Podcast Short 1:24 September 1, 2026From Season 2, Episode 5

Why People and Process Must Come Before Technology in Denial Prevention

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Tami McMasters Gomez·Executive Director of Mid-Revenue Cycle, UC Davis Health
In this clip

Tami McMasters Gomez describes how UC Davis Health built its denial prevention infrastructure before evaluating technology. Patient access, mid-cycle, and back-end teams are coordinated through a cross-functional group called the Write-Off Avoidance and Denials Avoidance Task Force, which meets regularly to review documentation schemas and denial reasons, routing cases to the right work queues. With the people-and-process foundation established, the organization is now interviewing vendors to determine which technology fits best on top of that infrastructure, rather than selecting technology first and building process around it afterward.

Key Takeaway

The most effective approach to denial prevention AI starts with people and process, not the other way around. Organizations that close upstream gaps, establish cross-functional collaboration, and define denial ownership before evaluating vendors are better positioned to identify what they actually need and achieve real ROI from technology adoption.

“We plugged the gaps upstream with people and process. Now that we have all of these things in place, the question is what technology are we hoping to adopt and what are we hoping to achieve.”

Tami McMasters Gomez, Executive Director of Mid-Revenue Cycle, UC Davis Health

Claims Denial ManagementLeadership
From the full episode

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Tami McMasters Gomez
Season 2 · Episode 5 · 37 min

Denials Prevention at the Source: Autonomous Coding, CDI, and AI Governance in the Mid-Revenue Cycle

Tami McMasters Gomez · Executive Director of Mid-Revenue Cycle, UC Davis Health

Tami McMasters Gomez describes how she leads the mid-revenue cycle at UC Davis Health as a proactive control point focused on denials prevention at the source, stopping revenue loss before claims are ever coded or dropped. She explains the framework she uses to anchor priorities around authorization accuracy, real-time clinical documentation integrity, and upstream claims denial management, and describes the bold decision to discontinue the CDI and coding reconciliation process, which drove a 33 percent increase in productivity alongside coding accuracy near 99.9 percent. The conversation covers two active autonomous coding implementations across radiology and outpatient evaluation and management coding, the human-in-the-loop quality assurance model that governs AI accuracy thresholds and direct-to-bill decisions, and the write-off avoidance task force she built to create cross-functional alignment among patient access, clinical, mid-cycle, and back-end teams. Tami also shares her perspective on where agentic AI will create transformational impact in the mid-revenue cycle through denials management automation and embedded clinical workflow intelligence, the governance challenges introduced by California legislation restricting AI in clinical decision-making, and the leadership philosophy she draws from trust-based relationships and empathic change management.

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