| And perfect along with the development of medical software development in recent years, the hospital informationization level has improved, there are a lot of potential in its information system database knowledge and rules, both in clinical auxiliary diagnosis and operation management in hospitals, we can use some of the data mining platform or tools to dig up these rules.This article mainly created based on the HIS data warehouse by the SQL Server2012, using data mining technology, the analysis of data, from two aspects of clinical auxiliary diagnosis and outpatient service management experiment design and implementation.The first to use the SQL Server2012 data mining tools, doctor’s advice for outpatient prescription drugs category using the association rules mining, found the diazepam and tartaric acid metoprolol pills have the strongest correlation. After clinical expert analysis mining data, they found the rules of the said after generalization can also form the clinic doctors use manual, auxiliary clinical diagnosis and treatment, to repare for later realize intelligent prescription system.Second use relationship rules mining the data related to prescribing information, use the WEKA mining tools found two significant rule: if the issue is excessive, the possibility of drug quantity more than 5 is 95%; the possibility of outpatient excessive is director of the physician is 93%. Through the above conclusion outpatient management system has made corresponding regulations: a prescription can’t more than 5 kinds of drugs, limit the number of doctors use of antimicrobial drugs and the category,attending physician used to general antimicrobial drug by the superior doctor authorized and approved,above of physician using a special class of antimicrobial drugs to pharmaceutical affairs committee authorized.Finally by using neural network algorithm for the outpatient’s satis- faction of related data mining, using the SQL Server2012 data mining tools,found that the most important factors of affect patient satisfaction is outpatient service scheduling, followed by the number of checks on the day.Through the analysis of mining results, draws some conclusions of practical value, these results can provide data support for outpatient medical management decisions. |
