Implementation research investigates the best methods and strategies for sustainably integrating evidence-based health interventions into new settings.
The steps outlined below will help orientate your thinking as you develop and implement your project. You may find that you consider or complete the steps in a different order to that given.
Engage stakeholders
Stakeholder engagement is the process of involving and working together with stakeholders before, during, and after the research project. It helps to ensure the project’s relevance to local communities and health systems as well as its sustainability, bridging the gap between research, practice, and policy. Engaging stakeholders is critical from project ideation, throughout the project duration, and afterwards in sustainment and knowledge translation.
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Fundamentals Programme – click here
Module 2, Lecture 2A: Who, what, when, and why: the importance of stakeholders (Presented by Lijing Yan)
Advanced Programme – click here
Module 2, Lecture 2A: Stakeholders – who should be involved in scaling up? (Presented by Aneth Dinis)
Module 3, Lecture 3A: Who should be involved in implementing NCD interventions at scale? (Presented by Rachel Sturke) – coming soon
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💻 Websites and hubs
- GACD stakeholder engagement resource collection – click here
- NIH Fogarty International Center Toolkit: Participatory research models and building stakeholder relationships – click here
📑 Publications and papers
- The science of stakeholder engagement in research: classification, implementation, and evaluation (Goodman and Thompson, 2017) – click here
- How to engage stakeholders in research: design principles to support improvement (Boaz et al. 2018) – click here
Formulate your research question
A good implementation project will start with a clearly articulated research question and a well-reasoned hypothesis. You should be able to demonstrate how and why the evidence-based intervention you wish to implement will be effective in your chosen study setting(s).
Peters and colleagues (2013) suggest that implementation research questions can be categorised by the objectives the project seeks to achieve, namely, exploring, describing, influencing, explaining, and predicting.
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📑 Publications and papers
- Implementation research: what it is and how to do it (Peters et al. 2013) – click here
- What research questions should the implementation evaluation be asking? (Resource Platform for Knowledge and Practice, the University of Melbourne) – click here
- Appendix 1.7 Example IR projects and questions; in Fundamentals of implementation research (MEASURE Evaluation, 2012) – click here
Select your theories, models, and/or frameworks
Theories, models, and frameworks can be useful before you begin implementation (for guiding the process), during implementation (for real-time adjustments), and after implementation (for evaluation). They can help you to understand what you expect to happen and what contextual factors you need to measure. It can be as simple as developing a driver diagram, or as complex as mapping out multiple interacting frameworks.
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Fundamentals Programme – click here
Module 3, Lecture 3A: Theories, models, and frameworks for implementation research (Presented by Pilvikki Absetz)
Module 3, Lecture 3B: Mechanisms of change (Presented by Pilvikki Absetz)
Advanced Programme – click here
Module 3, Lecture 3A: Overview of theories, models, and frameworks for implementation science (Presented by Brian Oldenburg)
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💻 Websites and hubs
- The RE-AIM Framework website – click here
- The CFIR website – click here
- The EPIS Framework website – click here
📑 Publications and papers
- Making sense of implementation theories, models and frameworks (Nilsen, 2015) – click here
- Ten recommendations for using implementation frameworks in research and practice (Moullin et al. 2020) – click here
- Models in dissemination and implementation research: useful tools in public health services and systems research (Tabak et al. 2013) – click here
- A guide to systems-level, participatory, theory-informed implementation research in global health (Seward et al. 2021) – click here
- The Implementation Research Logic Model: a method for planning, executing, reporting, and synthesizing implementation projects (Smith et al. 2020) – click here
Assess the context
Assessing and understanding context is not just an optional add-on, but a fundamental requirement for successful non-communicable disease programme implementation research. By understanding the local context, researchers can tailor interventions to the specific needs and challenges of the target population, increasing relevance and effectiveness. This might involve adapting communication strategies, incorporating traditional practices, or addressing logistical barriers to access.
Some examples of how context can influence NCD programme implementation are noted below:
- Socioeconomic context: A programme promoting healthy eating habits might need to consider the affordability of fresh produce in a food desert.
- Cultural context: Addressing smoking cessation in a community with strong tobacco-growing traditions requires acknowledging cultural values and livelihoods.
- Healthcare system context: A mobile health intervention for diabetes management needs to integrate with existing healthcare infrastructure and provider workflows.
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Fundamentals Programme – click here
Module 4, Lecture 4A: COntext in implementation research (Presented by Zahra Aziz)
Module 4, Lecture 4B: Practical application – Context in the PRONASA project (Presented by Juliana Kagura)
Module 4, Lecture 4C: Practical application – Context in the Access Cancer Care India project (Presented by Arunah Chandran)
Advanced Programme – click here
Module 4, Lecture 4A: Context for interventions at scale (Presented by Dike Ojji)
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💡 GACD workshops
- Working with context to implement non-communicable disease programmes (2023) – click here
- Context, complexity, and the rise of case study research for implementation (2022) – click here
📑 Publications and papers
- The role of context in implementation research for non-communicable diseases: Answering the ‘how-to’ dilemma (Daivadanam et al. 2019) – click here
- Context matters in implementation science: a scoping review of determinant frameworks that describe contextual determinants for implementation outcomes (Nilsen and Bernhardsson, 2019) – click here
- Defining and assessing context in healthcare implementation studies: a systematic review (Rogers et al. 2020) – click here
- Studying complexity in health services research: desperately seeking an overdue paradigm shift (Greenhalgh and Papoutsi, 2018) – click here
- Unraveling implementation context: the Basel Approach for coNtextual ANAlysis (BANANA) in implementation science and its application in the SMILe project (Mielke et al. 2022) – click here
Design appropriate implementation strategies
At the core of implementation research are the strategies employed to integrate the evidence-based intervention(s) into the existing healthcare context. Identifying appropriate and effective strategies for your project can be make-or-break. They should be co-developed with stakeholders and informed by a comprehensive analysis of the context.
Implementation strategies might be discrete (a single technique or approach) or multifaceted (a combination of two or more discrete strategies). In addition, the way you report your strategies should be standardised so that other investigators and implementers can learn from your research findings and apply the learning in other settings.
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Fundamentals Programme – click here
Module 1, Lecture 1B: Evidence-based intervention or implementation strategy? (Presented by Leslie Johnson)
Module 5, Lecture 5A: Implementation strategies (Presented by Leslie Johnson)
Advanced Programme – click here
Module 4, Lecture 4B: Strategies for interventions at scale (Presented by Lisa Hirschhorn)
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📑 Publications and papers
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- Getting a clinical innovation into practice: An introduction to implementation strategies (Kirchner et al. 2020) – click here
- A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project (Powell et al. 2015) – click here
- Use of concept mapping to characterize relationships among implementation strategies and assess their feasibility and importance: results from the Expert Recommendations for Implementing Change (ERIC) study (Waltz et al. 2015) – click here
- Beyond “implementation strategies”: classifying the full range of strategies used in implementation science and practice (Leeman et al. 2017) – click here
- Development of a framework and coding system for modifications and adaptations of evidence-based interventions (Stirman et al. 2013) – click here
Develop your research methods
The broad scope of implementation research means that approaches employed by a range of disciplines may be useful templates for tackling your research question. For example, your design may draw from operations research, health systems research, impact evaluation, economic evaluation, or many others.
Relevant experimental designs include randomised controlled trials (e.g., cluster, step-wedged, hybrid types 1–3), quasi-experimental designs (e.g., interrupted time series), or mixed methods (e.g., sequential exploratory, concurrent embedded).
Your research methods are the tools and processes you use to gather and analyse data. Methods might include surveys, interviews, focus groups, experiments, or secondary data analyses; often multiple methods are employed in implementation research projects.
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Fundamentals Programme – click here
Module 5, Lecture 5B: Study designs for implementation research – part 1 (Presented by Vilma Irazola)
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💡 GACD workshops
- GACD-CONNECT: From pragmatic trials to effectiveness-implementation hybrid designs, presented by Nadine Seward – click here
📑 Publications and papers
- An overview of research and evaluation designs for dissemination and implementation (Brown et al. 2017) – click here
- Effectiveness- implementation hybrid designs: combining elements of clinical effectives and implementation research to enhance public health impact (Curran et al. 2012) – click here
- Best practices for mixed methods research in the health sciences (Creswell et al. 2011, for the Office of Behavioral and Social Sciences Research) – click here (pdf)
- Mixed method designs in implementation research (Palinkas et al. 2011) – click here
Choose your variables and outcome measures
Measuring aspect of ongoing implementation of healthcare innovations is a significant challenge to the field, not least because of the intrinsically complex nature of what an implementation research project is trying to achieve. There is complexity at all levels of the Socioeconomic Model, as well as complexity in the implementation strategies.
A review by Rabin and colleagues (2016) identified 17 measure resources and reported that the number of constructs ranged from 1 to 359 and the number of measures ranged from 1 to 450+. The quality, validity, and appropriateness of measures should be evaluated during selection.
Implementation outcomes are defined by Proctor et al. (2011) as “the effects of deliberate and purposive actions to implement new treatments, practices and services and are distinct from service and client (patient) outcomes”. The authors categorise such outcomes into three groups: implementation outcomes, services outcomes, and client outcomes.
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Fundamentals Programme – click here
Module 5, Lecture 5D: Choosing and using implementation outcomes (Presented by Enola Proctor)
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💻 Websites and hubs
- GACD Data outcomes standardisation resources – click here
📕 Books
- Chapter 14: Measurement issues in dissemination and implementation research (Lewis et al. 2018); In: Dissemination and implementation research in health: translating science to practice (Brownson et al. New York: Oxford University Press) – click here
📑 Publications and papers
- Measuring factors affecting implementation of health innovations: a systematic review of structural, organizational, provider, patient, and innovation level measures (Chaudoir et al. 2011) – click here
- Measurement resources for dissemination and implementation research in health (Rabin et al. 2016) – click here
- Instrumentation issues in implementation science (Martinez et al. 2014) – click here
- Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda (Proctor et al. 2011) – click here
Secure funding
It has been proposed by Proctor et al, that there are ten ‘key ingredients’ to writing successful implementation research grants. The ingredients prompt researchers to consider their project from numerous standpoints including access and equity gaps, evidence-based practices, conceptual models, stakeholder engagement, setting readiness, implementation strategies, team experience, feasibility of methods, measurement and analysis, and alignment with current policy and funding procedures.
Get started with one of our free e-Hub lectures
Fundamentals Programme – click here
Module 6, Lecture 6B: The GACD funding model and grant applications (Presented by Carolyn Johnson)
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💻 Websites and hubs
- See our Resource and toolkit library – scroll down to the grantsmanship resource section
- GACD Research funding application guidance – click here
📑 Publications and papers
- Concocting that magic elixir: Successful grant application writing in dissemination and implementation research (Brownson et al. 2015) – click here
- Standardizing an approach to the evaluation of implementation science proposals (Crable et al. 2018) – click here
- Writing implementation research grant proposals: ten key ingredients (Proctor et al. 2012) – click here
Knowledge sharing
Once you have completed the data collection and analysis, the work is not over yet! Knowledge sharing is a crucial component of good research practice. Your findings, recommendations, and next steps should be clearly communicated to your stakeholders in a suitable manner. Knowledge sharing may take the form of community meetings, webinars, newspaper articles, or policy dialogues, to name a few. One form of knowledge sharing that may be appropriate for your project is through academic journals.
In addition, effective knowledge sharing also contributes to developing the field of implementation science. As a science, there is a need to systematically organise and curate accumulated knowledge about a phenomenon in the world. As well as undertaking new investigations, there is a need to improve the use and uptake of current implementation knowledge, including the application of existing frameworks, guidelines, and tools.
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💻 Websites and hubs
- Implementation Science journal submission guidelines – click here
📑 Publications and papers
- Ten simple rules for innovative dissemination of research (Ross-Hellauer et al. 2020) – click here
- How to give a good talk (Alon, 2009) – click here
- Standards for Reporting Implementation Studies (StaRI) Statement (Pinnock et al. 2017) – click here
- Enhancing the reporting of implementation research (Wilson et al. 2017) – click here
Scaling up and scaling out
The World Health Organization and ExpandNet (2011) define scale up as “[d]eliberate efforts to increase the impact of successfully tested health innovations so as to benefit more people and to foster policy and programme development on a lasting basis.”
Scaling up (expanded implementation to similar populations and delivery systems) and/or scaling out (implementation in new populations, delivery systems, or both) is the natural next step to explore once you have demonstrated effective implementation through your primary project.
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Advanced Programme – click here
See our Advanced Programme which takes a deep-dive into scaling up non-communicable disease programmes
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🌍 WHO guidelines
- Beginning with the end in mind: planning pilot projects and other programmatic research for successful scaling up (WHO and ExpandNet, 2011) – click here
- Nine steps for developing a scaling-up strategy (WHO and ExpandNet, 2010) – click here
- Practical guidance for scaling up health service innovations (WHO, 2009) – click here
De-implementation and de-adoption
Niven and colleagues (2015) describe how the “adoption of clinical practices that are later de-adopted imposes substantial inefficiencies on the healthcare system”, highlighting that the time, money, and resources used for this inefficient process could have been diverted to other activities. Therefore, efficient de-adoption processes are needed to improve the quality of healthcare provided to patients.
Wang and colleagues (2018) describe four types of de-implementation – (i) partial reduction; (ii) complete reversal; (iii) substitution with related replacement; and (iv) substitution with unrelated replacement of existing practice. They propose that de-implementation efforts should be coupled with the implementation process.
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📑 Publications and papers
- Towards understanding the de-adoption of low-value clinical practices: a scoping review (Niven et al. 2015) – click here
- Studying de-implementation in health: an analysis of funded research grants (Norton et al. 2017) – click here
- Understanding mis-implementation in public health practice (Brownson et al. 2015) – click here
- Working smarter not harder: Coupling implementation to de-implementation (Wang et al. 2018) – click here
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