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The CHOICE Institute and Department of Pharmacy Welcome Dr. Noémi Kreif to the Faculty

Dr. Noémi Kreif, MA, MS, PhD
Dr. Noémi Kreif, MA, MS, PhD

Dr. Noémi Kreif, MA, MS, PhD joined the CHOICE Institute and the Department of Pharmacy in March as an Assistant Professor. She joins us most recently from the University of York Centre for Health Economics (CHE) where she was a Senior Research Fellow in Health Economics. Dr. Kreif earned a PhD in Health Economics in 2013 at the London School of Hygiene and Tropical Medicine (LSHTM), University of London (UK). Dr. Kreif also holds an MA in Economics from Central European University, Hungary and an MSc in Economics from Corvinus University of Budapest, Hungary.

Dr. Kreif has an established publication and funding track record in methods-focused and applied health economics research. She is passionate about bridging the gap between health economics/health policy research and modern causal inference. She has developed a research agenda that centers on innovative causal inference methodology, collaborating with researchers from various fields, including global health and decision science, as well as psychiatry and computer science.

Dr. Kreif’s early (PhD and post-doctoral) research, conducted at the London School of Hygiene and Tropical Medicine focused on statistical methods underpinning cost-effectiveness analyses that use observational data. Later, at the University of York she developed a research agenda in global health economics, focused on health policy issues in low- and middle-income countries, such as the heterogenous policy impacts of national health insurance reforms in Indonesia, or the health impacts of civil conflict in Colombia.

Dr. Kreif’s current research focuses on combining causal inference and machine learning methods to improve health policy evaluations and economic evaluations by using healthcare data in flexible ways to inform personalized decision making that considers resource and equity constraints. Her most recently awarded research grant allowed her to lead a team that brought together expertise from health economics, causal inference, decision science, and computer science. She is passionate about training a new generation of graduate students and researchers in modern causal inference and computational statistics methods. Dr. Kreif is open to advising MS and Ph.D. students conducting research on a wide range of topics, including using real-world data for comparative effectiveness research and health policy analysis and incorporating machine learning into health outcomes research for stratified decision making.

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