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Cognitive and system factors contributing to diagnostic errors in radiology

机译:导致放射学诊断错误的认知和系统因素

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OBJECTIVE. In this article, we describe some of the cognitive and system-based sources of detection and interpretation errors in diagnostic radiology and discuss potential approaches to help reduce misdiagnoses. CONCLUSION. Every radiologist worries about missing a diagnosis or giving a falsepositive reading. The retrospective error rate among radiologic examinations is approximately 30%, with real-time errors in daily radiology practice averaging 3-5%. Nearly 75% of all medical malpractice claims against radiologists are related to diagnostic errors. As medical reimbursement trends downward, radiologists attempt to compensate by undertaking additional responsibilities to increase productivity. The increased workload, rising quality expectations, cognitive biases, and poor system factors all contribute to diagnostic errors in radiology. Diagnostic errors are underrecognized and underappreciated in radiology practice. This is due to the inability to obtain reliable national estimates of the impact, the difficulty in evaluating effectiveness of potential interventions, and the poor response to systemwide solutions. Most of our clinical work is executed through type 1 processes to minimize cost, anxiety, and delay; however, type 1 processes are also vulnerable to errors. Instead of trying to completely eliminate cognitive shortcuts that serve us well most of the time, becoming aware of common biases and using metacognitive strategies to mitigate the effects have the potential to create sustainable improvement in diagnostic errors.
机译:目的。在本文中,我们描述了诊断放射学中检测和解释错误的一些认知和基于系统的来源,并讨论了有助于减少误诊的潜在方法。结论。每个放射线医师担心会错过诊断或给出错误的阳性读数。放射检查之间的追溯错误率约为30%,而日常放射实践中的实时错误平均为3-5%。在所有针对放射科医生的医疗事故索赔中,将近75%与诊断错误有关。随着医疗费用的下降趋势,放射科医生试图通过承担额外的责任来提高生产率来进行补偿。工作量的增加,对质量的期望不断提高,认知偏见以及不良的系统因素都导致放射学的诊断错误。在放射学实践中,诊断错误未被充分认识和重视。这是由于无法获得有关影响的可靠的国家估算,难以评估潜在干预措施的有效性以及对全系统解决方案的反应较差。我们的大多数临床工作都是通过1型流程执行的,以最大程度地降低成本,焦虑和延迟。但是,类型1进程也容易出错。与其尝试完全消除大多数时候对我们有用的认知捷径,不如意识到常见的偏见并使用元认知策略来减轻这种影响,有可能在诊断错误方面带来可持续的改善。

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