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Safety of micromobility transportation: What We Can – and Cannot – Learn from United States Emergency Department Records - Over the last several years, the use of micromobility devices for transportation (e.g. e-bikes, e-scooters, skateboards) has expanded around the world. This has been seen both with the emergence of shared micromobility systems and usage of personally owned devices. The rise of micromobility has come with both promise and concerns. Given that micromobility riders are vulnerable road users in relation to automobiles, one notable concern has been safety. Researchers have published several articles investigating the safety of various micromobility modes, however, most have been authored by medical researchers. Unsurprisingly, these articles well-describe the types of injuries micromobility riders suffer. However, they generally provide less insight into the transportation context and the possible infrastructure improvements or policy changes that could be undertaken to foster safer micromobility transportation.
To further explore micromobility safety from a transportation management lens, we analyzed emergency room data from the National Electronic Injury Surveillance System (NEISS). The NEISS provides information on ER visits from a sample of 96 hospitals nationwide. The National Transportation Safety Board (2022) noted that the NEISS is the “only source of national estimates of injuries involving micromobility devices.” The NEISS provides data on ER visits associated with the use of various consumer products, including multiple micromobility devices. For each patient, an array of pre-coded data is reported as well as a one-sentence narrative comment line for each injury case. From this comment line we coded additional transportation-related variables.
We looked at data from six devices from 2020-22 (bicycles, e-bikes, powered scooters, mopeds, skateboards, and powered skateboards/hoverboards). Injuries increased for four of the six devices over this time period, most notably powered scooters (+94%) and e-bikes (+357%) implying very rapid increases in use of these two devices in particular.
Further explorations of the data highlighted several interesting similarities and differences across the devices. One notable difference was the age of patients. Non-motorized devices had younger age distributions versus motorized devices, indicating different target populations for measures attempting to improve safety.
We found interesting similarities though when looking at bicycles, e-bikes, and powered scooters, the three most popular devices we explored. In terms of severity, hospitalization rates were not significantly different from each other (e-bikes 15%, bicycles 13%, powered scooters 13%). Head injury rates were also not significantly different from each other (e-bikes 21%, bicycles 19%, powered scooters 20%). These similarities in types of injuries suffered across the three devices indicate that measures to improve bicycle safety are likely to also be beneficial for micromobility devices as a whole.
Reading of the case comment lines also revealed common factors associated with injuries. Vehicle collisions were an unfortunately common factor. Collision rates were generally higher for motorized devices and devices ridden on the street versus sidewalk (e.g. 30% for e-bikes). Other occasional factors that appeared in measurable numbers in case comment lines included pavement issues, multiple riders on a device, and use of drugs/alcohol.
