An alternate level of care plan: Co‐designing components of an intervention with patients, caregivers and providers to address delayed hospital discharge challenges
Bibliographic record
Abstract
OBJECTIVE: To engage with patients, caregivers and care providers to co-design components of an intervention that aims to improve delayed hospital discharge experiences. DESIGN: This is a qualitative study, which entailed working groups and co-design sessions utilizing World Café and deliberative dialogue techniques to continually refine the intervention. SETTING AND PARTICIPANTS: Our team engaged with 61 participants (patients, caregivers and care providers) in urban and rural communities across Ontario, Canada. A 7-member Patient and Caregiver Advisory Council participated in all stages of the research. RESULTS: Key challenges experienced during a delayed discharge by patients, caregivers and care providers were poor communication and a lack of care services. Participants recommended a communication guide to support on-going conversation between care providers, patients and caregivers. The guide included key topics to cover and questions to ask during initial and on-going conversations to manage expectations and better understand the priorities and goals of patients and caregivers. Service recommendations included getting out of bed and dressed each day, addressing the psycho-social needs of patients through tailored activities and having a storyboard at the bedside to facilitate on-going engagement. DISCUSSION AND CONCLUSIONS: Our findings outline ways to meaningfully engage patients and caregivers during a delayed hospital discharge. Combining this with a minimal basket of services can potentially facilitate a better care experience and outcomes for patients, their care providers and 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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".