Data mining applications that are used to
detect fraud and abuse often establish norms and then identify
unusual or abnormal patterns of claims by physicians, laboratories,
clinics, or others. Among other things, these applications
can highlight inappropriate prescriptions or referrals and
fraudulent insurance and medical claims. For example, the
Utah Bureau of Medicaid Fraud has mined the mass of data
generated by millions of prescriptions, operations and treatment
courses to identify unusual patterns and uncover fraud
[12]. As a result of fraud and abuse detection, ReliaStar Financial
Corp. has reported a 20 percent increase in annual savings,
Wisconsin Physician’s Service Insurance Corporation has noted
significant savings [13] and the Australian Health Insurance
Commission has estimated tens of millions of dollars of
annual savings.