目的:大数据时代,数据成为决策最重要的参考之一.通过抓取病案首页数据,然后通过关联分析,从原始数据中挖掘出有用信息,为管理决策者正确把握医疗形式、客观分析问题,提供准确可靠的医疗统计信息.方法:运用关联规则数据挖掘算法Apriori算法,对2016年病案首页数据的关联性进行分析和挖掘,探索出院科室与性别,病人类型、住院天数、总费用,药费的关联规则,分析住院病人的结构比情况,并分析其结果.结果:对2016年所有出院患者病历首页进行Apriori算法分析,提取一部分有用rule,得到住院病人结构比情况;神经内科、脑梗死与总费用、药费的关联规则;妇产科早孕人工流产(妊娠12周之前),稽留流产,胎膜早破,单胎顺产这几种疾病总费用、药费及住院天数关联情况,并且用不同的图表展现出来.结论:基于Apriori算法关联规则挖掘,可以从海量数据中挖掘出隐含的、先前未知但潜在的有用信息.关联规则挖掘是当前数据挖掘领域中最受瞩目的研究方向之一,具有重要的研究价值和广阔的应用前景[1].%Objective:In the era of big data,data has become one of the most important reference for decision-making.By capturing the medical record data,and then through the correlation analysis,dig out the useful information from the raw data,objective analysis for management decision makers to correctly grasp the problem of medical treatment,medical statistics,to provide accurate and reliable information.Methods:The application of association rules data mining algorithm Apriori algorithm,analysis and mining association of the medical record data in 2016,to explore the gender department and hospital,patient type,length of stay,total cost,cost of association rules,analysis of inpatient structure than the situation,and the analysis of its results.Results:The results of 2016 all patients discharged from hospital records of the home Apriori algorithm analysis,to extract a part of useful rule,get inpatient structure ratio,association rules of Neurology,cerebral infarction and the total cost,expenses for medicine,department of Obstetrics and Gynecology,artificial abortion (before 12 weeks of pregnancy),abortion,premature rupture of membranes,the total of these days Association cost of illness,single fetus delivery of drugs and hospitalization,and show different chart.Conclusion:The mining association rules Apriori algorithm based on mining the hidden,unknown but potentially useful information from massive data,association rules mining is one of the most remarkable research direction in the field of data mining,which has an important research value and broad application prospect.
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