Home Healthcare Services and Interventions for Older Adults: An Umbrella Review of Systematic Reviews and Meta-Analyses
Bibliographic record
Abstract
As global populations age, there is increasing demand for effective, person-centered healthcare solutions that support older adults to age in place. Home healthcare has emerged as a crucial strategy to address the complex health and social needs of older adults while reducing reliance on institutional care. This umbrella review aimed to synthesize evidence from existing systematic reviews and meta-analyses on home healthcare services and interventions targeting older adults. A comprehensive search was conducted across five databases and gray literature sources, including Google Scholar, for reviews published between 2000 and 2025. The review followed the Joanna Briggs Institute methodology and PRISMA statement. Twenty reviews met the inclusion criteria, encompassing a total of over 3.1 million participants. Interventions were grouped into four categories: integrated and multidisciplinary care, preventive and supportive home visits, technological and digital interventions, and physical, transitional, and environmental support. Results indicated that many interventions led to improved health outcomes, including enhanced functional ability, reduced hospital readmissions, and increased satisfaction. However, effectiveness varies depending on the intervention type, delivery model, and population. Challenges such as caregiver burden, digital exclusion, and implementation in diverse settings were noted. This review highlights the promise of home healthcare interventions and underscores the need for context-sensitive, equitable, and scalable models to support aging populations.
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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 | 0.034 | 0.109 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.027 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".