Does Implementation of Biomathematical Models Mitigate Fatigue and Fatigue-Related Risks in Emergency Medical Services Operations? A Systematic Review

NHTSA - Behavioral Safety Researchhttps://doi.org/10.1080/10903127.2017.13848752018PDFJournal ArticleJames, Francine O.Waggoner, Lauren B.Weiss, Patricia M.Patterson, P. DanielHiggins, J. StephenLang, EddyVan Dongen, Hans P.A.University of Pittsburgh. Department of Emergency MedicineUnited States. National Highway Traffic Safety AdministrationTaylor & FrancisUnited StatesEmergency medical servicesFatigue (Physiological condition)SafetyFatigue risk managementBiomathematical models of fatigue and performanceShift workPublished in Prehospital Emergency Care, Volume 22, 2018 - Issue sup1: NHTSA Fatigue in EMS projectBackground: Work schedules like those of Emergency Medical Services (EMS) personnel have been associated with increased risk of fatigue-related impairment. Biomathematical modeling is a means of objectively estimating the potential impacts of fatigue on performance, which may be used in the mitigation of fatigue-related safety risks. In the context of EMS operations, our objective was to assess the evidence in the literature regarding the effectiveness of using biomathematical models to help mitigate fatigue and fatigue-related risks. Methods: A systematic review of the evidence evaluating the use of biomathematical models to manage fatigue in EMS personnel or similar shift workers was performed. Procedures proposed by the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology were used to summarize and rate the certainty in the evidence. Potential bias attached to retained studies was documented using the Cochrane Collaboration's Risk of Bias tool for experimental studies. Results: The literature search strategy, which focused on both EMS personnel and non-EMS shift workers, yielded n = 2,777 unique records. One paper, which investigated non-EMS shift workers, met inclusion criteria. As part of a larger effort, managers and dispatchers of a trucking operation were provided with monthly biomathematical model analyses of predicted fatigue in the driver workforce, and educated on how they could reduce predicted fatigue by means of schedule adjustments. The intervention showed a significant reduction in the number and cost of vehicular accidents during the period in which biomathematical modeling was used. The overall GRADE assessment of evidence quality was very low due to risk of bias, indirectness, imprecision, and publication bias. Conclusions: This systematic review identified no studies that investigated the impact of biomathematical models in EMS operations. Findings from one study of non-EMS shift workers were favorable toward use of biomathematical models as a fatigue mitigation scheduling aid, albeit with very low quality of evidence pertaining to EMS operations. We propose three focus areas of research priorities that, if addressed, could help better elucidate the utility and impact of biomathematical models as a fatigue-mitigation tool in the EMS environment. Supplemental data for this article can be accessed via https://doi.org/10.6084/m9.figshare.5778192.v1129