Research & Publications
Natalia Kunst, PhD is a Post-doctoral Research Fellow and Pyle Fellowship Awardee in the Department of Population Medicine at Harvard Medical School and Harvard Pilgrim Health Care Institute. Her research addresses weighting tradeoffs among costs, benefits, and risks in cancer prevention and treatment policies, and designing and prioritizing clinical research when resources are limited. The methods she uses to answer these research questions include disease simulation modeling, cost-effectiveness analysis, and a value of information (VOI) analysis. In her PhD work, she formalized an iterative decision-making framework in health and medicine that propagated the principles of evidence-based medicine and highlighted the importance of iteration in the process of medical decision making. For her post-doctoral training, she is focusing on gaining new skills and expertise in the area of genomics and precision medicine. More specifically, she joined the Precision Medicine Treatment (PreEMPT) Modeling team that works on simulating short- and long-term clinical benefits and estimating the cost-effectiveness of integrating different genome screening strategies into clinical care for healthy or high-risk newborns for a wide variety of heritable conditions.
Dr. Kunst is also a Research Affiliate at the Yale University School of Public Health and a founding member of the Collaborative Network for Value of Information (ConVOI). She completed her PhD in Health Economics and Health Policy with concentration in Health Decision Science at the University of Oslo, Norway, and was a Postgraduate Research Fellow at Yale University School of Medicine and a Visitng PhD Candidate at Yale School of Public Health. Prior to her PhD, she worked as a Senior Health Economist in Norway, developing and adapting decision-analytic models and preparing Health Technology Assessment (HTA) applications predominantly in cancer in collaboration with the Norwegian Medicines Agency.
Education & Training
- PhDUniversity of Oslo, Health Decision Science (2021)