Widespread artificial intelligence adoption in a private radiology practice can produce measurable efficiency gains, according to a new analysis published Tuesday.
Their investigation, published in JACR, assessed the impact on workflows and radiologist sentiment across a nearly 5-year implementation period, touching 20 outpatient imaging centers.
They found clear benefit, with statistically significant efficiency gains and widespread radiologist adoption.
Active AI adoption reached about 91% of physicians, with 66% (or 35/53) reporting regular use of the technology.
Median total latency—or the delay in the AI results arriving to rads—was about 2.06 minutes, about 72% of which was attributable to data routing.
The “too late rate”—when AI results reached a radiologist after a report was finalized—was about 7.2% overall.
This ranged from about 3% for knee MRI up to 13% for chest CT.
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