了解临床医生对CONCERN预警系统的使用模式:来自多站点实用集群随机对照试验的见解
Rachel Y Lee1, Kenrick D Cato2,3, Patricia C Dykes4,5
1Columbia University, Department of Biomedical Informatics, New York, NY.
Studies in health technology and informatics
|August 8, 2025
概括
作为人工智能工具的CONCERN早期预警系统 (EWS) 显著降低了住院患者的死亡率和住院时间. 临床医生与EWS的接触详细显示,根据角色,班次和单位类型而有所不同,为优化医疗保健中AI实施提供了洞察力.
科学领域:
- 医疗保健信息学 医疗保健信息学
- 临床决策支持系统 临床决策支持系统
- 人工智能在医学中的应用
背景情况:
- 住院患者面临临临床恶化的风险.
- 早期发现和干预对于改善患者的治疗结果至关重要.
- 现有的预警系统 (EWS) 可以通过人工智能来提高预测准确性.
研究的目的:
- 为了分析临床医生的参与模式,使用CONCERN早期预警系统 (EWS) 详细显示.
- 了解用户与人工智能驱动的临床决策支持的互动如何变化.
- 确定影响CONCERN EWS使用的因素,以优化其实施和影响.
主要方法:
- 电子健康记录 (EHR) 日志文件数据的回顾性分析.
- 检查了2572例由393名临床医生发布的CONCERN详细显示器.
- 数据按临床医生的角色,患者的并发症,地点,班次和单位类型分层.
主要成果:
- 注册护士和订单提供者表现出与CONCERN详细展示的平衡参与.
- 使用主要是在白天班 (89.9%) 和急症病房 (83.5%).
- 基于临床医生的角色,患者和护理环境特征,观察到不同的使用模式.
结论:
- 临床医生与CONCERN EWS的接触受到各种因素的影响,包括用户角色和护理环境.
- 了解这些使用模式是完善人工智能驱动工具实施策略的关键.
- 优化临床医生与人工智能决策支持的互动,可以提高其有效性,改善患者的治疗结果.
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