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Statistical Medical Fraud Assessment: Exposition to an Emerging Field
Author(s) -
Ekin Tahir,
Ieva Francesca,
Ruggeri Fabrizio,
Soyer Refik
Publication year - 2018
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/insr.12269
Subject(s) - exposition (narrative) , field (mathematics) , computer science , health care , data science , estimation , sampling (signal processing) , political science , engineering , mathematics , art , systems engineering , filter (signal processing) , pure mathematics , law , computer vision , literature
Summary Health care expenditures constitute a significant portion of governmental budgets. The percentage of fraud, waste and abuse within that spending has increased over years. This paper introduces the emerging area of statistical medical fraud assessment, which becomes crucial to handle the increasing size and complexity of the medical programmes. An overview of fraud types and detection is followed by the description of medical claims data. The utilisation of sampling, overpayment estimation and data mining methods in medical fraud assessment are presented. Recent unsupervised methods are illustrated with real world data. Finally, the paper introduces potential future research areas such as integrated decision making approaches and Bayesian methods and concludes with an overall discussion. The main goal of this exposition is to increase awareness about this important area among a broader audience of statisticians.