Connected Care Hub: Filling a gap with virtual transitional care and decreasing Emergency Department visits and inpatient readmissions.
Notice bibliographique
Résumé
Background: In April 2020, COVID-19 was filling Emergency Departments (EDs). The University Health Network (UHN) identified a need for coordinated care of COVID-19 patients outside the ED to reduce overcapacity burden, safely care for infected individuals, and reduce spread within UHN hospitals. The Connected Care Hub was launched with the goal of reducing this burden by providing integrated, holistic, timely and equitable access to quality patient care. A virtual clinic led by Nurse Practitioners, provided comprehensive assessment, diagnosis, and treatment of COVID-19 patients, along with close ongoing follow-up until symptoms improved. It has since expanded beyond COVID-19 to provide timely, effective care for respiratory and transitional care needs. The Hub works with home care providers, community pharmacy, specialists, and primary care providers to better support patients and address gaps in transitional care. Population/Engagement: Co-developed by partners from public health, government, acute, primary, home and community care, and involved partnership with local public health units as well as regional and provincial levels of governments. The Hub works closely with inter-professional teams including transplant, oncology, infectious disease, internal medicine, ED, primary care providers, and community care in order to maintain and spread current knowledge, and ensure seamless care and effective transitions for these populations. The Hub serves a variety of high risk patients across Ontario, including patients with COVID-19, RSV, influenza, and pneumonia. Most respiratory patients come from EDs, Transplant and Oncology units and community clinics. Additionally, the Hub serves patients transitioning home from hospital (including CHF, COPD, diabetes). Continual monitoring and feedback from Hub NPs, patients, referring clinicians, community and primary care providers informs Hub improvements and innovations. Having a diversity of opinions, expertise, and lived experience around the table led to greater creativity, innovation, critical analysis, and strength of solutions where they are most needed. Intervention: The Hub virtual clinic provides comprehensive care for ~14 days, with support including rapid initial assessment and treatment (e.g. therapeutics), ongoing monitoring and timely access to specialists, including links to primary and home and community care, rehabilitation and psychosocial supports. Results/Impact: In the last year 2,000+ patients have benefited in being cared for at home while maintaining timely access to acute care when needed. Assuming each patient would have gone to ED, we averted ~2,000 unnecessary ED visits and prevented a minimum of 830 inpatient bed days. The Hub provides: Better patient outcomes by support of one coordinated team with a central point of contact Comprehensive care by NPs, including collaboration with community supports Lessen patient anxiety and improve self-care through timely access, continuity of care and education for self-management Equitable and accessible care, complimenting public health efforts Learnings/Next Steps: Many neighbourhoods in Toronto do not have access to this comprehensive care and this is critical to equitable access and outcomes for patients. As we expand to new populations, continued collaboration with community and patients, along with additional NP education will be critical. During this presentation, we will discuss how this model can be leveraged across multiple pathways using our principles.
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 | 0,000 | 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».