通过使用OHDSI工具与OMOP共同的数据模型实现非洲人口健康数据的数据共享和利用
Sylvia Kiwuwa-Muyingo1, Jim Todd2, Tathagata Bhattacharjee2
1African Population and Health Research Center (APHRC), Nairobi, Kenya.
Frontiers in public health
|June 26, 2023
概括
INSPIRE平台使用观察医学结果伙伴关系共同数据模型来标准化COVID-19数据收集和共享. 这便于人工智能驱动的分析,以获得公共卫生见解和患者康复策略.
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
- 公共卫生 公共卫生
背景情况:
- 随着COVID-19的爆发,人们越来越需要强大的数据收集和分析.
- 现有的COVID-19数据管理实践缺乏标准化,阻碍了数据的重用.
- 撒哈拉以南非洲地区因数据碎片化而面临着优化公共卫生响应和患者康复的挑战.
研究的目的:
- 建立一个标准化的平台来收集,记录和传播COVID-19数据.
- 利用基于云的解决方案和共同的数据模型来改善数据的可访问性和分析.
- 为了实现跨研究机构和数据网络的安全和受控的数据共享.
主要方法:
- 实施观察医疗结果伙伴关系 (OMOP) 共同数据模型 (CDM) 作为云中的服务平台 (PaaS).
- 对于个别研究组织和数据网络来说,利用云端网关.
- 使用数据映射和术语映射来构建提取,转换,加载 (ETL) 进程来填充CDM.
- 评估COVID-19协调数据的INSPIRE平台 (PEACH) 协调了肯尼亚和马拉维的数据.
主要成果:
- INSPIRE PaaS提供了FAIR数据管理,分析和共享功能.
- 该平台支持使用OMOP CDM在联合模型中协调各地数据.
- 与OMOP集成的AI技术可以通过干预来发现和评估COVID-19患者的途径.
结论:
- INSPIRE平台提供了一个标准化,基于云计算的解决方案,用于管理和分析COVID-19数据.
- 它增强了数据互操作性,并为公共卫生和患者护理提供了人工智能驱动的见解.
- 该平台促进安全的数据共享,同时赋予数据生产者对其数据的控制权.
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