The 2025 State of Claims survey from Experian Health found that 43% of healthcare organizations report insufficient staffing in revenue cycle operations.
That figure has become a fixture in industry discussions about denial management, with the standard framing focused on hiring, training, and automation as solutions.
What that framing misses is a more immediate problem: the staffing shortage is being made worse, not just by volume, but by the type of work that existing staff are being asked to do. A meaningful portion of the rework burden that is consuming revenue cycle capacity is preventable. It is being generated by provider data errors that should never have reached the billing team.
The Math Behind the Burden
AHIMA’s productivity benchmarks show inpatient records averaging 38 to 42 minutes each to code under normal conditions. Outpatient encounters average 12 to 20 minutes. Those benchmarks represent the irreducible baseline, the time required when every input is complete and correct.
Provider data errors add time on top of that baseline. When a rendering provider’s NPI does not match their enrollment record, someone has to identify the discrepancy, locate the correct information, correct the claim, and resubmit. When a billing provider’s taxonomy code is outdated, the correction requires cross-referencing credentialing records, updating the claim, and verifying the fix before resubmission. None of that time appears in productivity benchmarks. It accumulates silently, claim by claim, and compounds across a billing organization’s entire client portfolio.
That silent accumulation has real dollar consequences. As documented in Article 3, the average administrative cost to rework a Medicare Advantage denial is $47.77 and a commercial denial is $63.76. When those rework events are driven by preventable provider data errors, each one represents not just a financial loss but a measurable drain on the capacity of a team that is already operating below its required headcount.
The Compounding Effect on Morale and Retention
The MGMA 2024 benchmarking report on denials and appeals notes that each denied claim compounds staff burnout and turnover as teams repeatedly address the same errors. That observation is more significant than it might appear in a bullet-point summary.
Billing and coding staff who repeatedly encounter the same provider data errors are not experiencing random variability. They are experiencing a structural failure that their organization has not addressed.
When a claims submission specialist corrects the same provider’s NPI for the fifteenth time in a quarter, the frustration is not with the complexity of the work. It is with the preventability of it. That distinction matters for retention, because preventable frustration is distinguishable from complexity frustration, and staff know the difference.
The retention consequences are quantifiable. A 2023 hospital poll cited by Relias found that nearly 9 in 10 organizations report double-digit turnover in RCM roles, with almost half experiencing annual turnover above 25%. The cost of recruiting and onboarding replacement staff, who are both slower and more error-prone during their ramp-up period, compounds the original drain from the provider data errors that contributed to the departure.
The 2025 State of Claims report further found that 90% of denied claims require at least some human review before resubmission. With 43% of organizations understaffed, and denial rates at 11.8% overall and climbing, the workload math does not improve without addressing the upstream cause.
What High-Performing RCM Firms Are Doing
The firms consistently reporting lower denial rates and better staff utilization share a common characteristic: they have invested in upstream data quality rather than expanding downstream rework capacity. MGMA’s 2024 survey of practices with reduced denial rates found they credited enhanced front-end controls and improved eligibility and credentialing verification — not additional headcount in denial management.
The workforce math supports this approach. Cloudmed revenue cycle leaders, interviewed by Becker’s Hospital Review, found that clients who automated routine, tedious revenue cycle tasks reported increased employee engagement, reduced burnout, and improved retention. The mechanism is straightforward: when staff are no longer absorbing preventable rework, they can redirect their time toward the complex, higher-value work that is actually satisfying and career-building, and that the organization needs most.
Dastify Solutions, which processes more than 2 million claims annually and reports a 98.5% clean-claim rate, attributes its performance explicitly to front-end error prevention using AI-driven automation. The benefit is not just fewer denials. It is staff time redirected toward work that generates revenue rather than recovers it.
For submission staff: If you are spending significant time each week correcting the same provider data issues, that pattern is meaningful data your organization should be tracking and escalating. You are not making errors. You are absorbing the downstream consequences of upstream data failures. Making that visible, logging it, quantifying it, and surfacing it. That is how billing firms start changing the dynamic instead of just managing it.
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 talk. Schedule a Strategy Session. There’s no sales pitch, just a working discussion about your current data posture and the revenue you’re leaving on the table.
We invite you to learn more through third-party and Datagence resources:
- Datagence: Provider Data Is Not a Compliance Problem. It’s a Revenue Problem.
- Datagence: The Provider Enforcement Reckoning
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