The Centers for Medicare and Medicaid Services will acquire cutting edge analytic technology to predict and prevent potentially fraudulent payments in Medicare, Medicaid and the Children's Health Insurance Program.
The tools will integrate many of the agency's pilot programs into the National Fraud Prevention Program and complement the work of the joint Health and Human Services and Justice Departments' Health Care Fraud Prevention and Enforcement Action Team (HEAT).
Banks, credit card companies, insurance and other consumer companies already use predictive modeling tools to identify potential fraud before it occurs, said Donald Berwick, MD, CMS administrator. The agency is exploring the use of similar systems to identify background information on potential fraudsters and links to questionable affiliations.
This type of information will help prevent criminals from enrolling as healthcare providers or suppliers for the sole purpose of defrauding the healthcare system, he said in an announcement Dec. 16. Other tools will track billing patterns and other information to uncover in real-time any suspicious trends.
"Preventing fraud is more effective than the old 'pay and chase' model of fighting fraud after a sham provider has been paid and disappeared," Berwick said.
CMS will use the results to take anti-fraud actions before a claim is paid. The agency has already started to take administrative action to stop payments to "false fronts" in Texas that were exposed through sophisticated predictive modeling, he said.
CMS is also establishing new and expanded authority provided in the health reform law to take such actions, including suspending payments when investigating a credible allegation of fraud.
Many companies in the private sector, as well as CMS, have been testing and using predictive modeling programs to help identify possible fraudulent providers and scams based on historical information about the individual, or the company to which the individual is affiliated.
In one pilot program, CMS partnered with the Federal Recovery Accountability and Transparency Board to investigate a group of high-risk providers. By linking public data available on the Internet with other information, like fraud alerts from other payers and existing court records, a sophisticated and potentially fraudulent scheme was uncovered, Berwick said.
The scheme involved opening multiple companies at the same location on the same day using provider numbers of physicians in other states. The data confirmed several suspect providers who were already under investigation and, through linkage analysis, identified affiliated providers who are now also under investigation.
