How AI Coding Lifts HCC Capture Rates
Kimberly Scaccia describes how Mercyhealth addressed physician coding gaps by deploying autonomous and computer-assisted coding AI. Before the implementation, physician-dropped charges left the building without systematic review, creating constant cleanup work. The AI layer caught missing elements before claims went out, driving up HCC capture rates and improving physician satisfaction through faster, more continuous documentation feedback.
Key Takeaway
When autonomous coding AI handles the systematic review of physician-dropped charges, HCC capture rates rise and physician satisfaction improves. The mechanism behind both outcomes is the same: AI reads records continuously and surfaces documentation gaps faster than any manual review, shortening the feedback loop to physicians.
“What a lot of folks don’t realize is that AI is here to help us move our team members to operate at the top of their skill set.”
Kimberly Scaccia, Vice President of Revenue Cycle, TriHealth
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