Abstract
BACKGROUND: Keeping best practice guidelines up-to-date with rapidly emerging research evidence is challenging. 'Living guidelines' approaches enable continual incorporation of new research, assisting healthcare professionals to apply the latest evidence to their clinical practice. However, information about how living guidelines are developed, maintained and applied is limited. The Stroke Foundation in Australia was one of the first organisations to apply living guideline development methods for their Living Stroke Guidelines (LSGs), presenting a unique opportunity to evaluate the process and impact of this novel approach. METHODS: A mixed-methods study was conducted to understand the experience of LSGs developers and end-users. We used thematic analysis of one-on-one semi-structured interview and online survey data to determine the feasibility, acceptability, and facilitators and barriers of the LSGs. Website analytics data were also reviewed to understand usage. RESULTS: Overall, the living guidelines approach was both feasible and acceptable to developers and users. Facilitators to use included collaboration with multidisciplinary clinicians and stroke survivors or carers. Increased workload for developers, workload unpredictability, and limited information sharing, and interoperability of technological platforms were identified as barriers. Users indicated increased trust in the LSGs (69%), likelihood of following the LSGs (66%), and frequency of access (58%), compared with previous static versions. Web analytics data showed individual access by 16,517 users in 2016 rising to 53,154 users in 2020, a threefold increase. There was also a fourfold increase in unique LSG pageviews from 2016 to 2020. CONCLUSIONS: This study, the first evaluation of living guidelines, demonstrates that this approach to stroke guideline development is feasible and acceptable, that these approaches may add value to developers and users, and may increase guideline use. Future evaluations should be embedded along with guideline implementation to capture data prospectively.