Evidence for Good Practice in Public and Patient Involvement in Population Health and Health Research - Report

Background: Public and patient involvement (PPI) is increasingly seen as something that is integral to research in terms of importance to research funders and there is a general recognition that it is the right thing to do for both moral and practical reasons. this review sets out to do is to examine the question of exactly how PPI can be done ‘properly’ looking at the evidence that exists from published reviews and assessing it against the UK Standards for Involvement in Research, as well as examining the specific features of population health research that can make PPI even more challenging.
Methods: A review of reviews was carried out. A comprehensive search strategy was developed following by screening activities. The results were then subject to data extraction using the 5-stage framework. 31 reviews are included.
Results: Based on the information from the reviews the team developed two outputs. The first being a list of recommended actions to address PPI in population health research. The second is a guidance framework for use in health research projects concerning PPI based on the UK Standards. Both outputs combine the solutions and outstanding challenges taken from the reviews considered in this study and aims to provide useful tools for project staff to use in order to enhance and improve their PPI activity within population health and general health research.
Conclusions: It is clear from this review of reviews that there are several important areas of PPI activity that require further research. Looking at the UK Standards mapped against the findings, it is clear that there is a lack of current research or clarity around Governance and Impact. There could also be more research done about PPI with under-represented groups. With regards to Population Health research, there remain gaps in knowledge about how to ensure key, specific, attributes of this type of research are addressed for PPI team members – particularly around how to deal with complexity and the data-driven nature of the research.