AI-Powered COVID-19 Solution to Analyze Chest-CT Scans Reduces Turnaround Time, Finds Large-Scale Study

A large-scale multi-medical center study has found that an AI-powered COVID-19 solution reduces report turnaround time by 30%.

Moscow Diagnostics and Telemedicine Center (Moscow, Russia) and RADLogics Inc. (New York, NY, USA) have shared the results of a large-scale study which found that the introduction of RADLogics’ AI-Powered solution into radiology workflow to analyze chest-CT scans during the COVID-19 pandemic reduced report turnaround time by an average of 30%, which is equivalent to 7 minutes per case. The extensive research included a total of 128,350 chest-CT scans, out of which 36,358 were processed by RADLogics AI-Powered COVID-19 solution, reported by 570 participating radiologists at over 130 hospitals and outpatient clinics in Moscow.

The study found that report turnaround time was significantly shorter for all time periods in a group of radiologists with available AI results that were seamlessly integrated into radiologists’ current workflow, compared to a group with non-available AI results. In addition, in the shift between the two study time periods, additional clinical parameters were added to the standard of care, including the addition of a disease severity score. The added information created an increased workload on radiologists, which increased the average read time by more than 25%. In response, the RADLogics AI-Powered COVID-19 solution was enhanced to support the new clinical requirements. Results shown indicate that with the augmented AI solution, including all clinical measurements and severity scoring, was able to maintain the overall productivity gain of 30%.

“In addition to finding that the integration of AI did not have a negative effect on the interpretation or report accuracy, our researchers found a significant improvement in productivity and report turnaround time by the expert radiologists that leveraged AI,” said Dr. Sergey Morozov, MD, PhD, MPH, who serves as CEO of Moscow Diagnostics and Telemedicine Center.

“This study – first of its kind in its scale – demonstrates the full potential of AI as a tool to augment radiologists to increase throughput, improve efficiency and reduce time-to-treatment,” said Moshe Becker, CEO and Co-Founder of RADLogics. “This research provides large-scale clinical validation to an earlier academic study by UCLA that was published in Academic Radiology, which conducted a time-motion study using our AI-powered solution to measure the impact of our solution on radiologists’ productivity that found out using our solution saved up to 44% in radiologists’ reading time.”

“In the near-term, responsive and scalable AI algorithms could play a critical role as healthcare systems across the world contend with potential coronavirus surges as new variants spread – not to mention the tremendous burnout and economic pressures across the healthcare sector,” added Becker. “In the long-term, this groundbreaking research also illustrates the tremendous benefit of adopting robust AI platforms that can be deployed rapidly at scale and seamlessly integrated into existing workflows to augment radiology teams.”

Related Links:
Moscow Diagnostics and Telemedicine Center
RADLogics Inc.