Department of Medical Informatics, Amsterdam UMC, Location AMC, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; National Intensive Care Evaluation (NICE) Foundation, Department of Medical Informatics, Amsterdam UMC, Amsterdam, the Netherlands.
Department of Medical Informatics, Amsterdam UMC, Location AMC, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; National Intensive Care Evaluation (NICE) Foundation, Department of Medical Informatics, Amsterdam UMC, Amsterdam, the Netherlands.
J Crit Care. 2021 Apr;62:223-229. doi: 10.1016/j.jcrc.2020.12.008. Epub 2020 Dec 19.
To measure efficiency in Intensive Care Units (ICUs) and to determine which organizational factors are associated with ICU efficiency, taking confounding factors into account.
We used data of all consecutive admissions to Dutch ICUs between January 1, 2016 and January 1, 2019 and recorded ICU organizational factors. We calculated efficiency for each ICU by averaging the Standardized Mortality Ratio (SMR) and Standardized Resource Use (SRU) and examined the relationship between various organizational factors and ICU efficiency. We thereby compared the results of linear regression models before and after covariate adjustment using propensity scores.
We included 164,399 admissions from 83 ICUs. ICU efficiency ranged from 0.51-1.42 (average 0.99, 0.15 SD). The unadjusted model as well as the propensity score adjusted model showed a significant association between the ratio of employed intensivists per ICU bed and ICU efficiency. Other organizational factors had no statistically significant association with ICU efficiency after adjustment.
We found marked variability in efficiency in Dutch ICUs. After applying covariate adjustment using propensity scores, we identified one organizational factor, ratio intensivists per bed, having an association with ICU efficiency.
衡量重症监护病房（ICU）的效率，并确定哪些组织因素与 ICU 效率相关，同时考虑混杂因素。
我们使用了 2016 年 1 月 1 日至 2019 年 1 月 1 日期间所有连续入住荷兰 ICU 的患者数据，并记录了 ICU 的组织因素。我们通过平均标准化死亡率（SMR）和标准化资源使用率（SRU）来计算每个 ICU 的效率，并检查了各种组织因素与 ICU 效率之间的关系。我们通过使用倾向评分对协变量调整前后的线性回归模型的结果进行了比较。
我们纳入了 83 个 ICU 的 164399 例住院患者。ICU 效率范围为 0.51-1.42（平均 0.99，0.15 SD）。未调整模型和倾向评分调整模型均显示，每 ICU 床位雇用的重症监护医师比例与 ICU 效率之间存在显著关联。其他组织因素在调整后与 ICU 效率无统计学显著关联。
我们发现荷兰 ICU 的效率存在显著差异。在使用倾向评分进行协变量调整后，我们确定了一个组织因素，即每床重症监护医师比例，与 ICU 效率相关。
