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OBJECTIVES: Real-time automated alert and trigger systems that notify clinical staff beyond the patient's assigned bedside nurse are increasingly used to improve the recognition and response to clinical deterioration in hospital wards. This review evaluated their effects on clinical outcomes in adult general ward patients.

DATA SOURCES: Seven electronic databases were searched from inception to April 1, 2024, supplemented with citation tracking.

STUDY SELECTION: Two sets of reviewers independently screened for comparative studies assessing automated clinical deterioration alert and trigger systems vs. conventional manual escalation processes.

DATA EXTRACTION: Two sets of reviewers extracted data. Primary outcomes were hospital mortality and in-hospital cardiac arrest. Secondary outcomes included unplanned ICU transfers, and hospital and ICU length of stay. Data were pooled using random-effects meta-analysis.

DATA SYNTHESIS: Eighteen studies (n = 349,818) were included: two randomized controlled trials (RCTs), 15 before-and-after designs, and one quasi-experimental study. All studies had at least moderate risk of bias. The main meta-analysis included nine studies (n = 58,632) involving alert-eligible cohorts (i.e., patients meeting alert thresholds). Based on two before-and-after studies, automated alert and trigger systems were associated with a significant reduction in-hospital cardiac arrests (risk ratio [RR], 0.60; 95% CI, 0.43-0.85; p = 0.004). No significant reduction in hospital mortality was observed (RR, 0.80; 95% CI, 0.62-1.05; p = 0.09), based on pooled data from RCTs and before-and-after studies. ICU length of stay was also significantly reduced, based on one RCT and one before-and-after study. No significant effects were found for hospital length of stay or unplanned ICU transfers in either alert-eligible or all-admission cohorts.

CONCLUSIONS: Real-time clinical deterioration automated alert and trigger systems are associated with reduced in-hospital cardiac arrests and may offer mortality benefits when integrated into structured escalation pathways. Further high-quality trials are needed to confirm these findings and optimize system design.

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