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Record W1556713028

Beneficiary cost sharing under Canadian provincial prescription drug benefit programs: history and assessment.

2002· preprint· en· W1556713028 on OpenAlexaffabout
Paul Grootendorst

Bibliographic record

VenuePubMed · 2002
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMcMaster UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsBeneficiaryLegislationCost sharingGovernment (linguistics)BusinessMedical prescriptionGenerosityPrescription drugMandateHealth careEconomic growthMedicineFinancePolitical scienceEconomicsNursing
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Federal legislation outlined in the Medical Care Act of 1966 and the Canada Health Act of 1984 stipulates that Canadian provincial governments are to administer insurance programs for "medically necessary" services provided by hospitals and physicians. The legislation did not mandate provincial government coverage for prescription drugs taken outside of the hospital. Each province has, however, provided coverage to senior citizens and social assistance recipients; some provinces have introduced drug coverage for the general public. METHODS: The present paper reviews the history of the provincial drug insurance programs for these three beneficiary groups (seniors, social assistance recipients and the general public), from the inception dates of the programs to October 31, 2000. Attention is given to eligibility conditions and amounts of beneficiary cost sharing. RESULTS: A review of the history of the provincial drug programs reveals a significant variation in the amounts of patient cost sharing between and within programs and over time. In addition, starting in the early 1990s, there was a trend in most provinces to increase the generosity of coverage for those with large drug expenses relative to income, irrespective of beneficiary age, typically at the expense of reduced coverage for senior citizens. Some implications of this trend are drawn in light of evidence of the deleterious effects of cost sharing targeted at senior citizens.

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)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.555

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0110.029
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.369
GPT teacher head0.353
Teacher spread0.016 · 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 designNot applicable
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

Citations19
Published2002
Admission routes2
Has abstractyes

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