How community pharmacists envision using pharmacogenomic data: A qualitative analysis

Background: Nearly 300 medications contain pharmacogenomic information in their labeling approved by the U.S. Food and Drug Administration. As this number continues to grow, community pharmacists will be called on to use available pharmacogenomic data at the point of dispensing. Objective: This qualitative study aimed to describe how pharmacists envision the integration of pharmacogenomic data into the current workflows of community pharmacy practice. Methods: Community pharmacists from a regional supermarket chain pharmacy in the greater Pittsburgh area were interviewed using a semistructured interview guide. Participating pharmacists were presented with 3 clinical scenarios, followed by questions, to gain insight into how they envisioned the integration of pharmacogenomic data into community pharmacy workflow. The interview transcriptions were transcribed and coded. The content was analyzed to deduce the final themes. Supporting quotes were selected to illustrate each theme. Results: Ten community pharmacists from 3 different pharmacy locations participated in the study. A thematic analysis produced 6 themes: (1) integrating pharmacogenomic data into the dispensing software, (2) receiving an alert for pharmacogenomic information within the dispensing software, (3) accessing pharmacogenomic clinical guidelines to guide drug–decision-making, (4) contacting the prescriber by adding a task to the call queue, (5) placing a mandatory counseling alert on medications that were adjusted using pharmacogenomic data, and (6) counseling the patient on the first refill of a medication that was adjusted using pharmacogenomic data. Conclusion: This study describes how pharmacists envisioned the integration of pharmacogenomic data into community pharmacy workflow. The participants sought the integration of pharmacogenomic data into existing dispensing software, alerts for actionable prescribing changes using patient-specific pharmacogenomic data when available, and access to clinical decision support. In addition, the participants preferred to engage prescribers and receive alerts to counsel patients at prescription pick-up. These findings are key to integrating pharmacogenomic data into community pharmacy practice.