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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/3422


    Title: A Back-Propagation Networks System For Hospital Patient Churn Premonitory
    Authors: Fan Mu-Lan
    Contributors: Department of Business Administration
    Keywords: Foundational Health Treatment;Customer Relationship Management;Customer Churn;Data Mining;Back-Propagation Networks
    Date: 2004
    Issue Date: 2009-11-17 11:16:58 (UTC+0)
    Publisher: Asia University
    Abstract: The current increasingly competitive pressure has been created in the health medical industry due to the facts such as the performance of health insurance for the entire people, extremely high medical costs, and fast and quick media propagation. It has been taken under consideration by heath medical institutions how to invest in loyal patients with the same health medical concept by using the limited health medical resource to hold existing patients? loyalty and prevent from potential patients? churns?
    This research is to discuss and analyze the customers? churn in the issue of customers relationship management for An-Xin clinic, Tai-Pin City, Taizhong County, by means of Artificial Neural Networks, ANNs to construct the analysis mode of customers churns and hope to forecast relevant influential variables for customers? churns, giving a premonition to health medical institutes prior to customers? churns. The result of research is as follows:
    1.Sexual variables of patients? are the most significant, among which males? churn condition is higher than females.
    2.Types of illness are secondary, among which the churns of patients with acute diseases are more than ones with chronic diseases.
    3.The third is the status of patients, among which the churns of patients at one?s own expense are less than the ones with the states of healthcare insurance.
    4.The fourth is marriage state, among which churns of the unmarried are more than the married.
    5.The fifth is the age of patients, among which the older are more
    than the young.
    Therefore, the management should accurately make policy, adjust the operation of medical treatment and further after learning the churn characteristics. The premonition mode offered by our graduate school can effectively find potential churn patients and possess value of practical applications.
    Appears in Collections:[經營管理學系 ] 博碩士論文

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