Whether you’re working towards stroke certification, trying to advance to the next certification level, or are a small rural healthcare facility, vRad’s Stroke Imaging Service of Excellence can help you reduce door-to-intervention times for your patients. vRad’s team delivers average stroke imaging turnaround times under 7 minutes on over 130,000 stroke studies annually with a 99.6% accuracy rate.
How we do it:
our highest priority
Stroke cases trigger alerts to every privileged radiologist. Studies are auto-assigned to the top of all available radiologists’ worklists and must be read next.
Boosted by AI
All non-contrast head CT studies pass through vRad’s AI model for ICH (over 2,200 studies per month). Positive cases are immediately boosted to stroke protocol.
Critical result calls
under 2 minutes
A call to the ordering physician is automatically triggered the moment Natural Language Processing identifies relevant stroke language in the radiologist dictation.
Because of our high volume of emergency department cases, every vRad neuro imaging specialist reads over 200 CTA Head and CT Perfusion studies each month on average, keeping skills sharp.
Augment your existing service with vRad to ensure certification standards are met during off-peak hours or in the event of a spike in demand.
Satisfy reporting requirements at every level of Joint Commission AHA/ASA certification with vRad’s monthly Teleradiology Metrics Report. vRad radiology reports include an ASPECTS score and the volume of acute parenchymal hemorrhage if present, meeting Comprehensive Stroke Center guidelines from The Joint Commission. vRad’s Stroke Committee meets quarterly to review new guidelines and actively monitor quality and performance metrics.
Neuroradiologist Joshua Morais, MD opened the next case on his vRad worklist one afternoon in 2019. The non-contrast head CT revealed acute intracranial hemorrhage. Dr. Morais reported his diagnosis to the ordering physician just 2.9 minutes after the images had been uploaded.
What Dr. Morais didn’t know at the time was that a proprietary vRad Radiology AI algorithm had identified the criticality of the patient’s case and elevated it to the top of his worklist. This enabled him to quickly deliver his findings — getting the patient to surgery an estimated 10 minutes faster with AI than the typical time. Read the full case study here.