Evidence map›Paper›PMID 33094232›Full record

ArticleFuture healthcare journal2020

General medicine consultant of the week model shortens hospital length of stay and improves the patient journey.

Amir Aziz, April Hawkins, Yasmina Gainer, Craig Simpson, Rachel Barlow, Chetan Varma

Open access · diamondAbstract read
In one paragraph

Article in Future healthcare journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 24% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

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  5. The digital transformation - all good?Future healthcare journal · 2020
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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 at 1 institution in 1 country.

Amir AzizSandwell and West Birmingham NHS Trust, Birmingham, UK.
April HawkinsSandwell and West Birmingham NHS Trust, Birmingham, UK.
Yasmina GainerSandwell and West Birmingham NHS Trust, Birmingham, UK.
Craig SimpsonSandwell and West Birmingham NHS Trust, Birmingham, UK.
Rachel BarlowSandwell and West Birmingham NHS Trust, Birmingham, UK.
Chetan VarmaSandwell and West Birmingham NHS Trust, Birmingham, UK.
Sandwell & West Birmingham Hospitals NHS Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsThe consultant of the week (COW) model of inpatient care means the consultants' primary focus is to deliver ward-based care daily. At Sandwell and West Birmingham Hospitals NHS Trust, a COW model has been successfully used for cardiology and stroke services. This has improved continuity of care and developed a 7-day working week. Our aim was to extend this model to all general medical consultants who manage inpatients.

methodsWe introduced the COW model to the unselected general medical take. Restructuring of consultant job plans allowed daily ward presence, 5 days per week. Outcome measures included length of stay (LOS) and accuracy of expected date of discharge (EDD).

resultsLOS over a 12-month period improved from an average of 9.17 days to 6.61 days. The number of EDD changes reduced, from a previous average of 3.0 changes to 1.8 changes. Consultant feedback showed there was an improvement in collaboration between teams, improved training of junior doctors and higher job satisfaction.

conclusionsImproved 5-day consultant presence is associated with reduced LOS. Learning points included the delay in implementation due to the complexity of consultant job planning. We plan to extend COW to 7-days for all general medical wards.

Indexed as

consultant of the weeklength of stayService improvement

Identifiers

PMID33094232
PMCPMC7571745
OpenAlexW3092905073

What OpenQuestion holds

Textmetadata
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.