The thing that should stop a refill usually does not arrive through the system that processes the refill.
A patient mentions a new symptom during an outreach call about something else. A caregiver phones in a change nobody has entered yet. Someone calls to move an appointment and says something that does not match what is in the chart.
None of that is a device signal. There is no output to review, no confidence score, nothing flagged. The system processing the refill cannot see any of it, and no amount of logging what the reviewer did with the output would surface it, because the reviewer never saw it either.
It reached a person on a phone call about something else.
That is one of two ways this happens. Information arrives on a channel the system is not watching, which is the refill case. Or it sits with someone the system is not connected to, a specialist, a pharmacy, a family member, who knows something relevant and has no path into the record.
Either way the system is operating on a complete picture of everything it can see, which is always a subset of the full picture.
Someone will point out that this closes with better integration, and that is partly right. Every feed you connect moves the boundary outward. But the boundary moves, it does not close. There is always a current edge, and the organization is always living on whichever side of it has not been staffed.
I raised this with the FDA last week in our comment on generative AI devices. Most of the postmarket conversation is about what the reviewer does with the output. We argued that oversight adequacy is also a question of what channels are staffed around the system, not only what happens at the review step. A question in the comments on that post pushed me to say it more plainly, which is what this is.
So when the question is what a human is actually for in an AI workflow, the review step is the easy answer and the smaller one.
The larger one is that organizations run on information that never enters the system at all. Somebody has to be positioned to hear it, trained to recognize that it matters, and authorized to route it.
That is not a review function. It is a coverage question, and most AI implementations never ask it.
Xillium keeps human accountability present across the channels and handoffs AI-supported workflows cannot see. What that looks like in practice is on our Solutions page.
