Healthcare Cost-Effectiveness Modeling for Decision Makers

Healthcare systems worldwide face the critical challenge of allocating limited resources to maximize patient outcomes. Understanding how to evaluate the economic value of medical interventions is essential for making impactful policy and clinical decisions. This text-based course guides you from foundational health economics concepts to constructing decision-analytic models. You will learn how to systematically compare the costs and consequences of different healthcare pathways to guide resource allocation. What you'll learn: - Understand key concepts of health economics, including quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs). - Build decision trees to map clinical pathways and evaluate short-term treatment outcomes. - Develop Markov models to simulate chronic diseases and long-term patient transitions over time. - Apply sensitivity analysis to assess the impact of uncertainty on your economic evaluations. - Analyze real-world healthcare datasets to inform resource allocation and policy decisions. The course begins with essential terminology and economic frameworks before guiding you through structured written exercises to design and interpret decision models. You will progress from basic decision trees to complex state-transition simulations. This course is designed for healthcare professionals, administrators, policy researchers, and analysts who are new to health economics and want to build modeling skills without prior experience. Start reading today to master the core principles of healthcare decision-making and economic evaluation.