Improving medical decision making: Evidence and uncertainty considerations 
Medical decision making is based on imperfect information, often leading to uncertainty in the expected outcomes, decision uncertainty, and potential negative consequences of making wrong decisions. To guide decision makers with model-based cost-effectiveness analyses, it is crucial to ascertain that the decision problem and the decision-analytic model are appropriately conceptualized, and that the model is populated with reliable evidence. Furthermore, evidence plays a central role in the process of model-based decision analysis. This evidence drives the iteration in the decision-making process. To ensure this iteration, a value of information analysis should be performed as a part of the evaluation to assess decision uncertainty, evaluate whether gathering new evidence would be worthwhile, and identify the optimal designs of research. In this seminar, I will present an iterative decision-making framework in health and medicine including application examples.