Volume 5

V5 N1 Pages 51-61

January 2012


Applying Business Intelligence Concepts to Medicaid Claim Fraud Detection


Leanndra Copeland
Nevada Department of Employment, Training and Rehabilitation
Carson City, NV 89713, USA

Dana Edberg
University of Nevada, Reno
Reno, NV 89557, USA

Anna K. Panorska
University of Nevada, Reno
Reno, NV 89557, USA

Jeanne Wendel
University of Nevada, Reno
Reno, NV 89557, USA

Abstract: U.S. governmental agencies are striving to do more with less. Controlling the costs of delivering healthcare services such as Medicaid is especially critical at a time of increasing program enrollment and decreasing state budgets. Fraud is estimated to steal up to ten percent of the taxpayer dollars used to fund government supported healthcare, making it critical for government authorities to find cost effective methods to detect fraudulent transactions. This paper explores the use of a business intelligence system relying on statistical methods to detect fraud in one state’s existing Medicaid claim payment data. This study shows that existing Medicaid claim transactions that have been collected for payment purposes can be reformatted and analyzed to detect fraud and provide input for decision makers charged with making the best use of available funding. The results illustrate the efficacy of using unsupervised statistical methods to detect fraud in healthcare-related data.

Keywords: Business Intelligence, government information systems, Healthcare, fraud, statistical analysis, unsupervised methods

Download this article: JISAR - V5 N1 Page 51.pdf


Recommended Citation: Copeland, L., Edberg, D., Panorska, A.K., Wendel, J. (2012). Applying Business Intelligence Concepts to Medicaid Claim Fraud Detection. Journal of Information Systems Applied Research, 5(1) pp 51-61. http://jisar.org/2012-5/ ISSN: 1946-1836. (A preliminary version appears in The Proceedings of CONISAR 2011)