A scoping review of patient engagement activities during COVID-19: More consultation, less partnership
Notice bibliographique
Résumé
BACKGROUND: The COVID-19 pandemic has had a devastating impact on healthcare systems and care delivery, changing the context for patient and family engagement activities. Given the critical contribution of such activities in achieving health system quality goals, we undertook to address the question: What is known about work that has been done on patient engagement activities during the pandemic? OBJECTIVE: To examine peer-reviewed and grey literature to identify the range of patient engagement activities, broadly defined (inclusive of engagement to support clinical care to partnerships in decision-making), occurring within health systems internationally during the first six months of the COVID-19 pandemic, as well as key barriers and facilitators for sustaining patient engagement activities during the pandemic. METHODS: The following databases were searched: Medline, Embase and LitCOVID; a search for grey literature focused on the websites of professional organizations. Articles were required to be specific to COVID-19, describe patient engagement activities, involve a healthcare organization and be published from March 2020 to September 2020. Data were extracted and managed using Microsoft Excel. A content analysis of findings was conducted. RESULTS: Twenty-nine articles were included. Few examples of more genuine partnership with patients were identified (such as co-design and organizational level decision making); most activities related to clinical level interactions (e.g. virtual consultations, remote appointments, family visits using technology and community outreach). Technology was leveraged in almost all reported studies to interact or connect with patients and families. Five main descriptive categories were identified: (1) Engagement through Virtual Care; (2) Engagement through Other Technology; (3) Engagement for Service Improvements/ Recommendations; (4) Factors Impacting Patient Engagement; and (5) Lessons Learned though Patient Engagement. CONCLUSIONS: Evidence of how healthcare systems and organizations stayed connected to patients and families during the pandemic was identified; the majority of activities involved direct care consultations via technology. Since this review was conducted over the first six months of the pandemic, more work is needed to unpack the spectrum of patient engagement activities, including how they may evolve over time and to explore the barriers and facilitators for sustaining activities during major disruptions like pandemics.
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 | 0,030 | 0,136 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,006 |
| Bibliométrie | 0,022 | 0,030 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,005 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 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 ».