开发和验证非呼吸器医院获得的肺炎半自动监测系统的选择算法
Anna Mueller1, Marc Pfister1, Mirjam Faes Hesse1
1Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, University of Zurich, Zurich, Switzerland.
概括
半自动监控系统提高了检测非呼吸器医院获得的肺炎 (nvHAP) 的效率. 复杂的算法显著降低了手动审查工作量,同时保持了对识别有风险的患者的高度敏感性.
科学领域:
- 医疗保健信息学 医疗保健信息学
- 传染病监测 传染病监测 传染病
- 临床操作 临床操作
背景情况:
- 非呼吸器医院获得的肺炎 (nvHAP) 是一种严重的医院感染,影响非输管患者.
- 传统的nvHAP手动监测方法耗时.
- 半自动化系统利用算法预选高风险患者进行手动确认,以提高效率.
研究的目的:
- 评估各种单个指标和算法的性能,以便预先选择面临 nvHAP 风险的患者.
- 为了比较不同监控策略的灵敏度和工作量减少.
主要方法:
- 用文献审查,专家意见和数据可用性来确定单个nvhap指标.
- 单个指标被组合成简单和复杂的算法.
- 算法和指标应用于157,902名患者的队列,其中947例确诊的nVHAP病例.
主要成果:
- 单个指标显示了可变的灵敏度 (35.1%至99.7%) 和工作量减少 (57.3%至98.4%).
- 结合多个因素的复杂算法实现了92%的灵敏度,同时减少了96.2%的手动审查.
- 这种复杂的算法所需查的患者数量为6.4人.
结论:
- 一些单一的指标和算法显示了高工作量减少和超过90%的灵敏度.
- 这些发现支持为nvHAP监测开发定制算法.
- 这些优化的算法可以帮助医疗机构提高监测效率和资源分配.
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