Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 43, Pages: 1-6
Hojjat Ahmadinejad1 , Amir Norouzi2*, Ahura Ahmadi3 and Ali Yousefi4
1 Engineer of Information Technology, NouAndish Pars Co., Tehran, Iran; [email protected] 2Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran; [email protected] 3Shahid Beheshti University of Medical Sciences, School of Medical Education, Tehran, Iran; [email protected] 4Engineer of Computer Engineering, Department of Computer Engineering, Malayer Branch, Islamic Azad University, Malayer, Iran; [email protected]
*Author for correspondence
Amir Norouzi Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran; [email protected]
Objectives: Healthcare fraud costs the country tens of billions of dollars a year. Methods: Fraudulent behaviors of healthcare providers and patients have become a serious burden to insurance systems by bringing unnecessary costs. Insurance companies thus developed methods to identify fraud. Results: In this paper a methodology offered based on data mining approach to discover fraud in healthcare insurance. Applications: To test and evaluate model real-world data set related to healthcare insurance in Iran has been used. Investment result of operation model on this data set indicates proper performance of it.
Keywords: Anomaly Detection, Data Mining, Healthcare Fraud, Outlier Detection, Unsupervised Method
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