Agent skill
prior-authorization-mdbabumiamssm-llms-universal-life-
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/prior-authorization-mdbabumiamssm-llms-universal-life-
SKILL.md
---name: prior-auth-coworker description: Prior Auth Review keywords:
- utilization-management
- payer-policy
- fhir
- claims
- audit measurable_outcome: Generates a policy-compliant approval/denial decision with trace for 100% of valid inputs. license: MIT metadata: author: Anthropic Health Stack version: "2.0.0" compatibility:
- system: Python 3.9+ allowed-tools:
- run_shell_command ---"
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
- Policy Matching: Checks against specific criteria (e.g., "Pain > 6 weeks").
- Trace Generation: Produces an "Anthropic-style"
<thinking>trace for auditability. - Structured Output: Returns a JSON object with decision, reasoning, and timestamps.
Workflow
- Extract Data: Parse the clinical note and procedure code from the user's input.
- Execute Review: Run the coworker script.
- 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:
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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