Developing HIS And Data Mining Based On HIS

Management-information-system acts as a useful tool to increase the economic and management efficiency for companies , and it has been penetrated wildly in most of contemporary industries. In our country, informationization technology has been already begun in the large and medium-sized hospitals, it has deposited many technologies and products - HIS (Hospital Information System). The article describes the current development of HIS in China, focuses on how to build HIS, especially involves in the business and functions for the health-care modules, describes how the patients realize the flow of being treated in HIS, and puts forward to build function distribution and structure design for some modules which are necessary for HIS, such as out-patient fees, Doctor-station for outpatient, patient registration, nursing station for inpatient, admit. and the designation of some key tables. Taking into account of the convenience to implement HIS, this paper uses shell language to initialize data for HIS.Data Mining Technology (abbs DM) seeks out the data, which are interested by users, from a large number of data stored in database, data warehouse or other information files. It uses statistics, artificial intelligence, machine learning, database technology and other methods to research the model and structure of data, to find valuable relationship or knowledge, and provide a basis support and reference for the leader's decision for inpatient, system managementThe second part of the thesis elaborates the development situation of DM technology, describes separately some methods which are commonly used in DM, points the key steps in a DM process at the same time, focuses on association rules and a typical algorithm of association rules– Apriori;Additional, this paper elaborates the Clustering method and the k-means algorithm for DM. and presents a detailed description of DM tools at domestic and abroad.HIS has been successfully used in the majority of hospitals in our country, and it has accumulated a large amount of data. Part of the data become static data and no more used after patients leave the hospital, or simply removed regularly. The valuable knowledge and historical experience contained in these data , has not been pumped out yet in most of our hospitals. The second part of article starts with the data in the current HIS, attempts to exploit the associated rules between the diseases, age and sex using the Apriori algorithm, exploit the class between the fee and the disease using the k-means algorithm .The DM's results can also provide a reference and support for the decision maker in certain aspects.