Optimizing pharmacogenomic clinical decision support: a usability study of epic's Genomic-Indicators

BMC Pharmacol Toxicol. 2026 Feb 21;27(1):49. doi: 10.1186/s40360-026-01109-z.

Abstract

Background: Pharmacogenomic (PGx)-guided therapy has demonstrated improved medication-related outcomes and reduced healthcare costs. Interruptive clinical decision support (CDS) alerts are crucial in providing guidance to providers in PGx-informed clinical decision making. However, the integration of comprehensive PGx information into clinical practice remains challenging. Epic’s Genomics Module, featuring Genomic-Indicators (Gen-Ind) aims to address this gap by providing clinicians with a customizable PGx profile within the electronic health record (EHR). We aimed to evaluate the usability of the PGx patient profile (Gen-Ind) implemented through Epic’s Genomic Module at UF Health, providing actionable feedback for improvement and standardization for real-world PGx-CDS implementation.

Methods: We conducted usability evaluation sessions with ten prescribers at UF Health who had seen at least one PGx Our Practice Advisory (OPA) implemented at UF Health. Participants completed tasks within a test environment, including first and second attempts to navigate to the Genomic-Indicators and exploring its features. Quantitative data were collected through demographic surveys, assessment of task completion times, and a Post-Study System Usability Questionnaire (PSSUQ). Qualitative data was gathered through think-aloud sessions and debrief interviews on which thematic analysis was performed.

Results: Quantitative analyses revealed significant improvement in navigation efficiency between first and second attempts (p = 0.004). The PSSUQ indicated positive evaluation for system usefulness and both information and interface quality. Inductive thematic analysis identified five main themes: navigation, workflow integration, visibility of key features, content quality, and suggestions for optimization and alert systems.

Conclusions: The Genomic-Indicators may support clinical decision-making and were generally well received by users. Continued refinements in interface design, customization options, and integration of notification to alert clinicians to the presence of the Genomic-Indicators could further improve its utility and clinical value. These findings provide valuable insights into approaches for improving the user experience and clinical relevance of PGx-CDS tools based on clinician feedback.

Supplementary Information: The online version contains supplementary material available at 10.1186/s40360-026-01109-z.

Keywords: Clinical decision support; Electronic health record; Epic genomics module; Genomic indicators; Pharmacogenomics; Usability testing.