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Record W4360614656 · doi:10.37829/hf-2023-p12

Stressed and overworked: What the Commonwealth Fund’s 2022 International Health Policy Survey of Primary Care Physicians in 10 Countries means for the UK

2023· report· en· W4360614656 on OpenAlexfundno aff
Jake Beech, Caroline Fraser, Tim Gardner, Luiza Buzelli, Skeena Williamson, Hugh Alderwick

Bibliographic record

Venuenot available
Typereport
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
FundersMinisterie van Volksgezondheid, Welzijn en SportMinistère de la SantéMinistère de la Santé et des Services sociauxRoyal New Zealand College of General PractitionersBundesamt für GesundheitCommonwealth Fund
KeywordsCommonwealthPrimary carePrimary health careFamily medicineBusinessMedicinePolitical scienceEconomic growthHealth careEconomicsLaw

Abstract

fetched live from OpenAlex

Key points •At the time of the survey, GPs in the UK reported providing a higher proportion of remote appointments than any other country.In England, GPs reported providing around 60% of appointments remotely -higher than estimates from other available data.Understanding exact rates of remote consultations is challenging -and differences between countries may be down to GP and patient preferences, policy context, COVID-19 rates and more.• GPs in the UK report assessing patients' social and economic needs, including social isolation, housing issues and domestic violence.But they also identify major barriers to coordinating support for patients -including lack of follow-up from community services and staff gaps.UK GPs rate these as greater challenges than GPs in most countries.• Decisive policy action is needed to improve the working lives of GPs in the UKincluding to boost GP capacity and reduce workload.Policymakers considering options for primary care reform should recognise the strengths of general practice in the UK and work with the profession rather than against it -not least because retaining GPs and other primary care staff is essential for the long-term sustainability of services. About this reportHow do the experiences of GPs compare between countries?And how have they changed over time?We worked with the Commonwealth Fund to survey primary care physicians in 10 high-income countries, including the UK, during 2022.The survey has been running for several years 34,35 and asks GPs about their working lives and wellbeing, quality of care and how it is delivered.The 2022 survey is the first since the COVID-19 pandemic, so we also added questions about its impact on GPs.Taken together, the data help tell us how general practice is changing internationally -for better and for worse.* Countries in the survey use different terminology to refer to physicians working in primary care and some have multiple specialties working in primary care.We use general practitioner or GP as a shorthand to refer to all primary care physicians within the survey when presenting the results.† Norway was included in the 2012, 2015 and 2019 versions of the survey, but is not included in this survey.* Margins of error for the countries of the UK are: England -4.4%, Scotland -9.8%, Wales -9.5%, Northern Ireland -11.5%.Further information, including margins of error for international comparisons, can be found in the full methodology report.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.551
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.225
GPT teacher head0.507
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations35
Published2023
Admission routes1
Has abstractyes

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