Evidence map›Paper›PMID 41222414›Full record

SynthesisCritical care medicine2026

Effects of Real-Time Automated Clinical Deterioration Alert and Trigger Systems on Clinical Outcomes in Adult General Ward Patients: A Systematic Review and Meta-Analysis.

Wei Ling Chua, Mina Azimirad, Mabel Chia, Daryl Jones, Pei Yi Woon

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Critical care medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Wei Ling ChuaAlice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.ORCID 0000-0002-4870-2728
Mina AzimiradDepartment of Nursing Science, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.
Mabel ChiaNursing Service, Tan Tock Seng Hospital, Singapore, Singapore.
Daryl JonesDepartment of Intensive Care, Austin Health, Melbourne, VIC, Australia.
Pei Yi WoonNursing Service, Tan Tock Seng Hospital, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesReal-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.

conclusionsReal-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.

Indexed as

Clinical DeteriorationAdultHeart ArrestHospital MortalityHumansIntensive Care UnitsLength of Stayautomated alertsclinical deteriorationearly warning scoremortalityrapid response system

Identifiers

PMID41222414
PMCPMC13134660

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.