Effect of case management on services use under the PRISMA coordination model: a nested matched cohort study
Bibliographic record
Abstract
INTRODUCTION: Under the PRISMA coordination model, all older people benefit from several model components, but only subjects identified with moderate to severe disabilities are eligible for case management. The PRISMA model has proven its effectiveness at the population level. However, for the sub-group with case management, what is its effect on services use? STUDY: We used data from the PRISMA study on adults aged 75 or over at risk of functional decline to compare subjects exposed to case management to unexposed ones, matched for functional disabilities, age, and gender. We studied change in annual services use, contrasting the year of assignment to the previous year. RESULTS: Among subjects in the PRISMA experimental group, 18% were assigned a case manager. Matched pairs were created for 49 cases for which data were available before and after assignment. Change in the number of annual ER visits was similar across groups, but the number of annual hospitalisations tended to increase less for exposed subjects (p=0.08). Change in annual hours for home maintenance was similar across groups, but more hours of help for personal care were added for case-managed older people (p=0.01), possibly by increasing access to home care. This strengthens the value of case management in an ISD network.
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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 | 0.018 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".