For a study, researchers sought to outline the EMS response times for suspected stroke patients in North Carolina (NC) and assess how the  socioeconomic status (SES) of the community and rurality affected the EMS response times.

Data on EMS contacts with suspected stroke in NC from the whole state were utilized for the cross-sectional research in 2019. Adults who required EMS transfer to a hospital as a result of a 9-1-1 call for stroke-like symptoms qualified as eligible patients. Street addresses for incidents were geocoded to census tracts, connected to SES data from the American Community Survey, and assigned RUCA (rural-urban commuting area) codes. Community SES was classified as high, medium, or low based on the tertiles of an SES index. RUCA codes 1, 2–6, and 7–10, respe identify urban, suburban, and rural areas. To determine how the median and 90th percentile of EMS time intervals changed by community SES and rurality, controlling for each other; patient age, gender, race/ethnicity; and incident characteristics, multivariable quantile regression was utilized.

From 2028 census tracts, they found 17,117 qualified EMS contacts with suspected strokes. The median age of the population was 65+ years old, and 69% of people were non-Hispanic white. Interquartile range (IQR) values for the median response, scene, and transit durations were 8 (IQR 6-11), 16 (IQR 12-20), and 14 (IQR 9-22), respectively. The median response and scene times by community SES and rurality showed modest variations in quantile regression adjusted for patient demographics. When comparing rural (4.7 min, 95% CI 4.2, 5.1) and suburban tracts (6.7 min, 95% CI 5.8, 7.6) to urban tracts, the highest median differences were seen for transit times. Transport times for the 90th percentile were significantly different between rural and urban areas when adjusted (16.0 min, 95% CI 14.5, 17.5). In comparison to high SES tracts, low SES tracts had modestly shorter median (-3.3 min, 95% CI -3.8, -2.9) & 90th percentile (-3.0 min, 95% CI -4.0, -2.0) travel times.

EMS response and scene times for stroke were not highly influenced by community-level characteristics, but transport times were noticeably longer in rural areas and somewhat shorter in low SES areas once patient demographics were taken into consideration. Further study was required to determine the contribution of rurality and socioeconomic hardship on delays in prehospital stroke treatment.