Yesudian Rohan I, Yesudian Paul D
Department of Medicine, University of Cambridge, Cambridge, UK.
Department of Dermatology, Wrexham Maelor Hospital, Wrexham, UK.
Int J Dermatol. 2023 Feb;62(2):137-142. doi: 10.1111/ijd.16348. Epub 2022 Jul 8.
Cognitive biases are a significant cause of medical error. They arise from "system 1" thinking, which depends on heuristics to make quick decisions in complex situations. Heuristics make us "predictably irrational," distorting our ability to accurately assess probabilities in clinical scenarios. It is well reported in the literature that metacognition, the art of reflecting on one's thought processes, is the optimal way to deal with cognitive biases. However, it is unclear how this can be consistently implemented in dermatological practice. Our debiasing attempts thus far have been sporadic at best. This article categorizes important cognitive biases according to each stage of the doctor-patient interaction (history taking, clinical examination, investigations, diagnosis, and management). We hope that providing this clinically relevant framework can foster metacognition and a platform for algorithmic debiasing. This will enable us to engage "system 2" (analytical thinking) in a targeted way, thereby avoiding excessive cognitive load. Organization-level interventions should also be implemented to free up the cognitive capacity of an individual and to enable them to employ system 2 thinking more regularly.
认知偏差是医疗差错的一个重要原因。它们源于“系统1”思维，这种思维依靠启发式方法在复杂情况下迅速做出决策。启发式方法使我们“可预见地不理性”，扭曲了我们在临床场景中准确评估概率的能力。文献中充分报道，元认知，即反思自己思维过程的艺术，是应对认知偏差的最佳方式。然而，目前尚不清楚如何在皮肤科实践中持续实施这一点。到目前为止，我们消除偏差的尝试充其量只是零星的。本文根据医患互动的每个阶段（病史采集、临床检查、检查、诊断和管理）对重要的认知偏差进行了分类。我们希望提供这个与临床相关的框架能够促进元认知，并为算法去偏提供一个平台。这将使我们能够有针对性地运用“系统2”（分析性思维），从而避免过度的认知负荷。还应实施组织层面的干预措施，以释放个人的认知能力，并使他们能够更经常地运用系统2思维。
