Factors associated with hospitalisations for ambulatory care‐sensitive conditions among persons with an intellectual disability – a publicly insured population perspective
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Hospitalisations for ambulatory care-sensitive (ACS) conditions are used as an indicator of access to, and the quality of, primary care. The objective was to identify factors associated with hospitalisations for ACS conditions among adults with an intellectual disability (ID) in the context of a publicly insured healthcare system. METHODS: This study examined adults with an ID living in a Canadian province between 1999 and 2003 identified from administrative databases. Using 5 years of data for the study population, characteristics of persons hospitalised or not hospitalised for ACS conditions were compared. Using a conceptual model, independent variables were selected and an analysis performed to identify which were associated with hospitalisations for ACS conditions. The correlated nature of the observations was accounted for statistically. RESULTS: Living in a rural area [odds ratio (OR) 1.3; 95% confidence intervals (CI) = 1.0, 1.8], living in an area with a high proportion of First Nations people (OR 2.3; 95% CI = 1.3, 4.1), and experiencing higher levels of comorbidity (OR 25.2; 95% CI = 11.9, 53.0) were all associated with a higher likelihood of being hospitalised for an ACS condition. Residing in higher income areas had a protective effect (OR 0.56; 95% CI = 0.37, 0.85). None of the health service resource variables showed statistically significant associations. CONCLUSIONS: Persons with an ID experience inequity in hospitalisations for ACS conditions according to rurality, income and proportion who are First Nations in a geographic area. This suggests that addressing the socio-economic problems of poorer areas and specifically areas densely populated by First Nations people may have an impact on the number of hospitalisations for ACS conditions. Study strengths and limitations and areas for potential future research are discussed.
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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 | 0.005 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it