Association of Neighborhood-Level Material Deprivation With Health Care Costs and Outcome After Stroke
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: To determine the association between material deprivation and direct health care costs and clinical outcomes following stroke in the context of a publicly funded universal health care system. METHODS: In this population-based cohort study of patients with ischemic and hemorrhagic stroke admitted to the hospital between 2008 and 2017 in Ontario, Canada, we used linked administrative data to identify the cohort, predictor variables, and outcomes. The exposure was a 5-level neighborhood material deprivation index. The primary outcome was direct health care costs incurred by the public payer in the first year. Secondary outcomes were death and admission to long-term care. RESULTS: Among 90,289 patients with stroke, the mean (SD) per-person costs increased with increasing material deprivation, from $50,602 ($55,582) in the least deprived quintile to $56,292 ($59,721) in the most deprived quintile (unadjusted relative cost ratio and 95% confidence interval 1.11 [1.08, 1.13] and adjusted relative cost ratio 1.07 [1.05, 1.10] for least compared to most deprived quintile). People in the most deprived quintile had higher mortality within 1 year compared to the least deprived quintile (adjusted hazard ratio [HR] 1.07 [1.03, 1.12]) as well as within 3 years (adjusted HR 1.09 [1.05, 1.13]). Admission to long-term care increased incrementally with material deprivation and those in the most deprived quintile had an adjusted HR of 1.33 (1.24, 1.43) compared to those in the least deprived quintile. DISCUSSION: Material deprivation is a risk factor for increased costs and poor outcomes after stroke. Interventions targeting health inequities due to social determinants of health are needed. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that the neighborhood-level material deprivation predicts direct health care costs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".