title: [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.
authors.affiliation: Semmelweis Egyetem, Egyetemi Gyógyszertár Gyógyszerügyi Szervezési Intézet, Budapest. inotai.andras@gytk.sote.hu
authors.forename: András
authors.initials: A
authors.lastname: Inotai
authors.forename: Zoltán
authors.initials: Z
authors.lastname: Kaló
authors.forename: Agnes
authors.initials: A
authors.lastname: Mészáros
mesh_terms: D003362:Cost-Benefit Analysis; D003657:Decision Making; D003661:Decision Support Techniques; D003663:Decision Trees; D003695:Delivery of Health Care / Q000191:economics*; D006801:Humans; D008390:Markov Chains; D018803:Models, Economic