About this Event
Beginner course with the following outcomes: 1. Describe the key steps involved in model-based economic evaluations for HTA purposes 2. Define the main types of uncertainty in decision-analytic modeling 3. Discuss the methods to handle and assess different types of uncertainty 4. Interpret and report the results of various uncertainty analyses performed for HTA purposes
Due to scarce resources, decisions must be made regarding which interventions to reimburse in the healthcare sector. In many countries, model-based economic evaluations are used as part of the Health Technology Assessment (HTA) process to systematically assess the magnitude and tradeoffs of the expected health effects and costs of decision options considered. Such assessment is based on incomplete information, often resulting in uncertainty, which in the extreme can result in suboptimal decision making. Consequently, an economic evaluation for HTA purposes should be performed using a coherent framework to properly structure the decision-making process and should carefully assess the uncertainty surrounding the expected outcomes and the decision being addressed. This course will provide participants with 1) a taxonomy of the types of uncertainty that should be considered when preparing and assessing economic evaluations for HTA purposes; 2) a more in-depth understanding of different methods to appropriately assess the underlying uncertainty and make more informed decisions based on economic evaluations; and 3) guidance on how to report uncertainty using the latest good-practice guidelines. Further, the participants will practice with several of these methods and interpretation of their results in hands-on exercises. This course requires familiarity with basic economic evaluation and HTA concepts and methodologies.