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Weighted risk models for dynamic healthcare fraud detection

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  • Alyssa J. Rolfe

Abstract

Despite efforts to prevent it, fraud in the United States healthcare system remains a serious and pressing issue. Since healthcare fraud is a complex and multi‐faceted problem, fraud‐fighting solutions must be flexible enough to address the ever‐evolving nature of the crime. Here, we present a method to identify healthcare fraud in such a manner that incorporates both potential fraud as well as risky provider behavior. The proposed weighted risk model provides a framework for creating a dynamic fraud detection database that can be easily scaled up to incorporate emerging fraud schemes.

Suggested Citation

  • Alyssa J. Rolfe, 2021. "Weighted risk models for dynamic healthcare fraud detection," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 24(2), pages 143-150, June.
    • Handle: RePEc:bla:rmgtin:v:24:y:2021:i:2:p:143-150
    DOI: 10.1111/rmir.12183
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    References listed on IDEAS

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    1. Holmberg, Sören & Rothstein, Bo, 2011. "Dying of corruption," Health Economics, Policy and Law, Cambridge University Press, vol. 6(4), pages 529-547, October.
    2. van Capelleveen, Guido & Poel, Mannes & Mueller, Roland M. & Thornton, Dallas & van Hillegersberg, Jos, 2016. "Outlier detection in healthcare fraud: A case study in the Medicaid dental domain," International Journal of Accounting Information Systems, Elsevier, vol. 21(C), pages 18-31.
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