Pharmacogenomic augmented machine learning in electronic health record alerts: A health system-wide usability survey of clinicians.

ABSTRACT: Pharmacogenomic (PGx) biomarkers integrated using machine learning can be embedded within the electronic health record (EHR) to provide clinicians with individualized predictions of drug treatment outcomes. Currently, however, drug alerts in the EHR are largely generic (not patient-specific) and contribute to increased clinician stress and burnout. Improving the usability of PGx alerts is an urgent need. Therefore, this work aimed to identify principles for optimal PGx alert design through a health-system-wide, mixed-methods study. Clinicians representing multiple practices and care settings (N = 1062) in urban, rural, and underserved regions were invited to complete an electronic survey comparing the usability of three drug alerts for citalopram, as a case study. Alert 1 contained a gener

SUBMITTER: Grant CW 

PROVIDER: S-EPMC11473792 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature