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Record W4409337003 · doi:10.5334/ijic.icic24182

Integrated Model of Primary Care Delivery for Unattached Low-Income Seniors in Community Housing

2025· article· en· W4409337003 on OpenAlexaboutno aff
Jocelyn Charles, Alison Culbert, Jane Smart, Einat Danieli, Jagger Smith, Naomi Ziegler, Stacy Landau, Jaipreet Kohli, Kiara Fine

Bibliographic record

VenueInternational Journal of Integrated Care · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicKorean Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPrimary careIntegrated careLow incomeLow income housingBusinessGerontologyMedicineNursingEconomic growthFamily medicineHealth careSociologySocioeconomicsEconomics

Abstract

fetched live from OpenAlex

City of Toronto owned Toronto Seniors Housing Corporation (TCHC) provides housing for 15,000 low-income seniors in 83 seniors-designated buildings across Toronto. The North Toronto Ontario Health Team (including primary care, hospital, community, home-care) partnered with Toronto Senior Housing to develop and implement a Neighbourhood Care Team (NCT) integrated model to address tenants' health and social needs, co-designed with the tenants. Central to the model is a multi-modal tenant engagement strategy to tailor health and social services to tenants’ needs. This engagement identified inconsistent access to family physicians. One NCT objective is to increase primary care provider connections. Identifying unattached or poorly attached tenants included door to door surveys to engage tenants regarding their barriers and the services and supports most meaningful to them, multi-organization immunization clinics with wellness checks and assistance with accessing dental and foot care, and biweekly NCT huddles. Our team worked with each tenant with inadequate or no access to primary care in order to: 1.Strengthen attachments through video connections with the tenant’s family physician 2.Provide assistance with transportation to appointments 3.Connect tenants to local family physicians accepting patients 4.Identify family physicians speaking the tenant’s language and facilitate attachment 5.Provide on-site primary care for more vulnerable tenants with complex needs. On-site primary care included monthly primary care clinics by a regular family physician and a monthly nursing clinic for blood pressure checks, foot care, assistance accessing care for all tenants. The clinics were in an equipped clinical space in the building and home visits were provided for homebound patients, including those requiring palliative care. The unattached clinic has been very well attended and highly valued by the tenants. Tenant needs that required wider interprofessional and housing team members included: 1.Medication access and compliance 2.Cognitive impairment and/or low health literacy 3.Adequate nutrition 4.Hoarding/pest infestations Barriers to providing care and achieving health outcomes included: 1.Social resources: Poor or no family connections 2.Communication: Language, access and/or ability to use phone, ability to receive messages, few use email 3.Ability to follow a simple plan – eg. Go to pharmacy, go to lab, notify team if problems 4.Ability to navigate government programs for assistance 5.Transportation and navigation to get to appointments 6.Finances Opportunities to improve access to primary care for more vulnerable tenants include: Engaging local pharmacists to call team when a tenant is not picking up their medications Engagement of tenants’ family physicians to reach out to our team for assistance connecting to their patients, supporting their care Multi sectoral interprofessional team helped to understand and address care needs holistically Working with hospitals to identify unattached TCH building patients prior to discharge and confirming attachment if family physician identified. A collaborative multi-sector integrated team (primary care, community and home care, and housing) used a range of communication strategies and co-designed the approach with tenants to provide on-site primary care to assist more vulnerable tenants at risk for hospitalization and poor health outcomes.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.851

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.265
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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