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Overview:

The private health insurance expenditures in U.S. are expected to hit one trillion dollars by 2010. With over two hundred million insured lives, complexity in claim processing and government regulated timeliness for payment to medical providers; health insurance companies are susceptible for making payment errors. An insurance company covering 10 million lives approximately pays medical providers in excess of $400 million a year in "Identified overpayments". Current industry practice to identify and recover such over-payments involves ad-hoc querying of medical claims databases and manual auditing of potentially overpaid claims. This paper describes the successful deployment of a data mining framework, predominantly using predictive modeling and association rule discovery techniques to correctly identifying overpaid claims.

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Format:PDFSize:111 KB
Date:Oct 2008
Pages:7

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