MétaCan
Menu
Back to cohort
Record W2496734960

Maternité et pratique de la pharmacie : cadre juridique, programme et enjeux

2016· article· fr· W2496734960 on OpenAlexaboutno aff
Jean‐François Bussières, Alexia Janes, Céline Poupeau, Iciar Piaget, René-Claude Bernier, Suzanne Atkinson

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldHealth Professions
TopicSafe Handling of Antineoplastic Drugs
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

Resume Objectif : L’objectif principal est de presenter le programme « Pour une maternite sans danger » qui assure une reaffectation ou un retrait preventif du travail des travailleuses enceintes ou qui allaitent, ainsi que la mise en oeuvre de ce programme en pharmacie hospitaliere. Description de la problematique : Un examen de la documentation scientifique a ete realise avec les termes suivants : maternite, conge de maternite, employees enceintes, sante et securite au travail, maternity, maternity leave, pregnant employee et occupational safety and health. Les references pertinentes ont ete relevees sur Google, Google Scholar et PubMed. Cet etat des lieux du programme a servi de base de reflexion pour son application en pharmacie. Resolution de la problematique : En 2014, la Direction de la sante publique de Montreal a recu 9 490 demandes d’etude de dossier, dont 0,4 % issues du milieu pharmaceutique. Selon l’etude de poste standardisee, des mesures de prevention etaient necessaires et pouvaient mener a une reaffectation pour 4 des 5 categories de risque, a savoir le risque ergonomique, physique, chimique ou biologique (aucune recommandation n’etait emise pour la categorie psychosociale). En pharmacie, nous avons considere qu’une majorite des travailleuses pouvait etre reaffectee sans qu’un retrait preventif soit requis, en raison de la diversite du travail. Douze recommandations sont proposees, telles qu’une reaffectation hors de la zone de preparation de medicaments dangereux ou le maintien a la prestation de soins en clinique si des mesures de protection sont prises. Conclusion : Le personnel de pharmacie a relativement peu recours au programme de retrait preventif du travail. Les nombreuses possibilites de reaffectation en pharmacie hospitaliere peuvent expliquer ce constat. Chaque departement de pharmacie devrait se doter d’une politique de reaffectation pour les travailleuses enceintes ou qui allaitent. Abstract Objective: The primary objective is to present the Pour une maternite sans danger (Safe Maternity) program, which provides for the reassignment and/or preventative withdrawal of pregnant workers, and its application in hospital pharmacies. Problem description: A literature review was conducted with the following terms: maternity, maternity leave, pregnant employee and occupational safety and health. The relevant references were identified via Google, Google Scholar and PubMed. This review of the program served as a basis for reflection on its application in pharmacies. Problem resolution: In 2014, the Montreal Public Health Department received 9,490 requests pertaining to the program, 0.4% of which were from the pharmaceutical sector. According to the standardized job analysis, preventive measures were necessary and could lead to a reassignment in four of the five risk categories, i.e., ergonomic, physical, chemical and biological (no recommendation for the psychosocial category). We found that most pregnant pharmacy employees could be reassigned. Preventative withdrawal was not necessary due to the diversity of the work. Twelve recommendations are proposed, such as a reassignment outside the hazardous drug preparation area and maintaining offers of clinical care if protective measures are taken. Conclusion: Pharmacy staff seldom use the preventive withdrawal program. This can be explained by the numerous reassignment options in hospital pharmacies. Each pharmacy department should adopt a reassignment policy.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.651
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.004

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 head0.060
GPT teacher head0.436
Teacher spread0.376 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicSafe Handling of Antineoplastic DrugsFrench-language works237,207