Factors associated with presentation to the emergency department during an intensive post-discharge intervention in patients with substance use disorders
Bibliographic record
Abstract
BACKGROUND: Early identification of patients with substance use disorders (SUDs) with a higher risk of emergency department (ED) presentations after being discharged can be useful. We performed a chart review of patients from the Intensive Recovery Discharge Team (IRDT) program, which provides two weeks of outpatient support for patients with SUDs discharged from a mental health hospital. METHOD: Demographic, service utilization, and clinical data from 716 patients enrolled in IRDT from February 2021-February 2023 were extracted from electronic health records. Receiver operating characteristic (ROC) analysis was performed to identify risk factors associated with increased ED presentations during the two weeks of IRDT follow-up with five-fold cross validation. RESULTS: In two years, 10.7% of IRDT patients presented to the ED during the 2 weeks of follow-up. Having been enrolled in IRDT more than once, not having opioid use disorder (OUD), and self-identifying as male was associated with ED presentations, where an average of 20.1% of patients with all three risk factors presented to the ED. The presence of comorbid mental disorders did not emerge as a significant predictor. DISCUSSION: Our results suggest that patients who had previous inpatient admissions, a SUD other than OUD, and/or self-identify as male have a higher risk of presenting to the ED post-discharge and may benefit from more intensive follow-up. Larger studies involving multiple sites are required to validate the generalizability of our findings. Findings from our study can be used to guide future studies examining post-discharge programs in patients with SUDs with and without comorbid mental disorders.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".