Authors: Nikolas Popper, Michael Gyimesi, Günther Zauner, Felix Breitenecker
Modelling and Simulation in Health Economy has two main challenges to cope with. First modelling aspects are widely scattered, dealing with problems in economy, epidemics, medical aspects and more. Second the identification of models is difficult as data sets are in some ways ?hided? in different areas (clinical studies, statistics, economic studies, ..), quality and type of given data sets are various and relationships are complicate to identify. This contribution shows the achievements of the cooperation with one of the most important institution in the Austrian health care system, which was started to optimize the solutions of problems mentioned above and to integrate new modelling approaches for analysis of data. An outline of the different aspects like implementation of big data sets in modelling of diabetes mellitus, comparisons of different modelling approaches, combining such approaches to get more effective models and implementing models based on clinical problems should be given.