Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach.
Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach.
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DOI：
10.1186/s12871-021-01548-7
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发表时间：
2022-01-04
影响因子：
2.2
通讯作者：
Pickering BW
中科院分区：
文献类型：
--
作者：
Park J;Zhong X;Dong Y;Barwise A;Pickering BW
ICU 操作条件可能会导致认知超负荷并对临床决策产生负面影响。我们的目的是开发一个定量模型来研究操作条件与药物订单数量之间的关联，作为多学科护理团队认知能力的可衡量指标。使用 2016 年 2 月至 2018 年 3 月期间明尼苏达州罗切斯特市 Mayo Clinic 的一个医疗 ICU (MICU) 患者的时间数据。该数据集总共包括 4822 名入住 MICU 的独特患者以及总共 6240 名 MICU 入院患者。在患者安全系统工程倡议模型的指导下，确定了可从电子病历中获得的量化措施，并开发了 ICU 分布式认知的概念框架。建立单变量分段泊松回归模型来研究系统级工作量指标之间的关系，包括患者普查和患者特征（疾病严重程度、新入院和死亡风险）与药物订单数量之间的关系，作为护理团队决策的输出。使用广义F检验比较回归模型获得的不同线段的系数，我们发现，当ICU占用率超过50%时（患者普查> 18），每个患者每小时的用药订单数显着减少（平均值 = 0.74；标准差（SD） = 0.56 vs 平均值 = 0.65； SD = 0.48；p < 0.001）。下降更为明显（平均 = 0.81；SD = 0.59 vs. 平均 = 0.63；SD = 0.47；p < 0.001），当住院期间需要有创机械通气的重症患者较多时，断点转移到较低的患者普查（16 名患者），这可能会在住院期间遇到。 ICU 治疗 COVID-19 患者。我们的模型表明，ICU 操作因素（例如入院率和患者病情严重程度）可能会影响重症监护团队的认知功能，并导致药物订单产生的变化。该分析的结果凸显了提高护理团队的情境意识的重要性，以发现并应对 ICU 中可能导致认知超负荷的不断变化的环境。在线版本包含可在 10.1186/s12871-021-01548-7 获取的补充材料。
ICU operational conditions may contribute to cognitive overload and negatively impact on clinical decision making. We aimed to develop a quantitative model to investigate the association between the operational conditions and the quantity of medication orders as a measurable indicator of the multidisciplinary care team’s cognitive capacity. The temporal data of patients at one medical ICU (MICU) of Mayo Clinic in Rochester, MN between February 2016 to March 2018 was used. This dataset includes a total of 4822 unique patients admitted to the MICU and a total of 6240 MICU admissions. Guided by the Systems Engineering Initiative for Patient Safety model, quantifiable measures attainable from electronic medical records were identified and a conceptual framework of distributed cognition in ICU was developed. Univariate piecewise Poisson regression models were built to investigate the relationship between system-level workload indicators, including patient census and patient characteristics (severity of illness, new admission, and mortality risk) and the quantity of medication orders, as the output of the care team’s decision making. Comparing the coefficients of different line segments obtained from the regression models using a generalized F-test, we identified that, when the ICU was more than 50% occupied (patient census > 18), the number of medication orders per patient per hour was significantly reduced (average = 0.74; standard deviation (SD) = 0.56 vs. average = 0.65; SD = 0.48; p < 0.001). The reduction was more pronounced (average = 0.81; SD = 0.59 vs. average = 0.63; SD = 0.47; p < 0.001), and the breakpoint shifted to a lower patient census (16 patients) when at a higher presence of severely-ill patients requiring invasive mechanical ventilation during their stay, which might be encountered in an ICU treating patients with COVID-19. Our model suggests that ICU operational factors, such as admission rates and patient severity of illness may impact the critical care team’s cognitive function and result in changes in the production of medication orders. The results of this analysis heighten the importance of increasing situational awareness of the care team to detect and react to changing circumstances in the ICU that may contribute to cognitive overload. The online version contains supplementary material available at 10.1186/s12871-021-01548-7.
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DOI：
10.1016/j.ijmedinf.2007.04.008
发表时间：
2008-04-01
影响因子：
4.9
作者：
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