Scaling-up an evidence-based intervention for osteoarthritis in real-world settings: a pragmatic evaluation using the RE-AIM framework

BACKGROUND: Scaling-up and sustaining effective healthcare interventions is essential for improving healthcare; however, relatively little is known about these processes. In addition to quantitative experimental designs, we need approaches that use embedded, observational studies on practice-led, naturally occurring scale-up processes. There are also tensions between having adequately rigorous systems to monitor and evaluate scale-up well that are proportionate and pragmatic in practice. The study investigated the scale-up of an evidence-based complex intervention for knee and hip osteoarthritis (ESCAPE-pain) within 'real-world' settings by England's 15 Academic Health Science Networks (AHSNs). METHODS: A pragmatic evaluation of the scale-up of ESCAPE-pain using the RE-AIM framework to measure Reach, Effectiveness, Adoption, Implementation and Maintenance. The evaluation used routine monitoring data collected from April 2014 to December 2018 as part of a national scale-up programme. RESULTS: Between 2014 and 2018, ESCAPE-pain was adopted by over 110 clinical and non-clinical sites reaching over 9000 people with osteoarthritis. The programme showed sustained clinical effectiveness (pain, function and quality of life) and high levels of adherence (78.5% completing 75% of the programme) within a range of real-world settings. Seven hundred seventy people (physiotherapists and exercise professionals) have been trained to deliver ESCAPE-pain, and 84.1% of sites have continued to deliver the programme post-implementation. CONCLUSIONS: ESCAPE-pain successfully moved from being an efficacious "research intervention" into an effective intervention within 'real-world' clinical and non-clinical community settings. However, scale-up has been a gradual process requiring on-going, dedicated resources over 5 years by a national network of Academic Health Science Networks (AHSNs). Whilst the collection of monitoring and evaluation data is critical in understanding implementation and scale-up, there remain significant challenges in developing systems sufficiently rigorous, proportionate and locally acceptable.