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Record W4417523815 · doi:10.12927/hcpol.2025.27693

Pharmacists’ perspectives on delivery of clinical services and the current payment model in British Columbia, Canada

2025· article· en· W4417523815 on OpenAlexaffvenueabout
Angela Pang, Adam Easterbrook, Alexander C. T. Tam, Nick Bansback, Michael R. Law, Craig Mitton, Larry D. Lynd, I Fan Kuo, Olivia L. Tseng, Wei Zhang

Bibliographic record

VenueHealthcare policy · 2025
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsCentre for Advancing Health OutcomesProvidence Health CareMinistry of HealthVancouver Coastal HealthGovernment of British ColumbiaUniversity of British Columbia
Fundersnot available
KeywordsPaymentService (business)Service delivery frameworkPayment service providerHealth servicesCurrent (fluid)

Abstract

fetched live from OpenAlex

Introduction: Pharmacists' service fees are paid to pharmacies, not directly to pharmacists, which may hinder the adoption of expanded pharmacists' services. Our aim was to identify barriers and enablers to pharmacists' delivery of services in relation to the payment model. Methodology: We conducted semi-structured interviews with community pharmacists or owners in British Columbia using a constructivist approach and performed a thematic analysis. Results: Three themes emerged: Conclusion: While payment is a significant factor in deterring pharmacists from clinical service delivery, systemic factors also influence how pharmacists feel about their role.

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)0.003
metaresearch head score (Gemma)0.009
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.809

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0180.005
Scholarly communication0.0070.001
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.120
GPT teacher head0.483
Teacher spread0.363 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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