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Revenue Cycle Automation Has Earned Its Place in the CFO's Playbook

December 29, 2025

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An estimated 5 trillion dollars flowed through the U.S. healthcare system this year, but almost 40% of hospitals still lost money. Cash reserves have hit a 10-year low. Something in the revenue cycle is clearly not working. This financial strain jeopardizes both balance sheets and the quality of care that hospitals deliver to patients every day.

Manual revenue cycle management processes are buckling under the weight of coder shortages, intense payer scrutiny, rising denial rates, and growing chart volumes. Revenue cycle automation offers a way out of this financial morass.

The Pressure Points in Today's Revenue Cycle

What is the revenue cycle in healthcare, exactly? It covers three stages: front-end operations (registration through prior auth), mid-cycle functions (documentation and coding), and back-end processes (billing through collections). The revenue cycle management workflow spans all three, and problems compound across each stage.

Consider these numbers; they paint a vivid picture of the revenue cycle management challenges that hospitals face today. One survey found that payers initially reject roughly 15% of submitted claims. Another survey indicates that half of hospitals have more than $100 million tied up in claims that have aged past six months. At the same time, coders top the list of hardest-to-fill revenue cycle roles for more than a third of medical groups.

Changes in the payer space have added another layer of difficulty. Many now use AI tools to adjudicate claims, and 61% of physicians worry that these automated systems are raising denial rates. Health systems now assume that payers are going to contest a significant portion of every dollar billed.

When denied claims do get appealed, over half are eventually overturned. But reworking each denial costs anywhere from $25 to $181, delays payment, and pulls staff away from higher-value work. Around 60% of denials never get appealed at all, so that revenue simply vanishes.

What Revenue Cycle Automation Really Means?

Automation frees staff from repetitive tasks that don't need a human touch. The relationship between coding and revenue cycle management is central here, as medical coding and denials management represent the highest-impact areas for automation. This distinction matters when comparing medical billing vs revenue cycle management.

Billing is an important component, but coding drives what gets billed, how quickly it gets billed, and how much delivered care gets reimbursed for. When coding is slow, claims sit. When coding is inaccurate, claims get denied. And with coders in short supply, most health systems can't review every chart manually, which is why coding tools are so central to this discussion.

Computer-assisted coding (CAC) tools emerged in the 1990s. They suggest codes based on clinical documentation, but aren’t good with unstructured text and still need a coder’s eyes on every chart. Their recommendations lack transparency, making audits and denial appeals difficult.

Autonomous coding tools are something completely different. This technology can:

Code the majority of charts without human oversight
Decipher unstructured clinical narratives
Apply payer-specific rules
Generate clear explanations tied to clinical documentation for every decision

The latest generation of autonomous coding solutions, built using generative AI and large language models, handles complexity with greater accuracy. They adapt faster to new requirements and can scale across diverse care settings.

The Financial Impact of Automating the Revenue Cycle

Mercyhealth, a multi-regional health system serving 55 communities across northern Illinois and southern Wisconsin, processes more than 130,000 patient claims monthly. The organization was struggling with the growing gap between chart volume and coder capacity. In ambulatory care, their coding team could only review about 30% of charts. The remaining charts were sent straight to billing with little oversight.

After the evaluation process, Mercyhealth chose Arintra's GenAI-powered solution for its accuracy, native Epic integration, transparency, and minimal workflow changes. They launched autonomous coding in primary care and quickly expanded to urgent care, pediatrics, radiology, and more. The results of Mercyhealth’s healthcare revenue cycle automation speak for themselves:

88% of charts now go direct-to-billing
Revenue increased 5.1%
Work queue aging was cut in half
112,000+ charts processed in five months
The equivalent of 8 FTEs of coding capacity

Every coding decision includes a clear, explainable trail, reducing the audit burden and giving revenue cycle teams the documentation they need to challenge denials effectively.

"Arintra frees up my highly skilled team to focus on complex cases and revenue integrity projects, bringing greater value to the organization," says Kelly Pierson, Mercyhealth's Director of Coding.

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The goals of revenue cycle management are straightforward. Hospitals need to get paid accurately, quickly, and compliantly. Automation makes all three possible at scale.

Beyond Efficiency: The Strategic Value

Revenue cycle automation pays off in ways that don’t immediately show up on a dashboard. Clinical documentation gets better over time as autonomous coding flags gaps and gives providers concrete, financially relevant feedback. This creates credibility and urgency, making it easier for physicians to improve their notes over time.

Physician experience improves, too, as fewer administrative tasks reduce burnout and "pajama time," the after-hours documentation work that drains providers.

Scalability also becomes possible. Automated coding can adjust dynamically to handle chart volume fluctuations, new specialties, and changes in payer requirements. This matters, as outpatient volumes are projected to grow 18% over the next decade, compared to just 5% for inpatient care.

In a challenging reimbursement environment, automated revenue cycle functions like coding create predictability and give CFOs the visibility they need for revenue cycle management optimization.

How to Get Started?

How can an organization improve its revenue cycle management? Organizations considering revenue cycle automation should begin the process with an honest assessment of their readiness. Here’s a five-question framework illustrating the key factors, which include:

Provider volume
EHR integration capabilities
Hosting model
In-house coding capacity
Specialty mix

Best practices in revenue cycle management include the following: start in an area where automation delivers the most immediate ROI, which is usually in high-volume, lower-dollar specialties like primary care and radiology. Prioritize solutions capable of integrating directly into your EHR. Native integration with systems like Epic or Athena means no data extraction, no separate interfaces, and no disruption to your teams' workflows.

Involve your coding team in the automation process early. Position automation as a way to elevate their expertise, not replace it. Coders freed from spending their days processing routine charts can focus on complex cases, CDI initiatives, and revenue integrity work. This strategy can help organizations understand how to improve revenue cycle management without alienating the staff who know it best.

Moving Beyond Survival to Sustainable Growth

Revenue cycle automation has earned a place in every CFO's playbook. The results–faster revenue recognition, fewer denials, measurable ROI, and improved documentation–are hard to argue with. As generative AI matures, expect automation to impact the process upstream by catching denials before they happen and giving finance teams real-time revenue assurance. This is the future of revenue cycle management.

Health systems that adopt revenue cycle automation position themselves for sustainable growth. Those that don't will keep fighting the same financial battles with diminishing resources and thinner margins.