The Medical Treatment Charge Datamining Of Hospital Information System

The HIS( the hospital information system) bagged the hospital in medical treatment, nursing, finance, drugs, supplies and the research, teaching...etc. big and parts of information within usual activities. Currently local and many hospitals are circulating or preparing to circulate the system of HIS, having already save several years or more than ten years of data, a great deal of data piles up to occupy the bigger saving space, also limit at the simple search only to the exploitation of these data, but have no applied value of real exertive these amount of seas data, containing in these data actually a great deal of, even useful information that is not know for people. For this, the high that choice keep overdue data after simple processing of many hospitals, no longer use, thus lost the data to be worth of discover again. Make use of the HIS in the existing medical treatment expenses data, follow the data warehouse and datamining the technical theories and method according to designing the good research contents in advance, set up the medical treatment expenses data warehouse, the excavation method of the main adoption connection rule, to the medical treatment expenses the data carries on the data to mining to discover with knowledge, the origin study the topic in the main adoption Oracle9i data warehouse technique the establishment data warehouse, adopt the Powerbuilder to be the head development tool, developped the MTC-DM( the medical treatment expenses data mining) on the existing foundation of HIS the application procedure. The MTC-DM collects from the hospital each medical treatment database with the basic information, the expenses data of related patient of the hospitalization medical treatment expenses first, the formation medical treatment expenses database, this is the data phase zero; Connect down to need to carry on the data to prepare the processing to basic information and the expenses informations and other related informationses of patient, handle the process to follow the connection rule calculate way, become the connection rule business form; mining in the data that the data mining the stage to carry on the medical treatment expenses knowledge detection with the connection rule calculate way( apriori), and put the excavation of the rule knowledge into the rule knowledge base; Carry on explaining and evaluating to the knowledge in the knowledge base finally. That procedure is good to followed the data to mining the medium data preparation, data to clean, the datamining, the knowledge discovers etc. carried out to the analytical processing of the history and the existing medical treatment expenses data, and compare to carry out new detection of knowledge goodly. This research topic makes use of the data excavation method for the very first time to the hospital medical treatment expenses in knowledge discover of application carry on the research, for the basis that the fast growth of the valid control hospital medical treatment expenses provided the macro view, especially in the knowledge detection of the medical treatment expenses and obtain automatically the aspect contain more recent breakthrough. 1. The Along with the the development the of the the economy and the the progress the of the society, the people continuously the raise of the the physical the life level, the and in the recent years the the irregularity the that the the medical treatment the system bring the when reform, thecause stay in the hospital the medical treatment the expenses to fly the fierce long, people see a doctor difficult, despise the phenomenon of the disease increasingly outstanding. 2. This stationery body analyzed the macroscopic reason of the upsurge of the influence inpatient expenses, and is applied this to scoop out in the data of belong to in sex, pass the test, these factors compare good of reaction the medical treatment expenses condition of the inpatient. 3.Combine the patient's expenses structure, this text scoops out the data that the connection rule applied to patient's expenses to discover to win with knowledge, and compared the system to elaborate the calculate way of Apriori detailedly. 4. The Full in the consideration of the data the source that the data scoop out, the data that this selected works take machine data the processing as the foundation, establishment the data scoops out the warehouse, the sampling to the wait the long-term periodical the renewal that the measure the solves data through a data, acquiring the training data continuously, with the accuracy that the exaltation data mining to discovers the mode with knowledge, thus raise its credibility. 5. In order to solve the hospital medical treatment data to increase the huge pressure that saves to bring to the hospital information quickly, at the same time for the exploitation attain efficiently purpose of the current data. data mining the different from the data warehouse can is saving hospital in database, different position, not contemporaneous data to integrate together, the knowledge warehouse that form can make use of again.This research passes the theories and applied two aspect log arithmseses according to data mining the technique and hospital medical treatment expenseses to carry on the research, try hard for to an integrity of, the viable quest hospital medical treatment expenses affects the factor of estimate and knowledge obtain the method, providing for the decision of the leadership can go the basis, with attain to lower the patient the hospitalization medical treatment expenses, reduce the otiose expenditure for main purpose. The textual research result express that make use of the data warehouse and datamining the technique to carry on the excavation to the hospital medical treatment expenses, can attain to manage efficiently and the result for make policy, its result can apply to the all levels medical treatment organization of set up the system of HIS, and will become each medical treatment organization to lead the most emollient assistance in layer decision tool, under the network and information-based social milieus, it will have vast applied foreground necessarily.