Improving transitions in care for children and youth with mental health concerns: implementation and evaluation of an emergency department mental health clinical pathway
Bibliographic record
Abstract
BACKGROUND: Emergency departments (EDs) are often the first access point for children and youth seeking mental health (MH) and addiction care. However, many EDs are unprepared to manage large volumes of pediatric MH patients. In addition, the fragmented Canadian MH system is challenged in connecting youth seen in the ED for follow-up community services. A provincial Emergency Department Mental Health Clinical Pathway (EDMHCP) for children and youth presenting to the ED with MH concerns was developed to address these challenges. The objective of the current study was to determine if EDMHCP implementation resulted in: (1) pathway use, (2) more patients discharged with MH recommendations, (3) MH service recommendations that aligned with patients' risk assessments, and (4) changes in service outcomes, including ED length of stay (LOS), revisits, and admissions/transfers. METHODS: We implemented the pathway at four ED sites from 2018 to 2019 using the Theoretical Domains Framework to develop a tailored strategy at each site. We conducted chart reviews retrospectively in 2017-2018 (pre-implementation) and prospectively in 2019-2020 (post-implementation). Non-parametric tests examined differences in service outcomes between the implementation periods. RESULTS: Pathway use varied widely across sites, ranging from 3.1% at site 4 to 83.0% at the lead site (site 2). More referrals to community MH agencies (p <.001) were made at discharge during post-implementation at the lead site compared to pre-implementation, and mixed results were obtained regarding whether clinicians' risk assessments aligned with MH service recommendations. LOS significantly increased at the lead site (p <.001) and non-lead sites (sites 1, 3, 4; p =.02) between pre- and post-implementation. Revisits and admissions/transfers did not change significantly at any site. CONCLUSION: Implementation was partially successful at the lead site, showing high pathway use and greater referrals to community MH agencies. These findings emphasize the complexity of implementing pathways in various ED settings. Successful implementation requires integration into existing workflows. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02590302). Registered on 29 October 2015.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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 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".