Based On The New Rural Cooperative Medical Insurance Information System

Health insurance is China's social insurance system and the social security system which is an important part of national economy and the people's livelihood important strategic composition, which plays an important role social stability and sustainable economic development. With China's medical insurance system reform, rural medical insurance coverage unceasingly expands, coverage unceasing increase, all levels of orgnaization of agency of medical treatment insurance has been difficult to meet needs of broad ginseng to keep staff, it is difficult to realize their impact on social made by the service commitment, to realize the new rural cooperative medical insurance business efficiency and accuracy, it must establish perfect medical insurance service system, i.e., improve the medical insurance work of informationization level, which can improve the work efficiency and quality. Reduce health-care insurance operating costs, improve the medical reform level, further solving farmers doctor difficult to see doctor your problem. So this paper introduces the design of the new rural cooperative medical insurance information system to meet the needs of society today.This paper mainly work content is firstly analyzed the new rural cooperative medical insurance information systems research situation, proposed the new rural cooperative medical insurance information system of necessity. In order to solve the problem of software cannot be general, this paper designed a model repository, deposit each application, each application is equivalent to a component, according to customers' demand from using artificial neural network model libraries select satisfy need, then select component parts in CORBA framework based on the needs of users integration into the new rural cooperative medical insurance information system. In using artificial neural network select component, before data pretreatment, the upcoming rough set theory and artificial neural network, combined with neural network training samples before in rough set theory, citing the attribute reduction remove neural network training data redundant attributes, thus reducing the input vector of dimension, and simplify the structure of the neural networks, and can improve network training samples of learning speed and the new rural cooperative medical insurance information system is practical.