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jbell on DSKJLSW7X2PROD with PROPOSALS2

Federal Register / Vol. 86, No. 129 / Friday, July 9, 2021 / Proposed Rules behavior for each year was simulated by adjusting the ETC Participants baseline home dialysis or transplant rate for a simulated statistical fluctuation and then summing with the assumed increase in home dialysis or transplant rate multiplied by a randomly generated improvement scalar. The achievement and improvement scores were assigned by comparing the ETC Participants simulated home dialysis or transplant rate for the MY to the percentile distribution of home dialysis or transplant rates in the prior year. Last, the MPS was calculated using the weighted sum of the higher of the achievement or improvement score for the home dialysis rate and the transplant waitlist rate. The home dialysis rate constituted two-thirds of the MPS, and the transplant rate onethird of the MPS.
For MY3 through MY10, the home dialysis rate calculation accounts for modifications proposed in this proposed rule. For Managing Clinicians, the proposed revisions include changing the numerator for the home dialysis rate from the home dialysis beneficiary months to the home dialysis beneficiary months + 0.5in-center self-dialysis beneficiary months + 0.5nocturnal incenter dialysis beneficiary months, such that 1-beneficiary year is comprised of 12-beneficiary months.
The proposed revision for the numerator of the home dialysis rate for ESRD
facilities varied if the facility was owned in whole or in part by an ETC
LDO, as identified by ownership information for the associated CCN. If the CCN had facilities owned by an ETC
LDO, then the proposed numerator for the home dialysis rate was the home dialysis beneficiary months + 0.5incenter self-dialysis beneficiary months;
therefore, not including nocturnal incenter dialysis months from the numerator. Otherwise, if the CCN did not have facilities owned by an ETC
LDO, then the numerator was the same as described above for Managing Clinicians, such that the numerator for the home dialysis rate was home dialysis beneficiary months + 0.5incenter self-dialysis beneficiary months + 0.5nocturnal in-center dialysis beneficiary months.
The number of beneficiaries on incenter self-dialysis who met the eligibility criteria for the ETC Model was very small, ranging from 102 to 277
over the period 20122019 and decreasing 89.9 percent to 22
beneficiaries in 2020 based on preliminary 2020 data at CMS. With such a small sample size, the growth rate vacillated significantly. In addition, the in-center nocturnal dialysis UJ

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modifier code did not become effective until January 1, 2017; therefore, there were insufficient data to generate growth rate assumptions. The in-center nocturnal dialysis beneficiary growth rate decreased by 91.3 percent in 2020.
As a solution to these data limitations, to simulate the impact of incorporating in-center self-dialysis and in-center nocturnal dialysis for the purpose of the savings to Medicare estimate, the simulation assumed any given ESRD
facility or Managing Clinician would have a one percent chance of receiving an increased achievement score due to this policy proposal.
The overall process for generating achievement and improvement scoring followed modeling from section VI.C.2
of the Specialty Care Models final rule 85 FR 61352, with the exception of the following changes.
Beginning for MY3 and beyond, the achievement benchmarking methodology had two proposed modifications. First, the home dialysis rate and transplant waitlist rate benchmarks were increased by a total of 10 percent relative to ESRD facilities and Managing Clinicians not selected for participation, every two MYs. To clarify, no changes to the achievement benchmarking methodology were made to MYs 1 and 2. The latter MY couplets achievement benchmarking included the following preset benchmark updates:
MYs 3 and 4: Comparison Geographic Area percentiles1.10, MYs 5 and 6: Comparison Geographic Area percentiles1.20, MYs 7 and 8: Comparison Geographic Area percentiles1.30, and MYs 9 and 10: Comparison Geographic Area percentiles1.40.
The percentiles represented the 30th, 50th, 75th, and 90th percentile of the home dialysis rate and transplant rate for ESRD facilities and Managing Clinicians not selected for participation.
The preset benchmark updates method provides greater certainty to ETC
Participants than the rolling updates in section IV.C.2.b3 of the Specialty Care Models final rule 85 FR 61353, which would have involved updating benchmarks based on emerging trends over the most recent experience periods for which data were available.
Second, in this proposed rule, we proposed to incorporate two proxies for socioeconomic status, dual eligibility status or receipt of the Low Income Subsidy LIS, as part of the achievement benchmarking starting for MY3 and beyond. Dual eligibility status was defined as a Medicare beneficiary with any of the following full-time dual type codes: 02=Eligible is entitled to
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Medicare Qualified Medicare Beneficiary QMB and Medicaid coverage including prescription drugs, 04=Eligible is entitled to Medicare Specified Low-Income Medicare Beneficiary SLMB and Medicaid coverage including prescription drugs, or 08=Eligible is entitled to Medicare Other dual eligible with Medicaid coverage including prescription drugs.
Separately, a yes/no indicator was created for any beneficiary that was either deemed or determined by the Social Security Administration SSA to be receiving the LIS. The home dialysis rate and transplant waitlist rate achievement benchmarks were then stratified by the proportion of attributed beneficiaries who are dual-eligible or receive the LIS. Two strata were created with a cutpoint of approximately 50
percent for participants with any dualeligible or LIS recipient beneficiaries and those who do not have beneficiaries meeting the socioeconomic status proxies.
Third, a Health Equity Incentive was proposed for improvement scoring starting in MY3. For the purpose of the estimates in this Regulatory Impact Analysis, we incorporated a random variable to simulate each ETC
Participants baseline variation and behavioral improvement for each MY. If the participants simulated improvement behavior in MY3 through MY10 was greater than 5 percent, then the participant received a 0.5 point increase on their improvement score, allowing for a maximum of 2.0 total points.
For all MYs, the transplant waitlist benchmarks were annually inflated by approximately 3-percentage points growth. This was a modification from section VI.C.2 of the Specialty Care Models final rule 85 FR 61352, where the waitlist benchmarks were annually inflated by approximately 2-percentage points growth observed during years 2017 through 2019 in the CCSQ data, to project rates of growth. The additional 1 percentage point growth in this proposed rule was included to account for uncertainty from the COVID19 PHE
disruption and section 17006 of the 21st Century Cures Act Cures Act Pub. L.
114255, which amended the Act to increase enrollment options for individuals with ESRD into Medicare Advantage. To clarify, applying the 3percentage point annual growth from the median transplant waitlist rate across HRR condensed facilities grew from 8 percent in 2017 to 11 percent in 2018 to 14 percent in 2019 that is, not a growth rate of 1.03 percent per year.
To assess the impact of the COVID
19 PHE on the kidney transplant
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