使用两态马尔可夫模型调查巴尔的摩市急诊部门的级联事件

IF 1.5 Q3 HEALTH CARE SCIENCES & SERVICES
Xu Zhang , Bruce Golden , Edward Wasil , Laura Pimentel , Jon Mark Hirshon
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引用次数: 0

摘要

急诊科(ED)使用率过高或无法进入急诊科可能会导致一个城市的一家又一家医院不接受需要紧急医疗护理的新患者。我们称之为级联事件。在本文中,我们使用双状态马尔可夫模型研究了2018年和2019年巴尔的摩市11个ed之间的级联事件。此外,利用转移概率来监测级联事件的演变。同时,我们预测每个州的预期剩余时间。在计算和比较了每个ED发生级联事件的概率之后,我们最终使用聚类分析确定了ED之间的相似性和异质性。我们的研究结果表明,约翰霍普金斯医院、约翰霍普金斯湾景医疗中心(JH Bayview)、西奈医院和马里兰大学医学中心(UMMC)的持续黄色警报与城市发生连锁事件的可能性很大,影响到所有11家医院。工作日大大增加了发生连锁事件的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigating cascading events for emergency departments in Baltimore City using a two-state Markov model

The event of high emergency department (ED) utilization or inaccessibility to the ED may result in hospital after hospital in a city not accepting new patients in need of urgent medical care. We call this a cascading event. In this paper, we investigate cascading events among 11 EDs in Baltimore City in 2018 and 2019 using a two-state Markov model. Additionally, the transition probabilities are used to monitor the evolution of cascading events. Meanwhile, we predict the expected remaining hours in each state. After we calculate and compare the probabilities of having a cascading event for each ED, we finally identify the similarity and heterogeneity among EDs using cluster analysis. The findings of our study reveal that the continuous yellow alerts at Johns Hopkins Hospital, Johns Hopkins Bayview Medical Center (JH Bayview), Sinai Hospital, and the University of Maryland Medical Center (UMMC) are associated with a large chance of having a cascading event in the city that affects all 11 hospitals. Weekdays dramatically increased chances of having a cascading event.

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来源期刊
Operations Research for Health Care
Operations Research for Health Care HEALTH CARE SCIENCES & SERVICES-
CiteScore
3.90
自引率
0.00%
发文量
9
审稿时长
69 days
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