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The emergency department (ED) is the first point of contact in a hospital, and managing the inflow and outflow of patients using a decision support system can help the providers and other stakeholders optimally utilize the limited resources available. The limited resources observed in this research are the providers and the bed resources available in the pods (or different treatment areas in the ED). These limited resources often lead to problems like diversion and overcrowding in the ED, and predicting when these scenarios are likely to happen is very important in the optimal utilization of these resources. The decision support system described in this chapter employs the use of agent-based models to simulate a real-life system. It utilizes the Emergency Department Information System (EDIS) historical dataset from the Seven Oaks General Hospital emergency department (SOGH-ED). The agent-based NetLogo simulation assists in decision support, by helping the user determine the best combination of hospital resources that will lead to a more stable system. This agent-based model, developed using the NetLogo simulation software, was run using the same scenarios evident in the SOGH-ED, and a comparison was made with the historical dataset for validation. In this chapter, we describe how we used the causal link and the stock and flow modeling paradigms to analyze the coupling of the system between different scales and how we used the agent-based modeling concept to build the model.

DOI: 10.1007/978-3-319-73636-5_15

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