What question did this study set out to answer?

This research aims to investigate how the timing of Early Recognition Team activations relates to the occurrence of Code Blue events.

May 20, 2026

C56-34 Examining the Temporal Relationship Between Time of Early Recognition Team Activation and Conversion to Code Blues: A Baseline Quality-Improvement Analysis

Key Points

This research aims to investigate how the timing of Early Recognition Team activations relates to the occurrence of Code Blue events.
Single-center retrospective study at University Hospital in Newark, New Jersey, from January to July 2025.
ERT activations were categorized into 4-hour and 12-hour time blocks for analysis.
Comparative statistics utilized Chi-squared tests and odds ratios.
The majority of ERT activations occurred during day hours (7 AM - 7 PM) with 64% overall activations (n = 234).
No significant relationship was found in the 4-hour block analysis (p = .20).
In the 12-hour block analysis, a significant association was detected, with evening/night shifts showing higher conversion rates to Code Blue (p = .004, odds ratio = 0.22).

Abstract

Abstract Introduction Early Recognition Team (ERT) activations are in place to identify and intervene in patient deterioration prior to progression to Code Blue (CB). This study aims to compare the temporal distribution of ERTs with those that progress to CB to understand the relationship better. Methods This single-center retrospective study included all ERT activations at University Hospital in Newark, New Jersey, from January to July 2025. ERT activations were divided into 4-hour blocks and 12-hour blocks. The variables were ERTs without CB and ERTs with conversion to CB. Descriptive statistics were generated for all. Comparisons were performed using Chi-squared tests with 95% confidence intervals (CI). Analyses were conducted using RStudio (Posit team, 2025). Results Preliminary data review shows a higher percentage of ERTs called between 8 AM and 12 PM (n = 87, 23.7%). There is a large decline in ERTs from 4 PM to 8 PM (n = 79, 21.5%) to 8 PM to 12 AM (n = 35, 9.5%). However, there was no statistical significance in this breakdown. In the 12-hour block, there were more ERTs overall during 7 AM to 7 PM (n = 234, 64%), than during the night 7 PM to 7 AM. The first analysis using 4-hour blocks; showed no relationship between time of day and event type, χ²(5, N = 367) = 6.10, p = .20. The second analysis using the 12-hour block; indicated a significant association between time of day and type of response, χ²(1, N = 367) = 7.61, p = .006. Due to low counts, Fisher’s exact test was performed, confirming a significant effect, p = .004, with an odds ratio of 0.22 (95% CI 0.06, 0.69). These results indicate that CB events were proportionally more likely to occur during the evening/night period than during the morning/daytime period, relative to ERT events without CB. Conclusion There are higher rates of ERT activations during the day shift than the night shift. This may correspond to increased monitoring, patients’ wake cycles, and increased house-staff response. However, the night shift had a statistically significantly higher rate of ERT conversion to CB. It is possible that this reflects delays in calling ERT during the night, and ERTs are activated later in the clinical decompensation of patients. Further studies are needed to elucidate the underlying causes of the observed difference. We hope to replicate this study in the future with a larger sample to further understand the relationship. This abstract is funded by: none

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