Implementation researchers’ perspectives on bridging the research-practice gap

In our blog earlier this year, we talked about simplifying implementation science, and making it more accessible to frontline staff. In this blog we will share critical insights that the implementation team, based at the Improvement Academy, has gathered while supporting, and facilitating putting evidence into practice. 

While there are several factors that contribute to the widening of the research to practice gap, the way the research pipeline is structured is a key one. The traditional research pipeline focuses on demonstrating efficacy and effectiveness of interventions before moving onto implementation and sustainability. This is a linear way of looking at how research moves into practice and limits the usefulness of implementation science. While this is changing, it will still take some time before implementation is fully integrated into research designs. Due to this, several well-researched and evidence-based programmes and interventions do not make it to practice. De Geest and colleagues describe this as the ‘valley of death’ where evidence-based innovations fail to cross the wasteland between the research world to the real-world settings. Implementation science will continue to play catch-up unless we change the way we think about it. 

Our implementation team aims to challenge and change the assumption of how evidence moves into practice in a linear way by arguing that practice also generates robust evidence. We encourage a ‘learning by doing’ approach that acknowledges the expertise of frontline staff, practitioners, and communities. This means that as implementation researchers, we bring the research evidence and across project learning to a real-world problem, and work with the implementers who bring the operational and functional knowledge to undergo multiple cycles on implementation knowledge generation together. This helps us in developing a deeper understanding of implementation. This is demonstrated using a short case study in Box 1.

This approach has enabled us to build and strengthen partnerships and relationships with our implementation stakeholders which has helped us in developing a better understanding of implementation factors in our research, and more meaningful outcomes. Additionally, we have been developing our methods to support this approach by facilitating rapid feedback to enable improvement and adaptation and map implementation factors in real-time. This way of working is accompanied by a reflection on our role as implementation researchers as we move from being passive observers towards a role with more overlap across the research-practice boundary.  This has added depth to our understanding of causal pathways about what works and why and which implementation strategies can be brought to life within a setting. 

Case study: Implementing Community health checks in Bradford

Bradford District is among the most deprived local authorities in England and has a high rate of the cardiovascular disease (CVD) and there was a demand in the community for pre-emptive actions to reduce this risk. In response to this need, the Improvement Academy established a network of clinicians, voluntary sector organisations, community members, local authority representatives, and researchers to implement of a series of collaborative, outreach health check events with an aim of CVD prevention, reducing inequalities, and improving community access to social prescribing and primary care. This was based on a ‘learning by doing’ and ‘practice to evidence’ approach where each health check event was used as a learning opportunity to understand how implementation works in practice and using this learning to inform future events and generate implementation learning. 

Integrating implementation science in research studies from the start could amplify the impact of research and research teams. This involves looking at research and implementation as complementary, and cyclical, where both inform each other. Following are some of the key learnings from our approach: