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Record W4391090897 · doi:10.7870/cjcmh-2023-027

Closing the Referral Loop: Piloting a Clinical Pathway Between Primary Care and Community-Based Mental Health and Addictions Services

2023· article· en· W4391090897 on OpenAlexaffvenueabout
Christine Polihronis, Laura Ziebell, Paula Cloutier, Ashley D Radomski, Purnima Sundar, S Leith, J. Ryan Stewart, Mario Cappelli

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsUniversity of OttawaCarleton UniversityEssar Steel Algoma (Canada)Children's Hospital of Eastern Ontario
Fundersnot available
KeywordsReferralAddictionPrimary careMental healthMedicineFamily medicineAgency (philosophy)Care pathwayClosing (real estate)Clinical pathwayPsychiatryNursingHealth care

Abstract

fetched live from OpenAlex

Findings from a novel Primary Care (PC) Mental Health (MH) pathway for children and young people in Northern Ontario, Canada are presented. Overall, 166 MH referrals from PC to a community-based child and youth MH and addictions agency (CB-CYMHA) occurred, with outstanding PC uptake (100%) and faxing referral outcomes (99%) from the CB-CYMHA to the PC provider. Half of referral outcomes (50%) were returned within 2 weeks and 83% of contacted clients reported satisfaction with services received. This successful pilot serves as an example for care pathway improvements and mobilizes knowledge for other pathway sites across Ontario.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.111
GPT teacher head0.344
Teacher spread0.233 · 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 teacher head, not a consensus.

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
Published2023
Admission routes3
Has abstractyes

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