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Record W2162984248 · doi:10.12927/hcq..16635

How Should Canada Fund the Blood System? An Evaluation of the Chargeback Proposal

2003· article· en· W2162984248 on OpenAlexaffabout
Kumanan Wilson, Laura MacDougall, Brigitte Pinard, Mohammad Al Amin, Dean Fergusson, Ian D. Graham, Morris A. Blajchman, John Freedman, Doug Angus, Paul C. Hébert

Bibliographic record

VenueHealthcare Quarterly · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIncentivePaymentStakeholderBusinessHealth careHealthcare systemPublic relationsMedicineFinanceEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The Canadian blood system is a critical interface between public health and the delivery of patient care. The organization of the blood system plays a vital role in ensuring that its functions are effectively fulfilled. Previous structural problems in the blood system led to serious health consequences by contributing to the blood transmission of hepatitis C and HIV in the 1980s. To address these problems, the Canadian blood system has recently undergone considerable organizational reform. However, policy-makers, particularly in Ontario, are considering further structural reform specifically focusing on how the blood system is financed. This move for reform is partially motivated by the rising cost of blood products and the perception that the current system has failed to provide incentives for the efficient use of these products. The suggested payment mechanism, a "chargeback system," involves the provincial ministries of health funding hospitals so that hospitals can directly purchase blood products from the Canadian Blood Services. This approach would replace the current system in which the provinces directly fund the Canadian Blood Services, which in turn provides blood products free of charge to hospitals. Based on a review of documents and stakeholder interviews, we report the potential advantages and disadvantages of a change to a new system of funding and make recommendations on how provinces should proceed.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.066
GPT teacher head0.290
Teacher spread0.224 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2003
Admission routes2
Has abstractyes

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