A novel configurable agent-based simulation model for reducing patient's waiting time in any oncology department
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Nowadays, the increasing of demand and the progressive decrease of resources are causing an increase of patient's waiting time in many chemotherapy oncology departments. The reduction of these waits is one of the main goal of any healthcare manager, since it implies to enhance the quality of health services and to avoid claims and disappointments. Simulation models are considered an effective tool for identifying possible ways for improving the oncology patient's pathway. Differently from the typical discrete-event simulations existing in the literature, in this paper a novel agent-based approach, which can be adapted to the needs of any oncology department, is presented. The model is statistically validated exploiting data collected from a real oncology unit chosen as case study and several alternative scenarios have been tested in order to improve the performance of the system.
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