Patient engagement in health implementation research: A logic model

• Main Authors: Mathieu Bisson (Author), Kris Aubrey‐Bassler (Author), Maud‐Christine Chouinard (Author), Shelley Doucet (Author), Vivian R. Ramsden (Author), Olivier Dumont‐Samson (Author), Dana Howse (Author), Mireille Lambert (Author), Charlotte Schwarz (Author), Alison Luke (Author), Norma Rabbitskin (Author), André Gaudreau (Author), Jude Porter (Author), Donna Rubenstein (Author), Jennifer Taylor (Author), Mike Warren (Author), Catherine Hudon (Author)
• Format: Book
• Published: Wiley, 2023-10-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1369-7625; 1369-6513; 10.1111/hex.13782
• Keywords: health implementation research; logic model; patient engagement; patient involvement; patient partnership in research; Medicine (General); R5-920; Public aspects of medicine; RA1-1270
• Source: Health Expectations, Vol 26, Iss 5, Pp 1854-1862 (2023)

Abstract Introduction Growing evidence supports patient engagement (PE) in health implementation research to improve the quality, relevance and uptake of research. However, more guidance is needed to plan and operationalize PE before and throughout the research process. The aim of the study was to develop a logic model illustrating the causal links between context, resources, activities, outcomes and impact of PE in an implementation research programme. Methods The Patient Engagement in Health Implementation Research Logic Model (hereafter the Logic Model) was developed using a descriptive qualitative design with a participatory approach, in the context of the PriCARE programme. This programme aims to implement and evaluate case management for individuals who frequently use healthcare services in primary care clinics across five Canadian provinces. Participant observation of team meetings was performed by all team members involved in the programme and in‐depth interviews were conducted by two external research assistants with team members (n = 22). A deductive thematic analysis using components of logic models as coding categories was conducted. Data were pooled in the first version of the Logic Model, which was refined in research team meetings with patient partners. The final version was validated by all team members. Results The Logic Model highlights the importance of integrating PE into the project before its commencement, with appropriate support in terms of funding and time allocation. The governance structure and leadership of both principal investigators and patient partners have significant effects on PE activities and outcomes. As an empirical and standardized illustration that facilitates a shared understanding, the Logic Model provides guidance for maximizing the impact of patient partnership in various contexts for research, patients, providers and health care. Conclusion The Logic Model will help academic researchers, decision makers and patient partners plan, operationalize, and assess PE in implementation research for optimal outcomes. Patient or Public Contribution Patient partners from the PriCARE research programme contributed to developing the research objectives and designing, developing and validating data collection tools, producing data, developing and validating the Logic Model and reviewing the manuscript.