Using a patient’s genetic information to inform medication prescriptions can be clinically effective; however, the practice has not been widely implemented. Health systems need guidance on how to engage with providers to improve pharmacogenetic test utilization. Approaches from the field of implementation science may shed light on the complex factors affecting pharmacogenetic test use in real-world settings and areas to target to improve utilization. This paper presents an approach to studying the application of precision medicine that utilizes mixed qualitative and quantitative methods and implementation science frameworks to understand which factors or combinations consistently account for high versus low utilization of pharmocogenetic testing. This approach involves two phases: (1) collection of qualitative and quantitative data from providers—the cases—at four clinical institutions about their experiences with, and utilization of, pharmacogenetic testing to identify salient factors; and (2) analysis using a Configurational Comparative Method (CCM), using a mathematical algorithm to identify the minimally necessary and sufficient factors that distinguish providers who have higher utilization from those with low utilization. Advantages of this approach are that it can be used for small to moderate sample sizes, and it accounts for conditions found in real-world settings by demonstrating how they coincide to affect utilization.

Background: Pharmacogenetic (PGx) testing could identify actionable drug–gene interactions, reducing the risks of inappropriate prescribing of certain medications in some patients. An area of growing public health concern is rising global rates of depression and antidepressant use over the last two decades. Prior research has elucidated perspectives of healthcare providers who prescribe antidepressants regarding the clinical utility of genetic information, including PGx testing, but there is a gap in understanding how individual perspectives and systemic contextual factors may combine to influence PGx testing adoption. Objective: The objective of this study was to elucidate combinations of individual and contextual conditions associated with willingness to adopt PGx testing for Cytochrome P450 Subfamily IID, Polypeptide 6 (CYP2D6) and Subfamily IIC, Polypeptide 19 (CYP2C19) among antidepressant prescribers. Methods: We conducted a cross-sectional, mixed-methods study using structured questionnaires and semi-structured interviews with healthcare providers who prescribe antidepressants within their scope of practice across four healthcare systems in the United States. We collected data on implementation science concepts from the Theoretical Domains Framework, the Consolidated Framework for Implementation Research (CFIR), and the Implementation Outcomes Framework. Coincidence analysis (CNA), a case-based, Boolean logic-based method that identifies minimally sufficient combinations of conditions that lead to a particular outcome, was used to identify combinations of conditions for PGx test adoption among antidepressant prescribers. Interviews were also conducted with 10 patients who received pharmacogenetic testing within these healthcare systems to contextualize findings with patient perspectives. Results: Prescribers adopted PGx testing when they believed it would be beneficial to patients and were not deterred by cost-related concerns; the combination of these conditions led to PGx adoption in the most highly supported CNA model. Patient perspectives were also consistent with the selected model, with data suggesting they may have greater willingness to tolerate costs when they perceived or experienced benefits from testing. Conclusions: Insights from this study may be used by health system administrators and public health policymakers to inform future PGx implementation strategies that enhance uptake and awareness of existing evidence for clinical benefits of PGx testing and mitigate cost-related barriers to adoption.