Seamless Support: Improving Health Outcomes in Long-Term Care Through System Integration and Partnerships
Notice bibliographique
Résumé
Background: Increased acuity and complexity of long-term care (LTC) residents along with chronic underfunding has led to gaps in the delivery of health care services within LTC homes. In response, the integrated care system in North York, Ontario, has facilitated a partnership between the local hospital and LTC homes in the region to improve access and integration under a single program called North York Congregate Access and Support Team (NY CAST). This oral presentation will highlight our experiences creating and leading the NY CAST program, along with data on numerous quality indicators. Approach: In June 2023, a group of 88 representatives including health system planners, hospital and LTC representatives, and patient partners came together for a workshop to collaboratively design an initiative that would leveraging existing and new resources to better support local LTC homes. The North York Congregate Access and Support Team (NY CAST) model that we developed provides a variety of supports for LTC homes, including:. Nurse-Led Outreach Team. A specialized team of Advanced Practice Nurses provides remote and on-site support to LTC homes through direct provision of care, advice on care management, and capacity building activities to train LTC staff.2. Palliative Care Consults work together with the LTC care team to provide suggestions for timely symptom management, advance care planning, psychosocial, social, and spiritual support, with a focus on early integration of palliative care rather than just end of life care.3. Digital Health. All program services can be accessed via the SCOPE (Seamless Care Optimizing the Patient Experience) digital line, allowing for a one stop shop for practitioners in LTC. SCOPE connects the LTC care team to a nurse navigator, who can assist by connecting to acute care or community support services.The NY CAST program also brings together patient partners, community and hospital staff leaders, and LTC staff leaders for monthly Collaborative meetings to discuss issues and implement shared quality improvement initiatives.Experience to DateAs part of its first phase launched in July 2023, NYCAST has engaged with eight long-term care homes in North York. The Nurse-Led Outreach team has educated 25% of all staff across the 8 participating LTC homes and had over 500 encounters with LTC residents, leading to a measurable decrease in ED visits. In-person Palliative Care Consultations have been provided to over 50 LTC residents, who have subsequently experienced fewer hospital transfers or in-hospital deaths. In total, the SCOPE digital line has received over 00 calls for services.Through the first 9 months of the NY CAST program, relationships have been developed between the hospital, LTC, and patient partners, allowing for us to work collaboratively on difficult issues and develop shared priorities for the year to come. Implications: The NYCAST model is an alliance-based approach to building a model of sustainable integrated care. Most of the service changes within the program have been enabled through relationship building between sectors and a collaborative quality improvement approach. Although there are always challenges to new alliances and partnerships, dedicated champions can help overcome these concerns and build trusting relationships that allow for collaborative, solution-focused improvement across healthcare sectors.
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 | 0,014 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,003 |
| Communication savante | 0,008 | 0,006 |
| Science ouverte | 0,002 | 0,025 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 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 ».