The Clinical Advantages of Making Our Hospitals Older Adult Friendly
Bibliographic record
Abstract
Older adults (≥ 65 years), now constitute half of the hospital inpatient population. Catering for the needs of this group requires consideration of the processes of care, the inpatient environment, and care practices operating in our hospitals. Older adults are often multimorbid, more likely than older adults in the community to be malnourished and have coexistent physical and cognitive impairments. These older adults are at great risk of suffering hospital-associated harms or being designated as "bed blockers," partly owing to inadequate understanding of their needs, a failure of recognition, or an unwillingness to address them. The adoption of older adult-friendly care presents considerable opportunity to transform the manner in which care is delivered in order to mitigate avoidable harms and optimise outcomes for older adults. This review explores the nature of our older adult inpatients, the implications of older adult-friendly care, the requirement for true interprofessional care, and the advantages of systematic assessment spanning pre-hospital to post-hospital care, and highlights specific interventions to deal with in-hospital problems that differently impair health-related outcomes for older adults. As such, it hopes to raise awareness of the needs of older adults under cardiologic care to improve outcomes for hospitalised older adults.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".