Spencer Dorn: Why AI Decision Support Must Integrate Local Clinical Context
Spencer Dorn, Executive Medical Director, UNC Faculty Physicians at The University of North Carolina at Chapel Hill, shared a post on LinkedIn:
“A healthy 29-year-old woman on oral contraceptives presents to an urgent care in Marlboro, NJ, with left calf swelling.
The NP immediately suspects a DVT and confirms it with a bedside ultrasound.
His AI app tells him to start anticoagulation and, given her possible family history of ‘clots,’ perform a further workup.
But it’s Sunday night – how does he get her anticoagulation quickly?
And she doesn’t have a PCP – who will she follow up with?
AI decision support is great for specific, evidence-based recommendations across a broad range of questions.
But real world practice is shaped by local factors, not just the published literature.
This app doesn’t know that this urgent care is part of a larger health system with a DVT clinic and an anticoagulation pharmacist.
The NP might know this DVT care pathway if he’s worked there long enough.
Or maybe he’ll stumble on the right SharePoint page.
But maybe he won’t.
Yes, tell us the right things to do for a hypothetical patient living anywhere.
But then make it more specific for a Sunday night in Marlboro.
Embedding local knowledge is the obvious next step to making these tools more useful and powerful.”
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