TY - GEN
T1 - Characterization of Stigmatizing Language in Medical Records
AU - Harrigian, Keith
AU - Zirikly, Ayah
AU - Chee, Brant
AU - Ahmad, Alya
AU - Links, Anne R.
AU - Saha, Somnath
AU - Beach, Mary Catherine
AU - Dredze, Mark
N1 - Publisher Copyright:
© 2023 Association for Computational Linguistics.
PY - 2023
Y1 - 2023
N2 - Widespread disparities in clinical outcomes exist between different demographic groups in the United States. A new line of work in medical sociology has demonstrated physicians often use stigmatizing language in electronic medical records within certain groups, such as black patients, which may exacerbate disparities. In this study, we characterize these instances at scale using a series of domain-informed NLP techniques. We highlight important differences between this task and analogous bias-related tasks studied within the NLP community (e.g., classifying microaggressions). Our study establishes a foundation for NLP researchers to contribute timely insights to a problem domain brought to the forefront by recent legislation regarding clinical documentation transparency. We release data, code, and models.
AB - Widespread disparities in clinical outcomes exist between different demographic groups in the United States. A new line of work in medical sociology has demonstrated physicians often use stigmatizing language in electronic medical records within certain groups, such as black patients, which may exacerbate disparities. In this study, we characterize these instances at scale using a series of domain-informed NLP techniques. We highlight important differences between this task and analogous bias-related tasks studied within the NLP community (e.g., classifying microaggressions). Our study establishes a foundation for NLP researchers to contribute timely insights to a problem domain brought to the forefront by recent legislation regarding clinical documentation transparency. We release data, code, and models.
UR - http://www.scopus.com/inward/record.url?scp=85172219488&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85172219488&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85172219488
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 312
EP - 329
BT - Short Papers
PB - Association for Computational Linguistics (ACL)
T2 - 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023
Y2 - 9 July 2023 through 14 July 2023
ER -