Stressed and overworked: What the Commonwealth Fund’s 2022 International Health Policy Survey of Primary Care Physicians in 10 Countries means for the UK
Bibliographic record
Abstract
Key points Key points• GPs in the UK are under extreme strain and public satisfaction with general practice has plummeted.Pressures on general practice are not unique to the UK and GPs around the world are contending with the impact of the pandemic on their patients and working lives.• 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".