Academic articles

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.

We propose an epidemic agent-based simulation model for disease (TB) transmission dynamics study and to find out the role of various contact networks. Our model simulates the TB epidemic course across a single population and uses a hierarchical network of contacts in three levels, typical to the transmission of airborne diseases (Mossong et al. 2005). Parameters are chosen from the literature, and the model is calibrated to a setting of high TB incidence. We use our model to study the transmission dynamics at an individual level with regard to the timing and distribution of secondary infections from a single source. The average time for disease diffusion to reach 50% of infections at an individual level is estimated, and the timing patterns are compared among different networks. We perform sensitivity analysis of results with regard to multiple parameter values, and discuss the implications for TB control policy.

After its first introduction in 1999, West Nile Virus (WNV) has spread very widely along the east coasts of the United States before appearing in Texas where 1792 cases were reported of which 82 were fatal in 2012. The interesting patterns and behavior of the virus and its amplified impact on the county of Dallas drove this work. This paper encompasses a thorough development of a systems dynamics simulation model of virus's infectious behavior and dynamics in Dallas County, TX utilizing historical data collected and the aid of suitable software packages.

This paper discusses the development of an individual based simulation of interventions for better treatment of patients with abdominal aortic aneurysms (AAA). The interdisciplinary subject required collaboration of medical doctors, Health Technology Assessment (HTA) experts and modelers.

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.

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.

AnyLogic è un ambiente di modellazione virtuale di sistemi discreti, continui ed ibridi. Con questo strumento è possibile creare prototipi di sistemi durante le fasi di studio, progettazione o sviluppo, attraverso cui esplorare aspetti e dettagli della progettazione o della implementazione dei relativi sistemi in modo semplice e privo di rischi

This interdisciplinary research focuses on improving the oral health of older adults as a means of enhancing their overall wellbeing and quality of life. Periodontal disease is a risk factor for other chronic illnesses, notably diabetes and cardiovascular disease. In order to identify policies that improve oral health for older adults, a dynamic modeling approach that considers community and individual level factors is utilized.

A simulation model called VirSim was developed to aid policy making in Sweden. The model simulates the spread of pandemic influenza, using real population data on a national and regional level. Swedish authorities wanted a model that was both quick to run and to implement as a complement to the existing model MicroSim.

Emergency Departments (EDs) require advanced support systems for monitoring and controlling their processes: clinical, operational, and financial. A prerequisite for such a system is comprehensive operational information (e.g. queueing times, busy resources,…), reliably portraying and predicting ED status as it evolves in time. To this end, simulation comes to the rescue, through a two-step procedure that is hereby proposed for supporting real-time ED control.