kidney transplant, individuals must be referred and then undergo a 
comprehensive evaluation process by a transplant center.
    Organ transplantation and donation in the U.S. remains highly 
inequitable amongst racial and ethnic minorities as compared to White 
Americans, with many factors influencing disparities.\318\ As one study 
notes regarding kidney transplants, ``racial disparities were observed 
in access to referral, transplant evaluation, waitlisting and organ 
receipt'' and ``SES [socioeconomic status] explained almost one-third 
of the lower rate of transplant among black versus white patients, but 
even after adjustment for demographic, clinical and SES factors, blacks 
had a 59 percent lower rate of transplant than whites.'' \319\
---------------------------------------------------------------------------

    \318\ Inequity in Organ Donation [middot] The Costly Effects of 
an Outdated Organ Donation System. (n.d.). Bloomworks.digital. 
https://bloomworks.digital/organdonationreform/Inequity/; Patzer, 
R.E., Perryman, J.P., Schrager, J.D., Pastan, S., Amaral, S., 
Gazmararian, J.A., Klein, M., Kutner, N., & McClellan, W.M. (2012). 
The Role of Race and Poverty on Steps to Kidney Transplantation in 
the Southeastern United States. American Journal of Transplantation, 
12(2), 358-368. https://doi.org/10.1111/j.1600-6143.2011.03927.x.
    \319\ Patzer, R.E., Perryman, J.P., Schrager, J.D., Pastan, S., 
Amaral, S., Gazmararian, J.A., Klein, M., Kutner, N., & McClellan, 
W.M. (2012). The Role of Race and Poverty on Steps to Kidney 
Transplantation in the Southeastern United States. American Journal 
of Transplantation, 12(2), 358-368. https://doi.org/10.1111/j.1600-6143.2011.03927.x
---------------------------------------------------------------------------

    In addition, Black/African Americans, Hispanics/Latinos, Asian 
Americans, and other minorities are at a higher risk of illnesses that 
may eventually lead to kidney failure, such as diabetes and high blood 
pressure.\320\ ``Black/African Americans are almost 4 times more likely 
and Hispanics or Latinos are 1.3 times more likely to have kidney 
failure as compared to White Americans.'' \321\ Yet those Black/African 
American and Hispanic/Latinos patients on dialysis are less likely to 
be placed on the transplant waitlist and also have a lower likelihood 
of transplantation.\322\ In particular, Black/African Americans make up 
the largest group of minorities in need of an organ transplant and yet 
the number of organ transplants performed on Black/African Americans in 
2020 was 28.5 percent of the number of Black/African Americans 
currently waiting for a transplant.\323\ The number of transplants 
performed on White Americans, however, was 40.4 percent of the number 
currently waiting.\324\
---------------------------------------------------------------------------

    \320\ National Kidney Foundation. (2016, January 7). Minorities 
and kidney disease. National Kidney Foundation. https://www.kidney.org/atoz/content/minorities-KD.
    \321\ Ibid.
    \322\ Reed, R.D., & Locke, J.E. (2019). Social Determinants of 
Health. Transplantation, 1. https://doi.org/10.1097/tp.0000000000003003.
    \323\ Organ and Tissue Donation--The Office of Minority Health. 
(2019). Hhs.gov. https://minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=27.
    \324\ Ibid.
---------------------------------------------------------------------------

    We are seeking public comments on the following questions:
     For kidney transplant hospitals: What existing measures 
are currently being used to measure access to the waitlist?
    ++ What are the strengths and weaknesses of those measures?
    ++ What are the domains of those measures?
     For kidney transplant recipients and dialysis and ESRD 
patients: Why is a quality measure that looks at access to waitlist 
important to include?
     When measuring access to waitlist, what components should 
be analyzed (for example, time from referral to waitlist, time from 
waitlist to transplant)?
     What data would be necessary to create a measure on those 
specified components? How could that data be transmitted to CMS that 
minimizes additional burden to transplant hospitals?
     What data would be necessary to create a measure of time 
to referral to waitlist, time from referral to waitlist and time from 
waitlist to transplant? How could that data be transmitted to CMS that 
reduces burden to transplant hospitals?
    While we would not be responding to specific comments submitted in 
response to this RFI, we intend to use

[[Page 43605]]

this input to inform any future quality measure efforts.
3. Interoperability
    Improved interoperability of software systems and tools used to 
manage CKD, ESRD, and kidney transplant patients supports the goals of 
value-based care to encourage care coordination and data-driven 
decision making to improve outcomes and lower healthcare expenditures. 
We understand that transplant hospitals rely on transplant specific 
platforms that are components of market-leading electronic health 
records (EHRs) or transplant management software that can integrate 
into an existing EHR. Dialysis organizations and dialysis facilities 
generally use hemodialysis-specific EHRs from large software 
companies.\325\ EHRs have proprietary components that have historically 
limited the transfer of clinical data to other EHRs and clinical 
systems, though interest in exchange, defined at 45 CFR 171.102 as the 
ability for electronic health information to be transmitted between and 
among different technologies, systems, platforms, or networks, is 
growing.\326\ Exchange is facilitated by health information networks or 
health information exchanges, defined at 45 CFR 171.102 as an 
individual or entity that determines, controls, or has the discretion 
to administer any requirement, policy, or agreement that permits, 
enables, or requires the use of any technology or services for access, 
exchange, or use of electronic health information among more than two 
unaffiliated individuals or entities (other than the individual or 
entity to which this definition might apply) that are enabled to 
exchange with each other; and that is for a treatment, payment, or 
health care operations purpose, as such terms are defined in 45 CFR 
164.501 regardless of whether such individuals or entities are subject 
to the requirements of 45 CFR parts 160 and 164. For the purposes of 
this proposed rule, we refer to health information networks or health 
information exchanges, as defined at 45 CFR 171.102, solely as health 
information exchanges. Health information exchanges facilitate exchange 
via different mechanisms, such as within a proprietary EHR or across 
different geographic areas. For example, a transplant hospital may be 
connected to several local organizations, sometimes called regional 
health information organizations (RHIOs), that organize and facilitate 
exchange within a defined geographic area. Dialysis organizations are 
investing in exchange to streamline the transmission of clinical data 
and improve care coordination; for example, to support the management 
of patients across the transition of care between CKD and ESRD.\327\
---------------------------------------------------------------------------

    \325\ Sutton, P.R., & Payne, T.H. (2019). Interoperability of 
electronic health information and care of dialysis patients in the 
United States. Clinical Journal of the American Society of 
Nephrology, 14(10), 1536-1538. https://doi.org/10.2215/cjn.05300419.
    \326\ HealthIt.gov. (2019, April 18). Health Information 
Exchange [bond] HealthIT.gov. Healthit.gov. https://www.healthit.gov/topic/health-it-and-health-information-exchange-basics/health-information-exchange.
    \327\ Interoperability Reduces Provider Burden and Improves 
Patient Care. (n.d.). Fmcna.com. Retrieved March 18, 2024, from 
https://fmcna.com/insights/amr/2019/advancing-interoperability-to-reduce-provider-burden-and-improve/.
---------------------------------------------------------------------------

    Interest has also grown in the use of health information technology 
(HIT), defined at 45 CFR 170.102 as ``hardware, software, integrated 
technologies or related licenses, IP, upgrades, or packaged solutions 
sold as services that are designed for or support the use by health 
care entities or patients for the electronic creation, maintenance, 
access, or exchange of health information.'' HIT can be leveraged to 
track transplant referrals, a patient's progress through transplant 
evaluation, pre-transplant testing results, and waitlist status.\328\ 
HIT can also be used to communicate the status of a transplant referral 
and support care coordination by allowing for sharing of a patient's 
records between a dialysis facility and a transplant hospital.
---------------------------------------------------------------------------

    \328\ Wu, C., Shah, N., Sood, P., Chethan Puttarajappa, 
Bernardo, J.F., Mehta, R., Tevar, A. D., Shapiro, R., Tan, H.P., 
Wijkstrom, M., Sturdevant, M., & Hariharan, S. (2014). Use of the 
Electronic Health Record (EHR) to Improve the Pre-Transpalnt Process 
for Kidney and Pancreas Transplantation. Transplantation, 98, 833-
834. https://doi.org/10.1097/00007890-201407151-02846.
---------------------------------------------------------------------------

    Despite the growth of data exchange and investment in kidney and 
transplant care HIT, an infrastructure for interoperability that 
supports the exchange of clinical data across different HIT tools, 
different approaches to exchange, and proprietary systems and tools is 
still emerging. We understand that barriers to interoperability create 
silos that limit care coordination between transplant hospitals, as 
well as with dialysis facilities and nephrology practices.
    Use of health information exchanges that facilitate data sharing 
across different platforms, tools and non-affiliated health care 
providers, referred to hereafter as non-proprietary health information 
exchanges (HIEs), may have special value to participants in value-based 
care models. For example, a central convener could facilitate data 
sharing to support care coordination among model participants that are 
supported by different EHR vendors.\329\ Non-proprietary HIEs are 
particularly important for clinicians and health care organizations 
that do not use an EHR with a significant share of the market or who 
engage in broader co-management of their patient population.\330\
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    \329\ Everson, J., & Cross, D.A. (2019). Mind the gap: the 
potential of alternative health information exchange. The American 
journal of managed care, 25.(1), 32-38.
    \330\ Ibid.
---------------------------------------------------------------------------

    Implementation of non-proprietary exchange has been fragmented due 
to a patchwork of local, State, and Federal investments.\331\ The 
Health Information Technology for Economic and Clinical Health Act 
(HITECH Act), part of the American Recovery and Reinvestment Act of 
2009 (Pub. L. 111-5), made grants to State-based organizations to 
provide the framework and governance for non-proprietary exchange, the 
only restriction being geography.\332\ As a result, non-proprietary 
exchange can be regionally based. Non-proprietary exchange facilitated 
on a regional basis has geographic limitations, including that 
providers outside an RHIO's area of operation have little incentive to 
participate in a RHIO with other providers with which they do not share 
patients.\333\ Overcoming regional barriers to exchange could be an 
important element of realizing the value of non-proprietary exchange in 
the IOTA Model and for value-based care efforts, more broadly.
---------------------------------------------------------------------------

    \331\ Holmgren, A.J., & Adler[hyphen]Milstein, J. (2017). Health 
Information Exchange in US hospitals: The current landscape and a 
path to improved information sharing. Journal of Hospital Medicine, 
12(3), 193-198. https://doi.org/10.12788/jhm.2704.
    \332\ Ibid.
    \333\ Ibid.
---------------------------------------------------------------------------

    The Trusted Exchange Framework and Common Agreement (TEFCA) is an 
initiative to facilitate exchange of electronic health information 
across health information networks. In the 21st Century Cures Act, 
Congress required the National Coordinator to convene public-private 
and public-public partnerships to build consensus and develop or 
support a trusted exchange framework, including a common agreement 
among health information networks nationally.\334\ ONC released the 
Trusted Exchange Framework, Common Agreement--Version 1, and Qualified 
Health Information Network (QHIN) Technical Framework--Version 1, which 
appeared in the Federal Register on January 19, 2022 (87 FR 2800). 
Version 1.1 of the Common Agreement appeared in the Federal Register on 
November 7, 2023 (88 FR

[[Page 43606]]

76773). ONC anticipates releasing Version 2 of the Common Agreement in 
2024. Version 2 is anticipated to include updates that will support 
Health Level Seven (HL7[supreg]) Fast Healthcare Interoperability 
Resources (FHIR[supreg]) based transactions.\335\
---------------------------------------------------------------------------

    \334\ Section 4003(b) of the 21st Century Cures Act (Pub. L. 
114-255)
    \335\ Trusted Exchange Framework and Common Agreement (TEFCA) 
[bond] HealthIT.gov. (n.d.). www.healthit.gov. https://www.healthit.gov/topic/interoperability/policy/trusted-exchange-framework-and-common-agreement-tefca.
---------------------------------------------------------------------------

    TEFCA has three goals:
     Establish a governance, policy, and technical floor for 
nationwide interoperability;
     Simplify connectivity for organizations to securely 
exchange information to improve patient care, enhance the welfare of 
populations, and generate health care value; and
     Enable individuals to gather their health care 
information.\336\
---------------------------------------------------------------------------

    \336\ 3 . . . 2 . . . 1 . . . TEFCA is Go for Launch. (2022, 
January 18). Health IT Buzz. https://www.healthit.gov/buzz-blog/interoperability/321tefca-is-go-for-launch.
---------------------------------------------------------------------------

    TEFCA promotes interoperability by defining technical standards and 
a governing approach for secure information sharing on a national 
scale. The Recognized Coordinating Entity (RCE) develops, updates, 
implements, and maintains the Common Agreement. The RCE is also 
responsible for soliciting and reviewing applications from 
organizations seeking QHIN status, administering the QHIN designation, 
operationalizing the Common Agreement, overseeing Qualified Health 
Information Network (QHIN)-facilitated network operations, and 
monitoring compliance by participating QHINs.\337\
---------------------------------------------------------------------------

    \337\ https://rce.sequoiaproject.org/.
---------------------------------------------------------------------------

    QHINs are health information networks that agree to the common 
terms and conditions of exchange with each other, as specified in the 
Common Agreement, and to the functional and technical requirements for 
exchange (as specified in the QHIN Technical Framework (QTF)). Each 
QHIN voluntarily enters into an agreement with the RCE by signing the 
Common Agreement. On February 13, 2023, HHS announced the first six 
applicant organizations approved for onboarding as QHINs under 
TEFCA.\338\ On December 12, 2023, TEFCA became operational as five 
organizations that completed the TEFCA onboarding process were 
officially designated as QHINs.\339\ On February 12, 2024, HHS 
announced the designation of two additional organizations as 
QHINs.\340\
---------------------------------------------------------------------------

    \338\ Building TEFCA. (2023, February 13). Health IT Buzz. 
https://www.healthit.gov/buzz-blog/electronic-health-and-medical-records/interoperability-electronic-health-and-medical-records/building-tefca.
    \339\ Affairs (ASPA), A. S. for P. (2023, December 12). HHS 
Marks Major Milestone for Nationwide Health Data Exchange. 
www.hhs.gov. https://www.hhs.gov/about/news/2023/12/12/hhs-marks-major-milestone-nationwide-health-data-exchange.html.
    \340\ https://www.hhs.gov/about/news/2024/02/12/hhs-expands-tefca-by-adding-two-additional-qhins.html.
---------------------------------------------------------------------------

    CMS acknowledged the importance of TEFCA in the Medicare Program; 
Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals 
and the Long-Term Care Hospital Prospective Payment System and Policy 
Changes and Fiscal Year 2023 Rates; Quality Programs and Medicare 
Promoting Interoperability Program Requirements for Eligible Hospitals 
and Critical Access Hospitals; Costs Incurred for Qualified and Non-
Qualified Deferred Compensation Plans; and Changes to Hospital and 
Critical Access Hospital Conditions of Participation final rule (87 FR 
48780) by adding Enabling Exchange under TEFCA (87 FR 49329) as a new 
measure under the Health Information Exchange Objective for the 
Medicare Promoting Interoperability Program. Participants in the 
Medicare Promoting Interoperability Program may also earn credit for 
the Health Information Exchange Objective by reporting on the 
previously finalized Health Information Exchange (HIE) Bidirectional 
Exchange measure (86 FR 45470).
    In the Medicare and Medicaid Programs; CY 2023 Payment Policies 
Under the Physician Fee Schedule and Other Changes to Part B Payment 
and Coverage Policies; Medicare Shared Savings Program Requirements; 
Implementing Requirements for Manufacturers of Certain Single-dose 
Container or Single-use Package Drugs To Provide Refunds With Respect 
to Discarded Amounts; and COVID-19 Interim Final Rules final rule (87 
FR 70067 through 70071), CMS also added a new optional measure, 
Enabling Exchange Under TEFCA, to the Health Information Exchange 
objective for the Merit-based Incentive Payment System (MIPS) Promoting 
Interoperability performance category beginning with the CY 2023 
performance period/2025 MIPS payment year. Currently, for the CY 2024 
performance period/2026 MIPS payment year, MIPS eligible clinicians may 
fulfill the Health Information Exchange objective via three avenues by 
reporting: (1) the two Support Electronic Referral Loops measures; (2) 
the Health Information Exchange Bidirectional Exchange measure; or (3) 
the Enabling Exchange under TEFCA measure (88 FR 79357 through 79362).
    CMS would like to support IOTA participants' interoperability 
efforts that could lead to best practices in CKD and ESRD care. 
However, we recognize that given the existing Federal interoperability 
initiatives, we do not want to create duplicate efforts or create 
unnecessary burden on IOTA participants. We are seeking comment on how 
CMS can promote interoperability in the proposed IOTA model; in 
particular, we seek comment on the extent to which participants are 
planning on participating in TEFCA in the next 1-2 years, as well as 
other means by which interoperability may support care coordination in 
the IOTA model. Any further proposals related to interoperability 
included in the IOTA model would be proposed through future notice and 
comment rulemaking.

IV. Collection of Information Requirements

    The Standard Provisions for Innovation Center Models and the 
Increasing Organ Transplant Access (IOTA) Model would be implemented 
and tested under the authority of the CMS Innovation Center. Section 
1115A of the Act authorizes the CMS Innovation Center to test 
innovative payment and service delivery models that preserve or enhance 
the quality of care furnished to Medicare, Medicaid, and Children's 
Health Insurance Program beneficiaries while reducing program 
expenditures. As stated in section 1115A(d)(3) of the Act, Chapter 35 
of title 44, United States Code, shall not apply to the testing and 
evaluation of models under section 1115A of the Act. As a result, the 
information collection requirements contained in this proposed rule 
would need not be reviewed by the Office of Management and Budget.

V. Regulatory Impact Analysis

A. Statement of Need

    The best treatment for most patients with kidney failure is 
transplantation. Kidney transplants provide improved survival and 
quality of life relative to dialysis and generates savings to the 
Medicare Trust Fund over 10 years, but only 30 percent of patients with 
end-stage renal disease (ESRD) are living with one.\341\ The 
underutilization of kidney transplantation is particularly

[[Page 43607]]

prominent among structurally disadvantaged populations. The kidney 
transplant process involves silos of care, gaps in accountability, 
disparities, and misaligned financial incentives that we believe value-
based care incentives are well positioned to target.\342\
---------------------------------------------------------------------------

    \341\ Organ Procurement and Transplantation Network. Kidney 
Donor Profile Index (KDPI) Guide for Clinicians. https://
optn.transplant.hrsa.gov/professionals/by-topic/guidance/kidney-
donor-profile-index-kdpi-guide-for-clinicians/
#:~:text=Figure%201%20shows%20that%20a,function%20for%20about%209%20y
ears; United States Renal Data System. 2022. USRDS Annual Report. 
Volume 2. End-stage Renal Disease (ESRD) in the United States, 
Chapter 9: Healthcare Expenditures for Persons with ESRD. Figure 
9.11.
    \342\ King, K.L., Husain, S.A., Schold, J.D., Patzer, R.E., 
Reese, P.P., Jin, Z., Ratner, L.E., Cohen, D.J., Pastan, S.O., & 
Mohan, S. (2020). Major Variation across Local Transplant Centers in 
Probability of Kidney Transplant for Wait-Listed Patients. Journal 
of the American Society of Nephrology, 31(12), 2900-2911. https://doi.org/10.1681/ASN.2020030335.
---------------------------------------------------------------------------

    The proposed IOTA Model would be a mandatory payment model, 
beginning on January 1, 2025, and ending December 31, 2030, that tests 
whether upside and downside performance-based payments (``upside risk 
payments'' and ``downside risk payments'') increase the number of 
kidney transplants performed by select IOTA participants (that is, 
transplant hospitals). Performance would be measured across three 
domains: (1) Achievement; (2) Efficiency; and (3) Quality. The 
achievement domain would assess each selected IOTA participant on the 
overall number of kidney transplants performed relative to a 
participant-specific target. The efficiency domain would assess the 
kidney organ offer acceptance rates of each selected IOTA participant 
relative to a national rate. The quality domain would assess the 
quality of care provided by the selected IOTA participant across a set 
of outcome metrics and quality measures. Each selected IOTA 
participant's performance score across these three domains would 
determine the amount of the performance-based payment that CMS would 
pay to the selected IOTA participant, or that the selected IOTA 
participant would pay to CMS. The upside risk payment would be a lump 
sum payment paid by CMS to the selected IOTA participants with high 
final performance scores. Conversely, the downside risk payment would 
be a lump sum payment paid to CMS by the selected IOTA participants 
with low final performance scores.
1. Analytic Baseline
    Historical data for the analytic baseline are from the Organ 
Procurement and Transplant Network/Scientific Registry of Transplant 
Recipients (OPTN/SRTR).\343\ There were 24,667 total adult kidney 
transplants in the United States in 2021, with a growth rate of 7.3 
percent from 2020 to 2021. Similarly, the 5-year compound annual growth 
rate (CAGR) for the pre-pandemic years of 2015-2019 was 7.1 percent. 
The majority, 86.7 percent, of adult kidney transplants were from 
deceased donors in 2021. The trend in growth for deceased donor kidney 
transplants has been steadily increasing since the revision of the 
kidney allocation system in 2014, while the trend in growth for living 
donor kidney transplants has been relatively stable. The number of 
adult deceased donor kidney transplants increased 5.7 percent from 2020 
to 2021, a slowdown from the 2015-2019 CAGR of 7.8 percent.
---------------------------------------------------------------------------

    \343\ Organ Procurement and Transplant Network/Scientific 
Registry of Transplant (OPTN/SRTR). ``OPTN/SRTR YYYY Annual Data 
Report: Kidney. Supplemental Data Tables.'' Where YYYY is for report 
years 2015, 2018, 2019, 2020, and 2021. https://www.srtr.org/reports/optnsrtr-annual-data-report/.
---------------------------------------------------------------------------

    Among the 18,931 adult deceased donor kidney transplant recipients 
in 2021, 64.7 percent reported Medicare as their primary payer (stable 
from 64.8 percent in 2020) and 24.0 percent reported private insurance 
as their primary payer (down from 25.7 percent in 2020). Deceased donor 
kidney transplant recipients had 2015-2019 CAGR of 6.9 percent for 
Medicare as their primary payer and 11.6 percent for private insurance 
as their primary payer. The age distribution of the 18,931 adult 
deceased donor kidney transplant recipients in 2021 showed that the 
majority of recipients are younger than the aged Medicare population. 
Specifically, 11.5 percent of recipients were ages 18-34 years, 26.1 
percent were ages 35-49 years, 40.5 percent were ages 50-64 years, and 
21.9 percent were at least 65 years of age at the time of transplant. 
The 2015-2019 CAGR was greatest for the two latter age categories, at 
9.3 percent and 14.4 percent for ages 50-64 years and 65+ years, 
respectively.
    The supply of donated kidneys has not grown with the demand from 
kidney transplant recipient candidates. There were a total of 96,130 
adult kidney transplant candidates on the transplant waitlist at the 
end of the year in 2021, which included 41,765 newly added candidates. 
The number of newly added adult candidates to the waitlist increased 
11.7 percent from 2020 to 2021, recovering from the pandemic-related 
decline in the prior year, and exceeding the 2015-2019 CAGR of 9.2 
percent.
    For the proposed model, we assumed an average of $40,000 in savings 
to Medicare over a 10-year period for each additional kidney transplant 
furnished to a Medicare beneficiary compared to remaining on dialysis. 
For the 50 percent of IOTA participants proposed to be randomly 
selected to participate in the model, we assume that the total number 
of kidney transplants from all payers over the 6-year model performance 
period would have a CAGR of 6.6 percent in the absence of the model 
(for example, if the rule is not finalized). We also assume that the 6-
year model performance period CAGR for the total number of kidney 
transplants furnished to beneficiaries with Medicare as the primary 
payer would be 7.0 percent. The baseline share of deceased donor 
kidneys that are currently discarded is roughly 20 percent. If the IOTA 
Model were not implemented, then IOTA participants would not have the 
performance-based upside and downside risk payments to increase their 
organ offer acceptance rate. Therefore, pre-pandemic growth rates for 
deceased donor kidney transplants would be expected to continue during 
the projection period. The living donor kidney transplant growth rate 
is also expected to continue close to pre-pandemic rates in the absence 
of the model.
    One initiative and one recent reform have the potential to impact 
the IOTA study population, even in the absence of the proposed model. 
First, the OPTN Modernization Initiative that HRSA announced in March 
2023 includes several actions to strengthen accountability, 
transparency, equity, and performance in the OPTN.\344\ Some of the 
proposed OPTN Modernization Initiative actions that are relevant to the 
IOTA Model's target population include data dashboards detailing 
individual transplant center and organ procurement organization data on 
organ retrieval, waitlist outcomes, and transplants, and demographic 
data on organ donation and transplant will be made available to 
patients. In the absence of the IOTA Model, the OPTN Modernization 
Initiative has the potential to incentivize IOTA participants to 
improve upon some of the IOTA model's incentive domains, such as 
improving the organ offer acceptance rate, post-transplant outcomes, 
and patient equity.
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    \344\ HHS. 2023. ``HRSA Announces Organ Procurement and 
Transplantation Network Modernization Initiative.'' https://www.hhs.gov/about/news/2023/03/22/hrsa-announces-organ-procurement-transplantation-network-modernization-initiative.html.
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    Second, the Comprehensive Immunosuppressive Drug Coverage for 
Kidney Transplant Patients Act (H.R. 5534; also known as the Immuno 
Bill) passed in November 2020, which stipulates lifelong coverage for 
immunosuppressive drugs for kidney transplant recipients, has the 
potential to improve patient survival.\345\

[[Page 43608]]

Beginning January 1, 2023, the Medicare Part B Immunosuppressive Drug 
benefit covers immunosuppressive drugs beyond 36 months for eligible 
kidney transplant recipients that do not have other health coverage for 
immunosuppressive drugs. The most current statistics of post-transplant 
patient survival are reported by Hariharan et al.\346\ The authors used 
data from the OPTN/SRTR and found that post-deceased donor kidney 
transplant patient survival rates at years 1 and 3 are 97.1 percent and 
93.3 percent, respectively, for transplantation taking place during 
2016-2019. Post-living donor kidney transplant patient survival rates 
are 99.1 percent and 96.5 percent during the same period. These rates 
decrease over the longer term. For kidney transplantation during 2008-
2011, patient survival rates at 10 years are 66.9 percent for deceased 
donor kidney transplants and 81.3 percent for living donor kidney 
transplants. The authors project that survival rates will continue to 
improve, explaining that the decline in survival starting 3 years after 
transplantation has been attributed to, and coincides with, the 
discontinuation of insurance coverage for long-term immunosuppressive 
medications.
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    \345\ CMS. 2022. ``Medicare Program; Implementing Certain 
Provisions of the Consolidated Appropriations Act, 2021 and Other 
Revisions to Medicare Enrollment and Eligibility Rules. Final 
Rule.'' Federal Register 87 FR 66454: 66454-66511.
    \346\ Hariharan S, Irani AK, Danovitch G (2023). ``Long-Term 
Survival after Kidney Transplantation.'' New England Journal of 
Medicine. 385:729-43. https://www.nejm.org/doi/full/10.1056/NEJMra2014530.
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B. Overall Impact

    We have examined the impacts of this rule 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), Executive Order 14094 entitled ``Modernizing 
Regulatory Review'' (April 6, 2023), 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).
    Executive Orders 12866 and 13563 direct agencies to assess all 
costs and benefits of available regulatory alternatives and, if 
regulation is necessary, to select regulatory approaches that maximize 
net benefits (including potential economic, environmental, public 
health and safety effects, distributive impacts, and equity). The 
Executive Order 14094 entitled ``Modernizing Regulatory Review'' 
(hereinafter, the Modernizing E.O.) amends section 3(f)(1) of Executive 
Order 12866 (Regulatory Planning and Review). The amended section 3(f) 
of Executive Order 12866 defines a ``significant regulatory action'' as 
an action that is likely to result in a rule: (1) having an annual 
effect on the economy of $200 million or more in any 1 year (adjusted 
every 3 years by the Administrator of OIRA for changes in gross 
domestic product), or adversely affect in a material way the economy, a 
sector of the economy, productivity, competition, jobs, the 
environment, public health or safety, or State, local, territorial, or 
tribal governments or communities; (2) creating a serious inconsistency 
or otherwise interfering with an action taken or planned by another 
agency; (3) materially altering the budgetary impacts of entitlement 
grants, user fees, or loan programs or the rights and obligations of 
recipients thereof; or (4) raise legal or policy issues for which 
centralized review would meaningfully further the President's 
priorities or the principles set forth in this Executive order, as 
specifically authorized in a timely manner by the Administrator of OIRA 
in each case.
    A regulatory impact analysis (RIA) must be prepared for major rules 
with significant regulatory action/s and/or with significant effects as 
per section 3(f)(1) ($200 million or more in any 1 year). Based on our 
estimates from the CMS Office of the Actuary, OMB's Office of 
Information and Regulatory Affairs (OIRA) has determined this 
rulemaking is not significant per section 3(f)(1). Accordingly, we have 
prepared an RIA that to the best of our ability presents the costs and 
benefits of the rulemaking. Pursuant to Subtitle E of the Small 
Business Regulatory Enforcement Fairness Act of 1996 (also known as the 
Congressional Review Act), OIRA has also determined that this rule does 
not meet the criteria set forth in 5 U.S.C. 804(2). We solicit comment 
on the RIA.

C. Detailed Economic Analysis

    Several important factors have been identified that lead to the 
discard of donated kidneys, including significant increased cost to 
hospitals for transplanting organs from older donors and/or donors with 
comorbidities. Value-based payments that reward hospitals for 
increasing the number of transplants as well as related quality and 
process measures may improve the acceptance of offered organs and 
outcomes for patients.\347\ A stochastic model was constructed to 
estimate the financial impact of the IOTA model. When possible, 
assumptions were informed by historical data. Transplant hospital adult 
transplant counts by donor type and recipients' primary source of 
payment were obtained from the SRTR dashboard.\348\ Organ offer 
acceptance ratios \349\ and survival rate data (for both years 1 and 3) 
\350\ were analyzed from SRTR's program-specific statistics and 
transplant hospital-level data on kidney transplants. The SRTR data 
source includes data on all transplant donors, candidates, and 
recipients in the U.S.
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    \347\ Cooper, M. et. al. (2018). Report of the National Kidney 
Foundation Consensus Conference to Decrease Kidney Discards. Journal 
of Clinical Transplantation and Translational Research, https://doi.org/10.1111/ctr.13419.
    \348\ Scientific Registry of Transplant Recipients. Adult 
Recipient Transplants By Donor Type, Center: U.S. Transplants 
Performed: January 1, 1988-July 31, 2023; For Organ = Kidney; 
Include: Transplant Year & Recipient Primary Source of Payment. 
https://optn.transplant.hrsa.gov/data/view-data-reports/national-data/. Accessed October 17, 2022.
    \349\ Scientific Registry of Transplant Recipients. National 
Center Level Data by Organ: Kidney CSRS Final Tables, Table B11 & 
Figures B10-B14. https://www.srtr.org/reports/program-specific-reports/. Accessed May 25, 2023.
    \350\ Scientific Registry of Transplant Recipients. National 
Center Level Data by Organ: Kidney CSRS Final Tables, Tables C5-C12 
Figures C1-C20. https://www.srtr.org/reports/program-specific-reports/. Accessed May 25, 2023.
---------------------------------------------------------------------------

    IOTA participants would receive upside or downside risk payments 
based on their performance across three domains: achievement, 
efficiency, and quality. The three domains would measure certain 
metrics and award points as shown in the following Table 12:

[[Page 43609]]

[GRAPHIC] [TIFF OMITTED] TP17MY24.012

    The upside risk payment would be a lump sum payment paid by CMS to 
the IOTA participants that achieve high final performance scores. 
Conversely, the downside risk payment would be a lump sum payment paid 
to CMS by the IOTA participants with low final performance scores. The 
performance-based payments would be based on the following thresholds. 
Total scores of 60 and above would result in a maximum upside risk 
payment of $8,000, as shown in equation 4. Scores below 60 would fall 
into the neutral zone with no upside or downside risk payment in PY 1. 
After the first PY, scores from 41 to 59 would fall in the neutral 
zone, and scores of 40 and below would receive a downside risk payment. 
The maximum downside risk payment in the model would be $2,000, as 
shown in equation 5. This performance-based payment would then be 
multiplied by the total number of kidney transplants furnished by the 
IOTA participant to attributed patients for which model payments apply 
during the PY.
Equation 4: IOTA Upside Risk Payment for Scores of 60 and Above
IOTA Lump Sum Payment = $8,000 * ((Final Performance Score-60)/40) * 
Medicare Kidney Transplants
Equation 5: IOTA Downside Risk Payment for Scores of 40 and Below
IOTA Performance Payment = $2,000 * ((40-Final Performance Score)/40) * 
Medicare Kidney Transplants

    CMS randomly selected half of all DSAs in the country and all 
eligible IOTA participants within those DSAs and applied assumptions 
for transplant growth and performance on other domains affecting the 
incentive formula for purposes of estimating impacts in this portion of 
the rule. Random variables accounted for variation in transplant growth 
and transplant hospital-level performance on other measures. A pivotal 
uncertainty relates to the potential growth in transplants as a result 
of upside and downside risk payments presented by the model. The 
current share of deceased donated kidneys that are discarded is roughly 
20 percent.351 352 Such growth was assumed to phase in over 
a 2- to 5-year period using a skewed distribution, with a gradual 
phase-in of 5 years being the most likely outcome.
---------------------------------------------------------------------------

    \351\ Li MT, King KL, Husain SA, et al. 2021. ``Deceased Donor 
Kidneys Utilization and Discard Rates During COVID-19 Pandemic in 
the United States.'' Kidney Int Rep; 6(9): 2463-2467. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419126/.
    \352\ Robinson A, Booker S, Gauntt K, UNOS Research Department. 
2022. ``Eliminate Use of DSA and Region from Kidney Allocation One 
Year Post-Implementation Monitoring Report.'' OPTN Kidney 
Transplantation Descriptive Data Report. https://optn.transplant.hrsa.gov/media/p2oc3ada/data_report_kidney_full_20220624_1.pdf.
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    For IOTA participants randomized into the model, assumptions were 
also made for gradual improvement over baseline kidney acceptance 
rates, with individual IOTA participants assumed to have, in year 1, up 
to a 10-percent chance (up to a 20-percent chance by year 2, etc.) of 
increasing their acceptance ratio by between 20 to 80 percentage points 
and maintaining such simulated improvement in ensuing model years. The 
share of IOTA participants receiving passing confidence intervals for 
the 1-year and 3-year failure ratios was assumed to be roughly 95 
percent in year 1, gradually improving by about half of a percentage 
point per year. Please see section III.C.5.e.(1). of this rule for the 
discussion on post-transplant outcomes.
    CMS assumed that all quality measures would be successfully 
reported by all IOTA participants in model PYs 1 and 2 (resulting in 
uniformly maximum scores in that domain). Table II illustrates below 
that on average, 60 percent of IOTA participants were assumed to 
achieve maximum quality scores throughout the remaining 4 years of the 
model; 30 percent were assumed to gradually improve from scores of 5 to 
8 in year 3 to scores of 5 to 9 by year 6; and 10 percent were assumed 
to improve from scores of 2 to 7 in year 3 to scores of 3 to 8 by year 
6. We assumed that most IOTA participants would be able to maximize 
scores early in the testing period and a minority would require more 
time to reach a higher scoring level. Actual scoring distributions will 
depend on how CMS ultimately sets targets and how IOTA participants 
respond.

[[Page 43610]]

[GRAPHIC] [TIFF OMITTED] TP17MY24.013

    Table III later in this section shows the projected impacts for 
upside and downside risk payments, transplants, and Federal spending. 
Although transplant recipients with any type of insurance may benefit 
from a transplant hospital's participation in the model, model payments 
will be based on the number of transplant recipients who are 
beneficiaries with Medicare fee-for-service (FFS) coverage and 
beneficiaries enrolled in Medicare as a secondary payer. In any given 
year, about 30 percent of IOTA participants are projected to receive 
upside risk payments (ranging from 20 to 40 percent), with only about 
half of that number of IOTA participants projected to have a downside 
risk payment in any of years 2 through 6 (ranging from 10 to 23 
percent). However, the magnitude of the average downside risk payment 
is relatively small, and the cumulative projected upside risk payments 
to IOTA participants, amounting to $36 million, are over 30 times the 
magnitude of a cumulative $1 million in projected receipts from 
downside risk payments from IOTA participants to CMS. The amount of 
projected savings from new transplants was greater than the net cost of 
payments in 85 percent of simulation trials. Mean net savings totaled 
$65 million over 6 years, ranging from a savings of $151 million to a 
cost of $11 million at the 10th and 90th percentiles.
[GRAPHIC] [TIFF OMITTED] TP17MY24.014

    In Table III, negative spending reflects a reduction in Medicare 
spending, while positive spending reflects an increase in Medicare 
spending. The mean net savings results were generated from the average 
of 400 individual simulation trials and the results for the percentiles 
are from the top 10th and 90th percentiles of the 400 individual 
simulations. The outcomes in each row do not necessarily flow from the 
same trial in the model at the 10th and 90th percentiles. For example, 
the 90th percentile for added transplants more likely corresponds to 
the trial that produced the 10th percentile in impact on FFS spending 
from those transplants (because spending is reduced when transplants 
grow).
    There is a wide range of potential changes in Federal spending for 
each new transplant. Savings on avoided dialysis may in many cases be 
exceeded when transplants are especially complex and post-transplant 
complications are more likely, for example when deceased organs have a 
high kidney donor profile index and/or recipients are of advanced 
age.\353\ But even in such cases Federal savings can be substantial if 
Medicare is not primary payer at time of transplant or the beneficiary 
eventually returns to private insurance post-transplant. We relied on 
the savings per transplant estimate published in the ESRD Treatment 
Choices (ETC) model final rule \354\ to account for different primary 
payer scenarios at the time of transplant, as well as the likelihood 
that the beneficiary would have remained on Medicare after 
transplantation. For the ETC model, OACT produced a 10-year savings to 
Medicare of approximately $32,000 per beneficiary for a deceased donor 
kidney transplant with a high-kidney donor profile index. For the 
proposed IOTA model, we assumed the average Federal spending impact 
could range from a cautious $20,000 increase to optimistically at most 
a $100,000 savings per additional transplant (mean assumption being a 
$40,000 savings).
---------------------------------------------------------------------------

    \353\ Axelrod DA, Schnitzler MA, Xiao H, et al. 2018. ``An 
Economic Assessment of Contemporary Kidney Transplant Practice.'' 
American Journal of Transplantation 18: 1168-1176. https://pubmed.ncbi.nlm.nih.gov/29451350/.
    \354\ Medicare Program; Specialty Care Models To Improve Quality 
of Care and Reduce Expenditures, 85 FR 61335 (September 29, 2020) 
(codified at 45 CFR part 512, subpart A).
---------------------------------------------------------------------------

    The mean assumption of $40,000 in savings is marginally higher than 
the ETC model's 10-year estimated savings to Medicare of approximately 
$32,000 per beneficiary for a deceased donor kidney transplant with a 
high-kidney donor profile index because it includes at least some 
potential for an increase in other types of transplants. The 10-year 
estimated savings to Medicare of approximately $32,000 per beneficiary 
used in the ETC model based on deceased donor, high-kidney donor 
profile transplants was assumed because of the relatively limited focus 
that model appeared to have on improving the number of transplants and 
outcomes

[[Page 43611]]

for transplants. By comparison, the estimate for the IOTA Model still 
focused on deceased donor kidneys, but this model warranted a 
marginally higher savings per transplant estimate, allowing for the 
mean assumption of $40,000 in savings. To determine the outer bounds of 
the assumption, we identified individual points in our organ-type/payer 
matrix that ranged from a $100,000 increase in costs to $200,000 (or 
wider) in savings, so the bounds we chose for the estimate were based 
on realizing new transplants were going to be mixed across the matrix 
and not all congregated at an extreme end on one side or the other 
(keeping in mind that they will likely come mostly from decedent donor 
kidneys). We assumed that kidney transplant savings would accumulate in 
the year of the transplant even though the cost of the transplant 
would, in practice, lead to higher spending in the first year (unless 
Medicare was not the primary payer). It would likely take longer than 
the 6 model years for the cumulative net savings projected in Table III 
to ultimately materialize. The timing of when savings would accumulate 
could not be estimated with more precision for the following reasons. 
Savings could range from being virtually immediate if new transplants 
occur when a beneficiary is not Medicare primary payer status, to being 
backloaded if the beneficiary receives the transplant when Medicare is 
primary payer, to being a net cost if the beneficiary transplant fails 
within a short period after transplant. Given those uncertainties, and 
the underlying uncertainties about where the new transplants will 
materialize from (by donor and recipient), we were not able to imply 
more precision than we were able to model from the evidence.
    While the proposed model is focused on transplant outcome measures 
that would be calculated by CMS, there would likely be some additional 
burden for compliance for the IOTA participants (that is, transplant 
hospitals). To estimate the compliance cost we focused on the proposed 
patient-reported survey measure. We estimate that the average IOTA 
participant would perform 50 surveys per year and that it would take a 
clinician 20 minutes to complete the survey. Using base wage 
information from BLS for a nurse practitioner, we estimate the cost of 
completing these surveys to be $59.94 per hour. The base wage is then 
doubled [$59.94 x 2] to account for fringe benefits and overhead to 
equal an estimated cost of $119.88 per hour.\355\ The cost of 
completing these surveys would then be $1,998 per hospital per year [50 
surveys x (\1/3\) hour per survey x $119.88 hourly wage]. Therefore, 
the total cost would come out to $179,820 to complete the surveys based 
on the assumption that 90 active transplant hospitals will be selected 
as IOTA participants [$1,998 x 90 hospitals = $179,820]. Average total 
revenue for the transplant hospitals that may be selected to be an IOTA 
participant using inpatient hospital codes DRG-008 simultaneous 
pancreas-kidney transplant and DRG-652 kidney transplant generated from 
adult Medicare FFS beneficiaries with Medicare as their primary payer 
was $1.2 million in calendar year 2022. Therefore, the $1,998 cost per 
IOTA participant to complete the patient-reported survey measure would 
represent 0.2 percent of the estimated total annual revenue per IOTA 
participant from DRGs 653 and 008 when Medicare is the primary payer.
---------------------------------------------------------------------------

    \355\ Guidelines for the adjustment in base wages is based on 
the following report: Office of the Assistant Secretary for Planning 
and Evaluation (ASPE). 2017. ``Valuing Time in U.S. Department of 
Health and Human Services Regulatory Impact Analyses: Conceptual 
Framework and Best Practices.'' https://aspe.hhs.gov/reports/valuing-time-us-department-health-human-services-regulatory-impact-analyses-conceptual-framework.
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1. Regulatory Review Cost Estimation
    We estimate the time it will take for a medical and health services 
manager to review the rule to be 5.33 hours [80,000 words/250 words per 
minute/60 minutes = 5.33 hours]. Using the wage information from the 
Bureau Labor of Statistics (BLS) for medical and health service 
managers (Code 11-9111), we estimate that the cost of reviewing this 
rule is $123.06 per hour, including overhead and fringe benefits.\356\ 
The cost of reviewing the rule would therefore be a $655.91 per 
hospital [5.33 hours x $123.06 per hour = $655.91] or a total cost of 
$59,031.90 [$655.91 x 90 hospitals = $59,031.90]. Using information 
from the OPTN, we estimate 230 active kidney transplant hospitals that 
are the potential IOTA participants would review this rule for a total 
cost of $150,859.30 [$655.91 per hospital x 230 hospitals = 
$150,859.30].\357\ In addition, the $655.91 cost per IOTA participant 
to complete the regulatory review would represent 0.1 percent of the 
estimated total annual revenue from DRGs 653 and 008 when Medicare is 
the primary payer.
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    \356\ Bureau of Labor Statistics (BLS). 2022. ``Occupational 
Employment and Wage Statistics.'' https://www.bls.gov/oes/current/oes_nat.htm.
    \357\ https://optn.transplant.hrsa.gov.
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D. Alternatives Considered

    Two alternative model specifications were tested for comparison to 
the results in Table III. The first alternative model specification 
estimated the impact of including MA beneficiaries as eligible 
transplant recipients for purposes of upside and downside risk payments 
to IOTA participants. Currently, MA beneficiaries represent 
approximately 50 percent of Medicare ESRD beneficiaries receiving 
transplants, and this share is expected to grow. Over the 6-year 
period, the projected costs from total net payments increased slightly 
from $35 million in the primary model specification to $47 million in 
this first alternative. As expected, most of the impact of the 
inclusion of MA beneficiaries was observed in added transplants, which 
increased from 2,625 to 3,428 and from $100 million to $133 million in 
savings. When MA beneficiaries were included, the mean net savings 
increased marginally from the primary model specification to $86 
million over 6 years, ranging from a savings of $201 million to a cost 
of $10 million at the 10th and 90th percentiles.
    The second alternative model specification excluded MA 
beneficiaries (that is, returned to the population of the primary model 
specification) and tested the use of a continuous grading scale instead 
of bands in the achievement domain for transplants for which the upside 
risk payments become much more generous (particularly for IOTA 
participants that would otherwise have resulted in a neutral outcome). 
The continuous grading scale works by taking the first year equity-
adjusted-transplants-to-target ratio for each IOTA participant and 
divides that by 2.5 times 100 and has a ceiling of 60 points. The 
reason why the continuous grading scale is costly is because it 
provides upside risk payments to a much larger group of IOTA 
participants because it gives sliding scale partial credit for IOTA 
participants that get above 1.00 in their ratio whereas the proposed 
method makes them go all the way to a ratio of 1.25 before they get 
more than 30 points (for example, they jump up to 45 points). Using the 
continuous grading scale approach, the cumulative projected upside risk 
payments grew from $36 million in the primary model specification to 
$118 million in this second alternative. The projected receipts from 
downside risk payments levied and the projected savings from new 
transplants were similar to the estimated impacts under the primary 
model specification. Overall, the mean

[[Page 43612]]

net savings for the second alternative significantly changed in sign 
and magnitude from the primary specification to $15 million in 
increased costs over 6 years, ranging from a savings of $77 million to 
a cost of $90 million at the 10th and 90th percentiles. This 
alternative model specification was not selected because we chose to 
create bands of performance rather than a continuous scale to provide 
participants with clear end points to incentivize performance to hit 
specific thresholds.

E. Impact on Beneficiaries

    The upside and downside risk payments in this model are expected to 
at least marginally increase the number of kidney transplants provided 
to beneficiaries with ESRD. This proposed model is projected to result 
in over 2,600 new transplants over the 6-year model performance period. 
Evidence shows that kidney transplants extend patients' lives and that 
such benefits have been increasing despite unfavorable trends in terms 
of donor and recipient risk factors.\358\ Even if added transplants 
most often were to involve high Kidney Donor Profile Index (KDPI) 
organs (that are most often discarded historically), the average 
recipient would still be expected to benefit from increased quality of 
life and longevity.\359\ In addition--though we did not explicitly 
assume specific benefits to beneficiaries--the model would include 
quality measures aimed at improving outcomes even for transplants that 
would have otherwise occurred absent the model. IOTA participants would 
be incentivized to improve graft survival outcomes (measured at 1 year 
post-transplant). The model could also improve the efficiency with 
which hospitals interact with organ procurement organizations and 
reduce the time from deceased organ donation to transplant surgery. 
These and other elements of the model have the potential to improve 
outcomes for the wider group of transplant patients beyond the fraction 
assumed to receive transplants under the proposed model.
---------------------------------------------------------------------------

    \358\ Hariharan S., Irani A.K., Danovitch G., (2023). ``Long-
Term Survival after Kidney Transplantation.'' New England Journal of 
Medicine. 385:729-43. https://www.nejm.org/doi/full/10.1056/NEJMra2014530.
    \359\ Axelrod D.A., Schnitzler M.A., Xiao H., et al. 2018. ``An 
Economic Assessment of Contemporary Kidney Transplant Practice.'' 
American Journal of Transplantation 18: 1168-1176. https://pubmed.ncbi.nlm.nih.gov/29451350/.
---------------------------------------------------------------------------

F. Accounting Statement and Table

    The annualized monetized benefits and transfers in Table IV were 
calculated based on constant payments and constant interest rates. 
Using the row labeled Total as an example for how the results were 
calculated, the primary estimate of $10 million in total savings was 
based on a 7 percent discount rate, with a 6-year study period, and a 7 
percent net present value of $45.6 million in savings. Net present 
value for the primary estimate was based on the IOTA Model's mean net 
savings estimate for years 2025-2030 reported in the bottom row of 
Table III. The minimum and maximum annualized monetized total benefits 
and transfers reported in Table IV use the same calculation as the 
primary estimate, with the exception of the annual mean net savings 
replaced with the IOTA model's annual mean net savings for the 10th and 
90th percentiles.
[GRAPHIC] [TIFF OMITTED] TP17MY24.015

[GRAPHIC] [TIFF OMITTED] TP17MY24.016

G. Regulatory Flexibility Act (RFA)

    Effects on IOTA participants in the proposed model include the 
potential for additional upside risk payments from CMS to the IOTA 
participant of up to $8,000 per eligible kidney transplant or downside 
risk payments from the IOTA participant to CMS of up to $2,000 per 
eligible kidney transplant (refer to section IV.C. of this proposed 
rule (Detailed Economic Analysis) for a description of how upside and 
downside risk payments are calculated in the model). We project that 
payouts will far exceed the relatively small sum of downside risk 
payments expected over the 6-year model performance period. Only about 
$1 million in total downside risk payments are expected over 6 years 
from approximately 10 to 23 percent of IOTA participants expected to be 
charged downside risk payments from year to year. By contrast, we 
project over 6 years that $36 million in total upside risk payments 
would be made to between 20 to 40 percent of IOTA participants expected 
to earn payments in the model from year to year.
    The RFA requires agencies to analyze options for regulatory relief 
of small entities, if a rule has a significant impact on a substantial 
number of small entities. The great majority of hospitals and most 
other health care providers and suppliers are small entities, either by 
being nonprofit organizations or by meeting the SBA definition of a 
small business (having revenues of less than $8.0 million to $41.5 
million in any 1 year). Although many IOTA participants

[[Page 43613]]

may be small entities as that term is used in the RFA, kidney 
transplants only represent a small fraction of the revenue such 
hospitals generate, and even the largest per-transplant downside risk 
payment of $2,000 (which notably is expected to be a very rare outcome 
in general) would not represent a significant economic impact. 
Additional sources of financial burden on IOTA participants to consider 
include the estimated cost of $1,998 per IOTA participant per year to 
complete the patient-reported survey that is included in the quality 
measure set and the one time cost of $655.91 per IOTA participant to 
have their medical and health services manager review this rule.
    As its measure of significant economic impact on a substantial 
number of small entities, HHS uses a change in revenue of more than 3 
to 5 percent. We do not believe that this threshold will be reached by 
the requirements in this proposed rule. Therefore, the Secretary has 
certified that this proposed rule will not have a significant economic 
impact on a substantial number of small entities.
    In addition, section 1102(b) of the Act requires us to prepare a 
regulatory impact analysis if a rule may have a significant impact on 
the operations of a substantial number of small rural hospitals. This 
analysis must conform to the provisions of section 603 of the RFA. For 
purposes of section 1102(b) of the Act, we define a small rural 
hospital as a hospital that is located outside of a metropolitan 
statistical area and has fewer than 100 beds. We believe this proposed 
rule will not have a significant impact on small rural hospitals since 
small rural hospitals do not have the resources to perform kidney 
transplants. Therefore, the Secretary has certified that this proposed 
rule will not have a significant impact on the operations of a 
substantial number of small rural hospitals.

H. Unfunded Mandates Reform Act (UMRA)

    Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also 
requires that agencies assess anticipated costs and benefits before 
issuing any rule whose mandates require spending in any 1 year of $100 
million in 1995 dollars, updated annually for inflation. In 2024, that 
threshold is approximately $183 million. This proposed does not mandate 
any requirements for State, local, or tribal governments, or for the 
private sector.

I. Federalism

    Executive Order 13132 establishes certain requirements that an 
agency must meet when it promulgates a proposed rule (and subsequent 
final rule) that imposes substantial direct requirement costs on State 
and local governments, preempts State law, or otherwise has Federalism 
implications. This proposed rule would not have a substantial direct 
effect on State or local governments, preempt States, or otherwise have 
a Federalism implication.

VI. Response to Comments

    Because of the large number of public comments we normally receive 
on Federal Register documents, we are not able to acknowledge or 
respond to them individually. We will consider all comments we receive 
by the date and time specified in the DATES section of this preamble, 
and, when we proceed with a subsequent document, we will respond to the 
comments in the preamble to that document.
    Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & 
Medicaid Services, approved this document on April 30, 2024.

List of Subjects in 42 CFR Part 512

    Administrative practice and procedure, Health facilities, Medicare, 
Recordkeeping requirements.

    For the reasons set forth in the preamble the Centers for Medicare 
& Medicaid Services proposes to amend 42 CFR part 512 as follows:

0
1. The part heading for part 512 is revised to read as follows:

PART 512--STANDARD PROVISIONS FOR INNOVATION CENTER MODELS AND 
SPECIFIC PROVISIONS FOR THE RADIATION ONCOLOGY MODEL AND THE END 
STAGE RENAL DISEASE TREATMENT CHOICES MODEL

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

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

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

Subpart A--Standard Provisions for Innovation Center Models

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


Sec.  512.100  Basis and scope.

    (a) Basis. This subpart implements certain standard provisions for 
Innovation Center models, as that term is defined in this subpart.
    (b) Scope. (1) The regulations in this subpart apply to each 
Innovation Center model that--
    (i) Began its first performance period before January 1, 2025, if 
incorporated by reference, in whole or in part, into the Innovation 
Center model's governing documentation; or
    (ii) Begins its first performance period on or after January 1, 
2025, unless otherwise specified in the Innovation Center model's 
governing documentation.
    (2) This subpart sets forth the following:
    (i) Basis and scope.
    (ii) Definitions.
    (iii) Beneficiary protections.
    (iv) Cooperation in model evaluation and monitoring.
    (v) Audits and record retention.
    (vi) Rights in data and intellectual property.
    (vii) Monitoring and compliance.
    (viii) Remedial action.
    (ix) Innovation Center model termination by CMS.
    (x) Limitations on review.
    (xi) Miscellaneous provisions on bankruptcy and other 
notifications.
    (xii) Reconsideration review processes.
    (3) Except as specifically noted in this subpart, these regulations 
do not affect the applicability of other provisions affecting providers 
and suppliers under Medicare FFS, including provisions regarding 
payment, coverage, or program integrity.
0
5. Section 512.110 is amended by--
0
a. Adding the definition of ``Governing documentation'' in alphabetical 
order;
0
b. Revising the definitions of ``Innovation Center model'', 
``Innovation Center model activities'', ``Model beneficiary'', and 
``Model participant''; and
0
c. Adding the definitions of ``Performance period'' and ``Standard 
provisions for Innovation Center models'' in alphabetical order.
    The additions and revisions read as follows:


Sec.  512.110 Definitions.  

* * * * *
    Governing documentation means the applicable Federal regulations, 
and the model-specific participation agreement, cooperative agreement, 
and any addendum to an existing contract with CMS, that collectively 
specify the terms of the Innovation Center model.
* * * * *
    Innovation Center model means an innovative payment and service 
delivery model tested under the authority of section 1115A(b) of the 
Act,

[[Page 43614]]

including a model expansion under section 1115A(c) of the Act.
    Innovation Center model activities means any activities affecting 
the care of model beneficiaries related to the test of the Innovation 
Center model.
* * * * *
    Model beneficiary means a beneficiary attributed to a model 
participant or otherwise included in an Innovation Center model.
    Model participant means an individual or entity that is identified 
as a participant in the Innovation Center model.
* * * * *
    Performance period means the period of time during which an 
Innovation Center model is tested and model participants are held 
accountable for cost and quality of care; the performance period for 
each Innovation Center model is specified in the governing 
documentation.
* * * * *
    Standard provisions for Innovation Center models means the 
provisions codified in subpart A of this part.
* * * * *
0
6. Section 512.190 is added to read as follows:


Sec.  512.190  Reconsideration review process.

    (a) Applicability of this section. This section is only applicable 
to the following:
    (1) Innovation Center models that have waived section 1869 of the 
Act, or where section 1869 of the Act is not applicable for model 
participants.
    (2) Model participants, unless the governing documentation for the 
Innovation Center model States otherwise.
    (b) Right to reconsideration. The model participant may request 
reconsideration of a determination made by CMS in accordance with an 
Innovation Center model's governing documentation only if such 
reconsideration is not precluded by section 1115A(d)(2) of the Act, 
this subpart, or the governing documentation for the Innovation Center 
model for which CMS made the initial determination.
    (1) A request for reconsideration by the model participant must 
satisfy all of the following criteria:
    (i) Must be submitted to a designee of CMS (reconsideration 
official) who--
    (A) Is authorized to receive such requests; and
    (B) Did not participate in the determination that is the subject of 
the reconsideration request, or, if applicable, the timely error notice 
review process.
    (ii)(A) Must include a copy of the initial determination issued by 
CMS; and
    (B) Must contain a detailed, written explanation of the basis for 
the dispute, including supporting documentation.
    (iii) Must be made within 30 days of the date of the initial 
determination for which reconsideration is being requested via email to 
an address as specified by CMS in the governing documentation for the 
Innovation Center model for which CMS made the initial determination.
    (2) Requests that do not meet the requirements of paragraph (b)(1) 
of this section are denied.
    (3) Within 10 business days of receiving a request for 
reconsideration, the reconsideration official sends CMS and the model 
participant a written acknowledgement of receipt of the reconsideration 
request. This acknowledgement sets forth all of the following:
    (i) The review procedures.
    (ii) A schedule that permits each party to submit position papers 
and documentation in support of the party's position for consideration 
by the reconsideration official.
    (4) If the request is regarding a model-specific payment and the 
governing documentation specifies an initial timely error notice 
process, the model participant must satisfy the timely error notice 
requirements specified in the governing documentation before submitting 
a reconsideration request under paragraph (b) of this section. In the 
event that the model participant fails to timely submit an error notice 
with respect to a particular model-specific payment, the 
reconsideration review process would not be available to the model 
participant with regard to that model-specific payment.
    (c) Standards for reconsideration. (1) The parties must continue to 
fulfill all responsibilities and obligations under the governing 
documentation during the course of any dispute arising under the 
governing documentation.
    (2) The reconsideration consists of a review of documentation that 
is submitted timely and in accordance with the standards specified by 
the reconsideration official and are enumerated in paragraph (b)(3) of 
this section.
    (3) The burden of proof is on the model participant to demonstrate 
to the reconsideration official with clear and convincing evidence that 
the determination is inconsistent with the terms of the governing 
documentation.
    (d) Reconsideration determination. (1) The reconsideration 
determination is based solely upon both of the following:
    (i) Position papers and supporting documentation that meet both of 
the following:
    (A) Submitted timely to the reconsideration official in accordance 
with the schedule specified in paragraph (b)(3)(ii) of this section.
    (B) The standards for submission under paragraph (b)(1) of this 
section.
    (ii) Documents and data that were timely submitted to CMS in the 
required format before CMS made the determination that is the subject 
of the reconsideration request.
    (2)(i) The reconsideration official issues the reconsideration 
determination to CMS and to the model participant in writing.
    (ii) Absent unusual circumstances, in which case the 
reconsideration official reserves the right to an extension upon 
written notice to the model participant, the reconsideration 
determination is issued within 60 days of receipt of timely filed 
position papers and supporting documentation in accordance with the 
schedule specified in paragraph (b)(3)(ii) of this section.
    (3) The reconsideration determination is final and binding 30 days 
after its issuance, unless the model participant or CMS timely requests 
review of the reconsideration determination in accordance with 
paragraphs (e)(1) and (2) of this section.
    (e) CMS Administrator review. The model participant or CMS may 
request that the CMS Administrator review the reconsideration 
determination. The request must meet both of the following:
    (1) Be made via email within 30 days of the date of the 
reconsideration determination to the address specified by CMS.
    (2) Include a copy of the reconsideration determination and a 
detailed written explanation of why the model participant or CMS 
disagrees with the reconsideration determination.
    (3) The CMS Administrator promptly sends the parties a written 
acknowledgement of receipt of the request for review.
    (4) The CMS Administrator sends the parties notice of the 
following:
    (i) Whether the request for review is granted or denied.
    (ii) If the request for review is granted, the review procedures 
and a schedule that permits each party to submit a brief in support of 
the party's position for consideration by the CMS Administrator.
    (4) If the request for review is denied, the reconsideration 
determination is final and binding as of the date the request for 
review is denied.
    (5) If the request for review is granted all of the following 
occur:

[[Page 43615]]

    (i) The record for review consists solely of--
    (A) Timely submitted briefs and the evidence contained in the 
record of the proceedings before the reconsideration official; and
    (B) Evidence as set forth in the documents and data described in 
paragraph (d)(1)(ii) of this section.
    (ii) The CMS Administrator reviews the record and issues to CMS and 
to the model participant a written determination.
    (iii) The written determination of the CMS Administrator is final 
and binding as of the date the written determination is sent.
0
7. Add subpart D to read as follows:
Subpart D--Increasing Organ Transplant Access (IOTA) Model
Sec.
512.400 Basis and scope.
512.402 Definitions.

Increasing Organ Transplant Access Model Scope and Participation

512.412 Participant eligibility and selection.
512.414 Patient population.

Performance Assessment and Scoring

512.422 Overview of performance assessment and scoring.
512.424 Achievement domain.
512.426 Efficiency domain.
512.428 Quality domain.

Payment

512.430 Upside risk payment, downside risk payment, and neutral 
zone.
512.434 Targeted review.
512.436 Extreme and uncontrollable circumstances.

Data Sharing

512.440 Data sharing.
512.442 Transparency requirements.
512.444 Health equity plans.

Beneficiary Protections, Financial Arrangements, Beneficiary 
Incentives, and Compliance

512.450 Required beneficiary notifications.
512.452 Financial sharing arrangements and attributed patient 
engagement incentives.
512.454 Distribution arrangements.
512.455 Enforcement authority.
512.456 Beneficiary incentive: Part B and Part D immunosuppressive 
drug cost sharing support.
512.458 Attributed patient engagement incentives.
512.459 Application of the CMS-sponsored model arrangements and 
patient incentives safe harbor.
512.460 Audit rights and records retention.
512.462 Compliance and monitoring
512.464 Remedial action.
512.466 Termination.
512.468 Bankruptcy and other notifications.

Waivers

512.470 Waivers.

Subpart D--Increasing Organ Transplant Access (IOTA) Model


Sec.  512.400  Basis and scope.

    (a) Basis. This subpart implements the test of the Increasing Organ 
Transplant Access (IOTA) Model under section 1115A(b) of the Act.
    (b) Scope. This subpart sets forth the following:
    (1) The method for selecting IOTA participants.
    (2) The patient population.
    (3) The methodology for IOTA participant performance assessment and 
scoring for purposes of the achievement domain, efficiency domain, and 
quality domain, including beneficiary attribution and transplant target 
calculation.
    (4) The schedule and methodologies for the upside risk payment and 
downside risk payment.
    (5) Data sharing.
    (6) Other IOTA Model requirements.
    (7) Beneficiary protections.
    (8) Financial arrangements.
    (9) Monitoring.
    (10) Evaluation.
    (11) Termination.
    (12) Except as specifically noted in this subpart, the regulations 
under this subpart do not affect the applicability of other provisions 
affecting providers and suppliers under Medicare fee for service, 
including the applicability of provisions regarding payment, coverage, 
or program integrity.
    (c) Applicability. IOTA participants are subject to the standard 
provisions for Innovation Center models specified in subpart A of this 
part and in subpart K of part 403 of this chapter.


Sec.  512.402  Definitions.

    For purposes of this subpart, the following definitions apply.
    Achievement domain means the performance assessment category in 
which CMS assesses the IOTA participant's performance based on the 
number of transplants performed relative to the transplant target, 
subject to the health equity performance adjustment, as described in 
Sec.  512.424.
    Alignment payment means a payment from an IOTA collaborator to an 
IOTA participant that is made in accordance with a sharing arrangement.
    Annual attribution reconciliation means the yearly process in which 
CMS--
    (1) Creates the final list of each IOTA participant's attributed 
patients for the prior performance year by retrospectively de-
attributing from each IOTA participant any attributed patients that 
satisfy a criterion for de-attribution under Sec.  512.414(c).
    (2) Creates a final list of each IOTA participant's attributed 
patients who remain attributed for the performance year being 
reconciled, subject to the attribution criteria under Sec. Sec.  
512.414(b)(1) and (2).
    Annual attribution reconciliation list means the final cumulative 
record of attributed patients that CMS generates annually for whom each 
IOTA participant is accountable for during the applicable PY as 
described at Sec.  512.414(c)(2).
    Attributed patient means an IOTA waitlist patient or an IOTA 
transplant patient.
    Attribution means the process by which CMS identifies the patients 
for whom each IOTA participant is accountable during the model 
performance period, as described in Sec.  512.414.
    Baseline year means a 12-month period within a 3-year historical 
baseline period, that begins 48 months (or 4 years) before the start of 
each model PY and ends 12 months (or 1 year) before the start of each 
model PY, as described in Sec.  512.424.
    Bypassed response means an organ offer not received due to 
expedited placement or a decision by a kidney transplant hospital to 
have all of its kidney transplant waitlist patients skipped during the 
organ allocation process based on a set of pre-defined filters selected 
by the kidney transplant hospital matching the characteristics of the 
potential organ to be transplanted.
    Critical access hospital (CAH) means a hospital as defined in 
section 1861(mm)(1) of the Act.
    Change in Control means at least one of the following:
    (1) The acquisition by any ``person'' (as this term is used in 
sections 13(d) and 14(d) of the Securities Exchange Act of 1934) of 
beneficial ownership (within the meaning of Rule 13d-3 promulgated 
under the Securities Exchange Act of 1934), directly or indirectly, of 
voting securities of the IOTA participant representing more than 50 
percent of the IOTA participant's outstanding voting securities or 
rights to acquire such securities.
    (2) The acquisition of the IOTA participant by any other individual 
or entity.
    (3) Any merger, division, dissolution, or expansion of the IOTA 
participant.
    (4) The sale, lease, exchange, or other transfer (in one 
transaction or a series of transactions) of all or substantially all 
the assets of the IOTA participant.
    (5)(i) The approval and completion of a plan of liquidation of the 
IOTA participant; or

[[Page 43616]]

    (ii) An agreement for the sale or liquidation of the IOTA 
participant.
    Collaboration agent means an individual or entity that is not an 
IOTA collaborator and that is a member of a PGP, NPPGP, or TGP that has 
entered into a distribution arrangement with the same PGP, NPPGP, or 
TGP in which he or she is an owner or employee, and where the PGP, 
NPPGP, or TGP is an IOTA collaborator.
    Composite graft survival rate means the rolling unadjusted total 
number of functioning grafts relative to the total number of adult 
kidney transplants performed, as described in Sec.  512.428.
    CORF stands for comprehensive outpatient rehabilitation facility.
    Days means calendar days unless otherwise specified by CMS.
    Distribution arrangement means a financial arrangement between an 
IOTA collaborator that is an PGP, NPPGP, or TGP and a collaboration 
agent for the sole purpose of distributing some or all of a gainsharing 
payment received by the PGP, NPPGP, or TGP.
    Distribution payment means a payment from an IOTA collaborator that 
is ana PGP, NPPGP, or TGP to a collaboration agent, under a 
distribution arrangement, composed only of gainsharing payments.
    Donation service area (DSA) means a geographical area of sufficient 
size to ensure maximum effectiveness in the procurement and equitable 
distribution of organs and that either includes an entire metropolitan 
statistical area (MSA) or does not include any part of such an area and 
that meets the standards of subpart G as defined in Sec.  486.302 of 
this chapter.
    Downside risk payment means the lump sum payment the IOTA 
participant must pay to CMS after the close of a performance year if 
the IOTA participant's final performance score falls within the ranges 
specified in Sec.  512.43.
    Efficiency domain means the performance assessment category in 
which CMS assesses the IOTA participant's performance using the organ 
offer acceptance rate ratio as described in Sec.  512.426.
    EFT stands for electronic funds transfer.
    Eligible attributed patient means an attributed patient that 
receives immunosuppressive coverage through Part B or Part D but that 
does not have secondary insurance that could provide cost sharing 
support.
    Final performance score means the sum total of the scores earned by 
the IOTA participant across the achievement domain, efficiency domain, 
and quality domain for a given PY.
    Gainsharing payment means a payment that is made from an IOTA 
participant to an IOTA collaborator, under a sharing arrangement as set 
forth in Sec.  512.452 and in accordance with Sec.  512.452(c).
    Health equity goals means the targeted outcomes relative to the 
health equity plan performance measures for the first PY and all 
subsequent PYs.
    Health equity performance adjustment means the multiplier applied 
to each kidney transplant performed for a patient from a low-income 
population when calculating the transplant target as described under 
Sec.  512.424(e).
    Health equity performance plan measure(s) means one or more 
quantitative metrics that the IOTA participant uses to measure the 
reductions in target health disparities arising from the health equity 
plan interventions.
    Health equity plan intervention means the initiative(s) the IOTA 
participant creates and implements to reduce target health disparities.
    Health equity project plan means the timeline for the IOTA 
participant to implement the IOTA participant's the health equity plan.
    HHA means a Medicare-enrolled home health agency.
    Hospital means a provider as defined by 1861(u) of the Act.
    Improvement benchmark rate means 120 percent of the IOTA 
participants' performance on organ offer acceptance rate ratio as 
specified under Sec.  512.426(c)(1)(ii)(A).
    Initial attribution means the process by which CMS identifies and 
prospectively attributes patients who meet the criteria specified under 
Sec.  512.414(a)(2)(b) to an IOTA participant prior to the model start 
date.
    IOTA activities mean the activities related to promoting 
accountability for the quality, cost, and overall care for attributed 
patients and performances across the achievement domain, efficiency 
domain and quality domain, including any of the following:
    (1) Managing and coordinating care.
    (2) Encouraging investment in infrastructure and redesigned care 
processes for high quality and efficient service delivery.
    (3) The provision of items and services pre- or post-transplant in 
a manner that reduces costs and improves quality.
    (4) Carrying out any other obligation or duty under the IOTA Model.
    IOTA collaborator means the following Medicare-enrolled providers 
and suppliers that enter into a sharing arrangement with an IOTA 
participant:
    (1) Nephrologist.
    (2) ESRD facility.
    (3) Skilled nursing facility (SNF).
    (4) Home health agency (HHA).
    (5) Long-term care hospital (LTCH).
    (6) Inpatient rehabilitation facility (IRF).
    (7) Physician.
    (8) Nonphysician practitioner.
    (9) Therapist in a private practice.
    (10) CORF.
    (11) Provider or supplier of outpatient therapy services.
    (12) Physician group practice (PGP).
    (13) Hospital.
    (14) CAH.
    (15) Non-physician provider group practice (NPPGP).
    (16) Therapy group practice (TGP).
    IOTA participant means a kidney transplant hospital, as defined at 
Sec.  512.402, that is required to participate in the IOTA Model under 
Sec.  512.412.
    IOTA transplant patient means a kidney transplant patient who 
receives a kidney transplant at the age of 18 years of age or older 
from an IOTA participant at any time during the model performance 
period and meets the criteria set forth in Sec.  512.412(b)(2).
    IOTA waitlist patient means a kidney transplant waitlist ESRD 
patient, regardless of payer type and waitlist status, who meets all of 
the following:
    (1) Is alive.
    (2) 18 years of age or older.
    (3) Registered on a waitlist (as defined in Sec.  512.402) to one 
or more IOTA participants, as identified by the OPTN computer match 
program.
    IRF stands for inpatient rehabilitation facility which must meet 
all of the following:
    (1) The general criteria set forth in Sec.  412.22 0f this chpater.
    (2) The criteria to be classified as a rehabilitation hospital or 
rehabilitation unit set forth in Sec. Sec.  412.23(b), 412.25, and 
412.29 of this chapter for exclusion from the inpatient hospital 
prospective payment systems specified in Sec.  412.1(a)(1) of this 
chapter.
    Kidney transplant means the procedure in which a kidney is 
surgically transplanted from a living or deceased donor to a transplant 
recipient, either alone or in conjunction with any other organ(s).
    Kidney transplant hospital means a transplant hospital with a 
Medicare approved kidney transplant program.
    Kidney transplant patient means a patient who is a transplant 
candidate, as defined in Sec.  121.2, and received a kidney transplant 
furnished by a kidney transplant hospital, regardless of payer type.

[[Page 43617]]

    Kidney transplant waitlist patient means a patient who is a 
transplant candidate, as defined in Sec.  121.2 of this chapter, and 
who is registered to a waitlist for a kidney at one or more kidney 
transplant hospitals.
    Low-income population means an IOTA transplant patient in one or 
more of the following groups:
    (1) Medicaid beneficiaries.
    (2) Medicare-Medicaid dually eligible beneficiaries.
    (3) Recipients of the Medicare low-income subsidy.
    (4) Recipients of reimbursements from the Living Organ Donation 
Reimbursement Program administered by the National Living Donor 
Assistance Center (NLDAC).
    (5) The uninsured.
    LTCH stands for long-term care hospital that meets the requirements 
as stated in 42 CFR part 483 subpart B.
    Match run means a computerized ranking of transplant candidates 
based upon donor and candidate medical compatibility and criteria 
defined in OPTN policies.
    Medicare kidney transplant means a kidney transplant furnished to a 
attributed patient in the IOTA Model whose primary or secondary 
insurance is Medicare fee for service (FFS), as identified in Medicare 
FFS claims with MS-DRGs 008, 019, 650, 651, and 652.
    Member of the NPPGP or NPPGP member means a nonphysician 
practitioner or therapist who is an owner or employee of an NPPGP and 
who has reassigned to the NPPGP their right to receive Medicare 
payment.
    Member of the PGP or PGP member means a physician, nonphysician 
practitioner, or therapist who is an owner or employee of the PGP and 
who has reassigned to the PGP their right to receive Medicare payment.
    Member of the TGP or TGP member means a therapist who is an owner 
or employee of a TGP and who has reassigned to the TGP their right to 
receive Medicare payment.
    Missing responses means organ offers that a kidney transplant 
hospital received from the OPO but did not submit a response (accepting 
or rejecting) in the allotted 1-hour timeframe from the time the offer 
was made per OPTN policy 5.6.B.
    Model performance period means the 72-month period from the model 
start date and is comprised of 6 individual performance years.
    Model-specific payment means a payment made by CMS only to IOTA 
participants, or a payment adjustment made only to payments made to 
IOTA participants, under the terms of the IOTA Model that is not 
applicable to any other providers or suppliers and includes, unless 
otherwise specified, both of the following:
    (1) The IOTA Model upside risk payment.
    (2) The IOTA Model downside risk payment.
    Model start date means the date on which the model performance 
period begins.
    National growth rate means the percentage increase or decrease in 
the number of kidney transplants performed over a 12-month period by 
all kidney transplant hospitals except for pediatric kidney transplant 
hospitals, as defined at Sec.  512.402, and kidney transplant hospitals 
that fall below a low-volume threshold of 11.
    National Provider Identifier (NPI) means the standard unique health 
identifier used by health care providers for billing payors, assigned 
by the National Plan and Provider Enumeration System (NPPES) in 
accordance with 45 CFR part 162.
    Neutral Zone means the final performance score range in which the 
IOTA participant neither owes a downside risk payment to CMS or 
receives an upside-risk payment from CMS, in accordance with Sec.  
512.430(b)(2).
    Non-pediatric facility means a kidney transplant hospital that 
furnishes more than 50 percent of their kidney transplants annually to 
patients 18 years of age or older.
    Nonphysician practitioner means (except for purposes of subpart G 
of this part) one of the following:
    (1) A physician assistant who satisfies the qualifications set 
forth at Sec.  410.74(a)(2)(i) and (ii) of this chapter.
    (2) A nurse practitioner who satisfies the qualifications set forth 
at Sec.  410.75(b) of this chapter.
    (3) A clinical nurse specialist who satisfies the qualifications 
set forth at Sec.  410.76(b) of this chapter.
    (4) A certified registered nurse anesthetist (as defined at Sec.  
410.69(b) of this chapter).
    (5) A clinical social worker (as defined at Sec.  410.73(a) of this 
chapter).
    (6) A registered dietician or nutrition professional (as defined at 
Sec.  410.134 of this chapter).
    NPPGP means an entity that is enrolled in Medicare as a group 
practice, includes at least one owner or employee who is a nonphysician 
practitioner, does not include a physician owner or employee, and has a 
valid and active TIN.
    OPTN computer match program means a set of computer-based 
instructions which compares data on a cadaveric organ donor with data 
on transplant candidates on the waiting list and ranks the candidates 
according to OPTN policies to determine the priority for allocating the 
donor organ(s).
    Organ procurement and transplantation network or OPTN means the 
network established under section 372 of the Public Health Service Act.
    Organ procurement organization or OPO means an entity designated by 
the Secretary under section 1138(b) of the Act and under 42 CFR 
486.304.
    Part B and Part D immunosuppressive drug cost sharing support means 
cost sharing support related to immunosuppressive drugs covered by 
Medicare Part B, the Medicare Part B Immunosuppressive Drug Benefit 
(Part B-ID), or Medicare Part D that is provided by an IOTA participant 
to an eligible attributed patient as codified at Sec.  512.458.
    Pediatric kidney transplant hospital means a kidney transplant 
hospital that performs 50 percent or more of its transplants in a 12-
month period on patients under the age of 18.
    Performance year (PY) means a 12-month calendar year during the 
model performance period.
    PGP stands for physician group practice.
    Physician has the meaning set forth in section 1861(r) of the Act.
    Post-transplant period means the 90-day period following an 
attributed patient's receipt of a kidney transplant.
    Preliminary performance assessment and payment calculations means 
the process by which CMS--
    (1) Assesses each IOTA participant's performance in accordance with 
Sec. Sec.  512.424, 512.426, 512.428; and
    (2) Calculates performance-based payments in accordance with Sec.  
512.430.
    Provider of outpatient therapy services means an entity that is 
enrolled in Medicare as a provider of therapy services and furnishes 
one or more of the following:
    (1) Outpatient physical therapy services as defined in Sec.  410.60 
of this chapter.
    (2) Outpatient occupational therapy services as defined in Sec.  
410.59 of this chapter.
    (3) Outpatient speech-language pathology services as defined in 
Sec.  410.62 of this chapter.
    Quality domain means the performance assessment category in which 
CMS assesses the IOTA participant's performance using a performance 
measure and quality measure set focused on improving the quality of 
transplant care as described in Sec.  512.428.
    Quality Health Information Network (QHIN) means a network of

[[Page 43618]]

organizations that agrees to common terms and conditions regarding data 
exchange with each other (a ``Common Agreement'') and to the functional 
and technical requirements for such data exchange (as specified in the 
QHIN Technical Framework or ``QTF'') under section 4003(b) of the 21st 
Century Cures Act (Pub. L. 114-255).
    Quarterly attribution list means the quarterly CMS-generated 
attributed patient list that CMS provides to the IOTA participant in 
advance of each quarter during the model performance period in 
accordance with Sec.  512.414(c)(ii)(2).
    Resource gap analysis means the resources needed to implement the 
health equity plan interventions and identifies any gaps in the IOTA 
participant's current resources and the additional resources needed.
    Response rate threshold means the level of complete and accurate 
reporting for each quality measure, within the quality measure set of 
the quality domain, that the IOTA participant must meet to earn points 
on the quality domain during a performance year as described in Sec.  
512.428(c) and (e).
    Scientific Registry of Transplant Recipients or SRTR means the 
registry of information on transplant recipients established under 
section 373 of the Public Health Service Act.
    Selected DSAs means those DSAs selected by CMS for purposes of 
selecting kidney transplant hospitals for participation in the IOTA 
Model.
    Sharing arrangement means a financial arrangement to only share the 
upside risk payment and the downside risk payment lump-sum amount as 
set forth in Sec.  512.452.
    SNF stands for skilled nursing facility that meets sections all 
applicable sections of 1819 of the Act.
    Survey and Reporting windows means the two distinct periods where 
IOTA participants are required to administer a quality measure-related 
survey or screening to attributed patients or submit patient responses 
on a quality measure to CMS as set forth in Sec.  512.428(b)(2)(ii).
    Target health disparities means health disparities experienced by 
one or more communities within the IOTA participant's population of 
attributed patients that the IOTA participant aims to reduce.
    Targeted review process means the process in which an IOTA 
participant may dispute performance and payment calculations made, and 
issued, by CMS as set forth in Sec.  512.34.
    TGP means an entity that is enrolled in Medicare as a therapy group 
in private practice, includes at least one owner or employee who is a 
therapist in private practice, does not include an owner or employee 
who is a physician or nonphysician practitioner, and has a valid and 
active TIN.
    Therapist means one of the following individuals as defined at 
Sec.  484.4 of this chapter:
    (1) Physical therapist.
    (2) Occupational therapist.
    (3) Speech-language pathologist.
    Therapist in private practice means a therapist that complies with 
one of the following special provisions:
    (1) For physical therapists in private practice in Sec.  410.60(c) 
of this chapter.
    (2) For occupational therapists in private practice in Sec.  
410.59(c) of this chapter.
    (3) For speech-language pathologists in private practice in Sec.  
410.62(c) of this chapter.
    Taxpayer identification number (TIN) means a Federal taxpayer 
identification number or employer identification number as defined by 
the Internal Revenue Service in 26 CFR 301.6109-1.
    Transplant hospital means a hospital that furnishes organ 
transplants as defined in Sec.  121.2 of this chapter.
    Transplant physician means a physician who provides non-surgical 
care and treatment to transplant patients before and after transplant 
as defined in Sec.  121.2 of this chapter.
    Transplant program means a component within a transplant hospital 
which provides transplantation of a particular type of organ as defined 
in Sec.  121.2 of this chapter.
    Transplant recipient means a person who has received an organ 
transplant as defined in Sec.  121.2 of this chapter.
    Transplant target means the target number of kidney transplants 
calculated by CMS for the IOTA participant to measure the IOTA 
participant's performance in the achievement domain, as described in 
Sec.  512.424.
    Underserved communities mean populations sharing a particular 
characteristic, as well as geographic communities, that have been 
systematically denied a full opportunity to participate in aspects of 
economic, social, and civic life as defined by Executive Order 13985 of 
January 20, 2021.
    Upside risk payment means the lump sum payment CMS makes to an IOTA 
participant if the IOTA participant's final performance score for a 
performance year falls within the payment range specified in Sec.  
512.430.
    Waitlist means a list of transplant candidates, as defined in Sec.  
121.2 of this chapter, registered to the waiting list, as defined in 
Sec.  121.2 of this chapter, maintained by a transplant hospital in 
accordance with Sec.  482.94(b) of this chapter.

Increasing Organ Transplant Access Model Scope and Participation


Sec.  512.412  Participant eligibility and selection.

    (a) Participant eligibility. A kidney transplant hospital is 
eligible to be selected as an IOTA participant, in accordance with the 
methodology described in paragraph (c) of this section, if the kidney 
transplant hospital meets both of the following criteria:
    (1) The kidney transplant hospital annually performed 11 or more 
kidney transplants for patients aged 18 years or older, regardless of 
payer, each of the baseline years.
    (2) The kidney transplant hospital annually performed more than 50 
percent of its kidney transplants on patients 18 years of age or older 
each of the baseline years.
    (b) IOTA participant selection. CMS uses the following process to 
select IOTA participants for inclusion in the model.
    (1) DSA stratification criteria. CMS uses the following approach to 
stratify DSAs using the list of DSAs as of January 1, 2024:
    (i) Census division of the DSA.
    (ii) Total number of adult kidney transplants performed per year 
across eligible kidney transplant hospitals in the DSA during PY 1's 
baseline years.
    (2) DSA stratification process. Prior to sampling DSAs, CMS uses 
the following steps to group DSAs into mutually exclusive groups.
    (i) CMS assigns each DSA to one of the nine Census Divisions. CMS 
assigns each DSA to the Census Division where the majority of the DSA's 
population resides. CMS determines each DSA's population, and the share 
of a DSA's population in the applicable Census Division(s) using data 
from the 2020 Census.
    (A) CMS assigns the Puerto Rico DSA to the South Atlantic Census 
Divisions.
    (B) CMS combines the Middle Atlantic and New England Census 
Divisions and all DSAs therewithin creating eight groups of Census 
Divisions.
    (ii) CMS identifies all kidney transplant hospitals located in each 
DSA within each Census Division group.
    (iii) For each DSA within its assigned Census Division group, CMS 
identifies the eligible kidney transplant hospitals using the criteria 
specified in paragraph (a) of this section.
    (iv) Using data from each of the baseline years for PY 1, CMS 
determines the average number of adult kidney

[[Page 43619]]

transplants performed annually by eligible transplant hospitals located 
in each DSA as follows:
    (A) Sums the number of adult kidney transplants performed across 
eligible kidney transplant hospitals in a DSA during each of the 
baseline years for PY 1; and
    (B) Divides each DSA's sum resulting from the calculation in 
paragraph (b)(2)(iv)(A) of this section by three to determine the 
amount the average number of adult kidney transplants furnished during 
the baseline years for PY 1.
    (v) CMS separates DSAs in each Census Division group into two 
mutually exclusive groups of the same size, based on the average number 
of adult kidney transplants performed annually across the baseline 
years for PY 1, except where there are an odd number of DSAs within a 
Census Division group:
    (A) DSAs with a higher number of adult kidney transplants per year 
across the baseline years for PY 1.
    (B) DSAs with a lower number of adult kidney transplants per year 
across the baseline years for PY 1.
    (vi) Where there are an odd number of DSAs within a Census Division 
group CMS uses the methodology set forth in paragraph (b)(3) of this 
section.
    (3) Random sampling of DSAs. (i) For each DSA group within a Census 
Division group containing an odd number of DSAs, CMS randomly selects 
one DSA and determines its participation in the IOTA Model with a 50 
percent probability.
    (ii) CMS randomly samples, without replacement, 50 percent of the 
remaining DSAs in each group within each Census Division group created 
in paragraph (b)(2)(v) of this section.
    (c) Selection of IOTA participants in selected DSAs. All eligible 
kidney transplant hospitals in the selected DSAs would be required to 
participate in the IOTA Model.
    (d) CMS notifies IOTA participants of their selection to 
participate in the IOTA Model in a form and manner chosen by CMS at 
least 3 months prior to the start of the model performance period.


Sec.  512.414  Patient population.

    (a) General. (1) CMS attributes kidney transplant waitlist patients 
and kidney transplant patients to IOTA participants based on the 
attribution criteria as described in paragraphs (b)(1) and (b)(2) of 
this section, for all of the following purposes:
    (i) Sharing Medicare claims data for attributed beneficiaries with 
IOTA participants.
    (ii) Assessing each IOTA participant's performance across the 
achievement domain, efficiency domain, and quality domain.
    (iii) Determining performance-based payments to IOTA participants.
    (2) Once a kidney transplant waitlist patient or kidney transplant 
patient is attributed to an IOTA participant, that respective patient 
may not opt out of attribution to an IOTA participant and remains 
attributed to the IOTA participant for the duration of the model 
performance period, unless the attributed patient meets the de-
attribution criteria under paragraph (b)(3) of this section during 
annual attribution reconciliation as described in paragraph (b)(3) of 
this section.
    (b) Patient attribution and de-attribution criteria--(1) IOTA 
waitlist patient attribution. (i) At the time CMS conducts attribution, 
as described in paragraph (c) of this section, if a kidney transplant 
waitlist patient meets the definition of an IOTA waitlist patient, as 
defined at Sec.  512.402, CMS attributes the kidney transplant waitlist 
patient as an IOTA waitlist patient to an IOTA participant.
    (2) IOTA transplant patient attribution. (i) At the time CMS 
conducts attribution, as described in paragraph (c) of this section, 
CMS attributes a kidney transplant patient as an IOTA transplant 
patient if the kidney transplant patient meets all of the following:
    (A) The definition of an IOTA transplant patient, as defined at 
Sec.  512.402.
    (B) Is 18 years of age or older at the time of the patient's kidney 
transplant.
    (C) Is alive.
    (3) De-attribution from an IOTA participant. During annual 
attribution reconciliation, CMS uses the fourth quarter attribution 
list for each IOTA participant and de-attributes any attributed 
patients who, as of the last day of the PY being reconciled, meet any 
of the following de-attribution criteria:
    (A) An IOTA waitlist patient was removed from and remains 
unregistered on an IOTA participant's kidney transplant waitlist.
    (B) An IOTA waitlist patient that has died at any point during the 
PY.
    (C) An IOTA transplant patient that has died at any point during 
the PY.
    (D) An IOTA transplant patient who experiences transplant failure 
at any point during the model performance period and has not rejoined 
an IOTA participant's kidney transplant waitlist or received another 
transplant from an IOTA participant before the last day of the 
respective PY.
    (c) Attribution methodology. CMS employs the following methodology 
to attribute kidney waitlist patients and kidney transplant patients to 
an IOTA participant after identifying all kidney waitlist patients and 
kidney transplant patients that meet the attribution criteria as 
specified in paragraphs (b)(1) and (b)(2) of this section:
    (1) Initial attribution. (i) Prior to the model start date, CMS 
conducts initial attribution, as defined at Sec.  512.402.
    (ii) Initial attribution list. (A) CMS provides the initial 
attribution list to the IOTA participant no later than 15 days prior to 
the start of PY 1 and in a form and manner as determined by CMS.
    (B) The initial attribution list includes a list of IOTA waitlist 
patients identified through initial attribution, effective-on the model 
start date.
    (2) Quarterly attribution. (i) CMS conducts attribution, as defined 
at Sec.  512.402, on a quarterly basis after the model start date, and 
updates the quarterly attribution list, as defined at Sec.  512.402, 
for each IOTA participant, except in the event of termination in 
accordance with Sec.  512.466.
    (ii) Quarterly attribution list. CMS provides the quarterly 
attribution list, as defined at Sec.  512.402, to the IOTA participant 
no later than 15 days prior to the start of each quarter and in a form 
and manner as determined by CMS. The quarterly attribution list 
includes, at minimum, all of the following:
    (A) A list of all newly attributed patients, whose attribution to 
the IOTA participant becomes effective on the first day of the relevant 
upcoming quarter.
    (B) A list of all attributed patients who continue to be attributed 
to the IOTA participant from the previous quarter.
    (C) The dates in which attribution began, changed, or ended, where 
applicable for attributed patients.
    (D) The attributed patient's data sharing preferences under Sec.  
512.440(b).
    (3) Annual attribution reconciliation. (i) After the fourth quarter 
of each PY, CMS conducts annual attribution reconciliation as defined 
at Sec.  512.402.
    (ii) Annual attribution reconciliation list. CMS provides the 
annual reconciliation list to the IOTA participant before the second 
quarter of the following PY. Using the fourth quarter quarterly 
attribution list for each IOTA participant, the annual attribution 
reconciliation list identifies, at a minimum, all of the following, 
where applicable:
    (A) A list of all attributed patients who remain attributed to the 
IOTA participant because they satisfied the

[[Page 43620]]

attribution criteria under Sec. Sec.  512.414(1) and 512.414(2) for the 
respective PY.
    (B) The dates in which attribution began, changed, or ended, where 
applicable.
    (C) A list of all attributed patients who are de-attributed because 
they failed to satisfy the attribution criteria under Sec.  
512.414(x)(1) and (2).
    (D) A list of all attributed patients who are de-attributed because 
they satisfy a de-attribution criterion under Sec.  512.414(e)(4)(i).
    (E) The dates on which each attributed patient satisfied a de-
attribution criterion as specified under Sec.  512.414(e)(4)(i).
    (F) A list of the de-attribution criterion each attributed patient 
satisfied under Sec.  512.414(e)(4)(i).

Performance Assessment and Scoring


Sec.  512.422  Overview of performance assessment and scoring.

    (a) General. (1) CMS establishes the performances measures 
described in Sec. Sec.  512.424, 512.426, and 512.428 to assess IOTA 
participants in the achievement domain, efficiency domain and quality 
domain.
    (2) CMS assigns each set of metrics within a domain a point value 
with the total possible points awarded to an IOTA participant across 
the three domains equaling 100, as described in Sec. Sec.  512.424, 
512.426, and 512.428.
    (b) Data sources. (1) CMS uses Medicare claims data and Medicare 
administrative data about beneficiaries, providers, suppliers, and data 
from the OPTN, to calculate performance for the IOTA participant based 
on the methodologies under Sec. Sec.  512.424, 512.426, and 512.428.
    (2) CMS may also use model-specific data reported by an IOTA 
participant to CMS under the IOTA Model to calculate IOTA participant 
performance in the domains.


Sec.  512.424  Achievement domain.

    (a) General. (1) After each PY, CMS calculates the number of kidney 
transplants that each IOTA participant performed for the respective PY, 
in accordance with the provisions in paragraph (d) of this section.
    (2) CMS compares the number of kidney transplants that an IOTA 
participant performed during the PY to the IOTA participant's 
transplant target, subject to a health equity performance adjustment as 
described in paragraph (e) of this section, for that PY, to determine 
the IOTA participant's score for the achievement domain.
    (b) Transplant target methodology. CMS determines the IOTA 
participant's transplant target for each PY as follows:
    (1) CMS analyzes the baseline years for the relevant PY and 
identifies:
    (i) The highest annual number of deceased donor kidney transplants 
furnished by the IOTA participant to patients 18 years of age or older 
during a baseline year; and
    (ii) The highest annual number of living donor kidney transplants 
furnished by the IOTA participant to patients 18 years of age or older 
during a baseline year.
    (2) CMS sums the numbers in paragraphs (b)(1)(i) and (ii) of this 
section.
    (3) National growth rate calculation. CMS calculates the national 
growth rate, as defined at Sec.  512.402, using the baseline years for 
the relevant PY as follows:
    (i) Subtracts the total number of kidney transplants furnished to 
patients 18 years of age or older during the second baseline from the 
total number of kidney transplants furnished to patients 18 years of 
age or older during the third baseline year.
    (ii) Divides the amount resulting from the calculation in paragraph 
(b)(3)(i) of this section by the total number of kidney transplants 
furnished to patients 18 years of age or older during the third 
baseline year. The resulting amount is the national growth rate for the 
relevant PY.
    (4) Calculation of transplant target. If the national growth rate 
calculated in paragraph (b)(3) of this section is--
    (i) Positive, CMS multiples that national growth rate by the sum 
calculated in paragraph (b)(2) of this section. The resulting amount is 
an IOTA participants transplant target for the relevant PY; or
    (ii) Negative, CMS does not multiply the national growth rate by 
the sum calculated in paragraph (b)(2) of this section. The IOTA 
participant's transplant target for the relevant PY is the sum 
calculated in paragraph (b)(2) of this section.
    (c) Notification of transplant target. CMS notifies the IOTA 
participant of the transplant target by the first day of the start of 
each PY in a form and manner determined by CMS.
    (d) Calculation of kidney transplants performed during the PY. 
(1)(i) After each PY, except as described in paragraph (d)(2) of this 
section, CMS counts the number of kidney transplants performed by the 
IOTA participant on patients who were 18 years of age or older at the 
time of transplant, during the PY.
    (ii) CMS identifies kidney transplants performed by the IOTA 
participant using OPTN data, regardless of payer, and Medicare claims 
data.
    (2) CMS counts each kidney transplant described in paragraph (d)(1) 
of this section as one transplant, except as described in paragraph (e) 
of this section.
    (e) Health equity performance adjustment. (1) If a kidney 
transplant identified under paragraph (d) of this section was performed 
on a low-income population patient, CMS applies the health equity 
performance adjustment to that kidney transplant by multiplying each 
low-income population patient's kidney transplant by 1.2.
    (2) CMS sums the number of kidney transplants identified under 
paragraph (d)(3) of this section and the number of kidney transplants 
adjusted by the health equity performance adjustment described in 
paragraph (e)(1) of this section to determine the total sum of kidney 
transplants performed by the IOTA participant in a PY.
    (3) CMS uses the total sum of kidney transplants identified under 
paragraph (e)(2) of this section and determines the IOTA participant's 
achievement domain score in accordance with paragraph (f) of this 
section.
    (f) Achievement domain scoring. For each PY, CMS awards the IOTA 
participant zero to 60 points for its performance in the achievement 
domain.
    (1) CMS compares the total number of kidney transplants identified 
under paragraph (e)(2) of this section to the IOTA participant's 
transplant target, as described in paragraph (b) of this section.
    (2) CMS uses the following scoring methodology to determine an IOTA 
participant's score on the achievement domain.

                 Table 1 to Paragraph (f)(2)--IOTA Model Achievement Domain Scoring Methodology
----------------------------------------------------------------------------------------------------------------
   Performance relative to transplant
                 target                      Lower bound condition       Upper bound condition     Points earned
----------------------------------------------------------------------------------------------------------------
150% of transplant target...............  Equals 150%...............  Greater than 150%.........              60
125% of transplant target...............  Equals 125%...............  Less than 150%............              45
100% of transplant target...............  Equals 100%...............  Less than 125%............              30

[[Page 43621]]

 
75% of transplant target................  Equals 75%................  Less than 100%............              15
75% of transplant target................  N/A.......................  Less than 75%.............               0
----------------------------------------------------------------------------------------------------------------

Sec.  512.426  Efficiency domain.

    (a) General. For each PY, CMS assesses each IOTA participant on the 
metric described in paragraph (b) of this section to determine the IOTA 
participant's score for the efficiency domain.
    (b) Metric included in the efficiency domain. For each PY, CMS 
assesses the IOTA participant on the following metric:
    (1) Organ-offer acceptance rate ratio. For each PY, CMS calculates 
the organ-offer acceptance rate ratio by dividing the number of kidneys 
the IOTA participant accepted by the risk-adjusted number of expected 
organ-offer acceptances using SRTR's methodology as described in 
equation 1 to paragraph (b)(1).

Equation 1 to Paragraph (b)(1): Organ Offer Acceptance Rate Ratio
[GRAPHIC] [TIFF OMITTED] TP17MY24.017

    (i) CMS uses both of the following:
    (A) SRTR data to calculate the organ-offer acceptance rate ratio.
    (B) SRTR's adult kidney model strata risk-adjustment methodology 
and most available set of coefficients to calculate the number of 
expected organ-offer acceptances.
    (ii) CMS includes all of the following kidney offers when 
calculating the organ-offer acceptance rate ratio for the IOTA 
participant:
    (A) Offers that are ultimately accepted and transplanted.
    (B) Offers to candidates on a single organ waitlist (except for 
Kidney/Pancreas candidates that are also listed for kidney alone).
    (iii) CMS excludes the following kidney offers when calculating the 
organ-offer acceptance rate:
    (A) Offers with multiple match runs from the same donor combined 
and duplicate offers.
    (B) Offers with no match run acceptances.
    (C) Offers that occurred after the last acceptance in a match run.
    (D) Offers with a missing or bypassed response.
    (E) Offers to multi-organ candidates (except for kidney/pancreas 
candidates that are also listed for kidney alone).
    (c) Efficiency domain scoring. For each PY, CMS awards the IOTA 
participant 0 to 20 points for its performance in the efficiency 
domain.
    (1) General. CMS determines the IOTA participant's score for the 
efficiency domain for each PY by taking the IOTA participant's score 
for the organ offer acceptance rate ratio, as described under paragraph 
(c)(2) of this section. This number is the IOTA participant's score for 
the efficiency domain for the PY.
    (2) Scoring for organ offer acceptance rate ratio. CMS calculates 
the IOTA participant's achievement score, as described in paragraph 
(c)(2)(i) of this section, and improvement score, as described under 
paragraph (c)(2)(ii) of this section, for the organ offer acceptance 
rate ratio, compares the IOTA participant's achievement score and 
improvement score and awards to the IOTA participant the points that 
correspond to the higher score.
    (i) Achievement scoring. CMS calculates the IOTA participant's 
achievement score based on the IOTA participant's performance on organ 
offer acceptance rate ratio ranking against a national target, 
including all eligible kidney transplant hospitals, using the scoring 
methodology described in table 1 to paragraph (c)(1)(i) of this 
section.

           Table 1 to Paragraph (c)(1)(i)--IOTA Model Organ Offer Acceptance Rate Achievement Scoring
----------------------------------------------------------------------------------------------------------------
Performance relative to national ranking     Lower bound condition       Upper bound condition     Points earned
----------------------------------------------------------------------------------------------------------------
80th Percentile relative to target OR     Equals 80th percentile....  Greater than 80th                       20
 for comparison.                                                       percentile.
60th Percentile.........................  Equals 60th percentile....  Less than 80th percentile.              15
40th Percentile.........................  Equals 40th percentile....  Less than 60th percentile.              10
20th Percentile.........................  Equals 20th percentile....  Less than 40th percentile.               6
20th Percentile.........................  N/A.......................  Less than 20th percentile.               0
----------------------------------------------------------------------------------------------------------------

    (ii) Improvement scoring. CMS compares the IOTA participant's organ 
offer acceptance rate ratio during the PY, calculated as described 
under paragraph (c)(1)(i) of this section, to the IOTA participant's 
improvement benchmark rate, calculated as described under paragraph 
(c)(1)(ii)(A) of this section.
    (A) Improvement benchmark rate. CMS calculates an improvement 
benchmark rate for the IOTA participant. To determine an IOTA 
participant's improvement benchmark rate for a given PY, CMS multiplies 
an IOTA participant's organ offer acceptance rate ratio during the 
third baseline year by 120 percent.
    (B) Improvement score calculation. For each PY, CMS uses the 
following methodology to determine each IOTA participant's improvement 
score on the organ offer acceptance rate ratio:
    (1) If the IOTA participant's organ-offer acceptance rate ratio is 
greater than or equal to the improvement benchmark rate, CMS awards the 
IOTA participant 12 points in the efficiency domain.

[[Page 43622]]

    (2) If the IOTA participant's organ offer acceptance rate ratio is 
equal to or less than the IOTA participant's organ-offer acceptance 
rate ratio in the third baseline year for that respective PY, CMS 
awards the IOTA participant 0 points in the efficiency domain.
    (3) If the IOTA participant's organ offer acceptance rate ratio is 
greater than the IOTA participant's organ-offer acceptance rate ratio 
in the third baseline year for that respective PY but less than the 
improvement benchmark rate, CMS uses the following equation:

Equation 1 to Paragraph (c)(1)(ii)(B)(1): IOTA Model Organ Offer 
Acceptance Rate Ratio Improvement Scoring Equation
[GRAPHIC] [TIFF OMITTED] TP17MY24.018

Sec.  512.428  Quality domain.

    (a) General. For each PY, CMS assesses each IOTA participant on the 
metrics described under paragraphs (b)(1) and (2) of this section to 
determine the IOTA participant's quality domain score, as described 
under paragraphs (c) through (e) of this section, for the quality 
domain.
    (b) Metrics included in the quality domain. For each PY, CMS 
assesses each IOTA participant using the following quality metrics:
    (1) Post-transplant graft survival. For each PY, CMS calculates an 
IOTA participant's composite graft survival rate by dividing the 
cumulative number of all functioning kidney grafts for the IOTA 
participant's IOTA transplant patients by the cumulative number of all 
kidney transplants performed by the IOTA participant during the first 
PY and all subsequent PYs on patients 18 years or older at the time of 
the transplant, as described in Equation 1 to Paragraph (b)(1).

Equation 1 to Paragraph (b)(1): Composite Graft Survival Rate
[GRAPHIC] [TIFF OMITTED] TP17MY24.019

    (i) For the first PY, CMS calculates the IOTA participant's 
composite graft survival rate based solely on the number of functioning 
grafts furnished to IOTA transplant patients during that PY and the 
number of completed kidney transplants during that PY, as described in 
paragraph (b)(1) of section.
    (ii) For all subsequent PYs, CMS calculates the IOTA participant's 
cumulative composite graft survival rate using the same calculation 
methodology described in paragraph (b)(1) of this section.
    (iii) CMS excludes the following from the numerator when 
calculating the composite graft survival rate:
    (A) Graft failure, based on OPTN adult kidney transplant recipient 
follow-up forms for all completed kidney transplants to determine 
failed grafts as defined by SRTR.
    (B) Re-transplant.
    (C) Death.
    (D) Patients who are under the age of 18 years of age at the time 
of the kidney transplant.
    (E) Offers to multi-organ candidates (except for kidney/pancreas 
candidates that are also listed for kidney alone).
    (iv)(A) When calculating the composite graft survival rate, CMS 
only includes kidney transplants for patients who are 18 years of age 
and older at the time of the kidney transplant in the number of kidney 
transplants performed by the IOTA participant during each PY in the 
denominator.
    (B) CMS identifies kidney transplants performed by the IOTA 
participant using OPTN data, regardless of payer, and Medicare claims 
data.
    (2) Quality measure set. (i) General. For each PY, CMS assesses the 
IOTA participant's performance on the following quality measures:
    (A) CollaboRATE Shared Decision-Making Score (CollaboRATE) (CBE 
ID:3327).
    (B) Colorectal Cancer Screening (COL) (CBE ID: 0034).
    (C) 3-Item Care Transition Measure (CTM-3) (CBE ID: 0228).
    (ii) Quality measure set survey and reporting requirements. (A) 
General. For each PY:
    (1) IOTA participants must survey, where applicable, attributed 
patients and submit data for the quality measures specified in 
paragraph (b)(2)(ii)(B) and (C) of this section to CMS during survey 
and reporting windows in a form and manner and at times established by 
CMS.
    (2) CMS notifies IOTA participants of the survey and reporting 
windows for each quality measure specified in paragraphs (b)(2)(ii)(B) 
and (C) of this section by the first day of each PY in a form and 
manner determined by CMS.
    (B) PRO-PM Survey and data reporting requirements. The IOTA 
participant must survey and submit data for all attributed patients 
once a PY, at minimum, on all of the following quality measures in 
accordance with paragraph (b)(2)(ii)(A) of this section:
    (1) CollaboRATE.
    (2) CTM-3
    (C) Process measure survey and data reporting requirements. The 
IOTA Participant must administer the COL measure yearly to all IOTA 
transplant patients who are Medicare beneficiaries.
    (3) Quality measure set selection under the IOTA Model. (i) 
General. CMS selects quality measures for inclusion in the IOTA Model 
quality measure set for the purpose of assessing IOTA participant 
performance in the quality domain.
    (ii) Updating of measure specifications. CMS uses rulemaking to 
make substantiative updates to the specifications of the quality 
measures used in the IOTA Model.
    (iii) Measure retention. All quality measures selected under 
paragraph (b)(2)(i) of this section will remain in the quality measure 
set unless CMS, through rulemaking, removes or replaces them.
    (iv) Measure addition, removal, suspension, or replacement through 
the rulemaking process. CMS will use the rulemaking process to add, 
remove, suspend, or replace quality measures in the IOTA Model to allow 
for public comment unless a quality measure raises specific safety 
concerns.
    (v) Factors for consideration of removal of quality measures. CMS 
weighs whether to remove a measure from the quality measure set 
specified in paragraph (b)(2)(i) of this section

[[Page 43623]]

based on one or more of the following factors:
    (A) A quality measure does not align with current clinical 
guidelines or practice.
    (B) Performance on a quality measure among IOTA participants is so 
high and unvarying that meaningful distinctions and improvement in 
performance can no longer be made (``topped out'' measure), as defined 
in 42 CFR 412.140(g)(3)(i)(A).
    (C) Performance or improvement on a quality measure does not result 
in better patient outcomes.
    (D) The availability of a more broadly applicable quality measure 
(across settings or populations) or the availability of a quality 
measure that is more proximal in time to desired patient outcomes for 
the particular topic.
    (E) The availability of a quality measure that is more strongly 
associated with desired patient outcomes for the particular topic.
    (F) Collection or public reporting of a quality measure leads to 
negative unintended consequences other than patient harm.
    (G) It is not feasible to implement the quality measure 
specifications.
    (H) The costs associated with a quality measure outweigh the 
benefit of its continued use in the IOTA Model.
    (vi) Application of measure removal factors. CMS assesses the 
benefits of removing or replacing a quality measure from the IOTA Model 
on a case-by-case basis.
    (vii) Patient safety exception. (A) If CMS determines that the 
continued requirement for IOTA participants to submit data on a quality 
measure raises specific patient safety concerns, CMS may elect to 
immediately remove the quality measure from the IOTA Model quality 
measure set.
    (B) CMS, upon removal of a quality measure and in a form and manner 
determined by CMS, does both of the following:
    (1) Provide notice to IOTA participants and the public at the time 
CMS removes the quality measure, along with a statement of the specific 
patient safety concerns that would be raised if IOTA participants 
continued to submit data on the quality measure.
    (2) Provide notice of the removal in the Federal Register.
    (c) Quality domain scoring. For each PY, CMS awards the IOTA 
participant zero to 20 points for the IOTA participant's performance in 
the quality domain, in accordance with the following:
    (1) For composite graft survival rate, as described under paragraph 
(d) of this section, the IOTA participant may receive up to 10 points.
    (2) For the quality measure set, as described under paragraph (e) 
of this section, the IOTA participant may receive up to 10 points.
    (i) The IOTA participant may receive a maximum of 4 points for 
their performance on the CollaboRATE Shared Decision-Making Score.
    (ii) The IOTA participant may receive a maximum of 2 points for 
their performance on the Colorectal Cancer Screening (COL) measure.
    (iii) The IOTA participant may receive a maximum of 4 points on the 
3-Item Care Transition Measure (CTM-3).
    (d) Composite graft survival rate scoring. CMS awards points to the 
IOTA participant based on the IOTA participant's performance on the 
composite graft survival rate, as described in paragraph (b)(1) of this 
section, ranked against a national target, inclusive of all eligible 
transplant hospitals. CMS awards points to the IOTA participant for 
composite graft survival rate as described in Table 1 to paragraph (d) 
of this section:

                   Table 1 to Paragraph (d)--IOTA Model Composite Graft Survival Rate Scoring
----------------------------------------------------------------------------------------------------------------
     Performance relative to target          Lower bound condition       Upper bound condition     Points earned
----------------------------------------------------------------------------------------------------------------
80th Percentile.........................  Equals 80th percentile....  Greater than 80th                       10
                                                                       percentile.
60th Percentile.........................  Equals 60th percentile....  Less than 80th percentile.               8
40th Percentile.........................  Equals 40th percentile....  Less than 60th percentile.               5
20th Percentile.........................  Equals 20th percentile....  Less than 40th percentile.               3
20th Percentile.........................  N/A.......................  Less than 20th percentile.               0
----------------------------------------------------------------------------------------------------------------

    (e) Quality measure set scoring. (1) For the first two PYs, CMS 
awards a maximum of 10 points to an IOTA participant, based on an IOTA 
participant's performance on the quality measures and requirements 
under paragraph (b)(2) of this section, as follows:
    (i) Response rate threshold: For the first two PYs CMS assesses an 
IOTA participant's performance on quality measures and awards points 
based on a response rate threshold for each measure.
    (A) CMS defines the response rate threshold at the level of 
complete and accurate reporting for each quality measure specified 
under paragraph (b)(2)(i) of this section.
    (B) CMS determines the response rate threshold for each measure 
before the start of each PY.
    (C) CMS informs IOTA participants of the response rate threshold 
for each quality measure by the first day of the PY in a form and 
manner chosen by CMS.
    (ii) Quality measure set scoring methodology. CMS uses the scoring 
methodology described in Table 1 to paragraph (e)(1) of this section to 
determine the following:
    (A) The IOTA participant's score on the CollaboRATE;
    (B) The IOTA participant's score on the CTM-3; and
    (C) The IOTA participant's score on the COL measure for all IOTA 
transplant patients who are Medicare beneficiaries.

                       Table 1 to Paragraph (e)(1)--IOTA Model Quality Measure Set Scoring
----------------------------------------------------------------------------------------------------------------
                                       Performance          Lower bound          Upper bound
             Measure                relative to target       condition            condition        Points earned
----------------------------------------------------------------------------------------------------------------
CollaboRATE/CTM-3................  90% Response Rate..  Equals 90%.........  Greater than 90%...               4
CollaboRATE/CTM-3................  50% Response Rate..  Equals 50%.........  Less than 90%......               2
CollaboRATE/CTM-3................  50% Response Rate..  N/A................  Less than 50%......               0
COL..............................  50% Response Rate..  Equals 50%.........  Greater than 50%...               2
COL..............................  50% Response Rate..  N/A................  Less than 50%......               0
----------------------------------------------------------------------------------------------------------------


[[Page 43624]]

    (2) For subsequent PYs--
    (i) The quality performance score will be phased in such that an 
IOTA participant must continue to report all measures, but CMS assesses 
an IOTA participant's performance based on quality performance 
benchmarks and response rate thresholds, as specified by CMS in future 
rulemaking, for each quality measure under Sec.  512.428(b)(2); and
    (ii) CMS awards a maximum of 10 points to an IOTA participant based 
on its performance as set forth in paragraph (e)(2)(i) of this section.

Payment


Sec.  512.430  Upside risk payment, downside risk payment, and neutral 
zone.

    (a) General. CMS determines if an IOTA participant qualifies for an 
upside risk, downside risk payment, or neutral zone for each PY based 
on the IOTA participant's final performance score, in accordance with 
paragraphs (b)(1) through (3) of this section.
    (b) Upside risk payment, neutral zone, and downside risk payment 
calculation methodology--(1) Upside risk payment calculation 
methodology. If in PYs 1-6 the IOTA participant's final performance 
score is 60 points or above, CMS calculates the IOTA participant's 
upside risk payment as follows:
    (i) Subtracts 60 from the IOTA participant's final performance 
score from 100.
    (ii) Divides the amount resulting from the calculation in paragraph 
(b)(1)(i) of this section by 40.
    (iii) Multiplies the amount resulting from the calculation in 
paragraph (b)(1)(ii) of this section by $8,000.
    (iv) Multiplies the amount resulting from the calculation in 
paragraph (b)(1)(iii) of this section by the total number of Medicare 
kidney transplants performed by the IOTA participant during the PY.
    (2) Neutral zone. (i) For PY 1, IOTA participants with a final 
performance score below 60 points qualify for the neutral zone and 
neither owes a downside risk payment to CMS nor receives an upside risk 
payment from CMS.
    (ii) For PYs 2-6, if an IOTA participant's final performance is 
between 41 to 59 points (inclusive), the IOTA participant qualifies for 
the neutral zone.
    (3) Downside risk payment calculation methodology. If an IOTA 
participant is at or below 40 points in PYs 1-6, the IOTA participant 
qualifies for a downside risk payment. The downside risk payment is 
calculated as follows:
    (i) For PY 1, this paragraph does not apply, and the IOTA 
participant does not owe a downside risk payment to CMS.
    (ii) For PYs 2-6, CMS calculates the IOTA participant's downside 
risk payment as follows:
    (A) Subtracts the IOTA participant's final performance score from 
40.
    (B) Divides the amount resulting from the calculation in paragraph 
(b)(3)(ii)(A) of this section by 40.
    (C) Multiplies the amount resulting from the calculation in 
paragraph (b)(3)(ii)(B) of this section by $2,000.
    (D) Multiplies the amount resulting from the calculation in 
paragraph (b)(3)(ii)(C) of this section by the total number of Medicare 
kidney transplants performed by the IOTA participant during the PY to 
calculate the amount of the IOTA participant's downside risk payment.
    (d) Upside risk payment and downside risk payment timeline. (1) CMS 
conducts and calculates preliminary performance assessment and payment 
calculations at least 3 to 6 months after the end of each PY.
    (2) CMS notifies the IOTA participant of their preliminary 
performance assessment and payment calculations in a form and manner 
determined by CMS at least 5 to 9 months after the end of each PY.
    (3) CMS gives IOTA participants 30 days to review preliminary 
performance assessment and payment calculations and request targeted 
reviews under Sec.  512.434.
    (4) CMS notifies the IOTA participant of their final performance 
score and any associated upside risk payment or downside risk payment 
at least 30 days after notifying the IOTA participant of their 
preliminary performance assessment and payment calculations.
    (5) Upside risk payment. After CMS notifies the IOTA participant of 
their final performance score and any associated upside risk payment, 
and by a date determined by CMS, CMS issues the upside risk payment to 
the tax identification number (TIN) on file for the IOTA participant in 
the Medicare Provider Enrollment, Chain, and Ownership System (PECOS).
    (6) Downside risk payment. After CMS notifies the IOTA participant 
of their final performance score and any associated downside risk 
payment and by a date determined by CMS, CMS issues a demand letter to 
the TIN on file for the IOTA participant in PECOS for any downside risk 
payment owed to CMS.
    (i) CMS includes all of the following details in the demand letter:
    (A) IOTA participant performance in the model.
    (B) Amount of downside risk payment owed to CMS by the IOTA 
participant.
    (C) How the IOTA participant may make payments to CMS.
    (ii) The IOTA participant must pay the downside risk payment to CMS 
in a single payment at least 60 days after the date which the demand 
letter is issued.


Sec.  512.434  Targeted review.

    (a) General. Subject to the limitations on review in subpart c of 
this part, an IOTA participant may submit a targeted review request for 
one or more calculations made, and issued by, CMS within the 
preliminary performance assessment and payment calculations, if either 
of the following occur:
    (1) The IOTA participant believes an error occurred in calculations 
due to data quality or other issues.
    (2) The IOTA participant believes an error occurred in calculations 
due to misapplication of methodology.
    (b) Requirements. The request must satisfy the following criteria:
    (1) Be submitted within 30 days, or another time period as 
specified by CMS, of receiving its preliminary performance assessment 
and payment calculations from CMS.
    (2) Include supporting information in a form and manner as 
specified by CMS.
    (c) Limitations on review. (1) CMS does not consider a targeted 
review request any policy or methodology, including without limitation 
the following:
    (i) The selection of the kidney transplant hospital to be an IOTA 
participant.
    (ii) The attribution of IOTA waitlist patients and the attribution 
of IOTA transplant patients to the IOTA participant, or to any other 
kidney transplant hospital selected for participation in the IOTA 
Model, or to any kidney transplant hospital not selected for 
participation in the IOTA Model.
    (iii) The methodology used for determining the achievement domain, 
efficiency domain, and quality domain.
    (iv) The methodology used for calculating and assigning points for 
each metric within the achievement domain, efficiency domain, and 
quality domain.
    (v) The methodology used for calculating the payment amount per 
Medicare kidney transplant paid to an IOTA participant.
    (2) CMS may review a targeted review request that includes one or 
more of the limitations in paragraph (c)(1) of this section, provided 
that all remaining

[[Page 43625]]

considerations of the request meet all other criteria for consideration 
by CMS in this section.
    (d) Targeted review process. The IOTA participant must submit a 
request for targeted review in accordance with paragraphs (a) through 
(c) of this section. The process for a targeted review is as follows:
    (1) Initial and final assessments. Upon receipt of a targeted 
review request from an IOTA participant CMS conducts an initial and 
final assessment as follows:
    (i) Initial assessment. (A) CMS determines if the targeted review 
request meets the targeted review requirements in paragraph (b) of this 
section and contains sufficient information to substantiate the 
request.
    (B) If the request is not compliant with paragraphs (a) through (c) 
of this section or requires additional information:
    (1) CMS follows up with the IOTA participant to request additional 
information in a form and manner as specified by CMS.
    (2) The IOTA participant must respond within 30 days of CMS's 
request for additional information in a form and manner as specified by 
CMS.
    (3) An IOTA participant's non-responsiveness to the request for 
additional information from CMS may result in the closure of the 
targeted review request.
    (ii) Final assessment. (A) Upon completion of an initial 
assessment, as described in paragraph (d)(1)(i) of this section, CMS 
determines whether it erred in calculation, as disputed by the IOTA 
participant.
    (B) If a calculation error is found as a result of an IOTA 
participant's targeted review request--
    (1) CMS--(i) Notifies the IOTA participant within 30 days of any 
findings in a form and manner as specified by CMS; and
    (ii) Resolves and correct any resulting error or discrepancy in the 
amount of the upside risk payment or downside risk payment in a time 
and manner as determined by CMS.
    (2) CMS' correction of any error or discrepancy may delay the 
effective date of an IOTA participant's upside risk payments or 
downside risk payments.
    (2) Targeted review decisions made by CMS are final, unless 
submitted for administrative review as described in Sec.  512.190.


Sec.  512.436  Extreme and uncontrollable circumstances.

    (a) General. CMS--
    (1) Applies determinations made under the Quality Payment Program 
with respect to whether an extreme and uncontrollable circumstance has 
occurred and the affected area during the PY; and
    (2) Has sole discretion to determine the time period during which 
an extreme and uncontrollable circumstance occurred and the percentage 
of attributed patients residing in affected areas.
    (b) Downside risk payment. In the event of an extreme and 
uncontrollable circumstance, as determined by the Quality Payment 
Program, CMS may reduce the amount of the IOTA participant's downside 
risk payment, if applicable, prior to recoupment. CMS determines the 
amount of the reduction by multiplying the downside risk payment by 
both the following:
    (1) The percentage of total months during the PY affected by the 
extreme and uncontrollable circumstance.
    (2) The percentage of attributed patients who reside in an area 
affected by the extreme and uncontrollable circumstance.

Data Sharing


Sec.  512.440  Data sharing.

    (a) General. CMS shares certain beneficiary-identifiable data as 
described in paragraph (b) of this section and certain aggregate data 
as described in paragraph (c) of this section with IOTA participants 
regarding attributed patients including attributed patients who are 
Medicare beneficiaries and performance under the model.
    (b) Beneficiary-identifiable data. CMS shares beneficiary-
identifiable data with IOTA participants as follows:
    (1) CMS makes available certain beneficiary-identifiable data 
described in paragraphs (b)(4) and (5) of this section for IOTA 
participants to request for purposes of conducting health care 
operations work that falls within the first or second paragraph of the 
definition of health care operations at 45 CFR 164.501 on behalf of 
their attributed patients who are Medicare beneficiaries.
    (2) An IOTA participant that wishes to receive beneficiary-
identifiable data for its attributed patients who are Medicare 
beneficiaries must do all of the following:
    (i) Submit a formal request for the data, on an annual basis in a 
manner and form and by a date specified by CMS, which identifies the 
data being requested and attests that--
    (A) The IOTA participant is requesting this beneficiary-
identifiable data as a HIPAA covered entity or as a business associate, 
as those terms are defined at 45 CFR 160.103, to the IOTA participant's 
providers and suppliers who are HIPAA covered entities; and
    (B) The IOTA participant's request reflects the minimum data 
necessary, as set forth in paragraph (b)(6) of this section, for the 
IOTA participant to conduct health care operations work that falls 
within the first or second paragraph of the definition of health care 
operations at 45 CFR 164.501;
    (ii) Limit the request to Medicare beneficiaries whose name appears 
on the quarterly attribution list who have been notified in compliance 
with Sec.  512.450 that the IOTA participant has requested access to 
beneficiary-identifiable data, and who did not decline having their 
claims data shared with the IOTA participant as provided in paragraph 
(b)(7) of this section; and
    (iii) Sign and submit a data sharing agreement with CMS as set 
forth in paragraph (b)(8) of this section.
    (3) CMS share beneficiary-identifiable data with an IOTA 
participant on the condition that the IOTA participant, its IOTA 
collaborators, and other individuals or entities performing functions 
or services related to the IOTA participant's activities observe all 
relevant statutory and regulatory provisions regarding the appropriate 
use of data and the confidentiality and privacy of individually 
identifiable health information and comply with the terms of the data 
sharing agreement described in paragraph (b)(8) of this section.
    (4) CMS omits from the beneficiary-identifiable data any 
information that is subject to the regulations in 42 CFR part 2 
governing the confidentiality of substance use disorder patient 
records.
    (5) The beneficiary-identifiable data will include, when available, 
the following information:
    (i) Quarterly attribution lists. For the relevant PY, CMS shares 
with the IOTA participant the quarterly attribution lists, which will 
include but may not be limited to the following information for each 
attributed patient:
    (A) The year that CMS attributed the patient to the IOTA 
participant.
    (B) The effective date of the patient's attribution to the IOTA 
participant.
    (C) The effective date of the patient's de-attribution from the 
IOTA participant and the reason for such removal (if applicable).
    (D) For Medicare beneficiaries, the attributed patient's data 
sharing preference.
    (ii) Beneficiary-identifiable claims data. CMS makes available 
certain beneficiary-identifiable claims data for retrieval by IOTA 
participants no later than 1 month after the start of each PY,

[[Page 43626]]

in a form and manner specified by CMS. IOTA participants may retrieve 
the following data at any point during the relevant PY. This claims 
data includes all of the following:
    (A) Three years of historical Parts A, B, and D claims data files 
from the 36 months immediately preceding the effective date of each 
attributed patient who is a Medicare beneficiary's attribution to the 
IOTA participant.
    (B) Monthly Parts A, B, and D claims data files for attributed 
patients who are Medicare beneficiaries.
    (C) Monthly Parts A, B, and D claims data files for Medicare 
beneficiaries who have been de-attributed from the IOTA participant for 
claims with a date of service before the date the Medicare beneficiary 
was de-attributed from the IOTA participant.
    (6) The IOTA participant must limit its attributed Medicare 
beneficiary identifiable data requests to the minimum necessary to 
accomplish a permitted use of the data.
    (i) The minimum necessary Parts A and B data elements may include 
but are not limited to the following data elements:
    (A) Medicare beneficiary identifier (ID).
    (B) Procedure code.
    (C) Gender.
    (D) Diagnosis code.
    (E) Claim ID.
    (F) The from and through dates of service.
    (G) The provider or supplier ID.
    (H) The claim payment type.
    (I) Date of birth and death, if applicable.
    (J) Tax identification number (TIN).
    (K) National provider identifier (NPI).
    (ii) The minimum necessary Part D data elements may include but are 
not limited to the following data elements:
    (A) Beneficiary ID.
    (B) Prescriber ID.
    (C) Drug service date.
    (D) Drug product service ID.
    (E) Quantity dispensed.
    (F) Days supplied.
    (G) Brand name.
    (H) Generic name.
    (I) Drug strength.
    (J) TIN.
    (K) NPI.
    (L) Indication if on formulary.
    (M) Gross drug cost.
    (7)(i)(A) IOTA participants must send Medicare beneficiaries a 
notification about the IOTA model and the opportunity to decline claims 
data sharing as required under Sec.  512.450.
    (B) Such notifications must state that the IOTA participant may 
have requested beneficiary-identifiable claims data about the Medicare 
beneficiary for purposes of its care coordination, quality improvement 
work, and population-based activities relating to improving health or 
reducing health care costs, and inform the Medicare beneficiary how to 
decline having his or her claims information shared with the IOTA 
participant in the form and manner specified by CMS.
    (ii) Medicare beneficiary requests to decline claims data sharing 
remain in effect unless and until a beneficiary subsequently contacts 
CMS to amend that request to permit claims data sharing with IOTA 
participants.
    (iii) The opportunity to decline having claims data shared with an 
IOTA participant under paragraph (b)(7)(i) of this section does not 
apply to:
    (A) The aggregate data that CMS provides to IOTA participants under 
paragraph (c) of this section.
    (B) The initial attribution lists that CMS provides to IOTA 
participants as defined at Sec.  512.402 and under Sec.  
512.414(c)(1)(ii).
    (C) The quarterly attribution lists that CMS provides to IOTA 
participants as defined at Sec.  512.402 and under Sec.  
512.414(c)(2)(ii).
    (D) The annual attribution reconciliation list that CMS provides to 
IOTA participants as defined at Sec.  512.402 and under Sec.  
512.414(c)(3)(ii).
    (8)(i) If an IOTA participant wishes to retrieve any beneficiary-
identifiable data specified in paragraph (b) of this section, the IOTA 
participant must complete and submit, on an annual basis, a signed data 
sharing agreement, to be provided in a form and manner specified by 
CMS, under which the IOTA participant agrees to all of the following:
    (A) To comply with the requirements for use and disclosure of this 
beneficiary-identifiable data that are imposed on covered entities by 
the HIPAA regulations at 45 CFR part 160 and part 164, subparts A and 
E, and the requirements of the IOTA model set forth in this part.
    (B) To comply with additional privacy, security, breach 
notification, and data retention requirements specified by CMS in the 
data sharing agreement.
    (C) To contractually bind each downstream recipient of the 
beneficiary-identifiable data that is a business associate of the IOTA 
participant, including all IOTA collaborators, to the same terms and 
conditions to which the IOTA participant is itself bound in its data 
sharing agreement with CMS as a condition of the business associate's 
receipt of the beneficiary-identifiable data retrieved by the IOTA 
participant under the IOTA model.
    (D) That if the IOTA participant misuses or discloses the 
beneficiary-identifiable data in a manner that violates any applicable 
statutory or regulatory requirements or that is otherwise non-compliant 
with the provisions of the data sharing agreement, CMS may:
    (1) Deem the IOTA participant ineligible to retrieve the 
beneficiary-identifiable data under paragraph (b) of this section for 
any amount of time;
    (2) Terminate the IOTA participant's participation in the IOTA 
model under Sec.  512.466; and
    (3) Subject the IOTA participant to additional sanctions and 
penalties available under the law.
    (ii) An IOTA participant must comply with all applicable laws and 
the terms of the data sharing in order to retrieve beneficiary-
identifiable data.
    (c) Aggregate Data. (1) CMS shares aggregate performance data with 
IOTA participants, in a form and manner to be specified by CMS, which 
has been de-identified in accordance with 45 CFR 164.514(b). This 
aggregate data includes, when available, certain de-identified data 
detailing the IOTA participant's performance against the transplant 
target information for each PY.


Sec.  512.442  Transparency requirements.

    (a) Publication of transplant patient selection criteria. The IOTA 
participant must publicly post on its website, the criteria used by the 
IOTA participant for evaluating and selecting patients for addition to 
their kidney transplant waitlist by the end of PY 1.
    (b) Transparency into kidney transplant organ offers. The IOTA 
participant must do the following for all IOTA waitlist patients who 
are Medicare beneficiaries during the model performance period:
    (1) Inform IOTA waitlist patients who are Medicare beneficiaries of 
the number of times an organ is declined on the patient's behalf.
    (i) For months in which an organ offer is made, provide notices to 
each IOTA waitlist patient who is a Medicare beneficiary on a monthly 
basis that include the following:
    (A) The number of times an organ is declined on the IOTA waitlist 
patient's behalf.
    (B) The reason(s) why the organ was declined.
    (2) Record in the IOTA waitlist patient's medical record that the 
patient--
    (i) Received the information specified in paragraph (b)(1) of this 
section; and
    (ii) The method by which information was delivered.
    (3) Share the information specified in paragraph (b)(1) of this 
section with the

[[Page 43627]]

IOTA waitlist patient's nephrologist or nephrology professional if 
deemed appropriate by the IOTA participant.
    (c) Review of selection criteria and organ-offer filters. IOTA 
participants must review transplant acceptance criteria and organ offer 
filters with their IOTA waitlist patients who are Medicare 
beneficiaries at least once every 6 months that the Medicare 
beneficiary is on their waitlist.
    (1) The IOTA participant must conduct this review via patient 
visit, phone, email or mail on an individual basis, unless the Medicare 
beneficiary declines this review.
    (2) [Reserved]


Sec.  512.444  Health equity plans.

    (a) For PY 2 through PY 6, each IOTA participant must submit a 
health equity plan, by a date and in a form and manner determined by 
CMS, that meets the following requirements:
    (1) Identifies target health disparities.
    (2) Identifies the data sources used to inform the identification 
of target health disparities.
    (3) Describes the health equity plan intervention.
    (4) Includes a resource gap analysis.
    (5) Includes a health equity project plan.
    (6) Identifies health equity plan performance measure(s).
    (7) Identifies health equity goals and describes how the IOTA 
participant will use the health equity goals to monitor and evaluate 
progress in reducing targeted health disparities
    (b) Once the IOTA participant submits their health equity plan to 
CMS, CMS uses reasonable efforts to approve or reject the health equity 
plan within 60 business days.
    (c) If CMS approves the IOTA participant's health equity plan, the 
IOTA participant must engage in activities related to the execution of 
the IOTA participant's health equity plan, including implementing 
health equity plan interventions and monitoring and evaluating progress 
in reducing target health disparities.
    (d) If CMS determines that the IOTA participant's health equity 
plan does not satisfy the requirements and is inconsistent with the 
applicable CMS Health Equity Plan guidance, does not provide sufficient 
evidence or documentation to demonstrate that the health equity plan is 
likely to accomplish the IOTA participant's intended health equity 
goals, or is likely to result in program integrity concerns, or 
negatively impact beneficiaries' access to quality care, CMS may reject 
the health equity plan or require amendment of the health equity plan 
at any time, including after its initial submission and approval.
    (1) If CMS rejects the IOTA participant's health equity plan, in 
whole or in part, the IOTA participant may not, and must require its 
IOTA collaborators to not, conduct health equity activities identified 
in the health equity plan.
    (2) [Reserved]
    (e) In PY 3, and each subsequent PY, in a form and manner and by 
the date(s) specified by CMS, the IOTA participant must submit to CMS 
an update on its progress in implementing its health equity plan. This 
update must include all of the following:
    (1) Updated outcomes data for the health equity plan performance 
measure(s).
    (2) Updates to the resource gap analysis.
    (3) Updates to the health equity project plan.
    (f) If the IOTA participant fails to meet the requirements 
described in paragraph (a) of this section, CMS may subject the IOTA 
participant to remedial action, as specified in Sec.  512.464, 
including either of the following:
    (1) Corrective action such as recoupment of any upside risk 
payments.
    (2) Termination from the model.

Beneficiary Protections, Financial Arrangements, Beneficiary 
Incentives, and Compliance


Sec.  512.450  Required beneficiary notifications.

    (a) General. (1) IOTA participants must provide notice to 
attributed patients that they are participating in the IOTA Model.
    (2) CMS provides a notification template that IOTA participants 
must use. The template, at minimum does all of the following:
    (i) Indicates content that the IOTA participant must not change.
    (ii) Indicates where the IOTA participant may insert its own 
content.
    (iii) Includes information regarding the attributed patient's 
opportunity to opt-out of data sharing with IOTA participants and how 
they may opt out if they choose to do so.
    (3) To notify attributed patients of their rights and protections 
and that the IOTA participant is participating in the IOTA Model the 
IOTA participant must do all of the following:
    (i) Prominently display informational materials in each of their 
office or facility locations where attributed patients receive 
treatment.
    (ii) Include in a clear manner on its public facing website, and to 
each attributed patient in a paper format.
    (iii) Provide this notification to each attributed patient in a 
paper format.
    (b) Applicability of general Innovation Center model provisions. 
(1) The requirement described in Sec.  512.120(c) do not apply to the 
CMS-provided materials described in paragraph (a) of this section.
    (2) All other IOTA participant communications that are descriptive 
model materials and activities as defined under Sec.  512.110 must meet 
the requirements described in Sec.  512.120(c).


Sec.  512.452  Financial sharing arrangements and attributed patient 
engagement incentives.

    (a) General. (1) The IOTA participant--
    (i) May enter into a sharing arrangement with an IOTA collaborator 
to make a gainsharing payment, or to receive an alignment payment, or 
both; and
    (ii) Must not make a gainsharing payment or receive an alignment 
payment except in accordance with a sharing arrangement.
    (2) A sharing arrangement must comply with the provisions of this 
section and all other applicable laws and regulations, including the 
applicable fraud and abuse laws and all applicable payment and coverage 
requirements.
    (3) The IOTA participant must develop, maintain, and use a set of 
written policies for selecting providers and suppliers to be IOTA 
collaborators.
    (i) The selection criteria must include the quality of care 
delivered by the potential IOTA collaborator.
    (ii) The selection criteria cannot be based directly or indirectly 
on the volume or value of referrals or business otherwise generated by, 
between or among any of the following:
    (A) The IOTA participant.
    (B) Any IOTA collaborator.
    (C) Any collaboration agent.
    (D) Any individual or entity affiliated with an IOTA participant, 
IOTA collaborator, or collaboration agent.
    (iii) The written policies must contain criteria related to, and 
inclusive of, the anticipated contribution to performance across the 
achievement domain, efficiency domain, and quality domain by the 
potential IOTA collaborator.
    (4) The board or other governing body of the IOTA participant must 
have responsibility for overseeing the IOTA participant's participation 
in the IOTA Model, including but not limited to all of the following:
    (i) Arrangements with IOTA collaborators.
    (ii) Payment of gainsharing payments.
    (iii) Receipt of alignment payments.

[[Page 43628]]

    (iv) Use of beneficiary incentives in the IOTA Model.
    (5) If an IOTA participant enters into a sharing arrangement, its 
compliance program must include oversight of sharing arrangements and 
compliance with the applicable requirements of the IOTA Model.
    (b) Requirements. (1) A sharing arrangement must be--
    (i) In writing;
    (ii) Signed by the parties; and
    (iii) Entered into before care is furnished to attributed patient 
during the PY under the sharing arrangement.
    (2) Participation in a sharing arrangement must be voluntary and 
without penalty for nonparticipation.
    (3) Participation in the sharing arrangement must require the IOTA 
collaborator to comply with the requirements of this model, as those 
pertain to their actions and obligations.
    (4) The sharing arrangement--
    (i) Must set out the mutually agreeable terms for the financial 
arrangement between the parties to guide and reward model care redesign 
for future performance across the achievement domain, efficiency 
domain, and quality domain;
    (ii) Must not reflect the results of model PYs that have already 
occurred; and
    (iii) Where the financial outcome of the sharing arrangement terms 
are known before signing.
    (5) The sharing arrangement must require the IOTA collaborator and 
its employees, contractors (including collaboration agents), and 
subcontractors to comply with all of the following:
    (i) The applicable provisions of this part (including requirements 
regarding beneficiary notifications, access to records, record 
retention, and participation in any evaluation, monitoring, compliance, 
and enforcement activities performed by CMS or its designees).
    (ii) All applicable Medicare provider enrollment requirements at 
Sec.  424.500 et seq. of this chapter, including having a valid and 
active TIN or NPI, during the term of the sharing arrangement.
    (iii) All other applicable laws and regulations.
    (5) The sharing arrangement must require the IOTA collaborator to 
have or be covered by a compliance program that includes oversight of 
the sharing arrangement and compliance with the requirements of the 
IOTA Model that apply to its role as an IOTA collaborator, including 
any distribution arrangements.
    (6) The sharing arrangement must not pose a risk to beneficiary 
access, beneficiary freedom of choice, or quality of care.
    (7) The written agreement memorializing a sharing arrangement must 
specify all of the following:
    (i) The purpose and scope of the sharing arrangement.
    (ii) The identities and obligations of the parties, including 
specified IOTA activities and other services to be performed by the 
parties under the sharing arrangement.
    (iii) The date of the sharing arrangement.
    (iv) Management and staffing information, including type of 
personnel or contractors that would be primarily responsible for 
carrying out IOTA activities.
    (v) The financial or economic terms for payment, including all of 
the following:
    (A) Eligibility criteria for a gainsharing payment.
    (B) Eligibility criteria for an alignment payment.
    (C) Frequency of gainsharing or alignment payment.
    (D) Methodology and accounting formula for determining the amount 
of a gainsharing payment that is substantially based on performance 
across the achievement domain, efficiency domain and quality domain, 
and the provision of IOTA activities.
    (E) Methodology and accounting formula for determining the amount 
of an alignment payment.
    (8) The sharing arrangement must not--
    (i) Induce--
    (A) The IOTA participant;
    (B) The IOTA collaborator; or
    (C) Any employees, contractors, or subcontractors of the IOTA 
participant or IOTA collaborator to reduce or limit medically necessary 
services to any attributed patient; or
    (ii) Restrict the ability of an IOTA collaborator to make decisions 
in the best interests of its patients, including the selection of 
devices, supplies, and treatments.
    (c) Gainsharing payments and alignment payments. (1) Gainsharing 
payments, if any, must meet all of the following:
    (i) Be derived solely from upside risk payments.
    (ii) Be distributed on an annual basis (not more than once per 
calendar year).
    (iii) Not be a loan, advance payment, or payment for referrals or 
other business.
    (iv) Be clearly identified as a gainsharing payment at the time it 
is paid.
    (2) To be eligible to receive a gainsharing payment an IOTA 
collaborator must contribute to performance across the achievement 
domain, efficiency domain or quality domain for the PY for which the 
IOTA participant earned the upside risk payment that comprises the 
gainsharing payment. The contribution to performance across the 
achievement domain, efficiency domain, or quality domain criteria must 
be established by the IOTA participant and directly related to the care 
of attributed patients.
    (3) To be eligible to receive a gainsharing payment, or to be 
required to make an alignment payment:
    (i) An IOTA collaborator other than PGP, NPPGP, or TGP must have 
directly furnished a billable item or service to an attributed patient 
that occurred in the same PY for which the IOTA participant earned the 
upside risk payment that comprises the gainsharing payment or incurred 
in a downside risk payment.
    (ii) An IOTA collaborator that is a PGP, NPPGP, or TGP must meet 
the following criteria:
    (A) The PGP, NPPGP, or TGP must have billed for an item or service 
that was rendered by one or more PGP member, NPPGP member, or TGP 
member respectively to an attributed patient that occurred during the 
same PY for which the IOTA participant earned the upside risk payment 
that comprises the gainsharing payment or incurred a downside risk 
payment.
    (B) The PGP, NPPGP, or TGP must have contributed to IOTA activities 
and been clinically involved in the care of attributed patients during 
the same PY for which the IOTA participant earned the upside risk 
payment that comprises the gainsharing payment or incurred a downside 
risk payment.
    (4) The total amount of a gainsharing payment for a PY paid to an 
IOTA collaborator that is a physician or nonphysician practitioner must 
not exceed 50 percent of the Medicare-approved amounts under the PFS 
for items and services billed by that physician or nonphysician 
practitioner to the IOTA participant's attributed patients during the 
same PY for which the IOTA participant earned the upside risk payment 
that comprises the gainsharing payment being made.
    (5) The total amount of a gainsharing payment for a PY paid to an 
IOTA collaborator that is a PGP, NPPGP, or TGP must not exceed 50 
percent of the Medicare-approved amounts under the PFS for items and 
services billed by that PGP, NPPGP, or TGP and furnished to the IOTA 
participant's attributed patients by the PGP members, NPPGP members, or 
TGP members respectively during the same PY for which the IOTA 
participant earned the upside risk

[[Page 43629]]

payment that comprises the gainsharing payment being made.
    (6) The amount of any gainsharing payments must be determined in 
accordance with a methodology that is substantially based on 
contribution to the performance across the achievement domain, 
efficiency domain or quality domain and the provision of IOTA 
activities. The methodology may take into account the amount of such 
IOTA activities provided by an IOTA collaborator relative to other IOTA 
collaborators.
    (7) For a PY, the aggregate amount of all gainsharing payments that 
are derived from the upside risk payment the IOTA participant receives 
from CMS must not exceed the amount of that upside risk payment.
    (8) No entity or individual, whether a party to a sharing 
arrangement or not, may condition the opportunity to make or receive 
gainsharing payments or to make or receive alignment payments directly 
or indirectly on the volume or value of referrals or business otherwise 
generated by, between or among the IOTA participant, any IOTA 
collaborator, any collaboration agent, or any individual or entity 
affiliated with an IOTA participant, IOTA collaborator, or 
collaboration agent.
    (9) An IOTA participant must not make a gainsharing payment to an 
IOTA collaborator that is subject to any action for noncompliance with 
this part, or the fraud and abuse laws, or for the provision of 
substandard care to attributed patients or other integrity problems.
    (10) The sharing arrangement must require the IOTA participant to 
recoup any gainsharing payment that contained funds derived from a CMS 
overpayment on an upside risk payment or was based on the submission of 
false or fraudulent data.
    (11) Alignment payments from an IOTA collaborator to an IOTA 
participant may be made at any interval that is agreed upon by both 
parties, and must not be--
    (i) Issued, distributed, or paid prior to the calculation by CMS of 
a payment amount reflected in the notification of the downside risk 
payment;
    (ii) Loans, advance payments, or payments for referrals or other 
business; or
    (iii) Assessed by an IOTA participant if the IOTA participant does 
not owe a downside risk payment.
    (12) The IOTA participant must not receive any amounts under a 
sharing arrangement from an IOTA collaborator that are not alignment 
payments.
    (13) For a PY, the aggregate amount of all alignment payments 
received by the IOTA participant must not exceed 50 percent of the IOTA 
participant's downside risk payment amount.
    (14) The aggregate amount of all alignment payments from a single 
IOTA collaborator to the IOTA participant may not be greater than 25 
percent of the IOTA participant's downside risk payment over the course 
of a single PY for an IOTA collaborator.
    (15) The amount of any alignment payments must be determined in 
accordance with a methodology that does not directly account for the 
volume or value of referrals or business otherwise generated by, 
between or among the IOTA participant, any IOTA collaborator, any 
collaboration agent, or any individual or entity affiliated with an 
IOTA participant, IOTA collaborator, or collaboration agent.
    (16) All gainsharing payments and any alignment payments must be 
administered by the IOTA participant in accordance with generally 
accepted accounting principles (GAAP) and Government Auditing Standards 
(The Yellow Book).
    (17) All gainsharing payments and alignment payments must be made 
by check, EFT, or another traceable cash transaction.
    (d) Documentation requirements. (1) The IOTA participant must do 
all of the following:
    (i) Document the sharing arrangement contemporaneously with the 
establishment of the arrangement.
    (ii) Maintain accurate current and historical lists of all IOTA 
collaborators, including IOTA collaborator names and addresses. With 
respect to these lists the IOTA participant must--
    (A) Update such lists on at least a quarterly basis; and
    (B) On a web page on the IOTA participant's website, the IOTA 
participant must--
    (1) Publicly report the current and historical lists of IOTA 
collaborators; and
    (2) Include any written policies for selecting individuals and 
entities to be IOTA collaborators required by the IOTA participant.
    (iii) Maintain and require each IOTA collaborator to maintain 
contemporaneous documentation with respect to the payment or receipt of 
any gainsharing payment or alignment payment that includes at a minimum 
all of the following:
    (A) Nature of the payment (gainsharing payment or alignment 
payment).
    (B) Identity of the parties making and receiving the payment.
    (C) Date of the payment.
    (D) Amount of the payment.
    (E) Date and amount of any recoupment of all or a portion of an 
IOTA collaborator's gainsharing payment.
    (F) Explanation for each recoupment, such as whether the IOTA 
collaborator received a gainsharing payment that contained funds 
derived from a CMS overpayment of an upside risk payment or was based 
on the submission of false or fraudulent data.
    (2) The IOTA participant must keep records of all of the following:
    (i) Its process for determining and verifying its potential and 
current IOTA collaborators' eligibility to participate in Medicare.
    (ii) A description of current health information technology, 
including systems to track upside risk payments and downside risk 
payments.
    (iii) Its plan to track gainsharing payments and alignment 
payments.
    (3) The IOTA participant must retain and provide access to, and 
must require each IOTA collaborator to retain and provide access to, 
the required documentation in accordance with Sec. Sec.  512.460 and 
1001.952(ii).


Sec.  512.454  Distribution arrangements.

    (a) General. (1) An IOTA collaborator may distribute all or a 
portion of any gainsharing payment it receives from the IOTA 
participant only in accordance with a distribution arrangement, as 
defined at Sec.  512.402.
    (2) All distribution arrangements must comply with the provisions 
of this section and all other applicable laws and regulations, 
including the fraud and abuse laws.
    (b) Requirements. (1) All distribution arrangements must be in 
writing and signed by the parties, contain the date of the agreement, 
and be entered into before care is furnished to attributed patients 
under the distribution arrangement.
    (2) Participation in a distribution arrangement must be voluntary 
and without penalty for nonparticipation.
    (3) The distribution arrangement must require the collaboration 
agent to comply with all applicable laws and regulations.
    (4) The opportunity to make or receive a distribution payment must 
not be conditioned directly or indirectly on the volume or value of 
referrals or business otherwise generated by, between or among the IOTA 
participant, any IOTA collaborator, any collaboration agent, or any 
individual or entity affiliated with an IOTA participant, IOTA 
collaborator, or collaboration agent.
    (5) The amount of any distribution payments from an NPPGP to an 
NPPGP

[[Page 43630]]

member, or from a TGP to a TGP member must be determined in accordance 
with a methodology that is substantially based on contribution to 
performance across the achievement domain, efficiency domain, and 
quality domain and the provision of IOTA activities and that may take 
into account the amount of such IOTA activities provided by a 
collaboration agent relative to other collaboration agents.
    (6) The amount of any distribution payments from a PGP must be 
determined either in a manner that complies with Sec.  411.352(g) of 
this chapter or in accordance with a methodology that is substantially 
based on contribution to performance across the achievement domain, 
efficiency domain and quality domain and the provision of IOTA 
activities and that may take into account the amount of such IOTA 
activities provided by a collaboration agent relative to other 
collaboration agents.
    (7) Except for a distribution payment from a PGP to a PGP member 
that complies with Sec.  411.352(g) of this chapter, a collaboration 
agent is eligible to receive a distribution payment only if the 
collaboration agent furnished or billed for an item or service rendered 
to an attributed patient that occurred during the same PY for which the 
IOTA participant earned the upside risk payment that comprises the 
gainsharing payment being distributed.
    (8) Except for a distribution payment from a PGP to a PGP member 
that complies with Sec.  411.352(g) of this chapter, the total amount 
of distribution payments for a PY paid to a collaboration agent must 
not exceed 50 percent of the total Medicare-approved amounts under the 
PFS for items and services billed by that PGP, NPPGP or TGP for items 
and services furnished by PGP members, NPPGP members or TGP members 
respectively to attributed patients that occurred during the same PY 
for which the IOTA participant earned the upside risk payment that 
comprises the gainsharing payment being distributed.
    (9) With respect to the distribution of any gainsharing payment 
received by a PGP, NPPGP, or TGP, the total amount of all distribution 
payments must not exceed the amount of the gainsharing payment received 
by the IOTA collaborator from the IOTA participant.
    (10) All distribution payments must be made by check, electronic 
funds transfer, or another traceable cash transaction.
    (11) The collaboration agent must retain the ability to make 
decisions in the best interests of the patient, including the selection 
of devices, supplies, and treatments.
    (12) The distribution arrangement must not--
    (i) Induce the collaboration agent to reduce or limit medically 
necessary items and services to any Medicare beneficiary; or
    (ii) Reward the provision of items and services that are medically 
unnecessary.
    (13) The IOTA collaborator must maintain contemporaneous 
documentation regarding distribution arrangements in accordance with 
Sec.  512.454, including the following:
    (i) The relevant written agreements.
    (ii) The date and amount of any distribution payment(s).
    (iii) The identity of each collaboration agent that received a 
distribution payment.
    (iv) A description of the methodology and accounting formula for 
determining the amount of any distribution payment.
    (14) The IOTA collaborator may not enter into a distribution 
arrangement with any collaboration agent that has a sharing arrangement 
with the same IOTA participant.
    (15) The IOTA collaborator must retain and provide access to, and 
must require collaboration agents to retain and provide access to, the 
required documentation in accordance with Sec.  512.460.


Sec.  512.455  Enforcement authority.

    (a) OIG authority. Nothing contained in the terms of the IOTA Model 
or this part limits or restricts the authority of the HHS Office of 
Inspector General, including its authority to audit, evaluate, 
investigate, or inspect the IOTA participant, IOTA collaborators, or 
any other person or entity or their records, data, or information, 
without limitation.
    (b) Other authority. Nothing contained in the terms of the IOTA 
Model or this part limits or restricts the authority of any government 
agency permitted by law to audit, evaluate, investigate, or inspect the 
participant hospital, CJR collaborators, or any other person or entity 
or their records, data, or information, without limitation.


Sec.  512.456  Beneficiary incentive: Part B and Part D 
immunosuppressive drug cost sharing support.

    (a) Cost sharing support for Part B and Part D immunosuppressive 
drugs. For immunosuppressive drugs covered under Medicare Part B or 
Medicare Part D and prescribed to an attributed patient, the IOTA 
participant may subsidize, in whole or in part, the cost sharing 
associated with the immunosuppressive drugs under Part B and Part D 
immunosuppressive drug cost sharing support defined at Sec.  512.402 if 
all of the following conditions are met:
    (1) The attributed patient is an eligible attributed patient as 
defined at Sec.  512.402.
    (2) The IOTA participant must provide a written policy in a form 
and manner specified by CMS for the provision of Part B and Part D 
immunosuppressive drug cost sharing support that is approved by CMS 
before the PY in which the cost sharing support is made available.
    (i) The IOTA participant must revalidate the written policy with 
CMS and in a form and manner specified by CMS for the provision of Part 
B and Part D immunosuppressive drug cost sharing support before its 
provision in a subsequent PY.
    (ii) The IOTA participant's initial written policy and the 
revalidation of the written policy must establish and justify the 
criteria that qualify an eligible attributed patient to receive Part B 
and Part D immunosuppressive drug cost sharing support.
    (iii) The IOTA participant's written policy and the revalidation of 
the written policy must include an attestation that the IOTA 
participant will not, in providing Part B and Part D immunosuppressive 
drug cost sharing support, take into consideration the type, cost, 
generic status, or manufacturer of the immunosuppressive drug(s) or 
limit an eligible attributed patients' choice of pharmacy.
    (b) Restrictions. (1) An IOTA participant must not take into 
consideration the type, cost, generic status, or manufacturer of the 
immunosuppressive drug(s) or limit an eligible attributed patients' 
choice of pharmacy when providing Part B and Part D immunosuppressive 
drug cost sharing support.
    (2) An IOTA participant may not receive financial or operational 
support for Part B and Part D immunosuppressive drug cost sharing 
support from pharmacies and pharmaceutical manufacturers.
    (c) Documentation. (1) An IOTA participant must maintain 
contemporaneous documentation that includes:
    (i) The identity of the eligible attributed patient to whom Part B 
and Part D immunosuppressive drug cost sharing support was provided;
    (ii) The date or dates on which Part B and Part D immunosuppressive 
drug cost sharing support was provided; and
    (iii) The amount or amounts of Part B and Part B immunosuppressive 
drug cost sharing support that was provided.

[[Page 43631]]

    (2) An IOTA participant must retain and make available records 
pertaining to Part B and Part D immunosuppressive drug cost sharing 
support to the Federal Government in accordance with Sec.  512.460.


Sec.  512.458  Attributed patient engagement incentives.

    (a) General. An IOTA participant may choose to provide any or all 
of the following types of attributed patient engagement incentives to 
an attributed patient under the conditions described in paragraph (b) 
of this section:
    (1) Communication devices and related communication services 
directly pertaining to communication with an IOTA participant or IOTA 
collaborator to improve communication between an attributed patient and 
an IOTA participant or IOTA collaborator.
    (2) Transportation to and from an IOTA participant and between 
other providers and suppliers involved in the provision of ESRD care.
    (3) Mental health services to address an attributed patient's 
behavioral health symptoms pre- and post-transplant.
    (4) In-home care to support the health of the attributed patient or 
the kidney transplant in the post-transplant period.
    (b) An IOTA participant may provide attributed patient engagement 
incentives of the type described in paragraph (a)(1) through (4) of 
this section when all of the following conditions are met:
    (1) An IOTA participant provides a written policy, in a form and 
manner specified by CMS, for the provision of attributed patient 
engagement incentives.
    (2) CMS approves an IOTA participants written policy before the 
first PY in which an attributed patient engagement incentive is first 
made available.
    (3) CMS revalidates the IOTA participant's written policy in a form 
and manner specified by CMS prior to each PY in which an attributed 
patient engagement incentive is offered subsequently.
    (4) The IOTA participant includes in its written policy:
    (i) A description of the items or services that will be provided as 
attributed patient engagement incentives.
    (ii) An explanation of how each item or service that will be an 
attributed patient engagement incentive has a reasonable connection to:
    (A) An attributed patient achieving and maintaining active status 
on a kidney transplant waitlist;
    (B) An attributed patient accessing the kidney transplant 
procedure; or
    (C) The health of the attributed patient or the kidney transplant 
in the post-transplant period
    (D) A justification for the need for the attributed patient 
engagement incentives that is specific to the IOTA participant's 
attributed patient population
    (iii) An attestation that items that are attributed patient 
engagement incentives will be provided directly to an attributed 
patient.
    (iv) An attestation that the IOTA participant will pay service 
providers directly for services that are attributed patient engagement 
incentives.
    (v) An attestation that any items or services acquired by the IOTA 
participant that will be furnished as attributed patient engagement 
incentives will acquired for the minimum amount necessary for an 
attributed patient to achieve the goals described in paragraph 
(b)(4)(ii) of this section.
    (c) Restrictions. (1) An IOTA participant must provide items that 
are attributed patient engagement incentives directly to an attributed 
patient.
    (2) An IOTA participant must pay service providers directly for any 
services that are offered as attributed patient engagement incentive.
    (3) An IOTA participant must not offer an attributed patient 
engagement incentive that is tied to the receipt of items or services 
from a particular provider or supplier.
    (4) An IOTA participant must not advertise or promote an item or 
service that is an attributed patient engagement incentive, except to 
make an attributed patient aware of the availability of the items or 
services at the time an attributed patient could reasonably benefit 
from them.
    (5) An IOTA participant may not receive donations directly or 
indirectly to purchase attributed patient engagement incentives.
    (6) An IOTA participant must retrieve items that that are 
attributed patient engagement incentives from the attributed patient 
when the attributed patient is no longer eligible for the that item or 
at the conclusion of the IOTA Model, whichever is earlier.
    (i) Documented, diligent, good faith attempts to retrieve items 
that are attributed patient engagement incentives are deemed to meet 
the retrieval requirement.
    (ii) [Reserved]
    (7) Items that are communication devices:
    (i) May not exceed $1000 in retail value for any one attributed 
patient in any one PY.
    (ii) Must remain the property of the IOTA participant;
    (iii) Must be retrieved from the attributed patient by the IOTA 
participant--
    (A) When the attributed patient is no longer eligible for the 
communication device or at the conclusion of the IOTA Model, whichever 
is earlier; and
    (B) Before another communication device may be made available to 
the same attributed patient.
    (d) Documentation. (1) The IOTA participant must maintain 
contemporaneous documentation of items and services furnished as 
attributed patient engagement incentives that includes, at minimum all 
of the following:
    (i) The date the attributed patient engagement incentive is 
provided.
    (ii) The identity of the attributed patient to whom the item or 
service was provided.
    (2) Retrieval documentation.
    (i) IOTA participants must document all retrieval attempts of items 
that are attributed patient engagement incentives, including the 
ultimate date of retrieval.
    (ii) [Reserved]
    (3) The IOTA participant must retain records pertaining to 
furnished attributed patient engagement incentives and make these 
records available to the Federal Government in accordance with Sec.  
512.460.


Sec.  512.459  Application of the CMS-sponsored model arrangements and 
patient incentives safe harbor.

    (a) Application of the CMS-sponsored Model Arrangements Safe 
Harbor. CMS has determined that the Federal anti-kickback statute safe 
harbor for CMS-sponsored model arrangements (Sec.  1001.952(ii)(1) of 
this chapter) is available to protect remuneration furnished in the 
IOTA Model in the form of Sharing Arrangement's gainsharing payments, 
Sharing Arrangement's alignment payments, and the Distribution 
Arrangement's distribution payments that meet all safe harbor 
requirements set forth in Sec.  1001.952(ii) this chapter, and 
Sec. Sec.  512.452 and 512.454.
    (b) Application of the CMS-sponsored Model Patient Incentives Safe 
Harbor. CMS has determined that the Federal anti-kickback statute safe 
harbor for CMS-sponsored model patient incentives (Sec.  
1001.952(ii)(2) of this chapter) is available to protect remuneration 
furnished in the IOTA model in the form of Part B and Part D 
immunosuppressive drug cost sharing support and the attributed patient 
engagement incentives that meet all safe

[[Page 43632]]

harbor requirements set forth in Sec.  1001.952(ii) of this chapter, 
and Sec. Sec.  512.456 and 512.458.


Sec.  512.460  Audit rights and records retention.

    (a) Right to audit. The Federal Government, including CMS, HHS, and 
the Comptroller General, or their designees, has the right to audit, 
inspect, investigate, and evaluate any documents and other evidence 
regarding implementation of the IOTA Model.
    (b) Access to records. The IOTA participant and its IOTA 
collaborators must maintain and give the Federal Government, including, 
but not limited to, CMS, HHS, and the Comptroller General, or their 
designees, access to all such documents (including books, contracts, 
and records) and other evidence sufficient to enable the audit, 
evaluation, inspection, or investigation of the implementation of the 
IOTA Model, including without limitation, documents, and other evidence 
regarding all of the following:
    (1) Compliance by the IOTA participant and its IOTA collaborators 
with the terms of the IOTA Model.
    (2) The accuracy of model-specific payments made under the IOTA 
Model.
    (3) The IOTA participant's downside risk payments owed to CMS under 
the IOTA Model.
    (4) Quality measure information and the quality of services 
performed under the terms of the IOTA Model.
    (5) Utilization of items and services furnished under the IOTA 
Model.
    (6) The ability of the IOTA participant to bear the risk of 
potential losses and to repay any losses to CMS, as applicable.
    (7) Contemporaneous documentation of cost sharing support furnished 
under Part B and Part D immunosuppressive drug cost sharing support 
that includes the following:
    (i) The identity of the eligible attributed patient to whom Part B 
and Part D immunosuppressive drug cost sharing support was provided.
    (ii) The date or dates on which Part B and Part D immunosuppressive 
drug cost sharing support was provided.
    (iii) The amount or amounts of the cost sharing support provided to 
the attributed patient.
    (8) Contemporaneous documentation of items and services furnished 
as attributed patient engagement incentives in accordance with Sec.  
512.458 that includes all of the following, at minimum:
    (i) The date the attributed patient engagement incentive is 
provided.
    (ii) The identity of the attributed patient to whom the item or 
service was provided.
    (9) Patient safety.
    (10) Any other program integrity issues.
    (c) Record retention. (1) The IOTA participant and its IOTA 
collaborators must maintain the documents and other evidence described 
in paragraph (b) of this section and other evidence for a period of 6 
years from the last payment determination for the IOTA participant 
under the IOTA Model or from the date of completion of any audit, 
evaluation, inspection, or investigation, whichever is later, unless--
    (i) CMS determines there is a special need to retain a particular 
record or group of records for a longer period and notifies the IOTA 
participant at least 30 days before the normal disposition date; or
    (ii) There has been a termination, dispute, or allegation of fraud 
or similar fault against the IOTA participant or its IOTA 
collaborators, in which case the records must be maintained for an 
additional 6 years from the date of any resulting final resolution of 
the termination, dispute, or allegation of fraud or similar fault.
    (2)(i) If CMS notifies the IOTA participant of the special need to 
retain a record or group of records in accordance with paragraph 
(c)(1)(i) of this section, the IOTA participant must maintain the 
records for such period of time as determined by CMS.
    (ii) If CMS notifies the IOTA participant of a special need to 
retain records in accordance with this paragraph (c)(1)(ii), the IOTA 
participant must notify its IOTA collaborators of this need to retain 
records for the additional period specified by CMS.


Sec.  512.462  Compliance and monitoring.

    (a) Compliance with laws. The IOTA participant must comply with all 
applicable laws and regulations.
    (b) CMS monitoring activities. (1) CMS, or its approved designee, 
may conduct monitoring activities to ensure compliance by the IOTA 
participant and IOTA collaborators with the terms of the IOTA Model 
under this subpart to--
    (i) Understand IOTA participants' use of model-specific payments; 
and
    (ii) Promote the safety of attributed patients and the integrity of 
the IOTA Model.
    (2) Monitoring activities may include, without limitation, all of 
the following:
    (i) Documentation requests sent to the IOTA participant and its 
IOTA collaborators, including surveys and questionnaires.
    (ii) Audits of claims data, quality measures, medical records, and 
other data from the IOTA participant and its IOTA collaborators.
    (iii) Interviews with the IOTA participant, including leadership 
personnel, medical staff, other associates, and its IOTA collaborators.
    (iv) Interviews with attributed patients and their caregivers.
    (v) Site visits to the IOTA participant and its IOTA collaborators, 
performed in a manner consistent with paragraph (c) of this section.
    (vi) Monitoring quality outcomes and attributed patient data.
    (vii) Tracking beneficiary complaints and appeals.
    (viii) Monitor the definition of and justification for the 
subpopulation of the IOTA participant's eligible attributed patients 
that may receive Part B and Part D Immunosuppressive Drug Cost Sharing 
Support in accordance with Sec.  512.456.
    (ix) Monitor the provision of attributed patient engagement 
incentives provided in accordance with Sec.  512.458.
    (x) Monitor out of sequence allocation of kidneys by--
    (A) Assessing the frequency at which IOTA waitlists patients, top-
ranked on an IOTA participant's kidney transplant waitlist, receive the 
organ that was initially offered to them; and
    (B) Determining the reasons behind cases where IOTA waitlist 
patients identified in paragraph (b)(x)(A) of this section, did not 
receive the kidney offered to them.
    (3) In conducting monitoring and oversight activities, CMS or its 
designees may use any relevant data or information including without 
limitation all Medicare claims submitted for items or services 
furnished to IOTA transplant patients or IOTA waitlist patients or 
both.
    (c) Site visits. (1) The IOTA participant must cooperate in 
periodic site visits performed by CMS or its designees in order to 
facilitate the evaluation of the IOTA Model in accordance with section 
1115A(b)(4) of the ACT and the monitoring of the IOTA participant's 
compliance with the terms of the IOTA Model, including this subpart.
    (2) When scheduling the site visit, CMS or its designee provides, 
to the extent practicable, the IOTA participant with no less than 15 
days advance notice of any site visit. CMS--
    (i) Attempts, to the extent practicable, to accommodate a request 
for particular dates in scheduling site visits; and
    (ii) Does not accept a date request from the IOTA participant that 
is more

[[Page 43633]]

than 60 days after the date of the initial site visit notice from CMS.
    (3) The IOTA participant must ensure that personnel with the 
appropriate responsibilities and knowledge associated with the purpose 
of the site visit are available during all site visits.
    (4) CMS may perform unannounced site visits at the office of the 
IOTA participant at any time to investigate concerns about the health 
or safety of attributed patients or other program integrity issues.
    (5) Nothing in this part may be construed to limit or otherwise 
prevent CMS from performing site visits permitted or required by 
applicable law.
    (d) Reopening of payment determinations. (1) CMS may reopen an IOTA 
Model-specific payment determination on its own motion or at the 
request of the IOTA participant, within 4 years from the date of the 
determination, for good cause (as defined at Sec.  512.462) except if 
there exists reliable evidence that the determination was procured by 
fraud or similar fault as defined in Sec.  512.464. In the case of 
fraud or similar fault, CMS may reopen an IOTA Model specific payment 
determination at any time.
    (2) CMS' decision regarding whether to reopen a model-specific 
payment determination is binding and not subject to appeal.


Sec.  512.464  Remedial action.

    (a) Grounds for remedial action. CMS may impose one or more 
remedial actions described in paragraph (b) of this section if CMS 
determines that:
    (1) The IOTA participant has failed to furnish 11 or more 
transplants during a PY or any baseline years.
    (2) The IOTA participant or its IOTA collaborator has failed to 
comply with any of the terms of the IOTA Model, including this subpart.
    (3) The IOTA participant has failed to comply with transparency 
requirements described at Sec.  512.442.
    (4) The IOTA participant or its IOTA collaborator has failed to 
comply with any applicable Medicare program requirement, rule, or 
regulation.
    (5) The IOTA participant or its IOTA collaborator has taken any 
action that threatens the health or safety of an attributed patient.
    (6) The IOTA participant or its IOTA collaborator has submitted 
false data or made false representations, warranties, or certifications 
in connection with any aspect of the IOTA Model.
    (7) The IOTA participant or its IOTA collaborator has undergone a 
Change in Control that presents a program integrity risk.
    (8) The IOTA participant or its IOTA collaborator is subject to any 
sanctions of an accrediting organization or a Federal, State, or local 
government agency.
    (9) The IOTA participant or its IOTA collaborator is subject to 
investigation or action by HHS (including the HHS Office of Inspector 
General or CMS) or the Department of Justice due to an allegation of 
fraud or significant misconduct, including any of the following:
    (i) Being subject to the filing of a complaint or filing of a 
criminal charge.
    (ii) Being subject to an indictment.
    (iii) Being named as a defendant in a False Claims Act qui tam 
matter in which the Federal Government has intervened, or similar 
action.
    (10) The IOTA participant or its IOTA collaborator has failed to 
demonstrate improved performance following any remedial action imposed 
under this section.
    (11) The IOTA participant has misused or disclosed beneficiary-
identifiable data in a manner that violates any applicable statutory or 
regulatory requirements or that is otherwise non-compliant with the 
provisions of the applicable data sharing agreement.
    (b) Remedial actions. If CMS determines that one or more grounds 
for remedial action described in paragraph (a) of this section has 
taken place, CMS may take one or more of the following remedial 
actions:
    (1) Notify the IOTA participant and, if appropriate, require the 
IOTA participant to notify its IOTA collaborators of the violation.
    (2) Require the IOTA participant to provide additional information 
to CMS or its designees.
    (3) Subject the IOTA participant to additional monitoring, 
auditing, or both.
    (4) Prohibit the IOTA participant from distributing model-specific 
payments, as applicable.
    (5) Require the IOTA participant to terminate, immediately or by a 
deadline specified by CMS, its sharing arrangement with an IOTA 
collaborator with respect to the IOTA Model.
    (6) Terminate the IOTA participant from the IOTA Model.
    (7) Suspend or terminate the ability of the IOTA participant to 
provide Part B and Part D immunosuppressive drug cost sharing support 
in accordance with Sec.  512.456 or attributed patient engagement 
incentives in accordance with Sec.  512.458.
    (8) Require the IOTA participant to submit a corrective action plan 
in a form and manner and by a deadline specified by CMS.
    (9) Discontinue the provision of data sharing and reports to the 
IOTA participant.
    (10) Recoup model-specific payments.
    (11) Reduce or eliminate a model-specific payment otherwise owed to 
the IOTA participant.
    (13) Any other action as may be permitted under the terms of this 
part.


Sec.  512.466  Termination.

    (a) Termination of IOTA participant from the IOTA Model by CMS. CMS 
may immediately or with advance notice terminate an IOTA participant 
from participation in the model if CMS does any of the following:
    (1) Determines that it no longer has the funds to support the IOTA 
Model.
    (2) Modifies or terminates the IOTA Model in accordance with 
section 1115A(b)(3)(B) of the Act.
    (3) Determines that the IOTA participant--
    (i) Has failed to comply with any model requirements or any other 
Medicare program requirement, rule, or regulation;
    (ii) Has failed to comply with a monitoring or auditing plan or 
both;
    (iii) Has failed to submit, obtain approval for, implement or fully 
comply with the terms of a CAP;
    (iv) Has failed to demonstrate improved performance following any 
remedial action;
    (v) Has taken any action that threatens the health or safety of a 
Medicare beneficiary or other patient;
    (vi) Has submitted false data or made false representations, 
warranties, or certifications in connection with any aspect of the IOTA 
Model;
    (vii) Assigns or purports to assign any of the rights or 
obligations under the IOTA Model, voluntarily or involuntarily, whether 
by merger, consolidation, dissolution, operation of law, or any other 
manner, without the written consent of CMS;
    (viii) Poses significant program integrity risks, including but not 
limited to--
    (A) Is subject to sanctions or other actions of an accrediting 
organization or a Federal, State, or local government agency; or
    (B) Is subject to investigation or action by HHS (including OIG and 
CMS) or the Department of Justice due to an allegation of fraud or 
significant misconduct, including being subject to the filing of a 
complaint, filing of a criminal charge, being subject to an indictment, 
being named as a defendant in a False Claims Act qui tam matter in 
which the government has intervened, or similar action.
    (b) Termination of Model participation by IOTA participant. The 
IOTA participant may not terminate their participation in the IOTA 
Model.

[[Page 43634]]

    (c) Financial settlement upon termination. If CMS terminates the 
IOTA participant's participation in the IOTA Model, CMS calculates the 
final performance score and any upside risk payment or downside risk 
payment, if applicable, for the entire PY in which the IOTA 
participant's participation in the model was terminated.
    (1) If CMS terminates the IOTA participant's participation in the 
IOTA Model, CMS determines the IOTA participant's effective date of 
termination.
    (2) If CMS terminates the IOTA participant for any reasons listed 
under Sec.  512.466:
    (i) CMS does not make any payments of upside risk payment for the 
PY in which the IOTA participant was terminated; and
    (ii) The IOTA participant will remain liable for payment of any 
downside risk payment up to and including the PY in which termination 
becomes effective.
    (d) Termination of the IOTA Model by CMS. (1) The general 
provisions for the Innovation Center model termination by CMS listed 
under Sec.  512.165 will apply to the IOTA Model.
    (i) CMS may terminate the IOTA Model for reasons including, but not 
limited to, those set forth in Sec.  512.165(a).
    (ii) If CMS terminates the IOTA Model, CMS provides written notice 
to IOTA participants specifying the grounds for model termination and 
the effective date of such termination.
    (2) In accordance with section 1115A(d)(2) of the Act and Sec.  
512.170(e), termination of the IOTA Model under section 1115A(b)(3)(B) 
of the Act is subject to administrative or judicial review.
    (3) If CMS terminates the IOTA Model, the financial settlement 
terms described in paragraph (c) of this section applies.


Sec.  512.468  Bankruptcy and other notifications.

    (a) Notice of bankruptcy. (1) If the IOTA participant has filed a 
bankruptcy petition, whether voluntary or involuntary, the IOTA 
participant must provide written notice of the bankruptcy to CMS and to 
the U.S. Attorney's Office in the district where the bankruptcy was 
filed, unless final payment has been made by either CMS or the IOTA 
participant under the terms of each model tested under section 1115A of 
the Act in which the IOTA participant is participating or has 
participated and all administrative or judicial review proceedings 
relating to any payments under such models have been fully and finally 
resolved.
    (2) The notice of bankruptcy must meet all of the following:
    (i) Be sent by certified mail no later than 5 days after the 
petition has been filed.
    (ii) Contain--
    (A) A copy of the filed bankruptcy petition (including its docket 
number); and
    (B) A list of all models tested under section 1115A of the Act in 
which the IOTA participant is participating or has participated.
    (b) Change in control. (1) The IOTA participant must provide 
written notice to CMS at least 90 days before the effective date of any 
change in control.
    (2) CMS may terminate an IOTA participant from the IOTA Model if 
the IOTA participant undergoes a change in control.
    (c) Prohibition on assignment. (1) Unless CMS provides prior 
written consent, an IOTA participant must not transfer, including by 
merger (whether the IOTA participant is the surviving or disappearing 
entity), consolidation, dissolution, or otherwise any--
    (i) Discretion granted it under the model;
    (ii) Right that it has to satisfy a condition under the model;
    (iii) Remedy that it has under the model; or
    (iv) Obligation imposed on it under the model.
    (2) The IOTA participant must provide CMS 90 days advance written 
notice of any such proposed transfer.
    (3) This obligation remains in effect after the expiration or 
termination of the model, or the IOTA participant's participation in 
the model, and until final payment by the IOTA participant under the 
model has been made.
    (4) CMS may condition its consent to such transfer on full or 
partial reconciliation of upside risk payments and downside risk 
payments.
    (5) Any purported transfer in violation of this requirement is 
voidable at the discretion of CMS.

Waivers


Sec.  512.470  Waivers.

    CMS waives the requirements of sections 1881(b), 1833(a) and (b) of 
the Act only to the extent necessary to make the payments under the 
IOTA Model described in this subpart.

Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2024-09989 Filed 5-8-24; 4:15 pm]
BILLING CODE 4120-01-P