The submission of false claims bilked health insurers out of $42 billion in 2001. Sniff out perpetrators and avoid losses with automated fraud detection.

Fraud. It's a short word, but it poses an enormous problem for the healthcare industry.

It occurs when providers or patients deliberately submit false claims to private health insurance plans or government programs such as Medicare or Medicaid. Sometimes the culprit is a dishonest service provider that bills for services never rendered; other times it happens when patients file claims for exams or medications they never received. Perpetrators' methods have grown increasingly complex as national annual healthcare spending registers in the trillions.

Roughly $42 billion—or 3 percent of the U.S. expenditure on healthcare—was lost to fraud in 2001, according to the National Health Care Anti-Fraud Association (NHCAA). On an up note, NHCAA-member insurers reported recovering or preventing payments of some $356 million in 2001, thanks to antifraud efforts. That's a lot of money—but it's only a sliver of the total loss.

Part of the problem is that rather than automating their fraud detection systems, healthcare organizations continue to fall victim to human error even as they strive to catch criminals.

Automated Fraud Prevention

The good news is that Sun Microsystems, Sybase, and SPSS have developed Predictive Fraud Detection for Healthcare, a proven template for detecting and analyzing patterns of fraud in large corporate data warehouses. Designed to be easy to integrate and customize, this offering enables customers to more quickly identify instances of fraud and take the actions necessary to stop it.

The Predictive Fraud Detection solution combines Sun Fire V480 Servers or Sun Fire V880 Servers and Sun StorEdge arrays; Sybase's industry-leading IQ Multiplex (IQ-M) relational database software; and SPSS's data mining workbench, Clementine, and healthcare-specific Clementine Application Templates (CATs). The solution handles key tasks, including:

• Profiling and segmenting claimants to pinpoint those most likely to commit fraud
• Predicting medical practices most likely to be subject to fraud
• Identifying services and product combinations most likely to break claim regulations
• Detecting claim fraud regionally and among certain practices
• Identifying such fraudulent practices as submitting duplicate claims, "unbundling" (submitting a claim for each procedure when only one is required), and "ping-ponging" (sharing a single patient ID to generate billings across multiple providers)
• Taking definitive steps to prevent fraud at every point in the claims submission and processing lifecycle

Sun and its partners have put together fraud detection solutions for small, medium, and large enterprises, ensuring that no healthcare organization is left behind. 

» Look under the hood at the solutions that comprise Predictive Fraud Detection for Healthcare from Sun, Sybase, and SPSS. » Visit Sybase and SPSS for more information on their technologies.