Key Takeaway: Coding-related denials surged 126% in 2024, costing providers $265 billion annually, with a significant percentage of denials stemming from medical coding-related errors. This article examines the three primary coding-related denial causes and reveals how autonomous medical coding solutions like Nym’s engine can help prevent these errors by ensuring alignment with internal, regulatory, and payer guidelines and drastically improving coding consistency.
Healthcare organizations face mounting pressure to optimize revenue cycle management while managing complex coding requirements and persistent staffing challenges. With the industry experiencing a 30% shortage of medical coders (1), providers need solutions that address both accuracy and efficiency concerns.
Recent benchmark data reveals the severity of this challenge: coding-related denials increased by 126% in 2024, representing one of the largest increases in three years (2). At least 15% of all medical claims in the United States are denied, according to Experian, costing providers $265 billion annually (3). These denials create cascading challenges, including payment delays, increased administrative overhead, and potential revenue loss.
The 2024 MDaudit Benchmark Report, analyzing data from over 650,000 providers and $8 billion in audited claims, reveals alarming trends:
These increases expose healthcare organizations to significant cash flow impacts and highlight growing scrutiny from payers seeking to identify and deny improperly coded claims.
Modifier errors, which refer to inaccuracies or issues with the two-digit codes that specify how, where, or when procedures were performed, lead to significant billing challenges. These mistakes frequently involve:
Industry data shows revenue opportunities from correcting modifier errors average $13 for professional billing and $191 for hospital billing (2). These oversights trigger automatic payer rejections, often delaying payment by 30-60 days.
Incomplete documentation creates another major denial category because clinical notes often lack sufficient detail to support assigned codes. Recent audit findings reveal that "diagnosis documented but not billed" represents 58% of professional billing issues and 37% of hospital billing problems (2). This challenge occurs when:
The revenue impact is substantial: correcting diagnosis undercoding represents an average opportunity of $202 for professional billing and $3,922 for hospital billing (2).
Code mismatches occur when diagnosis codes don't align with procedures performed, creating medical necessity questions. Insurance companies now use sophisticated technology to automatically flag these inconsistencies, contributing to a 122% increase in commercial payers' requests for information (RFI) denials (2). This results in:
Healthcare organizations have traditionally addressed coding challenges through staff augmentation, outsourced coding services, and Computer-Assisted Coding (CAC) systems. However, with the current 30% coder shortage and high turnover rates, these approaches often prove expensive and unsustainable while still requiring significant human oversight that maintains vulnerability to the coding errors driving current denial increases (1).
The autonomous medical coding industry has emerged as a comprehensive solution, representing a fundamental shift from computer-assisted coding to fully independent code assignment. These solutions process thousands of charts in minutes with industry-standard 95%+ accuracy while operating in the background and sending coded charts directly to billing systems.
Addressing the specific denial challenges outlined above, Nym's autonomous medical coding engine distinguishes itself through two key mechanisms that help prevent coding-related denials.
Consistent Alignment with All Guidelines: Nym's engine maintains continuous alignment with both external regulatory and payer guidelines (ICD-10, CPT, NCCI, LCD/NCD requirements) and internal health system, hospital, and physician group coding guidelines. This dual compliance ensures every code assignment meets both standard industry requirements and organization-specific coding philosophies, eliminating the guideline misalignment that drives denial increases.
Unwavering Coding Consistency: As an autonomous engine, Nym codes with complete consistency across all encounters, eliminating the human variability that creates coding pattern inconsistencies flagged by payer systems. This consistent application of guidelines prevents the modifier errors, documentation interpretation gaps, and code selection variations that trigger automatic denials and audit scrutiny.
Organizations implementing Nym's engine achieve measurable denial reduction results:
A large health system experienced a 97% decrease in radiology professional fee coding-related denial rate, directly countering the industry trend of surging denials through proactive error prevention.
Geisinger, a large health system, reduced coding-related denials to less than 0.1% after implementing Nym’s autonomous medical coding solution for emergency medicine. Read the Geisinger case study.
Request a demo to discover how Nym's transparent autonomous medical coding engine can help your organization prevent coding-related denials while simultaneously reducing coding costs, accelerating payment cycles, and increasing revenue capture.
Coding-related denials increased 126% in 2024, primarily due to three factors: missing or incorrect modifiers that trigger automatic payer rejections, incomplete documentation that fails to support assigned codes, and code mismatches where diagnosis codes don't align with procedures performed. These issues are compounded by a 30% medical coder shortage and increased payer scrutiny using sophisticated technology to flag inconsistencies.
Nym's engine prevents denials through two key mechanisms: consistent alignment with both external regulatory/payer guidelines and internal organizational coding guidelines, ensuring every code meets all requirements; and unwavering coding consistency across all encounters, eliminating human variability that creates the modifier errors, documentation gaps, and code selection variations that trigger denials. Organizations using Nym have achieved results like a 97% decrease in radiology coding-related denials.
Unlike "black box" AI solutions, Nym's engine provides fully transparent audit trails for every code assignment using rules-based CLU technology that enables complete explainability. Every encounter includes supporting documentation, specific guideline references, and step-by-step coding rationale. This comprehensive transparency makes it easier to defend coding decisions during appeals processes and demonstrate compliance with both regulatory and payer requirements when challenging denials. See an audit trail example here.