Implementation science (IS) conventionally addresses the gap between healthcare interventions that have been shown to work, and their successful adoption and routine use by service providers and individuals who may benefit from them in ‘real world’ settings. After efficacy studies discover the interventions yielding better health outcomes, IS focuses on factors and processes or the ‘how and why’ interventions are adopted, implemented and sustained in practice-based settings. IS is also focused on “the use of strategies to introduce or change evidence-based health interventions within specific settings” (Proctor et al, 2009). This means that strategies are purposefully chosen,and then tested for implementation effectiveness. Findings can be used to develop better strategies and guidelines to improve the uptake of successful implementation strategies, and enhance the potential for scale-up of programs across diverse settings with the goal of maximizing their uptake and impact. As Glasgow et al. note, there is a significant increase in the ‘return on investment’ of healthcare innovations and discoveries by optimizing intervention uptake, implementation, engagement, and scale-up (Glasgow 2012: 1274).
IS research usually draws upon a broad swath of conceptual frameworks, theoretical models, and methodological approaches from different disciplines, which are particularly well-suited to addressing research questions around implementation of interventions, and the strategies enabling their delivery.
For additional resources on Implementation Science, see:
- Bauer et al. 2015. An introduction to implementation science for the non-specialist. 2015 Sep 16. BMC Psychology. 3:32. doi: 10.1186/s40359-015-0089-9.
- Glasgow et al. 2012. National Institutes of Health Approaches to Dissemination and Implementation Science: Current and future directions. July 2012. American Journal of Epidemiology. 102(7): 1274-1281.
- Koh et al. 2018. An orientation for new researchers to key domains, processes, and resources in implementation science. 2018 Nov 16. Translational Behavioral Medicine. doi: 10.1093/tbm/iby095.
- Proctor et al. 2009. Implementation research in mental health settings: an emerging science with conceptual, methodological and training challenges. 2009 Jan. Administration and Policy in Mental Health. 36(1). doi: 1007/s10488-008-0197-4.
Implementation Science (IS) focused on population health outcomes is similar to conventional IS, but, aligned with population health principles, has an explicit intent to:
- Improve health outcomes and health status of groups of individuals, including the distributions of outcomes across groups with a particular focus on disparities by race, socioeconomic status, gender, ethnicity and sexual orientation, for example.
- Investigate the interactions of factors such as biology, health care systems, psychosocial, economic, and physical environments, and the impact of policies across population sub-groups and across individuals’ life spans (Lobb and Colditz, 2013).
- Use evidence-based interventions in the form of programs, policies, and strategies that have a measurable impact on health promotion, morbidity and mortality at the population level. These strategies will target changes at individual, organizational, societal and policy-making levels (Stamatakis Vinson, and Kerner 2012).
- Mitigate, minimize, or prevent health disparities that can arise because of unequal access to and/or uptake of effective interventions at scale.
IS through a public health lens is concerned with:
- Studies of implementation conducted at scale, as well as across geographies, populations, and over time;
- Assessing the uptake of implementation strategies and evaluating the effectiveness and impact of intervention, strategies, programs and policies aimed at improving population health outcomes at scale;
- Investigations of the effects across heterogeneous populations, with close monitoring of differential effects and ensuring there are methods to redress unequal outcomes, health inequities or disparities that may arise from implementation;
- Engagements within diverse settings taking a multi-sector approach;
- Establishing, monitoring and evaluating outcomes and impact of interventions using mixed methods approaches.
For additional resources on IS for Population Health, see:
- Lobb, R and GA Colditz. Implementation Science and its Application to Population Health. 2013. Annual Review of Public Health. 34:235-251.
- Stamatakis, KA, Vinson, CA, and Kerner JF. 2012. Dissemination and Implementation Research in Community and Public Health Settings in Dissemination and Implementation Research in Health: Translating science to practice, Brownson et al, eds. doi:10.1093/acprof:oso/9780199751877.003.0017.
Different IS theories, models and frameworks place the emphasis at different levels, or at multiple levels of change (i.e., individual, interpersonal/social, setting/organizational, societal/structural). It is important to figure out at which level you would like to be working, and then select the theory/theories to help study and change factors and processes that influence implementation at that appropriate level. For example, one theory may support the development of provider-level interventions to overcome clinician barriers to adopting a new practice, while another may seek to target the organization at the system or structural level.
In addition, it is important to decide the degree of experimentation, that is, if the researcher plans to observe or directly test implementation strategies, and if experimentation will be incorporated into the study by using, for example, a hybrid intervention-implementation effectiveness design (see below for description). Similarly, IS theories may be applied to the study of planning (intervention selection), implementation use processes (intervention use), or outcomes (results of use) phases; the period of focus will guide which theories will be most helpful based on what is the focus of inquiry. Another choice will involve the degree of community engagement/partnership to plan and implement the study; in turn, different IS theories will inform this process. Each of these choices require different study designs, data collection methods and types (qualitative, quantitative, or a combination; surveys, interviews, observations, cluster RCTs, etc).
When thinking about incorporating an IS theory, model or conceptual framework into your study, consider:
- What are the key questions the study aims to address and the assumed mechanisms of change to be brought about by the intervention or strategy?
- Are you piloting an implementation strategy to deliver an evidence-based intervention? Comparing an implementation strategy to usual care? Comparing implementation Strategy A to Strategy B?
- What phase are you studying: formative, evaluative, or both phases? Do you need a framework that helps you or your team plan what to implement, as well as the implementation process?What is the level at which implementation is occurring? Providers? Clinic? Community? Policy? Can the implementation be controlled as part of the study design?
- Do you need a theory or framework to study the development, implementation, or uptake/use of an intervention? Are you interested in adaptation, or questioning whether a currently used practice should be de-implemented? Is implementation the only endpoint of the study? Or is there also a health endpoint?
- Methods intended and available data sources
- Do you need a framework that uses quantitative or qualitative methods, or a combination of both? (i.e., mixed methods, site surveys, cluster RCTs, stepped wedge, etc)
- Resources available for data collection and analysis
- How simple or elaborate is your design?
- Who and how many specialists do you need to engage?
- Community/partner engagement
- Do you need a framework that facilitates multi-stakeholder and/or multi-sector involvement?
These are questions to keep in mind as you read through the subsequent sections that described specific IS theories, models, and frameworks, and methods and design features. Your research aims should “match” to the selected IS theories, model(s) or frameworks to support the achievement of your project’s scientific goals. It is important to remember that this may require the combining of more than one IS theory, model, or framework. For example, RE-AIM may assist in getting at the measurable effectiveness of implementation, but it needs to be combined with The Consolidated Framework on Implementation Research (CFIR) to understand the factors or processes shaping implementation.
Additional general resources to learn more about Implementation Science
- ACCORDS Dissemination and Implementation Resource Guide. University of Colorado.
- National Cancer Institute. Research Tools. IS Theories, Frameworks, and Models.
- Implementation Science Exchange: website devoted to IS resources including theories, frameworks, and models selection, University of North Carolina at Chapel Hill.
- IMPSIX. Theory, Model, and Framework Comparison and Selection Tool, University of North Carolina at Chapel Hill.
- Implementation Guide. Department of Veterans Health Administration, Health Services Research & Development, Quality Enhancement Research Initiative.
- Beidas, R.S. et al. (2013). Dissemination and Implementation Science: Research Models and Methods. In Comer, J.S. & Kendall, P.C. (Eds.), The Oxford Handbook of Research Strategies for Clinical Psychology. Oxford University Press.