A level one trauma center reported positive feedback from community radiologists after implementing a simple peer learning program that allowed them to review report discrepancies flagged by specialists after patient transfers.
Previous studies suggest that the greatest error margins in radiology overreads happen between community radiologists (CRs) and subspecialty rads, with rates ranging between 13%-68%. Researchers at the University of Washington, where thousands of patients are transferred from outside facilities annually, decided to use these numbers as inspiration to create a peer learning program for that specific situation.
The researchers note that there is vast literature available on peer-to-peer learning opportunities but very little guidance pertaining to communicating discrepancies with peers from outside facilities.
“We sought to develop a novel model to address this particular scenario, with the goal of improving the quality of radiology practice in general by providing feedback from an outside observer who may have subspecialty experience that differs from that available in the community setting,” corresponding author Garvit D. Khatri, MBBS, with the Department of Radiology at the University of Washington in Seattle, and coauthors explained.
During the program’s implementation, radiologists prospectively reviewed thousands of CT and MRI reports and exams from outside facilities. If their findings differed from those of the original reader, the report was flagged, and a summary of the changes was added to the initial report. For reads that had significant discrepancies, a paper copy of the additional findings was sent via U.S. mail to the original CR for review.
Out of more than 9,000 reports reviewed, significant discrepancies were found in only 176 reads from 139 radiologists, who were later surveyed on the effectiveness of the feedback. Out of those who completed the survey, 85% reported agreement with the overread and 88% supported the continuance of the program.
“We observed that the significant errors encountered were committed by a broad range of readers, rather than a few underperforming radiologists,” the authors disclosed. “This emphasizes the importance of peer learning for all radiologists.”
The authors suggest their model could be beneficial to other institutions that receive many patient transfers and may also be dealing with discrepancies.
You can view the full study in Current Problems in Diagnostic Radiology.
In addition to her background in journalism, Hannah also has patient-facing experience in clinical settings, having spent more than 12 years working as a registered rad tech. She joined Innovate Healthcare in 2021 and has since put her unique expertise to use in her editorial role with Health Imaging.