title: The evaluation of trustworthiness to identify health insurance fraud in dentistry.
abstract: According to the investigations of the U.S. Government Accountability Office (GAO), health insurance fraud has caused an enormous pecuniary loss in the U.S. In Taiwan, in dentistry the problem is getting worse if dentists (authorized entities) file fraudulent claims. Several methods have been developed to solve health insurance fraud; however, these methods are like a rule-based mechanism. Without exploring the behavior patterns, these methods are time-consuming and ineffective; in addition, they are inadequate for managing the fraudulent dentists.
  
  
  
  Based on social network theory, we develop an evaluation approach to solve the problem of cross-dentist fraud. The trustworthiness score of a dentist is calculated based upon the amount and type of dental operations performed on the same patient and the same tooth by that dentist and other dentists.
  
  
  
  The simulation provides the following evidence. (1) This specific type of fraud can be identified effectively using our evaluation approach. (2) A retrospective study for the claims is also performed. (3) The proposed method is effective in identifying the fraudulent dentists.
  
  
  
  We provide a new direction for investigating the genuineness of claims data. If the insurer can detect fraudulent dentists using the traditional method and the proposed method simultaneously, the detection will be more transparent and ultimately reduce the losses caused by fraudulent claims.
authors.affiliation: Department of Dental Technology and Materials Science, Central Taiwan University of Science and Technology, 666 Buzih Rd., Taichung 40601, Taiwan; Department of Industrial Engineering and Systems Management, Feng Chia University, No. 100, Wenhwa Rd., Seatwen, Taichung 40724, Taiwan. Electronic address: slwang@ctust.edu.tw.
authors.forename: Shu-Li
authors.initials: SL
authors.lastname: Wang
authors.affiliation: Department of Industrial Engineering and Management, Da-Yeh University, No.168, University Rd., Dacun, Changhua 51591, Taiwan. Electronic address: htpai@mail.dyu.edu.tw.
authors.forename: Hao-Ting
authors.initials: HT
authors.lastname: Pai
authors.affiliation: Department of Industrial Engineering and Systems Management, Feng Chia University, No. 100, Wenhwa Rd., Seatwen, Taichung 40724, Taiwan. Electronic address: mfwu@fcu.edu.tw.
authors.forename: Mei-Fang
authors.initials: MF
authors.lastname: Wu
authors.affiliation: Department of Information Management, National Chung Cheng University, 168 University Rd., Minhsiung 62102, Taiwan. Electronic address: kfwu@mis.ccu.edu.tw.
authors.forename: Fan
authors.initials: F
authors.lastname: Wu
authors.affiliation: Department of Information Management, National Chung Cheng University, 168 University Rd., Minhsiung 62102, Taiwan. Electronic address: porkcircle@gmail.com.
authors.forename: Chen-Lin
authors.initials: CL
authors.lastname: Li
mesh_terms: D057225:Data Mining; D003813:Dentistry; D005607:Fraud; D006801:Humans; D007348:Insurance, Health; D012189:Retrospective Studies; D013624:Taiwan
keywords: Dentistry; Fraud identification; Social network; Trustworthiness evaluation