Clinical Safety Boundaries for AI in Healthcare
Clinical Safety Boundaries for AI in Healthcare
Clinical safety boundaries define what AI can support and what must remain under qualified professional judgment. In healthcare, AI may help draft, summarize, organize, compare, and prepare information, but it should not independently diagnose, prescribe, triage, approve treatment, or make patient-specific care decisions.
The purpose of clinical safety boundaries is to protect patients, staff, organizations, and trust. AI output should be treated as draft support until it has been checked against source material, clinical context, policy, and professional review.
AI Can Support These Clinical-Adjacent Workflows
- Organizing approved patient education drafts for review
- Summarizing source material for professional checking
- Creating checklists or intake-support drafts
- Preparing documentation-support language
- Helping staff review policies, workflows, and training materials
- Flagging information that may need human review
AI Should Not Independently Do These Things
- Diagnose a patient
- Prescribe or recommend treatment without professional review
- Determine urgency or triage without approved oversight
- Approve clinical documentation or patient instructions
- Replace licensed clinical judgment
- Send high-risk patient-facing advice without review
Clinical Safety Review Questions
- Could this output affect patient understanding, care, or safety?
- Is the output grounded in approved source material?
- Who is qualified to review this output?
- What should trigger escalation?
- Could the AI output be incomplete, misleading, or too confident?
- How will final approval be documented?