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DER VERLAG IST IN DER ZEIT VOM 12.06.2019 BIS 23.06.2019 AUSCHLIESSLICH PER EMAIL ERREICHBAR.
aktualisiert am 13. Juni 2019
978-3-8439-2365-1, Reihe Informatik
Hybrid Simulation for Prospective Healthcare Decision-Support: System Dynamics, Discrete-Event and Agent-Based Simulation
252 Seiten, Dissertation Universität Erlangen-Nürnberg (2015), Hardcover, B5
Demographic changes, new technical opportunities, and a growing global demand for healthcare services are only three reasons why several decision-makers in healthcare are faced with numerous challenges. In particular, due to an improved life expectancy and the population aging, the health industry is getting highly essential for the economic growth in the future and the competitiveness at global markets. Making decisions in healthcare is usually a non-trivial task. It can be compared to a situation where “everything affects everything else” and no clear boundaries exist. In other words, an apparently harmless decision can affect stable things implicitly, and by the same token, costs savings on the one side can produce additional costs somewhere else. However, it is important to make decisions very fast in order to save people from severe damages and to profit from new innovative technologies. This is the reason why powerful tools for decision-making in healthcare are required.
This work describes a hybrid simulation approach that can be used within the scope of prospective healthcare decision-support. In particular, it will be explained how established simulation methods, such as System Dynamics, the process-oriented Discrete-Event Simulation and the Agent-Based Simulation, can be used to develop common models at different levels of abstraction. In this context we highlight a modular hybrid simulation environment, modeling issues describing the human behavior, and design aspects in typical decision-making situations. Furthermore, we introduce the implementation of several concepts in the HealthDS Framework and discuss two most representative case studies.