Last Updated
Categories
Data extraction
Document extraction
AI Agents
Why you need it
Prior authorizations are slow because information is spread across clinical notes, codes, medical necessity forms, and plan criteria. Someone has to read everything, check coverage rules, and figure out what is missing. This agent does that work for you. It accepts three core documents and the plan criteria, extracts the text, parses diagnoses and procedure codes, checks coverage, and spots missing documentation. It then returns a structured JSON summary that shows coverage determination, missing items, and suggested next steps so your team spends less time on manual review and fewer requests get denied for avoidable reasons.
What you need in Vellum
- Inputs for three document texts such as clinical notes, codes, and medical necessity forms
- Input for plan criteria or payer policy text
- A step to extract and clean text from the document inputs
- Tools or prompts that parse notes, extract diagnosis and procedure codes, and map them to criteria
- Logic that checks coverage against the plan criteria and identifies missing documents or gaps
- A node that formats the result as structured JSON with fields like coverage (Determination, missingItems, and recommendations)
- An integration or trigger that runs the agent when new prior authorization packets are ready for review
Related Templates
Discover more AI agent templates to automate different aspects of your business
sucCCESS STORIES
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