Evidence map›Paper›PMID 39515818›Full record

ArticleHealthcare management forum2025

Considerations for emergency department virtual triage.

Laila Nasser, Emily Morris, Irene Mathias, Justin N Hall

Abstract read
In one paragraph

Article in Healthcare management forum, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Laila NasserSunnybrook Health Sciences Centre, Toronto, Ontario, Canada.ORCID 0000-0003-3347-7107
Emily MorrisOxford University, Oxford, England, United Kingdom.
Irene MathiasOxford University, Oxford, England, United Kingdom.
Justin N HallSunnybrook Health Sciences Centre, Toronto, Ontario, Canada.ORCID 0000-0002-6211-9336

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health leaders are increasingly interested in harnessing Artificial Intelligence (AI) to remotely conduct virtual triage for Emergency Department (ED) patients. This study explores equity considerations and patient attitudes to virtual triage in a Canadian ED. A cross-sectional study surveyed 150 ED patients, with 32 additional patients interviewed in-depth. Descriptive statistics and qualitative descriptive methodology were employed: 84.7% of patients would consider virtual triage, 71.3% were comfortable following advice to seek alternate care, including their General Practitioner or virtual ED. Approximately 38.2% of patients >60 years would require assistance using virtual triage, with confidence in using technology to direct care decreasing with age. Thematic analysis revealed five key themes: value of decision support; care access expectations; technological literacy demographics; trust in AI; and confidentiality. In conclusion, virtual triage is a viable and promising tool if barriers to technological literacy are addressed, and tools are endorsed by health providers and patients.

Indexed as

Emergency Service, HospitalTriageAdolescentAdultAgedArtificial IntelligenceCanadaCross-Sectional StudiesFemaleHumansMaleMiddle AgedTelemedicineYoung Adult

Identifiers

PMID39515818
PMCPMC11849239

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.