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Implementation of automated early warning decision support to detect acute decompensation in the emergency department improves hospital mortality
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Implementation of automated early warning decision support to detect acute decompensation in the emergency department improves hospital mortality
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Journal Article
Implementation of automated early warning decision support to detect acute decompensation in the emergency department improves hospital mortality
2022
Overview
Methods In the ED at Baylor St. Luke’s Medical Center (Houston, Texas, USA), an automated, real-time decision support software system (Decisio Health; Houston, Texas, USA) was installed to help calculate the National Early Warning Score (NEWS) for each patient. With regards to the effect on O/E mortality, although there was not a statistically significant difference between intervention and control periods (mean=1.00, SD=0.18 and mean=1.14, SD=0.14, respectively) (z=1.67, p=0.08), O/E mortality was 12% lower during intervention months (as compared with control months) and the effect size was large (d=0.87).Table 1 Observed vs expected mortality and length of stay during the control and intervention periods and comparisons between the two using the Wilcoxon Mann-Whitney U test Control (n=12 months) Intervention (n=9 months) % Improvement P value Cohen’s d Mean (SD) Mean (SD) Mortality O/E** 1.14 (0.14) 1.00 (0.18) 12 0.09 0.87 Arithmetic LOS O/E†† 1.54 (0.05) 1.47 (0.05) 4.5 0.004 1.40 Geometric LOS O/E†† 1.25 (0.04) 1.17 (0.04) 6.5 0.001 2.00 *Based on data from 11 132 patient admissions for control months and 8346 for intervention months. †Based on data from 11 101 patient admissions for control months and 8313 for intervention months. The ED is a highly complex, and unpredictable clinical environment, making an automated early warning system a critical adjunct and safety net for patients in these dynamic and busy departments.9 10 This study demonstrates that a real-time decision support software system that automates calculation of and notification for abnormal early warning scores was correlated with an improvement of hospital mortality and LOS for ED patients facing hospitalisation. The study demonstrates, that in a complex, dynamic clinical environment such as an ED, an automated decision support software system is an effective tool to implement a vital sign-based early warning score to change the outcomes of hospitalised patients.
Publisher
British Medical Journal Publishing Group,BMJ Publishing Group LTD,BMJ Publishing Group
Subject
