ArticleJournal of the American Medical Informatics Association : JAMIA2018
Impact of an emergency department electronic sepsis surveillance system on patient mortality and length of stay.
Article in Journal of the American Medical Informatics Association : JAMIA, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 7 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
32 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Sepsis Alert Systems, Mortality, and Adherence in Emergency Departments: A Systematic Review and Meta-Analysis.JAMA network open · 2024Pooled it
- The role of information systems in emergency department decision-making-a literature review.Journal of the American Medical Informatics Association : JAMIA · 2024Pooled 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
- Digital Alerting and Outcomes in Patients With Sepsis: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2019Pooled it
- Antibiotic- and Fluid-Focused Bundles Potentially Improve Sepsis Management, but High-Quality Evidence Is Lacking for the Specificity Required in the Centers for Medicare and Medicaid Service's Sepsis Bundle (SEP-1).Critical care medicine · 2019Pooled it
- Scope and Influence of Electronic Health Record-Integrated Clinical Decision Support in the Emergency Department: A Systematic Review.Annals of emergency medicine · 2019Pooled it
- Clinical Decision Support for Septic Shock in the Emergency Department: A Cluster Randomized Trial.Pediatrics · 2025Trial
- Surviving Sepsis Campaign: international guidelines for management of sepsis and septic shock 2026.Intensive care medicine · 2026Article
- Analysis of the challenges in ensuring robust and effective clinical evaluation of AI-based digital medical devices.BMJ digital health & AI · 2026Review
- Views and Uses of Sepsis Digital Alerts in National Health Service Trusts in England: Qualitative Study With Health Care Professionals.JMIR human factors · 2024Article
- A nursing-led sepsis response team guiding resuscitation with point-of-care ultrasound: A review and model for improving bundle compliance while individualizing sepsis care.SAGE open 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
- Effectiveness of automated alerting system compared to usual care for the management of sepsis.NPJ digital medicine · 2022Article
- The Ramathibodi early warning score as a sepsis screening tool does not reduce the timing of antibiotic administration.International journal of emergency medicine · 2022Article
- Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Adult Inpatients: Scoping Review.Journal of medical Internet research · 2022Article
- The impact of recency and adequacy of historical information on sepsis predictions using machine learning.Scientific reports · 2021Article
- Applying A/B Testing to Clinical Decision Support: Rapid Randomized Controlled Trials.Journal of medical Internet research · 2021Article
- Physician documentation matters. Using natural language processing to predict mortality in sepsis.Intelligence-based medicine · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Objective: The purpose of this study was to determine whether an electronic health record-based sepsis alert system could improve quality of care and clinical outcomes for patients with sepsis. Materials and Methods: We performed a patient-level interrupted time series study of emergency department patients with severe sepsis or septic shock between January 2013 and April 2015. The intervention, introduced in February 2014, was a system of interruptive sepsis alerts triggered by abnormal vital signs or laboratory results. Primary outcomes were length of stay (LOS) and in-hospital mortality; other outcomes included time to first lactate and blood cultures prior to antibiotics. We also assessed sensitivity, positive predictive value (PPV), and clinician response to the alerts. Results: Mean LOS for patients with sepsis decreased from 10.1 to 8.6 days (P < .001) following alert introduction. In adjusted time series analysis, the intervention was associated with a decreased LOS of 16% (95% CI, 5%-25%; P = .007, with significance of α = 0.006) and no change thereafter (0%; 95% CI, -2%, 2%). The sepsis alert system had no effect on mortality or other clinical or process measures. The intervention had a sensitivity of 80.4% and a PPV of 14.6%. Discussion: Alerting based on simple laboratory and vital sign criteria was insufficient to improve sepsis outcomes. Alert fatigue due to the low PPV is likely the primary contributor to these results. Conclusion: A more sophisticated algorithm for sepsis identification is needed to improve outcomes.
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