ArticleFrontiers in pharmacology2024
Integration of pharmacogenetic data in epic genomic module drives clinical decision support alerts.
Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Impact of First-of-Its-Kind Patient-Facing Pharmacogenetics Tool on Dosing Decisions and Treatment Outcomes.Clinical pharmacology and therapeutics · 2025Trial
- Building a genomics-capable cancer workforce: a competency-based framework for education and training in precision oncology.EClinicalMedicine · 2026Review
- Trial of Preemptive Pharmacogenetic Testing in Underserved Patients (TOPP UP): Study Framework and Baseline Characteristics of Randomized Controlled Trial Participants.Clinical and translational science · 2026Article
- Optimizing pharmacogenomic clinical decision support: a usability study of epic's Genomic-Indicators.BMC pharmacology & toxicology · 2026Article
- Personal Health Data Spaces for precision prevention and continuity of care: integrating genomic, imaging, and clinical data in primary care.Frontiers in medicine · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The Precision Medicine Program (PMP) at the University of Florida (UF) focuses on advancing pharmacogenomics (PGx) to improve patient care. Methods: The UF PMP, in collaboration with the UF Health Pathology Laboratory (UFHPL), utilized Health Level Seven (HL7) standards to integrate PGx data into Epic's Genomic Module to enhance the management and utilization of PGx data in clinical practice. Results: A key feature of the Genomic Module is the introduction of genomic indicators-innovative tools that flag actionable genetic information directly within the electronic health record (EHR). These indicators enable the effective presentation of phenotypic information and, when leveraged with existing clinical decision support (CDS) alerts, help provide timely and informed therapeutic decisions based on genomic data. Discussion: This advancement represents a significant shift in the utilization of genetic data, moving beyond traditional PDF reports to provide a comprehensive understanding of PGx data. Ultimately, this integration empowers healthcare providers with genomics-guided recommendations, enhancing precision and personalization in patient care, contributing significantly to the advancement of personalized medicine.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.