Response, Agency, and Patient Characteristics Associated With EMS Transport Rates

The EMS 9-1-1 transport rate has important implications for current reimbursement practices and risks of negative outcomes related to nontransport. Little research exists regarding factors linked to EMS transport rate for 9-1-1 response.

Objective—To identify response, agency, and patient characteristics associated with EMS transport rates.

Methods—A retrospective analysis used all 9-1-1 responses with patient contact in 2017 in the ESO Solutions national database. Agencies without transport capability were excluded. Independent variables of interest were identified a priori: agency type, agency volunteer status, time of day, day of week, patient sex, patient race/ethnicity, and patient age. Multivariable logistic regression modeling was used to assess for an association between the independent variables and EMS transport. Adjusted odds ratios and 95% confidence intervals are reported.

Results—We analyzed 2,786,615 records; 85% resulted in EMS transports by more than 900 agencies. Compared to third-service agencies, private agencies demonstrated 80% greater odds of transporting (aOR 1.80; 95% CI, 1.78–1.84). Compared to nonvolunteer agencies, volunteer agencies had 31% increased odds of transport (aOR 1.31; 95% CI, 1.26–1.36). Hispanic patients had 26% decreased odds of transport compared to non-Hispanic white patients (aOR 0.74; 95% CI: 0.73–0.75). Compared to patients aged 18–39, older patients had progressively greater odds of transport with each age group, the largest aOR being 2.62 (95% CI, 2.59–2.65) for those older than 79 years. Patients younger than 18 years had lower odds of transport (aOR 0.74; 95% CI, 0.73–0.75). Compared to calls occurring between 7 a.m. and 3 p.m., odds of transport were lower between 3 p.m. and 11 p.m. (aOR 0.83; 95% CI, 0.83–0.85) and between 11 p.m. and 7 a.m. (aOR 0.88; 95% CI, 0.87–0.88). Smaller differences in transport rates, likely not clinically significant, were seen for sex, day of week, and fire-based agencies.

Conclusion—This analysis encompassing a broad range of EMS systems in various practice settings identified differences in transport rates by agency characteristics, time of day, patient race/ethnicity, and age. Further work is needed to elucidate the underlying causes of these differences for each variable. Limitations include information bias due to documentation practices and potential selection bias from analyzing a single PCR provider.