Education
- PhD, Health Policy (Economics Track), University of California at Berkeley, 2016
- MS, Economics, University of California at Berkeley, 2015
- MA, International Comparative Education, Stanford University, 2009
- BA, Economics and English, Peking University, China, 2008
Courses Taught
- HEOR 597: Graduate Seminar
- HEOR 598: HEOR Methodologies Seminar
Research Interests
- Decision-making in Aging
- Physician Behavior
- Policy Evaluation
- Experimental and Quasi-experimental Methods
Biography
Dr. Jing Li is a health economist with research interests in the economic, social and behavioral factors affecting individual decision-making in health and healthcare, for both providers and patients, and the impact of policies that leverage these factors to improve patient outcomes and healthcare market efficiency. Methodologically, she is interested in innovatively applying advanced experimental and econometric methods to addressing understudied questions in health economics and policy. Dr. Li’s current projects study experimentally measured social preferences (altruism) of physicians and their relationship with patient outcomes, healthcare and financial decision-making for older adults with cognitive impairments including Alzheimer’s disease and related dementias, and conflicts of interest in physician drug prescribing.
Selected Publications
https://www.ncbi.nlm.nih.gov/myncbi/jing.li.13/bibliography/public/
Education
- PhD, University of Manchester
- B. Pharm, University of London
Research Interests
- Mechanisms of drug transport and metabolism
- Maternal-fetal pharmacology
Courses Taught
- PCEUT 501
- PCEUT 506
- PCEUT 532
Biography
Jashvant (Jash) Unadkat, Ph.D. is a Professor of Pharmaceutics at the School of Pharmacy, University of Washington, Seattle. He received his Bachelor degree in Pharmacy (B.Pharm.) from the University of London (1977), his Ph.D. from the University of Manchester (1982) and his postdoctoral training at the University of California at San Francisco (1982-85).
Dr. Unadkat studies the mechanisms of transport and metabolism of drugs, including during pregnancy. Dr. Unadkat has published more than 270 peer-reviewed research papers. He is a fellow of AAAS, AAPS, JSSX, and the founding co-chair (1999-2001) of the focus group of AAPS on Drug Transport and Uptake. Dr. Unadkat received the AAPS Research Achievement Award in 2012, the ISSX Research Achievement Award in 2023 . Dr. Unadkat created and led for 10 years the UW Research Affiliates Program on Transporters (UWRAPT), funded by pharmaceutical companies, and UWPKDAP, a NIDA funded Program Project grant (P01) on drug disposition during pregnancy. He now co-leads the UW Transporter Elucidation Center (https://depts.washington.edu/uwtec/) funded by NICHD to identify and characterize novel transporters in the placenta and the developing intestine. In 2025, Dr. Unadkat was elected to the Washington State Academy of Sciences and as a President-elect of the International Society for the Study of Xenobiotics (ISSX).
Selected Publications
(PubMed.gov)
Education
- PhD, Public Policy (Health Economics), University of Chicago, 2004
- MS, Biostatistics, UNC-Chapel Hill, 1999
- MS, Industrial Pharmacy, University of Toledo, 1997
- BS, Pharmaceutical Technology, Jadavpur University India
Courses Taught
- Welfare Economics foundations for cost-effectiveness analysis (HSERV 583, ’11 & ‘12) – 1.5 hour sessions
- Understanding the role of uncertainty in decision models (HSERV 583, ’13 & ‘14) – 1.5 hour sessions
- Quantitative methods for valuing information in health care (HSERV 584, ‘11) – 1.5 hour sessions
- Introduction to comparative effectiveness methods (HSERV 523, ’11; HSERV 513 & HSERV 592, ’12) – 1.5 hour sessions
- Instrumental variable methods (HSERV 523, ‘11) – 1.5 hour session
- Financing healthcare (HuBio 555, ’13, ‘14) – 1.5 hour session to 250 2nd year medical students
- Quantile regression methods (HSERV 525, ’11, HSERV 523, ‘12) – 1.5 hour sessions
- Variations in healthcare spending: Observations & Implications (PHARM 568, ’14 -‘16) – 1.5 hour sessions
- Causal inference in observational studies (HSERV 525), Spring 2013 -2019- Ten 3 hour sessions.
Research Interests
- comparative and cost-effectiveness analyses
- causal inference methods
- program evaluation, and outcomes research
Biography
Anirban Basu, PhD, MS, is a health economist and a statistician who specializes in research on comparative and cost effectiveness analyses, causal inference methods, program evaluation, and outcomes research. He directs The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute at the University of Washington, Seattle, with appointments in the departments of Pharmacy, Health Services, and Economics at the university. He is a Faculty Research Fellow at the National Bureau of Economic Research, and a Fellow of the American Statistical Association. He was one of the panelists for the Second Panel on the Cost-Effectiveness Analysis in Health and Medicine. He studies heterogeneity in clinical and economic outcomes, micro behavior with respect to heterogeneous information, and the value of individualized care. He teaches topics in health economics, decision analysis, cost-effectiveness analysis, and health services research methods. He received his PhD in Public Policy (Health Economics Specialization) from The University of Chicago and an MS in Biostatistics from the University of North Carolina at Chapel Hill. http://faculty.washington.edu/basua/
Selected Publications
https://scholar.google.com/citations?user=AR72duAAAAAJ&hl=en
Dr. Bansal is an Associate Professor and the Edwin S.H. Leong Chair in Data Science for Child Health at the Institute of Health Policy, Management and Evaluation, University of Toronto and The Hospital for Sick Children. Prior to joining the University of Toronto in September 2025, Dr. Bansal served on the faculty at The CHOICE Institute and Department of Pharmacy for 12 years. Dr. Bansal’s research focuses on sequential decision-making using longitudinal data, prediction modeling, decision theoretic methods including value of information analysis, and comparative effectiveness and outcomes research using large healthcare claims databases and EHR data. She is the PI of a study to develop methods for cost-effective personalized risk-adaptive surveillance in cancer.
Education
- Ph.D. Biostatistics, University of Washington, Seattle, WA
- M.S. Biostatistics, University of Washington, Seattle, WA
- B.Math. Honors Computer Science: Bioinformatics Option, University of Waterloo, Waterloo, Ontario
Courses Taught
- BIOST 512: Medical Biometry II
- HEOR 552 Application of Machine Learning in Health Economics and Outcomes Research
Research Interests
- Clinical decision sciences
- Development and evaluation of prediction models
- Comparative effectiveness and outcomes research
Selected Publications
https://www.ncbi.nlm.nih.gov/myncbi/aasthaa.bansal.1/bibliography/public/