一个经验证的基于电子医疗记录的算法,用于识别患有严重疾病的住院患者
Laura A Schoenherr1, Yuika Goto1, Joanna Sharpless1
1Division of Palliative Medicine, Department of Medicine, University of California San Francisco, San Francisco, California, USA.
一个电子医疗记录算法有效地识别了严重疾病的住院患者,从而实现了主动性息治疗. 这种方法确保更多的患者能够平等地获得基本的支持服务.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 抚慰性护理医学 抚慰性护理医学
- 临床信息学 临床信息学
背景情况:
- 公平获得息治疗需要有效识别患有严重疾病的患者.
- 基于人口的方法对于系统和主动的息护理提供至关重要.
研究的目的:
- 在电子病历 (EMR) 中开发和验证一个算法,以识别患有严重疾病的住院患者.
- 为更广泛的患者群体提供积极的息护理咨询服务.
主要方法:
- 使用文献评论,临床专业知识和图表评论,代地开发了一个算法.
- 对算法性能进行了验证,对息治疗医生的专家共识进行了验证.
- 最终的算法在EMR中实施,用于9个月内每天对住院成年人进行查.
主要成果:
- 最终的算法表现出高性能:89%的灵敏度,82%的特异性,80%的正预测值和90%的负预测值.
- 平均而言,54%的住院患者 (每天284人) 检测出严重疾病标准呈阳性.
- 每天平均有38名患者新增查结果呈阳性,这表明需要大量的息治疗.
结论:
- 嵌入EMR的数据可以可靠地识别患有严重疾病的住院患者.
- 这种方法是朝着积极主动和系统的息护理提供迈出的关键一步.
- 经过验证的算法可以改善所有受益人获得息护理服务的机会.
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