Integrating Community Services into Primary Care: Improving the Quality of Dementia Care
Bibliographic record
Abstract
AIM: The purpose of this study was to describe the impact associated with a unique partnership between the Alzheimer's Society (AS) and primary care-based memory clinics, and in particular to describe the impact on access to community-based services, the role of the AS in these clinics and to identify key lessons learned in partnership formation. PARTICIPANTS & METHODS: A total of 35 memory clinic healthcare providers and nine AS representatives completed a survey assessing the impacts of this partnership, and 25 memory clinic members and 11 AS representatives were interviewed regarding the implementation and outcomes of this partnership. The number of referrals to the AS from the participating primary care settings in the 6 months prior to and following the formation of this partnership were collected. RESULTS: There was a fivefold increase in referrals to the AS in the 6 months following the launch of this partnership. Other identified impacts included improved care integration and coordination across community and primary care sectors, improved access to information and community supports at the time of diagnosis, and increased healthcare provider awareness of available community services. AS representatives assumed various roles in the clinic depending on available resources and existing gaps. Some key lessons were learnt in order to support the implementation of this partnership in other jurisdictions. CONCLUSION: This partnership was perceived as a significant quality improvement opportunity to better meet the needs of individuals with dementia and their caregivers, and highlights the importance of the integration of community agencies in primary care to improve access to community services.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".