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目的医疗数据深加工可为医院管理者提供医疗质量更高层次的数据分析,有助于医疗资源的整合、流程优化、降低运行成本,使医院的工作流程和医疗资源以先进的网络技术得到有效结合。方法通过参照数据钻取和数据挖掘的实践和指南,描述重要数据的模型或预测未来的数据趋势,进行微观、中观和宏观的统计,综合和推理,来发现医疗业务的相互关联。结果有助于医疗资源的整合,流程优化,降低运行成本,提高医疗质量,医疗工作效益和医疗管理水平,进一步解决看病难、看病贵的问题,使我院质量均值达92%以上。结论可以发现其中的医学诊断规则和模式,提供对各种医疗业务及其管理的强有力支持,从而帮助制定医疗决策。
Objective The deep processing of medical data can provide hospital administrators with higher-level data analysis of medical quality, which helps the integration of medical resources, optimize processes, reduce operating costs, and effectively integrate hospital workflows and medical resources with advanced network technologies. . Methods By referring to data drilling and data mining practices and guidelines, describing important data models or predicting future data trends, micro, meso, and macro statistics, synthesis, and reasoning are used to discover the interrelatedness of medical services. The results will help the integration of medical resources, process optimization, reduce operating costs, improve medical quality, medical work efficiency and medical management, and further solve the problem of difficulty in seeing a doctor and expensive medical treatment, so that the average quality of our hospital reaches more than 92%. Conclusions Medical diagnostic rules and patterns can be found among them, providing strong support for various medical services and their management to help make medical decisions.