Using Future Information to Reduce Waiting Times in the Emergency Department via Diversion
Using Future Information to Reduce Waiting Times in the Emergency Department via Diversion
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利用未来信息通过分流减少急诊科的等待时间
DOI：
10.1287/msom.2015.0573
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Carri W. Chan
中科院分区：
文献类型：
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作者：
Kuang Xu;Carri W. Chan
在医疗保健环境中，预测模型的发展一直在增长；一个这样的领域是病人到达急诊室（ED）的预测。这些工作背后的一般前提是，这些模型可以用来帮助管理始终面临高拥塞的ED。在这项工作中，我们提出了一类积极主动的政策，利用潜在患者到达的未来信息，有效地管理急诊室的入院，同时减少最终接受治疗的患者的等待时间。拟议的策略不是等待排队的标准策略，而是利用预测来识别何时拥堵会增加，并在情况变得“太糟糕”之前主动转移病人。我们证明，与实践中使用的标准策略相比，所提出的策略提供了延迟改进。我们还考虑了预测模型提供的信息中误差的影响，并发现即使有噪声的预测，我们也可以…
The development of predictive models in healthcare settings has been growing; one such area is the prediction of patient arrivals to the emergency department (ED). The general premise behind these works is that such models may be used to help manage an ED that consistently faces high congestion. In this work, we propose a class of proactive policies that utilize future information of potential patient arrivals to effectively manage admissions into an ED while reducing waiting times for patients who are eventually treated. Instead of the standard strategy of waiting for queues to build before diverting patients, the proposed policy utilizes the predictions to identify when congestion is going to increase and proactively diverts patients before things get “too bad.” We demonstrate that the proposed policy provides delay improvements over standard policies used in practice. We also consider the impact of errors in the information provided by the predictive models and find that even with noisy predictions, ou...