Two models to investigate Medicare fraud within unsupervised databases

被引：28
|
作者：
Musal, Rasim Muzaffer [1 ]
机构：
[1] Texas State Univ, Austin, TX 78701 USA
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2010年 / 37卷 / 12期
关键词：
Fraud; Medicare; Unsupervised methods; Distances analysis; Clustering methods;
D O I：
10.1016/j.eswa.2010.06.095
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We propose two models to identify fraud, waste and abuse in Medicare. These models are used to flag health care providers. The motivation for these models is based on observed cases of fraud. The paper details the use of clustering algorithms, regression analysis, and various descriptive statistics that are components of these models. Some of the challenges in the struggle to reduce fraud in Medicare are discussed. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：8628 / 8633
页数：6
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