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Record W2160033208 · doi:10.12927/hcq.2014.23647

Activity-Based Funding Model Provides Foundation for Province-wide Best Practices in Renal Care

2013· article· en· W2160033208 on OpenAlexaffabout
Adeera Levin, Christine Lo, Kevin Noel, Ogjnenka Djurdjev, Erlyn C Amano

Bibliographic record

VenueHealthcare Quarterly · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsBC Cancer AgencyFraser HealthVancouver Coastal Health
Fundersnot available
KeywordsTransparency (behavior)AccountabilityBest practiceFunding AgencyAgency (philosophy)Health careBusinessMedicinePopulationPublic relationsPolitical scienceEconomicsEconomic growthEnvironmental healthManagement

Abstract

fetched live from OpenAlex

British Columbia has a unique funding model for renal care in Canada. Patient care is delivered through six health authorities, while funding is administered by the Provincial Renal Agency using an activity-based funding model. The model allocates funding based on a schedule of costs for every element of renal care, excluding physician fees. Accountability, transparency of allocation and tracking of outcomes are key features that ensure successful implementation. The model supports province-wide best practices and equitable care and fosters innovation. Since its introduction, the outpatient renal services budget has grown less than the population, while maintaining or improving clinical outcomes.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.579
GPT teacher head0.542
Teacher spread0.037 · 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 designOther design
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

Citations10
Published2013
Admission routes2
Has abstractyes

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