Neighbourhood Care Team - Integrated care-model for team based primary care and aging at home
Bibliographic record
Abstract
Background: Seniors are living with more severe illness, while caregivers and providers are more prone to burnout 2. Systemic barriers contribute to seniors and families inability to access appropriate and timely healthcare services and poor outcomes.The challenge of coordinating/managing multiple services is worsened by language, cultural, income and functional barriers. Target populationToronto Seniors Housing Corporation (TSHC) provides housing for 5,000 low-income seniors in 83 seniors-designated buildings across the City of Toronto. The average age of tenants is 75 with a growing population of seniors over 85. A large percentage of tenants (44%) do not speak English as their first language, live on their own (90%), and suffer from a combination of mental health and chronic conditions that contribute to high rates of social isolation (TSHC ISM, 2023). Who did you involveThe NCT model, including all levels of care planning, was co-developed with the active participation of community members and local stakeholders from a variety of organizations such as: Community services, Primary-Care, Housing, Hospitals, City services, etc. and through active engagement with over 240 tenants in 7 languages. Engagement efforts included door knocking, surveys, lobby voting, and ongoing participation of tenant volunteers in planning meetings. The approach/intervention: The North Toronto Ontario Health Team (NT OHT) Neighbourhood Care Team (NCT) is an outreach-based integrated geriatric and population health model of care. The model brings together local partners from all sectors to operate as one team, beyond the walls of their institutions, in support of low-income tenants residing in Toronto Seniors Housing Corporation (TSHC) across North Toronto.The model objective is to promote an early identification of needs and support seniors access to team-based primary care and resources to prevent crisis, decrease use of institutional care, increase quality of life and promote aging at home.This scalable model brings existing service providers under a common set of goals and structures to work as one team, with maximum impact and efficiency. Client care is coordinated such that services are provided in the appropriate sequence, using the right mix of local, in-person services, and digital channels and resources. The model includes three levels of care starting with a core team that is imbedded within the building and serves as a first point of contact. Care is delivered through a combination of in-person and digital tools to support wellness and access to care. Results: The Neighbourhood Care Team model has been implemented in five TSHC buildings, available to over 900 tenants, with 3 partnering organizations engaged.Initial results have been very promising, with reductions seen in inpatient days. Over 75 tenants were connected to primary care services. Our screening demonstrated impact on early identification of needs and access with 95% identified to have gaps in preventative care and 92.5% needed support to access dental funding available to them. Individual cases demonstrate the transformative potential of the model. Patients referred for Long-Term Care instead of returning home for over 200 days without incident and a reduction in Emergency Department visit from 2 per year to zero year to date. Implications: In this oral presentation the audience will: Understanding how housing, social services and healthcare partners can come together as one team to support improved health and social outcomes for low-income seniors. Understand how to translate patients and family input into implementation. Learn about how the model removes access barriers and promotes earlier identification of at-risk individuals. Our next steps will focus on:Advancing communication systems to improve coordination and further support tenants ongoing inclusion in decision making as part of our team approach as well as identify sustainable primary care engagement models.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".