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. 2025 Aug;12(4):2675-2685.
doi: 10.1007/s40615-024-02080-3. Epub 2024 Jul 9.

Racial Differences in Stigmatizing and Positive Language in Emergency Medicine Notes

Sean Boley  1 , Abbey Sidebottom  2 , Marc Vacquier  2 , David Watson  3   4 , Bailey Van Eyll  5   6 , Sara Friedman  5 , Scott Friedman  7
Affiliations

Racial Differences in Stigmatizing and Positive Language in Emergency Medicine Notes

Sean Boley et al. J Racial Ethn Health Disparities. 2025 Aug.

Abstract

Objective: Language used by providers in medical documentation may reveal evidence of race-related implicit bias. We aimed to use natural language processing (NLP) to examine if prevalence of stigmatizing language in emergency medicine (EM) encounter notes differs across patient race/ethnicity.

Methods: In a retrospective cohort of EM encounters, NLP techniques identified stigmatizing and positive themes. Logistic regression models analyzed the association of race/ethnicity and themes within notes. Outcomes were the presence (or absence) of 7 different themes: 5 stigmatizing (difficult, non-compliant, skepticism, substance abuse/seeking, and financial difficulty) and 2 positive (compliment and compliant).

Results: The sample included notes from 26,363 unique patients. NH Black patient notes were less likely to contain difficult (odds ratio (OR) 0.80, 95% confidence interval (CI), 0.73-0.88), skepticism (OR 0.87, 95% CI, 0.79-0.96), and substance abuse/seeking (OR 0.62, 95% CI, 0.56-0.70) compared to NH White patient notes but more likely to contain non-compliant (OR 1.26, 95% CI, 1.17-1.36) and financial difficulty (OR 1.14, 95% CI, 1.04-1.25). Hispanic patient notes were less likely to contain difficult (OR 0.68, 95% CI, 0.58-0.80) and substance abuse/seeking (OR 0.78, 95% CI, 0.66-0.93). NH NA/AI patient notes had twice the odds as NH White patient notes to contain a stigmatizing theme (OR 2.02, 95% CI, 1.64-2.49).

Conclusions: Using an NLP model to analyze themes in EM notes across racial groups, we identified several inequities in the usage of positive and stigmatizing language. Interventions to minimize race-related implicit bias should be undertaken.

Keywords: Emergency medicine; Health inequities; Medical documentation; Natural language processing.

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Conflict of interest statement

Declarations. Ethics Approval: This study was determined to be exempt from review by the Allina Health Institutional Review Board. Competing Interests: The authors declare no competing interests.

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