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Do We Know Why We Make Errors in Morphological Diagnosis? An Analysis of Approach and Decision-Making in Haematological Morphology

机译:我们知道为什么我们在形态学诊断中会出错吗?血液形态学方法与决策分析

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Background: The laboratory interpretation of blood film morphology is frequently a rapid, accurate, and cost-effective final-stage of blood count analysis. However, the interpretation of findings often rests with a single individual, and errors can carry significant impact. Cell identification and classification skills are well supported by existing resources, but the contribution and importance of other skills are less well understood. Methods: The UK external quality assurance group in haematology (UK NEQAS(H)) runs a Continued Professional Development scheme where large digital-images of abnormal blood smears are presented using a web-based virtual microscope. Each case is answered by more than 800 individuals. Morphological feature selection and prioritisation, as well as diagnosis and proposed action, are recorded. We analysed the responses of participants, aiming to identify successful strategies as well as sources of error. Findings: The approach to assessment by participants depended on the affected cell type, case complexity or skills of the morphologist. For cases with few morphological abnormalities, we found that accurate cell identification and classification were the principle requirements for success. For more complex films however, feature recognition and prioritisation had primary importance. Additionally however, we found that participants employed a range of heuristic techniques to support their assessment, leading to associated bias and error. Interpretation: A wide range of skills together allow successful morphological assessment and the complexity of this process is not always understood or recognised. Heuristic techniques are widely employed to support or reinforce primary observations and to simplify complex findings. These approaches are effective and are integral to assessment; however they may also be a source of bias or error. Improving outcomes and supporting diagnosis require the development of decision-support mechanisms that identify and support the benefits of heuristic strategies while identifying or avoiding associated biases. Funding: The CPD scheme is funded by participant subscription.
机译:背景:实验室对血膜形态的解释通常是快速,准确且经济高效的血液计数分析的最终阶段。但是,对结果的解释通常取决于一个人,而错误可能会产生重大影响。现有资源很好地支持了单元识别和分类技能,但是对其他技能的贡献和重要性却知之甚少。方法:英国血液学外部质量保证小组(UK NEQAS(H))实施了持续专业发展计划,该计划使用基于Web的虚拟显微镜呈现异常血液涂片的大型数字图像。每个案例都有800多个人回答。记录形态特征选择和优先次序,以及诊断和建议的措施。我们分析了参与者的反应,旨在确定成功的策略以及错误的来源。结果:参与者进行评估的方法取决于受影响的细胞类型,病例的复杂性或形态学家的技能。对于形态学异常少的病例,我们发现准确的细胞鉴定和分类是成功的基本要求。但是,对于更复杂的电影,特征识别和优先级排序至关重要。然而,此外,我们发现参与者采用了一系列启发式技术来支持他们的评估,从而导致相关的偏见和错误。解释:广泛的技能结合在一起可以成功进行形态评估,并且此过程的复杂性并不总是被理解或认识到。启发式技术被广泛采用以支持或加强主要观察结果并简化复杂的发现。这些方法是有效的,是评估不可或缺的;但是它们也可能是偏差或错误的来源。改善结果并支持诊断需要开发决策支持机制,以识别和支持启发式策略的好处,同时识别或避免相关的偏见。资助:CPD计划由参与者订阅资助。

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