How to review a healthcare AI pilot before expanding it
Define the task, measure the errors that matter and make it easy for staff to flag poor results.
Describe one intended use
State who uses the tool, which workflow it supports, and where a person reviews the output. A pilot for organizing incoming messages has different consequences from a system that informs a clinical decision. Define what the pilot may process and what it must leave to staff.
Measure performance on local cases
Use appropriately approved data or representative synthetic examples. Include routine requests, ambiguous inputs and examples from workflows that differ across sites or teams. Record the errors reviewers consider serious and how much extra time it takes to correct them.
Assign a way to report problems
Give staff a clear place to report inaccurate output and a way to pause the workflow. Keep a record of the system version, settings and conditions in which the problem occurred. Use those details to decide what to retest when the tool changes.
Use a review framework
NIST's voluntary AI Risk Management Framework organizes work around governance, mapping, measurement and management. Apply those ideas to the pilot by writing down who owns the decision, what evidence is needed for expansion, and when the team will reevaluate it.