STATISTICS COLLOQUIUM
Professor Tahir Ekin
McCoy College of Business
Texas State University
Statistical Issues in Medical Fraud Assessment
ABSTRACT
U.S. governmental agencies report that three to ten percent of the annual health care spending is lost to fraud, waste and abuse. These fraudulent transactions have direct cost implications to the tax-payers and diminish the overall quality of the medical services. In this talk, firstly, the use of statistical sampling and estimation methods for medical fraud assessment will be discussed. The skewness and multi-modality within the payment populations make the over-payment estimation a challenging task. Proposed Bayesian inflated mixture based models will be presented and their conformance with the existing governmental guidelines will be investigated. Secondly, the use of data mining approaches for medical fraud detection will be discussed. The main objective of these approaches is to identify the billing behaviors and detect unusual behaviors. The focus will be on unsupervised approaches such as latent Dirichlet allocation and Bayesian co-clustering.
DATE: Friday, October 16, 2015
TIME: 11:00 a.m. – 12:00 p.m.
PLACE: Philip E. Austin Bldg., Rm. 344
Coffee will be served at 10:30 a.m. in the Noether Lounge (AUST 326)
For more information, contact: Tracy Burke at tracy.burke@uconn.edu