Background: The design of complex policy interventions to inform both management and clinical decision making requires due consideration of the 'best-available' evidence. Where appropriate and feasible, this should relate to evidence derived from high-quality quantitative or qualitative research. However, there remain many aspects of clinical care that either have not or cannot be fully explored by such evidence alone. The truth is that policy makers are frequently required to make their best assessment in the absence of definitive evidence and many areas of clinical care continue to be supported by clinicians’ tacit knowledge derived from their clinical experiences or the dominant healthcare discourse at the time of practice. Of critical importance in these instances, systematic review of text and opinion may serve as the best-available evidence. The value of cumulative, critically appraised evidence of this nature should not be underestimated.
Objectives: To highlight the important role that the richness of evidence derived from text and opinion synthesis may contribute within various healthcare settings, especially when there is an absence of research designs.
Methods: A methodology working group comprising experts from across the Joanna Briggs Collaboration has established and continues to review guidance and processes for this emerging methodology.
Results: The Joanna Briggs Institute has developed guidance and software to assist reviewers to appraise, extract and analyse data from textual and expert opinion-based evidence. Further ongoing work and challenges will be presented, including identifying the source of the opinion, considering the issue of credibility, and extracting conclusions from textual data.
Conclusions: Translating research evidence into policy and practice remains the ultimate goal. However, efforts also need to be cognisant of context and the pressures and urgency associated with the development of meaningful policies to inform decision making. As such, reviews that consider text and opinion may offer a credible approach to dealing with uncertainty in a real and systematic way.