Introduction: EMS typically transports patients to the closest ED. However, pediatric care is increasingly regionalized, limiting service availability at local community hospitals. Our previous research found that nearly 50% of pediatric EMS transports bypass the nearest facility, with little variation between urban, suburban, and rural settings. The purpose of this study was to examine whether there was geographic and socioeconomic variation in transport bypass. Methods: We performed a one-year retrospective study of children aged 18 years and younger transported by ground to hospitals by a single, urban, EMS agency that serves a region with approximately 120,000 children. The agency’s jurisdiction contains 10 acute care hospital-based EDs, including a level I pediatric trauma center. EMS scene and hospital destination (actual and nearest) locations were abstracted from the EMS patient care record and geocoded. EMS travel route was calculated using the Google Matrix Distance application. Bypass was defined as a transport with a difference in route length greater than 2 km between the actual destination and nearest identified facility. For each of the 200 census tracts (CT) in the study region, we determined the standardized bypass ratios (SBR), taken as the number of observed to expected bypasses based on the total number of transports, and estimated the probability of a CT SBR exceeding 2.0. Negative binomial and logistic regression were used to evaluate the association of CT poverty level and median income with bypass risk at both the CT and individual levels, respectively. Results: Over the study period there were 6,003 pediatric transports by the EMS agency, of which 32% bypassed the nearest facility. Figure 1 displays the probability for a twofold greater than expected rate of bypass for each CT. An increase in quartile of CT poverty level was associated with a lower bypass rate (IRR: 0.34; 95% CI 0.23, 0.51). Correspondingly, an increase in median CT income quartile was associated with a higher bypass rate (IRR: 2.68; 95% CI: 1.60, 4.50). The estimated bypass risk over CT median income is presented in Figure 2. Similar results were produced from individual-level analyses. Conclusions: This study found significant variation in rates of prehospital pediatric patients bypassing the nearest facility amongst CTs and indicate geographic clustering of bypasses for this population. The complementary directionality of findings for both CT poverty level and CT median income suggest differential resource allocation of EMS and pediatric regional resources within the same EMS region. Future studies are needed to examine the reasons for high concentrations of bypass, particularly in higher socioeconomic CTs, and outcomes associated with pediatric bypass.

Figure 1

Bypass Clusters where Probability that SBR exceeds 2.0

Figure 1

Bypass Clusters where Probability that SBR exceeds 2.0

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Predicted Incidence Rate for Bypass by Median Income

Predicted Incidence Rate for Bypass by Median Income

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