Evidence map›Paper›PMID 38812985›Full record

ArticleHealth affairs scholar2024

Medicare Advantage enrollees' reports of unfair treatment during health care encounters.

Megan Mathews, Megan K Beckett, Steven C Martino, Julie A Brown, Nate Orr, Sarah Gaillot, Marc N Elliott

Abstract read
In one paragraph

Article in Health affairs scholar, 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

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

1 citing paper in PubMed.

  1. Article
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.

Megan MathewsRAND Corporation, Arlington, VA 22202, United States.ORCID https://orcid.org/0000-0002-8813-6847
Megan K BeckettRAND Corporation, Santa Monica, CA 90401, United States.
Steven C MartinoRAND Corporation, Pittsburgh, PA 15213, United States.ORCID https://orcid.org/0000-0002-1514-4133
Julie A BrownRAND Corporation, Santa Monica, CA 90401, United States.ORCID https://orcid.org/0000-0002-6463-2360
Nate OrrRAND Corporation, Santa Monica, CA 90401, United States.
Sarah GaillotCenters for Medicare & Medicaid Services, Baltimore, MD 21244, United States.
Marc N ElliottRAND Corporation, Santa Monica, CA 90401, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigated unfair treatment among 1863 Medicare Advantage (MA) enrollees from 21 MA plans using 2022 survey data (40% response rate) in which respondents indicated whether they were treated unfairly in a health care setting based on any of 10 personal characteristics. We calculated reported unfair treatment rates overall and by enrollee characteristics. Nine percent of respondents reported any unfair treatment, most often based on health condition (6%), disability (3%), or age (2%). Approximately 40% of those reporting any unfair treatment endorsed multiple categories. People who qualified for Medicare via disability reported unfair treatment by disability, age, income, race and ethnicity, sex, sexual orientation, and gender/gender identity more often than those who qualified via age. Enrollees dually eligible for Medicare and Medicaid or eligible for a Low-Income Subsidy (DE/LIS) reported unfair treatment by disability, income, language/accent, race and ethnicity, culture/religion, and sex more often than non-DE/LIS enrollees. Compared with White respondents, racial and ethnic minority respondents more often reported unfair treatment by race and ethnicity, language/accent, culture/religion, and income. Female respondents were more likely than male respondents to report unfair treatment based on age and sex.

Indexed as

health equityMedicare Advantagesurveyunfair treatment

Identifiers

PMID38812985
PMCPMC11135643

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.