Shaping innovations in long-term care for stroke survivors with multimorbidity through stakeholder engagement

BACKGROUND:Stroke, like many long-term conditions, tends to be managed in isolation of its associated risk factors and multimorbidity. With increasing access to clinical and research data there is the potential to combine data from a variety of sources to inform interventions to improve healthcare. A 'Learning Health System' (LHS) is an innovative model of care which transforms integrated data into knowledge to improve healthcare. The objective of this study is to develop a process of engaging stakeholders in the use of clinical and research data to co-produce potential solutions, informed by a LHS, to improve long-term care for stroke survivors with multimorbidity. METHODS:We used a stakeholder engagement study design informed by co-production principles to engage stakeholders, including service users, carers, general practitioners and other health and social care professionals, service managers, commissioners of services, policy makers, third sector representatives and researchers. Over a 10 month period we used a range of methods including stakeholder group meetings, focus groups, nominal group techniques (priority setting and consensus building) and interviews. Qualitative data were recorded, transcribed and analysed thematically. RESULTS:37 participants took part in the study. The concept of how data might drive intervention development was difficult to convey and understand. The engagement process led to four priority areas for needs for data and information being identified by stakeholders: 1) improving continuity of care; 2) improving management of mental health consequences; 3) better access to health and social care; and 4) targeting multiple risk factors. These priorities informed preliminary design interventions. The final choice of intervention was agreed by consensus, informed by consideration of the gap in evidence and local service provision, and availability of robust data. This shaped a co-produced decision support tool to improve secondary prevention after stroke for further development. CONCLUSIONS:Stakeholder engagement to identify data-driven solutions is feasible but requires resources. While a number of potential interventions were identified, the final choice rested not just on stakeholder priorities but also on data availability. Further work is required to evaluate the impact and implementation of data-driven interventions for long-term stroke survivors

Stroke units: The implementation of a complex intervention

This article reports on selected findings from an action research study that looked at the lessons learnt from setting up a new in-patient stroke service in a London teaching hospital. Key participants in the design and evaluation of this 2-year study included members of the multi-professional stroke team and support staff within the unit, the hospital management team and representatives of patients and carers. Mixed methods (focus groups, indepth interviews, audits, documentary analysis, participant observation field notes) were used to generate data. Findings demonstrated positive change overtime with four main themes emerging from the process: building a team; developing practice-based knowledge and skills in stroke; valuing the central role of the nurse in stroke care; and creating an organisational climate for supporting change. The interplay of these non-linear, but interrelated factors is supported by complexity theory, which includes exploration of how the sum of a whole can be more than its constituent parts. Findings are likely to be of interest to practitioners, managers and policy makers interested in supporting change in a learning organisation