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Enregistrement W2217851873 · doi:10.3171/2015.4.jns142149

Assessment of the “July Effect”: outcomes after early resident transition in adult neurosurgery

2015· article· en· W2217851873 sur OpenAlexaboutno aff
Bryan Lieber, Geoffrey Appelboom, Blake Taylor, Hani Malone, Nitin Agarwal, E. Sander Connolly

Notice bibliographique

RevueJournal of neurosurgery · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueHospital Admissions and Outcomes
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineSubspecialtyNeurosurgeryQuarter (Canadian coin)PopulationFamily medicineGeneral surgeryEmergency medicineSurgery

Résumé

récupéré en direct d'OpenAlex

OBJECT Each July, 4th-year medical students become 1st-year resident physicians and have much greater responsibility in making management decisions. In addition, incumbent residents and fellows advance to their next postgraduate year and face greater challenges. It has been suggested that among patients who have resident physicians as members of their neurosurgical team, this transition may be associated with increased rates of morbidity and mortality, a phenomenon known as the "July Effect." In this study, the authors compared morbidity and mortality rates between the initial and later months of the academic year to determine whether there is truly a July Effect that has an impact on this patient population. METHODS The authors compared 30-day postoperative outcomes of neurosurgery performed by surgical teams that included resident physicians in training during the first academic quarter (Q1, July through September) with outcomes of neurosurgery performed with resident participation during the final academic quarter (Q4, April through June), using 2006-2012 data from the prospectively collected American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database. Regression analyses were performed on outcome data that included mortality, surgical complications, and medical complications, which were graded as mild or severe. To determine whether a July Effect was present in subgroups, secondary analyses were performed to analyze the association of outcomes with each major neurosurgical subspecialty, the postgraduate year of the operating resident, and the academic quarter during which the surgery was performed. To control for possible seasonal trends in certain diseases, the authors compared patient outcomes at academic medical centers to those at community-based hospitals, where procedures were not performed by residents. In addition, the efficiency of academic centers was compared to that of community centers in terms of operative duration and total length of hospital stay. RESULTS Overall, there were no statistically significant differences in mortality, morbidity, or efficiency between the earlier and later quarters of the academic year, a finding that also held true among neurosurgical subspecialties and among postgraduate levels of training. There was, however, a slight increase in intraoperative transfusions associated with the transitional period in July (6.41% of procedures in Q4 compared to 7.99% in Q1 of the prior calendar year; p = 0.0005), which primarily occurred in cases involving junior (2nd- to 4th-year) residents. In addition, there was an increased rate of reoperation (1.73% in Q4 to 2.19% in Q1; p < 0.0001) observed mainly among senior (5th- to 7th-year) residents in the early academic months and not paralleled in our community cohort. CONCLUSIONS There is minimal evidence for a significant July Effect in adult neurosurgery. Our results suggest that, overall, the current resident training system provides enough guidance and support during this challenging transition period.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,015
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,005
Score d'incertitude au seuil0,021

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,015
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0010,002
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,016
Tête enseignante GPT0,294
Écart entre enseignants0,278 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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

Citations44
Publié2015
Routes d'admission1
Résumé présentoui

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