Rate of admission and readmission to the emergency department (ED) associated with physician visits among patients with asthma
Bibliographic record
Abstract
Background: Asthma exacerbations are a common cause of emergency department (ED) admissions in Canada. In Alberta, Canada, from 2011-2015, there were on average 10,000 asthma-related ED visits annually. Objective: To better understand the patterns of physician visits, admissions and readmissions of patients with asthma to ED using a provincial health administrative database from Alberta Health Services. Methods: Patients ≥18 years of age that met the case definition of asthma and with at least one asthma-related ED visit were included (Apr 1, 2015 to Mar 31, 2020). Return to ED within 7 and 30 days of the initial admission were considered readmissions. Results: A total of 12,456 patients with a median age (IQR) of 33 (25,44) years had a total of 20,142 ED visits and a mean (SD) of 0.52 (0.83) visits/person/yr. Nearly 28% of patients experienced more than 1 asthma-related ED visit and nearly 20% returned to ED within 30 days, across all severities (Fig 1). In patients with high severity, 72% of ED visits were preceded by an asthma-specific physician visit within the prior 30 days (Fig 1). Conclusions: Nearly 20% of patients with asthma are readmitted to ED within 30 days of initial visit. A large proportion of these patients also visit their physicians in the 30 days prior to initial ED visit. These physician visits may be an opportunity for early intervention to prevent initial and repeat ED visits
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".