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Using an Agent-based Simulation for Predicting the Effects of Patients Derivation Policies in Emergency Departments

机译:使用基于代理的模拟来预测急诊科中患者派生策略的效果

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The increasing demand of urgent care, overcrowding of hospital emergency departments (ED) and limited economic resources are phenomena shared by health systems around the world. It is estimated that up to 50% of patients that are attended in ED have non complex conditions that could be resolved in ambulatory care services. The derivation of less complex cases from the ED to other health care devices seems an essential measure to allocate properly the demand of care service between the different care units. This paper presents the results of an experiment carried out with the objective of analyzing the effects on the ED (patients’ Length of Stay, the number of patients attended and the level of activity of ED Staff) of different derivation policies. The experiment has been done with data of the Hospital of Sabadell (a big hospital, one of the most important in Catalonia, Spain), making use of an Agent-Based model and simulation formed entirely of the rules governing the behaviour of the individual agents which populate the ED, and due to the great amount of data that should be computed, using High Performance Computing.
机译:紧急护理需求的增长,医院急诊部门的人满为患以及经济资源有限是世界各地卫生系统共享的现象。据估计,在急诊室就诊的患者中,多达50%的情况很复杂,可以通过非卧床护理服务解决。从急诊部向其他卫生保健设备派生较不复杂的病例似乎是在不同护理单位之间适当分配护理服务需求的一项重要措施。本文介绍了一项实验的结果,目的是分析不同派生策略对ED的影响(患者的住院时间,就诊人数和ED工作人员的活动水平)。实验是利用Sabadell医院(一家大型医院,西班牙加泰罗尼亚最重要的医院之一)的数据完成的,它使用了基于Agent的模型,并且模拟完全由支配各个Agent行为的规则构成由于要使用高性能计算来计算大量数据,因此它填充了ED。

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