Healthcare organizations want AI agents for coding, documentation, and workflow automation—but face significant compliance challenges. How do you leverage powerful AI capabilities while maintaining HIPAA compliance and protecting PHI?
The answer lies in specialized gateway architectures that create secure boundaries between your protected data and AI services, enabling productive use while maintaining audit trails and compliance controls.
Automatically strip or mask PHI before data reaches external AI services.
Pattern-based PII/PHI detection
Reversible tokenization for response rehydration
Audit logging of all transformations
Configurable rules by data type and context
Self-hosted or BAA-covered AI services within your compliance boundary.
Azure OpenAI with BAA
AWS Bedrock (Claude) with compliance controls
Google Vertex AI with healthcare certifications
Self-hosted open-source models
Generate compliant synthetic datasets for AI training and testing.
Statistically representative fake data
Maintains data relationships without PHI
Useful for development and testing environments
Enables AI experimentation without risk
Process data locally while leveraging cloud AI capabilities.
Local model inference on sensitive data
Cloud models for non-PHI tasks only
Hybrid architecture with clear boundaries
Model updates without data exposure
Major AI platforms offer varying levels of healthcare compliance support:
Microsoft offers BAAs for Azure OpenAI. Data processed in your Azure tenant with enterprise compliance controls.
HIPAA BAA Available
Anthropic's Claude available through AWS with existing healthcare compliance frameworks and BAAs.
HIPAA Eligible via AWS
Gemini models through Vertex AI with Google Cloud's healthcare and life sciences compliance certifications.
Healthcare API Available
Every AI interaction involving potential PHI must be logged with user identity, timestamp, data accessed, and AI responses. Design your gateway to capture comprehensive audit data.
Understand where your data is processed and stored. Some AI services may route through multiple regions. Gateway architectures should enforce data residency requirements.
Ensure your AI provider does not use your data for model training. Enterprise agreements typically include data usage restrictions—verify this explicitly.
Design prompts and workflows to use only the minimum PHI necessary for the task. Gateway rules should enforce data minimization automatically.
AI-assisted note generation, discharge summaries, and clinical correspondence with PHI sanitization gateways.
Development teams using AI coding assistants with gateways that prevent accidental PHI exposure in prompts.
Population health analytics and reporting with synthetic data generation for AI-powered insights.
I help healthcare organizations design and implement compliant AI architectures:
Gateway architecture design tailored to your compliance requirements
Platform selection and BAA evaluation
Implementation guidance for sanitization and audit systems
Developer training on compliant AI usage patterns