Engaging patients and informal caregivers to improve safety and facilitate person- and family-centered care during transitions from hospital to home – a qualitative descriptive study
Bibliographic record
Abstract
Chantal Backman,1–3 Danielle Cho-Young11School of Nursing, Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada; 2Ottawa Hospital Research Institute, Ottawa, ON, Canada; 3Bruyère Research Institute, Ottawa, ON, CanadaPurpose: The purpose was to describe patients and informal caregivers’ perspectives on how to improve and monitor care during transitions from hospital to home as part of a larger research study to prioritize the components that most influence the development of successful care transition interventions.Methods: We conducted a qualitative descriptive study between July and August 2016, during which time semi-structured telephone interviews (n=8) were completed with patients and informal caregivers across select Canadian provinces. Interviews were audio-recorded, transcribed and thematically analyzed.Results: Main themes included: the need for effective communication between providers and patients and informal caregivers; the need for improving key aspects of the discharge process; and increasing patients and informal caregivers involvement in care practices. Participants also provided suggestions on how to best monitor care transitions.Conclusion: This study highlighted the following strategies with patients and informal caregivers: focus on effective communication regarding important information; provide appropriate resources; and increase involvement. Future research is needed to incorporate the input from patients and informal caregivers into the design and implementation of care transition interventions.Keywords: care transitions, patient engagement, patient safety, person- and family-centered care
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".