multimodal-analysis
Analyzes medical images (X-ray, MRI, CT) using multimodal LLMs to identify anomalies and generate reports.
Prior Auth Review
--- name: 'prior-auth-coworker' description: 'Prior Auth Review' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- <!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA --> # 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) <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->--- name: 'prior-auth-coworker' description: 'Prior Auth Review' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- <!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA --> # 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) <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Includes source scripts; review them before use. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.