MétaCan
Menu
Back to cohort
Record W2891941799 · doi:10.4212/cjhp.v71i4.2834

Development of Pictograms to Enhance Medication Safety Practices of Health Care Workers and International Preferences

2018· article· en· W2891941799 on OpenAlexaffvenueabout
Régis Vaillancourt, Mike Zender, Laurie Coulon, Annie Pouliot

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2018
Typearticle
Languageen
FieldPsychology
TopicSafety Warnings and Signage
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsPictogramHealth carePatient safetyMedicineNursingFamily medicinePolitical science

Abstract

fetched live from OpenAlex

<p>ABSTRACT</p><p>Background: A panel of medication management experts previously<br />identified 9 key medication safety issues and high-alert drug classes as<br />representing the most pressing medication-handling issues in health care.</p><p>Objective: To develop medication safety pictograms depicting medication<br />safety issues and high-alert drug classes that represent medication-handling<br />risks for health care personnel.</p><p>Methods: An iterative design process, including activities such as semiotic<br />analysis, design/redesign, and evaluation, was used to develop medication<br />safety pictograms. Nurses, physicians, pharmacists, and students listed<br />and drew graphic elements to depict each of the 9 key medication safety<br />issues. Graduate students in graphic design developed the preliminary<br />pictograms for the study. A Delphi survey was then conducted with<br />experts recruited from the International Pharmaceutical Federation to<br />reach consensus on the pictograms and provide feedback to the graphic<br />designers. Health care providers from around the world were invited to<br />participate in a survey to determine a preferred pictogram for each safety<br />warning.</p><p>Results: For each medication safety issue, 3 to 5 pictograms were<br />developed on the basis of graphic elements suggested by 52 health care<br />providers. These pictograms were then presented to 58 experts in 2 rounds<br />of a Delphi process. For each medication safety issue, consensus on the<br />2 best pictograms was reached and feedback provided. A total of 799<br />participants from 61 countries responded to the international preference<br />survey. Most of the participants (n = 536, 67.1%) were Canadian, and of<br />those, 385 (71.8%) were pharmacists. In 8 categories, consensus on the<br />preferred pictogram was reached across the health care professions;<br />however, a difference in preference was apparent for the pictogram<br />representing “neuromuscular blocking agent”, with nurses’ preferred<br />pictogram differing from the preference of other participants.</p><p>Conclusion: This project produced pictograms to illustrate 9 important<br />medication safety issues, which can now be validated through comprehension<br />and recall assessments. Further study can also determine their<br />potential to reduce medication administration errors.</p><p>RÉSUMÉ</p><p>Contexte : Un groupe d’experts en gestion des médicaments avait auparavant<br />établi neuf principales questions de sécurité des médicaments ou classes<br />de médicaments de niveau d’alerte élevé qui méritaient l’attention la plus<br />urgente en santé du point de vue de la manipulation des médicaments.</p><p>Objectif : Concevoir des pictogrammes de sécurité des médicaments qui<br />illustrent adéquatement les questions de sécurité des médicaments et les<br />classes de médicaments de niveau d’alerte élevé représentant des risques<br />pour le personnel en santé lors de la manipulation des médicaments.</p><p>Méthodes : Un processus de conception itératif (comprenant des activités<br />comme l’analyse sémiotique, la conception et la rectification, et l’évaluation)<br />a été employé pour créer des pictogrammes de sécurité des médicaments.<br />Du personnel infirmier, des médecins, des pharmaciens et des étudiants<br />ont dressé une liste d’éléments graphiques qu’ils ont dessinés afin d’illustrer<br />chacune des neuf principales questions de sécurité des médicaments. Des<br />étudiants diplômés en graphisme ont conçu les ébauches de pictogrammes<br />destinées à l’étude. Un sondage Delphi a ensuite été mené auprès d’experts<br />recrutés au sein de la Fédération internationale pharmaceutique afin de<br />dégager un consensus quant aux pictogrammes et de fournir des<br />commentaires constructifs aux graphistes. Des fournisseurs de soins de santé<br />de partout dans le monde ont été invités à répondre à un sondage pour<br />déterminer quel pictogramme privilégier pour chacune des mises en garde.</p><p>Résultats : Pour chaque question de sécurité des médicaments, entre trois<br />et cinq pictogrammes ont été conçus à partir d’éléments graphiques<br />proposés par 52 fournisseurs de soins de santé. Ces pictogrammes ont<br />ensuite été présentés à 58 experts au cours d’un processus Delphi à deux<br />phases. Pour chacune des questions de sécurité des médicaments, un<br />consensus sur les deux meilleurs pictogrammes a été atteint et des<br />commentaires constructifs ont été émis. Au total, 799 participants de<br />61 pays ont répondu au sondage international sur leurs préférences. La<br />majorité des participants (n = 536, 67,1 %) étaient Canadiens et parmi<br />eux, 385 (71,8 %) étaient pharmaciens. Dans huit catégories, l’ensemble<br />des professions ont atteint un consensus quant au pictogramme à<br />privilégier. Cela n’a pas été le cas pour le pictogramme représentant les<br />« bloqueurs neuromusculaires », car le personnel infirmier a privilégié un pictogramme<br />différent de celui préféré par les autres professions participantes.</p><p>Conclusions : Ce projet a produit des pictogrammes pour illustrer neuf<br />importantes questions de sécurité des médicaments. Ces pictogrammes<br />peuvent maintenant être validés à l’aide de tests de compréhension et de<br />mémoire. De plus amples études pourront aussi déterminer dans quelle<br />mesure ces pictogrammes aident à réduire les erreurs d’administration de<br />médicaments.</p><p> </p>

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.044
GPT teacher head0.400
Teacher spread0.355 · 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 designOther design
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

Citations7
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of Hospital PharmacySame topicSafety Warnings and SignageFrench-language works237,207