Evidence map›Paper›PMID 34259849›Full record

ArticleJAMA network open2021

Physician Use of Stigmatizing Language in Patient Medical Records.

Jenny Park, Somnath Saha, Brant Chee, Janiece Taylor, Mary Catherine Beach

Registry-linked trialAbstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07602725 (Patient Experience and Trust When Viewing Original Medical Notes Versus Large Language Model), which is not on this map. Cited by 103 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
103citing papers in PubMed, 2 pooled it
–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.

NCT07602725 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Patient Experience and Trust When Viewing Original Medical Notes Versus Large Language Model (LLM)-Generated Plain Language Summaries

TypeinterventionalSponsorUniversity of Texas at AustinRan2026 to 2027Enrolled135ConditionsMusculoskeletal Disease, Orthopedic PatientsArmsLLM-Generated Medical Note, Control (Original Medical Note)
3 · Its place in the literature

Who cites it

103 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Understanding Stigmatizing Language Lexicons: A Comparative Analysis in Clinical Contexts.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024
    Pooled it
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  11. The Use of Biased Language in the Care of Seriously Ill Children: A Pilot Study.The American journal of hospice & palliative care · 2026
    Article
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43 more citing papers are in PubMed but not listed here.

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

5 authors.

Jenny ParkOregon Health and Science University, Portland.
Somnath SahaOregon Health and Science University, Portland.
Brant CheeApplied Physics Laboratory, Johns Hopkins University, Baltimore, Maryland.
Janiece TaylorJohns Hopkins School of Nursing, Johns Hopkins University, Baltimore, Maryland.
Mary Catherine BeachDivision of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Negative attitudes toward patients can adversely impact health care quality and contribute to health disparities. Stigmatizing language written in a patient's medical record can perpetuate negative attitudes and influence decision-making of clinicians subsequently caring for that patient. Objective: To identify and describe physician language in patient health records that may reflect, or engender in others, negative and positive attitudes toward the patient. Design, Setting, and Participants: This qualitative study analyzed randomly selected encounter notes from electronic medical records in the ambulatory internal medicine setting at an urban academic medical center. The 600 encounter notes were written by 138 physicians in 2017. Data were analyzed in 2019. Main Outcomes and Measures: Common linguistic characteristics reflecting an overall positive or negative attitude toward the patient. Results: A total of 138 clinicians wrote encounter notes about 507 patients. Of these patients, 350 (69%) were identified as female, 406 (80%) were identified as Black/African American, and 76 (15%) were identified as White. Of 600 encounter notes included in this study, there were 5 major themes representing negative language and 6 themes representing positive language. The majority of negative language was not explicit and generally fell into one or more of the following categories: (1) questioning patient credibility, (2) expressing disapproval of patient reasoning or self-care, (3) stereotyping by race or social class, (4) portraying the patient as difficult, and (5) emphasizing physician authority over the patient. Positive language was more often more explicit and included (1) direct compliments, (2) expressions of approval, (3) self-disclosure of the physician's own positive feelings toward the patient, (4) minimization of blame, (5) personalization, and (6) highlighting patient authority for their own decisions. Conclusions and Relevance: This qualitative study found that physicians express negative and positive attitudes toward patients when documenting in the medical record. Although often not explicit, this language could potentially transmit bias and affect the quality of care that patients subsequently receive. These findings suggest that increased physician awareness when writing and reading medical records is needed to prevent the perpetuation of negative bias in medical care.

Indexed as

Attitude of Health PersonnelElectronic Health RecordsStereotypingAcademic Medical CentersAdultEmotionsFemaleHumansInternal MedicineLanguageLinguisticsMaleMiddle AgedPhysician-Patient RelationsPhysiciansQualitative Research

Identifiers

PMID34259849
PMCPMC8281008

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.