The False Claims Act contains numerous requirements that are designed to prevent meritless cases from proceeding to discovery and trial. Among these provisions is the rule that, to establish liability, the government or a relator must show that an actual claim was submitted to federal Medicare or state Medicaid for reimbursement. In some Circuits, such as the Eleventh, the government or a relator must identify claims at the pleading stage. Failure to do so will result in dismissal.
But what about cases in which tens of thousands of claims have been submitted? Should the government or a relator be required to identify the falsity of each and every claim to survive a dismissal? In cases such as these in which large volumes of false claims were allegedly submitted, False Claims Act plaintiffs have increasingly argued, sometimes successfully, in the affirmative—i.e., statistical sampling is a valid methodology for establishing liability. See, e.g., United States v. Life Care Centers of America, Inc., 114 F. Supp. 3d 549, 565-570 (E.D. Tenn. 2014) (rejecting defendant’s argument that statistical sampling cannot be used to establish liability); United States v. Robinson, 2015 WL 1479396, at *10 (E.D. Ky. Mar. 31, 2015) (admitting sampling evidence and collecting cases supporting the finding that “statistical sampling methods and extrapolation have been accepted in the Sixth Circuit and in other jurisdictions as reliable and acceptable evidence in determining facts related to [False Claims Act] claims as well as other adjudicative facts” (citing cases)). Plaintiffs, having long enjoyed the freedom to establish damages using such methodologies, are now increasingly turning to statistical sampling to establish liability.
Notably, no federal appellate court has squarely addressed whether statistical sampling is appropriate for establishing liability under the False Claims Act. In 2017, the Fourth Circuit had an opportunity to address the issue, but declined to do so on the grounds that the matter was inappropriately raised on interlocutory appeal. United States ex rel. Michaels v. Agape Sr. Cmty., Inc., 848 F.3d 330, 333 (4th Cir. 2017). This case, which was recently settled, presented the most notable opportunity for an appellate court to provide meaningful guidance in this area. Thus, as of this writing, the law on whether statistical sampling can be used to establish liability under the False Claims Act remains unsettled.
So what is the healthcare industry to do in the face of such uncertainty? At the very least, we would encourage you to read our guide on litigating and winning False Claims Act cases involving statistical sampling. The guide provides a multi-disciplinary approach to the problem. In addition to describing the legal contours, it also provides guidance on how to develop an effective and persuasive sample. Maintaining data dictionaries, conducting a root cause analysis, engagement with outside experts, obtaining all potential universes of data early, performing distribution analyses, evaluating potential biases in the data, considering whether a stratified sample is needed, and discussing the results of such analysis with outside experts and counsel are all critical to success in False Claims Act litigation involving statistical sampling. In addition, we would encourage you to stay tuned to our Healthcare Law and False Claims Act blogs, where we will continue to follow developments in this important and unsettled area of law.