Hospital to Home: Supporting the Transition from Hospital to Home for Older Adults
Bibliographic record
Abstract
Abstract Background: An increasing proportion of older adults experience avoidable hospitalizations, and some are potentially entering long-term care homes earlier and often unnecessarily. Within Canada, approximately 10 percent of newly admitted long-term care residents could have potentially been cared for at home. Without adequate support from health care services to transition older adults from hospital to home, they often lack access to appropriate services when they are needed in the community thus making them more vulnerable to avoidable hospital visits, rapid deterioration of health, and earlier and unnecessary placement into residential long-term care. The purpose of this study was to collaborate with an existing enhanced home care program called Home Again in Halifax, Nova Scotia, to identify factors that contribute to older adult patients being assessed as requiring long-term care when they could potentially return home with enhanced supports. Methods: Through a retrospective case study design, we analyzed nine interviews for three focal patient cases including older adult patients, their family or friend caregivers, and healthcare professionals. Results: Findings indicate home care services for older adults are being sought too late, after hospital re-admission, or a rapid decline in health status when family caregivers are already experiencing caregiver burnout. Limitations in home care services ultimately led to barriers preventing family caregivers from continuing to care for older adults at home, such as absence of overnight services, a lack of information about home care services, and a lack of knowledge to navigate resources available. Conclusion: This study contributes knowledge about gaps within home care and transitional care services, highlighting the significance of investing in additional home care services for rehabilitation and the prevention of rapidly deteriorating health when older adults are discharged home after their first hospital visit. By understanding experiences and challenges of patients, family or friend caregivers, and healthcare professionals, we identified ways to reduce healthcare costs and improve the delivery and quality of home care services to better support older adult patients and their family or friend caregivers and to ensure hospitalized older adults are not unnecessarily admitted to nursing homes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".