A survey on statistical methods for health care fraud detection

Jing Li, Kuei Ying Huang, Jionghua Jin, Jianjun Shi

Research output: Contribution to journalReview articlepeer-review

113 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)275-287
Number of pages13
JournalHealth Care Management Science
Issue number3
StatePublished - Sep 2008


  • Fraud detection
  • Health care
  • Statistical methods

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Health Professions(all)


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