Understanding clinician support preferences related to the use of pharmacogenomic results in electronic health records: A qualitative study in an academic health system

Background

Integrating pharmacogenomic (PGx) test results into electronic health records (EHRs) represents a crucial step in the advancement of precision medicine. However, successful implementation is often hindered by lack of, or gaps in, clinician training; lack of clinician confidence; and system-level barriers such as limited awareness of PGx utility, complex interpretation of results, and time constraints.

Objectives

Through qualitative analysis, this study aimed to identify clinician preferences regarding the educational, technical, and workflow supports needed to effectively integrate PGx results into EHRs.

Methods

Clinicians practicing in a large academic health system in Western Pennsylvania, including physicians, advanced practice nurses, physician assistants, and pharmacists, were invited to participate in this study. The research team developed a semi-structured interview guide using the Consolidated Framework for Implementation Research as a framework. Interviews were conducted using videoconferencing software, transcribed, and analyzed using inductive reasoning analysis to identify key barriers and proposed solutions.

Results

Sixteen interviews were conducted, which revealed 7 themes: (1) contextualization of utility; (2) clinician confidence and comfort; (3) consultations; (4) resulting and alerting; (5) communication of pharmacogenomic results; (6) decelerators; and (7) education preferences. Participants emphasized the need for simplified workflows, specialty-specific training, embedded EHR tools, and patient-centered communication strategies.

Conclusion

Clinician-preferred strategies, including intuitive clinical decision support tools, modular education resources, and streamlined communication pathways, are critical to successful PGx implementation. These findings offer a practical blueprint for integrating PGx into clinical practice and inform scalable models for precision medicine adoption across health systems. Further research should explore nuanced themes to further accelerate PGx deployments.