Transition from Hospital to Home-Based Care for Older Adults in Southwestern Uganda: Informal Caregiver’s Experiences
Bibliographic record
Abstract
Background: The transition from hospital-based to home-based care is a complex and challenging process. In most developing countries, patients transfer directly from hospital to home immediately after stabilizing from acute illness. After discharge, all the patient's care needs are taken over by informal caregivers whose experiences and practices may directly or indirectly impact the quality of patient care as well as the outcomes. This study aimed at exploring the experiences of informal caregivers during the hospital to home transition process of older adults. Methods: We conducted a qualitative exploratory study that used one-on-one interviews to describe individual experiences of care givers of older adults admitted in a clinical care setting. We interviewed caregivers of older adults with diabetes and of hypertension who were admitted at the inpatient department of internal medicine at Mbarara regional referral hospital (MRRH). All audio recorded interviews were transcribed verbatim by the research assistant in the local dialect and back translated into English the official language spoken in Uganda. The study utilized content analysis approach to analyze 23 interviews conducted. Results: Of the 23 participants interviewed, majority were aged between 20 and 40 years and females. Three major themes emerged from the data: informal caregivers' experience during hospitalization, experience during preparation for discharge and experience after discharge. Conclusion: Caregiver experience during hospitalization influences their involvement and compliance with the discharge process which in turn affects their ability to deliver quality post discharge care to the patient. Healthcare systems need to put targeted effort and resources in the discharge process and home follow-up visits to improve home-based care by caregivers. Community-based geriatric care centers can bridge the care gap during transition from hospital to home-based 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".