Weighted risk models for dynamic healthcare fraud detection

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<rdf:Description>
<dc:creator>Rolfe, Alyssa J</dc:creator>
<dc:date>2021</dc:date>
<dc:description xml:lang="es">Sumario: 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.</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/176729.do</dc:identifier>
<dc:language>spa</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Salud</dc:subject>
<dc:subject xml:lang="es">Medicina</dc:subject>
<dc:subject xml:lang="es">Fraude</dc:subject>
<dc:subject xml:lang="es">Riesgo</dc:subject>
<dc:subject xml:lang="es">Fraude en el seguro</dc:subject>
<dc:subject xml:lang="es">Análisis de riesgos</dc:subject>
<dc:subject xml:lang="es">Estados Unidos</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Weighted risk models for dynamic healthcare fraud detection</dc:title>
<dc:relation xml:lang="es">En: Risk management & insurance review. - Malden, MA : The American Risk and Insurance Association by Blackwell Publishing, 1999- = ISSN 1098-1616. - 03/05/2021 Tomo 24 Número 2 - 2021 , p. 143-150</dc:relation>
<dc:coverage xml:lang="es">Estados Unidos</dc:coverage>
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