Tajaddini Atousa, Phan Thanh G, Beare Richard, Ma Henry, Srikanth Velandai, Currie Graham, Vu Hai L
Department of Civil Engineering, Institute of Transport Studies, Monash University, Melbourne, VIC, Australia.
Stroke Unit, Monash Health, Melbourne, VIC, Australia.
Front Neurol. 2019 Jun 28;10:692. doi: 10.3389/fneur.2019.00692. eCollection 2019.
Two hubs are designated to provide endovascular clot retrieval (ECR) for the State of Victoria, Australia. In an earlier study, Google Maps application programming interface (API) was used to perform modeling on the combination of hospitals optimizing for catchment in terms of current traveling time and road conditions. It is not known if these findings would remain the same if the modeling was performed with a large-scale transport demand model such as Victorian Integrated Transport Model (VITM). This model is developed by the Victorian State Government Transport has the capability to forecast travel demand into the future including future road conditions which is not possible with a Google Maps based applications. The aim of this study is to compare the travel time to potential ECR hubs using both VITM and the Google Maps API and model stability in the next 5 and 10 years. The VITM was used to generate travel time from randomly generated addresses to four existing ECR capable hubs in Melbourne city, Australia (i.e., Royal Melbourne Hospital/RMH, Monash Medical Center/MMC, Alfred Hospital/ALF, and Austin Hospital/AUS) and the optimal service boundaries given a delivering time threshold are then determined. The strategic transport model and Google map methods were similar with the of 0.86 (peak and off peak) and the Nash-Sutcliffe model of efficiency being 0.83 (peak) and 0.76 (off-peak travel). Futures modeling using VITM found that this proportion decreases to 82% after 5 years and 80% after 10 years. The combination of RMH and ALF provides coverage for 74% of cases, 68% by 5 years, and 66% by 10 years. The combination of RMH and AUS provides coverage for 70% of cases in the base case, 65% at 5 years, and 63% by 10 years. The results from strategic transport model are similar to those from Google Maps. In this paper we illustrate how this method can be applied in designing and forecast stroke service model in different cities in Australia and around the world.
澳大利亚维多利亚州指定了两个中心提供血管内血栓清除术（ECR）。在早期的一项研究中，谷歌地图应用程序编程接口（API）被用于对医院组合进行建模，以根据当前出行时间和道路状况优化集水区。尚不清楚如果使用诸如维多利亚综合交通模型（VITM）这样的大规模交通需求模型进行建模，这些结果是否会保持不变。该模型由维多利亚州政府开发，交通部门有能力预测未来的出行需求，包括未来的道路状况，这是基于谷歌地图的应用程序无法做到的。本研究的目的是使用VITM和谷歌地图API比较前往潜在ECR中心的出行时间以及未来5年和10年的模型稳定性。VITM被用于生成从随机生成的地址到澳大利亚墨尔本市四个现有的具备ECR能力的中心（即皇家墨尔本医院/RMH、莫纳什医疗中心/MMC、阿尔弗雷德医院/ALF和奥斯汀医院/AUS）的出行时间，然后确定给定交付时间阈值下的最佳服务边界。战略交通模型和谷歌地图方法相似，皮尔逊相关系数为0.86（高峰和非高峰），纳什 - 萨特克利夫效率模型在高峰时为0.83，非高峰出行时为0.76。使用VITM进行的未来建模发现，这个比例在5年后降至82%，10年后降至80%。RMH和ALF的组合覆盖74%的病例，5年后为68%，10年后为66%。RMH和AUS的组合在基础情况下覆盖70%的病例，5年时为65%，10年后为63%。战略交通模型的结果与谷歌地图的结果相似。在本文中，我们说明了这种方法如何应用于澳大利亚和世界各地不同城市的中风服务模型设计和预测。
