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开发基于便携式电子健康记录的算法,以识别患有糖尿病视网膜病变的个人
medRxiv : the preprint server for health sciences
|November 28, 2023
概括
开发了算法来识别糖尿病视网膜病变 (DR) 病例和电子健康记录 (EHR) 的控制. 这些算法在多个医疗保健系统中表现出强的性能,改进了高通量查的现有方法.
科学领域:
- 眼科医生 眼科 眼科
- 医疗信息学 医疗信息学
- 生物统计学 生物统计学
背景情况:
- 糖尿病视网膜病变 (DR) 是导致视力丧失的主要原因,需要有效的识别方法.
- 电子健康记录 (EHR) 提供了丰富的数据来源,用于识别患者队列,用于研究和临床护理.
研究的目的:
- 开发,验证和实施算法,用于识别糖尿病视网膜病变 (DR) 病例和来自EHR的对照.
- 评估这些算法在各种医疗保健系统中的性能.
主要方法:
- 基于EHR的算法被开发和验证,使用来自三个独立的EHR系统的数据:VUMC,VANEOHS和MGB.
- 病例识别需要特定的DR诊断代码或代码和临床数据的组合.
- 对照的鉴定包括糖尿病的证据和眼科检查.
主要成果:
- 算法表现出强的性能,正预测值 (PPV) 从0.84到0.94不等,负预测值 (NPV) 从0.76到0.97不等.
- 开发的算法在NPV方面显著超过了传统的全现象关联研究 (PheWAS) 定义.
- 申请百万退伍军人计划确定了超过62,000个DR病例,其中包括大量的非裔美国人和西班牙裔个人.
结论:
- 开发的EHR算法是强大的,在多个医疗保健中心都表现良好.
- 这些算法为DR病例和控制识别提供了与现有的高通量方法相比更好的NPV.
- 鼓励独立验证和EHR特定特征的整合,以进一步提高算法性能.
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