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Record W3164026061 · doi:10.3390/pharmacy9020107

A De Novo Pharmacist-Family Physician Collaboration Model in a Family Medicine Clinic in Alberta, Canada

2021· article· en· W3164026061 on OpenAlexaffabout
Hoan Linh Banh, Andrew Cave

Bibliographic record

VenuePharmacy · 2021
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPharmacistFamily medicineMedicineScope of practiceMedical prescriptionWorkloadClinical pharmacyChemistHealth careNursingPharmacy

Abstract

fetched live from OpenAlex

Collaborative practice in health-care has proven to be an effective and efficient method for the management of chronic diseases. This study describes a de novo collaborative practice between a pharmacist and a family physician. The primary objective of the study is to describe the collaboration model between a pharmacist and family physician. The secondary objective is to describe the pharmacist workload. A list of patients who had at least one interaction with the pharmacist was generated and printed from the electronic medical record. There were 389 patients on the patient panel. The pharmacist had at least one encounter with 159 patients. There were 83 females. The most common medical condition seen by the pharmacist was hypertension. A total of 583 patient consultations were made by the pharmacist and 219 of those were independent visits. The pharmacist wrote 1361 prescriptions. The expanded scope of practice for pharmacists in Alberta includes additional prescribing authority. The pharmacists' education and clinical experience gained trust from the family physician. These, coupled with the family physician's previous positive experience working with pharmacists made the collaboration achievable.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.200
GPT teacher head0.462
Teacher spread0.262 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2021
Admission routes2
Has abstractyes

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