对于产前和产后情节的OMOP CDM规范化EHR的计算表型化:一个信息学框架和对我们所有人的临床实施
Tianchu Lyu1, Chen Liang1,2
1University of South Carolina, Columbia, South Carolina, USA.
AMIA ... Annual Symposium proceedings. AMIA Symposium
|January 15, 2024
概括
本研究引入了一个计算框架,使用电子健康记录 (EHR) 准确识别怀孕阶段. 这通过精确分析产前和产后护理,改善了对母亲和婴儿健康的研究.
科学领域:
- 计算健康信息学 计算健康信息学
- 产科和妇科研究研究 产科和妇科研究
- 电子健康记录 (EHR) 数据分析 数据分析
背景情况:
- 准确的时间数据在怀孕护理中至关重要,因为临床特征因妊娠阶段而异.
- 电子健康记录 (EHR) 在准确定义怀孕情节和事件时间表方面存在挑战.
- 现有的EHR表型化方法难以应对怀孕的时间复杂性.
研究的目的:
- 为产前和产后发作开发一个全面的计算表型框架.
- 为了应对时间相对论和准确的情节区分在怀孕的EHR数据的挑战.
- 通过使用EHR数据,加强对母亲和婴儿健康结果的分析.
主要方法:
- 引入了"时间相对论"的概念,用于怀孕事件分析.
- 开发了一个基于观察医学结果伙伴关系 (OMOP) 共同数据模型 (CDM) 的计算表型框架.
- 实施和验证了"我们所有人"国家电子健康记录数据库的框架.
主要成果:
- 成功识别了6280个怀孕,准确的开始和结束日期.
- 分析了来自5399名女性患者的数据.
- 证明了框架能够区分不同的怀孕护理情节的能力.
结论:
- 拟议的框架允许在EHR数据中准确识别怀孕情节.
- 这有助于改善复杂的临床事件和妊娠性疾病的表型.
- 增加了研究机会,以改善母亲和婴儿健康结果.
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