Tebra does not ship a denial prediction dashboard. There is no score on each claim telling you it will bounce. But the platform carries two assets that, used deliberately, serve the same purpose: real-time eligibility data before a claim leaves your system, and a full denial history from every 835 ERA that has posted. Practices that combine those two inputs into a pre-submission checklist catch a large share of their denials before they enter the AR, rather than working them out of the denial queue afterward.
Tebra's built-in pre-submission checks
Tebra gives you two tools before a claim leaves your system: eligibility verification and the clearinghouse claim scrubber. Eligibility verification pulls real-time benefit data from the payer: active coverage status, copay and deductible, and for some payers, whether prior authorization requirements are flagged on the patient's plan. Running it as part of the check-in workflow, not just on new patients, catches coverage lapses, mid-year plan changes, and Medicare secondary payer situations before a claim is built around incorrect insurance information.
The clearinghouse scrubber runs format and rules checks before the claim reaches the payer. It catches missing required modifiers under payer rules, invalid code combinations, some NCCI edits, and basic structural errors. What it does not catch: medical necessity problems, CPT-diagnosis mismatches below the NCCI level, and authorization gaps that are not surfaced in the eligibility response.
Using ERA history as a prediction tool
Every denial that came in through an 835 is sitting in Tebra with its CARC code, payer name, and CPT code attached. That is a direct record of what each payer denies and why. Pull the last 90 days of denied claims, group by payer and CARC code, and you have a reasonably accurate forecast for what will deny next month.
If a commercial plan has returned CO-4 modifier denials on a specific CPT code eight times in three months, every claim for that code going to that payer is a CO-4 risk until the root modifier issue is fixed. If a payer has denied CO-15 repeatedly on services requiring prior auth, your authorization tracking for those services needs tightening before the next batch submits. This is denial prediction in practice: not an algorithm, but a pattern audit you run quarterly and convert into a pre-submission checklist.
Five signals that predict most denials
These patterns, visible in Tebra's existing claim and ERA data, account for the majority of predictable denials in most small practices:
- Authorization gaps. Claims for services that required prior auth, submitted without one or with an auth number that does not match the service. Check Tebra's authorization tracking and confirm the auth number is on the claim at charge entry, not as a post-billing review step.
- Modifier mismatches from the prior period. Look at your CO-4 and CO-97 denial history by payer and CPT combination. A modifier rule that denied five times last quarter will deny again on the same code unless the billing configuration changed. Document payer-specific modifier requirements in your charge entry reference.
- Eligibility exceptions from the morning run. Any patient whose same-day eligibility check returns an exception (inactive coverage, coordination of benefits, Medicare primary) is a denial risk that day. Work those before the claim is built, not after it bounces.
- CPT-diagnosis mismatches. CO-11 (diagnosis inconsistent with procedure) and CO-50 (medical necessity) denials concentrated on specific CPT-diagnosis combinations signal a documentation or coding problem at charge entry. Flag those combinations in your charge templates.
- Timely-filing risk. Claims still in pending status past 60 days are approaching the timely-filing window for some payers. Payer windows vary widely, from 90 days to 365 days. Flag open claims by aging bucket in Tebra's AR and work any claim approaching the payer's window before it becomes unrecoverable.
What the pre-submission layer does not cover
Eligibility verification and the claim scrubber together catch format errors and active-coverage issues reliably. They do not catch medical necessity arguments, payer-specific criteria the eligibility response does not expose, or authorization requirements that differ by CPT code within the same plan. A claim that clears every pre-submission check can still deny on a clinical ground.
The ERA history pattern audit fills most of that gap for established payer relationships. For a new payer or a new service line, the first few denials are largely unavoidable. The goal is not to repeat them. Document each new denial pattern as it occurs and add it to your pre-submission checklist so it becomes a prediction signal rather than a recurring loss.
The practical return
Catching a meaningful share of likely denials before submission does not eliminate the denial queue. It changes its composition. The claims that do deny become more likely to be genuinely ambiguous or new, rather than the same CO-4 from the same payer for the fourth month running. That shift reduces the per-appeal cost on the remaining denials, because you are working real edge cases rather than repeating fixable pattern errors. The revenue leakage that compounds from unworked small-dollar denials shrinks when fewer denials enter the queue in the first place.
Tebra's data for all of this already exists in your account. The prediction layer is the habit you build around it: quarterly ERA pattern audits, a pre-submission modifier reference by payer, same-day eligibility checks for every encounter, and a timely-filing aging flag. None of it requires additional software; all of it requires consistency.