ArticleApplied clinical informatics2020
Design, Implementation, and Validation of a Pediatric ICU Sepsis Prediction Tool as Clinical Decision Support.
Article in Applied clinical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.
- Alerts and Alarms-Can Electronic Medical Records Help Children and Adolescents Survive Sepsis?Journal of paediatrics and child health · 2026Pooled it
- Artificial intelligence in pediatric intensive care units: current applications in sepsis management.World journal of pediatrics : WJP · 2026Pooled it
- Review
- Deconstructing Participant Behaviors in Virtual Reality Simulation: Ethnographic Analysis.JMIR medical education · 2025Article
- Health Care Providers' Perspectives of Clinical Decision Support Tools for Pediatric Sepsis in Bangladesh: Qualitative Study.JMIR formative research · 2025Article
- Refining a Machine Learning Model for Predicting Infant Sepsis: A Multidisciplinary Team Supported by Human-Centered Design Methods.Applied clinical informatics · 2025Article
- Digital solutions in paediatric sepsis: current state, challenges, and opportunities to improve care around the world.The Lancet. Digital health · 2024Review
- Usability Testing of Situation Awareness Clinical Decision Support in the Intensive Care Unit.Applied clinical informatics · 2024Article
- SEPRES: Intensive Care Unit Clinical Data Integration System to Predict Sepsis.Applied clinical informatics · 2023Article
- Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Pediatric, Neonatal, and Maternal Inpatients: Scoping Review.JMIR medical informatics · 2022Article
- Evaluation of a Sepsis Alert in the Pediatric Acute Care Setting.Applied clinical informatics · 2021Article
- Clinical evaluation of an interoperable clinical decision-support system for the detection of systemic inflammatory response syndrome in critically ill children.BMC medical informatics and decision making · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSepsis is an uncontrolled inflammatory reaction caused by infection. Clinicians in the pediatric intensive care unit (PICU) developed a paper-based tool to identify patients at risk of sepsis. To improve the utilization of the tool, the PICU team integrated the paper-based tool as a real-time clinical decision support (CDS) intervention in the electronic health record (EHR).
objectiveThis study aimed to improve identification of PICU patients with sepsis through an automated EHR-based CDS intervention.
methodsA prospective cohort study of all patients admitted to the PICU from May 2017 to May 2019. A CDS intervention was implemented in May 2018. The CDS intervention screened patients for nonspecific sepsis criteria, temperature dysregulation and a blood culture within 6 hours. Following the screening, an interruptive alert prompted nursing staff to complete a perfusion screen to assess for clinical signs of sepsis. The primary alert performance outcomes included sensitivity, specificity, and positive and negative predictive value. The secondary clinical outcome was completion of sepsis management tasks.
resultsDuring the 1-year post implementation period, there were 45.0 sepsis events per 1,000 patient days over 10,805 patient days. The sepsis alert identified 392 of the 436 sepsis episodes accurately with sensitivity of 92.5%, specificity of 95.6%, positive predictive value of 46.0%, and negative predictive value of 99.7%. Examining only patients with severe sepsis confirmed by chart review, test characteristics fell to a sensitivity of 73.3%, a specificity of 92.5%. Prior to the initiation of the alert, 18.6% (13/70) of severe sepsis patients received recommended sepsis interventions. Following the implementation, 34% (27/80) received these interventions in the time recommended,
conclusionAn EHR CDS intervention demonstrated strong performance characteristics and improved completion of recommended sepsis interventions.
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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.