Decision analytic and population simulation models are relevant to numerous government agencies to guide policy decisions, forecast future spending, and evaluate existing programs. These models tend to focus on overall costs, revenues and budget limits. Academic investigators who study medical decisions often construct models that account for the natural history of disease and the effects of treatment, typically for the purposes of evaluating the cost effectiveness of specific interventions. However, these models tend to ignore budget constraints faced by policymakers. This symposium will convene panelists from government agencies and academia to discuss the similarities, differences and potential synergies of their modeling methods.
Symposium Chairs:
- Elbert S. Huang, MD, MPH, FACP, Associate Professor of Medicine, University of Chicago
- Negin Hajizadeh, MD, MPH, Instructor, New York University School of Medicine
Confirmed speakers:
- Chapin White, PhD, Center for Health System Change for Modeling of Healthcare Policy in the Congressional Budget Office
- Joseph Chin, MD, MS, Centers for Medicare & Medicaid Services, Center for Clinical Standards and Quality, Coverage and Analysis Group for Modeling of Healthcare Policy at the Center for Medicare and Medicaid Services
- Bill Lawrence, MD, MS, Agency for Healthcare Research and Quality for Modeling of Medical Decisions and Health Policy at the Agency for Healthcare Research and Quality
Andrew H Briggs, DPhil, University of Glasgow
Speaker Biographies:
Chapin White, PhD, Center for Health System Change
Chapin has focused on microsimulation modeling of health reform, long-term trends and geographic variation in health spending, medical malpractice, nonprofit hospitals, and Medicare payment policy. At HSC, he is focusing on policy analyses relating to the implementation of health reform and original research quantifying the likely impacts of health reform. White was formerly a principal analyst at the Congressional Budget Office, a post-doctoral fellow at the National Bureau of Economic Research, a consultant to the Medicare Payment Advisory Commission and an analyst at Abt Associates. White earned his doctorate in health policy from Harvard University, a master’s degree in public policy from Harvard’s Kennedy School of Government and a bachelor’s degree in social anthropology, cum laude, from Harvard.
Joseph Chin, MD, MS, Centers for Medicare & Medicaid Services, Center for Clinical Standards and Quality, Coverage and Analysis Group
Dr. Joseph Chin is a senior medical officer at the Centers for Medicare and Medicaid Services (CMS). He is board certified in preventive medicine and has focused his activities on improving coverage and utilization of clinical preventive services for Medicare and Medicaid beneficiaries. Recent applications of decision modeling have focused on utilization of colorectal cancer screening tests and behavioral risk factor reduction. Dr. Chin received his Doctor of Medicine and Master of Science in epidemiology degrees from the University of Maryland School of Medicine, has been at CMS for over 20 years and maintains a clinical practice in ambulatory medicine.
Bill Lawrence, MD, MS, Agency for Healthcare Research and Quality
William Lawrence, M.D., M.S., is a graduate of Duke University and the West Virginia University School of Medicine. He completed residency training in internal medicine and a fellowship in general internal medicine at the University of Wisconsin. During his fellowship, he received a Masters' degree in industrial engineering, concentrating on decision analysis and health preference measurement. Dr. Lawrence has served on faculty at the University of Wisconsin, and in the Departments of Medicine and Oncology at Georgetown University. Dr. Lawrence is a general internist and clinical decision analyst with research interests in cost-effectiveness analysis, health-related quality of life, and health preferences. His research focuses on improving the acceptability and usefulness of health care outcomes assessments, particularly measurement of health-related quality of life.
Andrew H Briggs, DPhil, University of Glasgow
Andrew holds the William R Lindsay Chair in Health Economics at the University of Glasgow. Previously, he held the position of Reader in Health Economics at the University of Oxford's Health Economics Research Centre (HERC). In addition, he spent the academic year 1999/2000 at the Centre for Evaluation of Medicines (CEM), at McMaster University and he remains a research associate of both CEM and HERC. Andrew has expertise in all areas of health economic evaluation -- he has published well over 100 articles in the peer-reviewed literature. He has particularly focused on statistical methods for cost-effectiveness analysis. This includes statistical methods for estimation of parameters for cost-effectiveness models as well as statistical analysis of cost-effectiveness alongside clinical trials. He also has a more general interest in epidemiological methods, in particular the use of prognostic scoring methods for predicting health outcomes and the relationship with heterogeneity in cost-effectiveness. Andrew recently took a leadership role as co-chair of the Joint Society for Medical Decision Making (SMDM) and International Society for PharamacoEconomics and Outcomes Research (ISPOR) Task Force on Modelling Methods. The Task Force, which was responsible for producing a set of seven papers covering all aspects of modelling methods applied to medical decision making and health technology assessment. He is also the author of two successful textbooks, one published by OUP entitled Decision Modelling for Health Economic Evaluation, and another published by Wiley entitled Statistical Methods for Cost-Effectiveness Analysis.