Hospitals and health systems are under increasing pressure to maintain coding accuracy, compliance, and audit readiness within their radiology departments—all while facing staffing shortages, growing imaging volumes, and evolving payer scrutiny. As automation becomes essential rather than optional, the question is no longer if AI should play a role—but how it can be trusted in radiology coding operations.
In this Office Hours session, we’ll explore how AI-driven coding is addressing the unique challenges hospital radiology teams face, from chargemaster dependencies and manual diagnosis coding to compliance and medical necessity risks. Joined by Stacie Buck, Director of Coding Compliance at Maverick Medical AI, we’ll discuss how autonomous coding is evolving to meet these demands—helping hospitals improve accuracy, reduce administrative burden, and build coder confidence while maintaining full oversight and control.
Learning Objectives:
- Identify the top challenges hospitals face in radiology revenue cycle management that make automation essential.
- Understand why traditional chargemaster and order-based coding models fall short in complex imaging environments.
- Explore compliance and medical necessity risks tied to manual and EHR-assigned diagnosis codes.
- Learn how autonomous coding supports quality, transparency, and coder confidence in radiology.
- Examine how hospital attitudes toward AI in radiology coding are evolving as trust and maturity grow.
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