In today’s charged debates about healthcare, one issue enjoys strong bipartisan support: the need to eliminate fraud, waste and abuse that collectively cost as much as $700 billion annually – nearly one-third of total healthcare spending. That’s more than 10 times more money than financial services firms lose to credit card fraud each year. Yet the health care industry devotes only one-tenth of the money that financial services firms spend to prevent, detect and resolve fraud.
Unfortunately, targeting this waste isn’t easy. When a payer tries to uncover fraud or waste, it must sift through growing volumes of data – sometimes tens of millions of records. And with the increasing prevalence of organized crime and collaborative theft rings, it’s more vital than ever to uncover the subtle patterns among patients, providers and facilities that could indicate collusion and far-reaching fraud.
With traditional software tools that require extensive data preparation and elite skills to create reports, investigators often can’t quickly identify truly suspect claims (after weeding through false-positives). The clock ticks and payers typically must make contractually mandated payments within specific time periods. If fraud is subsequently discovered, payers are trapped in the “pay and chase” recovery model, which is difficult, time-consuming, and largely unsuccessful. Typically, no more than 5 percent of dollars lost to fraud are recovered because providers have no incentive to cooperate in providing background documentation post-payment.
Better technology needed
There is a significant opportunity to ditch the rearview mirror approach and replace it with a prepayment review that dramatically reduces the incidence and costs of fraud and waste. Today’s payers need powerful analytics with easy-to-read screens that predict and spot fraudulent claims by merging data and prioritizing financial exposure. Our industry must also reinvent processes to accept the practice of suspending payments for suspicious claims until full documentation is received. Using the same techniques as financial services, new-breed analytics can hone in on doctor-shopping drug users and elaborate fraud schemes that employ networks of fraudsters with fake illnesses.
The best reasons for using powerful analytical, user-friendly approaches comes from payer successes:
- An insurer saved $11 million in just its first year and investigator productivity climbed 30 percent as activities that once took hours now take minutes.
- One state prevented $14 million in Medicaid fraud and detected an additional $27 million in fraudulent claims, leading to indictments.
- A national insurer’s fraud investigators now quickly stop payment on complex fraud cases. The solution frees up experienced investigators to work on highly complex cases.
Our industry needs a fraud-prevention framework that measures the likelihood of fraud using an analytical engine to calculate a fraud score. This can help health payers decrease losses and increase recoveries without increasing team resources by offering exceptional predictive modeling capabilities, delivered on point-and-click screens that are easy to read. It is an approach that forward-thinking payers need to implement now.
Julie Malida is the health care fraud principal in the Fraud and Financial Crimes Practice at SAS. Malida has 26 years of experience in senior leadership roles at health plans and healthcare consulting organizations, and was formerly the president of a premier healthcare fraud detection and investigations company.
