The characteristics of dockless electric rental scooter-related injuries in a large U.S. city

Traffic Inj Prev. 2020;21(7):476-481. doi: 10.1080/15389588.2020.1804059. Epub 2020 Aug 12.

Abstract

Objective: To describe the characteristics of dockless electric rental scooter ("e-scooter")-related injuries presenting to two emergency departments in one large U.S. city.

Methods: This observational cohort study utilized the city's public health syndromic surveillance system to prospectively identify patients with e-scooter-related injuries presenting between September and November 2018. The medical records for all adult patients treated at the two participating emergency departments were manually reviewed to extract demographic and clinical data. Cases involving mobility scooters or non-electric scooters were excluded.

Results: For the 124 included adult patients with e-scooter-related injuries, the median age was 30 years (IQR: 22-43), they were predominantly male (59.7%), and approximately half (51.6%) arrived by ambulance. Falling from the scooter (84.7%) was the most common mechanism; twelve patients (9.7%) had collided with a motor vehicle. Head and face injuries (45.5%) were common; only 2 patients (1.6%) were documented as wearing a helmet at the time of injury. Most patients (n = 112, 90.3%) required imaging, more than half (n = 78, 62.9%) required an emergency department procedure, and 26 (21.0%) required surgical intervention. Most patients were discharged home, but 35 (28.2%) were admitted to hospital. Two patients (1.6%) were admitted to the intensive care unit.

Conclusions: E-scooters are an emerging transportation technology associated with a wide range of potentially serious injuries that consume substantial emergency department and hospital resources. Head injuries are a particular concern, as few e-scooter riders are wearing helmets at the time of injury.

Keywords: Scooter; e-scooter; injury; motorized scooter; public health.

Publication types

  • Observational Study

MeSH terms

  • Accidents, Traffic / statistics & numerical data*
  • Adult
  • Cities / epidemiology
  • Cohort Studies
  • Emergency Service, Hospital / statistics & numerical data
  • Female
  • Humans
  • Male
  • Motorcycles / statistics & numerical data*
  • United States / epidemiology
  • Wounds and Injuries / epidemiology*
  • Wounds and Injuries / therapy
  • Young Adult