Evidence map›Paper›PMID 40802585›Full record

ArticlePloS one2025

Racial bias in clinician assessment of patient credibility: Evidence from electronic health records.

Mary Catherine Beach, Keith Harrigian, Brant Chee, Alya Ahmad, Anne R Links, Ayah Zirikly, Dingfen Han, Emily Boss, Shari Lawson, Mustapha Saheed and 3 more

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

13 authors.

Mary Catherine BeachDepartment of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0000-0002-1112-6309
Keith HarrigianDepartment of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.
Brant CheeApplied Physics Lab, Johns Hopkins University, Baltimore, Maryland, United States of America.
Alya AhmadDepartment of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0009-0003-3902-048X
Anne R LinksDepartment of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.
Ayah ZiriklyDepartment of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.
Dingfen HanDepartment of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.
Emily BossDepartment of Otolaryngology, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.
Shari LawsonDepartment of Obstetrics and Gynecology, School of Medicine, Howard University, Washington, District of Columbia, United States of America.ORCID https://orcid.org/0000-0002-0991-0962
Mustapha SaheedDepartment of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.
Yahan LiDepartment of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0009-0002-3300-8685
Mark DredzeDepartment of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.
Somnath SahaDepartment of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveBlack patients disproportionately report feeling disbelieved or having concerns dismissed in medical encounters, suggesting potential racial bias in clinicians' assessment of patient credibility. Because this bias may be evident in the language used by clinicians when writing notes about patients, we sought to assess racial differences in use of language either undermining or supporting patient credibility within the electronic health record (EHR).

methodsWe analyzed 13,065,081 notes written between 2016-2023 about 1,537,587 patients by 12,027 clinicians at a large health system with 5 hospitals and an extensive network of ambulatory practices in the mid-Atlantic region of the United States. We developed and applied natural language processing models to identify whether or not a note contained terms undermining or supporting patient credibility, and used logistic regression with generalized estimating equations to estimate the association of credibility language with patient race/ethnicity.

resultsThe mean patient age was 43.3 years and 55.9% were female; 57.6% were non-Hispanic White, 28.0% non-Hispanic Black, 8.3% Hispanic/Latino, and 6.1% Asian. Clinician-authors were attending physicians (44.9%), physicians-in-training (40.1%) and advanced practice providers (15.0%). Terms specifically related to patient credibility were relatively uncommon, with 106,523 (0.82%) notes containing terms undermining patient credibility, and 33,706 (0.26%) supporting credibility. In adjusted analyses, notes written about non-Hispanic Black vs. White patients had higher odds of containing terms undermining credibility (aOR 1.29, 95% CI 1.27-1.32), and lower odds of supporting credibility (aOR 0.82; 95% CI 0.79-0.85). Notes written about Hispanic/Latino vs. White patients had similar odds of language undermining (aOR 0.99, 95% CI 0.95-1.03) and supporting credibility (aOR 0.95, 95% CI 0.89-1.02). Notes written about Asian vs. White patients had lower odds of language undermining credibility (aOR 0.85, 95% CI 0.81-0.89), and higher odds of supporting credibility (aOR 1.30, 95% CI 1.23-1.38).

conclusionsClinician documentation undermining patient credibility may disproportionately stigmatize Black individuals and favor Asian individuals. As stigmatizing language in medical records has been shown to negatively influence clinician attitudes and decision making, these racial differences in documentation may influence patient care and outcomes and exacerbate health inequities.

Indexed as

Electronic Health RecordsPhysician-Patient RelationsRacismAdultBlack or African AmericanFemaleHispanic or LatinoHumansLanguageMaleMiddle AgedUnited StatesWhiteWhite People

Identifiers

PMID40802585
PMCPMC12349006

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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.