Every billing and coding leader has a sense of what denied claims cost. What is less commonly understood is how much the cost varies by denial type, how sharply it has risen in recent years, and how much of it is being absorbed silently as overhead rather than attributed to its source.
The numbers matter because they determine whether investing in upstream prevention is financially justified. For organizations still treating denial management as a cost of doing business, these figures make the case for a different approach.
The Per-Claim Cost Landscape Last Year
HFMA’s most current research places the average administrative cost to rework a Medicare Advantage denial at $47.77 and a commercial denial at $63.76. Those figures represent direct staff time and administrative overhead. They do not include the opportunity cost of the claims that were not submitted while staff was working the queue.
The broader range across all denial types runs from $25 to $181 per claim, with complexity driving the upper end. MDaudit’s 2025 analysis of data from 1.2 million providers found that the average amount per denied claim rose 18% from 2024 to 2025. Medicare Advantage denials specifically saw a 22.4% increase in average denied dollar value over the same period.
What that means in practice: the cost of reworking a denial is rising at the same time the volume of denials is rising. From 2022 to 2023, the average administrative cost per denied claim increased from $43.84 to $57.23. That trend has continued into 2025, making denial management more expensive per claim and more costly in aggregate than at any previous point.
The Hidden Cost: Claims That Are Never Resubmitted
The rework cost is significant. But the revenue loss from claims that are never corrected and resubmitted is larger. Industry data consistently shows that 35% to 65% of denied claims are never resubmitted at all. That is not rework cost. That is revenue abandonment.
For billing firms operating on performance-based contracts, abandoned claims represent a direct reduction in collections and a corresponding reduction in fees. For the providers they serve, it represents permanent revenue loss on services that were legitimately rendered. HFMA data shows that 22% of healthcare organizations lose at least $500,000 annually to denials, while 10% report annual denial-related losses exceeding $2 million.
What Other Companies Are Doing (and Whether It’s Working)
Some organizations are investing aggressively in denial management technology. Experian Health reports that 67% of providers now believe AI can meaningfully improve the claims process. According to the Deloitte Center for Health Solutions’ 2024 report on healthcare revenue cycle reinvention, automated claim-scrubbing and predictive validation can prevent up to 85% of avoidable denials. These results are real, but they depend on accurate underlying provider data to function.
The challenge is that denial management tools fix the symptom. Claim scrubbers, denial workflows, and AI-based prediction models all perform better when the provider data feeding them is accurate and current. When the NPI is wrong, when the taxonomy is stale, when the network status has not been updated, the most sophisticated denial management platform catches the rejection and sends it back for manual correction. The upstream problem persists.
Organizations that have addressed provider data infrastructure first are reporting materially better outcomes from their denial management investments. The technology works. It just needs clean data to work on. We examine exactly what that looks like operationally, including the staff time consumed in our upcoming article: Inside the Staffing Crisis: How Provider Data Errors Drain Your Team.
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For submission staff: When you’re correcting a denial related to provider information: wrong NPI, invalid taxonomy, incorrect billing address, that’s not a random error. It’s a data quality signal. Tracking how often the same provider’s information is triggering rejections, and surfacing that pattern to your operations leadership, is how billing firms start fixing problems at the source instead of fixing them claim by claim.
Ready to See What Provider Data Accuracy Can Do for Your Bottom Line?
If any of this resonates with what your team is dealing with, the next step is a conversation. Let’s schedule a Strategy Session. No sales pitch, just a working discussion about your current data posture and the revenue you’re leaving on the table.
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