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On the Use of the Concentration Function in Medical Fraud Assessment

Author

Listed:
  • Tahir Ekin
  • Francesca Ieva
  • Fabrizio Ruggeri
  • Refik Soyer

Abstract

We propose a simple, but effective, tool to detect possible anomalies in the services prescribed by a health care provider (HP) compared to his/her colleagues in the same field and environment. Our method is based on the concentration function that is an extension of the Lorenz curve widely used in describing uneven distribution of wealth in a population. The proposed tool provides a graphical illustration of a possible anomalous behavior of the HPs and it can be used as a prescreening device for further investigations of potential medical fraud.

Suggested Citation

  • Tahir Ekin & Francesca Ieva & Fabrizio Ruggeri & Refik Soyer, 2017. "On the Use of the Concentration Function in Medical Fraud Assessment," The American Statistician, Taylor & Francis Journals, vol. 71(3), pages 236-241, July.
    • Handle: RePEc:taf:amstat:v:71:y:2017:i:3:p:236-241
    DOI: 10.1080/00031305.2017.1292955
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    References listed on IDEAS

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    1. Jing Li & Kuei-Ying Huang & Jionghua Jin & Jianjun Shi, 2008. "A survey on statistical methods for health care fraud detection," Health Care Management Science, Springer, vol. 11(3), pages 275-287, September.
    2. Tahir Ekin & R. Muzaffer Musal & Lawrence V. Fulton, 2015. "Overpayment models for medical audits: multiple scenarios," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(11), pages 2391-2405, November.
    3. Iliana Ignatova & Roland C. Deutsch & Don Edwards, 2012. "Closed Sequential and Multistage Inference on Binary Responses With or Without Replacement," The American Statistician, Taylor & Francis Journals, vol. 66(3), pages 163-172, August.
    4. Gilliland, Dennis & Edwards, Don, 2011. "Using Randomized Confidence Limits to Balance Risk: An Application to Medicare Investigations," The American Statistician, American Statistical Association, vol. 65(3), pages 149-153.
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