Hierarchical Concept Relations Improve Detection of Off-Label Drug Use in Electronic Health Records Data.

ABSTRACT: Real-world clinical practice commonly veers from formal drug approvals in off-label use, accounting for 21% of prescriptions for common drugs. Due to its ad hoc nature, off-label use typically goes undocumented, evading the safety and efficacy scrutiny of clinical trials. A systematic and automated approach to detection of these uses in the electronic health record (EHR) would enable improved safety monitoring, provide insight into prescribing patterns, and support real-world evidence appraisal. Domain knowledge provided by medication-indication knowledge bases has been shown to improve the accuracy of EHR-based automated detection of off-label use, but remains limited due to diverse concept representations and granularities across data sources. We present a method to leverage hierarchical

SUBMITTER: Schiffer K 

PROVIDER: S-EPMC10283126 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature