Evidence map›Paper›PMID 41267189›Full record

ArticleHealth economics2026

Scale, Skill-Mix, and Access Implications of the Production of Appointments by Primary Care Practices in England.

Tianchang Zhao, Rachel Meacock, Matt Sutton

Abstract read
In one paragraph

Article in Health economics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Yonder: Scale, shared care, AI scribes, and trust in supervision.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
    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

3 authors.

Tianchang ZhaoHealth Organisation, Policy & Economics, School of Health Sciences. University of Manchester, Manchester, UK.ORCID 0000-0001-6063-3860
Rachel MeacockHealth Organisation, Policy & Economics, School of Health Sciences. University of Manchester, Manchester, UK.ORCID 0000-0001-8933-5058
Matt SuttonHealth Organisation, Policy & Economics, School of Health Sciences. University of Manchester, Manchester, UK.ORCID 0000-0002-6635-2127

Funding

NIHR Applied Research Collaboration Greater ManchesterNIHR School for Primary Care Research
6 · The paper itself

Abstract

Primary medical care has traditionally been provided by small organisations. Recent policy developments in many countries have encouraged larger practices in the hope of benefiting from increasing returns to scale, but there is little research evidence to support this. Using monthly data from 6149 primary care practices in England between August 2022 and July 2024, we applied a Generalized Linear Model with a logarithmic link and Poisson distribution to examine the relationship between staffing levels and appointment volumes. At the median level of administrative staffing, the estimated marginal productivity of doctors and other clinical staff on total appointments are 223 and 152 per month, respectively. The marginal effects of all types of staff on appointment volumes increase with staffing levels. We plot the isoquant and isocost curves at the median level of production and examine the implications of our findings for skill-mix and patient access. The current ratios of doctors to other clinical staff and nurses to Direct Patient Care (DPC) staff are lower than cost optimal, though this is less of an issue for larger practices who benefit more from DPC roles. Additional clinical staff improve patient access more when employed in larger practices.

Indexed as

Appointments and SchedulesHealth Services AccessibilityPrimary Health CareEfficiency, OrganizationalEnglandHumansPersonnel Staffing and SchedulingGLMGP appointmentsprimary care skill‐mixproduction functionscale

Identifiers

PMID41267189
PMCPMC12862127

What OpenQuestion holds

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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.