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Record W4416451292 · doi:10.1016/j.hpopen.2025.100155

Oral health care’s contribution to catastrophic spending in Canada: a descriptive study

2025· article· en· W4416451292 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealth Policy OPEN · 2025
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsWestern UniversityPublic Health OntarioUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchResearch and Development Corporation of Newfoundland and LabradorCanada Foundation for Innovation
KeywordsDescriptive researchOral healthDescriptive statisticsQualitative researchGovernment (linguistics)Oral cavity

Abstract

fetched live from OpenAlex

Background: Oral health care (OHC) in Canada is largely financed through employer-sponsored insurance and out-of-pocket (OOP) payments and is generally excluded from its system of universal health coverage, although public financing will increase substantially with the introduction of the Canadian Dental Care Plan (CDCP). We generate estimates of catastrophic health expenditure (CHE) in Canada and assess the contribution of OOP spending in OHC on CHE between 2010 and 2019. Methods: We examined the Survey of Household Spending from 2010 to 2019 by year and in pooled cross-sections and followed the WHO/Europe methodology to determine CHE. Spending OOP in OHC was compared to medicines, medical products, outpatient care, diagnostic tests, and inpatient care. We assessed CHE and the share of OOP spending annually, nationally, provincially, across income quintiles and presence of private insurance including oral health coverage. Results: Estimates in CHE dropped from 5 % (2010) to 3.4 % (2019) and was more common among lower income groups, those without private insurance and Québec residents. Oral health care was the second highest contributor to CHE (after medicines) especially among the lowest income groups. Having private insurance yielded a higher share of OOP spending among lower than higher income groups. Conclusions: From 2010 to 2019, OOP spending in OHC was the second-highest contributor to CHE in Canada. Further monitoring is warranted to ensure financial protection is achieved for OHC after the full implementation of the CDCP.

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.

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)0.001
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 score0.165
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.058
GPT teacher head0.445
Teacher spread0.387 · 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