Document Type
Article
Publication Date
8-1-2017
Abstract
BACKGROUND: 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.
METHODS AND RESULTS: 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.
CONCLUSIONS: 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.
Recommended Citation
Grossestreuer, Anne V.; Gaieski, David F.; Donnino, Michael W.; Nelson, Joshua I.M.; Mutter, Eric L.; Carr, Brendan G.; Abella, Benjamin S.; and Wiebe, Douglas J., "Cardiac arrest risk standardization using administrative data compared to registry data." (2017). Department of Emergency Medicine Faculty Papers. Paper 62.
https://jdc.jefferson.edu/emfp/62
Creative Commons License
This work is licensed under a
Creative Commons Public Domain Dedication 1.0 License.
PubMed ID
28783754
Comments
This article has been peer reviewed. It is the author’s final published version in PLoS ONE
Volume 12, Issue 8, August 2017, Article number e0182864.
The published version is available at DOI: 10.1371/journal.pone.0182864. Copyright © Public Library of Science