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基于医疗大数据分析系统开展的冠脉支架带量采购政策效果评估研究

Evaluation of the effect of coronary stent volume-based procurement based on medical big data analysis system
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摘要 目的:应用医疗大数据分析系统,对冠脉支架相关手术患者的数据进行采集、整合、分析、对比,并在数据分析结果的基础上评价冠脉支架带量采购政策的实施效果。方法:检索中国知网、万方数据库,整理当前冠脉之家带量采购政策效果评价。利用医院医疗大数据分析系统抽取患者病案数据进行清洗整合,采用描述性分析、差异性分析、实证分析等方法对数据进行研究分析。结果:通过对政策开展前后共计41245人次的患者数据进行研究后发现,患者平均医疗费用同比下降了43%;集采冠脉支架接受度高,使用量占比约为99.8%;同时政策前后患者的医疗费用结构得到了明显优化。结论:冠脉支架带量采购政策符合当前医疗改革大方向,有效遏制了“以械补医”的现象,同时极大减轻了患者的医疗负担。 Objective By applying the medical big data analysis system,to collect,integrate,analyze and compare the data of patients undergoing coronary stent-related surgery,and evaluate the implementation effect of the coronary stent-belt procurement policy on the basis of data analysis results.Methods Data resources related to the effect evaluation of the current volume procurement policies of Coronary Home were retrieved from CNKI and Wanfang.Patients'medical record data were extracted for cleaning and integration from the hospital's medical big data analysis system,and descriptive analysis,differential analysis,empirical analysis and other methods were conducted for data analysis.Results The data of 41,245 patients'records before and after the policy implementation were analyzed,and it was found that the average medical cost of patients decreased by 43%.The acceptance of coronary stent collection was high,and the usage ratio was about 99.8%.At the same time,the medical expenses structure of patients before and after policy implementation was significantly optimized.Conclusion The procurement policy of coronary stents is in line with the general direction of current medical reform,which can effectively curb the phenomenon of"supplementing medical treatment with equipment",and greatly reduce the patients'medical burdens.
作者 蒋琳 孙春光 JIANG Lin;SUN Chunguang(Beijing Anzhen Hospital Affiliated to Capital Medical University,Beijing 100029,China;Beijing Red Cross Rescue Service Center)
出处 《中国数字医学》 2023年第11期111-115,共5页 China Digital Medicine
关键词 医疗大数据分析 高值耗材 带量采购 Medical big data analysis High-value medical consumables Volume-based procurement
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