Online simulations of ambulatory care for medical residents
Notice bibliographique
Résumé
Context and setting Despite a shift in patient care from inpatient to outpatient settings, graduates of internal medicine training programmes in Canada have perceived weaknesses in ambulatory care training. Resident continuity clinics may better prepare graduates for ambulatory practice, but they are logistically difficult to organise. Alternative methods are needed to improve the learning of ambulatory care principles during residency. Why the idea was necessary Residents in the internal medicine residency programme at the University of Ottawa spend most time on inpatient wards, and outpatient rotations are short in duration. Without a continuity clinic, it is difficult for residents to learn the ambulatory care principles necessary for practice, specifically continuity of care and practice management. We found little in a formal literature search on how to improve learning of these topics in this setting. We developed web-based simulations of ambulatory care, which we called ‘Continuity of Care Online Simulations’ (COCOS), to help fill this void. What was done Using endocrinology as a model, we developed an ambulatory-care curriculum that emphasises: longitudinal care of disease (monitoring disease course or treatment, adjusting therapy, when and how to discontinue therapy); special situations (medical problems of pregnancy, perioperative care), and practice management (urgency of consultations, appropriate follow-up duration and tests, collaboration with other doctors). These objectives were used to create a template storyboard that depicts sequential appointments. By adding disease-specific content to this template, we created simulations of the longitudinal care of patients with those diseases. Following the template ensured the general objectives could be discussed in reference to each specific disease. We developed 3 cases for residents to use on a trial basis. These are accessible on the Internet and require no software other than an Internet browser. Throughout each case, residents are asked to make multiple clinical and practice management decisions based on real-life scenarios. Immediate feedback is shown in pop-up message screens. Users complete an online quiz before and after each case and results are electronically recorded. Evaluation of results and impact Informal feedback from a resident focus group was strongly positive. COCOS was easy to access and navigate, and each case required an average of 25 minutes to complete. Residents felt COCOS should be used in other ambulatory care rotations, and requested access to COCOS to help prepare for qualifying examinations. It stimulated self-directed learning and preceptors noted that residents were more proactive in discussing ambulatory care topics. We used endocrinology as a model, but the template storyboard allows cases to be easily written for any specialty. The program's ability to track resident's responses could potentially be used for individual as well as rotation evaluation. Software development and maintenance was costly, and it was time-consuming to create the template and the first case. However, subsequent cases were more easily created. Revisions, if needed, were easily made, allowing incorporation of the most recent evidence. COCOS may improve residents' learning of ambulatory care principles, particularly in the absence of a resident continuity clinic. It also has the potential to expose residents to uncommon conditions, assist with lifelong learning and be used by programmes to share teaching materials and content. We plan to add another 3 cases and conduct a final evaluation.
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 | 0,002 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,001 |
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 ».