Scenario-based governance case

Patient-facing Chatbot Consent and Safety Governance

Post-market decision state: Conditional approval

Problem

A healthcare organization launches a patient-facing chatbot for symptom queries, follow-up preparation, and general health information. Some patients believe the chatbot is a formal medical service and stop medication or delay care based on its responses.

Key risks

Governance mechanism

  1. Before first use, a layered consent notice states the AI’s identity, purpose, limitations, data handling, opt-out rights, and human support channels.
  2. The chatbot must not provide definitive diagnoses or medication cessation instructions, and must not present itself as replacing a clinician.
  3. Red flags (chest pain, stroke signs, suicidal ideation, severe allergic reaction) stop normal conversation and escalate immediately to human staff.
  4. High-risk outputs carry a fixed safety message; all interactions, alerts, and human takeover times are logged.

RACI

Responsible: clinical safety lead (safety rules); IT and vendor (consent flow, red-flag triggers, logging, escalation). Accountable: clinical governance committee. Consulted: doctors, nurses, legal and compliance, data protection officer, patient representatives, accessibility specialists. Informed: patients, hospital management, frontline teams.

Audit evidence

Consent notice versions, patient acknowledgements, privacy notice, prompt and output logs, red-flag trigger records, escalation timestamps, human takeover records, complaints, safety testing reports, monthly incident review.

Lesson

The core question is not how many questions the chatbot can answer, but whether patients clearly understand it is not a doctor. Effective consent must change system behaviour, not just appear once on an opening page. When the system meets high-risk symptoms, the most important capability is to stop and hand over.