[Decision analytic modeling and their impact on health care decision making]

Abstract

Cost-effectiveness evidence has become mandatory criteria before reimbursement of pharmaceuticals in several countries due to scarcity of resources for health care. Data for cost-effectiveness analysis can rarely be gained from a single clinical trial. As a method to synthesize input data from different sources, economic modelling earns increasing importance in the assessment of health technologies. This review paper depicts the main features of standard economic modelling techniques with special focus on decision tree and Markov models. It summarizes the interpretation of incremental cost-effectiveness ratio and sensitivity analysis for decision-making purposes. There is a trade-off between the transparency and complexity of economic models. It is important to develop economic models according to the best available scientific evidence and modelling standards, however the search for absolute accuracy in economic modelling of health care technologies may not improve the appropriateness of reimbursement decisions.