MétaCan
Menu
Back to cohort
Record W3123797639

Performance Measurement and Performance Management in OECD Health Systems

2001· article· en· W3123797639 on OpenAlexaboutno aff
Jeremy Hurst, Melissa Jee-Hughes

Bibliographic record

VenueOECD labour market and social policy occasional papers · 2001
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsHealthcare systemWelfare economicsPolitical scienceHumanitiesPerformance indicatorRegional scienceGeographyHealth careManagementEconomicsArt
DOInot available

Abstract

fetched live from OpenAlex

Health systems in OECD countries are under pressure to improve their performance. Against that background, this paper has three main aims: To compare concepts of the ‘performance’ of health care systems developed by the WHO and by the OECD, with ‘performance frameworks’ adopted in selected OECD countries. To compare the key indicators of performance derived from these proposed performance concepts. A secondary objective, here, is to try to identify new performance variables that might eventually be included in OECD Health Data. To compare and contrast the different performance management arrangements in the selected OECD countries, and to evaluate the extent to which there is evidence that new indicators and new institutions have been brought together successfully to improve performance itself. In order to achieve these aims, the paper reviews the performance frameworks and some of the performance indicators adopted recently by WHO, OECD, Australia, Canada, the UK and ... Toutes sortes de pressions s’exercent actuellement pour que les systemes de sante des pays de l’OCDE s’ameliorent. Dans ce contexte, on a adopte dans la presente etude trois principaux objectifs, a savoir : Comparer la definition de la performance des systemes de sante elabores par l’OMS et l’OCDE avec les cadres d’evaluation de la performance adoptes dans plusieurs pays de l’OCDE. Comparer les indicateurs cles de performance etablis a partir de ces definitions proposees. Un deuxieme objectif dans ce contexte, pourrait etre d’identifier de nouveaux parametres de performance qui pourraient eventuellement etre inclus dans Eco-Sante OCDE. Comparer les differents mecanismes de gestion de la performance dans les pays de l’OCDE retenus et faire ressortir les differences ; evaluer dans quelle mesure les faits indiquent que de nouveaux indicateurs et de nouvelles institutions ont ete mis en œuvre avec succes pour ameliorer la performance elle-meme. On a etudie les cadres ...

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)0.044
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.058
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0120.023
Science and technology studies0.0030.009
Scholarly communication0.0120.008
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.084
GPT teacher head0.408
Teacher spread0.324 · 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 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

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueOECD labour market and social policy occasional papersSame topicHealthcare Systems and PracticesFrench-language works237,207