Evidence map›Paper›PMID 26063343›Full record

ArticleJMIR medical informatics2015

A Web-Based Tool for Patient Triage in Emergency Department Settings: Validation Using the Emergency Severity Index.

Pierre Elias, Ash Damle, Michael Casale, Kim Branson, Chaitanya Churi, Ravi Komatireddy, Jamison Feramisco

Erratum issued 2 registry-linked trialsAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

NCT04577079 completednot on this mapstarted 2020, after this paper: background citation

Validation of Intelligent Patient Flow Management System in Kuopio University Hospital Emergency Department

TypeobservationalSponsorKuopio University HospitalRan2020 to 2022Enrolled273ConditionsEmergency Medical ServicesArmsEvaluation of the need of emergency medical services
NCT05382000 naunknown statusnot on this mapstarted 2022, after this paper: background citation

Evaluation of an Advanced Triage Tool for Gynecology and Obstetrics Emergencies Based on Artificial Intelligence Algorithms

TypeinterventionalSponsorFundació Institut de Recerca de l'Hospital de la Santa Creu i Sant PauRan2022 to 2024Enrolled450ConditionsEmergenciesArmsAdvanced triage tool for Gynecology and Obstetrics emergencies based on artificial intelligence algorithms.
3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Pierre EliasDuke Clinical Research Institute, Duke University School of Medicine, Durham, NC, United States. pierre.elias@duke.edu.ORCID http://orcid.org/0000-0002-9643-3024

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

clinical decision supportdifferential diagnosisemergency severity indextriage

Identifiers

PMID26063343
PMCPMC4526930

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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.