Preventing PHI Leaks in Clinical AI

Ambient scribes, clinical copilots, and patient chatbots move protected health information through prompts, model responses, and third-party APIs every minute. Legacy DLP was built for email and file transfers, not for conversational AI or MCP tool calls. PointGuard AI applies PHI-aware data protection at each AI interaction point so clinical teams can use AI while patient data stays within approved, governed workflows.

PHI now travels through AI channels that existing data controls were never designed to inspect.

• Clinicians paste notes, images, and lab results into AI assistants.
• Scribes and copilots send encounter data to third-party model APIs.
• Patient chatbots can reveal another patient's information in a response.
• Agent tools can retrieve more of the record than a task requires.

AI Data Protection, Runtime Guardrails, and MCP Security Gateway enforce PHI policies across clinical AI workflows.

1. Define protected data. Use built-in detectors for the HIPAA identifiers, medical record numbers, diagnoses, and medications. Add organization-specific identifiers and set permitted destinations for each AI application.

2. Inspect every interaction. Scan prompts, responses, and governed MCP tool calls for PHI at sub-100 ms latency, so clinical workflows are not slowed.

3. Redact or block exposure. Mask PHI when work can safely continue, and block interactions that would send it to an unapproved model, vendor, or user.

4. Record enforcement evidence. Log detections and actions for privacy officers and incident response teams. Map events to HIPAA and HITECH obligations to support breach assessment and audit.

• OWASP Top 10 for LLMs: LLM02 Sensitive Information Disclosure and LLM06 Excessive Agency, covering PHI disclosed through model interactions and agents reaching beyond the minimum necessary.
• OWASP Top 10 for Agentic Applications: ASI02 Tool Misuse and Exploitation and ASI03 Identity and Privilege Abuse, addressing agents that misuse tools or authority to retrieve and transmit patient data.
• NIST AI RMF: MAP identifies PHI flows; MEASURE evaluates exposure; MANAGE applies controls; GOVERN assigns privacy ownership.