Artificial intelligence is now embedded across health insurance and care delivery operations, but Aetna’s chief medical officer says the industry still has a choice in what it does with the technology, even if early results aren’t encouraging.
“AI opens the door to move at a speed and with a level of clinical engagement that’s really differentiated,” Ben Kornitzer, MD, said this month on the Becker’s Healthcare podcast. “On the other hand, there’s a risk that AI will just industrialize all those parts of healthcare that are most inefficient and most adversarial.”
Dr. Kornitzer, a primary care physician who spent years making house calls to homebound seniors in New York City, joined CVS Health’s insurance arm last year. He previously served as chief medical officer at Agilon Health, a primary care company serving Medicare Advantage patients, and before that held the same position at the Mount Sinai Health Network.
“Some of the early data out there, when looking at the impact of AI so far, shows it’s been largely inflationary,” he said. “We see that with coding intensity, but there’s no real strong evidence that people are getting different clinical outcomes.”
For the better part of two years, other major insurers, including Elevance Health, Cigna and Centene have also been flagging what they describe as “aggressive provider coding” as a growing concern, a reference to the growing adoption of AI-based documentation and coding tools across the industry. In turn, health systems have argued that higher-acuity documentation reflects a sicker patient population and stricter compliance with coding standards rather than an effort to inflate costs, along with an effort to keep up with constantly evolving claims edits, rules and bulletins set by insurers.
But instead of treating AI as a new weapon to continue fighting decades-old structural problems, Dr. Kornitzer argued the industry should reframe the question entirely.
“Rather than think about this as an agentic bot war, if you will, between the inflationary and deflationary influences on providers and payers, we should really step back and ask how we can use it to improve what clinicians are doing,” he said.
He pointed to giving clinicians the ability to go through thousands of pages of documents and figure out what conditions a member has or what’s affecting a certain population, surface those risks or care gaps to the relevant party, and help to make sure patients are on the right medications. Within Aetna, he said the technology is saving nurses time during clinical reviews, which they can then spend with the highest-risk members and help them better access the right resources.
Dr. Kornitzer also pointed to gains in prior authorization, the process at the center of much of the industry’s AI scrutiny. This year, Aetna said it has standardized 88% of its overall prior authorization volume and now approves more than 95% of eligible requests within 24 hours. The insurer has also moved into bundled, condition-specific reviews for areas like musculoskeletal care and cancer.
“In a perfect world, the prior authorization process would be almost invisible. It’d be working in the background,” Dr. Kornitzer said. “There would be interoperable, bidirectional data, and we’d be able to think through what outcomes are going to really put our members in the best position.”
You can listen to the full podcast episode with Dr. Kornitzer here.
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