A Practical Guide to Building, Evaluating and Refining a Multi-Sector Community-Based Integrated Care Model for Seniors
Notice bibliographique
Résumé
Background: Integrated care models that bring together health and social care services in the communities where people live are necessary to meet people’s needs in an effective, person-centred, and sustainable manner. However, designing, implementing, and evaluating these models remain challenging particularly given the complexity of need, services, and partnerships. Objectives: Over the last three years, we utilized a learning health system approach to design, implement, evaluate, and revisit our integrated care model that aims to integrate health and social care for seniors, with a focus on those facing socioeconomic or other challenges. The Community Wellness Hub is an alliance of health and social service providers that coordinate and deliver services to seniors. The Hub is located in affordable housing buildings and provides services to individuals who reside in the building and surrounding area. The aim is to enable members to lead healthy and fulfilling lives in the community by proactively addressing health and wellness needs and reducing health crises requiring acute care. Services provided are an intersection of three systems: health care, housing, and social care, spanning 15 organizations. In this workshop, we share the journey of the Community Wellness Hub from inception to date. We will reflect on facilitators, challenges, and learnings in three main areas: building and implementing the hub, evaluating the implementation, and enacting the results of the evaluation. Proposed Audience: Proposed participants include policy makers, program designers, evaluators, quality improvement specialists, patients, and caregivers as well as researchers interested in designing and evaluating complex integrated care initiatives. Structure: •The first 5-10 minutes of the workshop will be a round table introduction •Then 5 minutes for introducing the Community Wellness Hub and the agenda of the workshop to the participants •The last 10 minutes will be for summarizing the lessons learned and take-home messages. Similarities and variations amongst jurisdictions will be reflected on based on the participants •Then the rest of the time will be divided into three equal parts. The first will cover the creation of the hub, then the evaluation and finally enacting of the evaluation results into actionable steps. Each of the three sections will start by an open question inviting the audience to work in small groups to answer this question. These questions are: what are the key elements when creating a hub model via a partnership that spans health, social and community care? How to evaluate the implementation of an integrated hub model? How to enact the evaluation results? •After each group discussion, we will connect to reflect on the various approaches. Following that the presenters will share the approach they used within the hub highlighting resources, methods, tools, and practical tips. Outcome: By the end of the workshop, participants are expected to have learned some practical tips around designing, implementing, evaluating and utilizing the evaluation results in the context of integrating health and social care that may be applied to their local programs or initiatives.
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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 | 0,023 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,005 | 0,005 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,068 | 0,024 |
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 ».