Adoption of Closed-System Drug Transfer Devices: Effectiveness in Reducing Occupational Exposure to Hazardous Drugs and the Change Management Process.
Bibliographic record
Abstract
Background: Closed-system drug transfer devices (CSTDs) are known to be effective in reducing hazardous drug contamination and, in turn, the risk of exposure for health care workers. In response, the Fraser Health Authority in British Columbia had plans to introduce CSTDs into practice. Objectives: To confirm the effectiveness of CSTDs in reducing hazardous drug contamination and to understand health care workers’ perspectives regarding the change management process for CSTD implementation. Methods: Surface wipe samples were collected at 4 health care facilities within the health authority over 3 time points: T0, 1 month before CSTDs were introduced; T1, 1 month after CSTDs were introduced; and T2, 5 months after implementation. Comparative analysis of drug contamination levels was conducted between 2 pairs of sampling times: T0 vs T1 and T1 vs T2. To understand the change management process, health care workers at the same departments (as those where wipe samples were collected) were surveyed. Results: A total of 156 wipe samples were collected, consisting of 13 samples at each of the 4 sites at each of the 3 time points. There was a statistically significant reduction (p < 0.01) in the sum of the mass of drug contaminants from T0 to T1 (25.82 vs 4.01 ng/cm2) and from T1 to T2 (4.01 vs 0.068 ng/cm2). About 50 individuals responded to each question of the survey, and respondents had generally positive comments regarding the transition to CSTDs. Nevertheless, suggestions for improvement included offering various forms of training (e.g., online video, hands-on sessions) and ensuring ongoing communication. Conclusions: CSTDs were confirmed to be effective in reducing surface contamination levels, and the change management process employed by the health authority appeared to be well received. Keywords: health care, occupational exposure, hazardous drugs, closed- system drug transfer devices, change management RÉSUMÉ Contexte : Les dispositifs de transfert de médicaments en système fermé (CSTD) sont reconnus pour leur efficacité à réduire la contamination par des médicaments dangereux et, par conséquent, le risque d’exposition des travailleurs de la santé. Ainsi, l’autorité sanitaire Fraser Health en Colombie-Britannique prévoyait de les introduire dans la pratique. Objectifs : Confirmer l’efficacité des CSTD pour réduire la contamination par des médicaments dangereux, et comprendre les points de vue des professionnels de la santé concernant le processus de gestion du changement lié à leur mise en œuvre. Méthodologie : Des échantillons de surface ont été prélevés dans 4 établissements de santé relevant de l’autorité sanitaire, à 3 moments différents : à T0, soit un mois avant l’introduction des CSTD; à T1, soit un mois après leur mise en œuvre; et à T2, soit cinq mois après la mise en place. Une analyse comparative des niveaux de concentration des médicaments a été réalisée entre deux paires d’intervalles (T0 contre T1 et T1 contre T2). Afin de mieux comprendre le processus de gestion du changement, les travailleurs de la santé des services où les échantillons avaient été prélevés ont répondu à un sondage. Résultats : Au total, 156 frottis de surface ont été recueillis, soit 13 échantillons à chacun des 4 établissements, à chacun des 3 moments d’échantillonnage. Une réduction statistiquement significative (p < 0,01) de la somme de la masse des contaminants médicamenteux a été observée entre T0 (25,82 ng/cm²) et T1 (4,01 ng/cm²), puis entre T1 (4,01 ng/cm²) et T2 (0,068 ng/cm²). Environs 50 personnes ont répondu à chaque question du sondage, et les répondants commentaient généralement positivement le passage aux CSTD. Néanmoins, des suggestions d’amélioration ont été formulées, notamment l’offre de formations dans différents formats (p. ex. : vidéos en ligne, séances pratiques) et en assurant une communication continue. Conclusions : L’efficacité des CSTD pour réduire les niveaux de contamination de surface a été confirmée, et le processus de gestion du changement utilisé par l’autorité sanitaire semblait bien reçu. Mots-clés : soins de santé, exposition professionnelle, médicaments dangereux, dispositifs de transfert de médicaments en système fermé, gestion du changement
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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 | 0.006 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".