A Framework for Big Data Governance to Advance RHINs: A Case Study of China

• Published in: IEEE access Vol. 7; pp. 50330 - 50338
• Main Authors: Li, Quan, Lan, Lan, Zeng, Nianyin, You, Lei, Yin, Jin, Zhou, Xiaobo, Meng, Qun
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Big Data; Big data governance; Case studies; Domains; framework; Health care; Literature reviews; Regional development; regional health information networks (RHINs); Sustainable development; China
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2910838

The emergence of big data presents a serious challenge to the fast growth of regional health information networks (RHINs) globally. In China, many constructors of RHINs have spontaneously and independently created governance measures, which may be valuable as a point of reference for other countries. This paper aimed to propose a big data governance framework for healthcare data based on the governance activities associated with the processing of RHINs in China. Typical methodology for RHIN case studies in China, including rich personal experience in nationwide consulting, literature review, expert consultation, and interpretative structural modeling methods, was adopted. Based on the analysis of ten typical RHIN case studies, healthcare big data governance practices in China were summarized. A framework with 3 domains and 12 elements was proposed, which include a drive domain (big data strategy planning, laws and regulations, open transaction, and industry support), capability domain (healthcare big data organization, collection, storage, process and analysis, and usage), and support domain (healthcare big data resource planning, standards system, and privacy and security protection). We obtained 12 guidelines for healthcare big data governance. A big data governance framework with 3 domains and 12 elements was presented based on Chinese practice, which might serve as valuable references for the cross-dimensional development of RHINs, provide overall guidance for the sustainable development of regional health informatization, and contribute to realizing the business value of healthcare big data.