Partial Paradigm Hiding and Reusability in Hybrid Simulation Modeling Using the Frameworks Health-DS and I7-Anyenergy A. Djanatliev, P. Bazan, R. German, University of Erlangen-Nuremberg. Winter Simulation Conference, 2014.

Many complex real-world problems which are difficult to understand can be solved by discrete or continuous simulation techniques, such as Discrete-Event-Simulation, Agent-Based-Simulation or System Dynamics. In recently published literature, various multilevel and large-scale hybrid simulation examples have been presented that combine different approaches in common environments.
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An Agent-Based Explanation for 20th Century Living Situation Changes in America’s Severely and Persistently Mentally Ill Population Kyle L. Johnson, Dr. Dimitris Alevras, IBM Global Business Services; Dr. John Docherty, Dr. Erin Falconer, Otsuka Medical Affairs. AnyLogic Conference 2014

The largest public mental health facility in the United States is not a hospital; it is the Los Angeles County Jail. This paper describes an agent-based approach to explaining why prisons and jails house so many of America’s most seriously mentally ill. It traces this fact to the differing ways in which various housing situations react to mental illness and to legislation passed in the 1960’s, which allocated public funding away from state mental hospitals.
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The GAP-DRG Model: Simulation of Outpatient Care for Comparison of Different Reimbursement Schemes Patrick Einzinger, Niki Popper, Felix Breitenecker et al., Proceedings of the 2013 Winter Simulation Conference

In healthcare the reimbursement of medical providers is an important topic and can influence the overall outcome. We present the agent-based healthcare model, which allows a comparison of reimbursement schemes in outpatient care. It models patients and medical providers as agents. In the simulation of healthcare system, patients develop medical problems (i.e., diseases) and a need for medical services. This leads to utilization of medical providers. The reimbursement system receives information on the patients’ visits via its generic interface, which facilitates an easy replacement. We describe the assumptions of the model in detail and show how it makes extensive use of available Austrian routine care data for its parameterization. The model design is optimized for utilizing as much of these data as possible. However, many assumptions have to be simplifications. Further work and detailed comparisons with healthcare data will provide insight on which assumptions are valid descriptions of the real process.
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Prospective Healthcare Decision-Making By Combined System Dynamics, Discrete-Event And Agent-Based Simulation Anatoli Djanatliev, Reinhard German, Proceedings of the 2013 Winter Simulation Conference

Prospective Health Technology Assessment allows early decision making for innovative health care technologies. In our recent publications a hybrid simulation approach with System Dynamics and Agent-Based Modeling has been presented. This paper presents a mechanism to generate agents dynamically from SD models and extends the previously presented hybrid approach by process-oriented Discrete Event Simulation for hospital modeling.
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Large Scale Healthcare Modeling by Hybrid Simulation Techniques using AnyLogic Anatoli Djanatliev and Reinhard German, Computer Networks and Communication Systems Department of Computer Science 7. Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques

This paper describes a methodical and practical approach of hybrid model creation using the simulation tool AnyLogic. We focus on general modeling aspects and on advanced techniques using a Level-Based Architecture that help to develop large scale hybrid simulation models. An implementation of a stroke therapy use-case and its simulation results will be discussed. Finally, some practical ideas for validation will be outlined, as we experienced during the stroke use-case development.
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