AI in Breast Health.
When the person who maintained Iowa Radiology's pick-list code left, a critical workflow was at risk. See how the team rebuilt it with AI, returned four hours a week to staff, and kept patient letters moving.
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Half a day back, every week.
A dozen or more patient letters came back wrong every week. Twenty minutes to fix each one, an addendum filed every time, and every letter proofed by hand before it went out.
Half a day
of tech and radiologist time handed back, every single week.
4 hrs weekly · 200+ hrs a year
One word should not break a patient letter.
Laterality, recommendation, and timeframe had to be dictated in the right order. If one word was wrong, staff fixed the letter by hand.
Illustration: a simulated report read-out. Four mammography reports are dictated in different words and different orders. Each time, the same four data points, laterality, recommendation, follow-up timeframe, and BI-RADS category, are extracted correctly, with no addendum required.
When the super user leaves
How Iowa Radiology rebuilt a workflow that depended on one person.
Pick lists versus natural dictation
How AI captures key details without rigid phrasing.
The cost of small fixes
How corrections, addenda, and IT tickets added up.
The BI-RADS 0 follow-up problem
How automated outreach and portal access replaced manual mail runs.
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See how Iowa Radiology rebuilt a workflow that depended on one person.
See it on your own workflows