When Words Shape Care: Educating First-Year Medical Students on Identifying and Replacing Bias in Electronic Health Documentation
- 1Medical Student, Renaissance School of Medicine at Stony Brook University.
- 2Clinical Associate Professor, Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University.
- 3Clinical Associate Professor, Department of Emergency Medicine, Stony Brook University Hospital.
Abstract
Introduction
Although medical education increasingly addresses bias in patient care, less attention has been paid to biased language in clinical documentation within the Electronic Health Record (EHR), a critical concern as patients have increasing access to their records. Because biased language can influence clinicians' perceptions and negatively affect patient relationships, focused medical student training is needed to promote equitable, patient-centered care.Methods
We implemented a one-hour workshop on biased language in medical records using case-based discussions. First-year students (MS1s) completed pre- and postsurveys assessing their ability to identify biased language. Results were analyzed using paired t-tests, descriptive statistics, and thematic analysis.Results
Sixty-nine MS1s attended the workshop; 68 completed the presurvey (98.5%), and 63 the postsurvey (91.3%). Students demonstrated significant improvement in their ability to identify biased language in patient cases (P < .001) and survey scores (P < .001). Significant improvements were also observed in students' ability to identify the word "claims" as biased language (P < .001), identify language that defined patients by their illness (P < .001), and recognize negative patient descriptions (P < .001). Students valued the workshop's use of examples of biased language and neutral language alternatives, and many recommended incorporating this training into the medical school curriculum.Discussion
The workshop improved MS1s' recognition of biased language in EHR documentation. Incorporating documentation bias training early in medical school may strengthen students' awareness of biased language and support more patient-centered documentation.
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BibTeX
@article{konnayil2026when,
title = {{When Words Shape Care: Educating First-Year Medical Students on Identifying and Replacing Bias in Electronic Health Documentation}},
author = {Becka Konnayil and Sravya Varanasi and Christina Jacob and Pinhong Wu and Cordia Beverley and Andrew Wackett},
journal = {MedEdPORTAL : the journal of teaching and learning resources},
year = {2026},
month = oct,
doi = {10.15766/mep_2374-8265.11646},
url = {https://europepmc.org/article/PMC/PMC13717312},
note = {CC BY},
}
RIS
TY - JOUR
TI - When Words Shape Care: Educating First-Year Medical Students on Identifying and Replacing Bias in Electronic Health Documentation
AU - Becka Konnayil
AU - Sravya Varanasi
AU - Christina Jacob
AU - Pinhong Wu
AU - Cordia Beverley
AU - Andrew Wackett
PY - 2026
DA - 2026/10/29
JO - MedEdPORTAL : the journal of teaching and learning resources
DO - 10.15766/mep_2374-8265.11646
UR - https://europepmc.org/article/PMC/PMC13717312
AB - Introduction Although medical education increasingly addresses bias in patient care, less attention has been paid to biased language in clinical documentation within the Electronic Health Record (EHR), a critical concern as patients have increasing access to their records. Because biased language can influence clinicians' perceptions and negatively affect patient relationships, focused medical student training is needed to promote equitable, patient-centered care.Methods We implemented a one-hour workshop on biased language in medical records using case-based discussions. First-year students (MS1s) completed pre- and postsurveys assessing their ability to identify biased language. Results were analyzed using paired t-tests, descriptive statistics, and thematic analysis.Results Sixty-nine MS1s attended the workshop; 68 completed the presurvey (98.5%), and 63 the postsurvey (91.3%). Students demonstrated significant improvement in their ability to identify biased language in patient cases (P < .001) and survey scores (P < .001). Significant improvements were also observed in students' ability to identify the word "claims" as biased language (P < .001), identify language that defined patients by their illness (P < .001), and recognize negative patient descriptions (P < .001). Students valued the workshop's use of examples of biased language and neutral language alternatives, and many recommended incorporating this training into the medical school curriculum.Discussion The workshop improved MS1s' recognition of biased language in EHR documentation. Incorporating documentation bias training early in medical school may strengthen students' awareness of biased language and support more patient-centered documentation.
SN - 2374-8265
ER -