Evidence map›Paper›PMID 38700854›Full record

Observational studyJAMA health forum2024

Comprehensive Medication Review Completion Rates and Disparities After Medicare Star Rating Measure.

Anna Hung, Lauren Wilson, Valerie A Smith, Juliessa M Pavon, Caroline E Sloan, Susan N Hastings, Joel Farley, Matthew L Maciejewski

Erratum issuedAbstract readObservational Study
In one paragraph

Observational study in JAMA health forum, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Error in Figure 2.JAMA health forum · 2024
    Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Anna HungDepartment of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina.
Lauren WilsonDepartment of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina.
Valerie A SmithDepartment of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina.
Juliessa M PavonDivision of Geriatrics, Department of Medicine, Duke University School of Medicine, Durham, North Carolina.
Caroline E SloanDepartment of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina.
Susan N HastingsDepartment of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina.
Joel FarleyDepartment of Pharmaceutical Care & Health Systems, University of Minnesota College of Pharmacy, Minneapolis.
Matthew L MaciejewskiDepartment of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina.

Funding

U.S. Deprescribing Research NetworkR24AG064025 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI BOYD, CYNTHIA MELINDA, STEINMAN, MICHAEL A. · 2019 to 2023
$9.9M
Deprescribing Central Nervous System Medications in Hospitalized Older AdultsK23AG058788 · NIA · DUKE UNIVERSITY · PI PAVON, JULIESSA M · 2019 to 2023
$797k
Improving medication adherence and disease control for patients with multimorbidity: the role of price transparency toolsK23AG076889 · NIA · DUKE UNIVERSITY · PI Caroline Ellen Sloan · 2023 to 2026
$717k
HSRD VA IK2 HX003359NIA NIH HHS K23 AG058788NIA NIH HHS K23 AG076889NIA NIH HHS R24 AG064025
6 · The paper itself

Abstract

Importance: Comprehensive medication reviews (CMRs) are offered to qualifying US Medicare beneficiaries annually to optimize medication regimens and therapeutic outcomes. In 2016, Medicare adopted CMR completion as a Star Rating quality measure to encourage the use of CMRs. Objective: To examine trends in CMR completion rates before and after 2016 and whether racial, ethnic, and socioeconomic disparities in CMR completion changed. Design, Setting, and Participants: This observational study using interrupted time-series analysis examined 2013 to 2020 annual cohorts of community-dwelling Medicare beneficiaries aged 66 years and older eligible for a CMR as determined by Part D plans and by objective minimum eligibility criteria. Data analysis was conducted from September 2022 to February 2024. Exposure: Adoption of CMR completion as a Star Rating quality measure in 2016. Main Outcome and Measures: CMR completion modeled via generalized estimating equations. Results: The study included a total of 561 950 eligible beneficiaries, with 253 561 in the 2013 to 2015 cohort (median [IQR] age, 75.8 [70.7-82.1] years; 90 778 male [35.8%]; 6795 Asian [2.7%]; 24 425 Black [9.6%]; 7674 Hispanic [3.0%]; 208 621 White [82.3%]) and 308 389 in the 2016 to 2020 cohort (median [IQR] age, 75.1 [70.4-80.9] years; 126 730 male [41.1%]; 8922 Asian [2.9%]; 27 915 Black [9.1%]; 7635 Hispanic [2.5%]; 252 781 White [82.0%]). The unadjusted CMR completion rate increased from 10.2% (7379 of 72 225 individuals) in 2013 to 15.6% (14 185 of 90 847 individuals) in 2015 and increased further to 35.8% (18 376 of 51 386 individuals) in 2020, in part because the population deemed by Part D plans to be MTM-eligible decreased by nearly half after 2015 (90 487 individuals in 2015 to 51 386 individuals in 2020). Among a simulated cohort based on Medicare minimum eligibility thresholds, the unadjusted CMR completion rate increased but to a lesser extent, from 4.4% in 2013 to 12.6% in 2020. Compared with White beneficiaries, Asian and Hispanic beneficiaries experienced greater increases in likelihood of CMR completion after 2016 but remained less likely to complete a CMR. Dual-Medicaid enrollees also experienced greater increases in likelihood of CMR completion as compared with those without either designation, but still remained less likely to complete CMR. Conclusion and Relevance: This study found that adoption of CMR completion as a Star Rating quality measure was associated with higher CMR completion rates. The increase in CMR completion rates was achieved partly because Part D plans used stricter eligibility criteria to define eligible patients. Reductions in disparities for eligible Asian, Hispanic, and dual-Medicaid enrollees were seen, but not eliminated. These findings suggest that quality measures can inform plan behavior and could be used to help address disparities.

Indexed as

Healthcare DisparitiesAgedAged, 80 and overAsianBlack or African AmericanEthnicityFemaleHispanic or LatinoHumansInterrupted Time Series AnalysisMaleMedicareMedicare Part DUnited StatesWhite

Identifiers

PMID38700854
PMCPMC11069085

What OpenQuestion holds

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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.