Implementation of automated early warning decision support to detect acute decompensation in the emergency department improves hospital mortality.
Implementation of automated early warning decision support to detect acute decompensation in the emergency department improves hospital mortality.
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DOI：
10.1136/bmjoq-2021-001653
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发表时间：
2022-04
期刊：
影响因子：
1.4
通讯作者：
Naik AD
中科院分区：
文献类型：
--
作者：
Howard C;Amspoker AB;Morgan CK;Kuo D;Esquivel A;Rosen T;Razjouyan J;Siddique MA;Herlihy JP;Naik AD
基于临床和生理数据的早期预警警报评分已被证明可预测急诊科（艾德）患者的失代偿风险。然而，使用这些系统影响艾德中患者结果的效果很难一致地确定。在比较以前的研究的困难的一部分是各种系统的选择和错误的实施模式。我们的自动化系统与基于生命体征的国家预警评分的独特结合有助于减少识别和稳定失代偿患者的延迟和错误。我们的研究表明，使用自动决策支持监测和警报系统，以触发警报艾德患者降低了调整后的住院死亡率和住院时间。
Early warning alert scores based on clinical and physiological data have been shown to be predictive of risk of decompensation in patients in the emergency department (ED). However, the effect of using these systems to influence patient outcomes in the ED has been difficult to ascertain consistently. Part of the difficulty in comparing previous studies are the various systems chosen and faulty implementation models. The unique coupling of our automated system with the vital sign-based National Early Warning Score score helped to reduce delay and error in the attempt to identify and stabilise decompensating patients. Our study demonstrates that using an automated decision support surveillance and alert system to trigger alerts for ED patients reduced both adjusted hospital mortality and hospital length of stay.