Grossestreuer Anne V, Gaieski David F, Donnino Michael W, Nelson Joshua I M, Mutter Eric L, Carr Brendan G, Abella Benjamin S, Wiebe Douglas J
Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.
Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America.
PLoS One. 2017 Aug 4;12(8):e0182864. doi: 10.1371/journal.pone.0182864. eCollection 2017.
Methods for comparing hospitals regarding cardiac arrest (CA) outcomes, vital for improving resuscitation performance, rely on data collected by cardiac arrest registries. However, most CA patients are treated at hospitals that do not participate in such registries. This study aimed to determine whether CA risk standardization modeling based on administrative data could perform as well as that based on registry data.
Two risk standardization logistic regression models were developed using 2453 patients treated from 2000-2015 at three hospitals in an academic health system. Registry and administrative data were accessed for all patients. The outcome was death at hospital discharge. The registry model was considered the "gold standard" with which to compare the administrative model, using metrics including comparing areas under the curve, calibration curves, and Bland-Altman plots. The administrative risk standardization model had a c-statistic of 0.891 (95% CI: 0.876-0.905) compared to a registry c-statistic of 0.907 (95% CI: 0.895-0.919). When limited to only non-modifiable factors, the administrative model had a c-statistic of 0.818 (95% CI: 0.799-0.838) compared to a registry c-statistic of 0.810 (95% CI: 0.788-0.831). All models were well-calibrated. There was no significant difference between c-statistics of the models, providing evidence that valid risk standardization can be performed using administrative data.
Risk standardization using administrative data performs comparably to standardization using registry data. This methodology represents a new tool that can enable opportunities to compare hospital performance in specific hospital systems or across the entire US in terms of survival after CA.
比较医院心脏骤停（CA）结局的方法对于提高复苏效果至关重要，这些方法依赖于心脏骤停登记处收集的数据。然而，大多数CA患者是在未参与此类登记处的医院接受治疗的。本研究旨在确定基于行政数据的CA风险标准化模型是否能与基于登记处数据的模型表现相当。
使用2000年至2015年在一个学术医疗系统的三家医院接受治疗的2453例患者，开发了两个风险标准化逻辑回归模型。获取了所有患者的登记处数据和行政数据。结局为出院时死亡。登记处模型被视为“金标准”，用于与行政模型进行比较，使用的指标包括比较曲线下面积、校准曲线和布兰德-奥特曼图。行政风险标准化模型的c统计量为0.891（95%置信区间：0.876 - 0.905），而登记处模型的c统计量为0.907（95%置信区间：0.895 - 0.919）。当仅限于不可改变因素时，行政模型的c统计量为0.818（95%置信区间：0.799 - 0.838），而登记处模型的c统计量为0.810（95%置信区间：0.788 - 0.831）。所有模型校准良好。模型的c统计量之间无显著差异，这表明使用行政数据可以进行有效的风险标准化。
使用行政数据进行风险标准化与使用登记处数据进行标准化的表现相当。这种方法代表了一种新工具，能够为比较特定医院系统或整个美国医院在CA后生存方面的表现提供机会。
