- Design
- Retrospective before-and-after cohort with survival modelling
- Population
- 39,323 chest CT examinations in 19,433 patients at one Dutch tertiary centre
- Primary outcome
- Radiology reporting time
- Effect
- Median 21.3 to 18.2 minutes (14.6% reduction); adjusted HR 1.17 (95% CI 1.14 to 1.21)
A retrospective study in Radiology (1 September 2026) compared reporting times for 39,323 chest CTs in 19,433 patients at a Dutch tertiary centre before and after a commercial pulmonary nodule AI was introduced, adjusting for reader, examination type, location and requesting specialty.
After AI, adjusted median reporting time fell from 21.3 to 18.2 minutes, a 14.6% reduction. The effect varied: ECG-gated thoracic CTs fell by 41% and thoracic radiologists' times by 25%, but emergency department reports took 7% longer. The authors estimated a saving of about half a full-time radiologist at their volume.
A before-and-after design cannot rule out other changes over the same period. Still, it is rare to see AI's effect on workflow measured at this scale, and it shows the effect depends on who reads and what is being read.
- Expect time savings from nodule AI to vary by reader and examination type.
- Watch emergency reporting times after AI deployment; they lengthened here.
- Measure reporting time before and after any AI rollout in your own department.
- Do not budget staffing savings on vendor estimates alone.
Why it matters
Departments buying AI to save time now have a real-world benchmark, and a warning about acute work.
Don't overread it
A before-and-after comparison cannot separate the AI's effect from other changes over the study period.
The statistics, in plain English
A hazard ratio of 1.17 for report completion means reports were finished about 17% faster at any given moment after AI. The subgroup differences were planned, but each is less certain than the overall result.
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