Utilization of the emergency department after self‐inflicted injury
Bibliographic record
Abstract
OBJECTIVES: To compare emergency department (ED) utilization by individuals who present with self-inflicted injuries with utilization by control populations. Individuals with self-inflicted injuries commonly present to the ED, yet little research has been conducted on this population in this setting. METHODS: Individuals who had an ED presentation in 1995-1996 for a self-inflicted injury were tracked prospectively for three to four years of follow-up. This group was matched by age and gender to two groups: individuals who presented with asthma and individuals who presented with other complaints. Data on return visits to the ED were collected from an administrative database. Groups were compared on rates of return visits. RESULTS: There were 478 individuals randomly selected for each group. Individuals in the self-inflicted injury group had higher rates of return visits to the ED over the follow-up period: 232.7 visits per 100 person-years for the self-inflicted injury group, compared with 117.6 for the asthma group, and 83.0 for the "other" group (p < 0.001). The self-inflicted injury group had higher rates for many types of diagnoses: self-inflicted injuries, mental disorders, substance abuse, unintentional injuries, assault, headache pain, and other complaints (all p < 0.001). Patients with more than three repeat visits per year were more common in the self-inflicted injury group (20.1%) than the asthma or "other" groups (9.2% and 5.6%, respectively). CONCLUSIONS: Individuals who harm themselves are chronic users of the ED. The ED represents an opportune setting from which individuals can be directed to appropriate treatment programs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".