Antimicrobial Stewardship in Acute Care Centres: A Survey of 68 Hospitals in Quebec
Bibliographic record
Abstract
BACKGROUND: Antimicrobial stewardship programs (ASPs) and quantitative monitoring of antimicrobial use are required to ensure that antimicrobials are used appropriately in the acute care setting, and have the potential to reduce costs and limit the spread of antimicrobial-resistant organisms and Clostridium difficile. Currently, it is not known what proportion of Quebec hospitals have an ASP and/or monitor antimicrobial use. OBJECTIVES: To determine what proportion of Quebec hospitals have an ASP, and what is the nature of such a program. METHODS: A detailed questionnaire was sent to the pharmacy directors of all acute care hospitals in the province of Quebec. Information was collected on antimicrobial surveillance; antimicrobial stewardship and resource allocation to these areas were assessed. RESULTS: Questionnaires were completed for 68 of 81 (84%) hospitals contacted. ASPs were identified at 50 (74%) hospitals, but only 20 (29%) of hospitals had a quantitative antimicrobial surveillance program (QASP) in 2006. Academic centres (P=0.03) and hospitals with over 200 beds (P=0.02) were more likely to have a QASP. Even among hospitals with an ASP, 18% had less than one full-time pharmacist for a QASP. CONCLUSIONS: Over one-quarter of Quebec hospitals do not have an ASP, and few hospitals in Quebec are currently evaluating their use of antimicrobials on a quantitative basis. In some cases, the lack of a QASP may be due to the allocation of insufficient pharmaceutical resources to antimicrobial stewardship (ie, less than one full-time pharmacist).
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".