Evidence map›Paper›PMID 41631152›Full record

ArticleMayo Clinic proceedings. Digital health2026

Increased Utilization of Telemedical Emergency and Nonurgent Care Following Deployment of Virtual Triage and Care Referral in Australia.

George A Gellert, Bettina McMahon, Tim Price, Zhixin Liu, Aleksandra Kabat-Karabon, Maria Marecka, Mitchell Burger, Lijing Ma, Nirvana Luckraj

Abstract read
In one paragraph

Article in Mayo Clinic proceedings. Digital health, 2026. 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

9 authors.

George A GellertIndependent Adviser, San Antonio, TX.
Bettina McMahonHealthdirect Australia, Sydney, Australia.
Tim PriceIndependent Adviser, London, United Kingdom.
Zhixin LiuIndependent Adviser, San Antonio, TX.
Aleksandra Kabat-KarabonInfermedica, Wroclaw, Poland.
Maria MareckaInfermedica, New York, NY.
Mitchell BurgerHealthdirect Australia, Sydney, Australia.
Lijing MaHealthdirect Australia, Sydney, Australia.
Nirvana LuckrajHealthdirect Australia, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate whether an artificial intelligence-based national virtual triage and care referral (VTCR) service in Australia improved care acuity level alignment, increased patient engagement of telemedicine services, and reduced emergency department demand by offering lower acuity, less costly options for urgent, virtual, or in-person care services. Patients and Methods: Cross-sectional analyses examined changes in patient care intent following VTCR to determine whether it facilitated patient adoption of new emergency and nonurgent telemedicine and virtual care services. Results: Virtual triage and care referral more than doubled the number of patients selecting appropriate, lower acuity nonurgent care from 330,279 (21.3%) to 820,800 (52.9%), an increase of 31.6 percentage points [PPs] ( Conclusion: Artificial intelligence-based VTCR improved alignment between patient perceived needs and recommended care pathways, not only driving greater use of appropriate, lower acuity, and telemedicine services but also reducing unnecessary in-person emergency visits. By eliminating uncertainty in care seeking and advancing adoption of new virtual emergency and nonurgent care options, VTCR offers a scalable, evidence-based solution for optimizing emergent and urgent care delivery and easing pressure on emergency departments across Australia.

Identifiers

PMID41631152
PMCPMC12861203

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.