ArticleBMC pharmacology & toxicology2026
Optimizing pharmacogenomic clinical decision support: a usability study of epic's Genomic-Indicators.
Article in BMC pharmacology & toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
10 authors.
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Abstract
backgroundPharmacogenomic (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.
methodsWe 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.
resultsQuantitative 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.
conclusionsThe 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.
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