AI Article Synopsis

  • Hospitals struggle to meet the recommended time for percutaneous coronary intervention (PCI) in ST elevation myocardial infarction (STEMI) cases due to delays in staff recall caused by traffic and distance.
  • A study used Google Maps to estimate travel times for hospital staff at different times of day, revealing that traffic congestion significantly affects inner metropolitan hospitals while distance impacts outer ones.
  • The findings indicate that travel times increase during peak hours, with fewer staff arriving within the critical 30-minute window for STEMI treatment, highlighting the need for better planning and resource allocation for on-call staff.

Article Abstract

Background: 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.

Methods: 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.

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 13.4 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).

Conclusion: 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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766675PMC
http://dx.doi.org/10.3389/fcvm.2017.00089DOI Listing

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