Implementation Models

Below are some examples—not an exhaustive list—of implementation constructs and models that can guide and evaluate implementation, including implementation science research.

 

In May 2016, The Successful Implementation Measurement Project released a report on implementation science constructs based on an environmental scan of the literature. A federal technical working group helped support this work to inform federally funded initiatives related to implementation.

The Dissemination and Implementation Models in Health Research site describes its goal as follows:

"This interactive website was designed to help researchers and practitioners to select the D&I Model that best fits their research question or practice problem, adapt the model to the study or practice context, fully integrate the model into the research or practice process, and find existing measurement instruments for the model constructs."

The Quality Implementation Framework provides a 2012 synthesis of leading implementation frameworks in the literature:

Meyers, D. C., Durlak, J. A., & Wandersman, A. (2012). The Quality Implementation Framework: A synthesis of critical steps in the implementation process. American Journal of Community Psychology.

The PARIHS (Promoting Action on Research Implementation in Health Services) framework proposes that successful implementation is a function of the strength of the evidence supporting the intervention, the context in which the intervention is implemented, and the facilitation provided to support implementation.

Harvey, G., & Kitson, A. (2015). Implementing evidence-based practice in healthcare: A facilitation guide. London, England, & New York, NY.: Routledge. 

Kitson, A., Rycroft–Malone, J., Harvey, G., McCormack, B., Seers, K., & Titchen, A. (2008). Evaluating the successful implementation of evidence into practice using the PARIHS framework: Theoretical and practical challenges. Implementation Science, 3(1).

The CFIR website describes the framework as a compilation of constructs that have been associated with effective implementation in one organizing framework.

The CFIR provides a menu of constructs that can be used in a range of applications – as a practical guide for systematically assessing potential barriers and facilitators in preparation for implementing an innovation, to providing theory-based constructs for developing context-specific logic models or generalizable middle-range theories.

The CFIR was developed by implementation researchers affiliated with Veterans Affairs (VA) Diabetes Quality Enhancement Research Initiative (QUERI). The VA QUERI was launched in 1998 as part of a system-wide transformation aimed at improving the quality of healthcare for veterans and continues to contribute to this effort by implementing research findings and innovations into routine clinical practice.

This link takes you to a description of each construct, with links to ‘CFIR Wiki,’ which has more detail on each construct, including links to measures.

Table of CFIR Constructs can be found here.

Damschroder, L., Aron, D., Keith, R., Kirsh, S., Alexander, J., & Lowery, J. (2009). Fostering implementation of health services research findings into practice: A consolidated framework for advancing implementation science. Implementation Science, 4(50). 

RE–AIM is used to evaluate the impacts of population-based public health interventions. It can be used for planning the dissemination of EBPs:

Reach: proportion of the target population that participated in the intervention

Efficacy: success rate if implemented as in guidelines, defined as positive outcomes minus negative outcomes

Adoption: proportion of settings, practices, and plans that will adopt this intervention

Implementation: extent to which the intervention is implemented as intended in the real world

Maintenance: extent to which a program is sustained over time

The National Cancer Institute uses RE–AIM criteria to evaluate programs in their Research-tested Intervention Programs (RTIP).

An example can be found here.

Last Updated: 09/15/2017