Clinical AI explainability: why clinicians ignore alerts
Why do clinical decision support tools with strong validation scores get ignored on the ward? The position here is that the blocker is calibration and explainability, not model accuracy. A model that is right 94 percent of the time gives the clinician a lifetime average, not a way to judge the single alert in front of them. Epic's sepsis prediction model, and the external Michigan study that found missed cases and false alarms, is the worked example of how that ends in alert fatigue.
You come away with two design rules for clinical AI screens, a way to read OpenAI's medical benchmark claims…
The skinny
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