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Whistleblowers Can Offer Statistical Sampling to Support Fraud Claims

by | Jun 3, 2015 | Coding-lca, Essential, Lab Compliance Advisor

A federal trial court in Florida has ruled that qui tam or whistleblower plaintiffs can use statistical sampling to prove fraud in a False Claims Act lawsuit. The court explained:“[N]o 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 whistleblower in this case had brought claims against entities that operated facilities at which she had worked, claiming they defrauded the U.S. and Florida governments by upcoding or upcharging for services rendered. Arguing that it was too difficult to provide individual analysis of claims from 53 facilities, the plaintiff asked the court to admit expert testimony about statistical sampling she planned to provide. The sampling had not yet been performed but the plaintiff wanted to determine if the court would accept such evidence to prove falsity of claims. History of the case. The defendants had previously succeeded in getting the claims dismissed because the alleged fraud wasn’t stated with sufficient particularity. Federal Rules of Civil Procedure require that fraud allegations be stated with particularity—that is, with specific detail. The plaintiff had claimed in her original complaint that she “witnessed […]

A federal trial court in Florida has ruled that qui tam or whistleblower plaintiffs can use statistical sampling to prove fraud in a False Claims Act lawsuit. The court explained:“[N]o 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 whistleblower in this case had brought claims against entities that operated facilities at which she had worked, claiming they defrauded the U.S. and Florida governments by upcoding or upcharging for services rendered. Arguing that it was too difficult to provide individual analysis of claims from 53 facilities, the plaintiff asked the court to admit expert testimony about statistical sampling she planned to provide. The sampling had not yet been performed but the plaintiff wanted to determine if the court would accept such evidence to prove falsity of claims. History of the case. The defendants had previously succeeded in getting the claims dismissed because the alleged fraud wasn’t stated with sufficient particularity. Federal Rules of Civil Procedure require that fraud allegations be stated with particularity—that is, with specific detail. The plaintiff had claimed in her original complaint that she “witnessed false claims submissions and ‘flagrant upcoding’” of Medicare and Medicaid claims. The court ruled that she had alleged only a “general scheme to defraud the government” and described only one instance of fraud without giving “‘details about the fraudulent substance of the submission or about the time of the submission or about the government’s overpaying the claim.’” It ordered the plaintiff to file an amended complaint with more specific details to describe the alleged fraud—including “‘who, what, when, and where.’” The government chose not to intervene in the whistleblower’s case. The defendant refiled the complaint naming more defendants and claiming fraud occurred at 53 facilities—including facilities the plaintiff hadn’t visited. Sampling evidence. In support of her amended complaint, Plaintiff claimed gathering specific evidence of fraud from all 53 facilities and some off-site storage facilities was impossible. Therefore, she proposed using expert testimony based on statistical sampling to prove falsity of claims. The expert alleged that the sampling would estimate the total overpayments: “For example, if 1% of the population is sampled and reviewed, the total overpayment in the population is probably about 100 times the overpayment in the sample.” Court’s reasoning. The court relied on a case from a Tennessee district court in 2014 that allowed statistical sampling due to the “large universe of allegedly false claims” making it “impracticable for the Court to review each claim individually” without using “an unacceptable portion of the Court’s limited resources.” It also cited a Kentucky case decided earlier this year which allowed statistical sampling. The court rejected defendants’ arguments that sampling isn’t allowed in a qui tam action. The court denied the motion to admit the expert testimony that didn’t yet exist but unequivocally said such testimony, once it did exist, wouldn’t be excluded simply because it was based on statistical sampling. Defendants also argued that because the plaintiff was bringing the request before the sample was even conducted, the defendant couldn’t challenge the margin of error. The court left open the possibility of defendants’ successfully challenging the appropriateness of the sampling and the margin for error once the sampling was performed, stating “defects in method, among other evidentiary defects, might result in exclusion.” Takeaway: While this latest decision didn’t rule on the admissibility of specific sampling evidence, the court made an unequivocal statement that such evidence can be used to prove fraud in qui tam false claims lawsuits.

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