“It’s a waiting game” a qualitative study of the experience of carers of patients who require an alternate level of care
Bibliographic record
Abstract
BACKGROUND: Delayed hospital discharge (also known as Alternate Level of Care or ALC) is a global health care quality issue with negative implications for people (e.g., functional decline) and the health care system (e.g., costly interruptions in hospital flow and procedures). ALC disproportionately impacts people with cognitive impairment, and insight into the needs and experiences of this specific sub population and their carers is lacking. The purpose of this study was to understand the hospital experience of carers (e.g., family members) of patients with ALC and cognitive impairment who were waiting for long-term care from the hospital. METHODS: This is a qualitative descriptive study entailing 12 semi-structured interviews with 15 carers of patients with ALC from three hospitals in Northwestern Ontario. Interviews were conducted between October 2015 and February 2016. Two reviewers thematically analyzed the interview data. RESULTS: Five core themes were identified from the interview data: patient over person, uncertain and confusing process, inconsistent quality in care delivery, carers addressing gaps in the system, and personalization of long-term care. CONCLUSIONS: Waiting for long-term care from the hospital is a stressful and uncertain time for family carers. ALC is an 'in-between' phase when patients and carers may be at their most vulnerable yet receive the least care from the formal care system. Carers provide critical insight into the needs and behaviors of patients as well as processes that need to be improved to enhance their experience. Such insights will help health systems internationally as they grapple with the issue of ALC whilst trying to optimize engagement with patients and their families.
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".