2013
DOI: 10.3109/23256176.2013.881028
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Evaluation and Analysis of the Quality of Medical Records in Tertiary General Hospitals in Inner Mongolia Autonomous Region

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“…Good data quality is to ensure that medical big data to play its role in the foundation, at present China's health care big data quality evaluation of the relative lack of research, although the "data governance" concept has been involved in the medical field, China's policy to carry out a large number of studies [36,37], hospitals to carry out the data governance work is generally based on the big data platform or data warehouse construction, the use of big data-oriented governance model [38], such as the first hospital affiliated with Sun Yat-sen University using the "data center" technology, to the subject data as a clue to data governance, and achieved certain results [39];Guangzhou Women's and Children's Medical Center (GWCMC) uses the data governance cycle Plan-Do-Check-Action (PDCA) framework for multi-level data governance based on the construction of specialty databases to form a specialty data asset and scientific research data platform [40].On the other hand, there are fewer studies on the evaluation of big data in healthcare in China, and the main research focuses on improving data quality in healthcare organizations from a management perspective. The study [41] pointed out that the data quality problem is one of the core problems in hospitals, it cannot be solved only by the information department, and it needs the leadership to coordinate and unify all departments, strengthen the communication and collaboration between departments, establish a hospital sharing platform, reduce duplicate entries, and reduce the workload of healthcare workers.In addition, the study [42][43][44][45] pointed out that relevant review and supervision mechanisms should be established to strengthen the sense of responsibility of each health care worker, the implementation of accountability at all levels, and the relevant responsible personnel to give relevant disciplinary measures.…”
Section: Comparison With Prior Workmentioning
confidence: 99%
“…Good data quality is to ensure that medical big data to play its role in the foundation, at present China's health care big data quality evaluation of the relative lack of research, although the "data governance" concept has been involved in the medical field, China's policy to carry out a large number of studies [36,37], hospitals to carry out the data governance work is generally based on the big data platform or data warehouse construction, the use of big data-oriented governance model [38], such as the first hospital affiliated with Sun Yat-sen University using the "data center" technology, to the subject data as a clue to data governance, and achieved certain results [39];Guangzhou Women's and Children's Medical Center (GWCMC) uses the data governance cycle Plan-Do-Check-Action (PDCA) framework for multi-level data governance based on the construction of specialty databases to form a specialty data asset and scientific research data platform [40].On the other hand, there are fewer studies on the evaluation of big data in healthcare in China, and the main research focuses on improving data quality in healthcare organizations from a management perspective. The study [41] pointed out that the data quality problem is one of the core problems in hospitals, it cannot be solved only by the information department, and it needs the leadership to coordinate and unify all departments, strengthen the communication and collaboration between departments, establish a hospital sharing platform, reduce duplicate entries, and reduce the workload of healthcare workers.In addition, the study [42][43][44][45] pointed out that relevant review and supervision mechanisms should be established to strengthen the sense of responsibility of each health care worker, the implementation of accountability at all levels, and the relevant responsible personnel to give relevant disciplinary measures.…”
Section: Comparison With Prior Workmentioning
confidence: 99%