ArticleJournal of the American Medical Informatics Association : JAMIA2017
Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality.
Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 4 of them syntheses that pooled it.
What it found
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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
48 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Pooled it
- The Use of Patient Monitoring Systems to Improve Sepsis Recognition and Outcomes: A Systematic Review.Journal of patient safety · 2020Pooled it
- Digital Alerting and Outcomes in Patients With Sepsis: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2019Pooled it
- Influenza and other respiratory viruses: standardizing disease severity in surveillance and clinical trials.Expert review of anti-infective therapy · 2017Pooled it
- Trial
- Electronic health record-based clinical decision support alert for severe sepsis: a randomised evaluation.BMJ quality & safety · 2019Trial
- Artificial intelligence in the emergency department-- applications, perceptions and limitations: a narrative review.World journal of emergency medicine · 2026Review
- Review
- Adapting a digital quality improvement system (Neotree) for newborn care in primary health centres and community hospitals: a mixed-methods implementation study in Malawi.Global health action · 2025Article
- The Effect of Sepsis Recognition on Telemedicine Use in Rural Emergency Department Sepsis Treatment.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2025Article
- Impact of the National Early Warning Score-based sepsis response system on hospital-onset sepsis in a tertiary hospital in South Korea.Acute and critical care · 2025Article
- The role of artificial intelligence in sepsis in the Emergency Department: a narrative review.Annals of translational medicine · 2025Review
- Views and Uses of Sepsis Digital Alerts in National Health Service Trusts in England: Qualitative Study With Health Care Professionals.JMIR human factors · 2024Article
- The Global Burden of Sepsis and Septic Shock.Epidemiologia (Basel, Switzerland) · 2024Review
- Sepsis increases the risk of in-hospital cardiac arrest: a population-based analysis.Internal and emergency medicine · 2024Article
- Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring.Frontiers in medicine · 2024Review
- Information displays for automated surveillance algorithms of in-hospital patient deterioration: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Epic Sepsis Model Inpatient Predictive Analytic Tool: A Validation Study.Critical care explorations · 2023Article
- Development and implementation experience of a learning healthcare system for facility based newborn care in low resource settings: The Neotree.Learning health systems · 2023Article
- The Accuracy of Sepsis Screening Score for Mortality Prediction at Emergency Department Triage.The western journal of emergency medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe created a system using a triad of change management, electronic surveillance, and algorithms to detect sepsis and deliver highly sensitive and specific decision support to the point of care using a mobile application. The investigators hypothesized that this system would result in a reduction in sepsis mortality.
methodsA before-and-after model was used to study the impact of the interventions on sepsis-related mortality. All patients admitted to the study units were screened per the Institute for Healthcare Improvement Surviving Sepsis Guidelines using real-time electronic surveillance. Sepsis surveillance algorithms that adjusted clinical parameters based on comorbid medical conditions were deployed for improved sensitivity and specificity. Nurses received mobile alerts for all positive sepsis screenings as well as severe sepsis and shock alerts over a period of 10 months. Advice was given for early goal-directed therapy. Sepsis mortality during a control period from January 1, 2011 to September 30, 2013 was used as baseline for comparison.
resultsThe primary outcome, sepsis mortality, decreased by 53% (P = 0.03; 95% CI, 1.06-5.25). The 30-day readmission rate reduced from 19.08% during the control period to 13.21% during the study period (P = 0.05; 95% CI, 0.97-2.52). No significant change in length of hospital stay was noted. The system had observed sensitivity of 95% and specificity of 82% for detecting sepsis compared to gold-standard physician chart review.
conclusionA program consisting of change management and electronic surveillance with highly sensitive and specific decision support delivered to the point of care resulted in significant reduction in deaths from sepsis.
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Registered trials
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