Trained as a development economist, Sean Sylvia, PhD, associate professor of health economics at the UNC Gillings School of Global Public Health, focuses his work on using economic principles and behavioral psychology to improve the implementation of public health programs and health care delivery. Principal Investigator of Gillings’ Digital Health Economics and Policy (DHEP) Lab—which convenes interdisciplinary teams to weave insights from the behavioral, data, and computer sciences into transformative health policy research suited for the digital age—Sylvia is also a faculty fellow at the UNC Frank Porter Graham Child Development Institute (FPG).

With an interest in health and education programs, Sylvia spent much of the early part of his career in rural China, where he continues to conduct research. That work focused on education-related programs and school-based nutrition, including providing subsidies to schools to support more nutritious lunches and reducing rates of anemia in students. This successful project paved the way for policy changes in China in which the government began to invest more in school-based lunches. Sylvia’s first taste of having influence on public policy helped guide him toward policy-related work.

Currently, his main effort is leading the DHELP Lab, which focuses on three main areas of research: telemedicine; precision public health; and artificial intelligence and healthcare. Sylvia says that he and his colleagues are not as concerned with the technology of telemedicine itself as with the behaviors surrounding its use and how the technology affects access to care. The researchers also explore how laws, regulations and reimbursement policies regarding telemedicine affect care quality and access, both in the United States and globally. The DHEP Lab ’s objective is to harness digitization to increase healthcare utilization and patient satisfaction, decrease out-of-pocket costs, and improve health outcomes.

Precision public health utilizes algorithm-assisted interventions to support community health workers in rural communities around the world where maternal and child health outcomes are worse than in their urban counterparts. With collaborators at Stanford University, Sylvia and colleagues have created the “Healthy Future” app that community health workers can use to conduct home-based visits. The app helps workers tailor the education program to each family and community, based on their different needs and knowledge gaps.

In addition, Sylvia recently piloted a program in Ghana to use digital approaches to monitor infectious disease trends. This acute community engagement approach attempts to crowdsource the trends in diseases such as COVID and flu.

Sylvia spends much of his time working on AI and healthcare, looking at ways of combining human expertise with AI for better clinical decision making. He is working with colleagues in computer science to design behavioral experiments and putting together an open-source platform to understand how AI recommendations and machine learning algorithms affect simple decisions by healthcare providers. The goal is to design the AI so that it better supports clinicians rather than substitutes for their knowledge. With a current focus on colon cancer screening recommendations, Sylvia and his colleagues are trying to design more transparent systems that best leverage the knowledge of the clinician and the machine learning system. The aim is to “build a digital platform for human+AI decision-making experiments, create algorithms to summarize and highlight important patient case attributes and AI explanations, and assess the feasibility and acceptability of these AI-enabled decision support tools in community centers.”

Sylvia is utilizing AI in other ways as well. He is collaborating on building an algorithm called “The Recommenders.” He likens it to using Netflix, which recommends videos based on a user’s history. Sylvia is trying to determine how to implement a data-driven approach to allow community health workers to automate tailoring of home visiting programs. The first target will be to figure out which children would benefit from having more frequent visits within a village or community. This data will enable the finite resource of community health worker time to be allocated most efficiently, with some households needing semiweekly visits while others will thrive with just monthly visits.

By measuring the different outcomes of children and families and using that data to suggest which type of home visiting program and frequency are best, this algorithm can help optimize the work across the population receiving services. Sylvia emphasizes the importance of determining the right mix between a data driven approach and trying to align with the preferences of families. “Asking moms what they think when they are given a list of options for the content that is delivered in the next visit may be more effective than an algorithm,” he says. “Or maybe it's a combination of both. But we are trying to understand how to figure out what's going to be most effective for families and the program, as a whole, given the resources available.”

“I bring a methodological focus and approach, as well as economic theory, into the programs I work on,” says Sylvia. “I appreciate being able in all these projects to make sure that I am connected and working closely with domain experts who can guide that process as we work in different areas.”

Sylvia, who became an FPG faculty fellow in 2018, says that his involvement with the FPG community provides him with access to the expertise of his colleagues working in early childhood. While many of his projects are in the realm of early childhood, he recognizes that he is not an early childhood expert so the support of FPG experts enhances his work. “I bring a methodological focus and approach, as well as economic theory, into the programs I work on,” says Sylvia. “I appreciate being able in all these projects to make sure that I am connected and working closely with domain experts who can guide that process as we work in different areas.”

Because FPG is well-known globally for its excellence in research on early childhood-related programs, Sylvia says that his association with the Institute is helpful, particularly when working with policymakers. He recently returned from an early childhood conference in Shanghai where he met with China’s lead experts on early childhood. China is in the midst of designing a national policy around early childhood. Sylvia was asked to provide input and credits his connection to FPG as an important factor.

Beyond the direct benefits that Sylvia receives from being an FPG Faculty Fellow, he appreciates interacting with and being part of the FPG community. Through presenting his work at FPG and keeping abreast of what FPG researchers are working on, Sylvia continually learns and finds colleagues with whom to collaborate.

While Sylvia’s research agenda is broad, he says that the connecting thread is using data and behavioral science to improve public health and health care. “My work is around how we can harness behavioral science to better design and implement programs and the effects those programs have on individuals,” he says. “And because there's a revolution in the tools that we have access to, including AI and other machine learning and algorithms, my work is increasingly focused on digitization.”