Digital Twin Discharge Drafter

Generate AI-enhanced discharge summaries and personalized care plans using digital twin patient models to predict outcomes and optimize post-discharge care transitions.

Quick Start

from scripts.discharge_drafter import DischargeDrafter

drafter = DischargeDrafter()

# Generate comprehensive discharge summary
summary = drafter.generate(
    patient_id="PT12345",
    admission_data=admission_info,
    hospital_course=treatment_history,
    digital_twin_model=patient_model,
    output_format="structured"
)

# Export patient-friendly version
patient_version = drafter.generate_patient_friendly(summary)

print(summary.readmission_risk_score)  # 0.23
print(summary.key_interventions)       # ['home_health', 'med_reconciliation']

Core Capabilities

1. Digital Twin-Powered Summary Generation

summary = drafter.create_summary(
    patient_data=patient_record,
    digital_twin_model=twin_model,
    include_predictions=True,
    risk_stratification="high",
    readmission_risk_threshold=0.15
)

Summary Components:

• Hospital Course: AI-summarized treatment narrative
• Digital Twin Predictions: 7-day, 30-day outcome probabilities
• Risk Stratification: Readmission risk score with factors
• Medication Reconciliation: AI-validated med list
• Follow-up Schedule: Optimized based on patient model

2. Post-Discharge Outcome Simulation

scenarios = drafter.simulate_outcomes(
    patient_model=digital_twin,
    scenarios=[
        "medication_adherent",
        "medication_non_adherent", 
        "follow_up_missed",
        "social_support_optimal"
    ],
    timeframe="30_days",
    metrics=["readmission_risk", "recovery_trajectory", "cost_projection"]
)

Simulation Outputs:

3. Personalized Patient Instructions

instructions = drafter.create_personalized_instructions(
    patient_profile=profile,
    health_literacy_level="assessed",  # or "8th_grade", "college"
    language_preference="English",
    cultural_considerations=True,
    access_barriers=["transportation", "cost"]
)

# Returns structured instructions
print(instructions.medication_list)      # Formatted medication table
print(instructions.followup_appointments)  # Scheduled visits
print(instructions.red_flags)            # When to call doctor
print(instructions.lifestyle_changes)    # Diet, activity restrictions

Personalization Factors:

• Health Literacy: Adjust complexity (Flesch-Kincaid 6th-12th grade)
• Language: Multi-language support with medical accuracy
• Cultural: Dietary restrictions, family dynamics, beliefs
• Barriers: Transportation, cost, caregiver availability