将挪威登记处与OMOP共同数据模型协调:绘制怀孕和COVID-19研究的挑战和机遇
Nhung Th Trinh1, Jared Houghtaling2, Fabian Lm Bernal3
1PharmacoEpidemiology and Drug Safety Research Group, Department of Pharmacy, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway.
International journal of medical informatics
|August 17, 2024
概括
挪威的健康登记数据已成功与观察医疗结果伙伴关系共同数据模型 (OMOP CDM) 协调. 这为联邦COVID-19研究和数据合作伙伴提供了宝贵的资源.
科学领域:
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
- 流行病学 流行病学
背景情况:
- 挪威的卫生登记册对于管理,研究和应急准备至关重要.
- 协调各种健康数据对于大规模分析至关重要.
研究的目的:
- 将挪威全人口健康登记数据与观察医学结果伙伴关系共同数据模型 (OMOP CDM) 协调一致.
- 通过COVID-19相关信息以OMOP格式丰富现实世界的数据.
- 建立一个联邦COVID-19研究基金会.
主要方法:
- 来自六个注册表 (2018-2021) 的数据被映射到 OMOP CDM v5.3.3 中.
- 一个提取-转换-负载 (ETL) 管道被开发和精细使用质量检查.
- 实现了源代码的自动和手动映射,包括创建定制概念.
主要成果:
- 统一了来自5,673,845个人的15亿行数据.
- 数据包括804,277例怀孕和382,516例COVID-19阳性测试.
- 实现了高一致性,99.8%的质量检查通过,并绘制了237个非标准代码.
结论:
- 挪威注册数据成功地与OMOP CDM协调,为联合的COVID-19研究提供了宝贵的来源.
- 绘制地图的经验为与北欧卫生登记处合作的数据合作伙伴提供了重要的价值.
- 高数据一致性验证了ETL过程和协调数据集的实用性.
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