Healthcare organizations lose millions of dollars every year to both claim denials and underpayments. While these issues are often discussed together, they are fundamentally different revenue cycle problems that require different workflows, different technology, and different strategies to recover lost revenue.
The short answer:
- A denial means the payer refuses to pay a claim, either partially or in full.
- An underpayment means the payer pays the claim, but pays less than the provider was contractually owed.
Understanding the difference is essential because many organizations have mature denial management programs while underpayments remain largely invisible.
Denials vs. Underpayments
While both denials and underpayments reduce revenue, they affect the revenue cycle in different ways.
Claim Denials
- The payer refuses to pay all or part of a claim.
- Denied claims are typically visible in denial workqueues and aging reports.
- They often require correction, appeal, or resubmission before payment can be received.
- Common causes include missing documentation, coding errors, eligibility issues, prior authorization requirements, and timely filing limits.
- Revenue cycle teams typically measure denial rates to monitor performance.
Underpayments
- The payer processes and pays the claim, but reimburses less than the provider was contractually owed.
- Underpayments are often hidden because the claim appears paid.
- Recovering underpayments requires comparing actual reimbursement against expected payment based on payer contracts and fee schedules.
- Common causes include incorrect fee schedule application, payer policy changes, contract misinterpretation, or systematic payment errors.
- Revenue cycle teams often track underpayment rates or total recovered revenue to measure performance.
The biggest difference is visibility. Denials create immediate work because they prevent payment altogether. Underpayments are harder to identify because the claim has already been paid, even if the payment amount is incorrect.
What Is a Claim Denial?
A claim denial occurs when an insurance payer determines that all or part of a submitted claim will not be reimbursed.
Common reasons include:
- Missing documentation
- Coding errors
- Eligibility issues
- Prior authorization requirements
- Timely filing limits
- Medical necessity determinations
Denials are typically accompanied by adjustment or denial codes explaining why payment was withheld. Most healthcare organizations already dedicate significant staff time to denial prevention and appeals because denials are highly visible inside billing systems.
What Is an Underpayment?
An underpayment occurs when a payer processes and pays a claim, but reimburses less than the provider should have received according to:
- Contracted fee schedules
- Negotiated payer agreements
- Expected reimbursement methodologies
- Government payment policies
Unlike denials, underpayments often go unnoticed because the claim appears "paid."
For many revenue cycle teams, paid claims receive far less scrutiny than denied claims, allowing revenue leakage to accumulate over months or even years.
Why Underpayments Are Harder to Detect
Denials naturally create work because unpaid claims appear in denial queues and aging reports.
Underpayments are different. Many organizations simply assume that paid claims were paid correctly, however, identifying underpayments requires comparing each payment against the expected reimbursement based on contracts, payer policies, modifiers, coding, and reimbursement methodologies.
This process becomes increasingly difficult for organizations managing:
- Multiple payer contracts
- Hundreds of CPT codes
- Frequent contract updates
- Large claim volumes
- Multiple provider locations
Without automated payment validation, many underpayments remain undiscovered.
Can a Claim Be Both Denied and Underpaid?
Yes.
A payer may initially deny part of a claim, then later issue payment after reconsideration while still reimbursing below the contracted amount. Similarly, a payer may partially deny certain services while underpaying the remaining approved services. This is why leading revenue cycle teams analyze the entire reimbursement lifecycle instead of treating denials and payment accuracy as separate problems.
Which Costs Providers More?
Both can have a significant financial impact, but underpayments are often underestimated.
Denials create immediate operational work because staff must investigate, correct, and appeal claims.
Underpayments can quietly erode revenue over time because many organizations never identify the missing reimbursement.
For large health systems and physician groups processing millions of dollars in claims each month, even a small percentage of underpaid claims can translate into substantial lost revenue.
Best Practices for Managing Both
Strong revenue cycle teams approach denials and underpayments differently.
For denials:
- Track denial trends by payer and reason code.
- Improve front-end registration and documentation accuracy.
- Standardize appeal workflows.
- Monitor denial rates over time.
For underpayments:
- Compare payments against contracted reimbursement.
- Monitor payer behavior across specialties and locations.
- Detect emerging payment patterns.
- Prioritize high-value recovery opportunities.
- Regularly audit paid claims, not just denied claims.
Organizations that monitor both denied and paid claims gain a more complete picture of reimbursement performance.
How AI Is Changing Revenue Recovery
Historically, identifying underpayments required manual contract reviews, spreadsheets, and retrospective audits.
Today, AI can continuously analyze reimbursement data across millions of claims to identify payment anomalies, detect emerging payer trends, and surface revenue recovery opportunities much earlier.
Rather than waiting for finance teams to discover missing revenue months later, AI-powered revenue intelligence helps organizations proactively monitor reimbursement performance and focus staff on the highest-value opportunities.
How Adonis Helps
Adonis combines denial intelligence, reimbursement analytics, and AI-powered payment monitoring to help healthcare organizations understand where revenue is being lost.
Rather than only identifying denied claims, Adonis continuously analyzes paid claims to detect potential underpayments, payer behavior changes, and emerging reimbursement trends. Revenue cycle teams can prioritize recovery opportunities, monitor payer performance over time, and gain greater visibility into the revenue that traditional workflows often miss.
Frequently Asked Questions
What is the difference between a denial and an underpayment?
A denial occurs when a payer refuses to pay all or part of a claim. An underpayment occurs when the payer approves and pays the claim but reimburses less than the provider was contractually owed.
Is an underpayment considered a denial?
No. An underpayment occurs after a payer has approved and paid the claim, but the reimbursement amount is lower than expected. A denial means the payer refused payment for all or part of the claim.
Why are underpayments often missed?
Because the claim appears paid. Many organizations lack automated systems to compare actual reimbursement against contracted payment expectations.
Which should providers prioritize?
Organizations should manage both. Denials reduce cash flow and increase administrative work, while underpayments create hidden revenue leakage that can accumulate over time.
Can AI identify underpayments?
Yes. Modern AI-powered revenue intelligence platforms can analyze large volumes of paid claims, compare reimbursement against expected payment, identify unusual payer behavior, and prioritize the highest-value recovery opportunities.
Key Takeaway
Denials and underpayments are different problems, but both reduce healthcare revenue.
Denials are visible because claims go unpaid. Underpayments are often hidden because claims appear successfully processed, even when reimbursement is incorrect.
Healthcare organizations that monitor both denied and paid claims, especially with AI-powered reimbursement analytics, are better positioned to recover revenue, identify payer trends, and improve overall financial performance.
