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Predictive analytics can detect growing fraud in Healthcare Claims

I saw an interesting article in CIO Insight the other day: Health IT Must Target Fraud, Group Says. The report - from the Foundation of Research and Education (FORE) of the American Health Information Management Association (AHIMA) - says that it is essential that fraud management programs be built into the new National Health Information Network (NHIN) to significantly reduce health care fraud losses.

The report calls for interoperable Electronic Health Records as a major enabler - integrated data being no less important for healthcare than it is for CRM - and goes on to say that major strides can be made in reducing health care fraud by applying advanced analytics like those used so  successfully in the financial services industry.  The best results will be driven by both prospective and retrospective approaches, the report said, and made a fairly dramatic prediction of the value:

“By 2007, healthcare payer organizations that adopt automated systems for fraud and abuse detection will see a return on investment of at least 5 to 1,”

The report was prepared for the U.S. Department of Health and Human Services and incorporated information from Fair Isaac - healthcare fraud being one of our specialist subjects as it were.

An important action item noted in the CIO Insight story points towards using an EDM approach to address fraud in healthcare. It points out that one must fully integrate and implement fraud management programs and advanced analytics software in interoperable EHRs to achieve all of the estimated potential economic benefits.  Fortunately Fair Isaac already has an EDM solution available for this - Payment Optimizer - which combines the flexibility of business rules with the detection of patterns of fraud using predictive analytics.

Payment Optimizer provides healthcare payers with prepayment and post payment analysis to dramatically reduce fraud losses and ensure payment integrity.  It can detect suspicious activity and billing and policy errors in medical and pharmacy claims throughout the prepayment and post-payment continuum, including immediately after payment. So how does Payment Optimizer do this? Well, by analyzing millions of interactions in a fraction of a second, using both incoming and historical data, Payment Optimizer creates a multidimensional picture of the healthcare delivery system. Users can quickly identify fraudulent activity and the advanced analytics enable accurate and efficient detection of new and unknown fraud patterns as well as subtle and complex trends by looking at each claim in relation to deep contextual information, such as the patient’s and provider’s histories. 

The CIO Insight report quoted Dr. David J. Brailer, national coordinator for Health Information Technology in HHS on the importance of using national coding systems to detect fraud.  Brailer is also the subject of a major feature in the Oct. 31 issue of Business Week (www.businessweek.com) on his efforts to promote “the rewiring of American medicine.” A full copy of the FORE report is available from AHIMA (www.ahima.org).

Thanks to my colleague Teri Kim for additional insight into the report.

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