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Enregistrement W2023936105 · doi:10.4300/jgme-d-13-00316.1

The 7 Habits of Highly Effective Rounding

2013· article· en· W2023936105 sur OpenAlexaboutno aff
Daniel A. Handel, Nicole A. Steckler

Notice bibliographique

RevueJournal of Graduate Medical Education · 2013
Typearticle
Langueen
DomaineHealth Professions
ThématiqueFamily and Patient Care in Intensive Care Units
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAccreditationMedical educationCurriculumGraduate medical educationCourseworkSet (abstract data type)PsychologyCore competencyMedicinePedagogyManagementComputer science

Résumé

récupéré en direct d'OpenAlex

In this issue of the Journal of Graduate Medical Education, Sandhu et al1 evaluate the differences between highly effective and low-yield family-centered bedside rounds. The “manager,” or rounds leader, must engage in a high level of planning and collaboration, and the leader's managerial skills were found to be crucial to creating a successful educational experience for the team. Where are these skills taught in a typical residency curriculum? They are not explicitly mentioned in the Accreditation Council for Graduate Medical Education core competencies, although it could be argued that practice-based learning, systems-based practice, and communication skills are all part of the skills set of an effective manager.2 Pilot projects have sought to prepare residents for the real world after residency,3 but they have not been systematically incorporated on a national level. In Canada, the site of this study, the 7 CanMEDS competencies are used to assess trainees, with 1 of these encompassing the role of manager.4 However, it is not clear that the importance of the manager's role is widely recognized in all settings. When asked to rate the importance of the CanMEDS' manager role, Danish residents ranked it lower for outpatient versus inpatient specialties.5Managerial skills often are taught through an “informal curriculum,” the intentional or unintentional example set by the attending physician or senior resident leading rounds.6 Steven Covey's Seven Habits of Highly Effective People was the first of many best-selling management books offering self-management strategies.7 Covey's work has long been thought to have practical applications in systems improvement,8 including that in health care.We offer evidence from the literature in business management,9 as well as medicine, using Covey's 7 habits as a framework for conducting effective family-centered bedside rounds. The aim is to emphasize practices that likely will serve physicians well in the management of medicine as well as in their personal lives.The guiding principle of family-centered care is to anticipate needs and problems so they can be addressed before getting worse. This requires proactive engagement from every member of the team, including attending physicians, residents, students, nurses, family, and patient. While not mentioned in the study by Sandhu et al,1 this is also an opportunity for the nurses and other health professionals to participate and provide valuable, unique insights. In 1 study in a pediatric population, early clinician engagement and improved multidisciplinary communication led to a reduction of greater than 50% in adverse drug reactions.10Leaders, whether attending physicians or senior residents, should have an idea of what they hope to accomplish each day. Leaders on rounds also should have at least a general familiarity with each patient's condition prior to rounds, allowing them to guide learners and families. The plan should include setting a target for when rounds will conclude and the time available for each patient encounter, which will depend on the number of patients on the service. On busier days, a more streamlined approach is warranted; by setting goals for each encounter, lengthy conversations with families can be minimized. One study found that a lean, focused, patient-centric rounding structure not only increased patient and staff satisfaction but also improved patient throughput and decreased attending physicians' hours used.11 Lean and six-sigma methods12 have also been used to streamline rounding by standardizing practices and eliminating nonessential activities such as “pre-rounding.”13,14Time management was cited by Sandhu et al1 as an important educational component of family-centered bedside rounds. A key component of time management is prioritizing important tasks. The leader should prioritize the order of patients during rounds by seeing patients who are waiting for the team's action first, such as patients who are ready for discharge or waiting for time-sensitive tests to be ordered or who need team assessment to determine the next step in their care. This allows team members to initiate important decisions sooner and thereby improve patient throughput and quality of care. Articulating why patients are being seen in a particular order also teaches learners how to prioritize patient care, a valuable skill for their future careers.Sandhu et al1 identify competing patient care and educational priorities as a contributing factor to the educational success of family-centered bedside rounds. In order to optimize both the learner's educational experience and the patient's quality of care, leaders should seek mutually beneficial “win-win” solutions as an effective strategy to balance competing priorities. Leaders must help learners solicit knowledge about the patient and medical practice while not undermining the patient's confidence in the learner's skills once the leader leaves. Initial inquiries from the leader should start with general questions and increase in detail and complexity based on the learner's responses. If constructive feedback to the learner is needed, this should be given later and in private.After setting the tone and time frame for the patient encounter, the leader should remain quiet while the team presents the case. Any questions should be succinct to gain better understanding as well as demonstrate the leader's interest and engagement in the presentation. Prior review of the patient's chart will help the leader anticipate important questions.Once the team proposes an initial plan, the leader can help tailor it to meet patient and family needs. By explaining why changes are needed, the leader will further educate participants in the clinical reasoning process and underlying science.Improved patient health depends on active participation by all team members. For this reason, subtle discoveries by each team and family member should be celebrated. Each piece of data can have a profound impact on patient outcomes. When the leader invites and explicitly acknowledges input, it creates a positive feedback loop, encouraging future team participation and thereby improving the level of care.15 Several studies have demonstrated that interdisciplinary rounds improve learning and quality of care.16–19 Currently, this is not standard practice.20The leader should explicitly set aside time daily or weekly to debrief with the team to discuss how rounds went and how they can be improved, which should include requesting feedback about the leader's own organization of the process. By using the feedback to improve future rounds, the leader models commitment to lifelong learning and interest in improving the experience for all involved.Management strategies have traditionally been considered less relevant to medical education and more applicable to the business world, yet the management processes and practices used by attending physicians and senior residents are a valuable implicit part of the curriculum, whether intended or not. Consistent modeling of skillful daily rounds management by medical leaders can prepare learners to manage their own practice of medicine most effectively.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,029
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,711
Score d'incertitude au seuil0,979

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,029
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,063
Tête enseignante GPT0,417
Écart entre enseignants0,354 · 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 tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

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

En bref

Citations1
Publié2013
Routes d'admission1
Résumé présentoui

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