UNC Gillings School of Global Public Health
PIs: Sean Sylvia, PhD and Tara Templin, PhD
We study how people make health decisions and how digital tools, incentives, and information can improve care. Our work combines health economics, behavioral science, and computational methods, with an emphasis on practical interventions and rigorous evaluation. We welcome clinical, community, technical, and research partners.
What We Study
How do clinicians use information, learn from experience, and respond to AI advice? We study clinical reasoning, confidence, feedback, and the design of decision support and training.
How can services respond to what patients and families need and value? We study preference elicitation, demand for care, and the tailoring of prevention and family support.
How can health systems use knowledge distributed across clinicians and communities? We study expert judgment, information aggregation, incentives, and digital workflows in resource-constrained settings.
How We Work
Lab Updates
DHEPLab team publishes first cluster-randomized trial of drone-based medical supply delivery in the Global South, revealing that faster transportation alone is insufficient to solve health supply chain challenges.
Read moreA new NIH NIMHD-funded Phase I STTR project develops and evaluates asynchronous peer consultation for rural clinicians, with CollectiveGood as prime and UNC as subawardee.
Sean Sylvia led a department workshop on using AI to cut administrative burden in research, teaching, and service.
Work With Us
Randomized evaluations, causal analysis, and variation in intervention effects.
Preference elicitation, expert judgment, causal machine learning, and adaptive interventions.
Mixed methods, usability, and evaluation of workflow fit in clinical and community settings.
We welcome joint studies, methods collaborations, and partnerships that connect a concrete care-delivery problem with an intervention and a credible evaluation.
Sean Sylvia also co-founded CollectiveGood, a separate company developing clinician review and evidence tools for clinical AI evaluation. The lab's collaborations include the peer-consultation research described above.
Behavioral and computational science against the conventional wisdom on healthcare AI, digital health adoption, and health policy. Written by Sean Sylvia and the DHEPLab team.
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