Development and Use of Disease-Specific (Reference) Models for Economic Evaluations of Health Technologies: An Overview of Key Issues and Potential Solutions

Decision-analytic models are increasingly used to inform decisions about whether or not to publicly fund new health technologies such as pharmaceuticals. Therefore, few would argue the need for developing and using high-quality models [ 1 ]. Over the past years, significant efforts have been made to improve the quality of decision-analytic models (e.g., through improvement and use of good practice guidelines [ 2 ]); however, important challenges facing decision-analytic modelling still remain. Recently, Caro and Moller [ 3 ] outlined some of these challenges, including, among other things, “validation”, “transparency”, “uncertainty”, and “implementing the model”, with potential impact on the credibility of model outcomes to decision makers. Of these critical points, uncertainty of model outcomes is a broadly studied topic. Three major types of uncertainty influencing the results of decision-analytic models are (1) parameter uncertainty; (2) methodological uncertainty; and (3) structural uncertainty [ 4 ].