Join us as we explore the latest challenges, developments and innovations in the healthcare revenue cycle space. Don't forget to subscribe to get alerted when a new episode is uploaded.

A/R is familiar territory for revenue cycle leaders, but the way it is managed determines whether teams are simply tracking unpaid claims or actively moving them toward resolution. This RCMinutes episode reframes A/R as an operational discipline built around follow-up, prioritization, denials, underpayments, patient responsibility, and the decisions that protect cash flow.

Healthcare revenue cycle has relied on rules engines, manual workflows, and brittle automation for decades. In this episode, Monte Sandler, Chief Operating Officer at WebPT, joins Stuart Newsome to discuss why AI may finally give RCM teams a way to manage complexity more dynamically while keeping human expertise at the center.Brought to you by www.infinx.com

Prior authorization and eligibility verification remain too variable, payer-specific, and operationally complex to rely on automation alone. In this episode, David Byrd and Navaneeth Nair explain how Infinx Patient Access Plus orchestrates AI agents, automation, payer connectivity, analytics, and human expertise to reduce administrative burden and keep care moving.

This RCMinutes segment reframes prior authorization as more than a portal or paperwork problem — it is a data problem that affects access, scheduling, patient trust, and revenue. The episode explores why clean data, intelligent automation, and human oversight are essential to moving from reactive authorization chasing to proactive access management.

Same-day cancellations, delayed procedures, and scheduling disruption can create major strain for orthopedic practices. In this Office Hours Takeover, Lora Pada, VP of Customer Success at Infinx, speaks with Danelle Newman, Director of Patient Access at OSS Health, about the role prior authorization workflows play in keeping schedules moving, reducing preventable delays, and giving patient access teams more breathing room.Brought to you by www.infinx.com

Revenue cycle teams are often judged by how fast they react to problems, but the real opportunity is catching issues before they become urgent. This RCMinutes segment explores how better signals, cleaner prioritization, and smarter workflows can help teams move from constant firefighting to more predictable performance.

AI is changing more than speed and efficiency. It is changing who gets to contribute. In this Office Hours roundtable, the panel explores how everyday users are using AI to shape work, solve problems, and support better decisions in ways that matter for revenue cycle leaders.

Scott Cook, VP of Business Development for Acute Care at Infinx, explains how charge capture assessments can help hospitals identify missed revenue opportunities while strengthening documentation, education, and operational consistency. He also discusses why data alone is not enough, and how combining analytics with staff conversations can uncover practical improvements across departments like surgery, radiology, emergency care, anesthesia, and PT/OT.

AI can help revenue cycle teams improve consistency across shifts, locations, and workflows by reducing unnecessary variation in how work gets prioritized, documented, and escalated. In this episode, we explore how AI acts as a quality stabilizer, giving teams more reliable support without removing the human judgment complex revenue cycle work still requires.

Patient financial responsibility keeps growing, but a better financial experience does not start after the bill goes out. In this Office Hours session, Stuart Newsome and Evan Martin, VP Revenue Cycle at ZoomCare, discuss how upfront insurance verification, patient liability estimation, and clearer payment pathways can reduce friction for both patients and providers.Brought to you by www.infinx.com

Lindsey Nelson, Product Marketing Leader at Infinx, explains how Infinx is bringing Medical Necessity AI Agent to market through a phased launch shaped by research, beta feedback, and early customer evaluation. She also outlines what makes the solution different from rules-based tools, including explainable clinical reasoning that helps teams assess coverage earlier and prevent denials before submission.

Burnout in revenue cycle is not just a staffing problem. In this episode of RCMinutes, we explore how AI can reduce administrative strain, lower emotional pressure on teams, and create a more sustainable revenue cycle operation without framing automation as a headcount reduction strategy.

Payers are taking a closer look at E&M claims, and providers are feeling the impact. This session explores what is changing, why it matters, and what organizations can do to respond.Brought to you by www.infinx.com

AI in revenue cycle is not just about automation. In this RCMinutes episode of the Revenue Cycle Optimized podcast, we explore how AI-powered decision support helps revenue cycle teams prioritize work, reduce second-guessing, improve denial management, and make faster, more confident operational decisions.

Listen to how RCM Plus uses AI to predict denial recoverability, prioritize work by expected reimbursement, and orchestrate human teams around the claims most worth pursuing.Brought to you by www.infinx.com

Medical necessity review is getting harder as payer policies change more often and AI allows health plans to evaluate cases at greater speed and scale. In this episode, Navaneeth Nair explains why older rules-based tools could not fully solve the problem and how a new AI approach can help providers assess unstructured documentation, preserve scarce expertise, and prevent denials earlier in the revenue cycle.

AI and automation in revenue cycle mean very little without measurable outcomes to back them up. This episode explores why the real goal is relief from staffing strain, administrative burden, and constant rework, and why outcomes are the proof that progress is actually happening.

Long term care pharmacy billing is uniquely complex, shaped by changing patient status, payer transitions, and facility-specific requirements that do not exist in other pharmacy settings. In this episode, Derek Taylor, PharmD, explores the billing challenges that define LTC pharmacy operations and shares practical strategies for improving accuracy, efficiency, and financial performance.Brought to you by www.infinx.com

Prior authorization has changed dramatically over the last decade, but not every solution has evolved in the same way. In this episode, Jason Lewis explores the history of prior authorization automation and helps healthcare leaders understand the models, gaps, and realities behind today's competitive landscape.

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.Brought to you by www.infinx.com

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.Brought to you by www.infinx.com

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.Brought to you by www.infinx.com

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.Brought to you by www.infinx.com

Pharmacy prior authorization is far more complex than most teams realize, especially across long-term care, specialty, compounding, and infusion environments. In this episode, Derek Taylor explains how those workflows really function, where the operational friction lives, and why getting the process right is critical to faster medication access and cleaner coordination between pharmacies, payers, and prescribers.

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.

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 revenue cycle leaders can play a more active role in shaping AI success with a clearer understanding of how to evaluate AI initiatives, set realistic expectations, and lead AI adoption as an ongoing journey.Brought to you by www.infinx.com

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 to you by www.infinx.com

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 complexity.

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.