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Is Regular Visiting Associated with Lower Costs? Analyzing Service Utilization Patterns in the First Nations Population in Canada

2006· article· en· W1971029696 on OpenAlexaffabout
James L. Leake, Stephen Birch, Patricia A. Main, Elsa Ho

Bibliographic record

VenueJournal of Public Health Dentistry · 2006
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicinePopulationService (business)DemographyHealth careRecallTest (biology)Dental careFamily medicineGerontologyPsychologyEnvironmental healthBusiness

Abstract

fetched live from OpenAlex

OBJECTIVES: Using an administrative database of dental service records from the Non-Insured Health Benefits (NIHB) program of Health Canada for 1994-2001, the authors set out to test whether regular visitors had lower program expenditures. METHODS: The age-specific mean expenditures per client were compared among those with regular examinations in 8, 7 and fewer years. The study further examined the effect of regular visiting over the first 6 years on expenditures in the last 2 years. "Continuity of care" was measured by the numbers of consecutive years prior to 2000 in which clients had a regular examination. In a "gap analysis" individuals were classified according to the number of years prior to 2000 since they last had an initial or recall examination. Mean expenditures per client were analyzed by age group and type of service. FINDINGS: Over the 8-year period, clients with regular visits had the highest expenditures. In both the continuity of care and gap analyses, the findings were generally consistent; the more that clients visited over the first 6 years, the higher the expenditures in the final 2 years. Clients with more "regular" (initial and recall) examinations received a relatively standard, age-specific, pattern of service but incurred greater expenditures compared to clients with fewer regular, or longer gaps in, examinations. CONCLUSION: The observations of the authors in this client group do not support the thesis that regular visiting is associated with lower expenditures on dental care.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.312
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.314
Teacher spread0.276 · 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

Citations9
Published2006
Admission routes2
Has abstractyes

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