Fuzzy Analysis Methods for the Estimation of Medical Service Value Model

This article develops an estimation of a model for non-surgical and surgical medical service value of informal workers for the social security system in Thailand. By using the data of workers in the year 2010 provided by the Social Security Office, we analyzed and established the medical service value model. The data obtained from the fuzzy clustering analysis is used in creating a membership function in fuzzy logic. Subsequently, the result from this model, which is compensation for medical expenses, will be considered in the estimation of the monetary value of medical services for the informal workers. Moreover, the result of this method gave closer estimates to the real expenses comparing to the regression method.

[1]  Kazumitsu Nawata,et al.  An analysis of the length of hospital stay for cataract patients in Japan using the discrete-type proportional hazard model , 2009, Math. Comput. Simul..

[2]  J. Concato,et al.  A simulation study of the number of events per variable in logistic regression analysis. , 1996, Journal of clinical epidemiology.

[3]  Kazumitsu Nawata,et al.  An analysis of hip fracture treatments in Japan by the discrete-type proportional hazard and ordered probit models , 2008, Math. Comput. Simul..

[4]  D. L. Hudson,et al.  Fuzzy logic in medical expert systems , 1987 .

[5]  Huimin Wang,et al.  Risk Analysis of Flood Disaster Based on Fuzzy Clustering Method , 2011 .

[6]  Jihong Ding,et al.  A theoretical investigation of the reformed public health insurance in urban China , 2009 .

[7]  J. Galbraith,et al.  The abuse of regression in the National Health Service allocation formulae: response to the Department of Health's 2007 ‘resource allocation research paper’ , 2011 .

[8]  Kwang Hyung Lee,et al.  First Course on Fuzzy Theory and Applications , 2005, Advances in Soft Computing.

[9]  Arkady Bolotin.  Fuzzification of Linear Regression Models with Indicator Variables in Medical Decision Makin , 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

[10]  J. Brooks,et al.  Analyzing the volume and nature of emergency medical calls during severe weather events using regression methodologies , 2012 .

[11]  Chao Chung Ho,et al.  Optimal evaluation of infectious medical waste disposal companies using the fuzzy analytic hierarchy process. , 2011, Waste management.

[12]  S. Mahmoud Taheri,et al.  Fuzzy logistic regression based on the least squares approach with application in clinical studies , 2011, Comput. Math. Appl..

[13]  L. Baker,et al.  Medical costs in workers' compensation insurance. , 1995, Journal of health economics.

[14]  W. Dennis.  Wages, Health Insurance and Pension Plans: The Relationship Between Employee Compensation and Small Business Owner Income , 2000 .