A qualitative analysis of stigmatizing language in birth admission clinical notes.

bias birth discrimination electronic health records health disparities pregnancy qualitative research social stigma

Journal

Nursing inquiry
ISSN: 1440-1800
Titre abrégé: Nurs Inq
Pays: Australia
ID NLM: 9505881

Informations de publication

Date de publication:
07 2023
Historique:
revised: 06 04 2023
received: 03 02 2023
accepted: 07 04 2023
medline: 19 7 2023
pubmed: 19 4 2023
entrez: 19 04 2023
Statut: ppublish

Résumé

The presence of stigmatizing language in the electronic health record (EHR) has been used to measure implicit biases that underlie health inequities. The purpose of this study was to identify the presence of stigmatizing language in the clinical notes of pregnant people during the birth admission. We conducted a qualitative analysis on N = 1117 birth admission EHR notes from two urban hospitals in 2017. We identified stigmatizing language categories, such as Disapproval (39.3%), Questioning patient credibility (37.7%), Difficult patient (21.3%), Stereotyping (1.6%), and Unilateral decisions (1.6%) in 61 notes (5.4%). We also defined a new stigmatizing language category indicating Power/privilege. This was present in 37 notes (3.3%) and signaled approval of social status, upholding a hierarchy of bias. The stigmatizing language was most frequently identified in birth admission triage notes (16%) and least frequently in social work initial assessments (13.7%). We found that clinicians from various disciplines recorded stigmatizing language in the medical records of birthing people. This language was used to question birthing people's credibility and convey disapproval of decision-making abilities for themselves or their newborns. We reported a Power/privilege language bias in the inconsistent documentation of traits considered favorable for patient outcomes (e.g., employment status). Future work on stigmatizing language may inform tailored interventions to improve perinatal outcomes for all birthing people and their families.

Identifiants

pubmed: 37073504
doi: 10.1111/nin.12557
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Pagination

e12557

Informations de copyright

© 2023 The Authors. Nursing Inquiry published by John Wiley & Sons Ltd.

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Auteurs

Veronica Barcelona (V)

Columbia University School of Nursing, New York City, New York, USA.

Danielle Scharp (D)

Columbia University School of Nursing, New York City, New York, USA.

Betina R Idnay (BR)

Department of Biomedical Informatics, Columbia University, New York City, New York, USA.

Hans Moen (H)

Department of Computer Science, Aalto University, Espoo, Finland.

Dena Goffman (D)

Department of Obstetrics, Columbia University Irving Medical Center, New York City, New York, USA.

Kenrick Cato (K)

Family and Community Health, University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA.

Maxim Topaz (M)

Columbia University School of Nursing, New York City, New York, USA.

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