Implementing shared decision making support for cardiovascular disease prevention: Stakeholder interviews and case studies in Australian primary care

Abstract

Abstract Background: Australian cardiovascular disease (CVD) prevention guidelines recommend absolute CVD risk assessment, but less than half of eligible patients have the required risk factors recorded due to fragmented implementation over the last decade. Co-designed decision support tools for general practitioners (GPs) and consumers have been developed that improve knowledge barriers to guideline-recommended CVD risk assessment and management. This study used a stakeholder consultation process to identify and pilot test the feasibility of implementation strategies for these decision support tools in Australian primary care. Methods: This work was based on the Multiphase Optimisation Strategy (MOST) framework and included: 1) stakeholder consultation to map existing implementation strategies (2018-20); 2) interviews with 29 Primary Health Network (PHN) staff from all Australian states and territories to identify new implementation opportunities (2021); 3) pilot testing the feasibility of low, medium, and high resource implementation strategies (2019-21). Framework Analysis was used for qualitative data and Google analytics provided decision support usage data over time. Results: Informal stakeholder discussions indicated a need to partner with existing programs delivered by the Heart Foundation and PHNs. PHN interviews identified the importance of linking decision support tools with GP education resources, quality improvement activities, and consumer-focused prevention programs. Participants highlighted the importance of taking account of general practice processes, such as business models, workflows, medical records and clinical audit software. Specific implementation strategies were identified as feasible to pilot during COVID-19: 1) low resource: adding website links to local health area guidelines for clinicians and a Heart Foundation toolkit for primary care providers; 2) medium resource: presenting at GP education conferences and integrating the resources into audit and feedback reports; 3) high resource: auto-populate the risk assessment and decision aids from patient records via clinical audit software. Conclusions: This research identified a wide range of feasible strategies to implement decision support tools for CVD risk assessment and management. The findings will inform the translation of new CVD guidelines in primary care. Future research will use economic evaluation to explore the added value of higher versus lower resource implementation strategies.