Biomathematical Modeling Predicts Fatigue Risk in General Surgery Residents.
J Surg Educ
; 78(6): 2094-2101, 2021.
Article
en En
| MEDLINE
| ID: mdl-33994335
ABSTRACT
OBJECTIVE:
To assess resident fatigue risk using objective and predicted sleep data in a biomathematical model of fatigue.DESIGN:
8-weeks of sleep data and shift schedules from 2019 for 24 surgical residents were assessed with a biomathematical model to predict performance ("effectiveness").SETTING:
Greater Washington, DC area hospitalsRESULTS:
As shift lengths increased, effectiveness scores decreased and the time spent below criterion increased. Additionally, 11.13% of time on shift was below the effectiveness criterion and 42.7% of shifts carried excess sleep debt. Sleep prediction was similar to actual sleep, and both predicted similar performance (p ≤ 0.001).CONCLUSIONS:
Surgical resident sleep and shift patterns may create fatigue risk. Biomathematical modeling can aid the prediction of resident sleep patterns and performance. This approach provides an important tool to help educators in creating work-schedules that minimize fatigue risk.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Cirugía General
/
Internado y Residencia
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
J Surg Educ
Año:
2021
Tipo del documento:
Article