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Patient engagement in health implementation research: A logic model
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...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10485341/ https://www.ncbi.nlm.nih.gov/pubmed/37309078 http://dx.doi.org/10.1111/hex.13782 |
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author | Bisson, Mathieu Aubrey‐Bassler, Kris Chouinard, Maud‐Christine Doucet, Shelley Ramsden, Vivian R. Dumont‐Samson, Olivier Howse, Dana Lambert, Mireille Schwarz, Charlotte Luke, Alison Rabbitskin, Norma Gaudreau, André Porter, Jude Rubenstein, Donna Taylor, Jennifer Warren, Mike Hudon, Catherine |
author_facet | Bisson, Mathieu Aubrey‐Bassler, Kris Chouinard, Maud‐Christine Doucet, Shelley Ramsden, Vivian R. Dumont‐Samson, Olivier Howse, Dana Lambert, Mireille Schwarz, Charlotte Luke, Alison Rabbitskin, Norma Gaudreau, André Porter, Jude Rubenstein, Donna Taylor, Jennifer Warren, Mike Hudon, Catherine |
author_sort | Bisson, Mathieu |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10485341 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104853412023-09-09 Patient engagement in health implementation research: A logic model Bisson, Mathieu Aubrey‐Bassler, Kris Chouinard, Maud‐Christine Doucet, Shelley Ramsden, Vivian R. Dumont‐Samson, Olivier Howse, Dana Lambert, Mireille Schwarz, Charlotte Luke, Alison Rabbitskin, Norma Gaudreau, André Porter, Jude Rubenstein, Donna Taylor, Jennifer Warren, Mike Hudon, Catherine Health Expect Original Articles 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. John Wiley and Sons Inc. 2023-06-12 /pmc/articles/PMC10485341/ /pubmed/37309078 http://dx.doi.org/10.1111/hex.13782 Text en © 2023 The Authors. Health Expectations published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Bisson, Mathieu Aubrey‐Bassler, Kris Chouinard, Maud‐Christine Doucet, Shelley Ramsden, Vivian R. Dumont‐Samson, Olivier Howse, Dana Lambert, Mireille Schwarz, Charlotte Luke, Alison Rabbitskin, Norma Gaudreau, André Porter, Jude Rubenstein, Donna Taylor, Jennifer Warren, Mike Hudon, Catherine Patient engagement in health implementation research: A logic model |
title | Patient engagement in health implementation research: A logic model |
title_full | Patient engagement in health implementation research: A logic model |
title_fullStr | Patient engagement in health implementation research: A logic model |
title_full_unstemmed | Patient engagement in health implementation research: A logic model |
title_short | Patient engagement in health implementation research: A logic model |
title_sort | patient engagement in health implementation research: a logic model |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10485341/ https://www.ncbi.nlm.nih.gov/pubmed/37309078 http://dx.doi.org/10.1111/hex.13782 |
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