Setting
We performed a retrospective cohort study assessing all e-scooter-related injuries in Helsinki between January 2021 and December 2021. We analyzed all patients enrolled in the adult emergency departments (ED): one level I trauma center and two level IV trauma centers. The level I trauma center has a 24-hour capability to provide total care for all trauma patients with in-house surgeons on-call and is responsible for high-level trauma care for the whole Hospital district in southern Finland. The level IV trauma centers have a 24-hour capability to treat mild and moderate-level trauma patients and provide a primary evaluation of more severe trauma patients before referral to the level I trauma center. In Helsinki, the three hospitals are the only public hospitals to treat acute trauma patients.
The population base of Helsinki was 656 920 residents on 31.12.2020, with the mean age being 41 years and 53% being female [16]. During the study period, five shared e-scooter rental companies with a total fleet of approximately 4700 e-scooters were in operation [17]. The e-scooters were rented via a mobile application for users over 18 years old. In Finland, the maximum speed of e-scooters is 25 km/h by law. Furthermore, helmets are strongly encouraged but are not officially controlled.
During the study period, the city of Helsinki and the e-scooter rental companies constituted several restrictions for rental e-scooter usage. First, on the 7th of July 2021, the maximum speed limit was lowered to 15 km/h in several inner-city areas. Second, on the 3rd of September 2021, the use of rental e-scooters was prohibited on Friday and Saturday nights between 00.00 and 05.00. In addition, the top speed was lowered to 20 km/h during the daytime and 15 km/h between 00.00 and 05.00 on other days.
Data inquiry
We performed an initial data inquiry to detect e-scooter-related injuries using a keyword search from the hospital information system consisting of ED and ambulance records. Four different e-scooter-related words, including their inflected forms, were used. Next, the authors HV and LT examined all the detected patient records. Consequently, only the cases where the e-scooter involvement was definite were included. All remaining patients over 16 years old were included in the study. Exclusive inclusion and exclusion criteria are presented in Fig. 1.
Patient demographics
We collected the demographic factors from the ED visit. The collected variables were age, sex, time of the injury, injury mechanism, the person affected by the injury, helmet usage, and alcohol intoxication status. If the exact time of injury was not available, we set the injury time as the time when the patient registered at the ED. The breath alcohol level was recorded if measured at the ED or ambulance. In addition, alcohol intoxication was assessed as a binominal value considering the clinical assessment of the ED doctors if the breath alcohol level was not measured. Furthermore, we sought to obtain data regarding e-scooter ownership (shared vs. private e-scooter), but the data was available only in 84 (18%) cases, and therefore, the variable was abandoned.
Injury patterns and severity
We collected all sustained injuries based on the diagnoses from the e-scooter hospital episode according to the International Classification of Diagnoses-10 (ICD-10). In case of missing diagnoses, we added the injuries if they were described with enough precision in the patient records. The injuries are presented based on their anatomical location and severity.
Every patient’s most severe injury was graded retrospectively based on Abbreviated Injury Score (AIS) from the Abbreviated Injury Scale [18] to minor, moderate, serious, severe, or critical. According to AIS, superficial wounds, muscle or ligament sprains, mild contusions, dental injuries, and mild concussions with no loss of consciousness or equivalent were graded as minor. Moderate injuries were closed fractures of distal extremities, major ligament tears (e.g. knee cruciate ligament tear), and equivalent. Open fractures, fractures proximal femur, comminuted facial fractures, basilar skull fractures, and intracranial hemorrhages with coma of less than 6 hours and no definite diffuse axonal injury (DAI) were graded as serious injuries. Furthermore, intracranial hemorrhages requiring decompressive craniectomy, severe intracranial hemorrhages with coma of more than 6 hours or diagnosed DAI, and severe internal organ hemorrhages were graded as severe or critical.
To estimate the total effect of all injuries on the patient, we calculated the New Injury Severity Score (NISS) [19]. Accordingly, patients with ISS 1–8 were graded as minor, ISS 9–14 were graded as moderate, and ISS ≥ 15 were graded as major trauma patients, respectively.
Follow-up
After the initial ED visit, we followed up the patients from our hospital information system for a minimum of 2 months or to the end of the e-scooter-related hospital episode if the treatment continued beyond 2 months. If the patient required hospital admissions, we recorded the length and type of hospital admission. In addition, all scheduled additional injury-related hospital visits and surgeries were recorded and analyzed. Finally, we recorded the total number of radiographs (native radiographs, computed tomography scans, and magnetic resonance imaging), laboratory tests, and the number of sickness absence days the physician dictated for each patient during all hospital visits.
Cost analysis
The estimation of costs for the whole treatment (ED visits, inpatient care, outpatient visits, surgical procedures, radiological imaging, and laboratory tests) was done according to our hospital district’s service price listing for 2021, which was based on NordDRG diagnosis related group system. [20]. In our hospital district, the service price listing describes the costs billed from the patients’ home city after their care. A price was sought for all events during the hospital episode. If the price of an event was unequivocal, the lowest suitable value was used.
According to the Finnish social system, the pay for short-term absence (≤ 10 working days) is covered by the employer, and the Social Insurance Institution of Finland covers long-term absence (> 10 days). To further estimate sick leave costs for the work providers and society, we used the Finnish Ministry of Social Affairs and Health evaluation in 2014. Accordingly, we used an inflation-corrected price of 203,91 €/day for short-term and 158.83€/day for long-term sickness absence. [21, 22]
Statistics
We acquired descriptive statistics using cross-tabulations. Nominal values were presented as counts (percentages). Continuous values were presented as medians or means based on whether the values complied with Gaussian distribution. Medians were reported with interquartile range (IQR) for large groups or range for smaller (n < 50) groups. Means were reported with standard deviation (S.D.). The normality of continuous values was assessed visually using histograms and Q-Q plots, and with the skewness value of the distribution. We used the statistical program SPSS 28.0.1 (IBM corp. released on the 10th of November 2021) for the statistical analysis.
Ethics and approval
Organizational approval was gained for all participating hospitals (HUS/44/2021). As the study was retrospective and did not require interaction with the patients, it does not classify as a medical study by the definition of Finnish law. Therefore, the study was granted an exemption from requiring ethical committee processing.