Weighted risk models for dynamic healthcare fraud detection

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<title>Weighted risk models for dynamic healthcare fraud detection</title>
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<dateIssued encoding="marc">2021</dateIssued>
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<abstract displayLabel="Summary">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.</abstract>
<note type="statement of responsibility">Alyssa J. Rolfe</note>
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<topic>Salud</topic>
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<topic>Medicina</topic>
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<topic>Fraude</topic>
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<topic>Riesgo</topic>
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<topic>Fraude en el seguro</topic>
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<topic>Análisis de riesgos</topic>
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<geographic>Estados Unidos</geographic>
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<title>Risk management & insurance review</title>
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<publisher>Malden, MA : The American Risk and Insurance Association by Blackwell Publishing, 1999-</publisher>
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<identifier type="issn">1098-1616</identifier>
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<text>03/05/2021 Tomo 24 Número 2 - 2021 , p. 143-150</text>
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