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Record W2585023117 · doi:10.1922/cdh_4028hill05

Productive efficiency and its determinants in the Community Dental Service in the north-west of England.

2017· article· en· W2585023117 on OpenAlexaff
Harry Hill, Stephen Birch, Martin Tickle, Ruth McDonald, Paul Brocklehurst

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldHealth Professions
TopicDental Education, Practice, Research
Canadian institutionsMcMaster University
FundersNational Institute for Health and Care Research
KeywordsMedicineService (business)North westNew englandOptometrySocioeconomicsDentistryFamily medicineMarketingPoliticsLawPhysical geography

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess the efficiency of service provision in the Community Dental Services and its determinants in the North-West of England. SETTING AND SAMPLE: 40 Community Dental Services sites operating across the North-West of England. BASIC RESEARCH DESIGN: A data envelopment analysis was undertaken of inputs (number of surgeries, hours worked by dental officers, therapists, hygienists and others) and outputs (treatments delivered, number of courses of treatment and patients seen) of the Community Dental Services to produce relative efficiency ratings by health authority. These were further analyzed in order to identify which inputs (determined within the Community Dental Services) or external factors outside the control of the Community Dental Services are associated with efficiency. MAIN OUTCOME MEASURE: Relative efficiency rankings in Community Dental Services production of dental healthcare. RESULTS: Using the quantity of treatments delivered as the measure of output, on average the Community Dental Services in England is operating at a relative efficiency of 85% (95% confidence interval 77%- 99%) compared to the best performing services. Average efficiency is lower when courses of treatment and unique patients seen are used as output measures, 82% and 68% respectively. Neither the input mix nor the patient case mix explained variations in the efficiency across Community Dental Services. CONCLUSIONS: Although large variations in performance exist across Community Dental Services, the data available was not able to explain these variations. A useful next step would be to undertake detailed case studies of several best and under-performing services to explore the factors that influence relative performance levels.

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)0.004
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.165
GPT teacher head0.464
Teacher spread0.299 · 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.

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

Citations4
Published2017
Admission routes1
Has abstractyes

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