DocumentCode
2507024
Title
Using support vector machines to detect medical fraud and abuse
Author
Francis, Charles ; Pepper, Noah ; Strong, Homer
Author_Institution
Qmedtrix, Portland, OR, USA
fYear
2011
fDate
Aug. 30 2011-Sept. 3 2011
Firstpage
8291
Lastpage
8294
Abstract
This paper examines the architecture and efficacy of Quash, an automated medical bill processing system capable of bill routing and abuse detection. Quash is designed to be used in conjunction with human auditors and a standard bill review software platform to provide a complete cost containment solution for medical claims. The primary contribution of Quash is to provide a real world speed up for medical fraud detection experts in their work. There will be a discussion of implementation details and preliminary experimental results. In this paper we are entirely focused on medical data and billing patterns that occur within the United States, though these results should be applicable to any financial transaction environment in which structured coding data can be mined.
Keywords
fraud; medical administrative data processing; support vector machines; Quash; automated medical bill processing system; bill routing detection; medical abuse detection; medical fraud detection; support vector machines; Accuracy; Encoding; Hospitals; Humans; Machine learning; Medical diagnostic imaging; Training; Artificial Intelligence; Fraud; Health Services Misuse; Humans; Insurance Claim Reporting; Support Vector Machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location
Boston, MA
ISSN
1557-170X
Print_ISBN
978-1-4244-4121-1
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2011.6092044
Filename
6092044
Link To Document