Fuzzy Logic and Fuzzy Clustering for Medical Service Value Model

This research is to expand an estimation model for medical service value of informal workers for the social security system. In this study, the data of workers in year 2010 provided by the Social Security Office in Thailand was analyzed and used to create for non-surgical medical service value model. The data obtained from the fuzzy clustering analysis is used to establish a membership function in fuzzy logic. Subsequently, the result from this model, which is compensation for medical expenses will be used to estimate the monetary value of medical services for the informal workers when receive the treatment without surgery.