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09:36 PM
Charles Babcock and Marianne Kolbasuk McGee
Charles Babcock and Marianne Kolbasuk McGee
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Filter Out the Frauds

Health insurers fight back against fake claims with fraud-detection software.

About a year-and-a-half ago, a Medicare examiner noticed a run on powered wheelchairs around Dallas. Health insurance payouts for the chairs had soared by 300 percent in the region, and a quick review showed supersized payouts in parts of California and Florida as well. By the time the inspectors combed through all the national data for wheelchair payouts, Medicare found that paid claims had tripled across 21 states in four years - a big anomaly.

The perpetrators got taxpayer-ID numbers and other data, submitted false claims for the $5,000 wheelchairs and absconded from the country with millions of dollars, after evading investigators for four years, says Kimberly Brandt, a top fraud investigator for Medicare and Medicaid. Slow analysis was partly to blame. "We had seen a lot of little blips," she says. "But we couldn't pull all the data together."

Putting the Brakes on Fraud

Last September, Medicare slapped new software checks on its claims processing system that identified powered-wheelchair claims and tested them for possible abuse - before a claim was paid. That's unusual in the health insurance industry, which is projected to pay out $1.8 trillion across 4 billion claims this year.

In the huge consumer credit card market, sophisticated software looks for cheats before companies part with their money. But most public and private health insurers examine only a small number of claims - after the fact - hemmed in by industry pressure to pay claims quickly and a lack of technological tools. By looking at claims before they're paid, Medicare has been able to stop payment on $140 million in suspect wheelchair claims. "We'd like to move more of our fraud-prevention effort into a proactive mode," Brandt says.

That wish may soon become reality for broader categories than motorized wheelchairs. Armed with new software tools, two insurers - Aetna Corp. and Vista Healthplan - are applying fraud-detection techniques, historically used in the credit card market, to examine all claims before they're paid.

Fair Isaac, a Minneapolis-based maker of statistical credit-scoring software for insurance firms, credit card companies and retailers that reviews 65 percent of worldwide credit card transactions for fraud, recently released a new version of its Payment Optimizer software for the healthcare industry that applies fraud-detection techniques used by companies such as Visa U.S.A. and MasterCard International to health insurance claims. Hollywood, Fla.-based Vista, which insures more than 350,000 people in Florida, is testing Fair Isaac's system to review every claim before it's paid. Insurers traditionally use their claims review systems - after payment - to analyze only a fraction of the total claims paid, though that share can vary dramatically, from 5 percent to as much as 50 percent. "It's Fair Isaac's job to stay ahead of the criminal," says William Rushton, internal audit and fraud-prevention director, Vista.

Meanwhile, IBM (Armonk, N.Y.) is developing a software module for its Fraud and Abuse Management System, which is used by companies such as Horizon Blue Cross Blue Shield of New Jersey and Humana to review claims for possible insurance cheats. The module can review insurance claims for fraud before they're paid, and Aetna (Hartford) plans to go live with it in October. When cheats are chased after they have their money, insurers are lucky to collect a fraction of fraud losses. Instead, Aetna plans to unleash IBM's technology on up to 1 million daily claims that wend their way through Aetna's system, says Ben Wright, the carrier's business systems manager. "We think we will reduce the total loss," he says.

The software companies - and the insurers testing their latest technologies - hope using prepayment analysis can reduce fraud levels to something closer to what they are in the credit card industry: 0.06 percent of all transactions. Getting money back after it's been paid is more difficult. Months of investigation typically lead to negotiated settlements or court dates that recover only 10 cents on the dollar. Sometimes, suspects simply walk away because enough evidence to indict can't be found.

The 'Holy Grail'

Examining claims before they're paid "is the Holy Grail of the healthcare industry," says Bill Mahon, who consults for insurance payers on fraud and is the former president of the National Health Care Anti-Fraud Association, a nonprofit organization for sharing fraud information among insurance companies. Until recently, the industry took the point of view that examining claims before they were paid resulted in too little fraud detection and unacceptable delays. So, for all its heavy-duty claims processing systems and data mining techniques, the healthcare industry remains reactive to cases of fraud rather than trying to prevent them in the first place.

Bilking Medicare, Medicaid and private healthcare plans "is a national epidemic," says Dave Hennings, 2004 chairman of the National Health Care Anti-Fraud Association. "We've been combating fraud from a reactive mode," he says. "IBM and Fair Isaac are moving to a more proactive mode, as [exists] in the credit card industry."

The escalating costs of fraud may lead companies to look for new solutions. Estimates of the amount of U.S. healthcare fraud range from 3 to 5 percent of filed claims. That translates into an estimated $57 billion to $94 billion in losses this year - equivalent to the annual tax revenue of the state of California at the high end of that range.

And the problem is growing, at a 7 to 10 percent annual clip, reports Tim Delaney, chief of the Federal Bureau of Investigation's healthcare fraud unit. By 2010, $154 billion in claims a year could be bogus. The problem is so persistent that some observers ask why the healthcare industry can't do what the credit card industry has done over the past 12 years: cut fraud in half, or even greater, by using fraud-detection computer systems up front.

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