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Database Integration Correlates Street Crossing Design Strategies With Pedestrian Injury. | LitMetric

Introduction: Transportation databases have limited data regarding injury severity of pedestrian versus automobile patients. To identify opportunities to reduce injury severity, transportation and trauma databases were integrated to examine the differences in pedestrian injury severity at street crossings that were signalized crossings (SCs) versus nonsignalized crossings (NSCs). It was hypothesized that trauma database integration would enhance safety analysis and pedestrians struck at NSC would have greater injury severity.

Methods: Single-center retrospective review of all pedestrian versus automobile patients treated at a level 1 trauma center from 2014 to 2018 was performed. Patients were matched to the transportation database by name, gender, and crash date. Google Earth Pro satellite imagery was used to identify SC versus NSC. Injury severity of pedestrians struck at SC was compared to NSC.

Results: A total of 512 patients were matched (median age = 41 y [Q1 = 26, Q3 = 55], 74% male). Pedestrians struck at SC (n = 206) had a lower injury severity score (ISS) (median = 9 [4, 14] versus 17 [9, 26], P < 0.001), hospital length of stay (median = 3 [0, 7] versus 6 [1, 15] days, P < 0.001), and mortality (21 [10%] versus 52 [17%], P = 0.04), as compared to those struck at NSC (n = 306). The transportation database had a sensitivity of 63.4% (55.8%-70.4%) and specificity of 63.4% (57.7%-68.9%) for classifying severe injuries (ISS >15).

Conclusions: Pedestrians struck at SC were correlated with a lower ISS and mortality compared to those at NSC. Linkage with the trauma database could increase the transportation database's accuracy of injury severity assessment for nonfatal injuries. Database integration can be used for evidence-based action plans to reduce pedestrian morbidity, such as increasing the number of SC.

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http://dx.doi.org/10.1016/j.jss.2024.01.005DOI Listing

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