James Francine O, Waggoner Lauren B, Weiss Patricia M, Patterson P Daniel, Higgins J Stephen, Lang Eddy S, Van Dongen Hans P A
Prehosp Emerg Care. 2018 Feb 15;22(sup1):69-80. doi: 10.1080/10903127.2017.1384875. Epub 2018 Jan 11.
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.
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.
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.
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.
像紧急医疗服务(EMS)人员的工作时间表与疲劳相关损伤风险增加有关。生物数学建模是一种客观估计疲劳对工作表现潜在影响的方法,可用于减轻与疲劳相关的安全风险。在EMS运营背景下,我们的目标是评估文献中关于使用生物数学模型帮助减轻疲劳和与疲劳相关风险有效性的证据。
对评估使用生物数学模型管理EMS人员或类似轮班工人疲劳情况的证据进行了系统综述。采用推荐分级、评估、制定与评价(GRADE)方法提出的程序来总结和评定证据的确定性。使用Cochrane协作网的实验性研究偏倚风险工具记录纳入研究的潜在偏倚。
聚焦于EMS人员和非EMS轮班工人的文献检索策略共得到n = 2777条独特记录。一篇调查非EMS轮班工人的论文符合纳入标准。作为一项更大规模工作的一部分,为一家货运企业的经理和调度员提供了驾驶员群体预测疲劳的月度生物数学模型分析,并就如何通过调整时间表降低预测疲劳对他们进行了培训。在使用生物数学建模期间,干预措施使车辆事故的数量和成本显著降低。由于存在偏倚风险、间接性、不精确性和发表偏倚,证据质量的总体GRADE评估非常低。
本系统综述未发现研究生物数学模型在EMS运营中影响的研究。一项针对非EMS轮班工人的研究结果表明,使用生物数学模型作为减轻疲劳的排班辅助工具是有益的,尽管与EMS运营相关的证据质量非常低。我们提出了三个研究重点领域,如果加以解决,可能有助于更好地阐明生物数学模型作为EMS环境中减轻疲劳工具的效用和影响。