Skill: Medication Reconciliation

ID: 164
Name: Medication Reconciliation
Version: 1.0.0
Author: OpenClaw
Description: Compare patient pre-admission medication lists with inpatient orders to automatically identify omitted or duplicated medications and improve medication safety.

Function Overview

This Skill is used for medication reconciliation in medical scenarios. Main functions include:

1. Data Import: Support importing pre-admission medication lists and inpatient orders
2. Medication Comparison: Intelligent matching and comparison of two sets of medication data
3. Omission Identification: Automatically detect medications taken before admission but missing in inpatient orders
4. Duplicate Detection: Identify medications duplicated in both lists
5. Report Generation: Output structured reconciliation reports containing recommendations and warnings

Input Format

Pre-Admission Medications

{
  "patient_id": "P001",
  "patient_name": "Zhang San",
  "admission_date": "2026-02-06",
  "medications": [
    {
      "drug_name": "Atorvastatin",
      "generic_name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "Once daily",
      "route": "Oral",
      "indication": "Hyperlipidemia"
    }
  ]
}

Inpatient Orders

{
  "patient_id": "P001",
  "order_date": "2026-02-06",
  "medications": [
    {
      "drug_name": "Atorvastatin Calcium Tablets",
      "generic_name": "Atorvastatin Calcium",
      "dosage": "20mg",
      "frequency": "qd",
      "route": "po",
      "order_type": "Long-term order"
    }
  ]
}

Output Format

Reconciliation Report

{
  "report_id": "MR-20260206-001",
  "generated_at": "2026-02-06T08:30:00",
  "patient_id": "P001",
  "summary": {
    "pre_admission_count": 5,
    "inpatient_count": 4,
    "continued_count": 3,
    "discontinued_count": 2,
    "new_count": 1,
    "duplicates": []
  },
  "details": {
    "continued": [...],
    "discontinued": [...],
    "new_medications": [...],
    "duplicates": [...],
    "warnings": [...]
  }
}

Usage

Command Line Usage

# Basic usage
python scripts/main.py --pre-admission pre_meds.json --inpatient orders.json --output report.json

# Use example data
python scripts/main.py --example

# Detailed output
python scripts/main.py --pre-admission pre_meds.json --inpatient orders.json --verbose

Python API

from medication_reconciliation import MedicationReconciler

# Create reconciler
reconciler = MedicationReconciler()

# Load data
reconciler.load_pre_admission("pre_meds.json")
reconciler.load_inpatient_orders("orders.json")

# Execute reconciliation
report = reconciler.reconcile()

# Save report
report.save("report.json")

Core Algorithms

1. Medication Matching Algorithm

• Exact Match: Exact match of generic names
• Fuzzy Match: Brand name similarity calculation (using Levenshtein distance)
• Dosage Standardization: Unify dosage units for comparison
• Synonym Library: Support common medication alias mapping

2. Duplicate Detection Rules

• Same generic name + same dosage range
• Same pharmacological class + same indication
• Time-overlapping dosing regimens

3. Omission Detection Logic

• Essential medications before admission (such as antihypertensives, hypoglycemics) missing in inpatient orders
• Judging clinical importance based on medication class

Configuration Options

Configurable in config.json:

{
  "matching": {
    "fuzzy_threshold": 0.85,
    "enable_generic_name_match": true,
    "enable_brand_name_match": true
  },
  "warnings": {
    "critical_drug_classes": ["Anticoagulants", "Hypoglycemics", "Antihypertensives", "Antiepileptics"],
    "discontinuation_alert": true
  },
  "output": {
    "format": "json",
    "include_recommendations": true
  }
}

Notes

1. Medical Disclaimer: This tool is for reference only; final medication decisions must be confirmed by medical staff
2. Data Privacy: Patient data must comply with HIPAA/medical data protection regulations
3. Medication Database: It is recommended to regularly update medication aliases and interaction data

Dependencies

• Python 3.8+
• Standard libraries: json, argparse, difflib, datetime
• Optional: fuzzywuzzy (enhanced fuzzy matching)

Changelog

v1.0.0 (2026-02-06)

• Initial version release
• Implemented basic medication comparison function
• Support omission and duplicate detection
• Generate structured reports

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

# 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

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