In this month’s article, the second in a four part series examining enforcement trends in the long term care industry, our authors review the increasing importance of statistical analysis in defending against fraud and abuse allegations.
As noted in our previous article, False Claims Act enforcement, and the attendant risk of financial liability, is on the rise. The United States Department of Justice has obtained almost $44 billion in FCA settlements and judgments since 1986, and almost $6 billion in 2014 alone. Significantly, roughly $2.5 billion of the funds recovered in 2014 came from the health care industry, marking the fifth straight year of fraud recoveries in excess of $2 billion. If FBI estimates that 3% to 10% of all federal healthcare billings are lost to fraud, then it would appear that these eye-popping numbers still have room to grow.
FCA enforcement in the long term care industry has been no exception. The industry has been squarely in the sights of government enforcement attorneys following a 2012 report from the Office of Inspector General that found roughly 20% of all Medicare Part A SNF claims were upcoded to a higher RUG group in 2009, resulting in $1.2 billion in improper payments. Recent FCA complaints have relied on a number of arguments to substantiate the submission of false claims for Medicare reimbursement: systematic upcoding to higher RUG levels due to corporate “pressure” on front line care providers; targeting therapy at or around RUG thresholds; increasing therapy during “look back” periods; and providing skilled therapy that was not required for improvement in functioning.
Although long-term care providers and other FCA defendants have raised a wide range of reasonable explanations for the billing patterns identified in recent complaints, the DOJ and private whistleblowers have been emboldened by a series of significant settlements. Enforcement attorneys have also been given a new, and potentially game-changing, tool thanks to a series of recent court opinions involving the use of statistical sampling and extrapolation to demonstrate FCA liability.
Wait, don’t they need to identify an actual claim?
While courts have long recognized statistical sampling as a valid method of proof, its use in FCA cases has been —until recently — fairly limited. The reasons for this limitation are somewhat intuitive, as sampling has typically been used to prove the amount of damages resulting from a fraudulent billing scheme (i.e., the amount the government was overbilled). This status quo, however, was disrupted in late 2014 when the Eastern District of Tennessee gave its blessing for prosecutors in U.S. ex rel. Martin v. Life Care Centers of America to use statistical sampling and extrapolation to prove not only damages, but actual liability under the FCA.
Life Care operates over 200 skilled nursing facilities nationwide that received $4.2 billion in Medicare reimbursement between 2006 and 2011. In Martin, the company is alleged to have engaged in a systematic practice of upcoding and providing medically unnecessary services that resulted in the submission of 150,000 false claims involving over 54,000 patients. In the typical FCA case, the government would have needed to demonstrate which of those 150,000 claims were “false” (i.e., submitted for medically unnecessary services) and whether the defendant knew those claims were false at the time they were submitted to a federal health care program. In Martin, however, the government analyzed just 400 “representative” sample cases and then sought to extrapolate the percentage of claims identified as “false” to the larger universe of 150,000 unidentified claims. Not surprisingly, Life Care sought summary judgment (i.e., that there is no factual dispute and the law requires a judgment in its favor) as to the unidentified claims, arguing that the falsity of an individual claim cannot be determined through statistical means.
Contrary to established expectations, the court denied Life Care’s motion and allowed the case to go to trial. While granting that “using extrapolation to establish damages when liability has been proven is different than using extrapolation to establish liability,” and finding no definitive precedent for doing so, the court still found that the government could use the evidence to prove its case due to the general acceptability of statistical analysis. Life Care, meanwhile, would be free to argue that the jury should not credit the government’s analysis because it is wrong or flawed.
As a practical matter, the use of statistical analysis to prove liability instead of damages would do two things. First, it would dramatically reduce the time and scrutiny of individual claims that is usually necessary to prosecute a credible FCA case. Second, and relatedly, it would allow the government and/or private whistleblowers to expand vastly the universe of allegedly false claims and set the stage for an environment where, once a handful of allegedly false claims is identified, every claim a defendant made within a specific time period could be fair game. And in this sort of environment, long-term care providers could see their FCA exposure driven less by pesky details like “facts” and “medical necessity,” and more by their ability to hire a better mathematics expert than their whistleblower.
This is not good news for providers, especially in light of the other recent changes to the FCA statute that have made it easier for “whistleblowers” to extract significant settlements.
A slippery slope ahead
Already, Life Care is beginning to bear fruit for whistleblowers and their attorneys. In U.S. ex rel. Ruckh v. CMC II LLC, for example, a federal judge in the Middle District of Florida cited Life Care in an order allowing the relator to use statistical evidence to prove liability in an FCA case involving roughly identical allegations of upcoding and medically unnecessary procedures. If Life Care continues to gain traction in cases such as Ruckh, it will create a dangerous precedent for long term care providers.
In our next blog, we’ll discuss whether poor quality of care should lead to FCA liability, and whether long-term care that is “worth less” can truly be “worthless.”
Jason R. Edgecombe is of counsel in the Atlanta, GA, office of Baker Donelson. He can be reached at email@example.com. Ted Lotchin is of counsel in Baker Donelson’s Washington, D.C., office, and is a member of the Firm’s Health Law Group. He can be reached at firstname.lastname@example.org.