Discharge Summary Writer

Generate standardized, clinically accurate hospital discharge summaries by integrating all inpatient medical data.

When to Use

• Patient discharge preparation requires comprehensive summary documentation
• Compiling admission, treatment, and discharge data into unified records
• Generating follow-up instructions and medication lists for post-discharge care
• Creating legally compliant discharge documentation for medical records

Input Requirements

Required Patient Data

{
  "patient_info": {
    "name": "string",
    "gender": "string",
    "age": "number",
    "medical_record_number": "string",
    "admission_date": "YYYY-MM-DD",
    "discharge_date": "YYYY-MM-DD",
    "department": "string",
    "attending_physician": "string"
  },
  "admission_data": {
    "chief_complaint": "string",
    "present_illness_history": "string",
    "past_medical_history": "string",
    "physical_examination": "string",
    "admission_diagnosis": ["string"]
  },
  "hospital_course": {
    "treatment_summary": "string",
    "procedures_performed": ["string"],
    "significant_findings": "string",
    "complications": ["string"],
    "consultations": ["string"]
  },
  "discharge_status": {
    "discharge_diagnosis": ["string"],
    "discharge_condition": "string",
    "hospital_stay_days": "number"
  },
  "medications": {
    "discharge_medications": [
      {
        "name": "string",
        "dosage": "string",
        "frequency": "string",
        "route": "string",
        "duration": "string"
      }
    ]
  },
  "follow_up": {
    "instructions": "string",
    "follow_up_appointments": ["string"],
    "warning_signs": ["string"],
    "activity_restrictions": "string",
    "diet_instructions": "string"
  }
}

Usage

Python Script

python scripts/main.py --input patient_data.json --output discharge_summary.md --format standard

Parameters

Output Formats

Standard Format

Human-readable markdown document following clinical discharge summary structure:

1. Patient Information
2. Admission Information
3. Hospital Course
4. Discharge Status
5. Discharge Medications
6. Follow-up Instructions
7. Physician Signature

Structured Format

Sectioned markdown with clear headers for EMR integration.

JSON Format

Machine-readable structured data for system integration.

Technical Difficulty

⚠️ HIGH - Manual Review Required

This skill handles critical medical documentation. Output requires:

• Physician verification before use
• Compliance with local medical documentation standards
• Review for accuracy and completeness
• Institutional approval for template formats

Safety Considerations

1. Never use generated summaries without physician review
2. Verify all medication dosages and instructions
3. Confirm follow-up appointments with hospital scheduling system
4. Ensure discharge diagnoses match official medical records
5. Validate patient identifiers and dates

References

• references/discharge_template.md - Standard discharge summary template
• references/medical_terms.json - Standardized medical terminology
• references/section_guidelines.md - Guidelines for each section

Limitations

• Does not access live EMR systems (requires manual data input)
• Medication interactions not validated
• Does not generate ICD-10 codes automatically
• Requires structured input data
• Output format must align with institutional requirements

Risk Assessment

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

No additional Python packages required.

Evaluation Criteria

Success Metrics

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. 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