Analysis of Extreme Length of Stay Hospitalizations for Children and Youth in a Quaternary Care Hospital
Bibliographic record
Abstract
Length of stay (LOS) is an important issue for many healthcare organizations. In-patients with extreme LOS account for a disproportionately large percentage of hospital costs. Our analysis of over 15,000 pediatric hospital discharges at The Hospital for Sick Children (Toronto, Canada) between 2015 and 2016 revealed that the vast majority of patients with extreme LOS were discharged directly home, with only a minority receiving home-based services. Patients with the greatest LOS were accounted for by primarily four subspecialty services. Although this report outlines an analysis of pediatric in-patients, our findings and implications are relevant for all jurisdictions and populations as many acute care hospitals often "hold" patients with complex, chronic illness as in-patients for extended periods because alternate appropriate services may not exist or be available. Our case study highlights three key areas to improve quality of care for patients with extreme LOS: alternate levels of care, system resources and transitions to home.
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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 | 0.003 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".