Fundamentals of Diagnostic Error in Imaging

Abstract

Imaging plays a pivotal role in the diagnostic process for many patients. With estimates of average diagnostic error rates ranging from 3% to 5%, there are approximately 40 million diagnostic errors involving imaging annually worldwide. The potential to improve diagnostic performance and reduce patient harm by identifying and learning from these errors is substantial. Yet these relatively high diagnostic error rates have persisted in our field despite decades of research and interventions. It may often seem as if diagnostic errors in radiology occur in a haphazard fashion. However, diagnostic problem solving in radiology is not a mysterious black box, and diagnostic errors are not random occurrences. Rather, diagnostic errors are predictable events with readily identifiable contributing factors, many of which are driven by how we think or related to the external environment. These contributing factors lead to both perceptual and interpretive errors. Identifying contributing factors is one of the keys to developing interventions that reduce or mitigate diagnostic errors. Developing a comprehensive process to identify diagnostic errors, analyze them to discover contributing factors and biases, and develop interventions based on the contributing factors is fundamental to learning from diagnostic error. Coupled with effective peer learning practices, supportive leadership, and a culture of quality, this process can unquestionably result in fewer diagnostic errors, improved patient outcomes, and increased satisfaction for all stakeholders. This article provides the foundational elements for implementing this type of process at a radiology practice, with examples to help radiologists and practice leaders achieve meaningful practice improvement. ^©RSNA, 2018.

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