SynthesisJournal of hospital medicine2015
Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: A systematic review.
Synthesis in Journal of hospital medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 8 of them syntheses that pooled 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.
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.
Who cites it
56 citing papers in PubMed, 8 syntheses or guidelines pooled it.
- Alert fatigue measurement in clinical decision support: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2026Pooled it
- The Effect of Early Warning Systems for Sepsis on Mortality: A Systematic Review and Meta-analysis.Journal of general internal medicine · 2025Pooled it
- Optimizing clinical decision support alerts in electronic medical records: a systematic review of reported strategies adopted by hospitals.Journal of the American Medical Informatics Association : JAMIA · 2021Pooled it
- The Use of Patient Monitoring Systems to Improve Sepsis Recognition and Outcomes: A Systematic Review.Journal of patient safety · 2020Pooled it
- Sepsis Alerts in Emergency Departments: A Systematic Review of Accuracy and Quality Measure Impact.The western journal of emergency medicine · 2020Pooled it
- Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy.Intensive care medicine · 2020Pooled it
- Digital Alerting and Outcomes in Patients With Sepsis: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2019Pooled it
- Automated monitoring compared to standard care for the early detection of sepsis in critically ill patients.The Cochrane database of systematic reviews · 2018Pooled it
- Trial
- Electronic health record-based clinical decision support alert for severe sepsis: a randomised evaluation.BMJ quality & safety · 2019Trial
- Sepsis Diagnostic Excellence: Development and Validation of a Theoretical Framework for Conceptualizing Accurate, Timely Sepsis Diagnosis.Critical care explorations · 2026Observational
- The Global Impact of Sepsis: Epidemiology, Recognition, Management, and Health System Challenges.Epidemiologia (Basel, Switzerland) · 2026Review
- Timing matters: a machine learning-driven comparison of community and hospital-onset sepsis.BMC medical informatics and decision making · 2026Article
- Commercial or industrial use of mental health data for research: primer and best-practice guidelines from the DATAMIND patient/public Lived Experience Advisory Group.Frontiers in psychiatry · 2026Article
- Article
- When Clinical AI and Learner Reasoning Conflict: An Emerging Educational Blind Spot and a Framework for Pedagogical Response.Advances in medical education and practice · 2026Article
- Linezolid-Associated Lactic Acidosis Triggering a Sepsis Alert: A Case Report.Clinical case reports · 2025Article
- Identification and Validation of an Explainable Prediction Model of Sepsis in Patients With Intracerebral Hemorrhage: Multicenter Retrospective Study.Journal of medical Internet research · 2025Article
- Enhancing Hepatitis C Virus Testing, Linkage to Care, and Treatment Commencement in Hospitals: A Systematic Review and Meta-analysis.Open forum infectious diseases · 2025Article
- Exploring the Potentials of Artificial Intelligence in Sepsis Management in the Intensive Care Unit.Critical care research and practice · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundAlthough timely treatment of sepsis improves outcomes, delays in administering evidence-based therapies are common. PURPOSE: To determine whether automated real-time electronic sepsis alerts can: (1) accurately identify sepsis and (2) improve process measures and outcomes. DATA SOURCES: We systematically searched MEDLINE, Embase, The Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature from database inception through June 27, 2014. STUDY SELECTION: Included studies that empirically evaluated 1 or both of the prespecified objectives. DATA EXTRACTION: Two independent reviewers extracted data and assessed the risk of bias. Diagnostic accuracy of sepsis identification was measured by sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratio (LR). Effectiveness was assessed by changes in sepsis care process measures and outcomes. DATA SYNTHESIS: Of 1293 citations, 8 studies met inclusion criteria, 5 for the identification of sepsis (n = 35,423) and 5 for the effectiveness of sepsis alerts (n = 6894). Though definition of sepsis alert thresholds varied, most included systemic inflammatory response syndrome criteria ± evidence of shock. Diagnostic accuracy varied greatly, with PPV ranging from 20.5% to 53.8%, NPV 76.5% to 99.7%, LR+ 1.2 to 145.8, and LR- 0.06 to 0.86. There was modest evidence for improvement in process measures (ie, antibiotic escalation), but only among patients in non-critical care settings; there were no corresponding improvements in mortality or length of stay. Minimal data were reported on potential harms due to false positive alerts.
conclusionsAutomated sepsis alerts derived from electronic health data may improve care processes but tend to have poor PPV and do not improve mortality or length of stay.
Indexed as
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What OpenQuestion holds
Registered trials
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.