Health care system performance of 27 OECD countries
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
The article is based on a multidimensional conception of healthcare system performance. Our objectives are to assess the performance of the healthcare systems of 27 Organisation for Economic Co-operation and Development (OECD) countries and to discern the countries' profiles according to the homogeneity of their healthcare systems' levels of performance. The analyses were carried out on data collected from the 27 high-income OECD countries, primarily using the OECD Health Data 2007 database, the World Health Organization 2008 statistics, OECD Health at a Glance and OECD Social Indicators. Each healthcare system's performance was assessed on the basis of the volume of available resources, services produced and health outcomes achieved and efficiency, effectiveness and productivity, thus characterizing the investments made in proportion to the available resources and services produced. Overall performance profiles were constructed taking into account simultaneously the level of all these components. Using multiple clusters analysis, we were able to group the countries into four profiles (satisfactory, promising, weak-polarized and limited) according to the homogeneity of their performance levels. This article offers a broad overview of the performance of these healthcare systems. The results will enable decision-makers to know the strengths and weaknesses of their own health care system and also to compare it with those of other countries.
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.
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 | 0.004 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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