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Record W2793482020 · doi:10.1017/s174413311700041x

Expanding Canadian Medicare to include a national pharmaceutical benefit while controlling expenditures: possible lessons from Israel

2018· article· en· W2793482020 on OpenAlexaboutno aff
Bruce Rosen

Bibliographic record

VenueHealth Economics Policy and Law · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPer capitaDistribution (mathematics)BusinessPublic economicsConstraint (computer-aided design)Health careEconomicsEconomic growthMedicineEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

In Canada, there is an ongoing debate about whether to expand Medicare to include a national pharmaceutical benefit on a universal basis. The potential health benefits are understood to be significant, but there are ongoing concerns about affordability. In Israel, the National Health Insurance benefits package includes a comprehensive pharmaceutical benefit. Nonetheless, per capita pharmaceutical spending is well below that of Canada and the Organization for Economic Co-operation and Development average. This paper highlights seven strategies that Israel has employed to constrain pharmaceutical spending: (1) prioritizing new technologies, subject to a global budget constraint; (2) using regulations and market power to secure fair and reasonable prices; (3) establishing an efficient pharmaceutical distribution system; (4) promoting effective prescribing behavior; (5) avoiding artificial inflation of consumer demand; (6) striking an appropriate balance between respect for IP rights, access and cost containment; and (7) developing a shared societal understanding about the value and limits of pharmaceutical spending. Some of these strategies are already in place in some parts of Canada. Others could be introduced into Canada, and might contribute to the affordability of a national pharmaceutical benefit, but substantial adaptation would be needed. For example, in Israel the health maintenance organizations (HMOs) play a central role in promoting effective prescribing behavior, whereas in HMO-free Canada other mechanisms are needed to advance this important goal.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.121
GPT teacher head0.392
Teacher spread0.271 · 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 designTheoretical or conceptual
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

Citations17
Published2018
Admission routes1
Has abstractyes

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