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目测:通过观察外观来诊断“疾病”。

Eyeballing: the use of visual appearance to diagnose 'sick'.

机构信息

McMaster University, Hamilton, ON, Canada.

St Joseph's Healthcare, Hamilton, ON, Canada.

出版信息

Med Educ. 2017 Nov;51(11):1138-1145. doi: 10.1111/medu.13396. Epub 2017 Jul 31.

Abstract

CONTEXT

Prior studies suggest that clinicians can categorise patients in an emergency room as 'sick' or 'not sick' using rapid visual assessment. The rapid nature of these decisions suggests clinicians are relying on pattern recognition or System 1 processing; however, this has not been studied experimentally. In this study, we explore the accuracy of these decisions using patient disposition (discharge, admission to ward or admission to critical care) as an objective outcome, and collect evidence to argue for the use of System 1 processing in the 'sick' or 'not sick' decision process.

METHODS

Fourteen practising emergency physicians reviewed 25 videos of patients presenting to the emergency room. They were asked to predict patient disposition (discharge, admission to ward or admission to critical care) and estimate whether they were 'sick' or 'not sick' using a continuous slider on a 'sick' scale from 'not sick' (0) to 'sick' (100). We collected decision time and asked physicians to identify how they came to the decision using a continuous slider on a 'system processing' scale from 'knew immediately' (0) to 'deliberated intently' (1).

RESULTS

Inter-rater reliability judging 'sick' was computed as an intraclass correlation coefficient (ICC) of 0.54. Agreement among physicians in predicting disposition was 68% with ICC of 0.44, and accuracy at predicting disposition was 55%. Physicians made their decision in an average of 10 - 11 seconds and rated 70% of their decisions as < 0.5 on the scale from 'knew immediately' (0) to 'deliberated intently' (1).

CONCLUSIONS

Experienced emergency physicians are able to visually assess patients rapidly and predict disposition in a very short time, albeit with fair reliability and lower accuracy than reported previously. Subjectively, they reported that the majority of decisions were on the side of 'knew immediately', consistent with the application of System 1 processing.

摘要

背景

先前的研究表明,临床医生可以使用快速视觉评估将急诊科的患者分为“病”或“非病”两类。这些决策的快速性质表明临床医生依赖于模式识别或系统 1 处理;然而,这尚未通过实验研究证明。在这项研究中,我们使用患者的处置(出院、住院或转入重症监护病房)作为客观结果来探索这些决策的准确性,并收集证据支持在“病”或“非病”决策过程中使用系统 1 处理。

方法

14 名执业急诊医生查看了 25 名急诊科就诊患者的视频。他们被要求预测患者的处置(出院、住院或转入重症监护病房),并使用从“非病”(0)到“病”(100)的连续滑块在“病”量表上估计他们是否“病”。我们收集了决策时间,并要求医生使用从“立即知道”(0)到“深思熟虑”(1)的连续滑块在“系统处理”量表上标识他们是如何做出决策的。

结果

判断“病”的组内相关系数(ICC)为 0.54。医生预测处置的一致性为 68%,ICC 为 0.44,预测处置的准确性为 55%。医生平均在 10-11 秒内做出决策,70%的决策在从“立即知道”(0)到“深思熟虑”(1)的连续滑块上的评分<0.5。

结论

经验丰富的急诊医生能够快速对患者进行视觉评估,并在非常短的时间内预测处置情况,尽管可靠性一般,准确性低于先前报道。主观上,他们报告说大多数决策都偏向“立即知道”,这与系统 1 处理的应用一致。

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