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A survey on statistical methods for health care fraud detection

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Abstract

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.

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Acknowledgement

We would like to thank the reviewers for the valuable comments that helped us significantly improve the paper.

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Authors and Affiliations

  1. Department of Industrial Engineering, Arizona State University, P.O. Box 875906, Tempe, AZ, 85287-5906, USA

    Jing Li

  2. Department of Industrial and Operations Engineering, University of Michigan, 1205 Beal Avenue, Ann Arbor, MI, 48109-2117, USA

    Kuei-Ying Huang, Jionghua Jin & Jianjun Shi

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  1. Jing Li
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  2. Kuei-Ying Huang
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  4. Jianjun Shi
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Correspondence to Jing Li.

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Li, J., Huang, KY., Jin, J. et al. A survey on statistical methods for health care fraud detection. Health Care Manage Sci 11, 275–287 (2008). https://doi.org/10.1007/s10729-007-9045-4

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  • DOI: https://doi.org/10.1007/s10729-007-9045-4

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