Performance Measurement and Performance Management in OECD Health Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
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 ...
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it