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MedPAC's comments on the proposed ESRD Treatment Choices Model

by MedPAC Staff | Oct 22, 2020

In July 2019, the Centers for Medicare & Medicaid Services proposed a mandatory End-Stage Renal Disease (ESRD) Treatment Choices (ETC) Model that aimed to increase the use of home dialysis by beneficiaries with ESRD, and increase kidney transplantation among adult ESRD beneficiaries (“Medicare Program: Specialty Care Models to Improve Quality of Care and Reduce Expenditures,” Federal Register, vol. 84, no.138, pp. 34478-34595 (July 18, 2019)).  In the fall of 2019, the Commission submitted comments on the this proposed rule. In the interest of making our comments more broadly available, we are reprinting them here.

CMS finalized the ESRD Treatment Choices Model with modifications on September 18, 2020.

Proposed ESRD Treatment Choices Model

CMS is seeking comments on its proposal to implement a mandatory payment model—the End-Stage Renal Disease (ESRD) Treatment Choices (ETC) Model—through the Center for Medicare & Medicaid Innovation. The ETC Model, which would begin January 1, 2020, and end June 30, 2026, would test whether financial incentives result in increasing home dialysis use and kidney transplantation among adult ESRD beneficiaries. The model would adjust certain Medicare payments to ESRD facilities and managing clinicians (who receive a monthly capitated payment (MCP) established in the Part B physician fee schedule for outpatient dialysis–related management services) that are required to participate in the model, through upward or downward payment adjustments based on their home dialysis and kidney transplant rates.

CMS would select participants—ESRD facilities and managing clinicians—for the model according to their location in geographic areas (306 hospital referral regions) that would be randomly selected, stratified by region, so as to account for approximately 50 percent of adult ESRD beneficiaries in all 50 states and the District of Columbia. CMS would apply the following two payment adjustments to the base payment rate of providers (ESRD facilities and managing clinicians) required to participate in the ETC Model:

  • The home dialysis payment adjustment (HDPA) would increase the managing clinician’s MCP rate for home dialysis patients and the ESRD facility’s base rate for home dialysis treatments under the ESRD prospective payment system (PPS) by 3 percent in 2020, 2 percent in 2021, and 1 percent in 2022.

  • The performance payment adjustment (PPA) would apply to payments for all dialysis treatments beginning June 30, 2021; could be either positive or negative for a participant but would be net negative across all participants (asymmetric); and would be applied to each participant’s base payment rate. The PPA would be determined by comparing each participant’s rate of home dialysis and kidney transplant to a benchmark (calculated based on the rates of a control group of home dialysis and kidney transplantation of ESRD facilities and managing clinicians not included in the ETC). For managing clinicians only, the rate of kidney transplant would include both dialysis beneficiaries who receive a transplant as well as beneficiaries with advanced chronic kidney disease (CKD) (and not yet on dialysis) who receive a transplant.

Dialysis facilities and managing clinicians not selected as participants in the ETC would continue to be paid under the ESRD PPS and Part B physician fee schedule, respectively; Medicare would not adjust their payments using the HDPA or the PPA.

The PPA proposed by CMS would be based on home dialysis and kidney transplantation rates. CMS proposes to measure the home dialysis rate at the facility and managing clinician level, with the denominator defined as attributed beneficiary years of total dialysis treatments and the numerator defined as attributed beneficiary years of home dialysis treatments. Beneficiaries would be attributed on a monthly basis to the facility that submitted the most dialysis treatment claims for a beneficiary, and to the managing clinician that submitted the claim for a beneficiary’s monthly dialysis management. CMS proposes to use CMS hierarchical condition category (CMS–HCC) risk scores to account for differences in the propensity to use home dialysis among dialysis beneficiaries. In the first two measurement years, home dialysis rates for facilities and clinicians would be scored from 0 to 2 points in 0.5-point increments based on comparison with a control group where the 30th, 50th, 75th, and 90th percentile values from the control group distribution would define home dialysis rate ranges for each score.[1]

Achievement score scale for home dialysis and transplant rates

Points

Participant rate ≥ 90th percentile rate in comparison group

2

90th > Participant rate ≥ 75th percentile rate in comparison group

1.5

75th > Participant rate ≥ 50th percentile rate in comparison group

1.0

50th > Participant rate ≥ 30th percentile rate in comparison group

0.5

30th percentile rate in comparison group > Participant rate

0

 
Note: Proposed scores would be used for measurement years 1 and 2. We interpret Table 13 to be based on mutually exclusive achievement score categories.

Source: CMS proposed rule 2019, Table 13.

CMS proposes to measure the transplant rate at the facility level, with the denominator defined as attributed beneficiary years of total dialysis treatments and the numerator defined as attributed beneficiaries who received a transplant during the measurement year. The transplant rate would also be measured at the managing clinician level but would also include beneficiaries receiving a preemptive (before beginning dialysis) transplant to the numerator and the addition of dialysis treatment years for those beneficiaries to the denominator. The beneficiary attribution and scoring method would be the same as the home dialysis rate measure; however, to account for differences in the likelihood of receiving a transplant, CMS proposes to use the age categories and corresponding risk coefficients based on the percentage of patients at each dialysis facility who were on the kidney or kidney-pancreas transplant waitlist, a measure that will be included in the ESRD quality improvement program for facilities beginning in payment year 2022.[2]

CMS would randomly assign the 306 hospital referral regions (HRRs) in the United States into treatment (participating in the ETC Model) and control groups.[3] CMS believes that random assignment of HRRs to treatment and control group will account for relevant differences in the measurement.

The PPA will have the largest effect on program spending of any ETC Model component. Over the course of the model, CMS estimates that:

  • the PPA will reduce Medicare payments to facilities by $220 million and to managing clinicians by $8 million; and

  • the HDPA will increase Medicare payments to facilities by $39 million and to managing clinicians by $4 million.

Overall, there is net negative effect from the PPA and HDPA adjustments; Medicare spending to dialysis facilities and managing clinicians in the mandatory ETC Model will be reduced by $185 million over the 6.5-year model.

Comment

The Commission applauds the agency’s commitment to increasing use of kidney transplantation and home dialysis among ESRD beneficiaries. Kidney transplantation is widely regarded as a better ESRD treatment option than dialysis in terms of patients’ clinical and quality-of-life outcomes. Compared with in-center dialysis, home-based dialysis offers ESRD patients greater autonomy, fewer transportation challenges, improved quality of life, and enhanced satisfaction.

However, we have significant methodological concerns such that we believe CMS should not implement the proposed ETC Model. We believe the proposed measurement of home dialysis and kidney transplantation rates in the PPA adjustment lack sufficient validity to serve as the basis for the payment incentives. For both the home dialysis and transplant measures, we have specific concerns about the reliability of the measurement; the comparison-to-control-group benchmarks and scoring method; the risk-adjustment method; and, in certain instances, the alignment of incentives for participants.

The Commission believes that CMS should instead implement an approach similar to CMMI’s Comprehensive End-Stage Renal Disease Care (CEC) Model that could: (1) provide a holistic approach to the care of beneficiaries with CKD, who often have multiple comorbidities in addition to kidney disease; and (2) hold both dialysis facilities and managing clinicians jointly accountable for the outcomes (quality, utilization, and financial) of beneficiaries with CKD, including rates of home dialysis and transplantation. Kidney transplant centers, a key participant in the transplant process, should also be considered to participate in such a model.

Concerns with home dialysis measurement

  • Home dialysis rates are not uniform geographically, and we are concerned that random assignment of HRRs would not generate equal distributions of home dialysis rates among the participants in each group. In this proposed rule, CMS has not explained whether it would check that the distributions of home dialysis rates in treatment and control HRRs are equivalent after randomization, nor has it described a remedy if it discovered nonequivalent home dialysis distributions in the treatment and control groups.

  • The ETC Model may provide mid-sized and large dialysis providers conflicting incentives that undermine the goal of increasing the national home dialysis rate. Mid-sized and large dialysis organizations will likely operate facilities that will be assigned to the treatment group in some HRRs and the control group in other HRRs. The design of the model (i.e., the set of financial incentives) would potentially put these providers in the awkward position of maintaining a status quo level of effort in control HRRs while exerting additional effort to increase home dialysis rates in treatment HRRs. The diverging incentives of treatment and control HRRs could affect organizational decisions such as the opening or closing facilities, the location of home dialysis programs, and a myriad of other decisions about the allocation of organizational resources. Furthermore, the model’s incentives may unintentionally result in these organizations waiting until the model terminates to implement best practices organization-wide. Although CMS states its intent to increase treatment group benchmarks in each year, the model incentives do not guarantee that the status quo will be maintained in the control HRRs. CMS does not address the possibility that home dialysis rates may decrease in control HRRs if resources are shifted by dialysis organizations to treatment HRRs. Such a decline in home dialysis rates in the control group would affect the benchmark rates for scoring and could result in CMS rewarding participants in treatment HRRs for maintaining the status quo. These concerns also apply to transplant rate measurement.

  • CMS’s proposed scoring method does not reflect the distribution of home dialysis rates at facilities. CMS did not provide information about the distribution of home dialysis rates across facilities, but our analysis of 2017 cost reports submitted to CMS by freestanding dialysis facilities shows that roughly 50 percent of freestanding facilities furnished any home dialysis treatments. CMS’s proposal to score facilities based on home dialysis rates at the 30th, 50th, 75th and 90th percentile is not operational as there would be no differentiation among the lower three groups (scoring 0, 0.5, or 1 point) because the 30th and 50th percentile rates would be both 0 percent. Furthermore, CMS should publish information about the distribution of home dialysis rates across facilities and, consistent with the Commissions principles for measuring quality in the Medicare program, establish pre-determined targets for scoring measures.[4]

  • Given that home dialysis is used by approximately 11 percent of dialysis patients, some organizations strategically centralize their home dialysis program in one facility in a region to allow the nursing staff and the arrangement of the facility to specialize in the skills and knowledge that are unique to the training and management of home dialysis. Our analysis of 2017 freestanding cost reports showed that about 6 percent of freestanding facilities (approximately 400 facilities) furnished only home treatments and did not furnish any in-center treatments.

    Measuring the home dialysis rate at the facility level does not align with this approach to providing home dialysis through centralized facilities. In the ETC Model, not only would home dialysis–only facilities have a home dialysis rate of 100 percent, but other local facilities operated by the same organization are likely to have a 0 percent home dialysis rate, as patients interested in home dialysis are referred to the home dialysis–only facility in the region. It is likely that the centralization strategy also exists in a less distinct form in other regions, where organizations may not have a home dialysis–only facility, but limit the facilities in a region that offer home dialysis as part of a specialization strategy.

  • CMS–HCC risk scores are not highly correlated with the propensity to use home dialysis among beneficiaries and should not be used to risk adjust the home dialysis measure. Risk scores are a standardized unit of expected spending that use demographic characteristics and diagnoses from the prior year to estimate expected Medicare spending the next year. Although total Medicare spending is sometimes used as a proxy for relative health status, risk scores are not a good proxy for propensity to use home dialysis as they do not correlate with many of the factors identified in literature as indicative of increased home dialysis use.[5] Risk-score coefficients are not calibrated based on propensity to use home dialysis; they are calibrated for Medicare spending. For example, a beneficiary with a risk score of 2.0 is expected to have spending twice that of a beneficiary with risk score of 1.0, but the beneficiary with 2.0 risk score is not expected to be half as likely to use home dialysis (assuming an inverse relationship between risk score and home dialysis propensity) compared with the beneficiary with a risk score of 1.0. Furthermore, CMS notes that the appropriate risk scores for application in the measurement year would not be available and proposes to apply risk scores estimated for use in the prior year instead. Using prior year risk scores further diminishes any relationship between the risk scores and propensity to use home dialysis.

  • CMS has not explicitly addressed the effect of the current shortage of peritoneal dialysis solutions on measuring home dialysis rates. According to the Food and Drug Administration, peritoneal dialysis solutions are currently in shortage. The supply shortage resulted from the product’s leading manufacturer experiencing increased PD demand and limited manufacturing capacity.[6] Because of the shortage, beginning in August 2014, the manufacturer gave each dialysis provider an allocation for how many new patients could be started on peritoneal dialysis based on the provider’s history of growth during the first six months of 2014.[7] The shortage might affect a given facility’s use of home dialysis.[8] Although the agency states that it “would be examining the extent of any unintended consequences, including…fluctuations in machine and supplies markets...”, it does not explicitly address how it would determine whether the shortage is affecting a given provider’s use of home dialysis and the potential effect of such a shortage on the stability of home dialysis rates. For example, the model might create an incentive to divert supplies in shortage to the treatment HRRs.

  • We are concerned that the ETC does not formally measure beneficiary experience. According to CMS, it considered including the in-center hemodialysis CAHPS survey to monitor beneficiary perceptions of changes in quality of care as a result of the ETC Model but did not do so because this survey does not include home dialysis beneficiaries. The agency states that in its monitoring activities, it may include interviews with beneficiaries and their caregivers. Given the ETC Model’s potential effect on beneficiaries’ care, we urge CMS to implement a more formal approach to assess beneficiaries’ experiences, such as developing a home dialysis CAHPS instrument. (The agency is using CAHPS instruments to measure beneficiary experience in the proposed radiation model.) Assessing patient experience is a key component in the Commission’s principles for measuring quality.[9] These concerns also apply to monitoring the experience of beneficiaries undergoing a transplant.

    Concerns with transplant rate measurement

  • Measuring the transplant rate at the facility level is not likely to produce reliable estimates and may not allow for an operational scoring method for the ETC. CMS did not provide any information about the distribution of facility-level transplant rates, but we are skeptical that the measure is sensitive to a facility’s effort to increase transplant rates. CMS should provide transplant rates by facility (and managing clinician), including numerator and denominator values. Our analyses show that about 10,100 transplants were provided to Medicare beneficiaries in 2017. Dividing these transplants across 7,097 eligible dialysis facilities shows an average transplant rate of less than 1.5 transplants per facility. Given that Medicare dialysis patients are somewhat concentrated in larger facilities (about 64 percent of dialysis treatments were provided in the largest 40 percent of facilities),[10] we think most facilities would have 0 or 1 transplants among their attributed population. Given the lack of variation in the numerator, we note that (1) a single transplant carries significant weight on the transplant rate for any facility, yet the likelihood of transplantation is affected by a multitude of factors outside of a facility’s control,[11] and (2) differences in the transplant rate would mostly be driven by the denominator (i.e., the ETC would estimate 1 transplant out of 20 attributed patients [1/20 = 0.05] to be twice as good as 1 transplant out of 40 attributed patients [1/40 = 0.025]). Because of these factors, we do not believe facility transplant rates provide a robust basis for evaluating a facility’s efforts to increase the number of transplants. The transplant rate calculated for individual facilities would capture mostly noise rather than signal.

  • Similarly, measuring the transplant rate at the managing clinician level is also not likely to produce robust estimates. For managing clinicians, more transplants would be attributed to participants, as the ETC Model would attribute both transplants for Medicare beneficiaries (10,100 in 2017) and preemptive transplants (i.e., transplants that occur before the beneficiary requires dialysis) to managing clinicians. However, with about 20,000 kidney transplants provided in the U.S. in 2016 (not all of which would be attributed to managing clinicians participating in the model) and 7,283 eligible managing clinicians, the distribution of transplants per managing clinician would be similar to the facility-level measure.

CMS should use a broader approach to care for beneficiaries with advanced CKD

Overall, the Commission believes that the ETC Model, while laudable in its goal of increasing home dialysis use and kidney transplantation among ESRD beneficiaries, is too narrowly focused and does not promote holistic care for the multiple chronic and acute conditions that ESRD beneficiaries face. The Commission believes that CMS should implement a broader approach under a shared savings program, which would hold both dialysis facilities and managing clinicians jointly accountable for all the care furnished to their patients with advanced CKD. We have previously said that a shared savings program for dialysis facilities and managing clinicians, if structured properly, could present an opportunity to transform the FFS delivery system, improve care management and coordination, and reward providers who are doing their part to control costs and improve quality. By contrast, the narrow scope of the proposed ETC Model—focusing on increasing only home dialysis use and kidney transplantation—does not address some of the undesirable incentives inherent in FFS payment (such as the lack of collaboration among health care providers to coordinate a patient’s care.)

A broader approach under a shared savings program that would hold both dialysis facilities and managing clinicians accountable for all the care furnished to their patients with advanced CKD could incentivize home dialysis use and kidney transplantation by:

  • holding providers accountable for the service utilization, financial, and quality outcomes of beneficiaries following kidney transplantation;

  • holding providers accountable for the service utilization, financial, and quality outcomes of beneficiaries with advanced chronic kidney disease (e.g., CKD stage 3B and CKD stage 4); and/or

  • paying a bonus (e.g., through shared Medicare savings) for beneficiaries who are successfully maintained on home dialysis and kidney transplant.

The results of the CMMI’s CEC Model should inform CMS’s efforts to improve care of ESRD beneficiaries. Under the CEC Model, ESRD Seamless Care Organizations—which are accountable care organization–like entities specific to the dialysis population that consist of at least one dialysis facility and one nephrologist—are held accountable for the clinical and financial (Part A and Part B) outcomes of prospectively matched dialysis beneficiaries. The CEC Model does not include beneficiaries with advanced CKD and beneficiaries who received a kidney transplant.

The first performance year (2015–2016) of the CEC Model showed promising results, with lower total spending and improvements in utilization and quality of care. For example, the CEC Model significantly reduced total Part A and Part B spending, rates of hospitalization and office visits, and ESRD complications (e.g., volume depletion, hyperpotassemia, fluid overload, heart failure, and pulmonary edema).[12] During the first performance year, the CEC Model did not significantly change (increase or decrease) rates of home dialysis or kidney transplantation. CMS has not yet released the performance results of the CEC Model for performance years two (2017) and three (2018). The Commission has long supported two-sided risk ACOs with prospective assignment, such as the CEC, because they provide stronger incentives for providers, protect the Medicare trust funds, and make it possible to provide regulatory relief—and thus allow for more innovative care delivery models.

Under a broader model, CMS should consider including transplant centers, a key Medicare provider not included in the ETC. While ESRD facilities and managing clinicians together are responsible for educating beneficiaries about their renal management choices and referring beneficiaries for transplantation, transplant centers are responsible for determining which patients are placed on the kidney wait list and which organs are transplanted.[13] In the proposed rule, CMS acknowledges that, compared to improvements in home dialysis use, ETC participants may have more difficulty in improving rates of kidney transplantation due to the limited supply of organs and the number of other providers and suppliers that are part of the transplant process but are not included as participants in the ETC Model. A broader model that includes organ transplant hospitals would better align incentives to promote increased rates of transplantation, reduce rates of organ discard, promote living donation, and promote preemptive transplantation.[14]

CMS has also released two other kidney models—the Kidney Care First (KCF) Model and Comprehensive Kidney Care Contracting (CKCC) Models—that are broader than the ETC Model in that they include beneficiaries with advanced CKD and beneficiaries who have received a kidney transplant, as well as dialysis beneficiaries (similar to the Commission’s approach suggested above). Unlike the ETC, both models are voluntary. The KCF Model (with one-sided payment risk) requires the participation of nephrologists or nephrology practices while the CKCC Models (with either one-sided or two-sided payment risk) require that nephrologists or nephrology practices and transplant providers participate. Notably, the potential effectiveness of these models is limited by not requiring the participation of dialysis facilities, who are, together with managing clinicians, partners in caring for all ESRD beneficiaries on dialysis and (for some dialysis facilities) beneficiaries with advanced CKD.

Finally, CMS could consider implementing a nationwide quality improvement initiative, a complementary strategy that would focus on increasing rates of home dialysis and kidney transplantation by prioritizing proactive education nationwide among all Medicare beneficiaries with advanced CKD and kidney providers. Such an initiative has the potential to improve care among FFS beneficiaries as well as those enrolled in Medicare Advantage. In 2004, the agency implemented “Fistula First,” a quality improvement project conducted by all 18 ESRD networks that collaborated with major stakeholders, including dialysis providers, primary care physicians, nephrologists, vascular access surgeons, interventional radiologists/nephrologists, professional societies, and patient advocacy groups, to promote the use of arteriovenous fistulas in all suitable hemodialysis patients.[15] This initiative has contributed to the increasing use of AV fistulas in hemodialysis patients between 2004 and 2017.[16]

In summary, we find that although the ETC Model’s goals of improving rates of kidney transplantation and home dialysis are commendable, CMS should instead implement a broader approach using the ESCO as a model that would hold both dialysis facilities and managing clinicians accountable for all care furnished to beneficiaries with advanced CKD.

 


[1] CMS proposed that home dialysis scores be weighted double the value of transplant rate scores because participants have less of an influence on transplant rates than home dialysis use.

[2] CMS defines the percentage of prevalent patients waitlisted (“PPPW”) measure as the percentage of patients at each dialysis facility who were on the kidney or kidney-pancreas transplant waitlist averaged across patients prevalent on the last day of each month during the performance period (https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/ESRDQIP/Downloads/PY-2022-Technical-Specifications-.pdf). This measure includes patients under the age of 75 and excludes certain patients admitted to a skilled nursing facility or hospice.

[3] Hospital referral regions were developed by the Dartmouth Atlas project. Because of Maryland’s unique payment structure, CMS proposes to assign most HRRs that include Maryland to the treatment group.

[4] Medicare Payment Advisory Commission. 2016. Report to the Congress: Medicare and the health care delivery system. Washington, DC: MedPAC.

[5] Factors affecting use of home dialysis include: clinical factors (e.g., patients’ other health problems and prior nephrology care) and nonclinical factors (e.g., patients’ social circumstances, nephrologist’s training and preference, dialysis facility’s staff experience). In addition, since 2014, manufacturers have not produced enough dialysate, the solution used in peritoneal dialysis, to meet demand, which has limited recent growth in the use of peritoneal dialysis (http://medpac.gov/docs/default-source/reports/mar18_medpac_ch6_sec.pdf?sfvrsn=0).

[6] Baxter. 2014. Letter from Richard Marritt, Region Head and General Manager, US and Canada. July 28.

[7] Seaborg, E. 2015. Peritoneal dialysis fluid shortage disrupted growth of popular therapy. Kidney News, March.

[8] Beginning in 2014, this shortage may have affected the growth in home dialysis among Medicare beneficiaries. Between 2014 and 2017, the total number of home dialysis beneficiaries increased by 3 percent per year; by contrast, between 2012 and 2014, the total number of home dialysis beneficiaries increased by 7 percent per year.

[9] Medicare Payment Advisory Commission. 2018. Report to the Congress: Medicare and the health care delivery system. Washington, DC: MedPAC.

[10] Medicare Payment Advisory Commission. 2019. Report to the Congress: Medicare payment policy. Washington, DC: MedPAC.

[11] Factors that affect access to kidney transplantation besides donation rates include the clinical allocation process; patient’s health literacy, clinical characteristics, and preferences; the availability of education for patients; clinical referral for transplant evaluation at a transplant center; and transplant center policies.

[12] Marrufo, G., B. Negrusa, D. Ullman, et al. 2017. Comprehensive End-Stage Renal Disease Care (CEC) Model: Performance Year 1 annual evaluation report. Report prepared by the Lewin Group for the Centers for Medicare & Medicaid Services. Baltimore, MD: CMS.

[13] Regarding the role of transplant centers, UNOS states that: “Each transplant program makes its own decision about whether to accept someone for a transplant. The transplant team at each program has its own standards for accepting candidates. Each team may view the same facts and information different ways and make different decisions about listing a person for a transplant.” See https://unos.org/transplant/frequently-asked-questions/.

[14] Hippen, B. E., and F. W. Maddux. 2018. Integrating kidney transplantation into value-based care for people with renal failure. American Journal of Transplantation 18, no. 1: 43–52.

[15] In its announcement of the quality initiative, the agency said that “Fistula Fist” aims at having fistulas placed in at least half of new dialysis patients with a long-range goal of maintaining fistulas in 40 percent of eligible patients who remain on dialysis ( https://www.cms.gov/newsroom/press-releases/cms-launches-fistula-first-initiative-improve-care-and-quality-life-hemodialysis-patients). Over time, the quality initiative has focused to reducing use of central venous catheters—“Fistula First Cather Last.”

[16]United States Renal Data System, National Institute of Diabetes and Digestive and Kidney Diseases. 2018. USRDS 2018 annual data report. Bethesda, MD: NIDDK.

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