Patients Discharged Against Medical Advice from a Psychiatric Hospital in Iran: A Prospective Study
Bibliographic record
Abstract
AIM: Self- discharged patients are at high risk for readmission and ultimately higher cost for care.We intended to find the proportion of patients who leave hospital against medical advice and explore some of their characteristics. METHODS: This prospective study of discharge against medical advice was conducted in psychiatric wards of Zare hospital in Iran, 2011. A psychologist recorded some information on a checklist based on the documented information about the patient who wanted to leave against medical advice. The psychologist interviewed these patients and recorded the reasons for discharge against medical advice. Descriptive statistics were calculated for the variables. RESULTS: The rate of premature discharge was 34.4%. Compared to patients with regular discharges, patients with premature discharge were significantly more likely to be male, self-employed, to have co morbid substance abuse and first admission and positive family history of psychiatric disorder. Disappearance of symptoms was the most frequent reason for premature discharge. CONCLUSION: The 34.4% rate of premature discharge observed in our study is higher than rate reported in other studies. One possible explanation is our teaching hospital serves a low-income urban area and most patients had low socioeconomic status. Further studies are needed to compare teaching and non-teaching hospital about the rate of premature discharge and the reasons of patients who want to leave against medical advice.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".