مقایسهٔ روش‌ها

	تاکسونومی پیامدهای پیاده‌سازی	RE-AIM Framework
حوزه	علم پیاده‌سازی	علم پیاده‌سازی
خانواده	Process / pipeline	Process / pipeline
سال پیدایش	2011	1999
پدیدآور	Proctor, E. K., Silmere, H., Raghavan, R., et al.	Glasgow, R. E., Vogt, T. M., and colleagues
نوع	Taxonomy	Framework
منبع بنیادین	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.	Glasgow, R. E., Vogt, T. M., & Boles, S. M. (1999). Evaluating the public health impact of health promotion interventions: The RE-AIM framework. American Journal of Public Health, 89(9), 1322-1327.
نام‌های دیگر	implementation outcomes, Proctor framework, implementation success measures	RE-AIM, REAIM, Glasgow framework
مرتبط	5	5
خلاصه	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.	The RE-AIM framework (Reach, Effectiveness, Adoption, Implementation, Maintenance) is a five-dimension evaluation tool designed to assess the public health impact of evidence-based interventions in real-world settings. Developed by Glasgow et al. (1999) to address the gap between efficacy trials (controlled conditions) and effectiveness in practice, RE-AIM provides a comprehensive set of metrics to determine whether an intervention is 'worth it' from both scientific and practical perspectives. It has become the standard framework for evaluating implementation success across health domains.