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陈佳齐, 吕明, 王泽, 杨孝荣, 武睿婕, 张同超, 李紫琳, 张媛. 国内外医学通用数据模型研究现状及跨队列研究模型建立模式[J]. 中国公共卫生, 2023, 39(9): 1207-1211. DOI: 10.11847/zgggws1141655
引用本文: 陈佳齐, 吕明, 王泽, 杨孝荣, 武睿婕, 张同超, 李紫琳, 张媛. 国内外医学通用数据模型研究现状及跨队列研究模型建立模式[J]. 中国公共卫生, 2023, 39(9): 1207-1211. DOI: 10.11847/zgggws1141655
CHEN Jiaqi, LÜ Ming, WANG Ze, YANG Xiaorong, WU Ruijie, ZHANG Tongchao, LI Zilin, ZHANG Yuan. Research on common medical data model and establishment of cross-cohort models at home and abroad[J]. Chinese Journal of Public Health, 2023, 39(9): 1207-1211. DOI: 10.11847/zgggws1141655
Citation: CHEN Jiaqi, LÜ Ming, WANG Ze, YANG Xiaorong, WU Ruijie, ZHANG Tongchao, LI Zilin, ZHANG Yuan. Research on common medical data model and establishment of cross-cohort models at home and abroad[J]. Chinese Journal of Public Health, 2023, 39(9): 1207-1211. DOI: 10.11847/zgggws1141655

国内外医学通用数据模型研究现状及跨队列研究模型建立模式

Research on common medical data model and establishment of cross-cohort models at home and abroad

  • 摘要: 由于医疗信息资源的多来源、多类型、非标准等特征,“信息孤岛”现象在医学研究中普遍存在。中国大型队列数据来源复杂、类型丰富,在实现队列间数据的整合、共享和利用时存在较大难度。为促进医疗健康资源数据的标准化融合,本研究在深入剖析国内外医学通用数据模型(CDM)研究现状的同时,进一步探索跨队列研究CDM建立模式,并结合我国精准医学背景下医疗数据融合共享中存在的关键问题提出相关建议,以此为跨队列研究数据的集成、整合、共享及利用提供参考思路。

     

    Abstract: The phenomenon of "information islands" in medical studies is becoming increasingly prevalent since healthcare information resources are generally characterized by multiple sources, multiple types, and non - standardization. The data from large cohort studies in China have complex sources and multiple types and it is difficult for the data from different cohorts to be integrated, shared and utilized. For promoting the standardized integration of healthcare resource data in China, we conduct an in - depth literature analysis on the research on common medical data models (CDM) at home and abroad and patterns of CDM establishment for cross - cohort studies. The study also proposes some recommendations regarding the problems of medical data integration and sharing in the context of precision medicine in China for effective integration, consolidation, sharing, and utilization of cross - cohorts data.

     

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