Electronic Fraud Detection in the U.S. Medicaid Healthcare Program: Lessons Learned from other Industries

Peter Travaille, Roland Mueller, Dallas Thornton, Jos van Hillegersberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

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-matchedgovernment program which accounts for roughly one-quarter of all healthcare expenses in the US, has been particularlysusceptible targets for fraud in recent years. With escalating overall healthcare costs, payers, especially government-runprograms, must seek savings throughout the system to maintain reasonable quality of care standards. As such, the need foreffective 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 frauddetection in the Medicaid health care program? In this paper, we conduct a systematic literature study to analyze theapplicability of existing electronic fraud detection techniques in similar industries to the US Medicaid program.
Original languageEnglish
Title of host publicationProceedings of the 17th Americas Conference on Information Systems (AMCIS)
PublisherAssociation for Information Systems
Pages1-11
Number of pages10
Publication statusPublished - 4 Aug 2011
Event17th Americas Conference on Information Systems, AMCIS 2011 - Detroit, United States
Duration: 4 Aug 20117 Aug 2011
Conference number: 17

Conference

Conference17th Americas Conference on Information Systems, AMCIS 2011
Abbreviated titleAMCIS
Country/TerritoryUnited States
CityDetroit
Period4/08/117/08/11

Keywords

  • Health Care
  • Medicaid
  • Data Mining
  • Fraud detection

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