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HL Shorts: HL Shorts: Why AI Isn't the Answer for Every Denial

Analysis  |  By Luke Gale  
   January 14, 2026

WVU Medicine's revenue cycle leader discusses how AI helps prevent denials, and where basic automation is still the smarter choice.

In this episode of HL Shorts, Beth Carlson, Chief Revenue Cycle Officer at WVU Medicine, explains why AI isn't the right tool for every job. She details why she uses it for complex clinical appeals, but advises leaders to stick to standard software rules for clear-cut billing policies.

 

Luke Gale is the revenue cycle editor for HealthLeaders.


KEY TAKEAWAYS

Carlson points to clinical reviews, like level-of-care downgrades, as the best place for AI, where models can analyze documentation patterns.

For denials based on clear rules, like diagnosis codes, she advises using standard software rather than trying to train an AI model.

The health system uses data from successful appeals to train its AI, helping the tool suggest specific language that is more likely to get a denial overturned.


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