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利用电子健康记录中的元数据描述重症监护病房查房团队。

Characterizing intensive care unit rounding teams using meta-data from the electronic health record.

机构信息

CRISMA Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Health Policy & Management, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA.

CRISMA Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.

出版信息

J Crit Care. 2022 Dec;72:154143. doi: 10.1016/j.jcrc.2022.154143. Epub 2022 Sep 6.

Abstract

PURPOSE

Teamwork is an important determinant of outcomes in the intensive care unit (ICU), yet the nature of individual ICU teams remains poorly understood. We examined whether meta-data in the form of digital signatures in the electronic health record (EHR) could be used to identify and characterize ICU teams.

METHODS

We analyzed EHR data from 27 ICUs over one year. We linked intensivist physicians, nurses, and respiratory therapists to individual patients based on selected EHR meta-data. We then characterized ICU teams by their members' overall past experience and shared past experience; and used network analysis to characterize ICUs by their network's density and centralization.

RESULTS

We identified 2327 unique providers and 30,892 unique care teams. Teams varied based on their average team member experience (median and total range: 262.2 shifts, 9.0-706.3) and average shared experience (median and total range: 13.2 shared shifts, 1.0-99.3). ICUs varied based on their network's density (median and total range: 0.12, 0.07-0.23), degree centralization (0.50, 0.35-0.65) and closeness centralization (0.45, 0.11-0.60). In a regression analysis, this variation was only partially explained by readily observable ICU characteristics.

CONCLUSIONS

EHR meta-data can assist in the characterization of ICU teams, potentially providing novel insight into strategies to measure and improve team function in critical care.

摘要

目的

团队合作是重症监护病房(ICU)结局的重要决定因素,但 ICU 团队的性质仍知之甚少。我们研究了电子病历(EHR)中的元数据(以数字签名的形式)是否可用于识别和描述 ICU 团队。

方法

我们分析了一年内在 27 个 ICU 中的 EHR 数据。我们根据选定的 EHR 元数据将重症医师、护士和呼吸治疗师与单个患者联系起来。然后,我们通过团队成员的总体过去经验和共享过去经验来描述 ICU 团队;并使用网络分析来描述 ICU 的网络密度和集中化程度。

结果

我们确定了 2327 名独特的提供者和 30892 个独特的护理团队。团队的差异基于其平均团队成员经验(中位数和总范围:262.2 个班次,9.0-706.3)和平均共享经验(中位数和总范围:13.2 个共享班次,1.0-99.3)。各 ICU 的网络密度(中位数和总范围:0.12,0.07-0.23)、度中心化(0.50,0.35-0.65)和接近中心化(0.45,0.11-0.60)存在差异。在回归分析中,这种差异仅部分由易于观察的 ICU 特征解释。

结论

EHR 元数据可用于描述 ICU 团队,可能为衡量和改善重症护理团队功能的策略提供新的见解。

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