| 引用本文：张研, 段磊, 张亮.大数据理念下居民医疗服务利用监测研究[J].中国卫生政策研究,2017,10(7):71-74 |
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| 大数据理念下居民医疗服务利用监测研究 |
| 投稿时间：2017-04-07 修订日期：2017-06-10 PDF全文浏览 HTML全文浏览 |
| 张研1,2, 段磊1,2, 张亮1,2 |
1. 华中科技大学同济医学院医药卫生管理学院 湖北武汉 430030;
2. 湖北省人文社科重点研究基地农村健康服务研究中心 湖北武汉 430030 |
| 摘要:居民医疗服务利用监测是卫生政策管理与研究的重要内容之一。国家卫生服务调查、居民医保就诊数据等传统的服务利用监测存在成本高、偏倚大，监测指标更新缓慢，无法满足新时期的卫生管理决策等问题。多数据源的数据衔接与再构架为居民服务利用监测提供了新的思路，通过Access数据库管理与Excel的编程技术能够实现不同数据源的对接，同时构架出居民年度医疗服务利用等具体问题的新数据库，从而反映居民的年度服务利用、居民就诊偏好、不合理的服务利用行为等，推动居民医疗服务利用监测研究的发展。 |
| 关键词:国家卫生服务调查 医疗服务利用 监测 大数据 |
| 基金项目:国家自然科学基金青年项目（71603088） |
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| Study on the medical services monitoring under the concept of big data |
| ZHANG Yan1,2, DUAN Lei1,2, ZHANG Liang1,2 |
1. School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan Hubei 430030, China;
2. Research Center for Rural Health Service, Key Research Institute of Humanities & Social Sciences of Hubei Provincial Department of Education, Wuhan Hubei 430030, China |
| Abstract:Medical service utilization monitoring of county areas residents is one of the important contents of health policy management and research. Traditional service utilization monitoring, such as National Health Services Survey (NHSS), residents healthcare treatment (clinical) data from medical insurance, had problems of high cost, large deviation, slowly updating monitoring indicators, out of time in health management decisions. The data convergence and re-architecture of multi-source data provide a new idea for the monitoring of residents' service utilization. Different linking data-sources would come true with the tools of Microsoft Access database administration and Excel programming techniques. At the same time, a new database would be accessed with the indices of residents' annual medical service utilization, preference in medical services, unconscionable service utilization, and lead to the promotion of medical service utilization monitoring research development. |
| Key words:National Health Services Survey (NHSS) Medical service utilization Monitoring Big data |
| 摘要点击次数: 2023 全文下载次数: 8 |
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