Cole Justin, Beare Richard, Phan Thanh G, Srikanth Velandai, MacIsaac Andrew, Tan Christianne, Tong David, Yee Susan, Ho Jesslyn, Layland Jamie
Peninsula Health Heart Service, Frankston, VIC, Australia.
Peninsula Clinical School, Monash University, Melbourne, VIC, Australia.
Front Cardiovasc Med. 2018 Jan 8;4:89. doi: 10.3389/fcvm.2017.00089. eCollection 2017.
Recent evidence suggests hospitals fail to meet guideline specified time to percutaneous coronary intervention (PCI) for a proportion of ST elevation myocardial infarction (STEMI) presentations. Implicit in achieving this time is the rapid assembly of crucial catheter laboratory staff. As a proof-of-concept, we set out to create regional maps that graphically show the impact of traffic congestion and distance to destination on staff recall travel times for STEMI, thereby producing a resource that could be used by staff to improve reperfusion time for STEMI.
Travel times for staff recalled to one inner and one outer metropolitan hospital at midnight, 6 p.m., and 7 a.m. were estimated using Google Maps Application Programming Interface. Computer modeling predictions were overlaid on metropolitan maps showing color coded staff recall travel times for STEMI, occurring within non-peak and peak hour traffic congestion times.
Inner metropolitan hospital staff recall travel times were more affected by traffic congestion compared with outer metropolitan times, and the latter was more affected by distance. The estimated mean travel times to hospital during peak hour were greater than midnight travel times by 13.4 min to the inner and 6.0 min to the outer metropolitan hospital at 6 p.m. ( < 0.001). At 7 a.m., the mean difference was 9.5 min to the inner and 3.6 min to the outer metropolitan hospital ( < 0.001). Only 45% of inner metropolitan staff were predicted to arrive within 30 min at 6 p.m. compared with 100% at midnight ( < 0.001), and 56% of outer metropolitan staff at 6 p.m. ( = 0.021).
Our results show that integration of map software with traffic congestion data, distance to destination and travel time can predict optimal residence of staff when on-call for PCI.
近期证据表明，对于一部分ST段抬高型心肌梗死（STEMI）患者，医院未能达到指南规定的经皮冠状动脉介入治疗（PCI）时间。实现这一治疗时间的一个隐含要求是关键导管室工作人员迅速集合。作为概念验证，我们着手创建区域地图，以图形方式展示交通拥堵和距离目的地的远近对STEMI患者工作人员召回出行时间的影响，从而生成一种工作人员可用于改善STEMI再灌注时间的资源。
使用谷歌地图应用程序编程接口估计午夜、下午6点和早上7点被召回至一家市中心医院和一家市外医院的工作人员的出行时间。计算机建模预测结果被叠加在大城市地图上，地图显示了在非高峰和高峰时段交通拥堵情况下STEMI患者工作人员召回出行时间的颜色编码。
与市外医院相比，市中心医院工作人员召回出行时间受交通拥堵的影响更大，而市外医院工作人员召回出行时间受距离的影响更大。下午6点高峰时段前往医院的估计平均出行时间比午夜出行时间分别增加了13.4分钟（市中心医院）和6.0分钟（市外医院）（<0.001）。早上7点时，前往市中心医院的平均差值为9.5分钟，前往市外医院的平均差值为3.6分钟（<0.001）。预计下午6点时，市中心医院只有45%的工作人员能在30分钟内到达，而午夜时这一比例为100%（<0.001），市外医院下午6点时有56%的工作人员能在30分钟内到达（P=0.021）。
我们的结果表明，将地图软件与交通拥堵数据、距离目的地的远近和出行时间相结合，可以预测PCI值班时工作人员的最佳居住地点。
