Outcomes After Direct Discharge Home From Critical Care Units
Bibliographic record
Abstract
OBJECTIVES: To compare health service use and clinical outcomes for patients with and without direct discharge to home (DDH) from ICUs in Ontario. DESIGN: Population-based, observational, cohort study using propensity scoring to match patients who were DDH to those not DDH and a preference-based instrumental variable (IV) analysis using ICU-level DDH rate as the IV. SETTING: ICUs in Ontario. PATIENTS: Patients discharged home from a hospitalization either directly or within 48 hours of care in an ICU between April 1, 2015, and March 31, 2017. INTERVENTION: DDH from ICU. MEASUREMENTS AND MAIN RESULTS: Among 76,737 patients in our cohort, 46,859 (61%) were DDH from the ICU. In the propensity matched cohort, the odds for our primary outcome of hospital readmission or emergency department (ED) visit within 30 days were not significantly different for patients DDH (odds ratio [OR], 1.00; 95% CI, 0.96-1.04), and there was no difference in mortality at 90 days for patients DDH (OR, 1.08; 95% CI, 0.97-1.21). The effect on hospital readmission or ED visits was similar in the subgroup of patients discharged from level 2 (OR, 0.98; 95% CI, 0.92-1.04) and level 3 ICUs (OR, 1.02; 95% CI, 0.96-1.09) and in the subgroups with cardiac conditions (OR, 1.03; 95% CI, 0.96-1.12) and noncardiac conditions (OR, 0.98; 95% CI, 0.94-1.03). Similar results were obtained in the IV analysis (coefficient for hospital readmission or ED visit within 30 d = -0.03 ± 0.03 ( se ); p = 0.3). CONCLUSIONS: There was no difference in outcomes for patients DDH compared with ward transfer prior to discharge when two approaches were used to minimize confounding within a large health systemwide observational cohort. We did not evaluate how patients are selected for DDH. Our results suggest that with careful patient selection, this practice might be feasible for routine implementation to ensure efficient and safe use of limited healthcare resources.
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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 | 0.000 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".