Comparative study of medical common data models for FAIR data sharing.
10.3760/cma.j.cn112338-20221025-00908
- Author:
An Ran WANG
1
;
Si Zhu WU
1
;
Shegn Yu LIU
1
;
Xiao Lei XIU
1
;
Jia Ying ZHOU
1
;
Zheng Yong HU
1
;
Yi Fan DUAN
1
Author Information
1. Department of Medical Data Sharing, Institute of Medical Information, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing 100020, China.
- Publication Type:Journal Article
- MeSH:
Humans;
Big Data;
China;
Cohort Studies;
Data Collection;
Information Dissemination
- From:
Chinese Journal of Epidemiology
2023;44(5):828-836
- CountryChina
- Language:Chinese
-
Abstract:
The common data model (CDM) is an important tool to facilitate the standardized integration of multi-source heterogeneous healthcare big data, enhance the consistency of data semantic understanding, and promote multi-party collaborative analysis. The data collections standardized by CDM can provide powerful support for observational studies, such as large-scale population cohort study. This paper provides an in-depth comparative analysis of the data storage structure, term mapping pattern, and auxiliary tools development of the three international typical CDMs, then analyzes the advantages and limitations of each CDM and summarizes the challenges and opportunities faced in the CDM application in China. It is expected that exploring the advanced technical concepts and practical patterns of foreign countries in data management and sharing will provide references for promoting FAIR (findable, accessible, interoperable, reusable) construction of healthcare big data in China and solving the current practical problems, such as the poor quality of data resources, the low degree of semantization, and the inabilities of data sharing and reuse.
