Medication Adherence
Non-Adherence Prediction
Risk Factors
class AdherencePredictor:
def __init__(self):
self.risk_factors = ['complexity', 'cost', 'side_effects', 'age', 'regimen_frequency']
def predict(self, patient_data):
risk_score = 0
if patient_data['pills_per_day'] > 4: risk_score += 0.3
if patient_data['monthly_cost'] > 100: risk_score += 0.25
if patient_data['side_effect_count'] > 2: risk_score += 0.2
if patient_data['age'] < 30: risk_score += 0.15
return min(risk_score, 1.0)
Reminder Optimization
Reinforcement Learning for Timing
Multi-Channel Reminders
class ReminderOptimizer:
def optimize(self, patient, reminders):
best_channel = max(['sms', 'email', 'push', 'call'],
key=lambda c: self.response_rate(patient, c))
best_time = self._optimal_time(patient)
return {'channel': best_channel, 'time': best_time, 'frequency': self._frequency(patient)}