← 返回
未分类 中文

Discharge Summary Writer

Generate hospital discharge summaries from admission data, hospital course, medications, and follow-up plans. Trigger when user needs to create a discharge s...
根据入院信息、住院经过、用药情况及随访计划,自动生成医院出院小结。当用户需要创建出院小结时触发。
aipoch-ai
未分类 clawhub v0.1.0 1 版本 100000 Key: 无需
★ 0
Stars
📥 440
下载
💾 1
安装
1
版本
#latest

概述

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

ParameterTypeDefaultRequiredDescription
-------------------------------------------------
--inputstring-YesPath to JSON file containing patient data
--outputstringdischarge_summary.mdNoOutput file path
--formatstringstandardNoOutput format (standard, structured, json)
--templatestring-NoCustom template file path
--languagestringzhNoOutput language (zh or en)

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

Risk IndicatorAssessmentLevel
-----------------------------------
Code ExecutionPython/R scripts executed locallyMedium
Network AccessNo external API callsLow
File System AccessRead input files, write output filesMedium
Instruction TamperingStandard prompt guidelinesLow
Data ExposureOutput files saved to workspaceLow

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

版本历史

共 1 个版本

  • v0.1.0 当前
    2026-03-30 16:25 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

data-analysis

Medical Research Literature Reader Pro

aipoch-ai
一种面向临床、生物信息、转化及基础实验背景用户的医学研究原生文献阅读技能。使用此技能……
★ 1 📥 840
productivity

Peer Review Response Drafter

aipoch-ai
协助起草专业的同行评审回复信。当用户提及「审稿人意见」、「回复信」、「同行评审」、「修订再提交」等关键词时触发。
★ 0 📥 840
data-analysis

Survival Analysis (KM)

aipoch-ai
生成Kaplan‑Meier生存曲线,计算生存统计量(log‑rank检验、中位生存时间),并估算临床及生物...的 hazard ratios。
★ 2 📥 909