Healthcare SaaS · Patient support AI

Healthcare platform intercepted 23 PHI disclosures before patient inbox delivery

Published May 10, 2026

The problem

The customer ran an AI-powered patient support bot that answered queries about appointments, prescriptions, and care plans. During a routine compliance review, the security team discovered that the model occasionally echoed back SSNs, DOBs, and partial MRN numbers extracted from the patient record context window — exactly the kind of disclosure that triggers HIPAA §164.514 notification requirements.

The risk

A single unprotected PHI disclosure to the wrong patient inbox constitutes a HIPAA reportable breach. At $100–$50,000 per violation under HHS Office for Civil Rights enforcement, and with a patient population of 200,000+, the risk exposure was material.

Implementation

Signed a BAA with DataVibe. Deployed the gate at the patient message delivery layer: every bot reply is routed through POST /v1/gate/outbound before the sendgrid send call. The workspace policy uses the healthcare-safeguards bundle: PHI regex (SSN pattern, MRN pattern, DOB combos), a personal_data_reference denylist, and a HIPAA_DIAGNOSIS WARN rule. All BLOCKED and QUEUED decisions are written to the tamper-evident audit chain and exported weekly to the compliance officer.

What changed

• 23 PHI disclosure incidents blocked in the first 30 days.
• Zero HIPAA reportable incidents since deployment.
• Audit log exported to compliance weekly — 100% traceability on every bot reply.
• HITL escalation path: high-severity PHI intercepts route to the patient services lead within 4 hours.

Patient support bot — before and after DataVibe

// Before: bot reply sent directly to patient inbox
await sendgrid.send({
  to: patient.email,
  subject: "Re: Your appointment inquiry",
  html: botGeneratedReply,  // ← PHI may be present
});

// After: intercept before dispatch
import { DataVibeClient } from "@datavibe.cc/sdk";

const dv = new DataVibeClient({ apiKey: process.env.DATAVIBE_API_KEY });

const result = await dv.intercept({
  recipient: patient.email,
  subject: "Re: Your appointment inquiry",
  body_html: botGeneratedReply,
  source_model: "claude-3-haiku",
  metadata: { patient_id: patient.id, bot_session: sessionId },
});

if (result.status === "BLOCKED") {
  // PHI detected — never sent. Log and escalate.
  await escalateToClinicalOps(patient.id, result.policy_violations);
  return;
}

if (result.status === "QUEUED") {
  // WARN rule fired (e.g. diagnosis language) — human reviews within 4h
  await notifyPatientServicesLead(result.review_url!);
  return;
}

// SENT — all controls passed, patient message delivered