MétaCan
Menu
Retour à la cohorte
Enregistrement W2790257511 · doi:10.1016/j.ajic.2017.12.018

Effect of electronic real-time prompting on hand hygiene behaviors in health care workers

2018· article· en· W2790257511 sur OpenAlexafffund
Steven Pong, P. J. Holliday, Geoff Fernie

Notice bibliographique

RevueAmerican Journal of Infection Control · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueInfection Control in Healthcare
Établissements canadiensToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
Organismes subventionnairesCanadian Institutes of Health ResearchToronto Rehabilitation InstituteOntario Ministry of Health and Long-Term Care
Mots-clésMedicineHygieneOdds ratioConfidence intervalNursingNursing staffRandomized controlled trialDuration (music)Infection controlPhysical therapySurgeryInternal medicine

Résumé

récupéré en direct d'OpenAlex

•Real-time prompting when opportunities are missed approximately doubles handwash dispenser use.•Changes to prompt duration affect hand hygiene performance.•Staff members perform hand hygiene sooner after entering a patient room when they are prompted.•Increased hand hygiene performance with system use is maintained over a year but user participation rate drops. BackgroundPoor hand hygiene by health care workers is a major cause of nosocomial infections. This research evaluated the ability of an electronic monitoring system with real-time prompting capability to change hand hygiene behaviors.MethodsHandwashing activity was measured by counting dispenser activations on a single nursing unit before, during, and after installation of the system. The effect of changing the prompt duration on hand hygiene performance was determined by a cluster-randomized trial on 3 nursing units with 1 acting as control. Sustainability of performance and participation was observed on 4 nursing units over a year. All staff were eligible to participate.ResultsBetween June 2015 and December 2016, a total of 459,376 hand hygiene opportunities and 330,740 handwashing events from 511 staff members were recorded. Dispenser activation counts were significantly influenced by use of the system (χ2[3] = 75.76; P < .0001). Hand hygiene performance dropped from 62.61% to 24.94% (odds ratio, 0.36; 95% confidence interval, 0.34-0.38) when the prompting feature was removed. Staff participation had a negative trajectory of –0.72% (P < .001), whereas change in average performance was –0.18% (P < .001) per week for the year.ConclusionsUse of electronic monitoring with real-time prompts of 20 seconds' duration nearly doubles handwashing activity and causes handwashing to occur sooner after entering a patient room. These improvements are sustainable over a year. Poor hand hygiene by health care workers is a major cause of nosocomial infections. This research evaluated the ability of an electronic monitoring system with real-time prompting capability to change hand hygiene behaviors. Handwashing activity was measured by counting dispenser activations on a single nursing unit before, during, and after installation of the system. The effect of changing the prompt duration on hand hygiene performance was determined by a cluster-randomized trial on 3 nursing units with 1 acting as control. Sustainability of performance and participation was observed on 4 nursing units over a year. All staff were eligible to participate. Between June 2015 and December 2016, a total of 459,376 hand hygiene opportunities and 330,740 handwashing events from 511 staff members were recorded. Dispenser activation counts were significantly influenced by use of the system (χ2[3] = 75.76; P < .0001). Hand hygiene performance dropped from 62.61% to 24.94% (odds ratio, 0.36; 95% confidence interval, 0.34-0.38) when the prompting feature was removed. Staff participation had a negative trajectory of –0.72% (P < .001), whereas change in average performance was –0.18% (P < .001) per week for the year. Use of electronic monitoring with real-time prompts of 20 seconds' duration nearly doubles handwashing activity and causes handwashing to occur sooner after entering a patient room. These improvements are sustainable over a year.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,316
Score d'incertitude au seuil0,773

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,005
Tête enseignante GPT0,317
Écart entre enseignants0,313 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations28
Publié2018
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueAmerican Journal of Infection ControlMême sujetInfection Control in HealthcareTravaux en français237 207