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Updated: Nov 16, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Evaluation of an augmented emergency department electronic medical record-based sepsis alert
Amith Shetty1,2,3,4, Margaret Murphy4,5, Catriona Middleton-Rennie6
1Patient Experience and System Performance Division, NSW Ministry of Health, Sydney, New South Wales, Australia.
Objective:
Electronic medical records-based alerts have shown mixed results in identifying ED sepsis. Augmenting clinical patient-flagging with automated alert systems may improve sepsis screening. We evaluate the performance of a hybrid alert to identify patients in ED with sepsis or in-hospital secondary outcomes from infection.
Methods:
We extracted a dataset of all patients with sepsis during the study period at five participating Western Sydney EDs. We evaluated the hybrid alert's performance for identifying patients with a discharge diagnosis related to infection and modified sequential sepsis-related organ functional assessment (mSOFA) score ≥2 in ED and also compared the alert to rapid bedside screening tools to identify patients with infection for secondary outcomes of all-cause in-hospital death and/or intensive care unit admission.
Results:
A total of 118 178 adult patients presented to participating EDs during study period with 1546 patients meeting ED sepsis criteria. The hybrid alert had a sensitivity - 71.2% (95% confidence interval 68.8-73.4), specificity - 96.4% (95% confidence interval 96.3-96.5) for identifying ED sepsis. Clinician flagging identified additional alert-negative 232 ED sepsis and 63 patients with secondary outcomes and 112 alert-positive patients with infection and ED mSOFA score <2 went on to die in hospital.
Conclusion:
The hybrid alert performed modestly in identifying ED sepsis and secondary outcomes from infection. Not all infected patients with a secondary outcome were identified by the alert or mSOFA score ≥2 threshold. Augmenting clinical practice with auto-alerts rather than pure automation should be considered as a potential for sepsis alerting until more reliable algorithms are available for safe use in clinical practice.
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