Effectiveness of Early Sepsis Recognition Protocols in the Emergency Department

Abstract

Background:
Sepsis remains a leading cause of mortality in emergency departments (EDs) worldwide, accounting for approximately 11 million deaths annually. Early recognition and intervention significantly improve survival rates, yet compliance with standardized sepsis recognition protocols varies across healthcare settings. This study evaluates the effectiveness of early sepsis recognition protocols in improving patient outcomes in the ED.

Methods:
A retrospective cohort study was conducted across 20 emergency departments in the USA, UK, and Europe from 2018 to 2023. Data from 18,532 patients diagnosed with sepsis (mean age: 62.4 ± 14.7 years, 53.8% male) were analyzed. Patients were categorized into two groups: those managed with early sepsis recognition protocols (n = 9,476) and those receiving standard care without structured protocols (n = 9,056). Key outcome measures included time-to-antibiotic administration, in-hospital mortality, length of ED stay, and ICU admission rates. Statistical significance was set at p < 0.05, with odds ratios (OR) calculated using logistic regression.

Results:
Implementation of early sepsis recognition protocols resulted in a 41% reduction in time-to-antibiotic administration (median: 42 vs. 71 minutes, p < 0.001). The 30-day mortality rate was significantly lower in the protocol group (18.7%) compared to the standard care group (25.3%) (OR = 0.67, 95% CI: 0.59–0.75, p < 0.001). ICU admission rates decreased from 39.5% to 29.1% (p = 0.002). Additionally, ED length of stay was reduced by 17% (6.8 vs. 8.2 hours, p = 0.012). Compliance with the Surviving Sepsis Campaign (SSC) bundle was 85.2% in the protocol group, compared to 61.4% in the non-protocol group (p < 0.001).

Conclusion:
Early sepsis recognition protocols in the ED significantly improve key clinical outcomes, including reduced mortality, lower ICU admissions, and faster antibiotic administration. Widespread adoption and adherence to these protocols can enhance sepsis management and patient survival. Future studies should explore AI-driven sepsis detection tools to further optimize early intervention strategies.