Physician Management of Pediatric Mental Health Patients in the Emergency Department
Bibliographic record
Abstract
OBJECTIVE: The focus of this study was to describe the clinical data that pediatric emergentologists recorded and how they were used in the mental health (MH) care of patients. METHODS: A structured chart review was conducted for all MH presentations to a pediatric emergency department in 2007. Three research assistants extracted clinical chart data and completed the Child and Adolescent Needs and Strengths Tool. RESULTS: The clinical records of 495 children and youth were reviewed. Emergentologists referred 124 (25.4%) for a psychiatric consult, and 46 (37%) of these patients were admitted to either an inpatient psychiatric or eating-disorders unit. Psychosis, suicide risk, eating disturbance, anxiety, and resistance to treatment predicted admission to the psychiatric inpatient unit or the eating-disorders unit. Of the 365 patients discharged back to the community, the majority (n = 189, 51.8%) were referred back to their family physician. For 117 patients (32%), there was no discharge documentation in the medical chart. Age, parent present, currently on medication, currently receiving counseling, depression, anxiety, and adjustment to trauma predicted provision of charted recommendation. CONCLUSIONS: This study revealed that the pediatric emergentologists' charting of MH patients is inconsistent and incomplete. Although recorded clinical data predicted psychiatric consultation and disposition for these patients, missing data were evident in a significant number of records. The results of the study point to a need to develop a more uniform approach to the collection and recording of clinical data for MH patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".