Evidence map›Paper›PMID 38812374›Full record

ArticleHealth services research2024

Medicare Advantage plan characteristics associated with sorting their beneficiaries to providers that generate fewer avoidable hospital stays.

Jianhui Xu, Kelly E Anderson, Angela Liu, Daniel Polsky

Abstract read
In one paragraph

Article in Health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Jianhui XuDepartment of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.ORCID 0000-0003-2961-4236
Kelly E AndersonDepartment of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, Colorado, USA.
Angela LiuDepartment of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
Daniel PolskyDepartment of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.

Funding

TRAINING IN HEALTH SERVICES RESEARCHT32HS000029 · AHRQ · JOHNS HOPKINS UNIVERSITY · PI DY, SYDNEY MORSS · 1987 to 2024
$8.3M
Agency for Healthcare Research and Quality T32HS000029AHRQ HHS T32 HS000029Arnold Ventures
6 · The paper itself

Abstract

objectiveTo examine whether certain Medicare Advantage (MA) plan characteristics are associated with driving beneficiaries to providers that generate fewer avoidable hospital stays. DATA SOURCES: This paper primarily used 2018-2019 MA encounter data and traditional Medicare (TM) claims data for a nationally representative 20% sample of Medicare beneficiaries. STUDY

designFor each plan design aspect-plan type, carrier, star rating, and network breadth-we estimated two adjusted Poisson regressions of avoidable hospital stays: one without clinician fixed effects and the other with. We calculated the difference between the coefficients to evaluate the extent to which patient sorting affected avoidable hospital stays relative to TM. DATA EXTRACTION

methodsOur sample included Medicare beneficiaries 65 years and older who were continuously enrolled in either MA or TM during 2018-2019. Beneficiaries in our sample had one or more chronic, ambulatory care-sensitive conditions. PRINCIPAL

findingsPatient sorting can be attributed to certain characteristics of plan design aspects. For plan type, HMOs account for 86%, with PPOs accounting for only 14%. For carriers, Humana and smaller carriers account for 89%. For star ratings, high-star contracts account for 94%, with other stars only accounting for 6%. By network design, narrow network plan-counties explained 20% of the patient sorting effect.

conclusionsWhile MA plans were found to be associated with driving beneficiaries to providers that generate fewer avoidable hospital stays, the effect is not homogeneous across the characteristics of MA plans. HMOs and high-star contracts are drivers of this MA phenomenon.

Indexed as

Medicare Part CAgedAged, 80 and overFemaleHospitalizationHumansInsurance Claim ReviewMaleUnited Statesavoidable hospital staysMedicare Advantagepatient sortingplan characteristicsprovider network

Identifiers

PMID38812374
PMCPMC11250124

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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.