Case study of an integrated health and social care initiative for geriatric patients in rural Alberta
Bibliographic record
Abstract
Purpose Rural regions in Canada are aging faster than urban centers, but access to health and social care is limited. Integrated health and social care (IHSC) through collaboration across different health and social care organizations can support enhanced care for older adults living in rural regions. However, IHSC is not well understood within a rural Canadian context. Design/methodology/approach A case study of a Canadian IHSC initiative, Geriatric Assessment Program Collaboratory (GAPC), in northern Alberta was undertaken to understand how successful IHSC can occur in an urban/rural region. The study used key informant interviews and a focus group of representatives from the GAPC organizations. Findings Nine factors were identified that support GAPC: communications, information sharing, shared vision and goals, inter-organizational culture, diffused leadership, team-based approaches, dedicated resources, role clarity, champions and pre-existing relationships. Eight external influence factors were identified as influencing partnership including geography, strong sense of community, inter-sectoral work, public policy, governance authorities and structures, funding models, aging communities and operating within a not-for-profit (NFP) setting. Originality/value The study reveals insights into how IHSC can occur within a rural Canadian context. This study demonstrates that IHSC occurs at the local level and that primary care providers can drive IHSC successfully.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.003 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".