Patient Flow Congestion Control Based on Stochastic Timed Petri Net Model

Naijun Shen, Jun Wang, Jiacun Wang, Xingyun Liu, Lijun Yang, Yu Wang
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Abstract

Resource allocation has always been an important part of healthcare systems. The goal is to allocate resources more reasonably and thus reduce the waiting time of patients during their visits to healthcare facilities. In this paper, we use stochastic timed Petri nets (STPN) to model and simulate medical service processes and evaluate their performance. In particular, we propose a mechanism with which more doctors can be added to a service unit when a patient flow congestion is detected, and the added doctors will be freed when congestion is relieved. A case study is performed to show the effectiveness of this new adaptive resource allocation mechanism.
基于随机定时Petri网模型的患者流拥塞控制
资源配置一直是医疗卫生系统的重要组成部分。目标是更合理地分配资源,从而减少患者在访问医疗机构期间的等待时间。在本文中,我们使用随机定时Petri网(STPN)来建模和模拟医疗服务过程并评估其性能。具体来说,我们提出了一种机制,当检测到病人流拥堵时,可以向服务单元增加更多的医生,当拥堵缓解时,增加的医生将被释放。通过实例分析,验证了该自适应资源分配机制的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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