Geographic distribution of trauma centers and injury-related mortality in the United States

Abstract

Background Regionalized trauma care improves outcomes; however access to care is not uniform across the US. The objective was to evaluate whether geographic distribution of trauma centers correlates with injury mortality across state trauma systems. Methods Level I/II trauma centers in the contiguous US were mapped. State-level age-adjusted injury fatality rates/100,000people were obtained and evaluated for spatial autocorrelation. Nearest neighbor ratios (NNR) were generated for each state. A NNR<1 indicates clustering, while NNR>1 indicates dispersion. NNR were tested for difference from random geographic distribution. Fatality rates and NNR were examined for correlation. Fatality rates were compared between states with trauma center clustering versus dispersion. Trauma center distribution and population density were evaluated. Spatial-lag regression determined the association between fatality rate and NNR, controlling for state-level demographics, population density, injury severity, trauma system resources, and socioeconomic factors. Results Fatality rates were spatially autocorrelated (Moran's I=0.35, p<0.01). Nine states had a clustered pattern (median NNR 0.55, IQR 0.48–0.60), 22 had a dispersed pattern (median NNR 2.00, IQR 1.68–3.99), and 10 had a random pattern (median NNR 0.90, IQR 0.85–1.00) of trauma center distribution. Fatality rate and NNR were correlated (ρ=0.34, p=0.03). Clustered states had a lower median injury fatality rate compared to dispersed states (56.9 [IQR 46.5–58.9] versus 64.9 [IQR 52.5–77.1], p=0.04). Dispersed compared to clustered states had more counties without a trauma center that had higher population density than counties with a trauma center (5.7% versus 1.2%, p<0.01). Spatial-lag regression demonstrated fatality rates increased 0.02/100,000persons for each unit increase in NNR (p<0.01). Conclusions Geographic distribution of trauma centers correlates with injury mortality, with more clustered state trauma centers associated with lower fatality rates. This may be a result of access relative to population density. These results may have implications for trauma system planning and requires further study to investigate underlying mechanisms

A Comparison of Pediatric Traumatic Injuries on Farms and Residences from 2009 to 2014

“…Only children presenting to Level I and Level II ACS‐verified trauma centers are included in the study; therefore, results may not be generalizable to patients presenting to other emergency settings . This may result in an underrepresentation of children with farm injuries who presented to their closest emergency department for medical attention, but did not require transfer to a trauma center . The NTDB is not nationally representative of all trauma centers; however, it currently includes over 95% of all US‐certified Level I and II trauma centers .…”

“…7,26 This may result in an underrepresentation of children with farm injuries who presented to their closest emergency department for medical attention, but did not require transfer to a trauma center. 27 The NTDB is not nationally representative of all trauma centers; however, it currently includes over 95% of all US-certified Level I and II trauma centers. 23,26 Administrative data collected within the NTDB is subject to coding inaccuracies and misreport through physician documentation and trauma registrar collection of data.…”

Distance matters

“…11 Motor vehicle collisions (MVC) have been shown to be particularly influenced by geographical factors, as several have shown that mortality from MVC is influenced by geographic region, population density, and vehicle miles traveled. 12–15 Further, MVC events are dispersed throughout a trauma system and have a wide range of injury severity that mobilizes the full range of prehospital and trauma center resources.…”

Linked data systems for injury surveillance and targeted prevention planning: Identifying geographical differences in injury in Western Australia, 2009‐2012

“…The area based patterns may reflect the social ecology of these communities which also influences the choice and ability to undertake or maintain appropriate interventions and policies . Reflecting on the geographical contiguity of injury can influence where resources are targeted, highlight where variations in exposures exist with distinct socioeconomic characteristics and provide useful data for comparisons into the effectiveness of current prevention programs . By framing this evidence within a geographical context, we can start a conversation and raise awareness of local injury status in regional public health units and with other local stakeholders.…”