多站点实用集群随机控制试验CONCERN早期预警系统
Sarah C Rossetti1,2, Patricia C Dykes3,4, Chris Knaplund1
1Columbia University Irving Medical Center, Department of Biomedical Informatics, New York, NY.
medRxiv : the preprint server for health sciences
|June 17, 2024
概括
通过使用护理文档,CONSERN早期预警系统 (EWS) 显著降低了患者的死亡率和住院时间. 该系统可以改善早期检测患者病情恶化,提高临床结果.
科学领域:
- 临床信息学 临床信息学
- 患者安全 患者安全
- 改善医疗保健质量 改善医疗保健质量
背景情况:
- 患者病情恶化的延迟检测往往源于早期预警系统 (EWS) 的有限数据和团队局势意识不佳.
- 这可能导致临床干预延迟,患者的治疗结果更差.
研究的目的:
- 评估RN (CONCERN) 早期预警系统 (EWS) 对患者死亡率和停留时间的影响.
- 测试一个假设,即用CONCERN EWS数据告知护理团队可以降低死亡率和停留时间.
主要方法:
- 一个为期一年的多站点实用性临床试验,涉及急性和重症监护病房的集群随机化.
- 在CONCERN EWS干预中,使用实时护理监测文档模式的机器学习来预测患者病情恶化的风险.
- 包括急症和重症监护病房的成年患者,但不包括那些接受舒适护理或有特定提前指示的患者.
主要成果:
- 与通常护理组相比,干预组 (CONCERN EWS) 的住院死亡风险降低了35.6%,住院时间减少了11.2%.
- 在干预组中观察到败血症风险下降7.5%.
- 干预组中注意到意外ICU转移 (24.9%) 的风险增加.
结论:
- 将基于护理监测模式的全医院EWS整合到EHR工作流程中,可以显著降低住院死亡率,败血症发病率和住院时间.
- 康塞恩 (CONCERN) EWS展示了通过提升恶化的早期检测来提高患者安全和医疗保健效率的潜力.
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