Quality criteria and certification for paediatric oncology centres: an international cross-sectional survey
Bibliographic record
Abstract
Quality criteria and certification possibilities for paediatric oncology centres vary between countries and are not widely used. An overview of the type and how quality criteria and certifications are used in countries with highly developed healthcare systems is missing. This international cross-sectional survey investigated the use of quality criteria for paediatric oncology centres and whether certification is possible. We sent an online survey to paediatric oncologists from 32 countries worldwide and analysed the survey results and provided regional or national documents on quality criteria and certification possibilities descriptively. Paediatric oncologists from 28 (88%) countries replied. In most countries, the paediatric oncology centres were partly or completely grown historically (75%), followed by the development based on predefined criteria (29%), and due to political reason (25%), with more than one reason in some countries. Quality criteria are available in 20 countries (71%). We newly identified or specified five quality criteria, in addition to those from a previously performed systematic review. Certification of paediatric oncology centres is possible in 13 countries (46%), with a specific certification for paediatric oncology in seven, and a mandatory certification in three of them. The use of quality criteria and certification possibilities are heterogeneous, with quality criteria being more frequently used than certifications. Our study provides an overview of country-specific documents and links with quality criteria, and centre certification possibilities. It can serve as a reference document for stakeholders and may inform an international harmonization of quality criteria and centre certification between countries with similar healthcare systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".