Revenue Cycle Optimized

Eligibility errors, missing documentation, and prior authorization gaps may seem small in the moment, but they quietly erode cash flow, inflate AR, and drive avoidable denials. In this episode, we break down why front-end breakdowns still matter most and how AI can either strengthen your foundation or expose the cracks in it.

In this episode, Jonathan Aguiar, Senior Solutions Engineer, walks through prior authorization verification and demonstrates how the Follow Up AI agent works within the workflow. You will see how cases move through entry and validation, triage, payer review, pending initiation outreach, exception handling, and final status. Learn how automation and human expertise work together to deliver real time visibility, reduce cancellations, and accelerate scheduling.

Brought to you by www.infinx.com

E&M coding can look routine, but it quickly becomes a judgment-heavy exercise driven by documentation quality, medical necessity, payer policy, and audit risk. Julie Graham and Bo Bowman explain where autonomous coding and AI agents thrive in repeatable workflows, and why complex E&M decisions still need expert human review and provider education to stay compliant and fully reimbursed.

Denials are often blamed on payers or staffing shortages, but the true root causes usually begin much earlier in the workflow. This segment explores how diagnosing denials correctly allows AI to move from reactive appeals to proactive prevention and measurable financial improvement.

In this episode, Natalia Arzeno-Gonzalez, Chief Data Scientist at Infinx, helps revenue cycle leaders cut through the noise by setting realistic expectations for AI in RCM. The discussion explores what AI does well today, where it falls short, and why data readiness, workflow maturity, and integration matter more than buzzwords.

Brought to you by www.infinx.com

Even high-performing hospitals leave revenue on the table due to complexity, outdated charging methodologies, and process blind spots. In this episode, Anthony Amaya explains how disciplined charge capture optimization can deliver a measurable one to four percent net revenue lift without adding volume or increasing costs.

As AI becomes embedded into revenue cycle workflows, accountability can no longer be treated as a black box owned by technology. This episode explores how leaders should set expectations, measure outcomes, and stay responsible for results even as automation scales.

This episode, recorded live from the Oregon HFMA Winter Conference, reflects on how change shows up across healthcare revenue cycle operations and how augmented intelligence has become a recurring thread connecting those experiences. We’ll explore why some parts of healthcare evolve quickly while others resist change, and what that means for the people navigating it every day.

Brought to you by www.infinx.com

In this episode of Revenue Cycle Optimized, Jennifer Glockzin, Senior Director of Patient Access at Infinx, walks through the real-world prior authorization process from intake to determination and appeals. Her breakdown highlights how disciplined workflows, supported by AI agent automation and coordinated human in-the-loop, protect revenue and reduce preventable denials.

When leaders ask “Why AI?” in revenue cycle, they’re often reacting to growing complexity, staffing pressure, and loss of control rather than chasing innovation. This segment reframes the AI conversation around stability, predictability, and restoring confidence in day-to-day operations.