Designs and methods for implementation research: Advancing the mission of the CTSA program

Hwang, Soohyun; Birken, Sarah A.; Melvin, Cathy L.; Rohweder, Catherine; Smith, Justin D.

doi:10.1017/cts.2020.16

Cited by 51 publications

(41 citation statements)

References 68 publications

(60 reference statements)

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“…Implementation science focuses on applying rigorous frameworks, measures, and research designs,12 to study what, why, and how interventions are implemented in real world settings and tests strategies to improve their outcomes and impact.This helps policy makers, managers, and implementers understand existing and emerging evidence based interventions and choose strategies to implement them that take account of (and modify) contextual factors that influence success. Evidence produced through implementation research can inform countries’ responses as epidemics emerge and as strategies are considered and enacted globally and locally for subsequent phases.…”

mentioning

confidence: 99%

Integrating implementation science into covid-19 response and recovery

Hirschhorn

Smith

Frisch

et al. 2020

BMJ

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National and subnational responses to the covid-19 pandemic have varied in their implementation of critical evidence based interventions, including social distancing, handwashing, SARS-CoV-2 testing, and contact tracing. The variable success of such measures also reflects differences in the nature of initial outbreaks and contextual factors within communities and health systems. Implementation science methods can make all the difference, allowing us to build on these successes and ensure that new epidemiological and sociobehavioural models and other innovations can sustain and accelerate action to end this pandemic.Implementation science focuses on applying rigorous frameworks, measures, and research designs, 1 2 to study what, why, and how interventions are implemented in real world settings and tests strategies to improve their outcomes and impact.This helps policy makers, managers, and implementers understand existing and emerging evidence based interventions and choose strategies to implement them that take account of (and modify) contextual factors that influence success. Evidence produced through implementation research can inform countries' responses as epidemics emerge and as strategies are considered and enacted globally and locally for subsequent phases. Integrating this approach requires strong diverse partnerships-including among implementers, researchers, policy makers, and communities-within and across countries.The rapid spread of covid-19 highlights the need to use implementation science methods from the outset of outbreaks. Evidence from the 2014 Ebola outbreak on how strategies were chosen to tackle the epidemic and mitigate the damage to essential health services was slow to emerge and limited in its dissemination. 3 As a result, knowledge on what worked then and might be relevant in the covic-19 pandemic was lost. 4 5To respond effectively to covid-19, countries must identify, understand, and incorporate knowledge learnt throughout the course of the pandemic. Many countries are implementing established interventions. But they are not always applying the learning that implementation science can drive to select, analyse, and adapt data driven strategies for effective outcomes in different contexts and at different stages of the evolving pandemic. 6-8 Implementation differencesSouth Korea and the UK show this well, having implemented similar evidence based interventions for the covid-19 pandemic at different speeds and with implementation strategies that had different contexts and differing results. South Korea responded successfully, rapidly implementing key interventions for pandemic control, including widespread testing, early contact tracing, building health system capacity, and community education. 9 Its implementation strategies reflected the nature of the epidemic (first wave and concentrated), a strong health system and public health capacity and capability, and receptive sociopolitical and community attitudes based on experience with SARS. For example, high rates of mobile phone coverage...

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confidence: 99%

Integrating implementation science into covid-19 response and recovery

Hirschhorn

Smith

Frisch

et al. 2020

BMJ

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“…When quasi/experimental designs [3,4] are used, the independent variable(s) (i.e., the strategies that are introduced or manipulated or that otherwise differentiate study conditions) should be clearly labeled. This is important for internal validity and for differentiating conditions in multi-arm studies.…”

Section: For Quasi/experimental Designsmentioning

confidence: 99%

“…In the context of comparative implementation trials [3,4], a study of two or more competing implementation strategies are introduced for the purposes of the study (i.e., the comparison is not implementation-as-usual), and there is a need to indicate the determinants, strategies, mechanisms, and potentially outcomes that differentiate the arms (see Additional File A2). As comparative implementation can involve multiple service delivery systems, the determinants, mechanisms, and outcomes might also differ, though there must be at least one comparable implementation outcome.…”

Section: For Comparative Implementation Trialsmentioning

confidence: 99%

“…The IRLM can be used with various types of implementation studies and at various stages of research, from planning and executing to reporting and synthesizing implementation studies. Example IRLMs are provided for various common study designs and scenarios, including hybrid designs and studies involving multiple service delivery systems [3,4]. Last, we describe the preliminary use of the IRLM and provide results from a posttraining evaluation.…”

Section: Introductionmentioning

confidence: 99%

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The Implementation Research Logic Model: a method for planning, executing, reporting, and synthesizing implementation projects

2020

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Background Numerous models, frameworks, and theories exist for specific aspects of implementation research, including for determinants, strategies, and outcomes. However, implementation research projects often fail to provide a coherent rationale or justification for how these aspects are selected and tested in relation to one another. Despite this need to better specify the conceptual linkages between the core elements involved in projects, few tools or methods have been developed to aid in this task. The Implementation Research Logic Model (IRLM) was created for this purpose and to enhance the rigor and transparency of describing the often-complex processes of improving the adoption of evidence-based interventions in healthcare delivery systems. Methods The IRLM structure and guiding principles were developed through a series of preliminary activities with multiple investigators representing diverse implementation research projects in terms of contexts, research designs, and implementation strategies being evaluated. The utility of the IRLM was evaluated in the course of a 2-day training to over 130 implementation researchers and healthcare delivery system partners. Results Preliminary work with the IRLM produced a core structure and multiple variations for common implementation research designs and situations, as well as guiding principles and suggestions for use. Results of the survey indicated a high utility of the IRLM for multiple purposes, such as improving rigor and reproducibility of projects; serving as a “roadmap” for how the project is to be carried out; clearly reporting and specifying how the project is to be conducted; and understanding the connections between determinants, strategies, mechanisms, and outcomes for their project. Conclusions The IRLM is a semi-structured, principle-guided tool designed to improve the specification, rigor, reproducibility, and testable causal pathways involved in implementation research projects. The IRLM can also aid implementation researchers and implementation partners in the planning and execution of practice change initiatives. Adaptation and refinement of the IRLM are ongoing, as is the development of resources for use and applications to diverse projects, to address the challenges of this complex scientific field.

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“…Leppin et al 4 propose an integrated framework where D&I sciences are used to identify strategies for routinely and proactively accelerating research translation. Similarly, Hwang et al 5 propose utilization of novel implementation science methodologies to advance health in the US and worldwide, while Yousefi et al 6 discuss interactions between health equity research and D&I science, underlying the importance of translational research with the focus on equitable D&I. Bennett et al highlighted a need for research integration into Learning Health Systems (LHS). 7 Aarons et al 8 and Dolor et al 9 examined opinions of D&I researchers and CTSA leaders to identify strategies that could promote team science and improve population health.…”

Section: Broad Themes From Papers Published In This Jcts Special Issumentioning

confidence: 99%

Introduction to the JCTS special issue on Dissemination and Implementation Sciences

Stevens¹,

Tobin

2020

J. Clin. Trans. Sci.

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Designs and methods for implementation research: Advancing the mission of the CTSA program

Cited by 51 publications

References 68 publications

Integrating implementation science into covid-19 response and recovery

Integrating implementation science into covid-19 response and recovery

The Implementation Research Logic Model: a method for planning, executing, reporting, and synthesizing implementation projects

Introduction to the JCTS special issue on Dissemination and Implementation Sciences

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