HEOR Excellence—Methodology Award

For the paper, “Reproducibility of real-world evidence studies using clinical practice data to inform regulatory and coverage decisions” .

Dr. Wang is an Associate Professor at Brigham and Women’s Hospital, Harvard Medical School and Lead Epidemiologist for the Food and Drug Administration’s (FDA) Sentinel Innovation Center. She leads the Meta-Research in Pharmacoepidemiology program, with recent projects aimed at improving the transparency, reproducibility and robustness of evidence from healthcare databases (www.repeatinitiative.org) and informing when and how real-world evidence studies can draw causal conclusions to inform regulatory or other healthcare decision-making (www.rctduplicate.org).

She is currently PI on multiple NIH R01s and is also funded by FDA. She has previously received 3 awards from international societies for her methods work  (Reuel A. Stallones, Stanley A. Edlavitch, and Ronald D. Mann Awards).

For the paper, “A Multiple Imputation Procedure for Record Linkage And Causal Inference to Estimate The Effects of Home-Delivered Meals” .

Dr. Roee Gutman is an Associate Professor in the Department of Biostatistics at Brown University. His areas of research and expertise are causal inference, file linkage, missing data, Bayesian data analysis and their application to large data sources in health services research. Dr. Gutman has been involved in many comparative effectiveness studies where he contributed both in terms of the statistical theory and its implementation. He has vast experience in analyzing many types of secondary datasets from various sources (e.g. claims data, registries, VA health data), and data collected through large pragmatic randomized trials.

Dr. Gutman has received three PCORI methods awards relating to causal inference with multiple treatments, inference with linked datasets, and analyzing proxy responses of health outcomes. He received a Brown University School of Public Health award for Excellence in Research Collaboration, and he was recently awarded an ASA/NSF/BLS Senior Research fellowship.

For the paper, “Health technology assessment with risk aversion in health” .

For the paper, “The impact of pharmaceutical marketing on market access, treatment coverage, pricing and social welfare.”

For the paper, "Modeling a Bivariate Residential-Workplace Neighborhood Effect When Estimating the Effect of Proximity to Fast-Food Establishments on Body Mass Index,” [published ahead of print November 20, 2018]. Stat Med 2019;38(6):1-13-1035. doi:10.1002/sim.8039.

A. James O’Malley, MS, PhD, is Professor of Biostatistics in the Department of Biomedical Data Science and The Dartmouth Institute of Health Policy and Clinical Practice at the Geisel School of Medicine at Dartmouth. In 1999, he received his PhD in Statistics from the University of Canterbury, New Zealand and an MS degree along with the LJ Cote award for excellence in Applied Statistics from Purdue University. His methodological interests encompass multivariate hierarchical models, causal inference, using instrumental variables, Bayesian inference and social network analysis. Much of his work is motivated by problems in health services research. He has published over 170 peer-reviewed research papers, was chair of the Health Policy Statistics Section of the American Statistical Association in 2008, and cochaired its International Conference in 2011. In 2011, he received the HPSS Mid-Career Excellence award and in 2012 was elected to be a fellow of the ASA.

For the paper, "Regulator Loss Functions and Hierarchical Modeling for Safety Decision Making" Medical Decision Making, July 2017;38: 512-522

Laura Hatfield, PhD, is an Associate Professor of Health Care Policy (Biostatistics). Her research focuses on trade-offs and relationships among health outcomes. She develops statistical methods that incorporate multiple sources of information, relationships among outcomes, and loss functions to improve decision making. Dr. Hatfield has expertise in Bayesian hierarchical and multiple outcome modeling. In applied research, Dr. Hatfield has evaluated interventions ranging from price transparency initiatives to home care, and from accountable care organizations to patient-centered medical homes. She has modeled temporal and geographic variation in medical device use and outcomes. Inspired by this applied work, Dr. Hatfield is currently working to improve methods for causal inference using difference-in-differences designs. With Dr. Sherri Rose, she co-leads the Health Policy Data Science Lab. Dr. Hatfield received her BS in genetics from Iowa State University and her MS and PhD in biostatistics from the University of Minnesota.

For the paper, "A Comprehensive Algorithm for Approval of Health Technologies With, Without, or Only in Research: The Key Principles for Informing Coverage Decisions" Value In Health, 2016;19: 885-891

Claire Rothery, PhD, is a senior research fellow at the Centre for Health Economics (CHE), University of York, UK. She joined CHE in 2006 after completing her MSc in Health Economics at York. She holds a MSci in Mathematics, a PhD in Theoretical Physics, and an MPhil in Medical Statistics, all awarded by Queen’s University Belfast, Northern Ireland. Claire’s research interests focus on the development and application of decision analytic modelling methods and Bayesian approaches to Health Technology Assessment. She has specific interests in the use of constrained optimization methods in economic evaluation, and value of information analysis for informing research prioritization decisions. She is currently co-chairing the ISPOR Task Force on Emerging Good Practices for Value of Information analysis. Claire has led an extensive number of health technology appraisals for the National Institute for Health and Care Excellence (NICE) in the UK. She also served on the NICE Technology Appraisal Committee from 2013 to 2016, and is currently a member of the NICE Decision Support Unit. Claire serves as a co-editor for ISPOR’s scientific journal, Value in Health.

For the paper, "A Framework for Prioritizing Research Investments in Precision Medicine,” Med Decis Making 2016;36:567–80.

Dr Basu is a Stergachis Family Endowed Professor and Director of the Pharmaceutical Outcomes Research and Policy Program at the University of Washington, with additional appointments in the Department of Health Services, the Department of Economics, and the National Bureau of Economic Research. Anirban’s work sits at the intersection of microeconomics, statistics, and health policy. His research focuses on comparative and cost effectiveness analyses, causal inference methods, program evaluation, and outcomes research. Anirban is as an Associate Editor for Health Economics and Observational Studies. He is one of the panelists updating the Gold et al. book, Cost-Effectiveness in Health and Medicine. He is a past recipient of the ISPOR Bernie O’Brien New Investigator Award.

Anirban has a Bachelor’s degree from India, a Masters in Biostatistics from the University of North Carolina, Chapel Hill, and a PhD in Public Policy with a concentration in health economics from the University of Chicago.

For the paper, "Measuring Family HRQoL Spillover Effects Using Direct Health Utility Assessment" Med Decis Making 2015;35:81–93.

Dr Prosser is an Associate Professor and Interim Director of the Child Health Evaluation and Research (CHEAR) Unit at the University of Michigan. Her research focuses on measuring the comparative effectiveness and cost-effectiveness of childhood health interventions using methods of decision sciences and economics. Current research topics include: evaluating long-term health and economic outcomes for newborn screening programs using simulation modeling, measuring public values for screening programs, and developing new methods for valuing family spillover effects of childhood illness. Dr Prosser's research on the economic impact of influenza vaccination and using decision modeling to project health outcomes for newborn screening has been used in setting national policy recommendations. Dr Prosser received her PhD in health policy from Harvard University. She also holds a MS degree from the MIT Sloan School of Management and a MS from the Technology and Policy Program at MIT. Her undergraduate degree is in mathematics from Cornell University.

For the paper, “Efficiency and Equity: A Stated Preference Approach” Health Econ. 22: 568–581 (2013).

Richard Norman, PhD, is a Senior Research Fellow at the Centre for Health Economics Research and Evaluation (CHERE), at the University of Technology, Sydney. He joined CHERE in 2006, and holds a PhD from UTS in addition to an MSc in Health Economics, and a BA(Hons) in Philosophy and Economics, both from the University of York. He currently holds an Australian National Health and Medical Research Council (NHMRC) Early Career Researcher Fellowship, in addition to project funding from the NHMRC and Australian Research Council (ARC). His interests are in the fields of economic evaluation, discrete choice experiments, and health-related quality of life. He is a co-author on a range of methodological and applied studies in each of these areas, combining all three to answer questions relating to valuing health profiles for use in economic evaluation. Prior to working at UTS, he worked at Queen Mary, University of London developing economic analyses as part of NICE clinical guidelines.