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Weighted risk models for dynamic healthcare fraud detection
Author(s) -
Rolfe Alyssa J.
Publication year - 2021
Publication title -
risk management and insurance review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.386
H-Index - 16
eISSN - 1540-6296
pISSN - 1098-1616
DOI - 10.1111/rmir.12183
Subject(s) - health care , business , healthcare system , healthcare industry , risk analysis (engineering) , financial fraud , computer science , computer security , actuarial science , accounting , political science , law
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.