Clean Claims Submission: How to Hit 98% First-Pass Rate (2026)

Why Clean Claims Matter

Every claim that fails first-pass submission triggers a rework cycle: someone investigates the rejection, corrects the data, and resubmits. That cycle costs $25-35 per claim in staff time alone. If the claim is denied after reaching the payer and requires a formal appeal, the cost climbs to $43-57 (MGMA, 2025). Multiply by hundreds of claims per month and the revenue leakage is substantial.

But the direct rework cost is only part of the problem. Rejected and denied claims delay cash flow, inflate days in accounts receivable, and consume billing staff hours that could be spent on higher-value work like underpayment recovery and contract analysis. Practices with first-pass rates below 90% are typically running 10-15 days longer in A/R than peers at 97%+.

A first-pass rate below 90% almost always points to a structural issue: broken eligibility workflows, outdated scrubber rules, or a clearinghouse that is not configured properly. The fix is not working harder on denials -- it is building a pre-submission workflow that prevents them.

Anatomy of a Clean Claim

A clean claim is one that contains all required data elements, in the correct format, with valid codes, for an eligible patient, and submitted within the payer's timely filing window. Payers and clearinghouses evaluate claims in a predictable order, and understanding that order tells you where to focus quality controls.

What Payers Check First

1. Patient eligibility and coverage -- Is the patient active under this plan on the date of service? Is the subscriber ID valid?
2. Provider enrollment and NPI -- Is the rendering provider enrolled with this payer? Is the NPI on file and active?
3. Claim form completeness -- Are all required fields populated on the CMS-1500 (professional) or UB-04 (institutional)?
4. Code validity -- Are the ICD-10, CPT/HCPCS, and modifier codes valid and current? Do diagnosis pointers map correctly to procedure codes?
5. Medical necessity edits -- Does the diagnosis support the procedure under NCCI edits, LCD/NCD policies, and payer-specific rules?
6. Authorization status -- If the service requires prior authorization, is a valid auth number on file that covers this date of service and procedure?

Required Fields on CMS-1500 and UB-04

The CMS-1500 (used for professional claims) and UB-04 (used for institutional/facility claims) have different field requirements. Common rejection-causing omissions include:

• CMS-1500: Patient name and DOB (Box 2-3), subscriber ID (Box 1a), diagnosis codes with pointers (Box 21/24E), place of service (Box 24B), rendering NPI (Box 24J), referring provider NPI when required (Box 17/17a), and valid taxonomy code.
• UB-04: Type of bill (FL 4), admission/discharge dates and status (FL 12-17), revenue codes with corresponding HCPCS (FL 42-44), occurrence codes, value codes, and condition codes specific to the payer and service type.

Your claim scrubber should validate every required field before the claim leaves your system. Any field left blank or filled with invalid data will result in a rejection before the payer even evaluates medical necessity.

Pre-Submission Workflow: Five Steps to 98%

The clean claim rate is not determined at the billing desk. It is determined across five control points that span from scheduling to claim release. Each step catches a different category of errors, and skipping any one of them creates a predictable gap in your first-pass rate.

Step 1: Real-Time Eligibility Verification

Eligibility failures account for approximately 27% of all claim denials (Advisory Board). The fix is simple in concept and difficult in execution: verify coverage twice -- once at scheduling and once at check-in.

• At scheduling: Run a 270/271 eligibility transaction to confirm the patient has active coverage, the subscriber ID is valid, and the plan covers the type of service being scheduled. If the patient is uninsured or has a coverage gap, you know before the appointment, not after.
• At check-in: Run eligibility again. Coverage can change between scheduling and the visit (job change, plan termination, new plan effective date). Catch it before the patient is seen.
• Automate where possible: Most EHR systems support batch eligibility checks 24-48 hours before scheduled appointments. Configure this and have front desk staff review exceptions only, not every patient manually.

Step 2: Demographic and Insurance Data Validation

Even when a patient has active coverage, claims reject if the demographic data on the claim does not match the payer's records. Common mismatches include:

• Patient name spelled differently than the payer record (middle name, suffix, hyphenation)
• Date of birth transposition errors
• Stale address data that triggers payer fraud flags
• Wrong subscriber relationship code (self vs. spouse vs. dependent)
• Group number or plan ID that has changed due to employer plan renewal

Build a demographic verification step into your check-in workflow. Ask the patient to confirm name, DOB, address, and insurance card on file at every visit. Scan the insurance card front and back and compare against what is in the system. This takes 60-90 seconds and prevents a category of rejections that is otherwise impossible to catch downstream.

Step 3: Prior Authorization Confirmation

Missing prior authorization accounts for approximately 18% of denials (Advisory Board). The workflow control is straightforward: before any service that may require authorization, confirm that a valid authorization exists, covers the specific procedure code, and has not expired.

• Maintain a payer-specific authorization requirement matrix. Not every procedure requires auth from every payer, and requirements change frequently.
• Configure your EHR to flag orders that match authorization-required procedure codes and block claim release until the auth number is entered.
• Track authorization expiration dates. An auth that was valid when the procedure was scheduled may have expired by the time the claim is submitted.
• For behavioral health: monitor session count limits. Many authorizations approve a fixed number of sessions, and exceeding the approved count triggers automatic denials.

Step 4: Coding Review

Coding errors cause approximately 15% of denials. The most common coding issues that reach the billing desk are:

• Diagnosis pointer inaccuracy: The ICD-10 code in pointer position 1 must be the primary reason for the service. If the pointer order is wrong, the claim may be denied for medical necessity even though the documentation supports the service.
• NPI validation: The rendering provider NPI must be enrolled with the payer and linked to the correct taxonomy code. A common error is submitting with an organizational NPI when the payer requires the individual provider NPI, or vice versa.
• Modifier misuse: Incorrect use of modifiers 25, 59, 76, and the X{EPSU} modifiers accounts for a disproportionate share of coding-related denials. Each modifier has specific documentation requirements.
• Outdated codes: ICD-10, CPT, and HCPCS code sets are updated annually. Claims submitted with deleted or replaced codes are rejected immediately.

If your practice does not have a certified coder reviewing claims before release, your billing staff should at minimum use a coding validation tool that checks pointer logic, modifier appropriateness, and code currency.

Step 5: Claim Scrubber Rules

The claim scrubber is the last automated checkpoint before the claim leaves your system. A properly configured scrubber catches errors that slip through the first four steps by applying:

• NCCI edits: The National Correct Coding Initiative defines bundling rules, mutually exclusive code pairs, and medically unlikely edits (MUEs). Your scrubber must be current with the latest quarterly NCCI update.
• LCD/NCD checks: Local Coverage Determinations and National Coverage Determinations define which diagnoses support which procedures for Medicare and many commercial payers that follow Medicare guidelines.
• Modifier logic: The scrubber should validate that modifiers are appropriate for the procedure code, consistent with the place of service, and not conflicting with each other.
• Payer-specific rules: Beyond CMS edits, individual payers have their own submission requirements. A good scrubber allows you to configure payer-specific rule sets.

Clearinghouse Configuration

The clearinghouse sits between your practice management system and the payer. It receives your claims in ANSI X12 837 format, applies its own validation rules, and forwards clean claims to the appropriate payer. Claims that fail clearinghouse validation are rejected back to you before the payer ever sees them.

This is actually good news: a clearinghouse rejection is cheaper and faster to fix than a payer denial. The claim never entered the payer's adjudication system, so there is no formal denial to appeal. You correct the error and resubmit.

Rejection vs. Denial: Why It Matters

• Rejection (clearinghouse): Claim fails formatting or data validation before reaching the payer. Turnaround to fix: same day to 48 hours. Cost: $5-15 in staff time.
• Denial (payer): Claim reaches the payer, is adjudicated, and determined not payable. Turnaround to appeal: 30-60 days. Cost: $25-57 in staff time plus delayed cash flow.

A high clearinghouse rejection rate (above 3-4%) indicates configuration problems that are within your control. Below are the most common clearinghouse rejection codes and how to resolve them.

Top 10 Clearinghouse Rejection Codes

Maintaining Clearinghouse Rules

• Payer directory updates: Payers change clearinghouse routing, payer IDs, and submission requirements regularly. Review your clearinghouse payer directory monthly and subscribe to your clearinghouse's update notifications.
• Enrollment file accuracy: Ensure every rendering provider's NPI, taxonomy, and enrollment status are current in both the clearinghouse and each payer's system. A single provider whose enrollment lapses will generate rejections on every claim they render.
• Rejection report review: Pull your clearinghouse rejection report daily during the first week of any configuration change, and weekly thereafter. Sort by rejection code to identify systemic issues versus one-off data errors.

Claim Scrubber Optimization

The claim scrubber is your last line of defense before a claim enters the clearinghouse. Whether you use the scrubber built into your EHR or a standalone product, the effectiveness depends entirely on how well it is configured and maintained.

Built-In EHR Scrubbers vs. Standalone Products

• Built-in (EHR-native): Vendors like athenahealth, NextGen, and eClinicalWorks include claim scrubbing in their platform. These scrubbers leverage the vendor's network data (athenahealth's Rules Engine processes over 1 billion claims annually) and require no additional integration. Best for: single-specialty practices with straightforward payer mixes.
• Standalone products: Tools like Optum EncoderPro, ClaimRemedi, and Codify by AAPC provide deeper rule libraries, LCD/NCD databases, and payer-specific edit sets. They typically integrate with your PM system via API or batch file. Best for: multi-specialty groups, practices with high Medicare volume, or organizations seeing rejection rates above 5% on their built-in scrubber.

Rule Update Cadence

• Quarterly: NCCI edits, MUE values, and CMS fee schedule updates. These are published on predictable schedules (January, April, July, October).
• Annually: New CPT/HCPCS codes (January 1), ICD-10-CM updates (October 1), and Medicare physician fee schedule changes.
• As published: LCD/NCD revisions, payer medical policy changes, and state Medicaid rule updates.
• Immediately on detection: When you identify a new denial pattern from a specific payer, add a custom scrubber rule to catch that pattern before future claims submit.

Custom Rules by Payer

Generic scrubber rules catch generic errors. The claims that slip through are typically payer-specific. Build custom rules for your top five payers by volume:

• Which modifiers does this payer require (or reject) for telehealth, E/M with procedure, or bilateral services?
• Does this payer require NDC numbers on drug claims? What format?
• Does this payer require a referring provider NPI on specialist claims?
• What are this payer's specific documentation requirements for high-cost procedures?

Review your denial data monthly by payer and convert the top denial reasons into scrubber rules. A mature scrubber configuration is a living document that reflects your actual payer experience, not just CMS defaults.

Electronic vs. Paper Claims

The performance difference between electronic and paper claim submission is stark:

• Electronic claims: Average adjudication time of 5-14 days. Real-time validation at the clearinghouse. Automated status tracking (277 transactions). Lower error rates due to format enforcement.
• Paper claims: Average adjudication time of 30-45 days. No pre-submission validation. Manual status inquiries required. Higher error rates from handwritten data and OCR misreads.

When Paper Is Still Required

A small number of scenarios still require paper submission:

• Workers' compensation claims in states that do not yet support electronic submission
• Certain auto liability and personal injury claims
• Claims with attachments that the payer cannot receive electronically (though this is changing rapidly with the CAQH CORE Attachments Rule)
• Corrected claims for payers that do not accept electronic replacement (frequency code 7) submissions

For paper-required scenarios, use CMS-1500 form version 02/12 (the current version). Print from your PM system rather than handwriting to reduce OCR errors. Track paper claims separately and follow up more aggressively, as they lack the automated status tracking of electronic claims.

Payer-Specific Submission Rules

Every payer has idiosyncrasies. If you treat all payers the same in your submission workflow, you will generate avoidable rejections. The most impactful payer-specific variables to track are timely filing limits, unique modifier requirements, NDC requirements for drug claims, and referral/authorization workflows.

Major Payers: Timely Filing Limits and Common Gotchas

Managing Payer-Specific Requirements

• Maintain a payer matrix: Create and maintain a reference document (spreadsheet or internal wiki) that lists each payer's timely filing limit, authorization requirements, unique modifiers, NDC rules, and routing specifics. Assign a billing team member to own updates.
• Subscribe to payer bulletins: Every major payer publishes provider newsletters with policy changes, new prior auth requirements, and updated billing guidelines. These are typically available on the payer's provider portal.
• Convert denial patterns to rules: When you see a spike in denials from a specific payer for a specific reason, add that check to your pre-submission workflow immediately. Do not wait for the quarterly scrubber update.

Monitoring and Continuous Improvement

Hitting 98% first-pass rate is not a one-time achievement. It requires ongoing measurement, root-cause analysis, and workflow adjustment. The practices that sustain high clean claim rates treat rejection tracking as an operational discipline, not a retrospective report.

Rejection Rate Tracking

• Overall first-pass rate: Track weekly. Anything below 95% warrants immediate investigation.
• Rejection rate by category: Break rejections into eligibility, coding, NPI/enrollment, demographic, and payer-specific buckets. This tells you which part of your workflow is failing.
• Rejection rate by payer: If one payer accounts for a disproportionate share of rejections, you have a payer-specific configuration problem.
• Rejection rate by provider: If one provider's claims reject at a higher rate, the issue is likely in their documentation or coding pattern.

Weekly Scrub Reports

Generate a weekly report from your claim scrubber that shows:

1. Total claims scrubbed vs. total claims with edits triggered
2. Top 10 edit reasons by frequency
3. Claims held (not released) due to scrubber flags -- and how long they have been held
4. Override rate -- how often staff are bypassing scrubber warnings

A high override rate is a red flag. If billing staff routinely bypass scrubber warnings to move claims out the door, the scrubber is either misconfigured (too many false positives) or staff are not trained on why the edits matter. Both are fixable.

Root-Cause Trending

Monthly, aggregate your rejection and denial data into a root-cause trend report. The format is simple:

1. Rank rejection/denial reasons by frequency and dollar impact
2. For the top five reasons, identify the process failure point (scheduling, check-in, coding, billing, scrubber, clearinghouse)
3. Assign a corrective action to each with a responsible owner and due date
4. Track whether the corrective action reduced the occurrence in the following month

Frequently Asked Questions