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Record W2079148252 · doi:10.1258/135763306777889091

Equity of access to health care. Evidence from NHS Direct in the UK

2006· article· en· W2079148252 on OpenAlexaboutno aff
Emma Knowles, James Munro, Alicia O’Cathain, Jon Nicholl

Bibliographic record

VenueJournal of Telemedicine and Telecare · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Equity (law)HelplineMedicineHealth carePopulationSocioeconomic statusConfidence intervalTelephone surveyTelemedicineService (business)Logistic regressionFamily medicineGeographyBusinessEnvironmental healthPolitical scienceEconomic growthAdvertisingEconomics

Abstract

fetched live from OpenAlex

In the UK National Health Service (NHS), NHS Direct, the national 24-h telephone helpline, has been available in England and Wales since 2000 and has been termed a 'single gateway' to health care. We conducted a population survey of 15,004 people in areas covered by the service, which included questions about NHS Direct use and socio-economic characteristics. After removing undeliverable questionnaires, the survey response rate was 60% (8750/14,516). In all, a quarter of respondents had ever used NHS Direct (26%, 95% confidence interval 25-27), ranging from 32% of the population in Preston/Chorley (888/2,794) and Newcastle and North Tyneside (515/1,621) to 17% (2,215/8,536) in Sheffield, which had introduced the service 20 months later. Logistic regression showed that those from poorer socioeconomic groups or with communication difficulties were less likely to have used the service than others. Overcoming this apparent bias against those likely to have the greatest need is an unsolved problem not confined to telemedicine.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.069
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.091
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.069
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.001

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 head0.137
GPT teacher head0.469
Teacher spread0.332 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations42
Published2006
Admission routes1
Has abstractyes

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