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Record W2913001140

Drug samples in family medicine teaching units: a cross-sectional descriptive study: Part 2: portrait of drug sample management in Quebec.

2018· article· en· W2913001140 on OpenAlexaffabout
Andréa Lessard, Marie‐Thérèse Lussier, Fatoumata Diallo, Michel Labrecque, Caroline Rhéaume, Pierre Pluye, Roland Grad

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcGill University Health CentreInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité LavalCentre Integre de Sante et de Services Sociaux de LavalUniversité de MontréalCentre for Interdisciplinary Research in RehabilitationMcGill UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean
Fundersnot available
KeywordsSample (material)MedicineFamily medicineProcurementDescriptive statisticsCross-sectional studyExpiration dateDrugBusinessMarketingPharmacologyPathology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To draw a portrait of drug sample management in academic primary health care settings and assess conformity to existing Canadian guidelines. DESIGN: Descriptive cross-sectional survey. SETTING: All 33 family medicine teaching units (FMTUs) in Quebec that kept drug samples. PARTICIPANTS: ). MAIN OUTCOME MEASURES: (2007). RESULTS: All 33 FMTUs responded to the questionnaire. According to managers, no FMTUs had written selection criteria to guide sample choice. Almost one-third (30%) of FMTUs had uncontrolled access to drug sample cabinets. Even though pharmaceutical companies must distribute drug samples to authorized professionals only, these professionals were involved in the procurement and the reception of samples in 79% and 56% of FMTUs, respectively. Only 15% of FMTUs kept track of samples distributed, 82% checked expiration dates, and 85% ensured proper disposal as recommended. CONCLUSION: The management of drug samples in the FMTUs in Quebec is heterogeneous, with many FMTUs and pharmaceutical companies not following Canadian guidelines.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.144
GPT teacher head0.408
Teacher spread0.264 · 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 designObservational
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

Citations4
Published2018
Admission routes2
Has abstractyes

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