Another way to look at high service utilization: the contribution of disability
Bibliographic record
Abstract
OBJECTIVES: High users of health services are usually identified in terms of their health complications stemming from the coincidence of a number of chronic conditions. Instead, this analysis attempts to characterize high users in terms of disability, based on the belief that disability provides a more detailed and accurate representation of functional needs and health consequences. The study compares the characteristics of high users of health services among Canadian adults (aged 20-65) with those of low to moderate users and non-users. METHODS: Secondary analysis of data collected for the National Population Health Survey, a cross-sectional public-use population-based national survey, conducted in 1998-99. RESULTS: No matter how disability is conceptualized and measured, it has the strongest association of all the variables considered with health service utilization. Whether looking at the simple presence of a disability or at specific impairments or activity restrictions, there is at least a two-fold increase in the risk of high use over the non-disabled. CONCLUSIONS: The present study challenges the clinical wisdom that high users should be the target for efforts to reduce the overall consumption of health services. Many high users consume on the basis, not of choice, but of need rooted in disability. Moreover, when compared with low or moderate service users, their clinical condition is exacerbated by social factors, including lower income, less education and less immediate family support. Equity cannot be achieved by focusing on reducing consumption by this clinically and socially vulnerable group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".