HIPAA-Compliant Patient Risk Stratification Model

Design a Python machine learning pipeline using scikit-learn and pandas that predicts high-risk patient cohorts for preventative interventions, while maintaining strict HIPAA data anonymization protocols. The model should incorporate features like age, chronic condition history, medication adherence, and recent diagnostic markers. Implement differential privacy techniques to protect individual patient identities and generate risk scores with 85%+ accuracy. Include comprehensive error handling and logging mechanisms for medical compliance tracking.