基于替代索赔的算法对1型,2型和妊娠期糖尿病在怀孕期间的有效性
Deliwe P Ngwezi1, Anamaria Savu1, Roseanne O Yeung1
1Department of Medicine, University of Alberta, Edmonton, Alberta, Canada; Canadian VIGOUR Center, Edmonton, Alberta, Canada.
Canadian journal of diabetes
|July 14, 2023
概括
在孕妇中准确识别先前存在的1型或2型糖尿病 (T1DM/T2DM) 和妊娠期糖尿病 (GDM) 是可能的,使用结合分娩住院和门诊记录的算法.
科学领域:
- 医疗信息学 医疗信息学
- 公共卫生 公共卫生
- 产科和妇科 产科和妇科
背景情况:
- 准确识别怀孕期间的糖尿病对于孕产妇和胎儿的健康至关重要.
- 对于糖尿病分类的现有行政数据方法需要验证.
研究的目的:
- 评估使用行政健康记录的算法的准确性,以识别孕妇先前存在的1型或2型糖尿病 (T1DM/T2DM) 和妊娠期糖尿病 (GDM).
- 为了比较不同国际疾病分类第十次修订 (ICD-10) 基于代码的算法的性能.
主要方法:
- 使用临床糖尿病注册表作为黄金标准.
- 连接注册表数据与928例怀孕 (2002年至2009年) 的行政健康记录.
- 根据来自分娩住院和门诊的ICD-10代码评估了四种算法,其中包括一个算法的妊娠前数据.
主要成果:
- 算法#3 (分娩住院+怀孕期间门诊) 显示了最高的真实阳性率:T1DM为94%,T2DM为72%,GDM为99.9%.
- 使用算法#3,行政数据与注册表之间的总体一致率为97%.
- 算法#4,包括怀孕前的数据,与算法#3相比,显示出最小的改善.
结论:
- 结合从分娩住院和妊娠期间门诊记录的ICD-10代码的算法准确地识别了T1DM,T2DM和GDM的妇女.
- 这种经过验证的算法可以使用行政数据改善孕妇糖尿病监测和管理.
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