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Record W2074106242 · doi:10.4212/cjhp.v66i1.1206

Before-and-After Study of Interruptions in a Pharmacy Department

2013· article· en· W2074106242 on OpenAlexaffvenueabout
Aurélie Guérin, E. Caron, Denis Lebel, Jean‐François Bussières

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2013
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsPharmacyMedicineObservational studyStimulus (psychology)AudiologyFamily medicinePsychology

Abstract

fetched live from OpenAlex

Background: Few data exist on interruptions in the drug-use process in hospital pharmacies and their effects on patient care.Objective: The primary objective was to compare the hourly number of stimuli received and emitted (i.e., generated) by pharmacists and pharmacy technicians before and after implementation of measures intended to reduce interruptions. The secondary objective was to evaluate the impact of the corrective measures on 4 specific stimuli.Methods: This before-and-after cross-sectional observational study was conducted in the main dispensing area of the pharmacy department of a Canadian university hospital centre. Stimuli received and emitted by pharmacists and pharmacy technicians were counted before (2010) and after (2012) implementation of corrective measures designed to limit interruptions. The effect of corrective measures on targeted stimuli was measured with a t test.Results: Data were collected during a total of 93 randomly scheduled 30-min observation periods: 62 periods in 2010 (n 2663 stimuli) and 31 periods in 2012 (n = 1217 stimuli). The average hourly stimulus rate (± standard deviation) was unchanged after implementation of corrective measures: 85.9 ± 22.2 in 2010 and 78.5 ± 20.1 in 2012 (p = 0.06). However, a significant decline was observed for many individual stimuli, including the number of face-to-face nonprofessional conversations among pharmacists (4.4 ± 4.2 in 2010 versus 1.2 ± 1.8 in 2012, p = 0.003).Conclusion: Despite the implementation of corrective measures, there was no statistically significant change in the hourly stimulus rates from 2010 to 2012. Other studies are needed to better characterize the nature and repercussions of stimuli, distractions, and interruptions.RÉSUMÉContexte : Il existe peu de données sur les interruptions dans le processus de distribution des médicaments au sein des pharmacies d’hôpitaux et de leurs effets sur les soins aux patients.Objectif : Le principal objectif était de comparer le nombre de stimuli reçus et émis (c.-à-d. engendrés) à l’heure par les pharmaciens et les assistants techniques en pharmacie avant et après la mise en oeuvre de mesures correctives visant à limiter les interruptions. L’objectif secondaire était d’évaluer l’incidence des mesures correctives sur quatre stimuli particuliers.Méthodes : Il s’agit d’une étude d’observation transversale pré- et post-intervention menée dans la principale aire de distribution du service de pharmacie d’un centre hospitalier universitaire canadien. Les stimuli reçus et émis par les pharmaciens et les assistants techniques en pharmacie ont été comptés avant (2010) et après (2012) la mise en oeuvre de mesures correctives visant à limiter les interruptions. L’effet de ces mesures sur les stimuli ciblés a été mesuré au moyen d’un test t.Résultats : Les données ont été collectées au cours de 93 périodes d’observation aléatoires de 30 minutes : 62 périodes en 2010 (n = 2663 stimuli) et 31 périodes en 2012 (n = 1217 stimuli). Le taux moyen de stimuli par heure (± l’écart type) est demeuré inchangé après la mise en oeuvre des mesures correctives : 85,9 ± 22,2 en 2010 et 78,5 ± 20,1 en 2012 (p = 0,06). Cependant, plusieurs stimuli ont individuellement baissé de façon significative, dont le nombre de conversations non professionnelles en personne parmi les pharmaciens (4,4 ± 4,2 en 2010 contre 1,2 ± 1,8 en 2012, p = 0,003).Conclusion : Malgré la mise en oeuvre de mesures correctives, aucun changement statistiquement significatif n’a été observé dans les taux de stimuli par heure entre l’année 2010 et l’année 2012. D’autres études sont nécessaires afin de mieux caractériser la nature et les répercussions des stimuli, des distractions et des interruptions.

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)0.002
metaresearch head score (Gemma)0.010
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.050
GPT teacher head0.400
Teacher spread0.350 · 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".

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Citations7
Published2013
Admission routes3
Has abstractyes

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