Is Your Medical Coding Workflow Helping or Hurting Your Margin?

Every denied claim tells a story. So does every patient chart sitting in a coding queue for five days. Or every provider sitting at home on a Saturday night finishing up their documentation work instead of resting or spending time with family. 

These are symptoms of a systemic problem, caused in part by medical coding workflows inherited from a bygone era, when coding complexity was substantially lower, health system volumes were lower, margins were wider, and coders were less difficult to hire.

That era is over. Health systems now face substantial financial pressures, with industry profitability declining significantly since 2019. Coding workflow inefficiencies, long overlooked, quietly drain already scarce resources in this environment, causing:

• Extended A/R days
• Denial appeal costs
• Compliance exposure
• Provider burnout

These problems feed into each other, creating a feedback loop in which poor clinical documentation leads to delays and triggers denials, which require provider clarification, adding to their documentation burden and slowing payment. Medical coding workflows may sound mundane, but they’re a central part of the revenue cycle and directly impact the bottom line.

What Medical Coding Workflows Really Encompass

Medical coding workflows span far more revenue cycle territory than most people realize. The process starts when a provider documents a patient encounter and ends only when the associated claim gets paid. 

Here’s a breakdown of the workflow phases:

The front-end begins when a provider documents a patient visit in their electronic health records system (EHR), noting diagnoses, procedures, medications, and an encounter narrative. The quality and specificity of the provider’s documentation determine everything downstream. Once signed by the provider, becomes a legal document and becomes part of the patient’s permanent medical record.

Mid-cycle involves the actual code assignment. In many health systems, professional coders only review a fraction of charts. There are simply too many for coders to review every single one. Providers themselves often handle coding, selecting codes within the EHR during or after the visit. This mixed model creates challenges. Provider-assigned codes may lack the specificity needed for optimal reimbursement or miss nuances that affect code selection and compliance.

The back-end involves claim submission, denial management, and appeals. When payers reject a claim, someone on the revenue cycle team has to investigate the cause. During this process, they seek out supporting documentation for the claim and resubmit it. This consumes resources, which is especially frustrating as denials often stem from coding workflow issues that could have been prevented upstream.

Why Traditional Coding Workflows Can’t Keep Up

Manual coding workflows weren’t designed for today’s volumes and complexity. Here are some of the current problems that continue to compound.

1. Documentation quality varies widely across providers. One provider may write detailed, specific notes and have years of experience with different types of codes and stay up to date on the latest changes. Another provider in the same hospital may only use basic templates without any customization. These providers will quickly fall behind as CMS adds on average roughly 400 new ICD 10 diagnosis codes annually for example.

2. Coders can’t keep pace with volume fluctuations, which creates backlogs that delay revenue recognition.

3. Payer complexity compounds these issues. Each insurer has unique medical necessity criteria, modifier requirements, and other rules that change frequently. Medicare has its own guidelines, and Medicaid rules vary by state. 

Revenue recognition grinds to a halt when charts sit in queues. Days in A/R lengthen. Denials delay payment by weeks or months while costing money to appeal. Providers suffer because they spend off-hours working on documentation, known as pajama time.

How Next-Gen Coding Workflows Function

Attempts at medical coding automation aren’t new. Computer-assisted coding (CAC) emerged in the 1990s as a rule-based logic engine designed to suggest codes. However, these tools cannot code end-to-end without human intervention.

Autonomous medical coding is something fundamentally different. This represents a completely new era in medical coding. 

GenAI-powered coding solutions interpret both structured data (vitals, lab results, medication) and unstructured clinical narratives. They are capable of understanding context and recognizing the relationships between diagnoses. Within these systems, most charts are coded automatically, without human intervention. This technology also offers complete transparency into why it coded something a particular way, with clinical documentation supporting every code assignment.

GenAI-powered coding workflows include:

• Deep EHR integration, which means that the system can access complete patient records without changing provider workflows
• Proactive clinical documentation improvements in real time, within the EHR
• Payer intelligence, meaning that codes are validated against payer requirements before submission

Traditional CAC suggests codes for human validation. Medical coding AI tools code charts completely, referring only complex cases to human coders, with specific guidance on what needs to be reviewed.

The Future: Medical Coding Workflows as Revenue Assurance

Medical coding workflows have been a revenue cycle bottleneck for too long. They should be doing the opposite, protecting every dollar health systems earn. That’s exactly what Arintra’s GenAI-powered solution does, and it represents the future of medical coding.

This solution integrates natively with Epic and Athena, meaning that the technology works within existing workflows, not around them. Providers continue to document in their EHRs while coding happens in the background. Every code assignment includes full explainability, showing the supporting clinical evidence. CDI happens in real time, catching documentation gaps before they trigger denials. Real-world results prove Arintra’s model works.

Mercyhealth was struggling with revenue recognition challenges that threatened its financial stability. Within five months of deploying Arintra’s automated coding solution, they achieved:

• 5.1% revenue uplift
• Cutting A/R days in half
• Improved clinical documentation

Med First, a primary and urgent care provider group, saw similar positive outcomes:

• Over 6% revenue uplift
• Reduced compliance risks
• Time to work on strategic initiatives 

The technology exists now. The results are proven. While some organizations debate about whether it’s time to modernize their coding workflows, others are already capturing revenue.

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Discover how Arintra can streamline your medical coding workflows and improve your revenue cycle. Book a demo today.

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