Blue Cross Blue Shield: AI-Assisted Medical Coding Added $1 Billion in Hospital Costs

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Hospitals’ growing use of AI to assign medical billing codes contributed close to $1 billion in extra costs for Blue Cross Blue Shield health plans between 2023 and 2025, according to a new analysis from the insurer’s trade association. 70 percent of the additional cost involved additional diagnoses that did not change patients’ actual care, according to the insurer, which describes the situation as a “clear disconnect between coding and treatment.”

CNBC reports that the Blue Cross Blue Shield Association (BCBSA)  says AI-assisted coding helped drive $942 million in additional costs over that span, much of it from secondary diagnoses that pushed patients into higher-paying reimbursement categories. Medical coders translate procedures and diagnoses into standardized codes used for insurance claims and billing, and the rise in what BCBSA calls “complex coding” lines up with a period when roughly 60 percent of hospital systems adopted AI coding tools.

About 70 percent, or $653 million, of the billing BCBSA flagged involved additional diagnoses that came with no change in a patient’s actual care, according to Luke Chalker, the association’s senior vice president of product and data science. Many of these secondary diagnoses, the BCBSA report said, “may be derived from single laboratory values, making it particularly well suited for detection by AI tools.” Its conclusion: “There is a clear disconnect between coding and treatment.”

Chalker told CNBC that “while multiple factors contribute to coding intensity, the findings suggest AI-enabled coding and documentation tools are playing a role.” He warned the trend has consequences for patients, too: “Those costs can eventually show up in the form of higher premiums and out-of-pocket costs.” Benefits consulting firm Marsh projects the cost per employee for health coverage will rise 8.2 percent on average in 2027, the steepest increase since 2003.

Christopher Whaley, a health economist at Brown University who studies hospital coding, sees it differently: AI isn’t creating new billing incentives, he said, it’s exploiting ones that already exist. The technology is “accelerating, and in some sense making it easier to capture, the existing and underlying billing incentives that are in the system.” He cautioned against assuming the added diagnoses are improper. “In many cases, the diagnoses are legitimate and weren’t captured,” he said. Still, some flagged conditions “clinically just don’t really matter and don’t influence the patient’s care,” even though they can still support higher billing.

The American Hospital Association pushed back hard. A spokesperson told CNBC that “patients today are older and more clinically complex” and that AI tools help providers “appropriately capture their patients’ conditions to aid in care planning.” The group argued that “the BCBSA’s analysis lacks the context needed to meaningfully assess how these tools impact healthcare quality, patient access, or spending.” Then it turned the criticism back on insurers, calling it “particularly troubling to see insurers raising concerns about provider coding while continuing to rely on automated downcoding and denial practices that can impede coverage of medically necessary care, add burden on the workforce, and increase costs through administrative waste.”

Chalker acknowledged that Blue Cross Blue Shield companies use AI in claims review too, but said a human is always in the loop. “Any clinical denial is always reviewed by a qualified human clinician,” he said.

Whaley calls the standoff between hospitals and insurers an “administrative arms race.” Both sides are pouring money into tools that have nothing to do with patient care, he argued: “Whether it’s on the hospital side or the insurer side, these tools and technologies are both very expensive, and also have nothing to do with providing appropriate care to patients.”

Marisa Greenwald, a partner at Oliver Wyman’s Health and Life Sciences practice who advises hospitals and insurers on AI adoption and revenue-cycle management, takes a more mixed view. The technology can ease the load on physicians, she said, giving them “some semblance of work-life balance back,” and AI-assisted documentation can help providers “catch additional acuity and diagnosis components,” improving billing accuracy.

But untangling genuine improvement from everything else is hard, she admitted. “It’s hard to disentangle how much of it is better accuracy,” she said. “There’s always going to be misuse and user error and overcoding.” She doesn’t expect the standoff to cool off either: “The arms race is poised to exacerbate. The hope is going to be that on both sides of the equation, the players recognize that all we’re doing is adding” costs.

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