Organisational quality and hospital pharmacists’ roles of outpatient parenteral antimicrobial therapy (OPAT) in Belgian hospitals: a national survey
Bibliographic record
Abstract
OBJECTIVES: Implementation of outpatient parenteral antimicrobial therapy (OPAT), also known as intravenous (IV) antimicrobial treatment at home, has increased in recent years. Ensuring OPAT quality is crucial to achieve positive patient outcomes. However, data on the Belgian quality of OPAT organisation is lacking. We aimed to monitor the organisational quality of OPAT in Belgian hospitals and identify roles of hospital pharmacists involved in OPAT. METHODS: A cross-sectional study applying a web-based survey on OPAT quality was conducted from 2 to 29 April 2024. The survey assessed the presence of six core and five non-core structure indicators, and OPAT-related tasks of hospital pharmacists. RESULTS: Almost two-thirds (64%; 65/101) of Belgian hospitals answered the survey, with 77% of these hospitals providing OPAT, with an increase since 2023. All 11 structure indicators were present in 6% of hospitals, while 18% had all six core structure indicators.Three of the six core structure indicators were formally present in the majority of the hospitals: a policy on patient selection criteria (76%), a structured OPAT programme (70%), and a dedicated team (64%). In contrast, a system for fast communication between the patient and OPAT team members (50%), a mechanism for urgent clinical discussions (42%), and monitoring of quality indicators (28%) were not formally present in the majority of the hospitals. The primary tasks for hospital pharmacists included overseeing OPAT prescriptions and supplying antimicrobials and related materials. CONCLUSION: While the adoption of OPAT is increasing among Belgian hospitals, significant opportunities remain for improving the quality of the OPAT organisation and expanding the OPAT-related tasks of Belgian hospital pharmacists.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".