Inside 847 Production Clinical AI Notes — Sebastian Fox, Composo
Sebastian Fox from Composo analyzed clinical notes from AI tools that automatically write patient notes (known as ambient scribes).
He found that approximately one in twenty notes contained errors severe enough to harm patients, nearly one in five had important missing information, and more than one in ten contained fabricated information. Even when he built an advanced checker model to catch these errors, one-fifth of problematic notes still passed through. The biggest challenge is determining which differences between recordings and notes actually matter medically — a missing date may be insignificant, but missing symptoms such as jaw pain combined with new headache in patients over 50 could indicate a serious vision-threatening diagnosis.
Vibekollen prepared this summary with AI from the original publication. The content belongs to AI Engineer.
