Variation in Case Exposure During Internal Medicine Residency
Notice bibliographique
Résumé
Importance: Variation in residency case exposure affects resident learning and readiness for future practice. Accurate reporting of case exposure for internal medicine (IM) residents is challenging because feasible and reliable methods for linking patient care to residents are lacking. Objective: To develop an integrated education-clinical database to characterize and measure case exposure variability among IM residents. Design, Setting, and Participants: In this cohort study, an integrated educational-clinical database was developed by linking patients admitted during overnight IM in-hospital call shifts at 5 teaching hospitals to senior on-call residents. The senior resident, who directly cares for all overnight IM admissions, was linked to their patients by the admission date, time, and hospital. The database included IM residents enrolled between July 1, 2010, and December 31, 2019, in 1 Canadian IM residency. Analysis occurred between August 1, 2023, and June 30, 2024. Main Outcomes and Measures: Case exposure was defined by patient demographic characteristics, discharge diagnoses, volumes, acuity (eg, critical care transfer), medical complexity (eg, Charlson Comorbidity Index), and social determinants of health (eg, from long-term care). Residents were grouped into quartiles for each exposure measure, and the top and bottom quartiles were compared using standardized mean difference (SMD). Variation between hospitals was evaluated by calculating the SMD between the hospitals with the highest and lowest proportions for each measure. Variation over time was assessed using linear and logistic regression. Results: The integrated educational-clinical database included 143 632 admissions (median [IQR] age, 71 [55-83] years; 71 340 [49.7%] female) linked to 793 residents (median [IQR] admissions per shift, 8 [6-12]). At the resident level, there was substantial variation in case exposure for demographic characteristics, diagnoses, volumes, acuity, complexity, and social determinants. For example, residents in the highest quartile had nearly 4 times more admissions requiring critical care transfer compared with the lowest quartile (3071 of 30 228 [10.2%] vs 684 of 25 578 [2.7%]; SMD, 0.31). Hospital-level variation was also significant, particularly in patient volumes (busier hospital vs less busy hospital: median [IQR] admissions per shift, 10 [8-12] vs 7 [5-9]; SMD, 0.96). Over time, residents saw more median (IQR) admissions per shift (2010 vs 2019: 7.6 [6.6-8.4] vs 9.0 [7.6-10.0]; P = .04) and more complex patients (2010 vs 2019: Charlson Comorbidity Index ≥2, 3851 of 13 762 [28.0%] vs 2862 of 8188 [35.0%]; P = .03), while working similar shifts per year (median [IQR], 11 [8-14]). Conclusions: In this cohort study of IM residents in a Canadian residency program, significant variation in case exposure was found between residents, across sites, and over 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 distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| 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 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».