Day of discharge and hospital readmission rates within 30 days in children: A population-based study
Bibliographic record
Abstract
BACKGROUND: Adults discharged from hospital on a Friday are more likely to be readmitted within 30 days than are adults discharged midweek. No study has examined readmission rates for children by day of discharge. OBJECTIVE: To determine the risk of readmission within 30 days by day of discharge in the paediatric population. METHODS: The Canadian Institute for Health Information provided data on children 29 days to 18 years of age who were discharged from hospitals in Ontario between January 1996 and December 2000. Two groups of children (those who were readmitted within 30 days and those who were not) were compared on demographic and clinical characteristics. Multivariable modelling was used to account for potential confounding variables: age, sex, length of hospital stay, number of diagnoses, in-hospital operative procedure, in-hospital complication and hospital admission in the previous six months. RESULTS: A total of 506,035 hospitalizations (involving 334,959 children) occurred over the study period. Of these children, 3.4% were readmitted within 30 days of discharge. In total, 3.6% of children discharged on a Friday were readmitted within 30 days compared with 3.3% of children discharged on a Wednesday. After adjusting for patient and hospital factors, Friday discharge was not associated with readmission within 30 days (adjusted RR 1.07, 95% CI 0.99 to 1.15). More significant predictors of readmission included number of diagnoses, in-hospital complications and hospital admission in the six months previous to the index admission date. CONCLUSION: Risk of readmission within 30 days is not significantly increased for children discharged on a Friday compared with children discharged midweek. Significant risk factors for hospital readmission are patient complexity and disease severity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".