The association of asthma education centre characteristics on hospitalizations and emergency department visits in Ontario: a population-based study
Bibliographic record
Abstract
BACKGROUND: International guidelines recommend patient education as an essential component of optimal asthma management. Since 1990 hospital-based asthma education centres (AECs) have been established in Ontario, Canada. It is unknown whether patient outcomes are related to the level of services provided. METHODS: Using linked, population-based health administrative and hospital survey data we analyzed a population of patients aged 2 to 55 years with a hospitalization for asthma (N = 12 029) or a high acuity asthma emergency department (ED) visit (N = 63 025) between April 2004 and March 2007 and followed for three years. Administrative data documenting individuals' attendance at AECs were not available. Poisson models were used to test the association of potential access to various AEC service models (outpatient service availability and in-hospital services) with asthma readmissions, ED visits or death within 6 to 36 months following the index admission or ED visit. RESULTS: Fifty three of 163 acute care hospitals had an AEC (N = 36) or had access by referral (N = 17). All AECs documented use with guideline-based recommendations for AE programs. ED patients having access to an AEC that offered full-time, extended hours had reduced rates of adverse outcomes (adjusted relative rate [aRR] 0.78, 95% confidence interval [CI] 0.69, 0.90) compared to those with no AEC access. Hospitalized patients with access to asthma education during hospitalization had reduced rates of adverse events (aRR 0.87, 95% CI 0.75, 1.00) compared to those with no inhospital AEC access. CONCLUSION: Although compliant with asthma guideline-based program elements, on a population basis access to asthma education centres is associated only with a modest benefit for some admitted and ED patients and depends on the level of access to services provided. Review of both services provided and strategies to address potential barriers to care are necessary.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".