Changes in Heart Failure Outcomes After a Province-Wide Change in Health Service Provision A Natural Experiment in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: The Alberta Cardiac Access (ACA) initiative was implemented in the spring of 2008 to increase access to specialized heart failure (HF) clinics after hospital discharge. METHODS AND RESULTS: We identified all adults hospitalized with a most responsible diagnosis of HF between April 1999 and December 2009. We randomly selected 1 episode of care per patient and evaluated outcomes using interrupted time series: the a priori specified primary outcome was all-cause readmission or death in the first 30 days postdischarge. Between 1999 and 2009, median length of stay increased from 8 days to 10 days (P<0.001), and 30-day mortality increased from 9.1% to 11.5% (P<0.001) in the 37891 HF hospitalizations we examined. However, these temporal changes were attributable to the increasing comorbidity burden over time: the adjusted Risk Ratio for 30-day mortality in 2009 versus 1999 was 0.99, 95% confidence interval, 0.86 to 1.15. After adjusting for secular trends, the ACA initiative was associated with changes in 30-day postdischarge mortality or readmission rates (which were increasing 0.3% per month [0.2%-0.3%] pre-ACA and decreased 1.4% per month [0.3%-2.5%] in the 18 months post-ACA; P=0.008). After roll out of the ACA initiative, patients discharged from vanguard regions (those that had specialized HF clinics) exhibited lower 30-day postdischarge death/readmission rates than those discharged from other areas of the province (18.6% versus 22.2%, adjusted odds ratio 0.83, 95% confidence interval, 0.75-0.93). CONCLUSIONS: An initiative which increased specialized HF clinic access was associated with a statistically significant improvement in 30-day postdischarge mortality/readmission rates.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".