Carr Brendan G, Walsh Lauren, Williams Justin C, Pryor John P, Branas Charles C
1Office of the Assistant Secretary for Preparedness and Response,US Department of Health and Human Services,Washington,DCUSA.
3GAP Solutions, Inc.; in support of the Office of the Assistant Secretary for Preparedness and Response,US Department of Health and Human Services;Herndon,VirginiaUSA.
Prehosp Disaster Med. 2016 Aug;31(4):413-21. doi: 10.1017/S1049023X16000510. Epub 2016 May 25.
Though the US civilian trauma care system plays a critical role in disaster response, there is currently no systems-based strategy that enables hospital emergency management and local and regional emergency planners to quantify, and potentially prepare for, surges in trauma care demand that accompany mass-casualty disasters.
A proof-of-concept model that estimates the geographic distributions of patients, trauma center resource usage, and mortality rates for varying disaster sizes, in and around the 25 largest US cities, is presented. The model was designed to be scalable, and its inputs can be modified depending on the planning assumptions of different locales and for different types of mass-casualty events.
To demonstrate the model's potential application to real-life planning scenarios, sample disaster responses for 25 major US cities were investigated using a hybrid of geographic information systems and dynamic simulation-optimization. In each city, a simulated, fast-onset disaster epicenter, such as might occur with a bombing, was located randomly within one mile of its population center. Patients then were assigned and transported, in simulation, via the new model to Level 1, 2, and 3 trauma centers, in and around each city, over a 48-hour period for disaster scenario sizes of 100, 500, 5000, and 10,000 casualties.
Across all 25 cities, total mean mortality rates ranged from 26.3% in the smallest disaster scenario to 41.9% in the largest. Out-of-hospital mortality rates increased (from 21.3% to 38.5%) while in-hospital mortality rates decreased (from 5.0% to 3.4%) as disaster scenario sizes increased. The mean number of trauma centers involved ranged from 3.0 in the smallest disaster scenario to 63.4 in the largest. Cities that were less geographically isolated with more concentrated trauma centers in their surrounding regions had lower total and out-of-hospital mortality rates. The nine US cities listed as being the most likely targets of terrorist attacks involved, on average, more trauma centers and had lower mortality rates compared with the remaining 16 cities.
The disaster response simulation model discussed here may offer insights to emergency planners and health systems in more realistically planning for mass-casualty events. Longer wait and transport times needed to distribute high numbers of patients to distant trauma centers in fast-onset disasters may create predictable increases in mortality and trauma center resource consumption. The results of the modeled scenarios indicate the need for a systems-based approach to trauma care management during disasters, since the local trauma center network was often too small to provide adequate care for the projected patient surge. Simulation of out-of-hospital resources that might be called upon during disasters, as well as guidance in the appropriate execution of mutual aid agreements and prevention of over-response, could be of value to preparedness planners and emergency response leaders. Study assumptions and limitations are discussed. Carr BG , Walsh L , Williams JC , Pryor JP , Branas CC . A geographic simulation model for the treatment of trauma patients in disasters. Prehosp Disaster Med. 2016;31(4):413-421.
尽管美国民用创伤护理系统在灾难应对中发挥着关键作用,但目前尚无基于系统的策略,使医院应急管理部门以及地方和区域应急规划人员能够量化并可能为大规模伤亡灾难伴随的创伤护理需求激增做好准备。
提出一个概念验证模型,该模型可估算美国25个最大城市及其周边地区不同规模灾难下患者的地理分布、创伤中心资源使用情况和死亡率。该模型设计为可扩展的,其输入可根据不同地区的规划假设以及不同类型的大规模伤亡事件进行修改。
为证明该模型在实际规划场景中的潜在应用,使用地理信息系统和动态模拟优化相结合的方法,对美国25个主要城市的样本灾难应对情况进行了调查。在每个城市中,模拟一个快速发生的灾难震中,例如可能由爆炸引发的震中,随机位于其人口中心一英里范围内。然后,在模拟中,通过新模型将患者在48小时内分配并转运至每个城市及其周边地区的一级、二级和三级创伤中心,灾难场景规模分别为100、500、5000和10000名伤亡人员。
在所有25个城市中,总平均死亡率从最小灾难场景下的26.3%到最大灾难场景下的41.9%不等。随着灾难场景规模的增加,院外死亡率上升(从21.3%升至38.5%),而院内死亡率下降(从5.0%降至3.4%)。涉及的创伤中心平均数量从最小灾难场景下的3.0个到最大灾难场景下的63.4个不等。地理上不太孤立且周边地区创伤中心更集中的城市,其总死亡率和院外死亡率较低。与其余16个城市相比,被列为最有可能遭受恐怖袭击目标的9个美国城市平均涉及更多的创伤中心且死亡率较低。
本文讨论的灾难应对模拟模型可能为应急规划人员和卫生系统在更现实地规划大规模伤亡事件方面提供见解。在快速发生的灾难中,将大量患者分配到遥远创伤中心所需的更长等待和运输时间可能导致死亡率和创伤中心资源消耗出现可预测的增加。模拟场景的结果表明,在灾难期间需要一种基于系统的创伤护理管理方法,因为当地创伤中心网络往往太小,无法为预计的患者激增提供足够的护理。模拟灾难期间可能调用的院外资源,以及在适当执行互助协议和防止过度反应方面提供指导,可能对备灾规划人员和应急响应领导人有价值。讨论了研究假设和局限性。卡尔·B·G、沃尔什·L、威廉姆斯·J·C、普赖尔·J·P、布拉纳斯·C·C。一种用于灾难中创伤患者治疗的地理模拟模型。《院前灾难医学》。2016;31(4):413 - 421。