ArticleJMIR medical informatics2015
A Web-Based Tool for Patient Triage in Emergency Department Settings: Validation Using the Emergency Severity Index.
Article in JMIR medical informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to 2 registered trials, which are not on this map. Cited by 4 papers.
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.
Validation of Intelligent Patient Flow Management System in Kuopio University Hospital Emergency Department
Evaluation of an Advanced Triage Tool for Gynecology and Obstetrics Emergencies Based on Artificial Intelligence Algorithms
Who cites it
4 citing papers in PubMed.
- Diagnostic Performance, Triage Safety, and Usability of a Clinical Decision Support System Within a University Hospital Emergency Department: Algorithm Performance and Usability Study.JMIR medical informatics · 2023Article
- Human- Versus Machine Learning-Based Triage Using Digitalized Patient Histories in Primary Care: Comparative Study.JMIR medical informatics · 2020Article
- How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments.BMC medical informatics and decision making · 2016Article
- Usability of the Surprise Question by Nurses and Patients' Families for Risk Stratification in Emergency Patients: A Prospective Cohort Study.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWe evaluated the concordance between triage scores generated by a novel Internet clinical decision support tool, Clinical GPS (cGPS) (Lumiata Inc, San Mateo, CA), and the Emergency Severity Index (ESI), a well-established and clinically validated patient severity scale in use today. Although the ESI and cGPS use different underlying algorithms to calculate patient severity, both utilize a five-point integer scale with level 1 representing the highest severity.
objectiveThe objective of this study was to compare cGPS results with an established gold standard in emergency triage.
methodsWe conducted a blinded trial comparing triage scores from the ESI: A Triage Tool for Emergency Department Care, Version 4, Implementation Handbook to those generated by cGPS from the text of 73 sample case vignettes. A weighted, quadratic kappa statistic was used to assess agreement between cGPS derived severity scores and those published in the ESI handbook for all 73 cases. Weighted kappa concordance was defined a priori as almost perfect (kappa > 0.8), substantial (0.6 < kappa < 0.8), moderate (0.4 < kappa < 0.6), fair (0.2 < kappa< 0.4), or slight (kappa < 0.2).
resultsOf the 73 case vignettes, the cGPS severity score matched the ESI handbook score in 95% of cases (69/73 cases), in addition, the weighted, quadratic kappa statistic showed almost perfect agreement (kappa = 0.93, 95% CI 0.854-0.996). In the subanalysis of 41 case vignettes assigned ESI scores of level 1 or 2, the cGPS and ESI severity scores matched in 95% of cases (39/41 cases).
conclusionsThese results indicate that the cGPS is a reliable indicator of triage severity, based on its comparison to a standardized index, the ESI. Future studies are needed to determine whether the cGPS can accurately assess the triage of patients in real clinical environments.
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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.