The hospital-to-home care transition experience of home care clients: an exploratory study using patient journey mapping
Bibliographic record
Abstract
BACKGROUND: Care transitions have a significant impact on patient health outcomes and care experience. However, there is limited research on how clients receiving care in the home care sector experience the hospital-to-home transition. An essential strategy for improving client care and experience is through client engagement efforts. The study's aim was to provide insight into the care transition experiences and perspectives of home care clients and caregivers of those receiving home care who experienced a hospital admission and returned to home care services by thematically and illustratively mapping their collective journey. METHODS: This study applied a qualitative descriptive exploratory design using a patient journey mapping approach. Home care clients and their caregivers with a recent experience of a hospital discharge back to the community were recruited. A conventional inductive approach to analysis enabled the identification of categories and a collective patient journey map. Follow-up interviews supported the validation of the map. RESULTS: Seven participants (five clients and two caregivers) participated in 11 interviews. Participants contributed to the production of a collective journey map and the following four categories and themes: (1) Touchpoints as interactions with the health system; Life is changing; (2) Pain points as barriers in the health system: Sensing nobody is listening and Trying to find a good fit; (3) Facilitators to positive care transitions: Developing relationships and gaining some continuity and Trying to advocate, and (4) Emotional impact: Having only so much emotional capacity. CONCLUSIONS: The patient journey map enabled a collective illustration of the care transition depicted in touchpoints, pain points, enablers, and feelings experienced by home care recipients and their caregivers. Patient journey mapping offers an opportunity to acknowledge home care clients and their caregivers as critical to quality care delivery across the continuum.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".