When a healthcare AI system should be paused
By ChatGPT Health. Educational synthesis prepared with AI assistance. Sources checked September 28, 2026. Clinically reviewed by Harvey Castro, MD, MBA, on September 28, 2026. Approved as educational content. This page is not a clinical protocol or a claim of independent clinical peer review.
A monitoring plan needs an action path. Decide who can pause a system, what happens to affected work, and what evidence is needed before use resumes.
Define triggers before deployment
NIST describes monitoring, incident response, recovery and decommissioning within its voluntary risk management playbook. NIST AI RMF Playbook: Manage. For a healthcare program, translate those concepts into the specific clinical and operational workflow. There is no universal numeric threshold that makes every system safe.
Our trigger checklist
Ask the accountable clinical, security and operational owners to define thresholds for:
- A serious unexpected error or a credible pattern of near misses.
- Output reaching the wrong patient, user or record.
- Loss of required human review or inability to use the fallback.
- A privacy or security incident affecting the workflow.
- A material change in inputs, model version, integration or intended use.
- Worsening performance or unequal effects in a relevant patient group.
Contain the problem without losing the record
Make the fallback available. Preserve relevant versions, timestamps and approved incident evidence. Use established privacy and security procedures when collecting records. Assign responsibility for reviewing affected work and communicating through the appropriate institutional channels. Pausing a model does not automatically correct decisions already made.
Set restart conditions
Document the failure, the corrective change, the evaluation results and the remaining uncertainty. Test the revised workflow and its fallback before resuming. The same person who sells or develops the product should not be the only source of reassurance. Restart authority and post restart monitoring belong in the original governance plan.
Use incidents to improve the system
Review staffing, interface, training and data quality alongside the algorithm. A problem attributed to user error may expose an unrealistic review burden or confusing handoff. Track corrective actions to completion rather than treating incident reporting as the endpoint.
Sources and further reading
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