Toward More Precision in Implementation Science in the Age of COVID-19

June 26, 2020 by Mindy Clyne, David A Chambers, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland and Muin J. Khoury, Office of Genomics and Precision Public Health, Centers for Disease Control and Prevention, Atlanta, Georgia

Implementation Science with COVID-19

Implementation science (IS) is “the study of methods to promote the adoption and integration of evidence-based practices, interventions, and policies into routine health care and public health settings to improve the impact on population health.” The various factors that must be taken into consideration in designing, conducting, and evaluating IS studies dictate an inherent “precision” to ensure the success of evidence-based practice implementation within studied populations. These include but are not limited to

consideration of the different stakeholders involved;
the context in which an intervention takes place;
identification of appropriate implementation strategies;
the multi-level, multi-sectoral, and dynamic nature of implementation; and
the need to consider scale-up and sustainability.

In a recent article, one of this blog’s authors (DAC) explored the intersection between implementation science and COVID-19. Three major areas of integration between implementation science (IS) and the COVID-19 pandemic were highlighted: 1) how IS concepts can help the health care and public health communities understand COVID-19, 2) how implementation scientists can help respond to COVID-19, and 3) what lessons IS can learn from COVID-19.

The COVID-19 pandemic has shed a new light on the importance of implementation science both in delivering the right interventions for the control of the pandemic (direct impact) as well as adapting to the disruption in health services as a result of the pandemic (indirect impact such as immunization).

IS studies on the direct COVID-19 impact are getting under way. One published study compared the time to initiate and the effectiveness of social distancing. The authors assessed how state public health agencies had implemented social distancing approaches. This should prompt implementation scientists to help identify more precise strategies for different intervention approaches.

IS research on the indirect impact of COVID-19 will address adaptation of interventions including screening programs, prevention, and treatment services (e.g., immunization, blood pressure control, physical activity). New tools and technologies within the realm of precision health (e.g., telehealth) can be used to adapt interventions. A recent publication reported on the successful feasibility of telehealth to minimize risk for COVID-19 exposure for high-risk obstetric patients. The ongoing priority for implementation scientists to mitigate health inequities offers opportunities for use of big data (e.g., socio-economic, geographic, and genomic data). Additionally, the use of digital technologies such as mobile phone applications and measures of mobility health outcomes, and artificial intelligence and deep learning for modeling may help advance IS activities.

We expect that the COVID-19 pandemic will provide opportunities for innovation in IS towards more precision, while IS remains grounded in its core principles. In the short term, we could see more rapid-cycle studies, whereby ongoing data collection and continuous monitoring and feedback will enable faster translation time. Additionally, collaboration and coordination among researchers and practitioners, across geographic regions and between public and private sectors, will continue to increase. Strategies that use precision and digital technologies have been critical for health care continuity during the pandemic, so adaptation of interventions using these tools may become more commonplace even after we get back to the “new” normal.

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