Resources to Support Canadian Nurses to Deliver Virtual Care: Environmental Scan
Notice bibliographique
Résumé
BACKGROUND: Regulatory and professional nursing associations have an important role in ensuring that nurses provide safe, competent, and ethical care and are capable of adapting to emerging phenomena that influence society and population health needs. Telehealth and more recently virtual care are 2 digital health modalities that have gained momentum during the COVID-19 pandemic. Telehealth refers to telecommunications and digital communication technologies used to deliver health care, support health care provider and patient education, and facilitate self-care. Virtual care facilitates the delivery of health care services via any remote communication between patients and health care providers and among health care providers, either synchronously or asynchronously, through information and communication technologies. Despite nurses' adaptability to delivering virtual care, many have also reported challenges. OBJECTIVE: This study aims to describe resources about virtual care, digital health, and nursing informatics (ie, practice guidelines and fact sheets) available to Canadian nurses through their regulatory and professional associations. METHODS: An environmental scan was conducted between March and July 2023. The websites of nursing regulatory bodies across 13 Canadian provinces and territories and relevant nursing and a few nonnursing professional associations were searched. Data were extracted from the websites of these organizations to map out educational materials, training opportunities, and guidelines made available for nurses to learn and adapt to the ongoing digitalization of the health care system. Information from each source was summarized and analyzed using an inductive content analysis approach to identify categories and themes. The Virtual Health Competency Framework was applied to support the analysis process. RESULTS: Seven themes were identified: (1) types of resources available about virtual care, (2) terminologies used in virtual care resources, (3) currency of virtual care resources identified, (4) requirements for providing virtual care between provinces, (5) resources through professional nursing associations and other relevant organizations, (6) regulatory guidance versus competency in virtual care, and (7) resources about digital health and nursing informatics. Results also revealed that practice guidance for delivering telehealth existed before the COVID-19 pandemic, but it was further expanded during the pandemic. Differences were noted across available resources with respect to terms used (eg, telenursing, telehealth, or virtual care), types of documents (eg, guideline vs fact sheet), and the depth of information shared. Only 2 associations provided comprehensive telenursing practice guidelines. Resources relative to digital health and nursing informatics exist, but variations between provinces were also noted. CONCLUSIONS: The use of telehealth and virtual care services is becoming mainstream in Canadian health care. Despite variations across jurisdictions, the existing nursing practice guidance resources for delivering telehealth and virtual care are substantial and can serve as a beginning step for developing a standardized set of practice requirements or competencies to inform nursing practice and the education of future nurses.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,012 | 0,003 |
| Communication savante | 0,006 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 source (Gemma direct ou Codex distillé), 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 ».