Blog

7 Proven Strategies to Optimize Revenue Cycle Management in 2026

February 10, 2026

In this Article

What does it take to get paid correctly in healthcare right now?

More than it used to. Median health system operating margins have been at nearly 1% throughout the past year. Payers are denying more claims, while coders are in short supply, and providers are spending roughly 15+ hours a week on paperwork. Payer rules keep changing on top of it all.

The health systems making progress on these issues are treating revenue cycle management optimization as a structural priority. Here are seven strategies already producing results.

‍

At a Glance: 7 RCM Optimization Strategies

Prioritize Coding Accuracy

Put simply, medical coding is where revenue is won or lost. If a provider or coder inputs the wrong code, the claim is wrong. If the claim is wrong, you either don’t get paid or you spend time and money fixing it.

Most healthcare organizations don’t have the capacity for a professional coder to work on every chart. In ambulatory care settings, professional coders often process only about 30% of patient charts, according to internal data. The rest go to billing based on provider input alone, which creates gaps where revenue slips through and compliance risks build up.

Organizations seeing the best coding results are investing in:

Quality assurance processes that catch errors before claims go out
Automation that provides explainable, auditable coding decisions
Feedback loops that help providers improve documentation over time

Coding shouldn’t be considered a back-office function anymore. In truth, it’s the foundation of revenue cycle management in medical billing.

Prevent Denials Instead of Chasing Them

Think about how your team deals with denials. How much of that effort goes toward recovering revenue that should have cleared the first time?

Every denied claim costs money twice: once in lost revenue and again in the staff time used to appeal it. A recent Premier report showed that the healthcare industry spent $25.7 billion on claims adjudication in 2023, a 23% increase from the year before. Initial denial rates have also climbed to 11.8% in recent years.

About 70% of denials are ultimately overturned and paid, meaning billions of dollars go toward fighting for revenue that should have cleared the first time.

Most revenue cycle management strategies still treat denials as a back-end problem. The health systems gaining ground are flipping that approach by:

Embedding payer-specific logic into coding workflows before claims go out
Using denial pattern analytics to identify root causes and fix them upstream
Educating providers proactively based on the specific documentation gaps driving rejections

Chasing denials after the fact drains resources you don't have. Preventing them at the source is where you gain ground.

Scale with Autonomous Medical Coding

You probably know this firsthand, but it’s difficult to hire your way out of the coding shortage. Thirty-four percent of medical groups rank coders as their most difficult revenue cycle role to fill. Training takes hundreds or thousands of hours, and even fully staffed teams can't keep pace with rising chart volumes.

GenAI-powered autonomous medical coding solutions like Arintra offer a way forward without adding headcount. These platforms can:

Interpret unstructured clinical narratives with near-human fluency
Assign codes without human review for a majority of encounters
Route complex cases to coders with specific guidance on what needs attention
Generate explainable audit trails tied to clinical documentation

This is revenue cycle automation at the most critical point in the cycle.

‍Strengthen Clinical Documentation Integrity

Even the most accurate coding can only capture what providers document. If a doctor’s clinical notes lack specificity, you’re losing money regardless of how good your coding is. How do you close that gap without adding more work for already overburdened physicians?

Autonomous coding platforms like Arintra deliver provider-specific, encounter-level clinical documentation improvement (CDI) feedback tied directly to financial impact. Instead of your providers getting generic feedback every quarter, they see real-time, actionable guidance inside the EHR.

The payoff includes:

Improved HCC capture
More accurate risk adjustment scoring
Fewer post-payment audits
Catching documentation gaps before they become denials

Organizations that connect CDI to their coding workflows fix problems at the source, not downstream. That's the whole point.

‍Build Audit Readiness Into Coding

If your team has ever scrambled to reconstruct coding logic for a payer challenge, you're not alone.

Traditional audits involve sampling a small batch of charts after claims go out. They catch problems late and generally miss systemic issues. Explainable coding tools work differently:

Every coding decision generates a full audit trail linked to specific clinical documentation
Payer challenges get answered with reasoning already in hand, no reconstruction required
Audits become a continuous quality check

When you audit a provider-coded chart, you're only validating how that individual coded that specific encounter. Autonomous coding applies uniform logic across every encounter, so auditing a set of charts validates the entire system. Platforms like Arintra also update continuously as payer rules change, keeping your compliance current without your team chasing every guideline update.

That kind of transparency strengthens your revenue cycle management workflow at every step.

‍Free Coders and Physicians from Repetitive Work

Your coders are skilled professionals. Are they spending their days on work that matches that skill level?

When autonomous systems handle a majority of charts, coders reclaim time for the work that requires their expertise, such as:

Complex case review
Denial analysis and trend identification
Revenue integrity projects
Provider education

Providers benefit just as much. Autonomous coding cuts documentation queries and off-hours EHR work, directly tackling two top contributors to burnout.

Retention improves when people stop dreading their workflows. That alone justifies the investment for many organizations.

Invest in Scalable RCM Infrastructure

Revenue cycle management optimization isn't a one-and-done project. Your payer mix will change, your specialty footprint will expand, and your volumes will look different in two years than they do today. If your technology can't keep up with those changes, you'll find yourself rebuilding instead of building on what you have.

What scalable infrastructure looks like in practice:

Native EHR integration with platforms like Epic and Athena
Cross-specialty extensibility without ground-up rebuilds for each new service line
Automatic handling of volume surges

What is revenue cycle in healthcare if not a process that never stops evolving? Your infrastructure should evolve with it.

Seven Strategies, One Through Line: Coding

Health systems pulling ahead aren't patching individual problems one at a time. They're deploying autonomous, integrated, and explainable systems that compound results across the entire revenue cycle management workflow. Arintra customers, for example, report:

5.1% revenue uplift
43% fewer denials
12% shorter A/R timelines

For leaders asking how to improve revenue cycle management, the answer starts with coding. Not as a back-office task, but as strategic infrastructure. The organizations that commit to this now will collect more, collect faster, and spend far fewer resources chasing preventable problems.