Realizing the Potential of Digital Health Through Implementation Science

In 2022, the National Cancer Institute’s (NCI) Division of Cancer Control and Population Sciences (DCCPS) identified digital health as one of six key research priority areas where immediate and intensified focus could significantly accelerate scientific progress and increase the impact of DCCPS-sponsored research. Digital health encompasses technologies that can be used to improve health and well-being, such as mobile health apps, wearable devices, and telemedicine as well as the infrastructure and ecosystems that enable the integration and analysis of data collected through these platforms. In the context of cancer, digital health can support health promotion and behavior change, disease self-management, and care delivery across the cancer control continuum, in addition to advancing clinical, behavioral, and epidemiological research.

Digital health tools have the potential to improve cancer outcomes and enhance care delivery, but only if they are deployed effectively, equitably, and at scale. Studies have shown that the efficacy of digital health interventions established in randomized controlled trials often fails to replicate under real-world conditions. There are many potential reasons for this, including the fact that trials have strict eligibility criteria, studies are usually conducted in highly resourced settings, and technology can become outdated by the time a study concludes.¹ These are important considerations given that adequate uptake and adherence is needed for digital interventions to achieve meaningful population-level impact. It is therefore critical to conduct implementation research to examine how the integration and use of digital interventions can be optimized and sustained in real-world settings to improve cancer outcomes.

Implementation of Digital Health Interventions

There are many potential barriers that can hinder the adoption and use of digital interventions in the health care context, such as lack of interoperability, limited staff time and resources for implementation activities, and incongruency with existing workflows. Therefore, it is important that developers of digital health tools design these technologies with dissemination and implementation in mind from the outset, consider the effects of the intervention on existing practices, and involve stakeholders throughout the development and implementation process. Approaches from implementation science are key to ensuring these potentially transformative tools are successfully integrated into routine practice. Some strategies that have been used to implement cancer-relevant digital health innovations in clinical settings include leadership engagement,² quality improvement training and academic detailing,³ educational outreach to patients,² use of implementation champions, practice facilitation, and provision of technical assistance.⁴ It is also important to note that implementation is not an event, but rather a process, and requires an iterative approach to ensure that digital health tools are being implemented effectively, and to respond to emerging barriers by deploying new strategies when needed.

Although implementation best practices are critical to ensuring that digital health tools achieve their full potential, it is important to recognize that digital technologies themselves can also facilitate implementation by reducing data collection burden and enabling data to be captured in more standardized and useful formats. For example, metrics on implementation outcomes such as reach/penetration, adoption/utilization, cost, sustainability, and fidelity can potentially be assessed using data automatically generated by digital tools (e.g., log-in data, user activity, duration of use). These data can also be combined with information available about users (e.g., demographic information, practice characteristics) to help monitor the effects of the intervention on equity. For example, if under-resourced primary care or oncology practices are consistently performing poorly, that might suggest the need for additional support; similarly, if certain patients (e.g., those who are older) seem to be using a tool at lower rates or failing to use certain features, that might suggest a need for additional patient-facing education efforts.

Greater Integration between Implementation Science and Digital Health Research Going Forward

There is a growing recognition that applying knowledge from the field of implementation science is critical to promoting the successful deployment and sustainment of digital health efforts in cancer control. This is clearly demonstrated by NCI’s Telehealth Research Centers of Excellence (TRACE) initiative, which is aimed at supporting real-world, pragmatic research capable of generating best practices for the optimal delivery of cancer care via telehealth. Supported by President Biden’s reignited Cancer Moonshot^SM, this 5-year initiative awarded $23 million to four centers to conduct research on the role of telehealth in delivering cancer-related health care. These funded projects have significant implementation science components, incorporate implementation science frameworks like RE-AIM, and are collecting data on implementation metrics (e.g., reach, acceptability, sustainability, cost) in addition to standard measures of intervention effectiveness in order to inform the use and sustainment of telehealth as a model of care delivery.

Looking forward, there are many important questions that still need to be answered about how implementation science can advance digital health and how digital health tools can be leveraged in implementation efforts. We encourage the implementation science community to take up these challenges in their work and to explore opportunities and resources related to digital health offered by NCI and across NIH, such as PAR-22-145, which supports research that examines the impact of leveraging health information technology to reduce disparities. We also encourage investigators working on digital health interventions to consider how they can contribute to expanding the knowledge base on implementation of digital health interventions, particularly in the cancer care context. Lack of detail regarding context and implementation processes in studies can pose a barrier to replication and scale-up of digital health interventions. To close the gap between research and practice and advance implementation science in the context of digital health, clear and detailed reporting of implementation methods, intervention components, and contextual features is needed to ensure studies are maximally useful to researchers, practitioners, and other stakeholders.

¹ Fleming T, Bavin L, Lucassen M, Stasiak K, Hopkins S, Merry S. Beyond the trial: systematic review of real-world uptake and engagement with digital self-help interventions for depression, low mood, or anxiety. J Med Internet Res. 2018;20(6):e199. Published 2018 Jun 6. doi:10.2196/jmir.9275

² Khanna N, Klyushnenkova E, Rao V, Siegel N, Wolfe S. Electronic referrals to the tobacco Quitline: implementation strategies in a large health system to optimize delivery of tobacco cessation to patients. Transl Behav Med. 2021;11(5):1107-1114. doi:10.1093/tbm/ibaa094

³ Lowery J, Fagerlin A, Larkin AR, Wiener RS, Skurla SE, Caverly TJ. Implementation of a web-based tool for shared decision-making in lung cancer screening: mixed methods quality improvement evaluation. JMIR Hum Factors. 2022;9(2):e32399. Published 2022 Apr 1. doi:10.2196/32399

⁴ Snavely AC, Foley K, Dharod A, Dignan M, Brower H, Wright E, Miller DP Jr. Effectiveness and implementation of mPATH™-CRC: a mobile health system for colorectal cancer screening. Trials. 2023 Apr 14;24(1):274. doi: 10.1186/s13063-023-07273-5.