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AuthPilot AI — Prior Authorization Automation
AI Healthcare

AuthPilot AI — Prior Authorization Automation

Assembles prior auth packets from the chart, checks them against payer criteria before submission, and tracks every case to decision — cutting turnaround from 9 days to 2.

ClaudeLangChainFHIRX12 278OCRNode.jsPostgreSQLReact

AuthPilot AI takes the single most hated workflow in a medical practice — prior authorization — and turns it from a stack of faxes into a tracked, mostly automated pipeline.


The Problem:

  • Prior authorization is consistently ranked the #1 administrative burden by physicians and practice managers
  • Medicare Advantage denial rates now top 17% — more than double traditional Medicare's 5%
  • Medicaid inpatient initial denials run as high as 44%
  • Each denied or rejected submission costs roughly $57 to rework
  • Staff spend hours hunting for the exact chart notes, lab values, and failed-therapy history a payer requires
  • Cases fall through the cracks: no one owns tracking, so patients wait and care is delayed

    • The AI Solution:

  • Reads the payer's medical policy for the requested code and extracts the actual coverage criteria
  • Pulls the supporting evidence from the chart — diagnoses, prior conservative therapy, imaging, labs, dates
  • Flags missing criteria *before* submission, with a plain-English list of what the chart still needs
  • Drafts the letter of medical necessity in the payer's expected structure
  • Submits through payer portals or fax where no API exists, and logs the confirmation
  • Tracks every open case with automatic status follow-ups and escalation when a case goes quiet
  • Drafts a peer-to-peer prep sheet and an appeal packet when a case is denied

    • How It Helps Healthcare:

    An orthopedic group submitting 340 prior auths a month at a 22% rejection rate was reworking roughly 75 cases monthly — about $4,275 in pure rework cost, before counting delayed procedures. Pre-submission criteria checking took first-pass approval from 78% to 94%. Median turnaround went from 9 days to 2. Two authorization coordinators moved off data entry and onto the complex appeals that actually need a human.


    Real Use Case:

    A specialty infusion practice was losing patients to competitors purely because authorization took too long. AuthPilot cut time-to-first-dose by 6 days. The clinical team's comment was blunt: patients started therapy the week they were diagnosed instead of the month after.


    Important Design Decision:

    The AI never submits a clinical claim on its own judgment. It assembles, checks, and drafts — a human authorization specialist approves every submission. That is what made it acceptable to both the compliance officer and the physicians.


    Tech Stack: Claude (policy parsing, medical necessity drafting), LangChain, FHIR + X12 278, OCR for faxed payer responses, Node.js, PostgreSQL, React.

    Interested in building something like this?

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