Evidence map›Paper›PMID 42181010›Full record

ArticleHealth affairs scholar2026

Trends in medical debt in the United States by imputed borrower race and ethnicity, 2016-2022.

Alexander C Adia, Jenny S Guadamuz, Charleen Hsuan, Hector P Rodriguez

Abstract read
In one paragraph

Article in Health affairs scholar, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Alexander C AdiaDivision of Health Policy and Management, School of Public Health, University of California, Berkeley, CA 94704, United States.
Jenny S GuadamuzDivision of Health Policy and Management, School of Public Health, University of California, Berkeley, CA 94704, United States.ORCID https://orcid.org/0000-0002-2312-4140
Charleen HsuanDepartment of Health Policy & Administration, Pennsylvania State University, University Park, PA 16802, United States.ORCID https://orcid.org/0000-0001-8720-2323
Hector P RodriguezDivision of Health Policy and Management, School of Public Health, University of California, Berkeley, CA 94704, United States.ORCID https://orcid.org/0000-0002-6564-2229

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Medical debt is a major financial consequence of healthcare in the United States, but there is limited evidence about whether medical debt in collections varies across racial and ethnic groups. Methods: We analyzed credit report data from 2016 to 2022 for 23,093,888 adults to study medical debt in collections accrued within the past year (flow) and total outstanding medical debt in collections (stock). Results: Black borrowers had the highest levels of annual flow of medical debt, with 11.2% of borrowers facing any annual flow of debt in 2022 (mean conditional on any flow: $1524). Similar trends existed for stock, with 24% of borrowers having any stock in 2022 (mean conditional on any stock: $2074). Hispanic and White borrowers had similar medical debt, and Asian and Pacific Islander borrowers had the least debt. Gaps between racial and ethnic groups were smaller in states that expanded Medicaid compared to those that did not, especially on the flow of new medical debt. Discussion: Identifying evidence-based policies and interventions to reduce medical debt differences by borrower race and ethnicity should be a high policy priority.

Indexed as

disparitieshealth insuranceMedicaid expansionmedical debtrace and ethnicity

Identifiers

PMID42181010
PMCPMC13196874

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.