Healthcare Underpayments: What Providers Need To Know About Getting Fair Reimbursements

Key Takeaways:

• Healthcare underpayments occur when payers reimburse below contract rates — often due to coding errors, outdated payer logic, or system glitches.

• Underpaid insurance claims differ from denials: they are paid, but not correctly.

• Root causes include contract misalignment, missing modifiers, and delayed appeals.

• Identifying and resolving underpayment in medical billing requires automated reconciliation and contract intelligence.

• AI-powered agents like CombineHealth's Amy, Taylor, Penny, and Rachel help detect, prevent, and recover underpaid claims faster and with full transparency.

Healthcare underpayments silently drain revenue from even the most efficient hospitals and medical groups. Unlike denials, they often go unnoticed — hidden behind payment variances, vague explanations of benefits (EOBs), or contract misinterpretations.

According to the Medical Group Management Association (MGMA), underpayments account for 3–5% of annual net revenue losses for the average provider, costing mid-sized systems millions per year. The good news? Most of it is preventable with accurate detection, payer accountability, and better contract intelligence.

What Are Healthcare Underpayments?

Healthcare underpayments occur when a payer reimburses a provider less than the contracted or expected amount for a covered service. This can happen for a single claim or across entire service lines if payment rules aren’t applied correctly.

For example: A hospital’s contract specifies $350 reimbursement for CPT 99214, but the payer only pays $280. Unless the billing team manually reviews that EOB, the shortfall is never recovered.

This underpayment might seem small, but multiply that across tens of thousands of claims, and the lost revenue becomes staggering.

In practical terms, an underpaid insurance claim differs from a claim denial because it’s not rejected outright — it’s paid, but not paid correctly. Identifying it requires active reconciliation, data accuracy, and staff attention.

How Common Are Underpayments, and How Do They Impact Hospitals?

Underpayments are far more common than most finance teams realize. 

In large health systems, 2–3% of claims are underpaid due to payer edits or technical variances. For small-to-midsize physician groups, the number often rises to 5–7%, depending on payer mix and automation level.

The result:

• Lower cash flow
• Reduced margin on high-volume procedures
• Increased administrative costs from rework

Example: A cardiology group billing $25 million annually might lose $1.25 million each year from unnoticed underpayment in medical billing — often due to outdated payer rules or coding mismatches.

Are Underpayments a Type of Denial?

Not exactly. While underpaid claims can result from denial-related issues, they’re distinct in how they occur and how they should be managed. A denial means the claim wasn’t paid at all. An underpayment means the payer processed and paid it, but below the contract rate.

Underpayments vs Denials vs Write-Offs

Note: Not all underpaid medical claims stem from denials — many originate from automated system edits, outdated fee schedules, or payer contract interpretation errors.

Causes of Healthcare Underpayments

Understanding the root causes of healthcare underpayment recovery challenges is the first step to prevention. Below are the most frequent and financially damaging causes:

1. Payer Contract Issues

Contracts often contain ambiguous terms or rate tables that are misapplied in payer systems. When payers update their fee schedules but fail to align internal claims logic, providers receive underpaid insurance claims without explanation.

Example: A provider contract includes a 10% annual inflation adjustment, but the payer’s claims engine still uses the previous year’s rate. Over hundreds of claims, that 10% difference compounds into six-figure losses.

2. Incorrect Coding and Modifier Errors

Medical coding discrepancies — including missing or incorrect modifiers — can cause underpayment in medical billing even if the claim isn’t denied.

If a CPT code modifier changes reimbursement from 100% to 50%, but your coder misses it, payers will process the lower rate automatically.

Example: A surgical claim missing the modifier -59 (distinct procedural service) may trigger partial payment. 

CombineHealth’s Amy, the AI Medical Coding Agent, detects such omissions in real time and auto-flags mismatched CPT-modifier combinations before submission — maintaining 99.2%+ coding accuracy.

3. Technical or System Errors

Glitches in clearinghouses, billing systems, or payer adjudication platforms cause silent variances. Common issues include: 

• Duplicate charges
• Missing NPI mappings

Example: A provider sends a corrected claim, but the payer’s system ignores it, reprocessing the original — at the old rate. Result: chronic underpaid claims that look “closed” in AR.

4. Timeliness and Filing Delays

Late filing, resubmissions after deadlines, or slow claim follow-ups lead to reduced or denied adjustments. Without automation, these deadlines slip past unnoticed — especially when underpayments are detected months later.

5. Misapplied Edits and Medical Policy Updates

Many underpaid insurance claims arise when payers apply new National Correct Coding Initiative (NCCI) edits or Local Coverage Determinations (LCDs) retroactively.

6. Human Oversight and Resource Constraints

Manual AR review is slow, subjective, and error-prone. When billing staff handle thousands of claims weekly, small underpayments often go unnoticed. 

For many RCM teams, it’s a capacity issue — not a knowledge one. This is where automation can radically change the equation.

Check out CombineHealth’s AI A/R follow-up Agent Adam!

How To Identify Underpayments in Healthcare

Identifying underpaid insurance claims requires continuous reconciliation of posted payments against contracted amounts. However, most providers rely on manual Excel audits or inconsistent payer portals — both time-consuming and prone to human error.

Some best practices:

• Contract Validation: Maintain a digital repository of all payer contracts and fee schedules.
• Automated Payment Reconciliation: Use software to compare paid vs expected amounts automatically.
• Regular Audit Sampling: Audit 10–15% of monthly payments across top payers.
• Categorize by Payer and Code: Group underpayments by CPT, modifier, or payer.

Managing and Resolving Underpayments

Even when underpaid medical claims are flagged, resolution is rarely quick. Providers must contact payer representatives, provide contract evidence, and often resubmit corrected claims or denial appeals.

This constant back-and-forth creates operational drag and staff burnout.

Some challenges providers face:

• Long payer response cycles
• Vague or missing EOB details
• Manual appeals requiring policy documentation

Strategies to Streamline Reimbursement Recovery

1. Centralize Underpayment Management: Consolidate all underpayment cases in one dashboard for visibility and prioritization. CombineHealth’s AI revenue cycle analyst Taylor showcases real-time analytics dashboards on both activity (claims placed, claims submitted, etc.) and outcomes (net collection rate, average days in A/R, etc.)
2. Standardize Escalation Protocols: Define thresholds for when to appeal, adjust, or write off.
3. Automate Documentation Retrieval: Appeal automation tools like CombineHealth’s Rachel (AI Appeals Assistant) can quickly generate appeal documents and reference payer policies, reducing manual effort and speeding up underpayment resolution.

How AI Can Help Manage Underpayments

AI changes the game by enabling proactive monitoring, real-time reconciliation, and policy-aware coding.

CombineHealth’s AI RCM workforce integrates directly into existing EHR, ensuring every underpayment is detected, explained, and recovered — with a full audit trail and explainable AI decisions.

For instance, Amy, CombineHealth’s AI Coding Agent, detects missing modifiers or misapplied CPT codes before submission. Meanwhile, Penny, CombineHealth’s AI Policy Reviewer, tracks payer policy updates and NCCI/LCD changes automatically.

Turn Underpayments Into Revenue Using AI

Every dollar matters in today’s margin-constrained healthcare environment. If your team still relies on manual spreadsheets or payer portals, you’re likely missing thousands in recoverable revenue.

Automate your healthcare underpayment recovery workflow today. CombineHealth’s AI Workforce can monitor payer accuracy, detect underpaid claims, and automatically trigger appeals with human-in-the-loop control — ensuring you get every dollar you’ve earned.

Schedule a demo or contact CombineHealth to see how AI can recover your lost reimbursements in weeks, not months.

FAQs

What is the difference between an underpaid insurance claim and a denial?

An underpaid insurance claim is paid, but not correctly. The payer processes and reimburses the claim, but at an amount below the contracted rate. A denial, on the other hand, is rejected outright and not paid at all. Underpayments are often more challenging to identify because they require actively reconciling payments against contract terms, whereas denials are immediately visible.

Beyond lost revenue, what are the hidden costs of underpayments?

The financial impact goes beyond the unpaid amount. Hidden costs include:

Staff Labor: Hours spent by billing staff on manual research, phone calls, and submitting appeals.

Opportunity Cost: Time spent on underpayments is time not spent on other high-value revenue cycle tasks.

Administrative Burnout: The frustrating and repetitive nature of recovery contributes to staff turnover.

Can we negotiate our payer contracts to reduce underpayments?

Absolutely. Proactive contract negotiation is a powerful prevention tool. You can push for clearer language, defined fee schedules as appendices, and clauses that hold the payer accountable for timely and accurate payment based on the agreed-upon terms, including penalties for systematic underpayment.

How do underpayments for government payers (Medicare/Medicaid) differ from commercial payers?

Government payers typically pay based on fixed fee schedules (DRGs for hospitals, MPFS for physicians), so underpayments are less about contract rate disputes and more about incorrect claim setup, coding errors, or failure to capture all applicable quality program adjustments. The appeals process is also highly structured and regulated.

Can our existing EHR or practice management system automatically detect underpayments?

Most legacy systems have limited native functionality for this. They may post payments but lack the intelligent engine to automatically reconcile the paid amount against the complex rules and rates in your payer contracts. This gap is why specialized revenue cycle automation tools and AI solutions have become essential.