An International Working Definition for Quality of Oral Healthcare
Bibliographic record
Abstract
To assess and improve the quality of oral healthcare, we must first agree on what constitutes good care. Currently there is no internationally accepted definition for quality of oral healthcare. Therefore, the purpose of the study was to establish a working definition for quality of oral healthcare that would help to advance further improvements in the field of quality improvement in oral healthcare. The development of the working definition included a 3-step approach: 1) literature screening; 2) expert-based compilation of an initial list of topics, leaning on the National Academy of Medicine framework for quality of care; and 3) a World Café with voting, which took place during the annual general meeting of the International Association for Dental Research in 2018. Following this approach, the collective intelligence of involved participants yielded a comprehensive list of items, prioritized by relevance. The resulting working definition comprises 7 domains—patient safety, effectiveness, efficiency, patient-centeredness, equitability, timeliness, access to care—and 30 items, which together characterize quality of oral healthcare. This aspirational working definition provides the potential to facilitate further conversations and activities aiming at quality improvement in oral healthcare. KNOWLEDGE TRANSFER STATEMENT: This special communication describes the development of a working definition for quality of oral healthcare. The findings of this study are intended to raise awareness of the relevance of quality improvement initiatives in oral healthcare. The working definition described here has the potential to facilitate further conversations and activities aiming at quality improvement in oral healthcare.
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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 | 0.073 | 0.078 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.018 | 0.012 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.006 | 0.017 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".