Healthier Together: Strengthening collaboration, social value and getting to health and wellbeing outcomes.
Notice bibliographique
Résumé
Background: Over 60% of health is shaped by the places where we spend our time, our relationships, and the circumstances in which we live, work, learn, play, and age. Creating healthy environments with communities, workplaces, schools, and health care settings is one of the best ways to keep people healthy and well. For more than a decade, Alberta Health Services (AHS), in Alberta, Canada has implemented Healthier Together projects with partners across the province in individual settings based on funding and operational priorities. Action across settings must be coordinated and integrated to realize improvements in local and population health and well-being priorities. Healthier Together takes a super setting approach which is more than a multi setting approach. The coordination and integration of activities at a system level and across multiple settings provides the basis for synergistic effects and an impactful and sustainable approach to health promotion. Approach: Healthier Together is a population health approach designed that can be adapted and adaptable to meet various communities' needs. From small rural communities to large urban centers, this asset-based community development approach and population health principles are designed to impact the health and well-being of whole populations.At the system level, Healthier Together breaks down silos and enhances collaboration across the health system (public health, primary care, acute care, chronic disease prevention, data, and analytics, etc.) through a connected governance structure that has implementation, research, evaluation, analytics, communication, and engagement support at its core. At the local level, Healthier Together creates opportunities for intersectoral partners in health, education, employment, municipal government, social services, and citizens within diverse communities to work together across the pillars of integrated care to strengthen collaboration, create social value, and improve health and well-being outcomes. We have collaborated with seven diverse communities in Alberta, Canada to implement Healthier Together across multiple settings. This includes the establishment of multisectoral teams (MSTs) in each community which comprise of individuals from different settings and sectors who engage with the community to understand and identify health promotion priorities, design, implement and evaluate evidence-informed action plans to address those priorities, and then sustain the health promotion interventions.An evaluation framework has been designed which aims to measure collaboration at the system and local level using the Wilder Collaboration Factors Inventory, use a multi-level perspective framework to tell the story of change in each community, and measure the social value and collective impact of implementing the integrated actions across settings on population health and well-being outcomes through a social return on investment (SROI) analysis. Results: The Healthier Together approach has sparked collaboration across settings in the communities and has led to the identification of community health promotion priorities including food security, financial well-being, and social connectedness. Surveys have been deployed to measure collaboration at the system and local level, the data collection plan is being finalized for the multi-level perspective framework and forecast SROI analyses have begun in the communities. Initial results will be ready to share in Fall 2024. Implications: Findings from this work are anticipated to demonstrate the value of cross-setting collaboration to implement evidence-based strategies for improving population health and well-being. There is a plan to scale-up the seven community initiatives as well as Healthier Together as a unified approach to population health improvement.
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 | 0,025 | 0,028 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,012 | 0,009 |
| Communication savante | 0,010 | 0,011 |
| Science ouverte | 0,004 | 0,053 |
| Intégrité de la recherche | 0,004 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,022 | 0,004 |
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 ».