Pediatric Endoscopy Quality Improvement Network Quality Standards and Indicators for Pediatric Endoscopy Facilities
Bibliographic record
Abstract
INTRODUCTION: There is increasing international recognition of the impact of variability in endoscopy facilities on procedural quality and outcomes. There is also growing precedent for assessing the quality of endoscopy facilities at regional and national levels by using standardized rating scales to identify opportunities for improvement. METHODS: With support from the North American and European Societies of Pediatric Gastroenterology Hepatology and Nutrition (NASPGHAN and ESPGHAN), an international working group of the Pediatric Endoscopy Quality Improvement Network (PEnQuIN) used the methodological strategy of the Appraisal of Guidelines for REsearch and Evaluation (AGREE) II instrument to develop standards and indicators relevant for assessing the quality of facilities where endoscopic care is provided to children. Consensus was reached via an iterative online Delphi process and subsequent in-person meeting. The quality of evidence and strength of recommendations were rated according to the GRADE (Grading of Recommendation Assessment, Development and Evaluation) approach. RESULTS: The PEnQuIN working group achieved consensus on 27 standards for facilities supporting pediatric endoscopy, as well 10 indicators that can be used to identify high-quality endoscopic care in children. These standards were subcategorized into three subdomains: Quality of Clinical Operations (15 standards, 5 indicators); Patient and Caregiver Experience (9 standards, 5 indicators); and Workforce (3 standards). DISCUSSION: The rigorous PEnQuIN process successfully yielded standards and indicators that can be used to universally guide and measure high-quality facilities for procedures around the world where endoscopy is performed in children. It also underscores the current paucity of evidence for pediatric endoscopic care processes, and the need for research into this clinical area.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".