Development of a trauma system and optimal placement of trauma centers using geospatial mapping.

J Trauma Acute Care Surg

From the Trauma Services (M.A.H., S.J., B.W.G., E.H.B., M.M., D.V.N., F.B.R.), Penn Medicine Lancaster General Health, Lancaster, PA; Trauma Research Program (A.D.C.), Chandler Regional Medical Center, Chandler, AZ; and Pennsylvania Trauma Systems Foundation (J.A.), Camp Hill, PA.

Published: March 2018

AI Article Synopsis

  • The study aimed to find the best locations for trauma centers in Pennsylvania by using geospatial mapping, improving on the current system which has already optimized patient care at individual centers.
  • Researchers analyzed data on adult trauma cases from 2003 to 2015, considering factors like travel times and the capacity of trauma centers, using a modeling tool in ArcGIS.
  • The findings showed that optimally placing trauma centers could significantly improve coverage of trauma cases across the state; the ideal number of centers was estimated to be 22 for one data set and 16 for another, highlighting a need for changes in the existing trauma system.

Article Abstract

Background: The care of patients at individual trauma centers (TCs) has been carefully optimized, but not the placement of TCs within the trauma systems. We sought to objectively determine the optimal placement of trauma centers in Pennsylvania using geospatial mapping.

Methods: We used the Pennsylvania Trauma Systems Foundation (PTSF) and Pennsylvania Health Care Cost Containment Council (PHC4) registries for adult (age ≥15) trauma between 2003 and 2015 (n = 377,540 and n = 255,263). TCs and zip codes outside of PA were included to account for edge effects with trauma cases aggregated to the Zip Code Tabulation Area centroid of residence. Model assumptions included no previous TCs (clean slate); travel time intervals of 45, 60, 90, and 120 minutes; TC capacity based on trauma cases per bed size; and candidate hospitals ≥200 beds. We used Network Analyst Location-Allocation function in ArcGIS Desktop to generate models optimally placing 1 to 27 TCs (27 current PA TCs) and assessed model outcomes.

Results: At a travel time of 60 minutes and 27 sites, optimally placed models for PTSF and PHC4 covered 95.6% and 96.8% of trauma cases in comparison with the existing network reaching 92.3% or 90.6% of trauma cases based on PTSF or PHC4 inclusion. When controlled for existing coverage, the optimal numbers of TCs for PTSF and PHC4 were determined to be 22 and 16, respectively.

Conclusions: The clean slate model clearly demonstrates that the optimal trauma system for the state of Pennsylvania differs significantly from the existing system. Geospatial mapping should be considered as a tool for informed decision-making when organizing a statewide trauma system.

Level Of Evidence: Epidemiological study/Care management, level III.

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Source
http://dx.doi.org/10.1097/TA.0000000000001782DOI Listing

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