Drug use evaluation of oral antibiotics prescribed in the ambulatory care settings in the Canadian armed forces.
Bibliographic record
Abstract
OBJECTIVES: The primary objective was to evaluate the level of compliance of military prescribers (physician assistants, general practitioners and specialists) with treatment guidelines for commonly encountered community-based infections. The secondary objective was to identify infections encountered in the Canadian Forces ambulatory care services and to determine which ones were most frequently associated with noncompliance or partial compliance for the purpose of developing a training program for prescribers. METHODS: Retrospective chart review was performed using prescriptions written within a predetermined time frame. Appropriateness of prescribing was evaluated by comparing the drug prescribed for the indication with two sets of guidelines. RESULTS: A total of 704 charts were reviewed, of which 458 charts met inclusion criteria. From these, 477 prescriptions for anti-infectives were analyzed. Seventy-three per cent of the prescriptions analyzed were for the treatment of infections related to the respiratory system. Compliance rates were similar between physician assistants and general practitioners (ie, 86.2% and 85.3%, respectively). There were not enough data to assess accurately the compliance rate of specialists. The indications most commonly associated with noncompliance and/or partial compliance were bronchitis, community-acquired pneumonia, cellulitis, otitis media, pharyngitis, sinusitis and urinary tract infections. CONCLUSION: The majority of prescriptions met the criteria for compliance and the compliance rates among physician-assistants and general practitioners were similar. However, certain indications were associated with a significant level of partial or noncompliance. A training program should be developed to improve adherence to prescribing guidelines.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".