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Record W2024891408 · doi:10.3399/bjgp13x671597

Primary care-led commissioning: applying lessons from the past to the early development of clinical commissioning groups in England

2013· article· en· W2024891408 on OpenAlexaff
Kath Checkland, Anna Coleman, Imelda McDermott, Julia Segar, Rosalind Miller, Christina Petsoulas, Andrew G. Wallace, Stephen Harrison, Stephen Peckham

Bibliographic record

VenueBritish Journal of General Practice · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsInstitute of Health Services and Policy Research
Fundersnot available
KeywordsProject commissioningContext (archaeology)PublishingMedicineVariety (cybernetics)Focus groupQualitative researchQuality (philosophy)Public relationsNursingComputer sciencePolitical scienceSociologyLaw

Abstract

fetched live from OpenAlex

BACKGROUND: The current reorganisation of the English NHS is one of the most comprehensive ever seen. This study reports early evidence from the development of clinical commissioning groups (CCGs), a key element in the new structures. AIM: To explore the development of CCGs in the context of what is known from previous studies of GP involvement in commissioning. DESIGN AND SETTING: Case study analysis from sites chosen to provide maximum variety across a number of dimensions, from September 2011 to June 2012. METHOD: A case study analysis was conducted using eight detailed qualitative case studies supplemented by descriptive information from web surveys at two points in time. Data collection involved observation of a variety of meetings, and interviews with key participants. RESULTS: Previous research shows that clinical involvement in commissioning is most effective when GPs feel able to act autonomously. Complicated internal structures, alongside developing external accountability relationships mean that CCGs' freedom to act may be subject to considerable constraint. Effective GP engagement is also important in determining outcomes of clinical commissioning, and there are a number of outstanding issues for CCGs, including: who feels 'ownership' of the CCG; how internal communication is conceptualised and realised; and the role and remit of locality groups. Previous incarnations of GP-led commissioning have tended to focus on local and primary care services. CCGs are keen to act to improve quality in their constituent practices, using approaches that many developed under practice-based commissioning. Constrained managerial support and the need to maintain GP engagement may have an impact. CONCLUSION: CCGs are new organisations, faced with significant new responsibilities. This study provides early evidence of issues that CCGs and those responsible for CCG development may wish to address.

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)0.074
metaresearch head score (Gemma)0.112
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0740.112
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0150.024
Scholarly communication0.0180.016
Open science0.0040.015
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.103
GPT teacher head0.415
Teacher spread0.312 · 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 designQualitative
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

Citations27
Published2013
Admission routes1
Has abstractyes

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