Patient, informal caregiver and care provider acceptance of a hospital in the home program in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Hospital in the home programs have been implemented in several countries and have been shown to be safe substitutions (alternatives) to in-patient hospitalization. These programs may offer a solution to the increasing demands made on tertiary care facilities and to surge capacity. We investigated the acceptance of this type of care provision with nurse practitioners as the designated principal home care providers in a family medicine program in a large Canadian urban setting. METHODS: Patients requiring hospitalization to the family medicine service ward, for any diagnosis, who met selection criteria, were invited to enter the hospital in the home program as an alternative to admission. Participants in the hospital in the home program, their caregivers, and the physicians responsible for their care were surveyed about their perceptions of the program. Nurse practitioners, who provided care, were surveyed and interviewed. RESULTS: Ten percent (104) of admissions to the ward were screened, and 37 patients participated in 44 home hospital admissions. Twenty nine patient, 17 caregiver and 38 provider surveys were completed. Most patients (88%-100%) and caregivers (92%-100%) reported high satisfaction levels with various aspects of health service delivery. However, a significant proportion in both groups stated that they would select to be treated in-hospital should the need arise again. This was usually due to fears about the safety of the program. Physicians (98%-100%) and nurse practitioners also rated the program highly. The program had virtually no negative impact on the physician workload. However nurse practitioners felt that the program did not utilize their full expertise. CONCLUSION: Provision of hospital level care in the home is well received by patients, their caregivers and health care providers. As a new program, investment in patient education about program safety may be necessary to ensure its long term success. A small proportion of hospital admissions were screened for this program. Appropriate dissemination of program information to family physicians should help buy-in and participation. Nurse practitioners' skills may not be optimally utilized in this setting.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".