Parental Language and Return Visits to the Emergency Department After Discharge
Bibliographic record
Abstract
OBJECTIVE: Return visits to the emergency department (ED) are used as a marker of quality of care. Limited English proficiency, along with other demographic and disease-specific factors, has been associated with increased risk of return visit, but the relationship between language, short-term return visits, and overall ED use has not been well characterized. METHODS: This is a planned secondary analysis of a prospective cohort examining the ED discharge process for English- or Spanish-speaking parents of children aged 2 months to 2 years with fever and/or respiratory illness. At 1 year after the index visit, a standardized chart review was performed. The primary outcome was the number of ED visits within 72 hours of the index visit. Multivariable logistic regression was used to examine the relative importance of predictor variables and adjust for confounders. RESULTS: There were 202 parents eligible for inclusion, of whom 23% were Spanish speaking. In addition, 6.9% of the sample had a return visit within 72 hours. After adjustment for confounders, Spanish language was associated with return visit within 72 hours (odds ratio, 3.49; 95% confidence interval, 1.02-11.90) but decreased risk of a second visit within the year (odds ratio, 0.28; 95% confidence interval, 0.12-0.66). CONCLUSION: Spanish-speaking parents are at an increased risk of 72-hour return ED visit but do not seem to be at increased risk of ED use during the year after their ED visit.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".