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Record W2024107441 · doi:10.1308/1355761052894266

Linking Clinical Audit in General Dental Services to Primary Care Trust Clinical Governance—Progress Report of an Approach Used in Southend

2005· article· en· W2024107441 on OpenAlexaff
Phillip Cannell

Bibliographic record

VenuePrimary Dental Care · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsClinical governanceAuditClinical auditMedicineInternal auditIntervention (counseling)NursingFamily medicineMedical educationBusinessHealth careAccountingPolitical science

Abstract

fetched live from OpenAlex

Clinical audit has been defined as the systematic, critical analysis of the quality of dental care, including the procedures and processes used for diagnosis, intervention and treatment, the use of resources and the resulting outcome and quality of life as assessed by both professionals and patients. The aim of clinical audit is to encourage dentists to self-examine different aspects of their practices, to implement improvements where the need is identified and to reexamine, from time to time, those areas that have been audited to ensure that a high quality of service is being maintained or further improved. Since 1st April 2001, all general dental practitioners (principals and assistants) working in the General Dental Services (GDS) have been required to participate in a rolling programme of at least 15 hours of clinical audit or peer review every three years. The first three-year cycle ended on 31st March 2004. By the end of December 2003, 96% of dentists had either under- taken or committed to undertake clinical audit/peer review activities. This initiative, in conjunction with the voluntary clinical audit and peer review schemes which preceded it, has provided opportunities for dentists and their practices to use these activities to assist in quality improvements in their practices, for the benefit of their patients. However, there are other methods for carrying out clinical audit and, in the NHS, there is a need to link it to clinical governance. This paper gives a progress report on an approach that has been piloted by Southend Primary Care Trust (PCT). It deals with the rationale for the project and outlines the methods used. It does not report results. These will follow in a subsequent paper.

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)0.109
metaresearch head score (Gemma)0.097
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.575

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1090.097
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0040.003
Scholarly communication0.0100.003
Open science0.0020.011
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.100
GPT teacher head0.479
Teacher spread0.379 · 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

Citations6
Published2005
Admission routes1
Has abstractyes

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