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Record W3158383807 · doi:10.3390/pharmacy9020096

Pharmacist Prescribing for Minor Ailments Service Development: The Experience in Ontario

2021· article· en· W3158383807 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePharmacy · 2021
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMinor (academic)Service (business)PharmacyPharmacistStakeholderService delivery frameworkBusinessMedicineNursingPublic relationsPolitical scienceMarketing

Abstract

fetched live from OpenAlex

To date, eight of ten Canadian provinces have authorized pharmacists to prescribe for minor ailments. Prompted by a request by the Ontario Minister of Health, draft regulations were submitted to enable this pharmacy service in Ontario. Differences exist in how jurisdictions have approached development and delivery of these programs. This paper will summarize key differences and similarities among existing programs while highlighting the multi-pronged approach utilized by Ontario. Such an approach involved broad stakeholder engagement, implementation science, and an evaluations framework to guide an assessment of the impact of this new service. These insights can be leveraged by other jurisdictions planning to initiate or evolve their minor ailment prescribing services.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.329
GPT teacher head0.506
Teacher spread0.177 · 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