TY - JOUR
T1 - Using rapid response system trigger clusters to characterize patterns of clinical deterioration among hospitalized adult patients
AU - American Heart Association's Get With The Guidelines®-Resuscitation Investigators
AU - Piasecki, Rebecca J.
AU - Hunt, Elizabeth A.
AU - Perrin, Nancy
AU - Spaulding, Erin M.
AU - Winters, Bradford
AU - Samuel, Laura
AU - Davidson, Patricia M.
AU - Chandra Strobos, Nisha
AU - Churpek, Matthew
AU - Himmelfarb, Cheryl R.
N1 - Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2024/1
Y1 - 2024/1
N2 - Background: Many rapid response system (RRS) events are activated using multiple triggers. However, the patterns in which multiple RRS triggers occur together to activate RRS events are unknown. The purpose of this study was to identify these patterns (RRS trigger clusters) and determine their association with outcomes among hospitalized adult patients. Methods: RRS events among adult patients from January 2015 to December 2019 in the Get With The Guidelines- Resuscitation registry's MET module were examined (n = 134,406). Cluster analysis methods were performed to identify RRS trigger clusters. Pearson's chi-squared and ANOVA tests were used to examine differences in patient characteristics across RRS trigger clusters. Multilevel logistic regressions were used to examine the associations between RRS trigger clusters and outcomes. Results: Six RRS trigger clusters were identified. Predominant RRS triggers for each cluster were: tachypnea, new onset difficulty in breathing, decreased oxygen saturation (Cluster 1); tachypnea, decreased oxygen saturation, staff concern (Cluster 2); respiratory depression, decreased oxygen saturation, mental status changes (Cluster 3); tachycardia, staff concern (Cluster 4); mental status changes (Cluster 5); hypotension, staff concern (Cluster 6). Significant differences in patient characteristics were observed across clusters. Patients in Clusters 3 and 6 had an increased likelihood of in-hospital cardiac arrest (p < 0.01). All clusters had an increased risk of mortality (p < 0.01). Conclusions: We discovered six novel RRS trigger clusters with differing relationships to adverse patient outcomes. RRS trigger clusters may prove crucial in clarifying the associations between RRS events and adverse outcomes and aiding in clinician decision-making during RRS events.
AB - Background: Many rapid response system (RRS) events are activated using multiple triggers. However, the patterns in which multiple RRS triggers occur together to activate RRS events are unknown. The purpose of this study was to identify these patterns (RRS trigger clusters) and determine their association with outcomes among hospitalized adult patients. Methods: RRS events among adult patients from January 2015 to December 2019 in the Get With The Guidelines- Resuscitation registry's MET module were examined (n = 134,406). Cluster analysis methods were performed to identify RRS trigger clusters. Pearson's chi-squared and ANOVA tests were used to examine differences in patient characteristics across RRS trigger clusters. Multilevel logistic regressions were used to examine the associations between RRS trigger clusters and outcomes. Results: Six RRS trigger clusters were identified. Predominant RRS triggers for each cluster were: tachypnea, new onset difficulty in breathing, decreased oxygen saturation (Cluster 1); tachypnea, decreased oxygen saturation, staff concern (Cluster 2); respiratory depression, decreased oxygen saturation, mental status changes (Cluster 3); tachycardia, staff concern (Cluster 4); mental status changes (Cluster 5); hypotension, staff concern (Cluster 6). Significant differences in patient characteristics were observed across clusters. Patients in Clusters 3 and 6 had an increased likelihood of in-hospital cardiac arrest (p < 0.01). All clusters had an increased risk of mortality (p < 0.01). Conclusions: We discovered six novel RRS trigger clusters with differing relationships to adverse patient outcomes. RRS trigger clusters may prove crucial in clarifying the associations between RRS events and adverse outcomes and aiding in clinician decision-making during RRS events.
KW - Hospital mortality
KW - In-hospital cardiac arrest
KW - Rapid response systems
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U2 - 10.1016/j.resuscitation.2023.110041
DO - 10.1016/j.resuscitation.2023.110041
M3 - Article
C2 - 37952578
AN - SCOPUS:85177871763
SN - 0300-9572
VL - 194
JO - Resuscitation
JF - Resuscitation
M1 - 110041
ER -