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Interested in collaboration, have a question about our research, or want to learn more about our work? We'd love to hear from you.
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Experimental design and causal inference
Randomized evaluations, causal analysis, and variation in intervention effects.
Behavioral and computational methods
Preference elicitation, expert judgment, causal machine learning, and adaptive interventions.
Implementation research
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.
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Digital Health Economics & Policy Lab
Department of Health Policy and Management
UNC Gillings School of Global Public Health
Chapel Hill, NC 27599