Volume 33, Issue 1 (IJIEPR 2022)                   IJIEPR 2022, 33(1): 186-194 | Back to browse issues page

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Akbarzadeh janatabad A, Sadegheih A, lotfi M M, Mostafaeipour A. Determining the Tariffs of Physicians Using a Combined Model of Data Mining Techniques and Fuzzy Logic in Health Insurance. IJIEPR 2022; 33 (1) :186-194
URL: http://ijiepr.iust.ac.ir/article-1-1427-en.html
Determining the Tariffs of Physicians Using a Combined Model of Data Mining Techniques and Fuzzy Logic in Health Insurance
Amir Akbarzadeh janatabad1 , Ahmad Sadegheih 2, Mohammad mehdi Lotfi1 , Ali Mostafaeipour1
1- Department of Industrial Engineering, Yazd University, Iran
2- Department of Industrial Engineering, Yazd University, Iran , sadegheih@yazd.ac.ir
Abstract:   (1636 Views)
The health insurance system can play an effective role to control health expenditures. The purpose of this study is to provide a model for estimating the physician visit tariffs. To achieve this goal, a hybrid model was used. fuzzy logic is the most appropriate tool for controlling systems and deriving rules for the relationship between inputs and outputs. So, the output of the data mining techniques enter the fuzzy logic as an input variable. The data were collected from the Health Insurance Organization of Iran in two sections including the physicians' costs and physicians' deductions. Owing to the techniques used in this model, NN had the least error, as compared to other data mining techniques (0.0034 and 0.0013, respectively). After defining the variables, membership functions and fuzzy logic rules, the accuracy of the whole control model was confirmed by random data. This research has dealt with the domains of health insurance , their connections and defining effective variables better and more extensively than the other studies in the field.
Keywords: Data mining technique, Fuzzy logic, Health insurance, Tariffs for physicians, Neural network
Full-Text [PDF 691 kb]   (817 Downloads)    
Type of Study: Research | Subject: Intelligent Systems
Received: 2022/01/24 | Accepted: 2022/02/19 | Published: 2022/03/19
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