Detecting, Reporting and Alleviating Racial Biases in Standardized Medical Terminologies and Ontologies

Document Type

Conference Proceeding

Publication Date

1-1-2021

Abstract

Recently, the issue has been raised that personal and systemic biases in organizations, such as some police departments, have also been detected in healthcare organizations. Furthermore, victims of bias incidents often end up in the healthcare system for treatment. Providers use standardized terminologies to record the status of patients in EHRs. To accurately record patient data, these terminologies must contain all the terms that a healthcare provider needs, including terms that might be race-, ethnicity-, or gender-specific. Following reports about gaps in terminologies, we investigated the coverage with respect to such terms in major terminologies such as SNOMED CT, ICD-10, CPT, NCIt and MedDRA. To identify potentially missing terms, we drew on public databases and news articles describing incidents that resulted in minority members requiring medical attention after police interventions. We posit those terms should be added into medical terminologies to improve the ability to record incidents happening inside and outside of the healthcare system.

Identifier

85125197636 (Scopus)

ISBN

[9781665401265]

Publication Title

Proceedings 2021 IEEE International Conference on Bioinformatics and Biomedicine Bibm 2021

External Full Text Location

https://doi.org/10.1109/BIBM52615.2021.9669617

First Page

663

Last Page

667

Grant

UL1TR003017

Fund Ref

National Institutes of Health

This document is currently not available here.

Share

COinS