Supreme Court Permits Use of Statistical 'Representational Evidence': Implications for the FCA

Skadden, Arps, Slate, Meagher & Flom LLP

John T. Bentivoglio Jennifer L. Bragg Michael K. Loucks Gregory M. Luce

On March 22, 2016, the U.S. Supreme Court issued a decision in the Fair Labor Standards Act (FLSA) class action Tyson Foods, Inc. v. Bouaphakeo.1 In an opinion authored by Justice Anthony Kennedy, the majority held that class plaintiffs may introduce statistical “representational evidence” to prove FLSA liability. Although the Court expressly declined to pronounce any broad rule regarding the use of statistical evidence to prove liability in other types of cases, the opinion nevertheless may have significant ramifications in False Claims Act (FCA) litigation, especially for the health care industry.

Top Line Summary

  • The Supreme Court allowed the use of statistical evidence as “representative evidence” to prove liability in an FLSA case when other evidence was absent and the experts’ methodologies were not challenged under Daubert v. Merrell Dow Pharmaceuticals, Inc.2
  • While the Supreme Court has not addressed the use of statistical evidence in False Claims Act litigation to prove FCA liability, the Department of Justice and relators have increasingly argued that such evidence should be allowed for that purpose.
  • The health care industry should carefully consider the potential impact of statistical evidence at all stages of FCA investigations and litigation, including during settlement discussions.
  • Given the large volume of claims commonly associated with health care FCA cases, the government and relators have argued that allowing the use of statistical evidence to prove liability is required to avoid protracted and unmanageable litigation; such reasoning does not find support in the Court’s Tyson Foods ruling.

Factual and Procedural Background

Tyson Foods concerned a claim brought by plaintiff classes of Tyson Foods employees under the FLSA. The employees worked in a Tyson pork processing plant in Iowa as butchers and meat packers, and were required to wear certain protective gear according to their different jobs. Tyson paid the employees a wage based on “gang-time” spent at their work stations and paid certain employees for additional time spent “donning and doffing,” i.e., putting on and taking off, the protective gear. Employee Peg Bouaphakeo sued Tyson on behalf of a putative class of affected employees, claiming that the system did not properly compensate overtime work and violated the FLSA and state law.

The trial court certified plaintiff classes under the Federal Rules of Civil Procedure and Section 216 of the FLSA, and the claims proceeded to a jury trial. Because Tyson kept no records of actual time spent donning and doffing equipment, the plaintiffs relied on a study by an expert witness, Dr. Kenneth Mericle, admitted as evidence in the case. The jury returned a special verdict finding that time spent changing into and out of protective equipment at the beginning and end of the work day was compensable under FLSA, although changing at other times was not. To calculate damages, the plaintiffs called another expert, Dr. Liesl Fox, to provide a separate analysis of the total amount of uncompensated time for each individual employee. Based on Fox’s study and its earlier finding as to what time was compensable, the jury awarded total damages of $2.9 million, less than half the $6.7 million in damages supported by Fox’s analysis.

The Eighth Circuit affirmed the judgment and award, finding that the “inference” the jury drew from the statistical studies was allowable. The Supreme Court affirmed the appellate court’s ruling.

The Court Allows the Use of Statistical Evidence to Prove Classwide Liability

Although the Supreme Court did not announce a broad rule on the admissibility of statistical “representative evidence,” it held that statistical evidence was admissible to prove liability in this FLSA case where the employer had no records of employee time incurred in changing to and from work clothing. The Court cited a 1946 opinion addressing similar facts and noted that, in general, statistical evidence is admissible to the extent it is “reliable in proving or disproving the elements of the relevant cause of action.”3 The Court reasoned that “[i]f the [statistical] sample could have sustained a reasonable jury finding as to hours worked in each employee’s individual action, that sample is a permissible means of establishing the employees’ hours worked in a class action.”4 Because Tyson did not keep records of changing time, the Court found that each plaintiff would have needed to introduce Mericle’s study individually to prove the hours they had worked had those plaintiffs brought independent actions. Accordingly, the Court held that class plaintiffs’ statistical evidence was admissible, although the Court cautioned that “its persuasiveness is, in general, a matter for the jury.”5 The Court noted that the applicability of statistical evidence in other types of cases would depend upon those cases’ particular facts and circumstances.

The Court also emphasized that its holding in Tyson Foods was in accord with its rejection of a “Trial by Formula” in Wal-Mart Stores, Inc. v. Dukes.6 In that class action appeal, the Court rejected the use of a sample set of class members to determine an aggregate class damages award because doing so “enlarge[d] the class members’ substantive right[s] and deprive[d] defendants of their right to litigate statutory defenses to individual claims.”7 This impermissible disparate treatment of the parties in a class action would not occur in Tyson’s circumstances, according to the Court, because any member of the class could have used the same expert conclusions to support that individual member’s claim and provide the evidence missing from the employer’s records. This important distinction will likely color arguments in other cases as to the use of “representative evidence” based on statistical sampling, such as in FCA actions.

Considerations for Health Care Entities Facing FCA Claims

  • The Tyson Foods opinion notes that the permissibility of statistical evidence will turn on “the degree to which the evidence is reliable in proving or disproving the elements of the relevant cause of action.”8 Although the Supreme Court’s recent rulings have not expressly addressed the permissibility of statistical evidence to prove liability in an FCA cause of action, lower courts are split on the question, with some allowing such evidence to prove the elements of a False Claims Act violation and many allowing such evidence to establish damages.9
  • Recent press accounts and court filings indicate that the Department of Justice will seek to introduce statistical evidence of fraud as opposed to actual evidence of fraud as it pursues FCA claims against health care entities, and some of the broader language of Tyson Foods may be suggested as supporting the use of such evidence.
  • The government would likely attempt to introduce such statistical evidence where (1) evidence of individualized claims is lost or not maintained (like Tyson Foods); (2) the volume of claims at issue is very high; or (3) individual case adjudication is arguably not feasible given the time and expense of investigating and trying a large aggregation of claims. Each of these conditions is often found in health care FCA matters.
  • Attempts to rely on statistical evidence — and to extend Tyson Foods beyond the FLSA context — seem to be at odds with the pleading requirements and availability of claims information typically found in FCA matters. FCA case law generally requires a plaintiff to establish the elements of fraud for each claim; extrapolation would remove individual considerations of each claim. Moreover, unlike Tyson Foods, claim information underlying an FCA case is presumably known, cutting against an argument that “representative evidence” should be allowed.
  • Nevertheless, health care entities, including providers and pharmaceutical and device manufacturers, among others, should anticipate the use of statistical evidence by the government and relators at even the early stages of an investigation or settlement discussions and, if litigation commences, consider a Daubert challenge to such evidence.


1 No. 14-1146, --- S. Ct. ---, 2016 WL 1092414 (Mar. 22, 2016). See also our March 22, 2016, client alert, “Inside the Courts: Supreme Court Upholds Class Certification in Tyson Foods.”

2 509 U.S. 579 (1993).

3 Tyson Foods, 2016 WL 1092414 at *8.

4 Id.

5 Id. at *11.

6 564 U.S. 338 (2011).

7 Tyson Foods, 2016 WL 1092414 at *13-14 (internal alterations in original; internal quotation marks omitted) (citing Wal-Mart, 564 U.S. at 367).

8 Id. at *8.

9 See, e.g., United States ex rel. Michaels v. Agape Senior Cmty., Inc., No. 12-3466-JFA, 2015 WL 3903675, at *6-9 (D.S.C. June 25, 2015) (rejecting use of statistics to prove FCA liability and damages, and collecting cases and certifying question for interlocutory appeal), appeal docketed Nos. 15-2145, 15-2147 (4th Cir. Sept. 29, 2015); United States ex rel. Martin v. Life Care Ctrs. of Am., Inc., 114 F. Supp. 3d 549, 565-68 (E.D. Tenn. 2014) (allowing use of statistical sampling to prove the elements of FCA claims); United States v. Fadul, No. 11-0385, 2013 WL 781614, at *14 (D. Md. Feb. 28, 2013) (“Courts have routinely endorsed sampling and extrapolation as a viable method of proving damages in cases involving Medicare and Medicaid overpayments where a claim-by-claim review is not practical.”).

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