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Record W4389060614 · doi:10.1016/j.rcsop.2023.100379

Investigating the impact of the COVID-19 pandemic on the occurrence of medication incidents in Canadian community pharmacies

2023· article· en· W4389060614 on OpenAlexafffundabout
Benoit A. Aubert, James R. Barker, Carla Beaton, Paola A. González, Hanieh Ghalambor-Dezfuli, Denis O’Donnell, Kim Sears, Bo Yu

Bibliographic record

VenueExploratory Research in Clinical and Social Pharmacy · 2023
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsQueen's UniversityDalhousie UniversityUniversity of TorontoHEC Montréal
FundersMitacs
KeywordsPandemicPharmacyHarmCoronavirus disease 2019 (COVID-19)Community pharmacyCoping (psychology)Medical emergencyMedicine2019-20 coronavirus outbreakBusinessFamily medicinePsychologyPsychiatryDiseaseInfectious disease (medical specialty)Social psychologyVirology

Abstract

fetched live from OpenAlex

As the COVID-19 pandemic unfolded, community pharmacies adapted rapidly to broaden and adjust the services they were providing to patients, while coping with severe pressure on supply chains and constrained social interactions. This study investigates whether these events had an impact on the medication incidents reported by pharmacists. Results indicate that Canadian pharmacies were able to sustain such stress while maintaining comparable safety levels. At the same time, it appears that some risk factors that were either ignored or not meaningful in the past started to be reported, suggesting that community pharmacists are now aware of a larger set of contributing factors that can lead to medication incidents, notably for medication incidents that can lead to harm.

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)0.020
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.880
GPT teacher head0.680
Teacher spread0.200 · 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 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

Citations1
Published2023
Admission routes3
Has abstractyes

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