Glimpse into the future – How will the field of digital health evolve in the next 5 years and what are the implications for behavior science? An industry perspective
By Emma Norris, on 30 April 2019
By Madalina Sucala PhD & Nnamdi Ezeanochie MD, DrPH – Johnson & Johnson
The Society of Behavioral Medicine (SBM) is a leading forum for behavior scientists and connected disciplines to study and promote behavioral health. Within the organization, the Digital Health Council is responsible for leading initiatives to inform and prepare society members, and behavior scientists overall, for the evolution of this field. As a member of the Digital Health Council, Dr. Madalina Sucala led an initiative interviewing experts in the field for their perspective on the evolution of digital health and the expected implications for behavior science. In the interview below, Dr. Sucala interviewed her colleague, Dr. Nnamdi Ezeanochie, who provided an industry perspective on the dynamic and rapidly evolving field of digital health.
MS: When thinking about the next 5 years, what do you think will be most important for digital health? [this can be broad, as it applies to technology, legislation, etc.]. Why?
NE: In the next 5 years, it will be imperative to design digital health technologies that work for all. This not only means ensuring equitable implementation of digital health solutions across different populations, but also leveraging real-world data from diverse communities to inform and shape how solutions are built and optimized over time. This challenge means that digital solutions will need to become more personalized and optimized, while at the same time, ubiquitous with the deliberate intention of narrowing the “digital divide” and reducing health disparities.
To personalize and optimize solutions within and across different populations, two components are needed:
1. An insights generation loop that rests on: i) behavior science evidence, ii) robust data capture within digital solutions, and iii) advanced analytics via data science methodologies. These three components will ensure that insights on what works for different populations (sub-groups); and how different populations may respond or perform (predictive), are generated.
2. A platform that houses these insights and can mechanistically deploy them in relevant contexts, overtime, within and across different populations.
The presence of both capabilities (insights and platforms) will ensure that digital technologies in the next 5 years can truly be adaptive and effective for many populations globally. To facilitate the use of these capabilities on a larger scale, there needs to be sustained commitment in both public and private sectors—worldwide, to invest in technology/digital infrastructures such as expanded mobile telecommunications, satellites, network infrastructure, data centers, etc. This is critical to ensure that no population of people are left behind; and that access to the promised benefits of digital health solutions is achievable.
MS: When thinking about the next 5 years, which technology capabilities do you think will bring more promise for digital health? Why?
NE: The first category would be what I refer to as the “front-end layer,” which includes user – facing technologies. In this category, we can envision improved and highly convenient interfaces and product designs which will remove usage barriers and increase user engagement with technology. We can expect to see a trend towards technology that can be easily commodified, integrated into daily routines and used for increased user convenience. Voice technology, chatbots, and miniaturized devices with esthetic appeal for health behavior tracking will become more pervasively used as well.
The second category would be what I refer to as the “middle layer.” With so many health behavior tracking possibilities (e.g. health behavior passively and actively tracked alongside data from smart homes, social media, transportation, personal wearables, to care facilities, etc.), data integration and streamlining capabilities will become extremely relevant. For example, beyond the slick designs and attractive interfaces, digital health interventions need to consider application programming interfaces (API), which enable connectivity between various devices and programs, and facilitate the interaction between data, applications and devices.
Finally, the third category would be the “back-end layer.” Digital health interventions will need to be built with a configurable system architecture – one that allows artificial intelligence capabilities for intervention personalization and optimization. This will allow for the configuration of intervention components based on advanced analytic insights for improved health outcomes. In addition to the system architecture, advanced data science methods and computational capabilities are needed to support personalization and optimization.
MS: How do you see the digital field evolving in the next 5 years?
NE: Evolution of the digital field in the next 5 years will be very exciting, and to some extent, unpredictable. This evolution will be expected to occur at two levels: 1) the intrinsic evolution of digital solutions themselves, and 2) the extrinsic, or environmental, evolution within which digital solutions will exist, apply and interact with.
Digital health solutions will become more responsive and adaptive, thereby delivering more personalized experiences to users, and constantly updating features to ensure sustained optimization and effectives. Big drivers of this intrinsic evolution include: better passive data tracking devices and sensor capability, emergency of connected digital tools that seamlessly aggregate data from multiple sources, and new analytic tools and software that can develop algorithms to drive and automate how digital solutions respond in real-time and in different contexts. These features mean that we will no longer be required to manually or actively monitor our behavior, track our daily intakes, or complete a survey repeatedly. Information will be aggregated and synced across platforms and used to make more responsive decisions about things that affect people daily. Therefore, we can expect to have smart technology that actively influences our lives without our full participation.
However, technology will not exist in a vacuum and will be shaped by several extrinsic factors. These include: an expected rise in people’s data literacy; participation and agency in controlling their data – and decisions on its subsequent use by 3rd parties; the creation of new legislation responsive to emerging capabilities of digital technology solutions. The introduction of the General Data Protection Regulation (GDPR) requirements, news of technology companies ordered to pay huge fines in Europe, and FDA involvement with digital health solutions in the United States are examples of current extrinsic factors influencing technology. These are expected to shift further in the next 5 years. So, perhaps the most important takeaway, is that a 5-year evolution of the digital health field is largely dependent on how impactful these extrinsic factors will be in time, and thus, this evolution remains unpredictable.
MS: What do you think behavioral scientists can do to be more prepared to work with digital health in the next 5 years? [this can be broad, as it applies to training, partnerships, etc.]
NE: The interdisciplinary nature of digital health will require behavior scientists to become familiar (at least at a level that allows collaboration) with the following:
- Intervention co-design processes. While the scientific requirements for an intervention will still be the purview of science, learning how to offer them in an actionable way that lends itself to forming the foundation for the co-design process will be key.
- Intervention development. Although it might not be necessary for behavior scientists to learn how to develop software themselves, it is important for them to become familiar with current approaches in general technology or software development. For example, technology companies often adhere to what is called an Agile approach. This is an approach initiated to challenge the traditional “waterfall” software development model, wherein entire projects are pre-planned and subsequently fully built before being tested with users. In contrast, the Agile approach emphasizes an iterative flexibility, proposing testing early and often across development. Familiarity with the development team’s structure and roles, as well as a good understanding of the phases in which to offer input is needed (e.g. Sprint review meetings in which they, as stakeholders, would review and provide input on what the development team has accomplished; Demo testing to ensure adherence to the scientific requirements of the intervention).
- Advanced analytics. Digital interventions will increasingly rely on modern data science methodologies. Machine learning, data mining and other modern analytic methods are needed to capitalize on intensive longitudinal data to identify factors that would inform intervention optimization. It would be important for behavior scientists to become familiar with such data science methods.
MS: What is the role that behavioral scientists will play in digital health in the next 5 years?
NE: The role that behavior scientists can play ranges from offering subject matter expertise on content development, intervention design, and research design, to providing the necessary interpretation of evidence towards actionable insights for improved interventions. In all these roles, it is important to consider that developing effective digital health interventions will increasingly depend on strong interdisciplinary partnerships among behavior scientists, designers, software developers, system engineers and data scientists, as no single group has enough expertise and resources to develop successful, effective digital health technologies on their own. Previously, in non-digital interventions, behavior scientists were able to work in a rhythm dictated by government funding cycles, relying on their own and their peers’ expertise. Currently, in technology-based interventions, interdisciplinary collaborations are necessary, and the rhythm might be dictated by the technology’s evolution as well. Behavior scientists will likely find themselves working on collaboration platforms, whether working in academia, or in the private or public sector.
MS: How do you see technology supporting behavioral health in the next 5 years?
NE: Technology has an important role to play in supporting behavioral health in the next 5 years. This role includes several opportunities:
First, the behavior science and health fields can leverage engineered platforms to deliver real-time behavior change interventions. This function will help make digital health interventions more functional and applicable to real-world settings where factors that influence decisions and behaviors are different across and within populations.
Second, the behavior science field can deploy data analytic methods (e.g. machine learning, and deep learning) to inform insight generation that will help to improve existing behavior science theories and models. This will help ensure that the behavior science field continues to expand its theories to be more inclusive of different populations and contexts.
Third, technology can help support hybrid behavior science interventions. This means that behavior scientists can leverage several digital modalities and/or in-person experiences to deliver an intervention. This will help to reduce barriers-to-entry and access to such interventions – and ultimately, help ensure that no one is left behind.
Finally, behavior scientists can use predictive models to inform and support preventive interventions. For example, a predictive model that identifies at-risk groups for a vaccine-preventable infectious disease, can allow health promotion experts to channel resources to that specific group and build preventive programs focused on them, rather than the general population. The cost-benefit of such data guided interventions cannot be over-emphasized.
You can read a recent Digi-Hub blog giving a response from academics to these questions here.
- Based on your area of expertise, how would you answer these questions?
- What could you do to be more prepared for the way the behavior science field might evolve?
Madalina Sucala is a Senior Manager of Behavior Science at Johnson & Johnson, where she leads the development, evaluation and implementation of digital behavior change interventions. She is a member of the Digital Health Council for the Society of Behavior Medicine. Madalina has a PhD in Clinical Psychology and has completed a Postdoctoral Fellowship in Cancer Prevention and Control. Prior to joining Johnson & Johnson, Madalina was an Associate Scientist at Icahn School of Medicine at Mount Sinai, where in her dual role as a scientist and a practitioner, developed, investigated, and delivered behavioral medicine interventions. She joined Johnson & Johnson in 2017 to pursue her passion about applying data-driven behavioral science and innovative technology to improve health and wellbeing outcomes. @MadalinaSucala
Nnamdi Ezeanochie is a Senior Manager on the Behavior Science and Analytics team. He has extensive professional experience in technology-based health care and behavioral science implementation and research, with a unique focus on developing-country settings. His research expertise focuses on mobile technology adoption and implementation, health care program management, community and health behavior services, IT healthcare solutions, and disease outbreak management.@NnamdiEzeanoch1