Impact of the COVID-19 pandemic on the Canadian healthcare workforce: a rapid evidence synthesis of key considerations, lessons learned, and promising practices to address the healthcare workforce crisis
Notice bibliographique
Résumé
BACKGROUND: The ongoing impacts of the COVID-19 pandemic on Canada's healthcare workforce and service delivery necessitate focused health system planning and delivery that prioritizes coordination, collaboration, and evidence-based strategies. A rapid evidence synthesis was commissioned by Health Canada to determine the impacts of the pandemic on the healthcare workforce and to identify promising strategies and innovations that mitigate these challenges. METHODS: Two, sequential rapid evidence syntheses were conducted between October 2022 and March 2023 using methodologies aligned with Preferred Reporting Items for Systematic reviews and Meta-Analyses literature search extension (PRISMA-S) guidelines. The first review (October-November 2022) focused on the impacts of COVID-19 on Canadian healthcare workers and mitigation strategies, while the second (November 2022-March 2023) broadened the scope to international interventions. Findings were organized by impact level (individual, organizational, system). Quality assessment of sources was not performed. RESULTS: We included 176 and 31 sources, respectively in the analysis. Sources identifying impacts of the COVID-19 pandemic described significant mental health impacts on healthcare workers, alongside changes in demand and supply of services, physical health challenges, and shifts in scopes of practice or care models. Interventions were primarily targeted at the individual or organizational level and included mental health support, training and upskilling, enhanced organizational communication and workforce planning initiatives. System-level interventions were less common, and most interventions lacked robust evaluation or evidence-informed design. CONCLUSIONS: This review highlights a significant gap in literature regarding evaluated interventions to address healthcare workforce challenges during the pandemic. While numerous sources document the adverse impacts on healthcare workers, detailed reports on specific interventions are scarce. Most interventions focus on workforce planning, education, practice scopes, recruitment and technology integration. The research underscores the need for comprehensive recommendations addressing social and mental health support, workplace safety, organizational communication and pandemic preparedness. These recommendations are vital for developing future workforce strategies, thus enabling policymakers and healthcare leaders to effectively respond to current and future healthcare challenges. This strategic approach will enhance system resilience and improve healthcare delivery across Canada.
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 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 | 0,019 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| 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) | 0,000 | 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 ».