A survey on statistical methods for health care fraud detection

• Published in: Health care management science Vol. 11; no. 3; pp. 275 - 287
• Main Authors: Li, Jing, Huang, Kuei-Ying, Jin, Jionghua, Shi, Jianjun
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.09.2008; Springer; Springer Nature B.V
• Series: Health Care Management Science
• Subjects: Business and Management; Departments; Econometrics; Fraud; Fraud - statistics & numerical data; Fraud detection; Fraud prevention; Health Administration; Health care; Health care expenditures; Health care industry; Health care policy; Health Care Sector - statistics & numerical data; Health Informatics; Health insurance; Humans; Insurance Claim Reporting - statistics & numerical data; Insurance Claim Review - statistics & numerical data; Insurance companies; Management; Medicaid fraud; Models, Statistical; Operations Research/Decision Theory; Statistical methods; Studies; Subject specialists; Health care; Fraud detection; Statistical methods
• ISSN: 1386-9620; 1572-9389
• DOI: 10.1007/s10729-007-9045-4

Fraud and abuse have led to significant additional expense in the health care system of the United States. This paper aims to provide a comprehensive survey of the statistical methods applied to health care fraud detection, with focuses on classifying fraudulent behaviors, identifying the major sources and characteristics of the data based on which fraud detection has been conducted, discussing the key steps in data preprocessing, as well as summarizing, categorizing, and comparing statistical fraud detection methods. Based on this survey, some discussion is provided about what has been lacking or under-addressed in the existing research, with the purpose of pinpointing some future research directions.