Waite Stephen, Scott Jinel, Gale Brian, Fuchs Travis, Kolla Srinivas, Reede Deborah
1 Department of Radiology, SUNY Downstate Medical Center, 450 Clarkson Ave, Brooklyn, NY 11203.
AJR Am J Roentgenol. 2017 Apr;208(4):739-749. doi: 10.2214/AJR.16.16963. Epub 2016 Dec 27.
Although imaging technology has advanced significantly since the work of Garland in 1949, interpretive error rates remain unchanged. In addition to patient harm, interpretive errors are a major cause of litigation and distress to radiologists. In this article, we discuss the mechanics involved in searching an image, categorize omission errors, and discuss factors influencing diagnostic accuracy. Potential individual- and system-based solutions to mitigate or eliminate errors are also discussed.
Radiologists use visual detection, pattern recognition, memory, and cognitive reasoning to synthesize final interpretations of radiologic studies. This synthesis is performed in an environment in which there are numerous extrinsic distractors, increasing workloads and fatigue. Given the ultimately human task of perception, some degree of error is likely inevitable even with experienced observers. However, an understanding of the causes of interpretive errors can help in the development of tools to mitigate errors and improve patient safety.
尽管自1949年加兰的研究工作以来，成像技术有了显著进步，但解读错误率仍未改变。除了对患者造成伤害外，解读错误是导致诉讼以及给放射科医生带来困扰的主要原因。在本文中，我们讨论图像搜索所涉及的机制，对漏诊错误进行分类，并探讨影响诊断准确性的因素。还讨论了基于个人和系统的潜在解决方案，以减轻或消除错误。
放射科医生使用视觉检测、模式识别、记忆和认知推理来综合放射学研究的最终解读。这种综合是在一个存在众多外在干扰因素、工作量不断增加且疲劳感上升的环境中进行的。鉴于感知最终是一项人为任务，即使是经验丰富的观察者也可能不可避免地出现一定程度的错误。然而，了解解读错误的原因有助于开发减轻错误并提高患者安全的工具。
