Trends and Regional Variation in Hospital Mortality, Length of Stay and Cost in Hospital of Ischemic Stroke Patients in Alberta Accompanying the Provincial Reorganization of Stroke Care
Bibliographic record
Abstract
Objectives This study aimed to evaluate the trends and regional variation of stroke hospital care in 30-day in-hospital mortality, hospital length of stay (LOS), and 1-year total hospitalization cost after implementation of the Alberta Provincial Stroke Strategy. Methods New ischemic stroke patients (N = 7632) admitted to Alberta acute care hospitals between 2006 and 2011 were followed for 1 year. We analyzed in-hospital mortality with logistic regression, LOS with negative binomial regression, and the hospital costs with generalized gamma model (log link). The risk-adjusted results were compared over years and between zones using observed/expected results. Results The risk-adjusted mortality rates decreased from 12.6% in 2006/2007 to 9.9% in 2010/2011. The regional variations in mortality decreased from 8.3% units in 2008/2009 to 5.6 in 2010/2011. The LOS of the first episode dropped significantly in 2010/2011 after a 4-year slight increase. The regional variation in LOS was 15.5 days in 2006/2007 and decreased to 10.9 days in 2010/2011. The 1-year hospitalization cost increased initially, and then kept on declining during the last 3 years. The South and Calgary zones had the lowest costs over the study period. However, this gap was diminishing. Conclusions After implementation of the Alberta Provincial Stroke Strategy, both mortality and hospital costs demonstrated a decreasing trend during the later years of study. The LOS increased slightly during the first 4 years but had a significant drop at the last year. In general, the regional variations in all 3 indicators had a diminishing trend.
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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 | 0.002 |
| 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".