Rate of admission and readmission to the ED among patients with severe asthma
Bibliographic record
Abstract
Background: One third of asthma-related emergency department (ED) admissions in Canada result in readmissions within 90 days. However, the clinical and economic burden associated with readmissions remains unclear, especially among those with more severe asthma. This study characterized the health care resource use (HCRU) associated with readmissions among patients with GINA 4/5 severity. Methods: Adults with ≥1 asthma-related ED admission (baseline asthma severity of GINA steps 4/5) were identified from the Alberta provincial health administrative database (2015-2020). Rate of ED readmissions, hospital admission, mortality, specialist follow-up, and total costs were assessed within 90 days of the initial admission. Results were presented for all ED events and stratified by readmission status. Results: A total of 11,208 asthma ED admissions from 7,168 patients (mean[SD] age of 36.3[13.7] years; 61% female) were identified. In the 90-day post ED period, 39% were readmitted to the ED; 5% were hospitalized. While 30% had any outpatient follow-up, only 11% were with respiratory-related specialists; 3.5%, specifically for asthma. With an ED readmission, mean (SD) total costs estimated in the 90-day period were significantly higher ($3,376 [$8,669]) than without readmission ($326 [$1,580]); rates of hospitalization and mortality were also higher (12.8% vs. 1.1%; 0.3% vs 0.1%). Conclusions: The study findings suggest that readmissions among those with more severe asthma were frequent and associated with higher HCRU and costs, and worse clinical outcomes, while specialist follow-up was rare. Timely and appropriate follow-up post ED admission is a potential opportunity to reduce further readmissions and HCRU.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".