1365Identifying Opportunities to Improve Environmental Hygiene in Multiple Healthcare Settings
Notice bibliographique
Résumé
Background. Near-patient surfaces play a role in transmission of pathogens in healthcare settings. Thus, disinfection cleaning is an important infection prevention intervention. Our previous studies objectively documented opportunities to improve environmental cleaning in acute care hospitals. We used the same evaluation system to analyze cleaning practice in a range of defined healthcare venues. Methods. Trained healthcare professionals, primarily infection preventionists and hospital epidemiologists, in 140 facilities (121 acute care hospitals and 19 long-term care facilities) covertly evaluated disinfection cleaning practice using a fluorescent targeting system (DAZO®) to objectively quantify cleaning compliance of standardized sets of near-patient surfaces that had a high risk of transmitting pathogens between patients and healthcare workers. The objects chosen were specific to the particular venue evaluated. Results were expressed as the percentage of surfaces marked with the fluorescent target that were cleaned (DAZO® removed). Results. As summarized in the figure, thoroughness of discharge cleaning of 52,931 objects in 4,243 medical/surgical and ICU rooms averaged 49% (95% CI = 48.1 to 51.0). Thoroughness of daily cleaning of: 3,657 objects in 271 implantation operating rooms was 24%; 1,160 objects in 84 adult ICU rooms was 26%; 3,680 objects in both common areas and patient rooms in long-term care facilities was 24%; and 610 objects in 38 ambulatory clinic treatment areas was 20%. While potentially overestimated as a result of a Hawthorne effect, daily cleaning, which averaged 25%, was significantly less thorough than discharge cleaning (p = <.0001). Conclusion. The thoroughness of disinfection cleaning was surprisingly similar in the 129 facilities evaluated. Covert evaluation of disinfection cleaning of both inpatient and outpatient care areas consistently revealed opportunities for practice improvement. These findings were also similar to affiliated studies in Canada and Australia and they provided an objective basis for subsequent successful process improvement projects in all sites that implemented structured programs to enhance the thoroughness of cleaning practice. Disclosures. P. Carling, Ecolab: Patent License and Speaker's Bureau, Consulting fee and Licensing agreement or royalty S. S. Huang, Sage Products: Conducting clinical trial for which contributed product is being provided to participating hospitals, Contributed Product; Molnlycke: Conducting clinical trial for which contributed product is being provided to participating hospitals, Contributed product
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».