Revenue Cycle Optimized

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Even high-performing hospitals leave revenue on the table due to complexity, outdated charging methodologies, and process blind spots.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 ww...

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.

In this episode, Jaideep Tandon, CEO of Infinx, shares a sensible, leadership-driven perspective on the evolving role of AI in RCM. Rather than focusing on technology for technology’s sake, the conversation centers on outcomes: improving efficiency, reducing revenue leakage, and supporting better financial decision-making across increasingly complex healthcare environments. Jaideep addresses how r...

In this segment from What’s My Tagline? with host Carol Flagg, Stuart Newsome discusses why AI messaging in healthcare is hitting a wall and how skepticism is forcing a shift toward outcomes-based positioning. The conversation explores what revenue cycle leaders actually care about in 2026 — trust, specificity, governance, and real operational impact.

AI agents create the most value in revenue cycle workflows when they operate as a coordinated system rather than isolated tools. This episode explores how multi-agent orchestration combined with a tech-enabled human layer delivers reliability, accountability, and real operational outcomes in RCM.

EMR upgrades, clearinghouse changes, and AI are reshaping revenue cycle operations, but they can also disrupt cash flow if not carefully managed. This episode focuses on maintaining revenue continuity during system transitions, highlighting where delays commonly occur, how AI fits into modern workflows, and what operational safeguards help ensure revenue continues to flow through change. Brought t...

In this episode, Navaneeth Nair, Chief Product Officer at Infinx, explains what it really takes to make AI work in revenue cycle management, from decomposing workflows into task-level agents to maintaining human-in-the-loop oversight. The conversation explores why effective RCM automation depends on orchestration, agent lifecycle management, and tech-enabled workflows designed for real operational...

In this RCMinutes episode of the Revenue Cycle Optimized podcast, we unpack what healthcare teams truly trust about AI, and what still makes them hesitate. Drawing from real conversations with providers, this episode explores why reliability, transparency, and workflow alignment matter more than flashy automation.

AI can extract data from documents—but making that data usable, reliable, and scalable is where most efforts fall apart. In this episode, Charu Nevatia explores why AI document capture isn’t plug and play and what it really takes to operationalize it in healthcare. Brought to you by www.infinx.com

Ambulatory and acute care billing share many of the same building blocks, but the way data, workflows, and reimbursement are structured creates very different operational realities. In this episode, we explore how those differences shape not only revenue cycle strategy, but also how automation and AI should be applied effectively with these considerations across care settings.

Healthcare’s cautious approach to AI isn’t resistance to innovation, it’s a response to real operational, clinical, and financial risk. In this episode, we unpack why moving slowly is often the smartest move, and how intentional adoption builds trust, safety, and long-term value.

As payors increasingly use AI to review documentation and accelerate denials, radiology practices must adapt. This session explores how stronger documentation, AI-supported workflows, and proactive compliance strategies can reduce preventable denials and protect revenue in an evolving payer landscape. Brought to you by www.infinx.com

Many rendering healthcare organizations aren’t responsible for initiating prior authorizations, but they are still accountable for verifying them before care is delivered if they want to get paid. In this episode, we break down why follow-up verification has become its own critical workflow, especially for radiology, labs, and referral-driven specialties.

As healthcare organizations adopt AI across the revenue cycle, skepticism often centers on risk and trust. In this episode, we unpack why AI itself isn’t the problem, bad data is, and why protecting downstream systems starts with data integrity, not more sophisticated algorithms.

Faxes still sit at the center of referrals, orders, and authorizations by quietly slowing care, overwhelming staff, and delaying revenue. In this live demo, Stuart Newsome and Jonathan Aguiar show how AI agents transform document intake from a manual bottleneck into a reliable, scalable foundation for revenue performance. Brought to you by www.infinx.com

In this episode of Revenue Cycle Optimized, Charu Navatia and Neelam Yadav walk through how Document Capture AI evolved into Document Capture Plus, a scalable platform built for real-world healthcare workflows. From intelligent AI agents and human-in-the-loop design to enterprise integrations and compliance readiness, this conversation shows how document automation is moving from task support to t...

In 2025, AI made it easy for Health IT teams to scale content, but it also created noise, saturation, and growing buyer skepticism. In 2026, AI agents will matter most when they help close the trust gap by delivering practical outcome-driven impact, respects time, and reduces risk.

Best of Office Hours 2025 - In this episode, Infinx CEO Jaideep Tandon breaks down why automation alone can’t keep up with today’s revenue cycle complexity—and why AI must move beyond task execution to contextual thinking, prediction, and adaptation. From denial prevention and prior authorization to AR prioritization, this conversation explores how AI, automation, and human expertise must work tog...

Prior authorization and eligibility verification in therapy and rehab are shaped by payer urgency, visit limits, and fragmented automation. In this episode, we explore what it takes to manage these workflows at scale by combining payer-aware automation, human follow-through, and system integration to deliver complete, usable outcomes without shifting work back to internal teams.

As 2025 comes to a close, healthcare organizations are looking ahead with a mix of skepticism, hope, and fatigue. In this episode, we share grounded predictions for 2026 based on what teams told us all year. And that is where AI can truly help, where humans must stay involved, and how confidence and trust will matter more than hype.