Rural Geriatric Glue: A Nurse Practitioner–Led Model of Care for Enhancing Primary Care for Frail Older Adults within an Ecosystem Approach
Bibliographic record
Abstract
OBJECTIVES: This article describes the implementation of the Care for Seniors model of care, an innovative approach to improving care coordination and integration, and provides preliminary evidence of effective use of specialist resources and acute care services. DESIGN: Retrospective. SETTING: Primary care; cross-sector. PARTICIPANTS: Older adults living in a rural area in southwestern Ontario, Canada. MEASUREMENTS: Number of new geriatrician referrals and follow-up visits before and after the launch of the Care for Seniors program, number of Nurse Practitioner visits in a primary care setting, in-home, retirement home and hospital, number of discharges home from hospital and length of hospital stay between. RESULTS: In the 2 years before the launch of the program, the total number of visits to the geriatrician for individuals from this FHT was relatively low, 21 and 15, respectively for 2005-06 and 2006-07, increasing to 73 for the 2011-12 year. Although the absolute number of individuals supported by the NP-Geri has remained relatively the same, the numbers seen in the primary care office or in the senior's clinic has declined over time, and the number of home visits has increased, as have visits in the retirement homes. The percentage of individuals discharged home increased from 19% in 2008-09 to 31% in 2009-10 and 26% in 2011-12 and the average length of stay decreased over time. CONCLUSIONS: This model of care represents a promising collaboration between primary care and specialist care for improving care to frail older adults living in rural communities, potentially improving timely access to health care and crisis intervention.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".