Weighted risk models for dynamic healthcare fraud detection
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| Tag | 1 | 2 | Valor |
|---|---|---|---|
| LDR | 00000cab a2200000 4500 | ||
| 001 | MAP20210024320 | ||
| 003 | MAP | ||
| 005 | 20210723085545.0 | ||
| 008 | 210722e2021 esp|||p |0|||b|spa d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a7 | ||
| 100 | $0MAPA20210030017$aRolfe, Alyssa J | ||
| 245 | 1 | 0 | $aWeighted risk models for dynamic healthcare fraud detection$cAlyssa J. Rolfe |
| 520 | $aDespite 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. | ||
| 650 | 4 | $0MAPA20080539771$aSalud | |
| 650 | 4 | $0MAPA20080548124$aMedicina | |
| 650 | 4 | $0MAPA20080541064$aFraude | |
| 650 | 4 | $0MAPA20210011108$aRiesgo | |
| 650 | 4 | $0MAPA20080591052$aFraude en el seguro | |
| 650 | 4 | $0MAPA20080588953$aAnálisis de riesgos | |
| 651 | 1 | $0MAPA20080638337$aEstados Unidos | |
| 773 | 0 | $wMAP20077001748$tRisk management & insurance review$dMalden, MA : The American Risk and Insurance Association by Blackwell Publishing, 1999-$x1098-1616$g03/05/2021 Tomo 24 Número 2 - 2021 , p. 143-150 |