Human Factors in Healthcare AI Adoption

A model can perform well in a test and still be difficult to use inside a real healthcare task. People need to understand what the system did, what information it used and when the output requires closer review.

Human-factors work examines the AI-assisted step in context. It looks at workload, interruptions, handoffs, terminology, accessibility and the consequences of accepting, correcting or ignoring an output.

Human review must be a usable interaction, not only a statement in a policy. The interface should make uncertainty, source information, exceptions and escalation paths visible at the moment a decision is made.

A pilot should observe how representative users actually work with the system. Useful measures may include completion, corrections, overrides, time on task, failure recovery and whether the workflow creates new work elsewhere.

These findings belong in product requirements and acceptance criteria. Adoption is easier to evaluate when the expected user behaviour and support model are defined before rollout.