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Early Warning Software for Emergency Department Crowding
arXiv - EE - Systems and Control Pub Date : 2023-01-22 , DOI: arxiv-2301.09108
Jalmari Tuominen, Teemu Koivistoinen, Juho Kanniainen, Niku Oksala, Ari Palomäki, Antti Roine

Emergency department (ED) crowding is a well-recognized threat to patient safety and it has been repeatedly associated with increased mortality. Accurate forecasts of future service demand could lead to better resource management and has the potential to improve treatment outcomes. This logic has motivated an increasing number of research articles but there has been little to no effort to move these findings from theory to practice. In this article, we present first results of a prospective crowding early warning software, that was integrated to hospital databases to create real-time predictions every hour over the course of 5 months in a Nordic combined ED using Holt-Winters' seasonal methods. We showed that the software could predict next hour crowding with a nominal AUC of 0.98 and 24 hour crowding with an AUC of 0.79 using simple statistical models. Moreover, we suggest that afternoon crowding can be predicted at 1 p.m. with an AUC of 0.84.

中文翻译:

急诊科拥挤预警软件

急诊科 (ED) 拥挤是公认的对患者安全的威胁,并且反复与死亡率增加相关。对未来服务需求的准确预测可以带来更好的资源管理,并有可能改善治疗效果。这种逻辑激发了越来越多的研究文章,但几乎没有任何努力将这些发现从理论转化为实践。在这篇文章中,我们展示了一个前瞻性拥挤预警软件的初步结果,该软件被集成到医院数据库中,以使用 Holt-Winters 的季节性方法在北欧联合 ED 的 5 个月内每小时创建一次实时预测。我们展示了该软件可以用 0.98 的标称 AUC 预测下一个小时的拥挤和用 AUC 0 预测 24 小时的拥挤。79 使用简单的统计模型。此外,我们建议可以在下午 1 点预测下午拥挤,AUC 为 0.84。
更新日期:2023-01-24
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