Unmet needs for community services among the elderly : impact on health services utilization
Bibliographic record
Abstract
Seniors 75 years of age and older, the majority of whom live in the community, constitute a segment of the population that is vulnerable to loss of autonomy. Indeed many community dwelling seniors have difficulty performing daily living activities, such as bathing, toileting, walking, preparing meals and housekeeping. In the setting of a population based cohort study of community-dwelling seniors 75 years of age or older, we examined the effect of unmet needs for community services for activities of daily living (ADL) and instrumental activities of daily living (IADL) on health services utilization. Self-perceived unmet need status was determined using a baseline in-home interview. A total of 839 subjects were recruited from the Greater Montreal Region, Quebec, Canada, using random telephone number dialling. Health services utilization data were obtained from administrative databases from the Quebec Health Insurance Board (Regie de l'Assurance-Maladie du Quebec - RAMQ). Multivariable negative binomial regression models were used to examine the association between unmet need status and health services utilization during the six month period following the baseline interview. The results of this study indicate that unmet needs are associated with higher rates of emergency department visits, hospitalization and prescription drug use. No statistically significant association was found between unmet needs and physician utilization among single seniors, although married seniors with unmet needs in activities of daily living had 2.8 times the rate of medical specialist visits as compared to those who reported no unmet ADL needs. Unmet need for community services among the elderly has implications for the use of more expensive acute and long-term health care services. The results of this research suggest that developing programs to address unmet needs in the elderly population can potentially reduce health services utilization by the elderly.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".