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Staff Recall Travel Time for ST Elevation Myocardial Infarction Impacted by Traffic Congestion and Distance: A Digitally Integrated Map Software Study

Overview of attention for article published in Frontiers in Cardiovascular Medicine, January 2018
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Title
Staff Recall Travel Time for ST Elevation Myocardial Infarction Impacted by Traffic Congestion and Distance: A Digitally Integrated Map Software Study
Published in
Frontiers in Cardiovascular Medicine, January 2018
DOI 10.3389/fcvm.2017.00089
Pubmed ID
Authors

Justin Cole, Richard Beare, Thanh G. Phan, Velandai Srikanth, Andrew MacIsaac, Christianne Tan, David Tong, Susan Yee, Jesslyn Ho, Jamie Layland

Abstract

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. (p < 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 (p < 0.001). Only 45% of inner metropolitan staff were predicted to arrive within 30 min at 6 p.m. compared with 100% at midnight (p < 0.001), and 56% of outer metropolitan staff at 6 p.m. (p = 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.

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Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 100%
Readers by discipline Count As %
Nursing and Health Professions 1 50%
Engineering 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 January 2018.
All research outputs
#20,714,793
of 23,314,015 outputs
Outputs from Frontiers in Cardiovascular Medicine
#4,470
of 7,218 outputs
Outputs of similar age
#380,291
of 443,821 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#27
of 27 outputs
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