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Record W3005295377 · doi:10.1177/0840470419900646

Elective surgery wait time reduction in Canada: A synthesis of provincial initiatives

2020· article· en· W3005295377 on OpenAlexafffundabout
Erica Wennberg, Julie Takata, David R. Urbach

Bibliographic record

VenueHealthcare Management Forum · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsWomen's College Hospital
FundersWomen's College Hospital
KeywordsGovernment (linguistics)Reduction (mathematics)BusinessOperations managementElective surgeryMedicineEconomicsSurgery

Abstract

fetched live from OpenAlex

In an effort to reduce wait times, Canadian provincial governments have introduced numerous wait time reduction programs and policies. The objective of this study was to provide an overview of elective surgery wait time reduction initiatives across the Canadian provinces from 2000 to 2018. Each of the 10 provincial government web sites were searched. A theoretical framework for elective surgery wait time reduction policies was developed. The final framework is broadly organized into a supply-demand-performance management model. The majority were categorized as supply-oriented initiatives, which have been implemented by all the provinces in some form. Demand-oriented initiatives have been implemented the least. Our conceptual framework may be used to categorize wait time reduction initiatives for the purpose of policy development and evaluation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.922

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)0.0000.000

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 head0.016
GPT teacher head0.240
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 designObservational
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
Published2020
Admission routes3
Has abstractyes

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