Department of Social and Political Studies, University of Milan, Milan, Italy.
J Eval Clin Pract. 2012 Feb;18(1):82-8. doi: 10.1111/j.1365-2753.2011.01771.x. Epub 2011 Oct 17.
Diagnostic reasoning is a critical aspect of clinical performance, having a high impact on quality and safety of care. Although diagnosis is fundamental in medicine, we still have a poor understanding of the factors that determine its course. According to traditional understanding, all information used in diagnostic reasoning is objective and logically driven. However, these conditions are not always met. Although we would be less likely to make an inaccurate diagnosis when following rational decision making, as described by normative models, the real diagnostic process works in a different way. Recent work has described the major cognitive biases in medicine as well as a number of strategies for reducing them, collectively called debiasing techniques. However, advances have encountered obstacles in achieving implementation into clinical practice.
While traditional understanding of clinical reasoning has failed to consider contextual factors, most debiasing techniques seem to fail in raising sound and safer medical praxis. Technological solutions, being data driven, are fundamental in increasing care safety, but they need to consider human factors. Thus, balanced models, cognitive driven and technology based, are needed in day-to-day applications to actually improve the diagnostic process. The purpose of this article, then, is to provide insight into cognitive influences that have resulted in wrong, delayed or missed diagnosis.
Using a cognitive approach, we describe the basis of medical error, with particular emphasis on diagnostic error. We then propose a conceptual scheme of the diagnostic process by the use of fuzzy cognitive maps.
诊断推理是临床表现的一个关键方面，对护理质量和安全有重大影响。尽管诊断在医学中是基础，但我们对决定其过程的因素仍知之甚少。根据传统的理解，诊断推理中使用的所有信息都是客观的和逻辑驱动的。然而，这些条件并不总是满足的。虽然我们遵循规范模型中描述的理性决策制定，不太可能做出不准确的诊断，但实际的诊断过程以不同的方式运作。最近的研究描述了医学中的主要认知偏差，以及一些减少这些偏差的策略，统称为去偏技术。然而，在将这些技术应用于临床实践方面，已经遇到了一些障碍。
虽然传统的临床推理理解未能考虑到上下文因素，但大多数去偏技术似乎未能提高合理和安全的医疗实践。基于数据的技术解决方案是提高护理安全性的基础，但它们需要考虑人为因素。因此，需要在日常应用中使用基于认知和技术的平衡模型，以实际改善诊断过程。本文的目的是深入了解导致错误、延迟或遗漏诊断的认知影响。
我们使用认知方法描述了医疗错误的基础，特别强调了诊断错误。然后，我们通过使用模糊认知图来提出诊断过程的概念框架。
