MEDICAL BILLING GUIDE
How to evaluate AI-assisted claim review
Denial rates are rising, and billing teams are under pressure to catch problems earlier. In Tebra’s 2026 survey, 88% of billing professionals said denial rates increased over the past year, creating more rework across the revenue cycle.
This guide explores how AI-assisted claim review can surface higher-risk claims before submission and give billers the context they need to decide whether action is needed.
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What you’ll learn in the guide
AI-assisted claim review adds a new layer to the billing workflow: visibility into denial risk before a claim goes out. The guide breaks down what that looks like in practice, including:
- How denial-risk prediction helps billers move from reviewing every claim to working by exception
- How a higher-risk claim moves from flag to review to the biller’s final decision
- Where AI-assisted review fits alongside clearinghouse scrubbing, eligibility verification, and existing biller review
- Four criteria for evaluating AI claim review tools: explainability, actionability, control, and workflow fit
- Which metrics can help you measure the impact on denials, rework, payment timing, and staff capacity
