Development of a geospatial approach for the quantitative analysis of trauma center access.
Academic Article
Overview
abstract
INTRODUCTION: Decisions around trauma center (TC) designation have become contentious in many areas. There is no consensus regarding the ideal number and location of TC and no accepted metrics to assess the effect of changes in system structure. We aimed to develop metrics of TC access, using publicly available data and analytic tools. We hypothesize that geospatial analysis can provide a reproducible approach to quantitatively asses potential changes in trauma system structure. METHODS: A region in New York State was chosen for evaluation. Geospatial data and analytic tools in ArcGIS Online were used. Transport time polygons were created around TC, and the population covered was estimated by summing the census tracts within these polygons. Transport time from each census tract to the nearest TC was calculated. The baseline model includes the single designated TC. Model 1 includes one additional TC, and Model 2 includes two additional TC, chosen to maximize coverage. The population covered, population-weighted distribution of transport times, and population covered by a specific TC were calculated for each model. RESULTS: The baseline model covered 1.12 × 10 people. The median transport time was 19.2 minutes. In Model 1, the population covered increased by 14.4%, while the population catchment, and thus the estimated trauma volume, of the existing TC decreased by 12%. Median transport time to the nearest TC increased to 20.4 minutes. Model 2 increased coverage by 18% above baseline, while the catchment, and thus the estimated trauma volume, of the existing TC decreased by 22%. Median transport time to the nearest TC decreased to 19.6 minutes. CONCLUSIONS: Geospatial analysis can provide objective measures of population access to trauma care. The analysis can be performed using different numbers and locations of TC, allowing direct comparison of changes in coverage and impact on existing centers. This type of data is essential for guiding difficult decisions regarding trauma system design. LEVEL OF EVIDENCE: Care management, level IV.
