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Mapping Theories, Models and Frameworks from implementation science for evaluating quality improvement initiatives: a
Klaudia A Arizmendi-Barrera1,2, Jafet Arrieta3,4, Tamara Nevarez Tinoco5
1Institute for Healthcare Improvement, Boston, Massachusetts, USA.
This study reviewed how implementation science Theories, Models and Frameworks (TMFs) are used to evaluate healthcare quality improvement (QI) initiatives. Findings show varied application, highlighting the need for integrated TMFs to enhance rigor and generalizability.
Area of Science:
- Implementation Science
- Healthcare Improvement
- Evaluation Methodologies
Background:
- Improvement science underpins quality improvement (QI) in healthcare, but QI evaluation rigor remains a concern.
- Implementation science Theories, Models and Frameworks (TMFs) aid evidence-based practice uptake but their role in QI evaluation is unclear.
Purpose of the Study:
- Identify TMFs used for QI evaluation in healthcare.
- Assess the application of these TMFs in evaluations.
- Compare TMFs' intrinsic methodological attributes.
Main Methods:
- Scoping review following Arksey and O'Malley's framework (2010-2025).
- Searched PubMed, Scopus, Web of Science, and Google for studies evaluating QI initiatives using TMFs.
- Evaluated TMFs at article and TMF levels for application and attributes.
Main Results:
- 80 studies identified 23 unique TMFs; Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) and Consolidated Framework for Implementation Research (CFIR) were most frequent.
- TMFs guided data collection/analysis in 94% of studies, but only 43% tested construct relationships.
- TMFs showed strong conceptual clarity but limited equity and sociocultural responsiveness.
Conclusions:
- TMF application in QI evaluation is inconsistent; no single TMF suffices.
- An integrated TMF approach is needed for rigorous evaluation of context, mechanisms, and outcomes.
- Operationalizing TMF constructs, especially equity, is crucial for reproducibility and transferability.
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