Abstract

This review critically examines the role of emergency nursing interventions in enhancing the timeliness of antibiotic administration in patients presenting with sepsis. Recognizing sepsis as a time-sensitive and life-threatening condition, the study aims to synthesize existing evidence on clinical, organizational, and technological strategies that reduce delays in treatment initiation within emergency care settings. A structured narrative review approach was adopted, drawing on empirical studies, systematic reviews, and quality improvement reports to evaluate key interventions influencing time-to-antibiotic delivery.
The findings demonstrate that early identification through structured triage protocols and nurse-led screening tools significantly improves recognition of sepsis and accelerates clinical response. Nurse-initiated protocols and standing orders were shown to reduce reliance on hierarchical decision-making, thereby enabling more rapid initiation of antibiotic therapy. Additionally, workflow optimization and interdisciplinary collaboration were identified as critical factors in minimizing delays, particularly when supported by digital health systems and data-driven clinical decision tools. Emerging innovations, including artificial intelligence and predictive analytics, further enhance early detection and facilitate proactive intervention.
However, the review also identifies persistent barriers, including diagnostic uncertainty, workflow inefficiencies, and variability in clinical practice, which continue to impede optimal care delivery. Despite these challenges, evidence consistently indicates that reducing time to antibiotic administration is associated with improved patient outcomes, including lower mortality and reduced healthcare resource utilization.
In conclusion, timely antibiotic administration in sepsis requires a multifaceted and integrated approach that combines nursing leadership, standardized protocols, and technological innovation. It is recommended that healthcare systems prioritize nurse-driven interventions, invest in digital infrastructure, and strengthen interdisciplinary collaboration. Future research should focus on refining predictive technologies, standardizing clinical metrics, and addressing implementation challenges across diverse healthcare settings.