Overruled: Court Denies Relator’s Objection to False Claim Act Settlement

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Significant work goes into settling a False Claims Act action. Defendants may spend months negotiating with the government to reach an agreeable settlement — often even longer if the defendant pursues the arduous ability-to-pay financial analysis process. But what happens when you reach the end of this process and the relator objects to the agreed-upon settlement amount? The United States District Court for the Central District of California recently faced this question, ultimately denying the relator’s objection and allowing the settlement to proceed.

In 2015, Trilochan Singh filed a qui tam lawsuit against California nursing homes that allegedly engaged in a kickback scheme, and the United States intervened in June 2021 after a lengthy investigation. The government’s complaint alleged that defendant nursing homes entered into medical director agreements that were used to pay physicians in exchange for making patient referrals to the nursing homes. After two years of motion practice, the parties reached a settlement on an ability-to-pay basis.

The settlement included a consent judgment for over $45 million, payment schedules, and limitations on enforcement against the defendants. Relator Singh objected to the settlement agreement on the basis that it was not fair, adequate, and reasonable. Singh requested and was granted a fairness hearing under 31 U.S.C. 3730(c)(2)(B), which permits the government to settle an action notwithstanding objections after a court evaluates, at a hearing, whether the “proposed settlement is fair, adequate, and reasonable under all the circumstances.” The relator sought discovery in addition to the hearing, but the court denied the request to take further discovery.

Singh argued that the actual payments the government expected to receive under the payment plans were too small and would be insufficient to cover the relator’s attorneys’ fees. 28 C.F.R. 0.160(a)(2) authorizes the government to “[a]ccept offers in compromise of claims asserted by the United States in all cases in which a qualified financial expert has determined that the offer in compromise is likely the maximum that the offeror has the ability to pay.” Singh disagreed with the analysis of senior financial analyst for the U.S. Department of Justice Karen Sharp that the settlement was the maximum that the defendant could pay. Singh also alleged that the government did not adequately analyze other assets owned by the defendants or allegedly transferred to others. 

In reaching the settlement figures, Sharp requested and reviewed 17 productions of financial ability-to-pay documents by the defendants. The productions included certified financial disclosures, balance sheets, income statements, bank records, lease agreements, real estate foreclosure notices, IRS tax liens, and more. Despite the extensive financial information disclosed, Singh argued that Sharp’s analysis was inaccurate because the defendant’s financial statements were unaudited and that Sharp should have considered whether the defendants “engaged in related party transactions.”

The court determined that Singh did not identify any assets that the government overlooked and did not show the government’s assessment of the defendant’s ability to pay was erroneous. Singh’s objections that the defendants were untruthful and that the government had not done due diligence to root out assets the defendants may have hidden were deemed to be too speculative. Accordingly, the court did not find Singh’s concerns justified enough to second-guess the government’s determination that it had sufficiently protected its interests or to require the government to proceed with claims that it wanted to settle. The court found the settlement fair, appropriate, and reasonable, denied the relator’s objection, and allowed the settlement to proceed.

DISCLAIMER: Because of the generality of this update, the information provided herein may not be applicable in all situations and should not be acted upon without specific legal advice based on particular situations.

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