Frequent Attendance to the Emergency Department after Release from Prison: a Prospective Data Linkage Study
Bibliographic record
Abstract
The aim of this paper was to identify characteristics and predictors of frequent emergency department (ED) use among people released from prisons in Queensland, Australia. Baseline interview data from a sample of sentenced adults were linked to ED and hospital records. The association between baseline characteristics and frequent ED attendance was modelled by fitting multivariate logistic regression models. Participants who had ≥ 4 visits to the ED in any 365-day period of community follow-up were defined as frequent attenders (FA). The analyses included 1307 people and mean follow-up time in the community was 1063 days. After adjusting for covariates, those with a dual diagnoses of mental illness and substance use (RR = 2.42, 95% CI 1.47-3.99) and those with mental illness alone (RR = 2.47, 95% CI 1.29-4.73) were at higher risk of frequent ED attendance, compared with those with no disorder. Future research should assess whether individually tailored transition supports from prison to community reduce the frequency of ED use among this population.
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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 | 0.004 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".