探索住院EMR算法的可靠性,以识别糖尿病
Seungwon Lee1,2, Elliot A Martin3,2, Jie Pan3,4
1Community Health Sciences, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada seungwon.lee@ucalgary.ca.
BMJ health & care informatics
|December 20, 2023
概括
开发用于住院糖尿病患者识别的电子病历 (EMR) 算法可以克服行政数据滞后. 自由文本数据算法显示性能与ICD编码方法相比或优于它们,改善了及时的护理交付.
科学领域:
- 医疗信息学 医疗信息学
- 临床数据科学 临床数据科学
- 糖尿病研究 糖尿病研究
背景情况:
- 准确,实时识别住院患者的医疗状况对于卫生系统至关重要.
- 目前的并发症算法因行政数据集成而面临延误.
- 电子医疗记录 (EMR) 数据为及时的条件表型化提供了一个有希望的替代方案.
研究的目的:
- 开发和评估基于EMR数据的算法,用于住院糖尿病患者的表型.
- 为了比较不同EMR数据源用于糖尿病识别的性能.
- 评估自由文本数据在改善糖尿病病例识别方面的有用性.
主要方法:
- 对3040人进行的图表审查,其中583人患有糖尿病,作为黄金标准.
- 使用EMR数据,包括实验室结果,药物和自由文本笔记,开发了五种不同的糖尿病算法.
- 基于灵敏度 (SN) 和正预测值 (PPV) 评估了算法性能.
主要成果:
- "所有文档类型"算法实现了高性能:SN 0.95,特异性 (SP) 0.98,PPV 0.94和负预测值 (NPV) 0.99.
- 药物和实验室算法在SN 0.90,SP 0.95,PPV 0.80和NPV 0.97.7的情况下表现出强的性能.
- ICD编码的数据算法显示SN为0.84,SP为0.98,PPV为0.93和NPV为0.96.
结论:
- 基于EMR的糖尿病算法,特别是那些使用自由文本数据的算法,可以实现与传统ICD编码方法相当或优于的性能.
- 这些算法可以补充现有方法,为住院病例识别提供更及时的方法.
- 基于住院EMR的算法对于高效的资源规划和及时的护理提供至关重要.
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