Comparer des méthodes

	Cadre Consolidé pour la Recherche sur la Mise en Œuvre (CFIR)	Taxonomie des résultats de mise en œuvre
Domaine	Science de l'implémentation	Science de l'implémentation
Famille	Process / pipeline	Process / pipeline
Année d'origine	2009	2011
Auteur d'origine	Damschroder, L. J., Aron, D. C., et al.	Proctor, E. K., Silmere, H., Raghavan, R., et al.
Type	Framework	Taxonomy
Source fondatrice	Damschroder, L. J., Aron, D. C., Keith, R. E., Kirsh, S. R., Alexander, J. A., & Lowson, E. (2009). Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implementation Science, 4, 50.	Proctor, E. K., Silmere, H., Raghavan, R., Hovmand, P., Aarons, G. A., Bunger, A., ... & Rojas, D. (2011). Outcomes for implementation research: Conceptual distinctions, measurement challenges, and research agenda. Administration and Policy in Mental Health and Mental Health Services Research, 38(2), 65-76.
Alias	CFIR, CFIR model, consolidated framework	implementation outcomes, Proctor framework, implementation success measures
Apparentées	5	5
Résumé	The Consolidated Framework for Implementation Research (CFIR) is a five-domain model designed to systematically evaluate the factors influencing implementation success of evidence-based interventions in health systems. Developed by Damschroder et al. (2009) and refined through extensive use across health domains, CFIR provides a structured vocabulary and taxonomy of 39 constructs that identify implementation barriers and facilitators across intervention characteristics, organizational context, individual factors, and implementation process.	The Implementation Outcome Taxonomy is a framework defining eight measurable dimensions for assessing implementation success: Acceptability, Adoption, Appropriateness, Feasibility, Fidelity, Implementation Cost, Penetration, and Sustainability. Developed by Proctor et al. (2011), it provides a standardized vocabulary and measurement approach to distinguish implementation process outcomes (how well was the intervention delivered?) from clinical outcomes (did patients get better?). This taxonomy is foundational to implementation science because it acknowledges that an evidence-based intervention can be effective (clinical outcome) but poorly implemented (implementation outcome), or feasible to deliver but not adopted by organizations.