Patients’ and family caregivers’ experiences with a newly implemented hospital at home program in British Columbia, Canada: Preliminary results
Bibliographic record
Abstract
The Hospital at Home (HaH) model of care, which enables the provision of acute-level care in the patient’s own home as an alternative to brick and mortar hospital admission, was introduced in British Columbia, Canada in November 2020, starting with 9 inpatient “beds” in the community. The AT-HOME research group applied a patient-oriented approach to evaluate the patients’ and family caregivers’ (FCGs) experiences with the program as it was implemented and expanded throughout Victoria, BC. In this paper, we discuss the development of the survey instruments, including process and timelines (three phases); and present preliminary findings of the observational research study (six months of patient and FCG feedback data). The preliminary results show that 100% of patients (n=75) and 95% of FCGs (n=57) had an overall positive experience with the program (rated 6-10 on a 10-point scale where 0 meant ‘very poor’ and 10 ‘very good’). 100% of these patients and 96% of these FCGs would recommend the program to their friends and family and 97% of these patients and 96% of these FCGs would choose the program again if faced with the same situation. The preliminary results on metrics pertaining to care quality; information sharing and experiences with the admission and discharge processes; FCG’s roles, medication management, and more are discussed here. The final results of the patient and FCG experiences will be reported at the end of the data collection period. We can conclude that this new HaH program has been positively received by patients and FCGs thus far and they support program expansion Experience Framework This article is associated with the Innovation & Technology lens of The Beryl Institute Experience Framework (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".