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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 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)0.009
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.986

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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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