Quantification of Trauma Center Access Using Geographical Information System-Based Technology. Academic Article uri icon

Overview

abstract

  • OBJECTIVES: There is no generally accepted methodology to assess trauma system access. The goal of this study is to determine the influence of the number and geographical distribution of trauma centers (TCs) on transport times (TT) using geographic information system (GIS)-technology. METHODS: Using ArcGIS-PRO, we calculated differences in TT and population coverage in 7 scenarios with 1, 2, or 3 TCs during rush (R) and low-traffic (L) hours in a densely populated region with 3 TCs in the Netherlands. RESULTS: In all 7 scenarios, the population that could reach the nearest TC within <45 minutes varied between 96% and 99%. In the 3-TC scenario, roughly 57% of the population could reach the nearest TC <15 minutes both during R and L. The hypothetical geographically well-spread 2-TC scenario showed similar results as the 3-TC scenario. In the 1-TC scenarios, the population reaching the nearest TC <15 minutes decreased to between 19% and 32% in R and L. In the 3-TC scenario, the average TT increased by about 1.5 minutes to almost 21 minutes during R and 19 minutes during L. Similar results were seen in the scenarios with 2 geographically well-spread TCs. In the 1-TC scenarios and the less well-spread 2-TC scenario, the average TT increased by 5 to 8 minutes (L) and 7 to 9 minutes (R) compared to the 3-TC scenario. CONCLUSIONS: This study shows that a GIS-based model offers a quantifiable and objective method to evaluate trauma system access under different potential trauma system configurations. Transport time from accident to TC would remain acceptable, around 20 minutes, if the current 3-TC situation would be changed to a geographically well-spread 2-center scenario.

publication date

  • July 4, 2020

Research

keywords

  • Ambulances
  • Geographic Information Systems
  • Health Services Accessibility
  • Trauma Centers

Identity

Scopus Document Identifier

  • 85087414350

Digital Object Identifier (DOI)

  • 10.1016/j.jval.2020.05.005

PubMed ID

  • 32828213

Additional Document Info

volume

  • 23

issue

  • 8