The Analysis, Based On Electronic Medical Records Of Outpatient Medication

Data mining(DM) is one of hot spots for the computer science, many industries applied the new technology to their information systems, and gained remarkable benefits. The application of Electronic Health Record(EHR) cause the unceasing inflation of the information in hospital database. But the operations of hospital information system are limited to adding, deleting, updating and searching and so on. These operations are only fundamental applications for database of HER, and lack the data integration and analysis, far from the medical decision-making and the automatic gain from knowledge. By data mining technology, understanding the correlations and the developing regulations contained in every kind of medicine, summing up effect of every kind of treatment project has great value and prospect to the diagnosis and treatment with diseases and to the research of medical science.Among the methods of data mining, one of the most widespread in application is association rules mining. By the data preprocessing, item dataset that can be mined directly is produced which is stored in DM database. Through mining association rules with item dataset, many interesting association rules can be found.After the method for mining association rules is analyzed, a dynamic algorithm of frequent itemsets mining based on boolean matrix is put forward. The algorithm can not only scan the database once, but also has the virtues in high speed, less memory cost. Based on the above approach, the association analysis with EHR data is carried on, which to find the coalescence and compatibility of medicines. And the results is analysed at last.