Embedding Integrated Health & Wellness Centres in Toronto Community Housing
Bibliographic record
Abstract
Introduction: Over 19,000 West Toronto residents live in Toronto Community Housing, Canada’s largest social housing provider and the second largest in North America. This population includes a mix of older adults living with frailty and chronic diseases, tenants experiencing mental health and substance use issues, and new tenants via the City of Toronto’s Rapid Rehousing Program. Through the West Toronto Ontario Health Team member organizations, Health & Wellness Centres are being embedded in Toronto Community Housing locations to provide direct access to integrated care co-designed by tenants. Engagement & Design: To develop this integrated model of care for the target populations, we applied an asset-based approach in engaging a wide variety of stakeholders including community members, Toronto Community Housing tenants and staff, and service providers in the target buildings. This engagement ranged from informal conversations with tenants in building lobbies and recreation spaces to a three-day Community Hackathon event challenging participants to develop interventions for the target populations. Volunteers, community leaders and other experts were tasked with supporting participants in developing their concepts. One example of how this practice of Appreciative Inquiry informed the design was the development of an at-home cooling kit. Concerned for older adults at risk for heat stroke and respiratory exacerbations, a mother-daughter duo with experience living without air conditioning in 40 C temperatures proposed distributing at-home cooling kits they had designed and tested that included low-cost window treatments, plants and remote temperature sensors. With the Health & Wellness Centre as the hub, tenants will pick up a kit or get connected with a neighbour for installation support. For Summer 2024, tenants who have opted-in will receive alerts to check in on a neighbour who may be at risk of a heat-related illness. Intervention: The West Toronto OHT formed a partnership with Toronto Community Housing to integrate health and social services in their buildings through the establishment of Health & Wellness Centres. These Health & Wellness Centres are staffed by service providers from across West Toronto, primary care providers, Toronto Community Housing staff, and volunteers. Based on the insights and data collected, the priority services include harm reduction educators, a weekly Good Food market, access to in-home PSW supports, social prescribing services, group and personalized mental health supports, and primary care physician appointments. The Health & Wellness Centres will also distribute resources like the at-home cooling kit and harm reduction supplies. Results: The immediate results from this initiative demonstrate a scalable model of integrated care with capacity to support some of the most complex community care. While the long-term impact on the health of the target populations is still being evaluated, the early outcomes show greater engagement with the Health & Wellness Centres than previous service models, significantly improved collaboration and care coordination between providers, and increased rates of attachment for Toronto Community Housing tenants. Next Steps: The West Toronto OHT is actively monitoring the population health impacts while planning how best to scale this model across the 85 Toronto Community Housing locations in the region.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".