PNS98 Natural Language Processing (NLP)-Based Detection of Transgender and Gender Non-Conforming Patients in Electronic Health Record (EHR)-Derived Data

Abstract

Transgender and gender non-conforming (GNC) individuals are known to have inferior healthcare outcomes compared to their cisgender peers. However, studying this population in EHR-derived data is challenging as gender identity indicators (e.g., ICD codes, identity status drop-downs) are not reliably populated. We sought to remedy this by developing an NLP-based approach to detect transgender and GNC patients in a real-world dataset, benchmarking model performance against the use of ICD codes.