As those in the health care industry are well aware, the federal False Claims Act (FCA) imposes stiff penalties for each false claim submitted to the federal government, resulting in recoveries of over $2 billion in fiscal year 2014 relating to federal healthcare programs alone. In recognition of the highly fact-dependent analysis and per-claim liability, plaintiffs must allege fraud with particularity in FCA actions. However, while the FCA continues to attach liability at a claim-by-claim level, some district courts have shown an increased willingness to endorse plaintiffs' controversial use of statistical sampling and extrapolation of such samples to establish liability in FCA actions involving a large number of alleged false claims.
In an issue of first impression for the federal appellate courts, the United States Court of Appeals for the Fourth Circuit recently agreed to decide whether statistical sampling may be used to prove liability or damages under the FCA, in United States ex rel. Michaels v. Agape Senior Community Inc., No. 15-2145.
The FCA provides a cause of action against any person who, among other things, "(A) knowingly presents, or causes to be presented, a false or fraudulent claim for payment or approval; [or] (B) knowingly makes, uses, or causes to be made or used, a false record or statement material to a false or fraudulent claim . . ." 31 U.S.C. § 3729(a)(1)(A)-(B). Plaintiffs must prove every element of an FCA cause of action by a "preponderance of the evidence," including such elements as falsity, knowledge, and damages. See 31 U.S.C. § 3731(d).
Historically, some courts have recognized the use of statistical sampling in other types of litigation, such as antitrust, complex employment litigation, and toxic tort and mass tort cases. Statistical sampling involves the use of mathematical and statistical methods to estimate characteristics of a large population by extrapolating results from a small sample of that population. While courts have accepted analyzing samples of evidence as a method of proving liability about a significantly larger universe of evidence in other kinds of litigation, the courts that have allowed the use of statistical sampling in FCA actions generally have limited its use to determining damages. See United States v. Cabrera-Diaz, 106 F. Supp. 2d 234, 240 (D.P.R. 2000) (discussing cases endorsing the use of statistical sampling to establish damages).
In United States ex rel. Martin v. Life Care Centers of America, Inc., however, the United States District Court for the Eastern District of Tennessee sided with the government's request to employ statistical sampling to establish both FCA damages and liability by extrapolating from a random sample of 400 patient admissions to a universe of 54,396 patient admissions, totaling more than 154,000 claims. See Life Care, No. 1:08-cv-251, 2014 U.S. Dist. LEXIS 142660, at *20 (E.D. Tenn. Sept. 29, 2014). The government alleged that Life Care, as owner of more than 200 skilled nursing facilities nationwide, engaged in a corporate scheme whereby it submitted fraudulent claims to Medicare for unnecessary therapy services.
Life Care moved for partial summary judgment on the unidentified claims that the government sought to prove as false exclusively through the use of extrapolation. Life Care argued that the government's use of statistical extrapolation would inappropriately shift the burden of proof to Life Care, would violate Life Care's due process rights, and would not provide evidence to satisfy the elements of proof in an FCA action, including falsity, knowledge, and materiality.
After reviewing FCA cases addressing the use of statistical sampling and finding them non-determinative, the court found that neither the plain language of the FCA nor its legislative history reflects a prohibition or disinclination toward the use of statistical sampling in FCA cases. Id. at *43, 62. Ultimately, the court concluded that the government could employ statistical sampling to prove its FCA causes of action, focusing its holding on the impracticability of a claim-by-claim review in complex FCA actions and noting that to require such claim-by-claim review "would open the door to more fraudulent activity because the deterrent effect of the threat of prosecution would be circumscribed." Id. at *63.
The Life Care court emphasized that, while its holding permits plaintiffs to use statistical sampling to prove FCA causes of action involving Medicare overpayment, the burden of weighing the extrapolated evidence lies with the ultimate fact finder. Id. at *64. The court noted that defendants may challenge the statistical sample through a variety of methods, including cross-examination of plaintiffs' experts and presentation of competing witnesses, experts, and evidence. The Life Care court subsequently denied the defendant's request for permission to appeal its ruling.
Unlike the court in Life Care, the United States District Court for the District of South Carolina recently rejected the use of statistical sampling and extrapolation as a method of proving liability or damages in an FCA case involving the submission of more than 50,000 allegedly false claims for hospice services. See United States ex rel. Michaels v. Agape Senior Cmty. Inc., No. 12-3466, 2015 WL 3903675 (D.S.C. June 25, 2015). Though it declined to intervene, the government objected to a settlement reached by the parties on the basis of the government's extrapolation to a potential recovery amount significantly greater than the agreed-upon settlement. Interestingly, prior to the government's objection, the court had ruled during discovery that it would not allow the plaintiffs-whistleblowers to use statistical sampling to determine damages.
Faced with the government's use of statistical sampling, the court set forth its rationale for disallowing statistical sampling as a method of proving liability or damages, noting at the outset that this case is not one where direct proof of damages has dissipated or been destroyed. Acknowledging numerous cases on either side of the issue, the court found the case not suited to statistical sampling, as each payment claim presented a question of medical necessity requiring review of the detailed medical chart of each patient. Agape, 2015 WL 3903675, at *8.
The Agape court implored the parties to seek permission from the Fourth Circuit to review two questions: (1) whether the government has unreviewable veto power to reject a settlement in a case in which it has declined to intervene and (2) whether statistical sampling and extrapolation can be used to prove damages or liability in an FCA case. On September 29, 2015, the Fourth Circuit agreed to review both questions, opening the door to the first appellate ruling on the statistical-sampling issue. Briefing on the merits of that issue will take place later this year. Those interested in submitting their views via a friend-of-the-court brief will also have an opportunity to do so. A decision is not expected until late 2016.
In the meantime, health care providers have a number of available strategies for challenging the use of statistical sampling in FCA cases, including the following:
- Challenge the Need for Statistical Sampling: Consider whether other reasonable options exist for analyzing the claims at issue that would eliminate the need for statistical sampling.
- Challenge the Validity of the Sampling Technique: Highlight defects in the sampling methodology, including small sample sizes, unrepresentative samples, sample selection biases and randomness of the sample.
- Challenge the Extrapolation Method and Conclusions: Scrutinize the estimation method employed and extrapolation conclusions reached, paying close attention to the confidence (degree of certainty) and precision (range of accuracy) levels.
- Challenge the Admission of Statistical Sampling Evidence: Procedurally, providers may challenge the admission of statistical extrapolation evidence or testimony through so-called "Daubert motions." In Daubert proceedings, a court determines the admissibility of expert testimony or scientific evidence under Federal Rule of Evidence 702 by analyzing whether the evidence is both relevant and reliable.
- Challenge the Findings: Closely review the factual findings and examination processes used regarding the sample claims, conducting an independent examination of the sample claims as appropriate. This is a critical step, as allowing incorrect or questionable determinations about sample claims to go unchallenged has significant ramifications when multiplied exponentially as a result of extrapolation. Providers may also demonstrate uncertainty by challenging the credentials or the findings of the reviewers or by providing evidence of the subjectivity of the medical decisions underlying the submitted payment claims.
The Fourth Circuit's eventual ruling could have a significant impact on FCA cases in the healthcare sector. Should the Fourth Circuit agree with the lower court's disapproval of the use of statistical sampling, providers' ability to negotiate reasonable settlements likely will increase, as plaintiffs would need to expend additional resources to prove FCA liability. Conversely, judicial approval of the use of statistical sampling for determining liability under the FCA would significantly improve the government's bargaining position during settlement discussions and would arguably lower the bar for proving liability under the FCA. Faced with complex and widespread fraudulent schemes in which claim-by-claim review is impractical, the government would argue that refusing to allow statistical sampling and extrapolation would perversely incentivize large-scale fraud. However, while the availability of statistical extrapolation would lower the costs of prosecuting FCA actions, defendants will face higher costs as a result of increasing damages estimates and defending claims involving significantly larger universes of claims.
Whether at settlement or trial, providers should discuss available strategies for challenging the use of statistical sampling in FCA cases with knowledgeable counsel as early in the process as possible.
For additional information, please contact Kelly Carroll or James Segroves in Washington, D.C. at 202.580.7700; Patric Hooper in Los Angeles at 310.551.8111; Mark Reagan in San Francisco at 415.875.8500; or Mark Johnson in San Diego at 619.744.7300.