Rating the quality of intensive care units: Is it a function of the intensive care unit scoring system?
Rating the quality of intensive care units: Is it a function of the intensive care unit scoring system?
复制标题
DOI：
10.1097/00003246-200209000-00005
复制
发表时间：
2002-09-01
影响因子：
8.8
通讯作者：
Dick, A
中科院分区：
文献类型：
--
作者：
Glance, LG;Osler, TM;Dick, A
Objective.重症监护病房（ICU）使用严重程度调整的死亡率指标，如标准化死亡率比，以基准他们的表现。预后评分系统，如急性生理学和慢性健康评估（APACHE）11、简化急性生理学评分11和死亡概率模型110，允许通过调整疾病严重程度和病例组合对ICU进行基于性能的比较。是否不同的风险调整方法同意在一个单一的数据库中的ICU质量离群值的身份还没有以前的调查。本研究的目的是确定ICU质量离群值的身份是否取决于ICU评分系统，用于计算标准化死亡率ratio.Design，设置，患者：回顾性队列研究的16,604例患者来自32家医院的基础上的结果数据库（项目IMPACT）创建的重症医学会。ICU是城市和非城市环境中内科、外科和内科-外科混合ICU的混合体。使用APACHE 11、简化急性生理学评分11和死亡概率模型II 0计算每个ICU的标准化死亡率。ICU质量离群值定义为ICU标准化死亡率在统计学上不同于1。Kappa分析用于确定医院质量离群值识别评分系统之间的一致程度。计算组内相关系数，以估计使用三种风险调整方法获得的标准化死亡率的可靠性。Kappa分析显示，在识别ICU质量离群值方面，三种评分系统之间存在中度至中度一致性;组内相关系数表明评分系统之间存在中度至实质性一致性。通过所有三个评分系统，大多数ICU被归类为高性能INS。所有三个评分系统表现出良好的歧视和不良校准在此dataset.Conclusion：APACHE 11，简化急性生理评分11，死亡概率模型110表现出公平到中等的协议，在确定质量离群值。然而，发现这个数据库中的大多数ICU被认为是高性能的单位限制了这些模型的有用性，在其目前的形式为基准。
Objective. Intensive care units (ICUs) use severity-adjusted mortality measures such as the standardized mortality ratio to benchmark their performance. Prognostic scoring systems such as Acute Physiology and Chronic Health Evaluation (APACHE) 11, Simplified Acute Physiology Score 11, and Mortality Probability Model 110 permit performance-based comparisons of ICUs by adjusting for severity of disease and case mix. Whether different risk-adjustment methods agree on the identity of ICU quality outliers within a single database has not been previously investigated. The objective of this study was to determine whether the identity of ICU quality outliers depends on the ICU scoring system used to calculate the standardized mortality ratio.Design, Setting, Patients: Retrospective cohort study of 16,604 patients from 32 hospitals based on the outcomes database (Project IMPACT) created by the Society of Critical Care Medicine. The ICUs were a mixture of medical, surgical, and mixed medical-surgical ICUs in urban and nonurban settings. Standardized mortality ratios for each ICU were calculated using APACHE 11, Simplified Acute Physiology Score 11, and Mortality Probability Model II0. ICU quality outliers were defined as ICUs whose standardized mortality ratio was statistically different from 1. Kappa analysis was used to determine the extent of agreement between the scoring systems on the identity of hospital quality outliers. The intraclass correlation coefficient was calculated to estimate the reliability of standardized mortality ratios obtained using the three risk-adjustment methods.Measurements and Main Results., Kappa analysis showed fair to moderate agreement among the three scoring systems in identifying ICU quality outliers; the intraclass correlation coefficient suggested moderate to substantial agreement between the scoring systems. The majority of ICUs were classified as high-performance INS by all three scoring systems. All three scoring systems exhibited good discrimination and poor calibration in this data set.Conclusion: APACHE 11, Simplified Acute Physiology Score 11, and Mortality Probability Model 110 exhibit fair to moderate agreement in identifying quality outliers. However, the finding that most ICUs in this database were judged to be high-performing units limits the usefulness of these models in their present form for benchmarking.