How to Improve Revenue Cycle Management? Fix the Middle First

Healthcare generates trillions of dollars annually, yet many hospitals struggle to post positive operating margins. Nearly half of hospitals report more than $100 million tied up in claims older than six months, as denial rates climb and staffing shortages persist.

If you’re a revenue cycle leader, you already know this pressure. You need to collect more revenue, faster, with fewer and fewer resources. So when you understandably ask how to improve revenue cycle management, the answer starts in a place that doesn't always get the attention it deserves: medical coding.

Why Does the Mid-Cycle Hold the Key to RCM Performance?

What is the revenue cycle in healthcare, exactly? You can think of it as a three-phase process. Front-end operations entail eligibility verification and prior authorization. Back-end processes involve managing denials, appeals, and collections. But the mid-cycle, where clinical documentation is turned into billable codes, determines whether your organization actually gets paid for the care delivered.

Here’s why this matters. The revenue cycle management workflow depends on this translation layer, and coding controls more than most people realize:

• Coding accuracy dictates reimbursement amounts
• Coding speed impacts claim velocity
• Coding adherence to payer rules determines whether payers approve or reject

This is why so many revenue cycle management improvement efforts stall. Maybe your organization has even tried to improve things at either end of the process while the root cause sits in the middle.

What Does Inefficient Coding Actually Cost?

Let’s talk about what inefficient coding costs organizations. Take denials. Are they eating into your organization’s margins? If so, you aren’t alone.

Nearly 15% of claims are initially denied by payers. More than half are eventually paid after an appeal process, but each reworked claim costs $43 or more in administrative labor. Scale that across thousands of encounters, and you can see how quickly the losses compound. 

Every denial delays payments, slowing cash flow and hampering financial forecasting. Inconsistent coding also invites payer audits and regulatory scrutiny.

Providers shoulder part of this burden, too. They spend over 15 hours a week on administrative tasks like coding and answering coding queries. That's time your highest-paid, most specialized staff are spending on work that doesn't require their expertise.

And then there’s the volume problem. In ambulatory settings, coders touch roughly 30% of charts according to Arintra’s internal data. The remaining 70% go straight to billing with only provider input. That’s a lot of unchecked territory where revenue leaks and compliance risks hide.

Why Do Traditional Fixes Fall Short?

Your organization may have tried several approaches to these challenges already. But it’s likely that they didn’t scale effectively.

Hiring more coders sounds logical, but here’s what you’re up against: 

• Revenue cycle leaders rank coders as the most difficult RCM role to fill
• Training requires hundreds or thousands of hours
• Even fully staffed teams struggle with growing chart volumes

Outsourcing creates its own problems. When third-party vendors move coding outside your organization, you lose oversight for quality and compliance.

Computer-assisted coding (CAC) tools emerged in the 1990s as a possible solution. These tools suggest codes based on clinical documentation. But CAC still requires a human to review every single decision. It helps coders work faster, but the fundamental capacity problem still isn’t resolved.

How Does GenAI Redefine RCM Efficiency?

The technology has finally caught up to the need. AI in revenue cycle management now does more than suggest codes for human review. GenAI-native autonomous medical coding solutions like Arintra can: 

• Handle charts independently
• Maintain compliance 
• Generate audit-ready documentation 
• Interpret clinical context
• Apply payer-specific rules
• Assign codes in minutes

Complex cases are automatically routed to human coders with specific guidance on what needs review, while routine encounters go directly to billing. This is what genuine revenue cycle automation looks like.

What does this mean for your team’s work? The best solutions integrate natively with EHR platforms like Epic and Athena so that providers can continue documenting in their familiar workflows. Coding happens in the background with no interface changes, and you don’t have to worry about data extraction causing integrity risks.

This approach to revenue cycle management optimization delivers measurable results. In practice, this translates to faster cash flow, clearer financial visibility, better compliance, lower provider burden, and your coders working at the top of their license.

What Results Can You Expect?

The proof is in what Arintra customers are seeing.

Mercyhealth, a multi-regional health system processing over 130,000 claims monthly, achieved a 5.1% revenue uplift after deploying Arintra’s GenAI-powered coding. Work queue aging dropped by half, and denials fell 43%.

Across Arintra's customer base, the pattern holds: 12% reduction in A/R days, 43% fewer denials on automated claims, and significant cost savings as organizations handle higher chart volumes without expanding headcount. 

What Are Some Practical Ways to Improve Your Revenue Cycle Management?

So where should you start? Revenue cycle management strategies work best when they target high-impact interventions. Here’s a five-step approach that we’ve seen work:

1. Audit your coding workflows first. Identify where charts sit waiting for review. Map the blind spots where documentation isn’t reviewed by professional coders. Quantify the denial patterns that trace back to coding errors. You can’t fix what you can’t see.

2. Automate your mid-cycle. Adopt autonomous coding to handle routine encounters at scale. This removes the bottleneck that constrains everything downstream.

3. Empower your coders for strategic work. When automation handles volume, coders can focus on complex cases, clinical documentation improvement, and denial analysis. 

4. Strengthen your providers’ clinical documentation. Use AI-driven coding feedback to identify gaps before they become costly denials. Targeted, provider-specific guidance creates lasting behavior changes.

5. Choose native EHR integration. Solutions embedded within Epic or Athena minimize IT burden and preserve your provider’s existing workflows. 

This framework improves revenue cycle management in medical billing by fixing issues at the source, not after they've shown up downstream.

The Bottom Line: Coding is the Leverage Point

Here's what it comes down to. The answer to how to improve revenue cycle management isn't more staff, more systems, or more complexity. It's fixing the function that determines whether you get paid.

GenAI automation makes that possible through accurate reimbursement, compliant coding, relief from provider burnout, and measurable return on investment. That's why the future of revenue cycle management belongs to organizations that recognize coding as strategic infrastructure.

The path to stronger margins runs through the mid-cycle. If you automate coding today, your organization won’t be scrambling to fix revenue leakage later.

Ready to see what this looks like for your organization? Learn how Arintra helps health systems achieve 5.1% revenue uplift and 43% fewer denials. Book a demo.