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Enregistrement W2334143500 · doi:10.1097/acm.0b013e31826d5962

Fluency—Not Competency or Expertise—Is Needed to Incorporate Evidence Into Practice

2012· article· en· W2334143500 sur OpenAlexaffabout
Liz Bayley, Andrea McLellan, Jo‐Anne Petropoulos

Notice bibliographique

RevueAcademic Medicine · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueClinical Reasoning and Diagnostic Skills
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésFluencyMedical educationMEDLINEPsychologyMedicineMathematics educationPolitical science

Résumé

récupéré en direct d'OpenAlex

Twenty years ago, the Journal of the American Medical Association published an article describing a “new approach to teaching the practice of medicine”: evidence-based medicine (EBM).1 Today, the ability to apply research to practice is a program accreditation requirement at both the undergraduate and postgraduate levels in the United States and Canada as well as an ongoing practice competency requirement. The EBM process—assessing the patient, asking the question, acquiring the evidence, assessing and applying that evidence, and finally evaluating the whole process—seeks to provide a framework for the integration of evidence into clinical practice. Much of the training around EBM has focused on building expertise in literature searching and critical appraisal of resources; however, as Moore’s2 response to the 2011 Question of the Year indicated, these efforts have not been successful in practice. Perhaps one of the most effective ways to ensure that those who work and learn in medical schools and teaching hospitals can develop to their full potential is to shift from the perspective that these individuals must become experts in EBM to the view that they should become comfortable with the tools which will allow them to be fluent users of the evidence. To that end, we propose four levels of performance: Literacy—knowing and understanding the EBM concepts; Competency—being able to apply these concepts in controlled conditions; Fluency—having a comfort level with incorporating the concepts into daily practice; and Expertise—having the high level of skill needed to create and demonstrate the tools that translate research into practice. There is simplicity with building competency around a skill set that can be defined, taught, and evaluated through assignments, objective structured clinical examinations, or licensing examinations. But what is required to move a medical student or physician from a level of competency to one of fluency? Increasing their understanding of clinical information systems, both organizational and technological, is key. Building on Marcum’s3 position that fluency can only be achieved in the workplace, the focus must be on providing training and support for processes that can be readily integrated into regular practice routines. For medical students, this would include determining realistic competencies for the clinical practice environment and simulating that environment to train them to integrate the skills and clinical tools and resources required. Just as fluency in language is best developed through immersion in the native culture, fluency in the use of health information is best developed through immersion in the culture of EBM. Of particular importance is the identification and support of physician role models. For residents and clinicians to become fluent, it is necessary to integrate clinical practice tools and resources into the clinical interface and to ensure that ongoing support and training are available at the point of need. Librarians and informaticians play crucial roles in fostering EBM fluency in medical schools and teaching hospitals. The ideal, as outlined by Moore,2 is the integration of these specialists into health care teams. When this is not possible due to issues of availability, scalability, or sustainability, a level of self-sufficiency is required on the part of health care practitioners. In conjunction with physicians and informaticians, librarians are developing and supporting health information technology initiatives that integrate point-of-care resources into the clinical interface. Librarians are responsible for ensuring that point-of-care resources are licensed and linked at as granular a level as possible, as well as for providing ongoing support and training in the use of those resources. They also play a major role in building medical students’ EBM skills, particularly those related to the effective search for and use of high-quality, best-evidence resources. Librarians must collaborate with medical educators and informaticians in the development and utilization of simulated clinical interfaces to present patient data and to integrate best-evidence resources into those interfaces. When this is accomplished, EBM skills will come to be seen as a seamless part of the clinical process, with a resultant increase in students’ confidence and fluency. While the effective implementation of electronic health records and clinical information systems is challenging, using technology to deliver and integrate EBM resources is the best chance of attaining Garrity’s4 vision of focusing on “evidence” as part of treatment and care to ensure that “clinicians are given just the information they need to advance health, to provide each person the best care, at the right time, every time.”

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,050
score de la tête « metaresearch » (Gemma)0,149
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,050
Score d'incertitude au seuil0,264

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0500,149
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0030,001
Études des sciences et des technologies0,0040,013
Communication savante0,0110,018
Science ouverte0,0020,012
Intégrité de la recherche0,0070,007
Charge utile insuffisante (le modèle a refusé de juger)0,0070,005

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,146
Tête enseignante GPT0,464
Écart entre enseignants0,318 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2012
Routes d'admission2
Résumé présentoui

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