Profiling health-care accreditation organizations: an international survey
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
OBJECTIVE: To describe global patterns among health-care accreditation organizations (AOs) and to identify determinants of sustainability and opportunities for improvement. DESIGN: Web-based questionnaire survey. PARTICIPANTS: Organizations offering accreditation services nationally or internationally to health-care provider institutions or networks at primary, secondary or tertiary level in 2010. MAIN OUTCOME MEASURE: s) External relationships, scope and activity public information. RESULTS: Forty-four AOs submitted data, compared with 33 in a survey 10 years earlier. Of the 30 AOs that reported survey activity in 2000 and 2010, 16 are still active and stable or growing. New and old programmes are increasingly linked to public funding and regulation. CONCLUSIONS: While the number of health-care AOs continues to grow, many fail to thrive. Successful organizations tend to complement mechanisms of regulation, health-care funding or governmental commitment to quality and health-care improvement that offer a supportive environment. Principal challenges include unstable business (e.g. limited market, low uptake) and unstable politics. Many organizations make only limited information available to patients and the public about standards, procedures or results.
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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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