Examining Linguistic Differences in Electronic Health Records for Diverse Patients With Diabetes: Natural Language Processing Analysis

• Published in: JMIR medical informatics Vol. 12; p. e50428
• Main Authors: Bilotta, Isabel, Tonidandel, Scott, Liaw, Winston R, King, Eden, Carvajal, Diana N, Taylor, Ayana, Thamby, Julie, Xiang, Yang, Tao, Cui, Hansen, Michael
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 23.05.2024; JMIR Medical Informatics
• Subjects: Bias; Diabetes; Dictionaries; Electronic health records; Health disparities; Minority & ethnic groups; Natural Language Processing; Original Paper; Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals; Secondary Use of Clinical Data for Research and Surveillance; Systemic Racism and Racial Bias in Health Care and Society; sociodemographic factors; medical interaction; diversity; ethnic; natural language processing; sentiment analysis; bias; health care disparities; Hispanic; diabetes; electronic health record; racial

Individuals from minoritized racial and ethnic backgrounds experience pernicious and pervasive health disparities that have emerged, in part, from clinician bias. We used a natural language processing approach to examine whether linguistic markers in electronic health record (EHR) notes differ based...