An electronic audit tool to track the donning and doffing practices of personal protective equipment in the emergency department
Notice bibliographique
Résumé
An electronic audit tool to track the donning and doffing practices of personal protective equipment in the emergency department Maya Jusza, Ramya Sridhar, Jennifer Woods, Sharon Drury Background: Maintaining the safety of patients and healthcare professionals is a priority in all healthcare settings. Infection prevention measures such as donning and doffing practices of personal protective equipment (PPE) have become even more imperative in light of the SARS-CoV-2 pandemic. Potential PPE breaches and the degree of frontline compliance are currently being analyzed through the use of paper PPE audit tools which can be laborious and time-consuming. The development of an electronic alternative would improve frontline safety and enhance the efficiency of data collection, while optimizing the ability to share these observations with the frontline team in real time. Two nursing leadership students from the University of Alberta were tasked with developing an electronic PPE audit tool prototype for the University of Alberta Hospital’s emergency department. Implementation: An electronic PPE audit tool prototype was developed using Google Forms which provided a user-friendly interface. Google applications were used as no confidential or patient data was collected during PPE audits. The prototype auto-populated the data entries into linked spreadsheets and interactive data dashboards that visualized the data using graphs in real time. This enabled users to easily identify trends and direct educational interventions as required. Instructional one pagers and screencast videos were also created to accompany the prototype. The prototype was reviewed by and received extensive support from: Unit Managers, Patient Care Managers, Process Improvement Nurses, Infection Prevention Control (IPC), the Executive Director of the University of Alberta Hospital and Stollery emergency department and Edmonton Zone medicine programs, and the University of Alberta Hospital and Mazankowski Executive Leadership Team. Several changes and improvements were made using the Plan-Do-Study-Act cycle. This prototype has currently been replicated onto an Alberta Health Services (AHS) server and has completed the formal testing phase with a planned application launch date. Evaluation Methods: Plan-Do-Study-Act cycles were used to guide the implementation of this audit tool prototype. After development, the prototype was tested and revised which included six rounds of audit trials at the University of Alberta Hospital’s emergency department and on some inpatient medicine units. This prototype was consistently evaluated at various stages of development and changes were made to include feedback. After approval was received to recreate this prototype onto an AHS compatible server, additional changes were made to ensure functionality. These changes included adding designations and simplifying certain questions. IPC was consulted to ensure the steps outlined for donning and doffing in the prototype were accurate and reflected requirements in the clinical environment. Results: This audit tool prototype has gathered tremendous support through various demonstrations of its ability to streamline data collection in the healthcare setting. This data is relevant to the safety of both frontline workers and patients as it identifies inconsistencies in donning and doffing practices. In addition, the prototype also complements the Edmonton zone-wide PPE coaching initiative by allowing for a quantitative measurement of its efficacy. This has prompted the fast-tracked replication of an AHS compatible version with the assistance of a dedicated team that includes the creators of the prototype tool, IPC, Quality Assurance, Information Technology, and Clinical Services Development. This version has a scheduled launch date on March 22, 2021 and is to be initially rolled out to University of Alberta’s emergency department and medicine units. The objective is to eventually make this the standardized PPE audit tool throughout Alberta. Advice and Lessons Learned: 1) In order to be sustainable and implemented site-wide, an AHS compatible tool isrequired. The use of Google applications is not preferred as data will be stored outside ofthe AHS server. Even though there is no confidential information, wide-spread use mayoverwhelm the Google platform and a Gmail account is required to view data. An in-house AHS alternative has been developed. 2) Several discussions took place regarding discretions on what steps can be auditedaccording to IPC protocols. For example, some clinical nurse educators prefer handhygiene to be completed between donning steps, while this is not mandatory or auditableaccording to IPC. In addition, several discussions took place to identify the operationaland business owners of this tool which are required to support the AHS compatibleversion of the application. 3) PPE audits are vital across all hospital departments to improve the quality of healthcare.The use of PPE during patient care has grown exponentially due to the SARS-CoV2pandemic and has amplified the need for an electronic alternative to the existing paperPPE audit tool. The electronic audit tool offers an innovative way to accurately andefficiently collect and display data which will promote an improved quality of care.
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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 | 0,002 | 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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
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 ».