# Prior Auth Coworker

> Prior Auth Review

- Skill: `fridrichmethod/prior-auth-coworker` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add fridrichmethod/prior-auth-coworker`
- Raw SKILL.md: https://api.skillmd.com/api/skills/fridrichmethod/prior-auth-coworker/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: FridrichMethod (https://skillmd.com/u/fridrichmethod)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/fridrichmethod/prior-auth-coworker

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# Prior Authorization Coworker

This skill acts as an automated utilization management reviewer. It takes unstructured clinical notes and a procedure code, compares them against internal policy criteria (e.g., conservative therapy failure), and renders a decision.

## When to Use This Skill

*   When a user asks to "review a prior auth request".
*   When checking if a patient qualifies for a specific procedure (e.g., MRI).
*   When you need to generate a structured approval/denial letter justification.

## Core Capabilities

1.  **Policy Matching**: Checks against specific criteria (e.g., "Pain > 6 weeks").
2.  **Trace Generation**: Produces an "Anthropic-style" `<thinking>` trace for auditability.
3.  **Structured Output**: Returns a JSON object with decision, reasoning, and timestamps.

## Workflow

1.  **Extract Data**: Parse the clinical note and procedure code from the user's input.
2.  **Execute Review**: Run the coworker script.
3.  **Present Decision**: Output the JSON decision and the reasoning trace.

## Example Usage

**User**: "Check if this patient qualifies for an MRI of the Lumbar Spine: Patient has had back pain for 2 months, tried PT but it didn't work."

**Agent Action**:
```bash
python3 Skills/Clinical/Prior_Authorization/anthropic_coworker.py --code "MRI-L-SPINE" --note "Patient has back pain > 2 months. Failed PT."
```

## Supported Policies

*   `MRI-L-SPINE` (Lumbar Spine MRI)


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