HIPAA-Compliant Patient Risk Stratification Pipeline

Design a comprehensive Python data pipeline that anonymizes patient medical records while performing predictive risk stratification for chronic disease management. Implement differential privacy techniques using PySyft to ensure HIPAA compliance. The solution should handle structured EHR data from multiple hospital systems, integrate with scikit-learn for machine learning models, and generate risk scores with a confidence interval. Include robust error handling for protected health information (PHI) and create a modular architecture that can scale to millions of patient records.