Prior Authorization

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---
name: 'prior-auth-coworker'
description: 'SOTA Prior Auth Review Agent aligned with Anthropic and OpenAI healthcare initiatives.'
measurable_outcome: 'Achieve >95% accuracy matching human UM reviewers, completing analysis in under 5 minutes.'
license: MIT
metadata:
  author: Biomedical AI Team
  version: "2.0.0"
compatibility:
  - system: BioKernel/MCP
allowed-tools:
  - read_file
  - run_shell_command
  - mcp_bio_tool
---


# Prior Authorization Agent (SOTA 2026 Edition)

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.
4.  **Reference Architecture (Payer-Side)**: Microsoft's Prior-Authorization-Multi-Agent-Solution-Accelerator pairs with this workflow as an enterprise template — built on Microsoft Agent Framework with four Foundry Hosted Agents (Compliance, Clinical, Coverage, Synthesis), a gate-based decision rubric, MCP-based healthcare data access, confidence scoring, audit trails, and human-in-the-loop oversight, deployable via `azd` to Azure Container Apps.

## 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)

## References

*   Microsoft Prior-Authorization-Multi-Agent-Solution-Accelerator: https://github.com/microsoft/Prior-Authorization-Multi-Agent-Solution-Accelerator


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