Connect 2 Care, a Novel Community Outreach Program for Vulnerably Housed Patients With High Acute Care Use: A Mixed-Methods Study Protocol
Bibliographic record
Abstract
Introduction: Vulnerably housed individuals, especially those experiencing homelessness, have higher acute care use compared with the general population. Despite available primary care and social services, many face significant challenges accessing needed services. Connect 2 Care (C2C) is a novel transitional case management program that includes registered nurses and health navigators with complementary expertise in chronic disease management, mental health and addictions, social programs, community health, and housing, financial, transportation and legal resources. C2C bridges acute care and community services to improve care coordination. Methods and Analysis: We will perform a mixed-methods evaluation of the C2C program according to the Donabedian framework of structure, process and outcome, to understand how program structure and process, coupled with contextual factors, influence outcomes in a novel intervention. Eligible patients are homeless or unstably housed adults with complex health conditions and high acute care use. Change in emergency department visit rate 12-months after program enrolment is the primary outcome. Secondary outcomes include 12-month post-enrolment hospital admissions, cumulative hospital days, health-related quality of life, housing status, primary care attachment and substance use. Qualitative methods will explore experiences with the C2C program from multiple perspectives and an economic evaluation will assess cost-effectiveness. Discussion: Academic researchers partnered with community service providers to evaluate a novel transitional case management intervention for vulnerably housed patients with high acute-care use. The study uses mixed-methods to evaluate the Connect 2 Care program according to the Donabedian framework of structure, process and outcome, including an assessment of contextual factors that influence program success. Insights gained through this comprehensive evaluation will help refine the C2C program and inform decisions about sustainability and transferability to other settings in Canada.
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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 | 0.027 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.037 | 0.005 |
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".