In the health policy arena, information technology is seen as a panacea to improve efficiency, reduce repeat testing, and save billions. While those are some expected benefits of electronic medical record-keeping, its greater money-saving potential may lie in helping to uncover fraud.
The National Health Care Anti-Fraud Association (NHCAA.org) conservatively estimates that 3 percent of all health care spending--about $68 billion--is lost to fraud. A more jaundiced, or perhaps realistic estimate by the FBI and CDC puts the rate at 10 percent, a crippling $226 billion loss yearly.
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Suddenly the urgency for electronic medical record adoption is in sharp focus because the best way to spot fraud is by using high-tech data mining tools.
One company at the forefront of this effort is HealthCare Insight, South Jordan, UT. HCI explained to DOTmed News that medical identity theft is a multi-faceted problem. To begin with, in a nation of nearly 50 million uninsured the temptation is great for families to misrepresent who is eligible for insurance, a well meaning but nonetheless illegal activity.
"The intent might be just to get somebody coverage. The fact is that [the health insurance policy] wasn't underwritten that way. So there are perpetrators who add others falsely or give their card to a family member or someone else to get care, and it is still fraud," said Joel Portice, COO of HCI.
While health care consumers are sometimes the perpetrators or victims of medical ID theft, all too often the bad actors are not the patients but health care professionals.
"The whole idea around stealing identity is not only on the patient side but it's also on the provider side where billing schemes use a legitimate provider's identification number and name but set up a phony address," Portice said. Once the scheme is in place, reimbursements can be diverted to the bad guys.
HCI combats the problem for public and private insurers by using sophisticated software tools that sift through claims looking for something amiss. Rule-based technology and predictive analytics identify patterns and schemes that indicate fraud -- a kind of virtual magnifying glass.
"Our approach is to look at fraud from the perspective of it being perpetrated by a provider, or using their provider identification information; for example somebody stealing their ID," Portice said. "We look at profiles and patterns of provider data. We process millions of claims each month to establish those patterns and scores that give us some kind of probability of fraud risk."