A process-mining framework for the detection of healthcare fraud and abuse

People rely on government-managed health insurance systems, private health insurance systems, or both to share the expensive healthcare costs. With such an intensive need for health insurances, however, health care service providers' fraudulent and abusive behavior has become a serious problem....

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Bibliographic Details
Published in:Expert systems with applications 2006-07, Vol.31 (1), p.56-68
Main Authors: Yang, Wan-Shiou, Hwang, San-Yih
Format: Article
Language:English
Subjects:
Classification model
Clinical pathways
Data mining
Healthcare abuse
Healthcare fraud
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Summary:People rely on government-managed health insurance systems, private health insurance systems, or both to share the expensive healthcare costs. With such an intensive need for health insurances, however, health care service providers' fraudulent and abusive behavior has become a serious problem. In this research, we propose a data-mining framework that utilizes the concept of clinical pathways to facilitate automatic and systematic construction of an adaptable and extensible detection model. The proposed approaches have been evaluated objectively by a real-world data set gathered from the National Health Insurance (NHI) program in Taiwan. The empirical experiments show that our detection model is efficient and capable of identifying some fraudulent and abusive cases that are not detected by a manually constructed detection model.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2005.09.003