紧急护理数据集 (ECDS) 的价值 预测死亡率和住院患者入院的演示代码
Betsy Teresa1, Mohammed Subhi2, Adrian Boyle1
1Emergency Medicine, Cambridge University Hospitals National Health Service (NHS) Foundation Trust, Cambridge, GBR.
Cureus
|April 15, 2024
概括
提出投诉的急诊室 (ED) 可以预测患者的死亡风险. 诸如心脏骤停之类的高风险投诉需要立即注意,这有助于自动分拣工具的开发.
科学领域:
- 紧急医疗 紧急医疗
- 医疗信息学 医疗信息学
背景情况:
- 紧急服务部门 (ED) 在早期识别患者死亡率和入院风险方面面临挑战.
- 现有的分级表早于现代电子医疗记录 (EHR).
- 国家紧急护理数据集 (ECDS) 和电子健康记录使标准化数据收集和自动分拣的可能性成为可能.
研究的目的:
- 在标准化国家数据集中量化与特定投诉相关的死亡率和住院风险.
- 为开发自动分拣工具和临床决策支持系统提供信息.
主要方法:
- 一项观察性回顾性队列研究对2021年访问单个ED的84,999名患者进行了观察.
- 从随后的出席中提出投诉被排除在外.
- 患者数据与死亡记录手动匹配,包括所有在30天内死亡的死亡.
主要成果:
- 在急救服务30天内,有1,159人死亡.
- 在心脏骤停 (78.1%),心脏骤停由于创伤 (50%) 和呼吸骤停 (50%) 中观察到最高的死亡率.
- 其他高风险投诉包括昏昏欲睡 (12%),低温 (13%),色 (10%);胸痛 (0.6%) 是低风险的.
结论:
- 在ECDS中记录的最初提出的投诉可以有效地识别死亡风险较高和较低的患者.
- 这些数据对于构建用于紧急护理的自动分拣模型非常有价值.
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