Healthcare costs of road injuries in Saudi Arabia: A quantile regression analysis

Abstract

Background: Road traffic injuries (RTIs) are the second leading cause of death in Saudi Arabia. Their economic burden is significant but poorly quantified, as limited literature exists locally. We aim to estimate the impact of RTIs on healthcare costs.

Methods: We included all patients from the hospital's trauma registry for the year 2017 (n = 381). Due to the availability of data, the analysis focused only on direct medical costs incurred during the hospitalization period. We computed the components of hospitalization costs and evaluated the association between patient and RTI characteristics and total hospitalization costs (the average and median) using quantile and log-linear regression techniques respectively.

Results: Patients were relatively young with an average age of 31 years (SD ± 14.6). Overall, patients treated for RTIs cost the hospital around 77,657 Saudi Riyal (SAR) on average. Pedestrian injuries incurred the highest costs. Motor vehicle injuries accounted for the highest procedure-related costs (SAR 19,537). The quantile regressions results suggest that Glasgow coma scale (GCS), admission to intensive care unit (ICU), and hospital length of stay were significantly associated with an increase in hospitalization cost. Hospital home disposition was however, associated with a decrease in cost. One additional day of stay in the hospital increases total hospitalization cost by SAR 3,508. Additionally, the log-linear showed injury severity score (ISS < 16) was associated with a 20% decrease in the geometric mean of the hospitalization costs (p < 0.001).

Conclusions: This study underlines the economic burden of RTIs in addition to their impact on population health. The findings may be used to inform policymakers, researchers, and the public about the increasing burden of traffic crashes in the Kingdom. Public health interventions are warranted to reduce the severity and frequency of RTIs in order to improve traffic safety and reduce associated healthcare costs.

Keywords: Injury burden; Motor vehicle occupant; Motorcycle; Pedestrian.