Innovations in Seniors' Care: Home Care/Physician Partnership
Bibliographic record
Abstract
The Innovations in Seniors' Care (Primary Care Partnerships) Project was implemented in 2000 in the Calgary Health Region, Alberta, to look at integration of services for seniors. The goal was to develop a sustainable collaborative partnership between family physicians and Community Care Coordinators--RNs (Home Care). The design and model were established in Stage I of the project. Stage II addressed implementation, challenges, barriers, evaluation, learnings and successes to date. Stage III looked at refinement, revision, final evaluation of the processes and dissemination of learnings. This paper describes startup procedures and implementation (selection of participants, educational sessions, evolution of partnerships and development of the evaluation framework). As the focus of the project was quality improvement, the section on implementation will discuss how and why changes occurred in the course of the process. Key challenges related to the restructuring of Home Care, creating tools and fostering unique individualized partnerships are also discussed. The conclusion evaluates the project's benefits in relation to (1) participant satisfaction, (2) sustainability and (3) impact on the system. The initial partnerships were formed in May 2001. New partnerships continue to be developed and constitute a key strategy in the Calgary Health Region's Primary Care Initiative.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".