Saturday, May 30, 2015

Health Care Law: Statistical Sampling in False Claims Act Litigation

By Stephen V. Iglesias

The government and qui tam relators are increasingly using statistical sampling in False Claims Act to garner massive recoveries. Audit results based on reviewing a small sample of claims are extrapolated over a larger universe of claims to calculate overpayments. The government touts statistical sampling as a resource efficient means to calculate False Claims Act damages and penalties. Defendants counter that statistical sampling fails to account for the unique nature of each patient’s medical condition. Recent federal court decisions suggest a trend toward permitting the use of statistical sampling to establish both False Claims Act liability and damages.

In the Eleventh Circuit and the Middle District of Florida, statistical sampling was endorsed as a method to calculate False Claims Act damages in United States v. Rosin, 263 F. Ap'x 16 (11th Cir. 2008) and Baklid-Kunz v. Halifax Hospital Medical Center, 2014 WL 2968251 (M.D. Fla. Jul. 1, 2014), respectively. In United States ex rel. Martin v. Life Care Centers of America, 2014 WL 4816006 (E.D. Tenn. Sept. 29, 2014), however, the court expanded the use of statistical sampling beyond calculating damages. In Martin, the government selected a sample of 400 Medicare beneficiaries who received allegedly medically unnecessary services over a seven-year period and, from this sample, extrapolated 154,621 false claims. In denying the defendant’s motion for partial summary judgment, the court rejected the defendant’s due process argument that a claim-by-claim review is necessary. The court was concerned defendants stand to unfairly benefit in a case involving a high volume of claims knowing the impracticability of a claim-by-claim review. To establish False Claims Act liability, the court permitted sampling to extrapolate claims that supported the elements of falsity and materiality. The opportunity to cross-examine the statistical expert offers adequate protection to the defendant. Similar to Martin, the court in United States v. AseraCare, 2014 WL 6879254 (N.D. Ala. Dec. 4, 2014) permitted the government to proffer a statistical sample of claims to defeat the defendant’s motion for summary judgment on the element of falsity.

In United States ex rel. Guardiola v. Renown Health, 2014 WL 5780426 (D. Nev. Nov. 5, 2014) the court compelled the defendant to produce to the qui tam relator, for the purpose of deriving a statistical sample of claims, all Medicare claims data falling within the time span of the False Claims Act statute of limitations. The relator intended to use the sample to extrapolate the number of false claims over the course of the fraud scheme. Guardiola follows the same tack as Martin and AseraCare in expanding the use of statistical sampling to support FCA liability.

The above cases arguably have limited precedential value outside their respective federal judicial districts. Notably, none of the cases permit the use of statistical sampling to prove the elements of scienter or causation. Further, the courts did not pre-approve any sampling methodology, and they encouraged the defendants to vigorously challenge statistical evidence in Daubert motions and at trial.