Additional Resources

Implementation Science Basics

The Consortium for Implementation Science at University of North Carolina has a listserv with monthly newsletters and a section dedicated to a curated collection of resources, many of which have helpful accompanying commentary (“Resource of the Month“). For example, included in the list is NCI’s “At A Glance” guide for implementation science. 

Check out Hull and colleagues’ ImpRes Tool developed to guide design of high quality implementation research projects, available online.

Many researchers struggle with understanding, choosing, and applying theory in implementation science. A growing number of resources can help with this. Laura Damschroder recently published “Clarity out of Chaos: Use of Theory in Implementation Research, an article about implementation science theories that provides a high-level structure for thinking about theory and guidance on choosing, with example applications. In 2012, Tabak and colleagues conducted one of the earliest scans of implementation science models, theories, and frameworks (TMFs), identifying and classifying 61 of them. Nilsen and Bernhardsson published a 2019 narrative review of 8 determinant frameworks.  Sarah Birken and colleagues conducted a survey of 223 implementation researchers who collectively, reported the use of 100 different TMFs. Though the CFIR is one of the most widely cited frameworks, it may not be the best choice for you. This team extended their work by publishing The T-CaST Tool that provides a checklist to help guide selection of an appropriate TMF to guide your work. 

Prescriptive Frameworks and Models

The CFIR is a “determinant” framework because it provides a broad taxonomy of factors that influence implementation. In contrast, prescriptive theories and frameworks describe sequenced or interrelated activities to accomplish successful implementation (See Per Nilsen’s helpful classification of theories). Below is a list of a few frameworks and approaches that provide prescriptive guidance for conducting implementation: 

  • Active Implementation (AI) Hub : The AI Hub was recently redesigned and updated. It is a free, online learning environment geared toward anyone involved in active implementation or scaling up of programs and innovations. The site’s goal is to increase the knowledge and improve the performance of individuals engaged in actively implementing an innovation. They provide many helpful tutorials, tools and forums that provide in-depth information on the process of implementation.
  • Getting to Outcomes (GTO) : The GTO provides a model for carrying out implementation and support aimed at enhancing implementers’ capacity. The GTO model describes ten steps for successful implementation. The Quality Implementation Framework provides an update to this body of research.
  • Institute for Healthcare Improvement (IHI) Breakthrough Process : IHI’s Innovation Series white papers were developed to further their mission of improving the quality and value of health care. The findings and tools in these reports provide readers with an opportunity to understand and evaluate the issues, and begin testing changes that can help your organization make breakthrough improvements.
  • Recommendations for evaluation of health care improvement initiatives : In this paper, the authors argue for formative-theory driven evaluation of implementations that is iterative in nature and is changed to quickly reflect the realities of an implementation environment. The cyclical feedback loop advocated here can be categorized as evaluation of strategies and phases of improvements.
  • Stages of Implementation Completion (SIC) : This body of research describes and tests approaches to predict program start-up using the stages of implementation measure; the Stages of Implementation Completion (SIC) was developed as part of an implementation trial in 53 sites. It is unique in identifying the amount of time spent on each implementation activity and the proportion of activities completed. The results of this paper suggest that completing the first three stages of the SIC (Engagement, Consideration of Feasibility, Readiness Planning) relatively quickly is a strong predictor of successful implementation.

Quantitative Measures

The Seattle Implementation Research Conference’s Measures Project is in the process of identifying measurement instruments and mapping them to the CFIR and an outcomes framework; over 400 instruments have been identified and the SIRC is in the process of evaluating each instrument. Check back regularly for updates.

In addition, you can reference our Quantitative Data page and the “Quantitative Measures” sections within the individual constructs.

Training Resources

There are a number of training resources available for those interested in delving more deeply into implementation theory. Below is a list of materials and events. These events are offered as a resource. All are supported by non-profit funding (e.g., NIH grants) that are dedicated to building capacity and advancing the science of implementation. If you know of any training resources, please let us know and we will post as appropriate.

Training Institute for Dissemination and Implementation Research in Health (TIDIRH): The TIDIRH holds yearly conference dedicated to dissemination and implementation. It is run by Harvard University and the Dana-Farber Cancer Institute, with support from the NIH and the U.S. Department of Veterans Affairs.

Implementation of Evidence Based Practices from Evidence Based Behavioral Practice : Provides a compilation of resources and training aimed at bridging the gap between research and practice.


A Glossary provides a few definitions for frequently used terms in implementation. If you have suggestions for new terms to add to the Glossary or any other comments, please contact us