Evidence map›Paper›PMID 35930284›Full record

ArticleJAMA network open2022

Treatment Patterns and Characteristics of Dialysis Facilities Randomly Assigned to the Medicare End-Stage Renal Disease Treatment Choices Model.

Adam S Wilk, Kelsey M Drewry, Rebecca Zhang, Stephen O Pastan, Rebecca Thorsness, Amal N Trivedi, Rachel E Patzer

Abstract readComparative Study
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Neighborhood Built Environment and Home Dialysis Utilization: Varying Patterns by Urbanicity-Dependent Patterns and Implications for Policy.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2025
    Article
  3. Article
  4. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Adam S WilkRollins School of Public Health, Emory University, Atlanta, Georgia.
Kelsey M DrewryRollins School of Public Health, Emory University, Atlanta, Georgia.
Rebecca ZhangRollins School of Public Health, Emory University, Atlanta, Georgia.
Stephen O PastanEmory University School of Medicine, Atlanta, Georgia.
Rebecca ThorsnessBrown University School of Public Health, Providence, Rhode Island.
Amal N TrivediBrown University School of Public Health, Providence, Rhode Island.
Rachel E PatzerRollins School of Public Health, Emory University, Atlanta, Georgia.

Funding

Impact of Randomized Payment Incentives on Disparities in Home Dialysis and Kidney TransplantationR01MD017080 · NIMHD · BROWN UNIVERSITY · PI Rachel E Patzer, AMAL N. TRIVEDI · 2022 to 2026
$3.2M
NIMHD NIH HHS R01 MD017080
6 · The paper itself

Abstract

Importance: In 2021, Medicare launched the End-Stage Renal Disease Treatment Choices (ETC) model, which randomly assigned approximately 30% of dialysis facilities to new financial incentives to increase use of transplantation and home dialysis; these financial bonuses and penalties are calculated by comparing living-donor transplantation, transplant wait-listing, and home dialysis use in ETC-assigned facilities vs benchmarks from non-ETC-assigned (ie, control) facilities. Because model participation is randomly assigned, evaluators may attribute any downstream differences in outcomes to facility performance rather than any imbalance in baseline characteristics. Objective: To identify preintervention imbalances in dialysis facility characteristics that should be recognized in any ETC model evaluations. Design, Setting, and Participants: This cross-sectional study compared ETC-assigned and control dialysis facility characteristics in the United States from 2017 to 2018. A total of 6062 facilities were included. Data were analyzed from February 2021 to May 2022. Exposures: Assignment to the ETC model. Main Outcomes and Measures: Dialysis facilities' preintervention transplantations and home dialysis use, facility characteristics (notably, profit and chain status), patient demographic characteristics, and community socioeconomic characteristics. Results: Among 316 927 patients, with 6 178 855 attributed patient-months, the mean (SD) age in January 2017 was 59 (11) years, and 132 462 (42%) were female. Patients in ETC-assigned facilities had 9% (0.2 [95% CI, 0.1-0.2] percentage points) lower prevalence of living donor transplantation, 12% (3.2 [95% CI, 3.0-3.3] percentage points) lower prevalence of transplantation wait-listing, and 4% (0.4 [95% CI, 0.3-0.4] percentage points) lower prevalence of peritoneal dialysis use compared with control facilities. ETC-assigned facilities were 14% (5.1 [95% CI, 0.9-9.4] percentage points) more likely than control facilities to be owned by the second largest dialysis organization. Relative to control facilities, ETC-assigned facilities also treated 34% (6.6 [95% CI, 6.5-6.7] percentage point) fewer patients with Hispanic ethnicity and were located in communities with median household incomes that were 4% ($2500; 95% CI, $500-$4500) lower on average. Conclusions and Relevance: In this study, dialysis facilities in ETC-assigned regions had lower preintervention prevalence of transplantation wait-listing, living donor transplantation, and peritoneal dialysis use, relative to control facilities. ETC-assigned and control facilities also differed with respect to other facility, patient, and community characteristics. Evaluators should account for these preintervention imbalances to minimize bias in their inferences about the model's association with postintervention outcomes.

Indexed as

Kidney Failure, ChronicRenal DialysisAgedCross-Sectional StudiesFemaleHealth Facilities, ProprietaryHumansMaleMedicareMiddle AgedUnited States

Identifiers

PMID35930284
PMCPMC9356315

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.