Transition from a dedicated to a non-dedicated, ward-based pharmacist antimicrobial stewardship programme model in a non-academic hospital and its impact on length of stay of patients admitted with pneumonia: a prospective observational study
Bibliographic record
Abstract
Pharmacists play an integral role in antimicrobial stewardship (AS). Some AS programmes employ dedicated pharmacists, sometimes with infectious diseases (ID) training, while others employ ward-based pharmacists. The role and impact of both are under investigation. This study compares the length of stay (LOS) of patients admitted to hospital with community-acquired pneumonia (CAP) after the implementation of an AS programme initially led by a dedicated ID-trained pharmacist, and then transitioned to a ward-based pharmacist. Starting 1 April 2013, all adult patients admitted with CAP were prospectively reviewed by the AS programme. The control period (phase 0) lasted 3 months. Thereafter, AS was implemented in each of four medicine wards at 2-month intervals in a staggered fashion. During this period (phase 1), an ID-trained pharmacist and physician performed daily prospective audit and feedback. After 24 months, ward-based pharmacists assumed this AS role (phase 2). Over the 36-month study period, 1125 patients with CAP were entered into the AS database, with 518 and 247 patients receiving an AS audit and feedback in phases 1 and 2, respectively. The acceptance rate for AS recommendations was similar for phases 1 and 2, each exceeding 82%. After accounting for secular trends, the overall reduction in LOS was 19.4% (95% CI 1.4% to 40.5%). There was no difference in LOS between phases 1 and 2. This study demonstrated that an AS audit and feedback intervention reduced the median LOS in patients with CAP by approximately 0.5 days regardless of pharmacist model. However, fewer patients were exposed to the AS intervention in phase 2, suggesting dedicated AS pharmacists may be necessary to realise the full benefits of AS.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".