Healthier Together: Strengthening collaboration, social value and getting to health and wellbeing outcomes.
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.004 | 0.053 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".