Big data in the medical industry, there is data collection, storage, integration, management is not standardized, resulting in poor data utilization; coupled with the lack of cross-departmental, cross-institutional data **** enjoyment mechanism, the phenomenon of "information silos" is common, which directly affects the effective use of big data. The effective utilization of big data.
2, the medical industry on the requirements of data governance
(1) data collection link: the existence of massive multi-source heterogeneous data, data collection tools need to cover the whole business, multi-terminal, multi-format data.
(2) Data processing: standardized data processing tools are needed to convert the data collected and integrated into standardized data in a unified format by comparing them with international standards, national standards, and industry standards.
(3) Data quality control link: Data logic verification can be used to evaluate and manage the quality of data in terms of completeness, accuracy, consistency, relevance, standardization, and usability, and to make timely corrections to the aggregated data so as to improve the quality of data.
(4) Data security link: It needs to meet the data security protection needs of each link of data collection, transmission, storage, processing, exchange and destruction, etc., and to realize the services of classification and hierarchical control of data, authority control, monitoring of sensitive data, monitoring of abnormal behavior of data operation, and data encryption.
(5) Data application link: need to face the auxiliary diagnosis, precision medicine, clinical research and other data application scenarios, to provide convenient data query, analysis and display services, and based on certain security measures, to realize the data flow of the whole process of trace, query and traceability.
3, the medical industry data governance tools panorama
China Electronic Technology Standardization Institute of the new "Data Governance Tools Mapping Research Report (2021 Edition)", the data governance tools are divided into three layers, the data strategy layer, the data management layer, and the data operation layer, the following is the panoramic map.