AI success in revenue cycle rarely comes from a single implementation or vendor promise. This segment explores how leaders should evaluate partial wins, guide use cases, and actively shape AI outcomes instead of reacting to market hype.

Independent radiology centers face growing competition from hospital systems, where speed to schedule and authorization turnaround directly impact patient access and referral retention. In this episode, Heidi Simpson, Operations Manager at Advanced Diagnostic Radiology, shares how leveraging prior authorization services as a strategic advantage has helped her organization compete, grow, and modernize operations—while maintaining a patient-first approach.

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In this episode, Stephanie Cheng, Associate Director of Client Success, explains why eligibility and benefits verification in the physical therapy space still requires more than automation alone. She walks through how a hybrid model of payer integrations, workflow technology, and human support can help organizations scale, reduce bottlenecks, and improve visibility across patient access workflows.

Efficiency is often framed as eliminating humans from workflows, but that’s rarely realistic or measurable. This episode reframes efficiency as practical, incremental gains that reduce cost to collect, improve throughput, and support staff instead of replacing them.

Everyone is racing to reduce cost to collect by cutting the numerator, cost, through AI and automation. In this episode, Anthony Amaya, VP at Infinx, makes the case that a holistic approach, one that also drives the denominator up by increasing cash, delivers faster, measurable results and positions organizations for sustainable gains as automation continues to mature in healthcare.

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Determining whether documentation truly supports coverage is one of the most complex and costly challenges in revenue cycle today. In this episode, Navaneeth Nair and Yagna Velu discuss the early vision for using AI to strengthen medical necessity review, reduce avoidable denials, and improve decision-making before claims move forward.

Visibility into unpaid claims and time to pay remains a major struggle for revenue cycle leaders. This segment focuses on how AI should support prioritization and clarity without layering on more tools, dashboards, or operational complexity. 

This episode was recorded live from Infinx’s GTM Growth Summit in Denver. Navaneeth Nair, Chief Product Officer, joins us to discuss a new AI-driven approach to medical necessity review. We’ll explore how provider teams can catch coverage gaps earlier, reduce manual policy lookups, and route exception cases to the right human experts before delays and denials take hold.

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In this episode of Revenue Cycle Optimized, we explore how a Charge Capture AI Agent inside the Document Capture Plus platform helps turn unstructured healthcare documents into cleaner, more actionable billing data. Product leaders Neelam Yadav and Jainil Pariya, along with Jamie Campagna from MedReceivables Advisors, discuss how AI, business rules, duplicate detection, and human review work together to reduce manual effort and improve charge capture quality.

E&M coding performance rises or falls on ten predictable breakpoints that drive payment, denials, rework, audits, and compliance risk. Join our panel for a practical discussion on what fixes those breakdowns and how AI supports scalable oversight through pattern detection, documentation review, exception based workflows, and autonomous E&M coding with human specialist exception handling.

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