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Biomathematical Modeling Predicts Fatigue Risk in General Surgery Residents.

MedStar author(s):

Citation: Journal of Surgical Education. 2021 May 13PMID: 33994335Institution: MedStar Institute for Innovation | MedStar Washington Hospital CenterDepartment: Emergency MedicineForm of publication: Journal ArticleMedline article type(s): Journal ArticleSubject headings: IN PROCESS -- NOT YET INDEXEDYear: 2021 ISSN:

1878-7452

Name of journal: Journal of surgical educationAbstract: 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. Copyright (c) 2021 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.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").OBJECTIVE: To assess resident fatigue risk using objective and predicted sleep data in a biomathematical model of fatigue.SETTING: Greater Washington, DC area hospitals RESULTS: 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).All authors: Boyle L, Davis JE, Devine JK, Fitzgibbons SC, Hursh SR, Mosher E, Schumacher S, Schwartz LP, Smith MFiscal year: FY2021 Digital Object Identifier:

https://dx.doi.org/10.1016/j.jsurg.2021.04.007

Date added to catalog: 2021-06-28

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Title notes ( 5 )

Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Journal Article	MedStar Authors Catalog	Article	33994335	Available		33994335

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. Copyright (c) 2021 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

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").

OBJECTIVE: To assess resident fatigue risk using objective and predicted sleep data in a biomathematical model of fatigue.

SETTING: Greater Washington, DC area hospitals RESULTS: 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).

English