Fraud factors

Health care is a trillion dollar industry in the United States. Unfortunately, health care fraud is nearly a $100 billion dollar industry.

It is a cancer that affects everyone: Taxpayers must pay more to support Medicare and Medicaid; consumers must pay higher premiums or deductibles for health insurance; and companies must shell out more to provide coverage for employees.

For years, good old-fashioned investigative work has been used to ferret out such fraud. But this approach is useful only after a crime has been committed. As is the case with health care itself, prevention is a much-preferred approach. Fortunately, technology has advanced to the point that there are new solutions that can — and should — be used to combat fraud.

To understand how this technology can help, it is important to understand the beast that is health care fraud. It comes in many forms. Claims can be submitted for services that were never rendered or for more serious procedures than were actually performed. Or bills for a group of procedures typically reimbursed as one can be submitted separately.

Then there are kickback schemes, which involve hidden financial arrangements between health care providers and/or patients. In one documented case, underprivileged children were coerced into visiting a clinic, where they were checked by every doctor for every conceivable malady. After their “checkups,” the kids were dropped off back in their neighborhood and given $20 apiece for their time. The doctors received hundreds of thousands of dollars in reimbursements.

How can technology help? The main way is through the use of “decision support solutions,” a group of technologies that use complex databases, mathematical algorithms and often artificial intelligence to transform raw data into more usable information. Tremendous amounts of data are generated in health care. Unfortunately, most of it is fragmented among numerous information systems. By integrating these pieces of the puzzle, a comprehensive view of a provider’s billing practices can be generated. By using advanced decision support tools, patterns of care can be analyzed and payments that shouldn’t be made can be identified.

Analyzing combined data will quickly expose providers who have billed for more hours than it is possible to work in a day and identify providers whose billings are always just under the allowable threshold. All kinds of irregularities can be unearthed.

This technology is already having a dramatic impact in Texas. The state recently implemented a Medicaid fraud and abuse detection system that incorporates advanced decision support capabilities — including neural network technology or learning technologies. The result so far: the system’s hit rate is nearly 100 percent, which means that virtually every suspect flagged indeed was engaging in fraudulent activities. By the year 2000, the system is expected to uncover at least 2,000 additional fraud suspects and recover $14 million more annually.

The Medicare program has begun to take a similar approach. The Health Care Financing Administration, which oversees both the Medicare and Medicaid programs, is implementing an information system that will integrate data from the Medicare Part A and Part B programs (physician and hospital billing, respectively) as well as from its managed care programs. Once all this information is integrated, decision support tools can be used to identify aberrant patterns.

The ultimate goal is to get a consolidated view of a provider’s activity. This is complicated when the provider offers services to numerous state and federal programs, plus employer-funded insurance programs — each with its own designation for that individual. With the help of the National Provider Identifier, which was mandated under the Health Insurance Portability and Accountability Act of 1996, obtaining that consolidated view is closer to reality. When fully implemented, this unique identifier will be used to create an integrated database with records of all providers and suppliers who are certified to bill Medicare or Medicaid.

With this identifier, it will be possible to spot providers who have been excluded from one program or another. Then, before a claim is paid, the database can be checked for evidence of previous fraudulent practices. This will provide a Better Business Bureau of sorts for the health care industry — something that is badly needed.

Diane C. Davis is Fraud and Abuse Systems and Products Manager with EDS’ State Health Care unit in Texas.