Training in Trauma Surgery
Notice bibliographique
Résumé
OBJECTIVE: To describe outcomes from a clinical trauma surgical education program that places the board-eligible/board-certified fellow in the role of the attending surgeon (fellow-in-exception [FIE]) during the latter half of a 2-year trauma/surgical critical care fellowship. SUMMARY BACKGROUND DATA: National discussions have begun to explore the question of optimal methods for postresidency training in surgery. Few objective studies are available to evaluate current training models. METHODS: We analyzed provider-specific data from both our trauma registry and performance improvement (PI) databases. In addition, we performed TRISS analysis when all data were available. Registry and PI data were analyzed as 2 groups (faculty trauma surgeons and FIEs) to determine experience, safety, and trends in errors. We also surveyed graduate fellows using a questionnaire that evaluated perceptions of training and experience on a 6-point Likert scale. RESULTS: During a 4-year period 7,769 trauma patients were evaluated, of which 46.3% met criteria to be submitted to the PA Trauma Outcome Study (PTOS, ie, more severe injury). The faculty group saw 5,885 patients (2,720 PTOS); the FIE group saw 1,884 patients (879 PTOS). The groups were similar in respect to mechanism of injury (74% blunt; 26% penetrating both groups) and injury severity (mean ISS faculty 10.0; FIEs 9.5). When indexed to patient contacts, FIEs did more operations than the faculty group (28.4% versus 25.6%; P < 0.05). Death rates were similar between groups (faculty 10.5%; FIEs 10.0%). Analysis of deaths using PI and TRISS data failed to demonstrate differences between the groups. Analysis of provider-specific errors demonstrated a slightly higher rate for FIEs when compared with faculty when indexed to PTOS cases (4.1% versus 2.1%; P < 0.01). For both groups, errors in management were more common than errors in technique. Twenty-one (91%) of twenty-three surveys were returned. Fellows' feelings of preparedness to manage complex trauma patients improved during the fellowship (mean 3.2 prior to fellowship versus 4.5 after first year versus 5.8 after FIE year; P < 0.05 by ANOVA). Eighty percent rated the FIE educational experience "great -5" or "exceptional- 6." Eighty-five percent consider the current structure of the fellowship (with FIE year) as ideal. Ninety percent would repeat the fellowship. CONCLUSION: The educational experience and training improvement offered by the inclusion of a FIE period during a trauma fellowship is exceptional. Patient outcomes are unchanged. The potential for an increased error rate is present during this period of clinical autonomy and must be addressed when designing the methods of supervision of care to assure concurrent senior staff review.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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) | 0,000 | 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 ».