Evidence map›Paper›PMID 41947887›Full record

ArticleHome health care management & practice2025

Beyond Keywords: A Qualitative Study of Context-Dependent Stigmatizing Language in Clinical Documentation from a Large, Multi-Payer Home Healthcare Agency.

Zhihong Zhang, Stephanie Potts-Thompson, Laura Prescott, Morgan Morrison, Margaret V McDonald, Chase Wesley Raymond, Scott Sittig, Jacquelyn Y Taylor, Maxim Topaz

Abstract read
In one paragraph

Article in Home health care management & practice, 2025. 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

9 authors.

Zhihong ZhangColumbia University Data Science Institute, New York, New York, United States of America.
Stephanie Potts-ThompsonColumbia University School of Nursing, Center for Research on People of Color, New York, New York, United States of America.
Laura PrescottColumbia University School of Nursing, Center for Research on People of Color, New York, New York, United States of America.
Morgan MorrisonColumbia University School of Nursing, Center for Research on People of Color, New York, New York, United States of America.
Margaret V McDonaldCenter for Home Care Policy & Research, VNS Health, New York, New York, United States of America.
Chase Wesley RaymondUniversity of Colorado, Department of Linguistics, Boulder, Colorado, United States of America.
Scott SittigUniversity of Louisiana at Lafayette, Health Sciences, Lafayette, Louisiana, United States of America.
Jacquelyn Y TaylorColumbia University School of Nursing, Center for Research on People of Color, New York, New York, United States of America.
Maxim TopazColumbia University Data Science Institute, New York, New York, United States of America.

Funding

Optimizing Clinical Documentation Quality to Reduce Health Disparities in Home Healthcare: The ENGAGE StudyR01MD018028 · NIMHD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SITTIG, SCOTT M, TAYLOR, JACQUELYN Y · 2023 to 2025
$2.0M
NIMHD NIH HHS R01 MD018028
6 · The paper itself

Abstract

Background: Stigmatizing language in clinical documentation is increasingly recognized as a contributor to healthcare disparities, with evidence that such language disproportionately affects marginalized populations. Objective: This study aimed to explore home healthcare (HHC) clinicians' perceptions of stigmatizing language in documentation and to identify strategies for reducing bias. Methods: We conducted semi-structured interviews with seven nurses between may and October 2024 from a large nonprofit HHC agency in New York City, which serves patients across diverse payer types, such as Medicare, Medicaid, and private insurance. We used maximum variation sampling to ensure diversity in race, experience, and geography. Interviews were transcribed and analyzed using a thematic analysis approach to identify clinicians' views on stigmatizing terms, contextual influences, and strategies for bias reduction. Results: Five themes emerged. First, clinicians demonstrated varied interpretations of potentially stigmatizing language, emphasizing the role of context in how terms are perceived. Second, clinical and system-level factors, such as complex patient needs, time pressures, and regulatory demands, shape documentation practices. Third, stigmatizing language can influence provider attitudes, erode patient trust, and hinder patient-clinician care collaboration. Fourth, clinicians identified both individual and organizational strategies to reduce bias, including reflective documentation practices and formal education and training to increase language awareness. Fifth, participants highlighted the potential role of technology in reducing biased documentation. Conclusions: This study highlights the complexity of identifying stigmatizing language in HHC and the importance of contextual understanding. Findings support the development of clinician-informed, context-sensitive NLP tools and training programs to promote equitable, patient-centered documentation practices.

Indexed as

Bias reductionClinical documentationHealth equityHome healthcareNatural language processingStigmatizing language

Identifiers

PMID41947887
PMCPMC13052516

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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.