Quantifying random variability in decision-making in pediatric cardiac surgery

Kayla V. Dlugos HBASc , Mjaye Mazwi MD, MBChB , Marisa Signorile MMath , Chun-Po Steve Fan PhD , Patricia Trbovich PhD , Osami Honjo MD, PhD
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引用次数: 0

Abstract

Objective

Random variability in day-to-day decision-making referred to as “noise” is associated with variation that negatively affects both the reproducibility and quality of decision-making. Although well described in other fields, the prevalence and significance of noise in medical decision-making are understudied and largely unknown. The goal of this study was to quantify noise in medical decision-making using a noise audit.

Methods

A noise audit was completed by 71 (n = 71) Heart Centre staff at the Hospital for Sick Children and Seattle Children's Hospital and involved a series of cases and questions surrounding decisions commonly encountered in the care for patients with transposition of the great arteries and critical aortic stenosis. Entropy was used to quantify total variation in responses. Because absolute entropy was not immediately comparable across audit questions with a different number of prespecified options, we reported a standardized version of entropy, which was calculated by dividing the absolute entropy by its theoretical maximum for each case. To compare responses in easy to hard questions across years of experience (<10 years and >10 years) and role, we reported aggregate entropy ratios. Aggregate entropy ratios were calculated by first stratifying by group of comparison and then calculating the standardized entropy for each question and taking the average of standardized entropies for easy questions and hard questions. Finally, to determine the ratio (easy to hard), we divided the average standardized entropy of the easy questions by the average standardized entropy of the hard questions.

Results

The overall audit aggregate entropy ratio was 0.85 less than 1, indicating lower-complexity questions had less variation than higher-complexity questions. The aggregate entropy ratio for those with more than 10 years of experience was 0.8 and 0.87, respectively, for those with less than 10 years of experience. The aggregate entropy ratios for those in cardiac critical care, cardiology, and cardiovascular surgery were 0.85, 0.83, and 0.96, respectively.

Conclusions

Noise was pervasive in medical decision-making in the analysis of our responses to common medical decisions made for patients with congenital heart disease and can be quantified in a manner that facilitates comparisons.
量化儿童心脏手术决策中的随机变异性
目的日常决策中的随机变异性被称为“噪音”,与对决策的可重复性和质量产生负面影响的变化有关。虽然在其他领域有很好的描述,但噪音在医疗决策中的流行程度和重要性尚未得到充分研究,而且在很大程度上是未知的。本研究的目的是使用噪声审计来量化医疗决策中的噪声。方法对71例(n = 71)病童医院和西雅图儿童医院心脏中心工作人员进行噪声审计,对大动脉转位和主动脉瓣严重狭窄患者护理中常见的决策问题进行分析。熵被用来量化反应的总变异。由于绝对熵不能立即在具有不同数量的预先指定选项的审计问题之间进行比较,因此我们报告了熵的标准化版本,通过将绝对熵除以每种情况的理论最大值来计算。为了比较不同经验(<;10年和>;10年)和角色对简单和困难问题的回答,我们报告了总熵比。总熵比的计算方法是先进行分组比较分层,然后计算每个问题的标准化熵,对易题和难题取标准化熵的平均值。最后,我们用简单问题的平均标准化熵除以难问题的平均标准化熵来确定比率(易与难)。结果总体审计总熵比为0.85 < 1,说明低复杂度问题比高复杂度问题变异较小。10年以上从业人员的总熵比为0.8,10年以下从业人员的总熵比为0.87。心脏重症监护、心脏病学和心血管外科的总熵比分别为0.85、0.83和0.96。结论在分析我们对先天性心脏病患者的常见医疗决策的反应时,噪音在医疗决策中普遍存在,并且可以以一种便于比较的方式量化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.70
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