Big Data Health Care Platform With Multisource Heterogeneous Data Integration and Massive High-Dimensional Data Governance for Large Hospitals: Design, Development, and Application

作者：Miye Wang, Sheyu Li, Tao Zheng, Nan Li, Qingke Shi, Xuejun Zhuo, Renxin Ding, Yong Huang · 发表于：JMIR Medical Informatics · 年份：2022 · DOI：10.2196/36481 · 被引用次数：72 · 研究领域：Artificial Intelligence in Healthcare、Big Data and Digital Economy、Machine Learning in Healthcare

BACKGROUND: With the advent of data-intensive science, a full integration of big data science and health care will bring a cross-field revolution to the medical community in China. The concept big data represents not only a technology but also a resource and a method. Big data are regarded as an important strategic resource both at the national level and at the medical institutional level, thus great importance has been attached to the construction of a big data platform for health care. OBJECTIVE: We aimed to develop and implement a big data platform for a large hospital, to overcome difficulties in integrating, calculating, storing, and governing multisource heterogeneous data in a standardized way, as well as to ensure health care data security. METHODS: The project to build a big data platform at West China Hospital of Sichuan University was launched in 2017. The West China Hospital of Sichuan University big data platform has extracted, integrated, and governed data from different departments and sections of the hospital since January 2008. A master-slave mode was implemented to realize the real-time integration of multisource heterogeneous massive data, and an environment that separates heterogeneous characteristic data storage and calculation processes was built. A business-based metadata model was improved for data quality control, and a standardized health care data governance system and scientific closed-loop data security ecology were established. RESULTS: After 3 y...