Another federal court has accepted a whistleblower’s proposal to use a statistical approach in False Claims Act (FCA) litigation to extrapolate from a small billing sample to a much larger universe of claims. This is one of several federal courts to accept this alternative method of establishing liability under the FCA, which could pave the way for similar approaches in qui tam lawsuits alleging improper Medicare or Medicaid billing. While the court recognized that defects in the method could result in excluding the extrapolation results at a later point in the litigation, it declined to bar the approach outright.

In a brief April 28 opinion, the United States District Court for the Middle District of Florida cited decisions that recognized the validity of statistical sampling in FCA cases, including a 2014 opinion from a Tennessee federal court that supported extrapolation for FCA liability. The court concluded that “no universal ban on expert testimony based on statistical sampling applies in a qui tam action (or elsewhere), and no expert testimony is excludable in this action for that sole reason[.]”

The case is United States ex rel. Ruckh v. CMC II LLC et al., case number 8:11-cv-01303, brought against current defendants CMC II, LLC; Sea Crest Health Care Management, LLC; Salus Rehabilitation, LLC; 207 Marshall Drive Operations, LLC; and 803 Oak Street Operations, LLC. The relator ischallenging the billing practices of 53 skilled nursing facilities in Florida that allegedly defrauded the United States and Florida by “up-coding” and “up-charging” for patients. Given the large number of locations, the relator is proposing to analyze sample data to extrapolate across the many locations.

Even though the DOJ did not intervene in this case, it did file a brief in support of relator’s motion in limine to admit expert testimony based on statistical sampling. The government’s support tracks some of its other practices. For example, in the context of self-disclosures, the OIG accepts “a statistically valid random sample of the claims that can be projected to the population of claims affected by the matter.” A self-disclosing provider, however, would likely be in a better position to assess how to create a sampling approach that accurately reflects an identified issue than a relator alleging an unsubstantiated billing impropriety across a large number of potentially diverse locations serving dissimilar patients and covering long scopes of time.

Given these relaxed proof standards, defendants in FCA actions may need to focus on effective, early challenges to the data selected for use in a proposed statistical sample, or its applicability across multiple years or different facilities, as an important fallback argument should efforts to avoid the practice fail. Providers could apply their presumably broader knowledge of their operations to show an unacceptable margin of error or other defects in the relator’s extrapolation, or could counter with extrapolation models of their own. A defendant’s insider perspective could offer an advantage if the qui tam landscape continues to favor extrapolation, particularly if the debate turns from “whether” to “how” to extrapolate from a sample.