Home & Away: Demographics And “Time Spent At Home” Of Those Attending Community Specialist Teams For Older Adults, A Pilot Study
Bibliographic record
Abstract
Abstract Background Older people value time spent at home. The Integrated Care Programme for Older People (ICPOP) model provides specialist multidisciplinary interventions to maintain independence at home (Harnett et al., 2023). Understanding the demographics of this population and their outcomes is key to improved service planning and delivery. Decreased Time Spent at Home (TSAH) associated with Unscheduled Events (UEs) is associated with worse patient-centered outcomes (Lee et al., 2019) however it is not routinely measured in ICPOP populations. Methods Retrospective pilot cohort study of the population undergoing IPCOP Comprehensive Geriatric Assessment (CGA) between January 2023 and January 2024 and outcomes collected up to May 2025. Data was collected from online hospital databases and included: demographics, level of frailty, dependence, cognition and polypharmacy. The primary outcome of interest was the number of UEs including Emergency Department attendances, Pathfinder reviews, hospital/nursing home admission and death, as well as the average TSAH prior to first unscheduled event post-CGA. Results 100 older people were included. Mean age was 82.94 (+/-6.48) years, 53% (n=53) were female and 44% (n=44) lived alone. The majority were referred from primary care (84%). Median clinical frailty score was 4. Polypharmacy was common (79% taking ≥5 and 33% taking ≥ 10 medications). Median Barthel and Lawton Brody scores 19 and 4.5 respectively. 68% (n=68) had evidence of cognitive impairment (median Montreal Cognitive Assessment Score 17). 81% (n=81) had a UE. Of these19% (n=19) were admitted to a nursing home, 21% (n=21) died. Median TSAH was 320 days from CGA to first UE. Conclusion ICPOP CGA resulted in almost a year spent at home on average before a first UE, underlying the importance of CGA in preventing admissions in a frail population. Further evaluation is required to determine actual cost savings to the health service and the value older people place on this intervention.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".