Weaving Networks: How University Health Network’s NIC is supporting aging adults to create helping communities
Bibliographic record
Abstract
Over the past decade the team at UHN NORC Innovation Centre has had the privilege of learning from and working with aging adults living in naturally occurring retirement communities (NORCs). Together we have created a new integrated health and social care model that can be adapted to the needs of a diverse range of communities. The model currently supports up to ~4,000 aging adults including successfully addressing 95% of the needs identified through 0,000+ interactions. [PJ] Critical to the many successes has been the development and delivery of an Ambassador program as well as a steadfast commitment to take a participatory approach to build community and ensure aging adults have the agency to lead. The voices of aging adults guide implementation and improvement efforts as well as identify areas requiring innovation. Since many living in NORCs are relatively healthy and are living fairly independently there is a significant opportunity to preserve health system capacity by helping them stay healthy and, if needed, provide timely supports to get healthy. The community created through NORC programming as resulted in aging adults feeling they can take initiative and lead change, while their work in bringing community creates space to learn together, teach one another and normalize new ways to care for themselves and one another.These networks of mutual support resulted in the opportunity to address common health promotion and care challenges through care pathways that were initiated and co-developed by aging adults. In the first year of operation the team focused on three priorities- falls prevention, lung health and rapid access to appropriate care. We will share how care pathways have been developed and subsequently impacted care and health outcomes in participating sites. In one example, a resident who sustained a fall was cared for by a neighbour who kept a close eye for deterioration. Then, once a fractured hip was diagnosed, the person was supported by the community in the building both in the initial injury phase all through rehabilitation. Neighbors created a community of support for this person during rehab and worked closely with the NIC Team to ensure a smooth recovery.As a second example, aging adults indicated a desire to have a holistic end-to-end fall prevention, education and detection program. In this case on their won initiative, the aging adults in the building helped bring isolated individuals to the sessions, support the delivery of the intervention and assist with follow-up during the intervention.In a third example; a lung health initiative focusing on the early detection of COPD; neighbors were able to assist an individual in the building who presented as severely hypoxic. Working with the NIC Team, residents stepped up and assisted with the care delivery team to help get the person directly to the appropriate specialist while bypassing the emergency department.These and other similar instances provide several important learnings regarding people as partners in care: By providing agency to residents in buildings it possible to create a sense of confidence and courage for them to create supporting and engaged communities Responding to the needs identified in innovative ways can help create economies of scale by simultaneously reaching many individuals with one intervention. A community of aging adults can form and work with providers in delivering care to those who would normally be isolated and not have access to care. A group of aging adults can create a community of informal support for those who need extra help dealing with their conditions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".