Staff Recall Travel Time for ST Elevation Myocardial Infarction Impacted by Traffic Congestion and Distance: A Digitally Integrated Map Software Study - Cole, Justin; Beare, Richard; Phan, Thanh G.; Srikanth, Velandai; MacIsaac, Andrew; Tan, Christianne; Tong, David; Yee, Susan; Ho, Jesslyn; Layland, Jamie (Frontiers in Cardiovascular Medicine, 2018)
Background Recent evidence suggests hospitals fail to meet guideline specified time to Percutaneous Coronary Intervention for a proportion of ST elevation myocardial infarction 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. Methods Travel times for staff recalled to one inner and one outer metropolitan hospital at midnight, 6pm and 7am were estimated using Google Maps Application Programming Interface. Computer modelling predictions were overlaid on metropolitan maps showing colour coded staff recall travel times for STEMI, occurring within non-peak and peak hour traffic congestion times. Results 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 13.4minutes to the inner and 6.0minutes to the outer metropolitan hospital at 6pm (p<0.001). At 7am, the mean difference was 9.5minutes to the inner and 3.6minutes to the outer metropolitan hospital (p<0.001). Only 45% of inner metropolitan staff were predicted to arrive within 30minutes at 6pm compared with 100% at midnight (p<0.001), and 56% of outer metropolitan staff at 6pm (p=0.021). Conclusions 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.