Satisfaction is not a safety case
A positive rating can reflect convenience, novelty, bedside interaction, or a useful result. It cannot by itself establish calibration, informed consent, fairness, privacy, or safe escalation when the system is wrong.
Researchers should specify which patient factor they are measuring, why it matters to the clinical outcome, and how the measure changes design or deployment decisions.
Late feedback produces early blind spots
When patients enter mainly during validation, their role is to react to a system whose objectives, interface, data, and workflow are already established. That is too late to prevent many avoidable failures.
Patient representatives should help define acceptable error, explanations, privacy boundaries, accessibility, refusal, and human escalation before development choices harden into the product.
Go to the source
Read the evidence behind this analysis. External links open in a new tab.
Nature Health — Patient factors in medical artificial intelligence
