Touting a breakthrough in combating rampant fraud in the Medicare and Medicaid health care systems, the Obama Administration on Wednesday told Congress that it had prevented $42 billion of improper payments to doctors and other medical providers in fiscal 2013 and 2014 by using more sophisticated detection methods.
After years of haphazard auditing and enforcement practices that frequently missed multi-million dollar scams, federal authorities under prodding from Congress are now ferreting out corruption through the use of “big data” and predictive analytics, more frequent on-site inspections to check out suspicious activities and better coordination among federal and state authorities.
The results have marked a turnaround in the government success rate in preventing the loss of billions of dollars allotted to the healthcare of seniors, the poor, children and the disabled. The Centers for Medicare and Medicaid Services (CMS) says every dollar that was invested in the agency’s Medicare “integrity efforts” saved $12.40 for the Medicare program.
“This means that all our efforts – making sure health care providers enrolled in our programs are properly screened; using predictive analytics to prevent fraud, waste, and abuse; and coordinating our anti-fraud efforts with our federal and external partners – have resulted in billions of dollars saved in Medicare and Medicaid over the two-year period,” Shantanu Agrawal, the Director of CMS’s Center for Program Integrity,” wrote in a blog post yesterday.
President Obama has made cracking down on Medicare and Medicaid fraud a high priority in his second term, as federal and state law enforcement agencies have made a series of high-profile arrests and prosecutions.
Just last month, federal authorities announced that since 2010 their “Fraud Takedown” has resulted in the arrest and prosecution of about 1,200 people allegedly involved in defrauding Medicare and Medicaid of more than $3.5 billion.
The most recent charges came after investigators uncovered fraud involving an array of medical treatments and services, such as home health care, physical and occupational therapy, durable medical equipment sales and prescription drugs.
Doctors helped cook up schemes to submit claims to Medicare and Medicaid for treatments never provided to patients or that were unnecessary. Other health care providers offered kickbacks to “patient recruiters” to help assemble bogus patient information. Taken together, these unscrupulous physicians, occupational and physical therapists and others conspired to submit $900 million in fraudulent billings.
Agrawal said that CMS has come a long way from its antiquated “pay-and-chase” days of trying to recover improper payments long after they had been made. The 2010 Affordable Care Act included funding and tools to step up the policing of Medicare and Medicaid payments to providers.
That led to a new “multi-faceted” approach including the implementation of much tougher provider enrollment and screening standards, more aggressive use of law enforcement investigators and the use of advanced analytics such as “predictive modeling.”
Computer software is used to verify the addresses of health care providers and ferret out vacant buildings or mail drops. Investigators are frequently dispatched to the offices of doctors and others receiving inordinately large amounts of reimbursements or who practice in geographic areas with high records of fraud.
The Obamacare law set aside $100 million for CMS to develop a system of predictive analytics to curb improper or illegal payments and recruit two development teams led by major contractors Northrop Grumman and IBM.
A 2015 report by Modern Healthcare says the government system was inspired by the credit card industry’s success with predictive analytics in the 1990s in cracking down on fraud. Under CMS’s approach, four different analytical models were employed to detect fraud. One of them, a “rules-based model,” can quickly flag beneficiaries with ID numbers that are stolen or fraudulent. The “anomaly model” detects highly suspicious behavior, such as a doctor billing for a vast number of patients that he or she couldn’t possibly see in a given day or week.
A “predictive model” focuses attention on billing practices that strongly resemble past fraudulent activities. And a “social networking” model casts light on health care providers who have ties to previously identified fraudulent providers.
This overall approach to ferreting out potential fraud before it happens has enabled the government to avoid the situation of making billions of dollars in dubious or illegal payments and then struggling to recover the funds, according to CMS.
In fiscal year 2013, for instance, these new preventative actions resulted in about 68 percent of total savings, according to CMS. The following year, the portion of savings through these methods rose to nearly 74 percent.