The implementation of a part-time rapid response system reduced the cardiopulmonary arrest incidence based on the reduction of cardiopulmonary arrest during rapid response system operating times. Further analysis of the cost effectiveness of part-time rapid response system is needed.

Implementation of an RRS reduced the incidence of postoperative CPA in patients recovering in a general ward. Furthermore, this reduction was observed only during RRS operational hours.

Efforts to detect patient deterioration early have led to the development of early warning score (EWS) models. However, these models are disease-nonspecific and have shown variable accuracy in predicting unexpected critical events. Here, we propose a simpler and more accurate method for predicting risk in respiratory ward patients. This retrospective study analyzed adult patients who were admitted to the respiratory ward and detected using the rapid response system (RRS). Study outcomes included transfer to the intensive care unit (ICU) within 24 hours after RRS activation and in-hospital mortality. Prediction power of existing EWS models including Modified EWS (MEWS), National EWS (NEWS), and VitalPAC EWS (ViEWS) and SpO2/FiO2 (SF) ratio were compared to each other using the area under the receiver operating characteristic curve (AUROC). Overall, 456 patients were included; median age was 75 years (interquartile range: 65–80) and 344 (75.4%) were male. Seventy-three (16.0%) and 79 (17.3%) patients were transferred to the ICU and died. The SF ratio displayed better or comparable predictive accuracy for unexpected ICU transfer (AUROC: 0.744) compared to MEWS (0.744 vs. 0.653, P = 0.03), NEWS (0.744 vs. 0.667, P = 0.04), and ViEWS (0.744 vs. 0.675, P = 0.06). For in-hospital mortality, although there was no statistical difference, the AUROC of the SF ratio (0.660) was higher than that of each of the preexisting EWS models. In comparison with the preexisting EWS models, the SF ratio showed better or comparable predictive accuracy for unexpected ICU transfers in the respiratory wards.

Variability in rapid response system (RRS) characteristics based on the admitted wards is unknown. We aimed to compare differences in the clinical characteristics of RRS activation between patients admitted to medical versus surgical services. We reviewed patients admitted to the hospital who were detected by the RRS from October 2012 to February 2014 at a tertiary care academic hospital. We compared the triggers for RRS activation, interventions performed, and outcomes of the 2 patient groups. The RRS was activated for 460 patients, and the activation rate was almost 2.3 times higher for surgical services than that for medical services (70% vs. 30%). The triggers for RRS activation significantly differed between patient groups (P = 0.001). They included abnormal values for the respiratory rate (23.2%) and blood gas analysis (20.3%), and low blood pressure (18.8%) in the medical group; and low blood pressure (32.0%), low oxygen saturation (20.8%), and an abnormal heart rate (17.7%) in the surgical group. Patients were more likely classified as do not resuscitate or required intensive care unit admission in the medical group compared to those in the surgical group (65.3% vs. 54.7%, P = 0.045). In multivariate analysis, whether the patient belongs to medical services was found to be an independent predictor of mortality after adjusting for the modified early warning score, Charlson comorbidity index, and intervention performed by the RRS team. Our data suggest that RRS triggers, interventions, and outcomes greatly differ between patient groups. Further research is needed to evaluate the efficacy of an RRS approach tailored to specific patient groups.

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