AgentSkillsCN

Validate Drug Interaction

验证药物相互作用

SKILL.md

Skill: Validate Drug Interaction

Domain

healthcare

Description

Screens medication combinations for potential drug-drug interactions, contraindications, and dosage adjustments based on patient profile.

Tags

healthcare, pharmacy, drug-interactions, clinical-decision-support, patient-safety

Use Cases

  • •Prescription validation
  • •Medication reconciliation
  • •Clinical decision support
  • •Pharmacy dispensing checks

Proprietary Business Rules

Rule 1: Interaction Severity Classification

Multi-level severity scoring based on clinical significance and evidence quality.

Rule 2: Patient Factor Adjustments

Interaction risk modified by age, renal function, hepatic function.

Rule 3: Therapeutic Duplication

Detection of overlapping therapeutic classes.

Rule 4: Timing Recommendations

Administration timing to minimize interactions.

Input Parameters

  • •patient_id (string): Patient identifier
  • •medications (list): List of medications with doses
  • •patient_factors (dict): Age, weight, renal/hepatic function
  • •allergies (list): Known allergies
  • •diagnosis_codes (list): Active diagnoses

Output

  • •interactions_found (list): Identified interactions
  • •severity_score (int): Overall risk score
  • •recommendations (list): Clinical recommendations
  • •therapeutic_duplications (list): Duplicate therapy alerts
  • •dose_adjustments (list): Recommended dose changes

Implementation

The validation logic is implemented in interaction_checker.py and references the drug database in CSV files:

  • •interactions.csv - Reference data
  • •drug_classes.csv - Reference data
  • •severity_definitions.csv - Reference data
  • •parameters.csv - Reference data.

Usage Example

python
from interaction_checker import validate_interactions

result = validate_interactions(
    patient_id="PT-12345",
    medications=[
        {"name": "warfarin", "dose": "5mg", "frequency": "daily"},
        {"name": "aspirin", "dose": "81mg", "frequency": "daily"}
    ],
    patient_factors={"age": 72, "egfr": 45, "weight_kg": 70},
    allergies=["penicillin"],
    diagnosis_codes=["I48.0", "Z79.01"]
)

print(f"Interactions: {len(result['interactions_found'])}")

Test Execution

python
from interaction_checker import validate_interactions

result = validate_interactions(
    patient_id=input_data.get('patient_id'),
    medications=input_data.get('medications', []),
    patient_factors=input_data.get('patient_factors', {}),
    allergies=input_data.get('allergies', []),
    diagnosis_codes=input_data.get('diagnosis_codes', [])
)