Pharmacogenetics Clinical Decision Support Systems for Primary Care in England: Co-Design Study

Abstract

Background: Pharmacogenetics has been shown to impact patient care and outcomes through personalising the selection of medicines resulting in improved efficacy and a reduction in harmful side effects. Despite the existence of compelling clinical evidence and international guidelines highlighting the benefits of pharmacogenetics in routine clinical practice, its implementation within the National Health Service (NHS) in the United Kingdom has yet to be achieved. An important barrier that needs to be overcome is the development of information technology solutions that support the integration of pharmacogenetic data into healthcare systems. This necessitates a better understanding of the role of electronic health records (EHRs) and the design of clinical decision support systems that are acceptable to clinicians, particularly those in primary care. Objective:The objective of this study was to explore the needs and requirements of a pharmacogenetic service from the perspective of primary care clinicians and utilise this information to co-design a prototype solution.Methods: We utilised ethnographic observations, user research workshops and prototyping methods in this study. The participants for this study included general practitioners and pharmacists. In total we undertook five sessions of ethnographic observation to understand current practices and workflows. This was followed by three user research workshops, each with their own topic guide starting with personas and early ideation, through to exploring the potential of clinical decision support tools and prototype design. We subsequently analysed workshop data using affinity diagramming and refined the key requirements for the solution collaboratively as a multi-disciplinary project team.Results: User research results identified that pharmacogenetic data must be incorporated within existing EHRs rather than through a stand-alone portal. The information presented through clinical decision support tools must be clear, accessible and userfriendly as the service will be used by a range of end-users. Finally, the prescribing recommendations should be authoritative to provide confidence in the validity of the results. Based on these findings we co-designed an interactive prototype, demonstrating pharmacogenetic clinical decision support integrated within an EHR. Conclusions:This study marks a significant step forward in the design of systems that support pharmacogenetic-guided prescribing in primary care settings. Clinical decision support systems have the potential to enhance the personalisation of medicines, provided they are effectively implemented within existing EHRs and present pharmacogenetic data in a user-friendly, actionable, and standardised format. Achieving this requires the development of a decoupled, standards-based architecture that allows for the separation of data from application, facilitating integration across various EHRs through the utilisation of application programming interfaces (APIs). More globally, this study demonstrates the role of health...