Hospital readmissions and mortality following discharge against medical advice: a five-year retrospective, population-based cohort study in Veneto region, Northeast Italy
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to examine the odds of readmission and mortality after discharge against medical advice (DAMA) in the Veneto region of Northeast Italy, drawing on data from the regional archives of emergency department records and hospital discharge records. DESIGN: A retrospective cohort study. SETTING: Hospital discharges, Veneto region, Italy. PARTICIPANTS: All patients discharged after being admitted to a public or accredited private hospital between January 2016 and 31 January 2021 in the Veneto region were considered. A total of 3 574 124 index discharges were examined for inclusion in the analysis. PRIMARY AND SECONDARY OUTCOME MEASURES: Readmission and overall mortality at 30 days after the index discharge against admission. RESULTS: In our cohort, 7.6‰ of patients left hospital against their doctor's advice (n=19 272). These DAMA patients were more likely to be younger (mean age: 45.5 vs 55.0), foreign (22.1% vs 9.1%). The adjusted odds of readmission after DAMA was 2.76 (CI 95% 2.62-2.90) at 30 days (9.5% DAMA vs 4.6% not-DAMA), and the highest readmission rate was recorded in the first 24 hours after the index discharge. Mortality was higher for DAMA patients after adjusting for patient-level and hospital-level characteristics (with adjusted ORs of 1.40 for in-hospital mortality and 1.48 for overall mortality). CONCLUSIONS: The present study shows that DAMA patients are more likely to die and to need hospital readmission than patients discharged by their doctors. DAMA patients should be more committed to a proactive and diligent postdischarge care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".