Use Data Mining Techniques to Detect Medical Fraud in Health Insurance
AbstractThe health insurance claims application case the inspection usually relies on experts’ experience for verification and experienced personnel in charge for checking. However, due to the heavy work load and the insufficiency of manpower and experience, the ratio of miscarriages of justice is high, leading to improper settlement of claims and the waste of social resources. This paper takes advantage of data-mining technology to design models and find out cases requiring for manual inspection so as to save time and manpower. Six models are designed in this paper. By the analysis of the 20/80 principle and the coverage and accuracy ratio, a great number of periodic data (over 2 million records) are fed back to the data-mining models after repetitive verification. Also, it is discovered that to integrate the data-mining technology and feed back to different business stages so as to establish early warning system will be an important topic for the health insurance system in hospital’s EMR in the future. Meanwhile, as the information acquired by data-mining needs to be stored and the traditional database technology has limitations. Next time, this paper explores the ontology framework to be set up by semantic network technology in the future in order to assist the storage of knowledge gained by data-mining.
Bolton, Richard J. and David J. Hand., “Statistical fraud detection: a review,” Statistical Science, vol.17.3, pp. 235-249, 2002.
C. F. Lee, “Aspects of data mining,” Information and Education, pp.10-19, Feb. 2001.
C. G. Hwang, R.O.C.'s Labor Standards Law, National Open University, Taipei County, Mar. 2002.
Clark, J., T. Davies and H. Tilley, “Fraud Investigation: A Claims Handler's Guide,” http://www.crawfordandcompany.com/pdf/fraud, October 24, 2003.
Council of Labor Affairs, Table of Actual Premium Changes Applicable for Occupational Accident Health insurance of Labor Health insurance, Labor Health insurance, 2006.
Council of Labor Affairs, Table of Business Category and Premium Applicable for the Occupational Accident, Labor Health insurance, 2005.
Derrig, R.A. and Ostaszewski, K., “Fuzzy techniques of pattern recognition in risk and claim classification,” Journal of Risk and Insurance, vol. 62, pp.447-482, 1995.
Derrig R. A., "Insurance fraud," Journal of Risk and Insurance, vol. 69.3, pp. 271-287, 2002.
Grupe F. H. and Owrang M. M., Information System Management, Minnesota: Management Information Systems Research Center, 1995.
Ghezzi and Susan Guarino, "A private network of social control: insurance investigative units,” Social Problems, vol. 30.5, pp. 521-531, 1983.
Heinrich H. W., Peterson D. and Roos N., Industrial Accident Prevention, New York: McGraw-Hill, 1980.
Robert E. Hoyt and Colquitt L. Lee, “An empirical analysis of the nature and cost of fraudulent life insurance claims,” Insurance Regulation, vol. 15, pp. 451-480, 1997.
Han J. and Kamber K., Data Mining: Concepts and Techniques, San Francisco: Morgan Kaufmann Publishers, 2001.
M. Stone. J., The Royal Statistical Society, pp. 36, Feb. 1974.
Manuel Art´is, Mercedes Ayuso & Montserrat Guill´ en, “Modeling different types of automobile insurance fraud behaviors in the spanish market,” Insurance: Mathematics and Economics, vol. 24, pp. 67-81, 1999.
Pierre Picard, “Auditing Claims in the Insurance Market with Fraud: The Credibility Issue,” Journal of Public Economics, vol. 63, pp.27-56, 1996.
Sharon Tennyson & Pau Salsas,”Patterns of Auditing in Markets with Fraud: Some Empirical Results from Automobile Insurance,” Working Paper, 2000.
Bureau of National Health insurance, “Codes and scopes of classifications of diseases,” http://www.nhi.gov.tw/02hospital/hospital_5.htm, Aug. 2005.
Weisberg, H.I. & Derrig, R.A., “AIB Claim Screening Experiment Final Report,” Insurance Bureau o f Massachusetts, 1998.
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