Evidence map›Paper›PMID 40099035›Full record

ArticleFrontiers in digital health2025

Use of artificial intelligence for reverse referral between a hospital emergency department and a primary urgent care center.

Yolanda Taules, Silvia Gros, Maria Viladrosa, Natàlia Llorens, Sílvia Solis, Oriol Yuguero

Abstract read
In one paragraph

Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yolanda TaulesEmergency Department, University Hospital Arnau de Vilanova, Lleida, Spain.
Silvia GrosEmergency Department, University Hospital Arnau de Vilanova, Lleida, Spain.
Maria ViladrosaEmergency Department, University Hospital Arnau de Vilanova, Lleida, Spain.
Natàlia LlorensPrimary Care Emergency Center, Catalan Health Instiute (ICS), Lleida, Spain, 4eHealth Center, Universitat Oberta de Catalunya (UOC), Barcelona, Spain.
Sílvia SolisPrimary Care Emergency Center, Catalan Health Instiute (ICS), Lleida, Spain, 4eHealth Center, Universitat Oberta de Catalunya (UOC), Barcelona, Spain.
Oriol YugueroEmergency Department, University Hospital Arnau de Vilanova, Lleida, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The demand for immediate care in emergency departments (EDs) has risen since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Objective: Test the ability of AI to promote reverse referral and to provide patient education. Methods: Pilot study that included patients presenting to our Hospital Emergency Department (HED) with a non severe disease and who met the inclusion criteria. The participants were asked to answer a series of questions using an electronic device and receive a recommendation for health attention. Then, patients could choose to either remain in the hospital or leave. Results: 427 patients finally participated in the pilot study. Within this population, 49.5% were women, and the mean patient age was 37.5 years. Mediktor recommended reverse referral to urgent care in 43.6%. Our results demonstrate that the tool is safe and provides accurate patient screening, correctly distinguishing between those who should continue to wait for HED care and those for whom an urgent care center is adequate.

Indexed as

AIemergency carehealth serivcesmedical informatic applicationsprimary care

Identifiers

PMID40099035
PMCPMC11911458

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.