医疗数据治理——构建高质量医疗大数据智能分析数据基础

doi:10.11959/j.issn.2096-0271.2019002

Abstract

Abstract:

The various problems of medical data governance and data availability in the context of real-world research on a specific disease type were analyzed. The definitions and concepts of the data governance were provided, such as hospital data governance, regional data governance, data governance of disease-specific alliances, governance of medical annotation data and knowledge-based data. Here, the common methodologies and personality methodologies of data governance were summarized. Furthermore, the technologies of master data management, metadata management and data quality control in data governance were further discussed. Finally, the basic framework of medical big data standards was given, and the medical data quality was simply evaluated which based on the existing data governance evaluation standards.

Key words: medical data governance, data availability, metadata, master data

CLC Number:

TP391

Tong RUAN, Jiahui QIU, Zhixing ZHANG, Qi YE. Medical data governance: building the data foundation for intelligent analysis of high quality medical big data[J]. Big Data Research, 2019, 5(1): 12-24.

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[1]	LIN J C , FAN C T , LIAO C C , et al. Taiwan biobank: making cross-database convergence possible in the big data era[J]. Journal Citation Reports, 2018,7(1): 1-4.
[2]	DEMARQUET G . Five key reasons enterprise data governance matters to finance and seven best practices to get you there[J]. Journal of Corporate Accounting &Finance, 2016,27(2): 47-51.
[3]	苏玉娟 . 大数据技术与高新技术企业数据治理创新——以太原高新区为例[J]. 科技进步与对策， 2016,33(6): 47-52.
	SU Y J . Big data technology and the high and new technology enterprises innovate Data management: Taiyuan HighTech Zone as an example[J]. Science &Technology Progress and Policy, 2016,33(6): 47-52.
[4]	SUSAN E . The DAMA guide to the data management body of knowledge (DAMADMBOK)[M]. Bradley Beach: Technics Publications LLC, 2010:58-72.
[5]	张明英，潘蓉 . 数据治理白皮书国际标准研究报告要点解读[J]. 信息技术与标准化， 2015(6): 54-57.
	ZHANG M Y , PAN R . Main points elaboration of international standard technical report “white paper of data covernance”[J]. Information Technology and Standardization, 2015(6): 54-57.
[6]	常朝娣，陈敏 . 大数据时代医疗健康数据治理方法研究[J]. 中国数字医学， 2016,11(9): 2-5.
	CHANG Z D , CHEN M . Research on governance methods of healthcare resources in big data era[J]. China Digital Medicine, 2016,11(9): 2-5.
[7]	BEGG C , CAIRA T . Exploring the SME quandary: data governance in practice in the small to medium-sized enterprise sector[J]. The Electronic Journal Information Systems Evaluation, 2012,15(1): 3-13.
[8]	王融 . 关于大数据交易核心法律问题——数据所有权的探讨[J]. 大数据， 2015,1(2): 49-55.
	WANG R . Discussion in the legal core question of the data ownership in big data trade[J]. Big Data Research, 2015,1(2): 49-55.
[9]	SEBASTIAN M , FELIX K , DENNIS T , et al. Ontology-based data integration between clinical and research systems[J]. Public Library of Science ONE, 2015,10(1): 1-20.
[10]	HANNELE H , KAIJA S , RIIKKA V , et al. Impacts of structuring the electronic health record: a systematic review protocol and results of previous reviews[J]. International Journal of Medical Informatics, 2014,83(3): 159-169.
[11]	NG P M L , LO M F , CHOY E . Improving China's corporate governance within the big data era– integration of knowledge management and data governance[C]// International Conference on Intellectual Capital and Knowledge Management and Organisational Learning, December 5-6,2019,Sydney, Australia.[S.l:s.n], 2015:183.
[12]	GE L , BREWSTER C A . Informational institutions in the agrifood sector: metainformation and meta-governance of environmental sustainability[J]. Current Opinion in Environmental Sustainability, 2016,18: 73-81.
[13]	RUAN T , DONG X , WANG H , et al. Evaluating and comparing web-scale extracted knowledge bases in Chinese and English[C]// Joint International Semantic Technology Conference, November 11-13,2015,Yichang, China.Heidelberg:Springer, 2015:167-184.
[14]	FAN W F , GEERTS F . Foundations of data quality management[M]. San Francisco Bay: Morgan and Claypool Publishers, 2012:1-217.
[15]	SOMA K , TERMEER C J A M , OPDAM P . Informational governance– a systematic literature review of governance for sustainability in the information age[J]. Environmental Science & Policy, 2016(56): 89-99.
[16]	RUAN T , LI Y , WANG H , et al. From queriability to informativity, assessing “quality in use” of DBpedia and YAGO[C]// International Semantic Web Conference, October 17-21,2016,Kobe, Japan.Heidelberg:Springer, 2016:52-68.
[17]	FLECKENSTEIN M , FELLOWS L . Modern data stratery[M]. Heidelberg: Springer, 2018:63-76.

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