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摘 要
随着社会的发展,人们的医保意识逐渐加强,加之医疗体制的改革,医保病人在医院病人中所占的比例就越来越高,医保的收入也在医院中的营业收入中所占的比重越来越多。医保费用的分配也随即成为医院管理的重点。而目前医院所面临的问题就是:在国家给定一定的医保数额时,医院应该如何分配,具体到分配到每个月份,每个科室,甚至到每个医生手中所占医保费用的份额。针对这个问题,需要对医院的医保数据进行挖掘分析。
现在国内许多医院都建立起了自己的医院信息系统(HIS系统),甚至有些大医院还都拥有了包括HIS系统,图像存储与传输系统(PACS)以及实验室信息系统(LIS)等配套关联的信息系统在内的医院综合信息系统。HIS系统应用复杂,经过多年的运行,现有的业务数据库中包含的不仅仅是大量的病人基本信息,还包含了病人的费用信息以及临床生理信息,影像图片信息等等。但是,传统的统计技术及数据管理工具无法对庞大的数据库进行深入的挖掘分析,针对这一问题,善于从海量数据中发现新的知识,模式的数据挖掘(DM)和统计产品与服务解决方案(SPSS)等技术应运而生。
基于数据挖掘和数据仓库技术的本课题需要做以下几点工作:
1.确定定额医保费用分配的主题。
2.经过大量的数据清洗,从数据库中抽取了十个医疗医保年度的数据,建立对应的医保费用数据仓库和数据模型。
3.对于多种模型中,采取季节模型进行操作。
4.对建立的模型采用关联规则的数据挖掘算法进行分析,并得出结论。
5.根据所得出的结论,确定医保费用的分配方案。
关键词: 数据挖掘;数据仓库;季节模型;医疗医保费用分析;关联规则
Abstract
With the development of society, people’s health consciousness gradually strengthened, and the health care system reform, health care patients in hospital patients in the proportion of more and more high, insurance income is accounted for in the hospital business income in the proportion of more and more. Allocation of health care costs also immediately become the focus of hospital management. At present, the hospital facing the problem is: in the state given a certain amount of care, the hospital should be how to allocate, specific to the assigned to each month, every department, every doctor hands even for the medical insurance cost share. In order to solve this problem, need to analyze the data of hospital medical insurance.
Now many domestic hospitals have established their own hospital information system (HIS system), and even some large hospitals also have included HIS, picture archiving and communication system (PACS) and laboratory information system (LIS) information system supporting the association, the hospital information system. The application of complex HIS system, after years of operation, including existing business in the database is not only a large number of patient information, also includes the cost to the patient clinical information and physiological information, image information and so on. However, traditional statistical techniques and data management tools can not be in-depth analysis and mining of large database, in order to solve this problem, be good at discovering new knowledge from large amounts of data, data mining (DM) and the statistical product and service solutions (SPSS) technology emerge as the times require.
Basing on DM and Data WareHouse(DW) , this dissertation contains following points :
1. Determine the quota allocation of the theme of medical insurance cost.
2. After a large number of data cleaning, is extracted from the database of ten medical insurance annual data, set up data warehouse and health care costs corresponding to the data model.
3. For a variety of models, take the seasonal model operation.
4 .Of the model by using the data mining association rules algorithm is analyzed, and the conclusion.
5. According to the obtained results, determine the allocation of the medical insurance cost.
Keywords: Data Mining; Data Warehouse; Seasonal Model; Medical Insurance Cost Analysis; Association Rules
目 录
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