Determinants of hospital readmissions in older people with dementia: a narrative review
Bibliographic record
Abstract
Abstract Introduction Over 50% of hospitalised older people with dementia have multimorbidity, and are at an increased risk of hospital readmissions within 30 days of their discharge. Between 20-40% of these readmissions may be preventable. Current research focuses on the physical causes of hospital readmissions. However, older people with dementia have additional psychosocial factors that are likely to increase their risk of readmissions. This narrative review aimed to identify psychosocial determinants of hospital readmissions, within the context of known physical factors. Methods Electronic databases MEDLINE, EMBASE, CINAHL and PsychInfo were searched from inception until July 2022 and followed up in February 2024. Quantitative and qualitative studies in English including adults aged 65 years and over with dementia, their care workers and informal carers were considered if they investigated hospital readmissions. An inductive approach was adopted to map the determinants of readmissions. Identified themes were described as narrative categories. Results Seventeen studies including 7,194,878 participants met our inclusion criteria from a total of 6369 articles. Sixteen quantitative studies included observational cohort and randomised controlled trial designs, and one study was qualitative. Ten studies were based in the USA, and one study each from Taiwan, Australia, Canada, Sweden, Japan, Denmark, and The Netherlands. Large hospital and insurance records provided data on over 2 million patients in one American study. Physical determinants included reduced mobility and accumulation of long-term conditions. Psychosocial determinants included inadequate hospital discharge planning, limited interdisciplinary collaboration, socioeconomic inequalities among ethnic minorities, and behavioural and psychological symptoms. Other important psychosocial factors such as loneliness, poverty and mental well-being, were not included in the studies. Conclusion Poorly defined roles and responsibilities of health and social care professionals and poor communication during care transitions, increase the risk of readmission in older people with dementia. These identified psychosocial determinants are likely to significantly contribute to readmissions. However, future research should focus on the understanding of the interaction between a host of psychosocial and physical determinants, and multidisciplinary interventions across care settings to reduce hospital readmissions.
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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 | 0.006 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".