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Record W4385956680 · doi:10.13162/hro-ors.v11i2.5324

Implementation of a Pharmacy Clinical Instructor Model to Facilitate Experiential Learning within Saskatchewan’s Entry-to-Practice Doctor of Pharmacy Program

2023· paratext· en· W4385956680 on OpenAlexaffvenueabout

Bibliographic record

VenueHealth Reform Observer - Observatoire des Réformes de Santé · 2023
Typeparatext
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsSaskatchewan Health AuthorityUniversity of ReginaUniversity of Saskatchewan
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

In response to nationally endorsed changes in pharmacy curricula, the University of Saskatchewan College of Pharmacy and Nutrition (CoPN) sought to expand experiential learning for its pharmacy program. In 2010, Canada’s faculties and deans of pharmacy committed to implementing entry-to-practice Doctor of Pharmacy (PharmD) programs in all schools by 2020. The expansion and change in credentialing of Canada’s pharmacy training from baccalaureate programs was intended to ensure graduates possess the competencies required within the modern scope of pharmacy practice. To further this transition, the Canadian Council for Accreditation of Pharmacy Programs increased the required hours of students’ experiential learning. In Saskatchewan, pre-existing operational and financial pressures on the CoPN, coinciding with the provincial health system’s amalgamation from twelve regional health authorities to a single health authority, prompted a collaborative approach. To address the growing need for practical experience within the Saskatchewan Health Authority, the CoPN implemented clinical instructor positions within tertiary care centres in Saskatoon and Regina. This unique approach among PharmD programs provided financial stability and accountability to student learning, although early student feedback identified several challenges with this model. These findings about the clinical instructor model can guide the ongoing implementation of experiential learning within PharmD and other health care professional programs. En réponse aux changements approuvés au niveau national dans les programmes d'études en pharmacie, le College of Pharmacy and Nutrition (CoPN) de l'Université de Saskatchewan a entrepris de multiplier les expériences d'apprentissage de son programme d'études en pharmacie. En 2010, les facultés et les doyens des facultés de pharmacie du Canada se sont engagés à mettre en place des programmes de doctorat en pharmacie (PharmD) dans toutes les écoles à l'horizon 2020. L'expansion et la modification de l'accréditation de la formation en pharmacie au Canada à partir des programmes de baccalauréat visaient à garantir que les diplômés possèdent les compétences requises au regard du champ d’exercice renouvelé de la pharmacie. Pour faciliter cette transition, le conseil canadien pour l'accréditation des programmes de pharmacie a augmenté le nombre d'heures requises pour l'apprentissage par l'expérience des étudiants. Dans la province de Saskatchewan, les tensions opérationnelles et financières préexistantes sur le CoPN, jointes à l’opération de fusion des douze autorités sanitaires régionales du système de santé provincial en une seule autorité sanitaire, ont incité à une approche collaborative. Pour répondre au besoin croissant d'expérience pratique au sein de la Saskatchewan Health Authority, le CoPN a mis en place des postes d'instructeurs cliniques dans les centres de soins tertiaires de Saskatoon et Regina. Cette approche originale parmi les programmes de doctorat en pharmacie a assuré la stabilité financière de l'apprentissage des étudiants et a clairement identifié les responsabilités, même si les premiers retours d’expérience des étudiants ont mis en évidence plusieurs défis liés à ce modèle. Ces résultats concernant le modèle d'instructeur clinique peuvent guider la mise en œuvre continue de l'apprentissage par l'expérience au sein des programmes de doctorat en pharmacie et d'autres programmes professionnels de soins de santé.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.158
GPT teacher head0.502
Teacher spread0.344 · 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 designNot applicable
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

Citations1
Published2023
Admission routes3
Has abstractyes

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