How AI Shifts Revenue Cycle from Reactive to Proactive with Kimberly Scaccia | Podcast Shorts from ArceeHQ

In this clip

Kimberly Scaccia frames the agentic AI opportunity in revenue cycle as a shift from reactive cleanup to proactive prevention. Revenue cycle operations are still largely organized around chasing problems after they occur: denials, underpayments, missed authorizations, and documentation gaps, with significant back-end remediation effort as a result. AI changes this by identifying documentation issues and payer-specific patterns before they become problems, and by prioritizing work toward dollars at risk rather than static work queues.

Key Takeaway

The traditional revenue cycle operating model spends most of its effort recovering value that was already lost. AI-driven prioritization shifts that effort upstream, catching documentation gaps and flagging payer behaviors before a claim goes out so that revenue is protected rather than recovered after the fact.

“Identifying dollars at risk, not static work queues. That’s where AI can help us prevent that revenue loss instead of just accelerating rework or operating model changes.”
Kimberly Scaccia, Vice President of Revenue Cycle, TriHealth

Agentic AIClaims Denial Management

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Kimberly Scaccia

Season 2 · Episode 4 · 38 min

From Reactive Denials to Proactive Revenue Protection: AI Prioritization and Leadership in Revenue Cycle

Kimberly Scaccia · Vice President of Revenue Cycle, TriHealth

Kim Scaccia shares how she sets strategic priorities at TriHealth under simultaneous pressures from payer delays, regulatory mandates, and staffing constraints, and why sequencing and explicit exclusions matter as much as what gets prioritized. The conversation covers an autonomous and computer-assisted coding initiative she led at Mercyhealth, the importance of phased implementation and psychological safety in surfacing obstacles, and the measurable results: a 5 percent net cash improvement and a 6 to 7 percent increase in HCC capture rates. Kim also discusses the shift from reactive denial management to upstream prevention through agentic AI, the change management framework she uses to build momentum across complex cross-functional teams, and why write-off percentage, not denial rate, is the metric that truly reflects revenue cycle performance.

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The themes our guests cover are the same ones our executive guides and ROI calculators are built around. If this clip resonated, here’s where to take it next.

Claims Denial Management, powered by agentic AI

How ArceeHQ catches denials before they happen, resolves them automatically, and gives your reviewers only the cases that need a human.

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Reducing claim denials with agentic AI

A practical framework for revenue cycle leaders. Covers the operating model shift, what to measure, and where automation actually pays.

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