Evidence map›Paper›PMID 39346935›Full record

ArticleFuture healthcare journal2024

Predictive modelling of the UK physician associate supply: 2014-2038.

Emyr Yosef Bakker, Peter Anthony Dixon, Tim Smith, Jane Frances Rutt-Howard

Abstract read
In one paragraph

Article in Future healthcare journal, 2024. 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. Review
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.

Emyr Yosef BakkerSchool of Medicine and Dentistry, University of Central Lancashire, Preston, PR1 2HE, UK.
Peter Anthony DixonSchool of Medicine and Dentistry, University of Central Lancashire, Preston, PR1 2HE, UK.
Tim SmithSchool of Medicine and Dentistry, University of Central Lancashire, Preston, PR1 2HE, UK.
Jane Frances Rutt-HowardSchool of Medicine and Dentistry, University of Central Lancashire, Preston, PR1 2HE, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The NHS Long Term Workforce Plan aims for 10,000 physician associates (PAs, formerly physician assistants) by 2036/7. This article uses three modelling approaches to project the UK PA supply from a baseline of 2014-2021 through to 2038 to forecast the profession's growth. Methods: The number of cClinically available PAs' (cPAs; qualified PAs either working clinically or seeking clinical employment) was estimated using raw data from the 2014-2021 Faculty of Physician Associates censuses. This provided baseline data for all models (linear regression (LRM), exponential regression (ERM) and time-series forecast (TSFM)). Attrition, using data from other healthcare professions, was also modelled. Results: Discussion: This article permits a wider view of potential PA numbers, with broad agreement between the LRM and the TSFM. It appears that future PA demand will be met, but factors such as attrition could impede this. Attrition itself may be mitigated through adequate resourcing, appropriate support mechanisms, and the development of a career structure. Professional regulation and legislation will further support PAs to work to their potential, subject to appropriate patient safety measures.

Indexed as

Health workforceMedical associate professionalsPhysician assistantsPhysician associatesPredictive modelling

Identifiers

PMID39346935
PMCPMC11437936

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.