MétaCan
Menu
Back to cohort
Record W2031268988 · doi:10.1016/j.hcmf.2010.02.005

Learning Lessons from the National Health Service

2010· article· en· W2031268988 on OpenAlexaffabout
Jasbir Sunner

Bibliographic record

VenueHealthcare Management Forum · 2010
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsHumber River Regional Hospital
Fundersnot available
KeywordsGeneral partnershipClinical governancePublic relationsHealth careCorporate governanceSalientContext (archaeology)Healthcare systemBusinessPolitical scienceKnowledge managementMarketingComputer scienceGeography

Abstract

fetched live from OpenAlex

The Canadian College of Health Service Executives has recently formalized a learning partnership with the UK's Institute of Healthcare Management. The development of such a partnership offers Canadian healthcare leaders an opportunity to learn from the UK's decade long multibillion pound effort to improve its healthcare system using a multipronged approach. This article provides an initial insight into the UK system starting with some of the high-level cultural differences between the UK and Canada. It is important to be aware of these differences as an appreciation of the context of the UK system can assist Canadian leaders in adapting the positive aspects to our system. The article describes some of the high-level cultural differences and then focuses on 3 specific areas that hold salient lessons for Canada: (1) the evolution of the primary care system, (2) the collection of structured and comparable consumer/patient feedback, and (3) a focus on quality (or clinical governance).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.728
Threshold uncertainty score0.546

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0140.010
Scholarly communication0.0110.006
Open science0.0020.006
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0070.001

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 head0.148
GPT teacher head0.493
Teacher spread0.345 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueHealthcare Management ForumSame topicHealthcare Quality and ManagementFrench-language works237,207