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Collaborating with Patient Partners to Model Clinical Care Pathways in Major Depressive Disorder: The Benefits of Mixing Evidence and Lived Experience

BACKGROUND: Partnering with patients can enrich the design and development of models of clinical care pathways, yet the practice is not commonplace. Guidelines or “best practices” for patient involvement in modeling are scarce. OBJECTIVES: In this paper, we outline the steps we took to form an effec...

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Detalles Bibliográficos
Autores principales: Bunka, Mary, Ghanbarian, Shahzad, Riches, Linda, Landry, Ginny, Edwards, Louisa, Hoens, Alison M., Bryan, Stirling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9522760/
https://www.ncbi.nlm.nih.gov/pubmed/35877043
http://dx.doi.org/10.1007/s40273-022-01175-1
Descripción
Sumario:BACKGROUND: Partnering with patients can enrich the design and development of models of clinical care pathways, yet the practice is not commonplace. Guidelines or “best practices” for patient involvement in modeling are scarce. OBJECTIVES: In this paper, we outline the steps we took to form an effective partnership with patients to design a robust microsimulation Markov model of major depressive disorder care pathways in British Columbia, Canada, with the aim of encouraging other teams to partner with patients in healthcare modeling endeavors. METHODS: We describe three unique phases of our collaborative process: uncertainty, mapping, and structured collaboration. We then explore the unique contributions the patient partners made, not only to the model itself, but to our process. Key perspectives are shared from both the modeler and the patient partners in their own words. RESULTS: The patient partners made distinct contributions by challenging and verifying modeling assumptions, noting limitations of the model, and suggesting areas for future research. Both the patient partners and the modelers saw great value in the partnership and agreed that the model was strengthened by the diversity of the team. CONCLUSIONS: We present our learning and key recommendations for future modeling teams in the absence of tested frameworks. We encourage more widespread adoption of patient involvement in modeling and the development of guidelines for such work to increase the democracy of scientific decision making.