ABSTRACTBACKGROUNDThe 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.METHODSWe used the Pennsylvania Trauma Systems Foundation (PTSF) and Pennsylvania Health Care Cost Containment Council (PHC4) registries for adult (age ≥15) trauma between 2003-2015 (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 prior 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.RESULTSAt 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.CONCLUSIONSThe 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 EVIDENCELevel III epidemiological study 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 2003-2015 (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 prior 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 Level III epidemiological study Conflicts of Interest and Source of Funding: The authors report no proprietary or commercial interest in any product mentioned or concept discussed in this article. This study was funded in part by a grant from the Louise von Hess Medical Research Institute. This study was presented at the 76th Annual Meeting of the American Association for the Surgery of Trauma and Clinical Congress of Acute Care Surgery from September 13-16, 2017 in Baltimore, Maryland. Corresponding Author: Frederick B. Rogers, MD, MS, FACS; frogers2@lghealth.org 1, 555 N. Duke St., Lancaster, PA 17602, 717-544-5945 (tel), 717-544-5944 (fax) © 2017 Lippincott Williams & Wilkins, Inc.
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