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August 7, 2026 · Umer Jamil

Denials are nine problems, not one

"Denial management" is a category name that hides more than it reveals. A duplicate-claim denial is resolved by comparing claim history and proving two visits are distinct. A medical-necessity denial is resolved by chart evidence and a clinical argument against a payer policy. These tasks share a filing cabinet and nothing else. Treating them as one problem is why generic tools are mediocre at all of them.

Where denial volume comes from Share of hospital denials by group, Optum 2024 Denials Index Eligibility and coverage Claim-data errors Authorization Documentation requests Not covered Other and admin Medical necessity Coding and bundling Timely filing 24% 16% 13% 12% 10% 9% 7% 5% 4% The two biggest groups are the most mechanical to fix: consult a source of truth, correct a field, resubmit.
Volume shares from 124 million hospital claim remittances, 2023 data.

The nine groups

Sort any denial worklist by what the fix actually requires and it collapses into roughly nine groups:

  1. Eligibility and coverage routing. The claim went to the wrong payer, coverage terminated, coordination of benefits is stale. The fix is always the same question: who actually covers this patient on this date of service.
  2. Claim-data corrections. One defective field, and the correct value already exists somewhere in the record. Find, fix, resubmit.
  3. Authorization and referral. The approval artifact exists and was not on the claim, or it never existed and the case becomes an appeal.
  4. Documentation requests. The payer wants records before paying. A retrieval-and-assembly job, not an argument.
  5. Non-covered services and benefit limits. The plan genuinely excludes or caps the service. The work is verifying that, then routing to recode, appeal, or the correct disposition.
  6. Medical necessity. Chart evidence against policy criteria, with a human clinical gate. The most expensive denials to work and the least automatable end to end.
  7. Coding, bundling, and units. Resolved against published coding rules and modifier logic. Rules-engine territory with bounded model judgment.
  8. Timely filing. Won by documentary proof of dates, not by argument.
  9. Duplicates and crossed claims. Resolved by claim-history comparison: either prove distinctness or concede the duplicate.

The volume is not evenly spread

Optum's 2024 Denials Index, built from over a hundred million hospital claim remittances, puts registration and eligibility issues at roughly a quarter of denial volume, missing or invalid claim data around 16 percent, authorization around 13 percent, documentation requests around 12 percent, and medical necessity at only about 7 percent. The distribution matters because the biggest groups, eligibility and claim data, are exactly the ones where the fix is mechanical: consult a source of truth, correct a field, resubmit.

Why separate pipelines win

Each group gets its own pipeline at Mohenara: its own deterministic checks, its own model steps, its own evaluation suite scored against synthetic cases with planted defects of exactly that type. Three practical advantages fall out.

First, routing is deterministic. Which pipeline a denial enters is a lookup on the denial codes and payer, not a model's judgment call, so the highest-stakes decision in the system cannot hallucinate. Second, evaluation stays honest. A single blended accuracy number hides the fact that a system might be excellent at duplicates and dangerous at coding. Per-group suites make every weakness visible. Third, improvement is local. Tightening the authorization pipeline cannot break the timely-filing pipeline, because they share nothing but an inbox.

The unglamorous conclusion: the right architecture for denial recovery looks less like one brilliant agent and more like nine boring, measurable production lines with a human gate at every judgment step. Boring, measurable production lines are what we are building.

Source for volume shares: Optum 2024 Revenue Cycle Denials Index (hospital claim remittances, 2023 data). Group taxonomy: Mohenara's own, from working denial worklists with US billing companies.