Peer Review: A Better Way

Peer Learning Through Multi-Institutional Case Conferences: Abdominal and Cardiothoracic Radiology Experience

RATIONALE AND OBJECTIVES

We describe a model of multi-institutional, multisociety, online case conferences that is a case-based group discussion of selected (nonrandom) cases which are subsequently hosted on social media and online platforms (e.g., YouTube, websites) to be available for a wider audience.

MATERIALS AND METHODS

Using online conferencing software (Zoom, GoToMeeting), participants from both abdominal and cardiothoracic radiologists engage in separate, subspecialty one-hour meetings discussing a variety of meaningful cases. Participants take turns presenting their cases to the group and discuss significant findings, interpretations, differential diagnoses, and any other teaching points. All of the case conferences for both societies are recorded and edited to be uploaded on YouTube and their respective websites.

RESULTS

Participants from these conferences log in from 14 institutions in 7 states across the United States. The YouTube videos reach thousands of people around the world. The abdominal case conference on YouTube has received almost 1,300 views with 90 videos uploaded. The thoracic (the Society of Thoracic Radiology) case conference has been running for over 7 years, with 226 videos uploaded to YouTube and 38,200 views, 1426 subscribers, and a total watch time of over 525,800 minutes. Twitter has been utilized by both groups to promote online viewership.

CONCLUSION

Our model is feasible and effective compared to traditional peer review. The cases selected are deliberate and focused on quality improvement and/or education. We harness online engagement, specifically social media presence, which has opened new opportunities to educate our peers and reach a global audience, including the nonradiologic community, to learn about radiology and unique practices.

Perceptual and Interpretive Error in Diagnostic Radiology-Causes and Potential Solutions

Interpretation of increasingly complex imaging studies involves multiple intricate tasks requiring visual evaluation, cognitive processing, and decision-making. At each stage of this process, there are opportunities for error due to human factors including perceptual and ergonomic conditions. Investigation into the root causes of interpretive error in radiology first began over a century ago. In more recent work, there has been increasing recognition of the limits of human image perception and other human factors and greater acknowledgement of the role of the radiologist's environment in increasing the risk of error. This article reviews the state of research on perceptual and interpretive error in radiology. This article focuses on avenues for further error examination, and strategies for mitigating these errors are discussed. The relationship between artificial intelligence and interpretive error is also considered.