How can I detect underpayments from insurance companies?

Understanding What Constitutes an Insurance Underpayment

An insurance underpayment occurs when the amount a payer remits is lower than the contracted allowable for a given CPT/HCPCS code, after patient responsibility has been applied. Unlike a straightforward denial, underpayments often appear as partial payments or unexplained adjustments on the remittance advice. Because they do not always trigger a hard denial code, they can quietly erode net collections if left unchecked.

To classify a shortfall as an underpayment, you need three data elements for every encounter: the billed charge, the contractual allowable, and the actual payment. When the actual payment is less than the allowable—and the difference cannot be explained by patient coinsurance, copay, or deductible—you are looking at an underpayment.

Common Root Causes of Payer Underpayments

Underpayments rarely stem from a single issue; most result from a mix of operational, contractual, or payer-system errors. Frequent causes include:

• Misinterpretation of newly negotiated fee schedules or effective dates
• Unbundling or down-coding at the claim adjudication stage
• System configuration gaps after payer policy or CPT code updates
• Application of outdated pricing methodologies, such as legacy RVUs
• Manual keying errors during payment posting or contract entry

Key Indicators That Signal You’re Being Underpaid

Because underpayments often hide in plain sight, revenue cycle teams should monitor the following warning signs:

• Consistent small-dollar variances across high-volume codes
• Frequent “CO45” (contractual adjustment) codes without clear documentation
• Average reimbursement per unit trending downward while volume and mix stay flat
• Repeat shortfalls from the same payer plan or product line
• Manual write-offs increasing despite stable denial rates

Critical Data Points to Track in Your Billing and EHR Systems

Detecting underpayments requires granular, encounter-level visibility. Ensure your billing platform captures and reports on these core data elements:

• Billed charge, contractual allowable, and paid amount for each CPT or HCPCS line
• Adjustment reason codes and remark codes from the ERA/EOB
• Modifiers, place of service, and rendering provider identifiers
• Payer name, plan type, and product (e.g., PPO vs. HMO)
• Date of service and claim received date to track timely filing issues

Storing this information in a structured format enables automated comparisons and variance alerts.

Benchmarking Contracted Rates Against Actual Payments

Benchmarking bridges the gap between expected and real-world reimbursement. Begin by loading the full fee schedule for each payer into a central repository. Next, map every remitted line item to its contractual rate. Variance reports—both at the code level and by service line—quickly reveal patterns of underpayment.

An effective benchmark process also incorporates peer or market rates when available. Although your primary concern is compliance with your own contracts, understanding broader market reimbursement helps you spot atypical payment behavior that might warrant renegotiation.

Automating Contract Management for Real-Time Variance Analysis

Manual contract tracking via spreadsheets makes it nearly impossible to identify underpayments at scale. A purpose-built contract management solution should:

• Store every fee schedule version with effective and termination dates
• Integrate directly with ERA feeds to compare expected versus paid amounts in real time
• Trigger alerts when deviations exceed user-defined dollar or percentage thresholds
• Provide drill-down capability to view charge-level explanations

Automation not only accelerates detection but also supplies the documentation needed for rapid appeals.

Building a Proactive Underpayment Recovery Workflow

Once detection is streamlined, a structured follow-up process is essential. Core steps include:

• Queueing underpaid claims into worklists prioritized by balance and age
• Assigning ownership to RCM staff with defined turnaround times
• Generating templated appeal letters with contract excerpts and remittance details
• Escalating unresolved items to payer representatives or state regulators when appropriate
• Capturing root causes to inform preventative measures and future negotiations

Leveraging Predictive Analytics and AI to Uncover Hidden Underpayments

Advanced analytics can flag anomalies that rule-based reports miss. Machine learning models analyze historical reimbursement patterns to predict what each claim should have paid, adjusting for variables such as modifier usage, place of service, and even seasonal case-mix shifts. When actual payments fall outside the predicted confidence interval, the claim is surfaced for review.

Natural language processing (NLP) further enhances visibility by extracting insights from payer remark codes and appeal correspondence, reducing manual data entry and classification errors.

Training Your Revenue Cycle Team to Escalate Underpayment Discrepancies

Technology is only as effective as the team using it. Make sure staff understand:

• The financial impact of even small variances on practice margin
• Where to find contractual language to support appeals
• Which payer contacts or portals expedite resolution
• Documentation standards for audit trails and compliance

Regular refresher sessions, paired with cross-functional meetings that include contracting, coding, and finance, create a culture that treats underpayments as preventable, not inevitable.

How MD Clarity Automates Underpayment Detection and Optimizes Reimbursement

If your organization is still asking, “How can I detect underpayments from insurance companies?” MD Clarity’s RevFind module delivers a turnkey solution. RevFind automatically ingests ERAs, reconciles each line item against your contracted rates, and flags payment variances the moment they occur. Interactive dashboards let you drill down to the charge level, uncovering trends by payer, plan, or CPT code.

The platform centralizes your contracts, so fee schedule updates are applied instantly—eliminating the risk of working from outdated terms. Built-in worklists route underpaid claims to the right team members, while robust analytics reveal which payer behaviors to target during negotiations.

Practices and health systems use RevFind to streamline denial management, accelerate appeal cycles, and strengthen their position at the contracting table. To see how MD Clarity can help you identify and recover underpayments before they impact your bottom line, contact MD Clarity for a personalized demo.