Skills icd10-cpt-coding-assistant
'Automatically recommend ICD-10 diagnosis codes and CPT procedure codes
install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/aipoch-ai/icd10-cpt-coding-assistant" ~/.claude/skills/openclaw-skills-icd10-cpt-coding-assistant && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/aipoch-ai/icd10-cpt-coding-assistant" ~/.openclaw/skills/openclaw-skills-icd10-cpt-coding-assistant && rm -rf "$T"
manifest:
skills/aipoch-ai/icd10-cpt-coding-assistant/SKILL.mdsource content
ICD-10 & CPT Coding Assistant
A medical coding assistant that parses clinical notes and recommends appropriate ICD-10 diagnosis codes and CPT procedure codes with confidence scoring.
Overview
This skill analyzes clinical documentation to extract relevant medical information and map it to standardized coding systems:
- ICD-10-CM: International Classification of Diseases, 10th Revision, Clinical Modification (diagnosis codes)
- CPT: Current Procedural Terminology (procedure/service codes)
Technical Difficulty: HIGH ⚠️
⚠️ HUMAN REVIEW REQUIRED: Medical coding directly impacts billing, reimbursement, and clinical documentation. All recommendations must be verified by a certified medical coder or healthcare provider.
Usage
python scripts/main.py --input "clinical_note.txt" [--format json|text]
Or use programmatically:
from scripts.main import CodingAssistant assistant = CodingAssistant() result = assistant.analyze("Patient presents with acute bronchitis...") print(result.icd10_codes) print(result.cpt_codes)
Parameters
| Parameter | Type | Default | Required | Description |
|---|---|---|---|---|
, | string | - | Yes | Path to clinical note file |
, | string | json | No | Output format (json, text) |
, | string | stdout | No | Output file path |
| float | 0.7 | No | Minimum confidence score (0.0-1.0) |
| flag | false | No | Include alternative code suggestions |
Input Format
Accepts clinical notes in various formats:
- Free-text narrative
- SOAP notes (Subjective, Objective, Assessment, Plan)
- Discharge summaries
- Progress notes
- Procedure reports
Output Format
ICD-10 Recommendations
{ "icd10_codes": [ { "code": "J20.9", "description": "Acute bronchitis, unspecified", "confidence": 0.92, "evidence": ["cough for 5 days", "wheezing on exam"], "alternatives": ["J20.0", "J44.9"] } ] }
CPT Recommendations
{ "cpt_codes": [ { "code": "99213", "description": "Office visit, established patient, moderate complexity", "confidence": 0.85, "evidence": ["detailed history", "low complexity decision making"], "time": "20 minutes" } ] }
Confidence Scoring
- 0.90-1.00: High confidence - Clear documentation, unambiguous mapping
- 0.70-0.89: Medium confidence - Good documentation, some interpretation required
- 0.50-0.69: Low confidence - Incomplete documentation, multiple possibilities
- <0.50: Very low confidence - Insufficient information, manual review essential
Limitations
- No Medical Advice: This tool does not provide clinical advice or diagnoses
- Coding Complexity: Cannot handle all coding nuances (comorbidities, sequencing, modifiers)
- Regional Variations: May not account for payer-specific coding requirements
- Updates: Code sets may not reflect the latest annual updates
References
See
references/ folder for:
: Frequently used ICD-10 codes by specialtyicd10_common_codes.json
: Frequently used CPT codes by specialtycpt_common_codes.json
: General coding guidelines and conventionscoding_guidelines.md
Safety & Compliance
- HIPAA Awareness: Ensure de-identification of PHI before processing
- Audit Trail: Maintain records of automated recommendations for compliance
- Human Oversight: All codes must be reviewed and approved by qualified personnel
Dependencies
- Python 3.8+
- See
for package dependenciesrequirements.txt
Risk Assessment
| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
Security Checklist
- No hardcoded credentials or API keys
- No unauthorized file system access (../)
- Output does not expose sensitive information
- Prompt injection protections in place
- Input file paths validated (no ../ traversal)
- Output directory restricted to workspace
- Script execution in sandboxed environment
- Error messages sanitized (no stack traces exposed)
- Dependencies audited
Prerequisites
# Python dependencies pip install -r requirements.txt
Evaluation Criteria
Success Metrics
- Successfully executes main functionality
- Output meets quality standards
- Handles edge cases gracefully
- Performance is acceptable
Test Cases
- Basic Functionality: Standard input → Expected output
- Edge Case: Invalid input → Graceful error handling
- Performance: Large dataset → Acceptable processing time
Lifecycle Status
- Current Stage: Draft
- Next Review Date: 2026-03-06
- Known Issues: None
- Planned Improvements:
- Performance optimization
- Additional feature support