O06 Development of AWaRe antibiotic quality indicators for optimal use
Bibliographic record
Abstract
Abstract Background The use of antibiotics varies by setting—hospital, outpatient/primary care—with a disproportionate impact of antimicrobial resistance in low-and middle-income countries. The WHO AWaRe (Access/Watch/Reserve) book gives detailed guidance on the optimal use of antibiotics across primary care and hospitals for adults and children with the aim of improving the quality of use of essential antibiotics. Objectives To develop universally applicable, model sets of appropriate and feasible quality indicators based on the WHO AWaRe system for primary care, hospital and general indicators for optimal antibiotic use. Methods Indicators identified in a scoping review were revised to focus on primary care and hospital facility infections in the AWaRe book. Condition-specific indicators captured measures such as appropriate antibiotic use, total daily dose and proportion of Access or Watch antibiotics. General indicators were developed from prescribing and dispensing guidelines in the AWaRe book and covered themes from proper documentation in medical records to population-level antibiotic use. The indicators were evaluated through a two-round Global Delphi Technique of 104 and 107 panellists, respectively, to determine appropriateness and feasibility in national and local settings, followed by a two-round RAND/UCLA Appropriateness Method (RAND/UCLA) with 12 panellists rating indicators on a global scale. Panels comprised experts from every WHO region. In Round 1 of each method, panellists also rated clarity and could suggest rewording or new indicators. Findings from Round 2 are reported. The median rating was calculated for each indicator to determine agreement. A median of 7–9 was considered appropriate or feasible. If ≥80% of panellists rated within ±1 of the 7–9 median, the indicator was considered appropriate with agreement. Results The indicators covered nine clinical conditions in primary care and nine in hospital settings, including respiratory tract infections, diarrhoea, urinary tract infections (UTIs), sepsis and others. There were 102 indicators (Primary Care: 46; Hospital: 39; General: 17) in Round 2 of the Delphi Technique. Of these, 100% were rated appropriate and 99 (97.1%) feasible in a local context. During the RAND/UCLA method, 136 indicators (Primary Care: 56; Hospital: 60; General: 20) were rated in Round 2, with 131 (96.3%) appropriate and 72 (52.9%) feasible in a global context. From these broad sets, 12 indicators from the Delphi Technique and 31 indicators from the RAND/UCLA method were rated both appropriate and feasible with agreement respectively. Most indicators rated appropriate and feasible with agreement by the Delphi panel measured the proportion of patients receiving Access or Watch antibiotics across clinical conditions. Those rated appropriate and feasible with agreement by the RAND/UCLA panel measured appropriate antibiotic choice, dose, duration and the proportion of Access and Watch antibiotics Conclusions These model AWaRe-based, universally applicable quality indicators can be locally adapted and measured with different tools to improve the optimal use of antibiotics and inform global and country specific antimicrobial stewardship programmes (AMS).
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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 | 0.098 | 0.152 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".