An article published in the June 2019 edition of the Journal 'Research Involvement and Engagement' reports the findings from work undertaken by the Maudsley Biomedical Research Centre (BRC). The article describes the experience of the authors (Amelia Jewell et al) in setting up a service user and carer advisory group with the aim of providing feedback and advice to researchers developing or making use of database linkages in the field of mental health research. After a trial period of 12 months, the team conducted an evaluation of the group with both group members and presenters.

The evaluation revealed that the service user and carer advisory group succeeded in promoting dialogue between service users/carers and researchers. Factors that contributed to the success of the group’s first year included the opportunity it provided for researchers to involve service users and carers in their projects, the training provided to group members, and the openness of researchers to receiving feedback from the group.

Data linkage is the joining of two or more data sets from different sources that relate to the same individual, family, place, or event. Re-using and extending existing routinely collected data through data linkage is a cost-effective way of supporting research in public health and epidemiology. It is also an effective way of examining the relationship between health and social factors and data linkage is thus increasingly being used in health research. Data linkage is a core skill of HCD Economics and the methodology engaged in Burden of Illness studies undertaken by HCD Economics mandates the involvement of patients, by working with Patient Groups as partners across those diseases currently being studied. Data linkage studies that draw upon the BOI data, collected in HCD studies from patients, is an important use of the data alongside relevant health administration data sets.

The paper in Research Involvement and Engagement confirms the limited data published in this area, so this paper forms an important contribution to the latest understanding in the conduct of data linkage studies that incorporate PPI in their design and implementation.

Link to the article here