Summary
California's First District Court of Appeal held that reimbursements set through a shared pricing algorithm can be challenged as price-fixing under the Cartwright Act, the state's main antitrust law. The ruling revives an antitrust case against MultiPlan and reaches well beyond healthcare, to any business that prices through a third-party algorithm fed by competitors' data.
If your company sets prices with help from a third-party algorithm, one that quietly runs on data pooled from your competitors, the setup can feel like nothing more than smart operations. But California’s First District Court of Appeal just looked at an arrangement like that and gave it a different name. The name was price-fixing.
The decision is VHS Liquidating Trust v. MultiPlan Corp., and while it arises in healthcare, the principle it sets down reaches any business that outsources pricing to a shared algorithm. The court held that payments set through that kind of algorithm can be attacked under California’s antitrust law. It didn’t decide whether the defendant actually broke the law. It decided the claim gets to move forward, and for a company on the receiving end of a lawsuit, that is often the whole ballgame.
The Scheme the Court Was Looking At
The plaintiff was the bankruptcy liquidator for Verity Health System, a group of six nonprofit hospitals that went bankrupt in 2018. It sued MultiPlan, now called Claritev, a data and analytics company that offers insurers a service called “repricing.” Here is how the complaint describes it. Insurers send their out-of-network claims, meaning claims for care from a provider that has no contract with the patient’s insurer, to MultiPlan. MultiPlan runs them through a proprietary algorithm built on a database of one billion claims drawn from more than 700 insurers, then tells each insurer how much to pay. By 2020, it was repricing 370,000 claims a day. Insurers accepted the recommended number 87 percent of the time without any human touch, and for inpatient care providers accepted the repriced amount up to 99.4 percent of the time.
The liquidator’s theory was a classic hub-and-spoke conspiracy, meaning a central player coordinates otherwise-competing businesses. MultiPlan sat at the hub, collected each insurer’s competitively sensitive claims data, and assured every insurer that its rivals were all following the same suppressed rates. The result, the complaint alleged, was reimbursement set by collusion rather than by competition.
Why “It’s Just a Reimbursement” Didn’t Work
The trial court threw the case out on a demurrer, a motion that argues a complaint fails to state a valid claim even if every fact in it is true. Its reasoning was that an out-of-network reimbursement is “part and parcel” of an insurance policy, so there is no standalone price to fix under the Cartwright Act.
The Court of Appeal reversed. Price-fixing is a per se violation, which means it is treated as automatically illegal without a court weighing its competitive effects, and the Cartwright Act reaches services and applies to buyers just as it does to sellers. There is, the court stressed, a heavy presumption against reading exemptions into the statute that the Legislature never wrote. A single payment can be two things at once. It can be an insurance benefit the insurer owes its subscriber, and it can also be a price for medical services that an algorithm is dictating. The court compared it to a general contractor who owes a homeowner a finished house and then hires subcontractors. The duty to the homeowner doesn’t strip the subcontractor deals of antitrust protection. The same logic applied here, and the court noted that even under narrower federal law it would reach the same result.
One more detail matters for the road ahead. The Legislature recently added a provision making it unlawful to use a common pricing algorithm as part of a conspiracy to restrain trade. That statute didn’t control this case, yet it points in the same direction the court did.
What This Means for Businesses That Use Pricing Algorithms
The healthcare facts are almost beside the point. The transferable lesson is that feeding competitor data into a shared pricing tool, and then moving in lockstep with the number it produces, can expose a company to antitrust liability in California. It doesn’t matter whether you are the buyer or the seller. It doesn’t matter that a vendor, not you, runs the model. If the practical effect is that competitors coordinate prices through a common intermediary, the conduct is exposed.
For any business using dynamic pricing software, rent-setting tools, or industry data cooperatives, now is the time to ask how the tool works, what data feeds it, and whether the output reflects independent judgment or coordinated behavior. In-house counsel should be reviewing those vendor relationships before a plaintiff does it for them.
The Bottom Line
VHS Liquidating Trust v. MultiPlan Corp. doesn’t declare anyone guilty. What it does is refuse to let an algorithm launder coordinated pricing into something that sounds harmless. Companies that rely on shared pricing tools should treat this decision as a prompt to audit those arrangements now, while the review is a planning exercise and not a litigation emergency. Antitrust exposure, algorithmic pricing, and the defense of business disputes are central to Horst Legal Counsel’s practice. If you want to understand how this decision affects your pricing practices or your risk, we are glad to talk it through. Contact us here.