Economic evaluation of a geriatric day hospital: cost-benefit analysis based on functional autonomy changes
Bibliographic record
Abstract
OBJECTIVE: to investigate whether the benefits related to a geriatric day hospital programme exceeded the costs, using a cost-benefit analysis based on changes in functional autonomy. DESIGN: a quasi-experimental design with a historical cohort as comparison group. SETTING: the geriatric day hospital programme at the Sherbrooke Geriatric University Institute in the Province of Quebec, Canada. SUBJECTS: 151 geriatric day hospital patients. METHODS: after admission to and at discharge from the geriatric day hospital programme, functional autonomy was assessed by a trained nurse using the Functional Autonomy Measurement System. Based on financial reports, costs associated with resources consumed at the geriatric day hospital programme by each subject were established. The benefit in dollars per day was estimated with a societal perspective through regression equations based on functional autonomy changes related to the geriatric day hospital programme. A model for spreading the benefit per day was proposed: the median time to institutionalisation or death. RESULTS: for every dollar invested in the geriatric day hospital programme, the benefit for the health system was $2.14 (95% confidence interval: $1.72-$2.56). CONCLUSION: based on our sample of Sherbrooke Geriatric University Institute patients, the benefit related to the geriatric day hospital programme seems to exceed the costs.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".