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An examination of cancer patients’ monthly ‘out-of-pocket’ costs in Ontario, Canada

2007· article· en· W2000488789 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEuropean Journal of Cancer Care · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsWestern UniversitySunnybrook Health Science CentreMcMaster UniversityCancer Care OntarioLondon Health Sciences CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineMedical prescriptionHealth careDemographyMultivariate analysisFamily medicineGovernment (linguistics)Environmental healthInternal medicineNursing

Abstract

fetched live from OpenAlex

Ontario cancer patients' monthly out-of-pocket costs (OOPC) were assessed to determine whether these costs were problematic. A self-administered questionnaire was administered to breast (n = 74), colorectal (n = 70), lung (n = 68) and prostate (n = 70) cancer patients between October 2001 and April 2003. It measured categorical OOPC, which were analysed using linear regression modelling, to determine whether any of a variety of independent variables influenced OOPC. Monthly OOPC (mean, range) were: parking/fares ($47, $0-450), devices ($46, $0-2350), prescription drugs ($45, $0-1400), accommodation ($43, $0-1500), complementary and alternative medicine ($29, $0-5000), vitamins ($25, $0-400), homemaking ($14, $0-1000), family care ($12, $0-1200), homecare ($2, $0-330) and other ($8, $0-250), with the total averaging $213 ($0-5230). Imputed travel mileage costs added $372 ($0-6180). Most patients were well served by the current healthcare programmes. In multivariate analysis, variables influencing several OOPC categories were: tumour site, hospitalization, age, and number of clinic trips. Travel costs proved the most problematic, with patients under 65 years and without insurance more likely to have high OOPC. Education and income were not reliable predictors for high OOPC. Many of these costs were for items not traditionally covered by public healthcare financing systems, raising important issues around defining 'medically necessary' care and the role of government.

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 score0.152
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.263
Teacher spread0.231 · 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