Outcomes after Rehospitalization at the Same Hospital or a Different Hospital Following Critical Illness
Bibliographic record
Abstract
RATIONALE: Intensive care unit (ICU) patients who receive mechanical ventilation are at high risk for early rehospitalization. Given the medical complexity of these patients, a lack of continuity of care may adversely affect their outcomes during rehospitalization. OBJECTIVES: To determine whether outcomes differ for patients who are rehospitalized at a different hospital versus the hospital of their index ICU stay. METHODS: We conducted a retrospective cohort study of mechanically ventilated ICU patients rehospitalized within 30 days in New York State hospitals between 2008 and 2013. MEASUREMENTS AND MAIN RESULTS: We measured frequency of rehospitalization at a different hospital, mortality, length of stay, and costs during rehospitalization. Of 26,947 mechanically ventilated ICU patients rehospitalized within 30 days of discharge, 8,443 (31.3%) were rehospitalized at a different hospital than that of the index ICU stay. For patients at a different hospital, 13.7% died during rehospitalization versus 11.1% who died at the index hospital (adjusted rate ratio [aRR], 1.11; 95% confidence interval [CI], 1.03-1.20; P = 0.009). Patients who died at a different hospital had shorter length of stay (aRR, 0.80; 95% CI, 0.70-0.92; P = 0.001) and decreased costs (adjusted mean difference, -$9,632.73; 95% CI, -$16,387.60 to -$2,877.88; P = 0.005), whereas survivors of rehospitalization at a different hospital had a modest increase in length of stay (aRR, 1.06; 95% CI, 1.01-1.11; P = 0.009) and increased costs of care (adjusted mean difference, $1,665.34; 95% CI, $602.12-$2,728.56; P = 0.002). CONCLUSIONS: Almost one-third of mechanically ventilated critically ill patients were rehospitalized at a different hospital than that of the index ICU stay. This care discontinuity was associated with increased mortality.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".