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Record W3008507422 · doi:10.7870/cjcmh-2019-015

Implementing a Clinical Pathway for Paediatric Mental Health Care in the Emergency Department

2019· article· en· W3008507422 on OpenAlexafffundvenueabout
Erin McCabe, Teresa Lightbody, Christine L. Mummery, Angela Coloumbe, Kathy GermAnn, Beverly Lent, Laurene Black, Kathryn E. Graham, Douglas P. Gross, Maxi Miciak

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsAlberta InnovatesAlberta Health ServicesUniversity of Alberta
FundersAlberta InnovatesAlberta Health Services
KeywordsEmergency departmentMental healthStakeholderMedicineNursingClinical pathwayMedical emergencyQuality (philosophy)Health careQuality managementService (business)BusinessPsychiatryPublic relationsPolitical science

Abstract

fetched live from OpenAlex

Practitioners in emergency departments across Canada are challenged with providing quality mental health (MH) care for children and youth despite increased demand for services. Coordinated service strategies, such as clinical pathways, are needed to effectively manage paediatric MH disorders. Practitioners in a children’s hospital emergency department implemented a pathway to improve the care of children and youth with MH conditions. This paper describes an external evaluation of practitioner and stakeholder experiences of the initiative as well as the implementation process, then explores current state and lessons learned. The paper provides a unique contribution to the practitioner-led implementation literature.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.709

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.066
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0050.003
Open science0.0020.008
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.437
GPT teacher head0.640
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2019
Admission routes4
Has abstractyes

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