A Back-Propagation Networks System For Hospital Patient Churn Premonitory

ASIAIR > College of Management > Department of Business Administration > Theses & dissertations > Item 310904400/3422

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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:	[Department of Business Administration] Theses & dissertations

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