ODP579 An EMR And Educational Intervention To Avoid Excessive Fingerstick Blood Glucose Testing In Low-risk Hospitalized Patients With Type Ii Diabetes
Notice bibliographique
Résumé
Abstract Introduction Telemedicine has become the cornerstone of health care delivery in the COVID-19 pandemic, as it allows patients to be cared for at a distance. Though institutions have published experiences with telemedicine incorporated into residency training programs during the pandemic, there is a lack of qualitative data in this field. This descriptive qualitative study sought to (1) explore internal medicine resident experiences with telehealth patient encounters during the COVID-19 pandemic, and (2) understand resident experiences with virtually reviewing cases with their supervisors. Methods From November 2020 to March 2021, the authors conducted 20 semi-structured interviews with internal medicine residents at the University of Toronto. Residents were included if they completed ambulatory rotations such as endocrinology. Interviews were transcribed, line-by-line coding was done in parallel, and themes were derived through inductive and constant comparative analysis. Results Resident experiences with telemedicine were divided into themes according to the perceived benefits and challenges with patient encounters, and with virtually reviewing cases with supervisors. Perceived benefits in patient encounters included less pressure for time and increased efficiency, and residents looked at this patient care modality as an important component of their future careers. Challenges included a deficiency of nonverbal cues to use for building rapport with patients and confirming their understanding, inability to confidently form an impression of a patient and their disease severity, the lack of physical examination, and technical audio-visual challenges. While most residents preferred in-person to virtual review with their supervisors, the benefits of the virtual review included a supportive learning environment, and a high level of autonomy for senior residents. However, residents felt that feedback over a virtual platform was generic and not constructive, and junior trainees did not have opportunities to observe staff demonstrate essential skills needed for telemedicine care. Discussion Telemedicine incorporation into postgraduate medical education is still in its early stages, and data on resident experiences is crucial to inform ways of optimizing the learning environment and preceptorship of such encounters. The virtual review process, limited by the same communication challenges that residents faced with patients, inherently involves less supervision and guidance than an in-person review. While this may support the learning needs of more experienced residents by offering more autonomy, junior residents may be affected by the lack of opportunities for observation of essential skills and the absence of coaching through constructive feedback. More research is needed especially on educational interventions that can help overcome the virtual communication challenges between residents, patients, and their clinical supervisors. Presentation: No date and time listed
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».