Does health intervention research have real world policy and practice impacts: testing a new impact assessment tool

There is a growing emphasis on the importance of research having demonstrable public benefit. Measurements of the impacts of research are therefore needed. We applied a modified impact assessment process that builds on best practice to 5 years (2003-2007) of intervention research funded by Australia's National Health and Medical Research Council to determine if these studies had post-research real-world policy and practice impacts.

We used a mixed method sequential methodology whereby chief investigators of eligible intervention studies who completed two surveys and an interview were included in our final sample (n = 50), on which we conducted post-research impact assessments. Data from the surveys and interviews were triangulated with additional information obtained from documentary analysis to develop comprehensive case studies. These case studies were then summarized and the reported impacts were scored by an expert panel using criteria for four impact dimensions: corroboration; attribution, reach, and importance.

Nineteen (38%) of the cases in our final sample were found to have had policy and practice impacts, with an even distribution of high, medium, and low impact scores. While the tool facilitated a rigorous and explicit criterion-based assessment of post-research impacts, it was not always possible to obtain evidence using documentary analysis to corroborate the impacts reported in chief investigator interviews.

While policy and practice is ideally informed by reviews of evidence, some intervention research can and does have real world impacts that can be attributed to single studies. We recommend impact assessments apply explicit criteria to consider the corroboration, attribution, reach, and importance of reported impacts on policy and practice. Impact assessments should also allow sufficient time between impact data collection and completion of the original research and include mechanisms to obtain end-user input to corroborate claims and reduce biases that result from seeking information from researchers only.