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Record W2414866897

Cancer Care Ontario's New Drug Funding Program: controlled introduction of expensive anticancer drugs.

2002· article· en· W2414866897 on OpenAlexaffabout
William K. Evans, Marilyn F. Nefsky, Joseph L. Pater, George P. Browman, D. H. Cowan

Bibliographic record

VenuePubMed · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsCancer Care Ontario
Fundersnot available
KeywordsMedicineCancer drugsFamily medicineAdvisory committeeDrugFiscal yearCancerPublic administrationFinancePharmacologyBusinessInternal medicinePolitical science
DOInot available

Abstract

fetched live from OpenAlex

In the mid 1990s, the high cost and increasing number of new anticancer and supportive care drugs began to result in an inequality of access to promising new treatment approaches in the Province of Ontario. Starting with a single drug, paclitaxel, in 1995, the New Drug Funding Program has evolved to a provincial program that enables cancer patients in Canada's most populous province to equitably access new and expensive, intravenously administered drugs. This article describes the development of the program, including the evolution of the administrative mechanisms necessary to manage the program and the decisions of the Policy Advisory Committee that shape provincial funding policies. In fiscal year 2000/2001, the Program made 14 drugs available for 24 indications for a total provincial expenditure of approximately $37.7 million. These intravenous drugs can now be accessed through nine Regional Cancer Centres, the province's only cancer hospital (Princess Margaret Hospital) and 80 community hospitals and will directly benefit more than 8,700 patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.000

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 head0.072
GPT teacher head0.270
Teacher spread0.198 · 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.

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

Citations13
Published2002
Admission routes2
Has abstractyes

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