Hospitalization for ambulatory care sensitive conditions among urban Métis adults.
Bibliographic record
Abstract
BACKGROUND: Hospitalizations for ambulatory care sensitive conditions (ACSCs) are potentially preventable, but may be required if these conditions are not managed well. National-level information about ACSC hospitalizations is available for Canada, but not for Aboriginal groups. This study describes ACSC hospitalizations among urban Métis adults relative to their non-Aboriginal counterparts. DATA AND METHODS: The 2006/2007-to-2008/2009 Discharge Abstract Database, which contains hospitalization records from all acute care facilities (excluding Quebec), was linked to the 2006 Census to obtain Aboriginal identity information. Age-standardized ACSC hospitalization rates (ASHRs) per 100,000 population and rate ratios were calculated for Métis aged 18 to 74 relative to non-Aboriginal people of the same ages. Odds of ACSC hospitalizations were estimated using logistic regression models, adjusting for demographic, geographic, and socioeconomic characteristics. RESULTS: The ASHR for ACSCs among urban Métis adults was twice that among non-Aboriginal adults (393 versus 184 per 100,000 population). Even when demographic, geographic, and socioeconomic characteristics were taken into account, Métis had higher odds of ACSC hospitalizations overall (OR 1.5). Most commonly, these hospitalizations were for diabetes (OR 1.8) or chronic obstructive pulmonary disease (OR 1.5). Modelled factors partly reduced differences between Métis and non-Aboriginal adults, but variations between the groups remained after all adjustments. INTERPRETATION: Rates of ACSC hospitalizations were higher among Métis than among non-Aboriginal adults who lived in urban areas. Further research using other data sources is warranted to assess the roles of factors not available for this analysis, such as primary care, co-morbidity, and health behaviours.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".