Evidence map›Paper›PMID 40443192›Full record

Observational studyEmergency medicine Australasia : EMA2025

Evaluation of a Novel Clinical Assistant Model of Care on Patient Flow and Emergency Department Length of Stay.

Jeremy Chou, Namankit Gupta, Alvin Lim, Josh Bryan, Katie Walker, Diana Egerton-Warburton, Jeniffer Kim-Blackmore, Rachel Rosler, Andy Lim

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Emergency medicine Australasia : EMA, 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

9 authors.

Jeremy ChouMelbourne Medical School, University of Melbourne, Parkville, Victoria, Australia.
Namankit GuptaSchool of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Alvin LimSchool of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.ORCID 0000-0002-0403-2355
Josh BryanSchool of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Katie WalkerSchool of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.ORCID 0000-0002-5313-5852
Diana Egerton-WarburtonSchool of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Jeniffer Kim-BlackmoreSchool of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Rachel RoslerSchool of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Andy LimSchool of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.ORCID 0000-0002-2522-3927

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo measure the contribution of clinical assistants (CAs) to departmental flow and length of stay.

methodsAn observational study comparing key performance indicators (KPIs) between shifts with and without assistants.

resultsA total of 122 shifts were included from 1 November to 31 December 2021. There was no difference in the proportion of patients who were seen by a doctor within 1 h, ambulance offload times, or 4-h departure metrics (regardless of non-admitted, admitted, or short stay status).

conclusionCAs do not have a demonstrable impact on ambulance offload times, cubicle availability, or 4-h KPIs.

Indexed as

Emergency Service, HospitalLength of StayFemaleHumansMaleMiddle Agedambulancesemergencyhumanslength of stayworkforce

Identifiers

PMID40443192
PMCPMC12123249

What OpenQuestion holds

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LicenceCC BY-NC
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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.