Pharmacogenetics clinical decision support tools for primary care in England: a co-design study (Preprint)

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 compelling clinical evidence and international guidelines indicating the benefit pharmacogenetics in routine clinical practice, implementation in the National Health Service (United Kingdom) is yet to be achieved. A key barrier to overcome is the development of information technology solutions to support implementation. This includes the ability to share data between genetics laboratories and the rest of the healthcare system. In particular, this requires a better understanding of the role of electronic health records (EHRs) and the design of clinical decision support systems that are acceptable to clinicians in primary care. The aims of this study were to understand the needs and requirements of a pharmacogenetic service from the perspective of primary care clinicians and use these to co-design a prototype solution. 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 brainstorming, 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. 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 and accessible 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. We have demonstrated for the first time how systems could be designed to support pharmacogenetic-guided prescribing in primary care. Clinical decision support systems can improve the personalisation of medicines if they are implemented within existing EHRs and present pharmacogenetic data in a user-friendly, actionable and standardised format. This would require the development of a decoupled standards-based architecture, which separates data from application, allowing integration across a range of EHRs through application programming interfaces (APIs). As such, the role of health informatics and user-centred design is critical in the realisation of personalised medicine at scale and in bringing the benefits of genomic innovation to patients and populations