Electronic Fraud Detection in the US Medicaid Healthcare Program: Lessons Learned from other Industries

被引:0
作者
Travaille, Peter [1 ]
Mueller, Roland M. [2 ]
Thornton, Dallas [1 ]
van Hillegersberg, Jos [3 ]
机构
[1] Univ Calif San Diego, La Jolla, CA 92093 USA
[2] Berlin Sch Econ & Law, Berlin, Germany
[3] Univ Twente, Enschede, Netherlands
来源
AMCIS 2011 PROCEEDINGS | 2011年
关键词
Fraud Detection; Data Mining; Health Care; Medicaid;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It is estimated that between $600 and $850 billion annually is lost to fraud, waste, and abuse in the US healthcare system, with $125 to $175 billion of this due to fraudulent activity (Kelley 2009). Medicaid, a state-run, federally-matched government program which accounts for roughly one-quarter of all healthcare expenses in the US, has been particularly susceptible targets for fraud in recent years. With escalating overall healthcare costs, payers, especially government-run programs, must seek savings throughout the system to maintain reasonable quality of care standards As such, the need for effective fraud detection and prevention is critical. Electronic fraud detection systems are widely used in the insurance, telecommunications, and financial sectors. What lessons can be learned from these efforts and applied to improve fraud detection in the Medicaid health care program? In this paper, we conduct a systematic literature study to analyze the applicability of existing electronic fraud detection techniques in similar industries to the US Medicaid program.
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页数:10
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