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The problem of the last bed: Contextualization and a new simulation framework for analyzing physician decisions

机译:最后一张床的问题:上下文化和用于分析医生决策的新模拟框架

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Faced with a full Intensive Care Unit (ICU), physicians need to decide between turning away a new patient in need of critical care and creating a vacancy by prematurely discharging a current occupant. This dilemma is widely discussed in the medical literature, where the influencing factors are identified, the patient discharge process described and the patient health consequences analyzed. Nevertheless, the existing mathematical models of ICU management practices overlook many of the factors considered by physicians in real-world triage decisions.This paper offers a review of the medical and mathematical literature on patient discharge decisions, and a proposal for a new simulation framework to enable more realistic mathematical modeling of the real-world patient discharge process. Our model includes a) the times at which discharge decisions are made and setup times for patient transfer from the ICU to a general ward and preparation of an ICU bed for an incoming patient, in order to capture the impossibility of an immediate switch of patients; b) advance notice of the number of patients due to arrive from elective surgery requiring intensive postoperative care and potentially triggering the need for early discharges to avoid surgery cancelations; and c) patient health status (to reflect the dependency of physicians' discharge decisions on health indicators) by modeling length of stay with a phase-type distribution in which a medical meaning is assigned to each state.A simulation-based optimization method is also proposed as a means to obtain optimal discharge decisions as a function of the health status of current patients, the bed occupancy level and the number of planned arrivals from elective surgery over the following days. Optimal decisions should strike a balance between patient rejection and LoS reduction.This new simulation framework generates an optimal discharge policy, which closely resembles real decision-making under a cautious discharge policy, where the frequency of early discharge increases with the ICU occupancy level. This is a contrast with previous simulation models, which consider only the triage of the last bed, disregarding the pressures on physicians faced with high bed occupancy levels. (C) 2019 The Authors. Published by Elsevier Ltd.
机译:面对一个全部重症监护单元(ICU),医生需要在拒绝需要批判性护理的新患者并通过过早地排放当前乘员来创造空缺。这种困境在医学文献中广泛讨论,其中鉴定了影响因素,描述的患者放电过程和分析患者的健康后果。尽管如此,ICU管理实践的现有数学模型忽视了实际审查的医生审议的许多因素。本文提供了对患者排放决策的医疗和数学文献的审查,以及新的模拟框架的提案实现现实世界患者放电过程的更现实的数学建模。我们的型号包括a)在ICU向普通病房到普通病房的患者转移以及为入门患者的ICU床进行设置时的时间,以捕获不可能的患者的不可能性; b)提前通知患者的数量,因为抵达选修术后需要密集的术后护理,并可能引发早期排放需求以避免手术取消; C)患者健康状况(以反映医生对健康指标的依赖性)通过使用相位类型分布的延长长度来模拟,其中医学含义被分配给每个状态。基于仿真的优化方法也是如此提出作为作为当前患者的健康状况的函数获得最佳排放决策的手段,床占用水平和在接下来的选修手术中的计划抵达数量。最佳决策应在患者拒绝和减少之间取得平衡。这一新的模拟框架产生了最佳的灭息政策,这在谨慎的卸货政策下非常类似于真正的决策,其中提前排放频率随着ICU占用水平而增加。这与先前的仿真模型相比,这只考虑了上一张床的分流,忽视了医生面临的受压率,占用高床占用水平。 (c)2019年作者。 elsevier有限公司出版

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