Evidence-Based Management: Tools for Making Decisions About Population Health

Just as evidence-based medicine has revolutionized the way individual patients are cared for, the advent of evidence-based management has the potential to improve how we make decisions about population health.

Randomized controlled trials, the gold standard for clinical care, are rarely available or even possible in evaluating strategies for population health management, and other methodologies are required to predict the impacts of different strategies. This webinar will review the basics of the quality of evidence, and describe several types of modeling tools that can be used to make predictions of population health interventions.

Mark S. Roberts, MD, MPP is Professor and Chair of Health Policy and Management, and hold secondary appointments in Medicine, Industrial Engineering, and Clinical and Translational Science. A practicing general internist, he has conducted research in decision analysis and the mathematical modeling of disease for over 25 years, and has expertise in cost effectiveness analysis, mathematical optimization and simulation, and the measurement and inclusion of patient preferences into decision problems. He has used decision analysis to examine clinical, costs, policy and allocation questions in liver transplantation, vaccination strategies, operative interventions, and the use of many medications. His recent research has concentrated in the use of mathematical methods from operations research and management science, including Markov Decision Processes, Discrete Even Simulation and integer programming to problems in health care.