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

Hospitalization costs of road traffic injuries in Hunan, China: A quantile regression analysis

BACKGROUND

Healthcare expenditure of road traffic injuries in China has not been adequately investigated so far. We aim to provide comprehensive information about the hospitalization costs of inpatients who suffered road traffic injuries, and explore the components and influencing factors of costs.

METHODS

We extracted the data of all inpatients (n = 60535) with road traffic injuries during the year 2019 from Chinese National Health Statistics Network Reporting System database in Hunan, China. We calculated the components of hospitalization costs and analyzed the association between hospitalization costs and patient characteristics using quantile regression models.

RESULTS

The median hospitalization cost was $853.48, and the median length of hospital stay was 9 days. Vulnerable road users accounted for 84.9 % of all cases. Medicine cost is the first driver of hospitalization cost, accounting for 25.94 %. In the low- and medium-cost groups, hospitalization costs were highly concentrated on diagnosis, medicine, and medical services, while in the high-cost groups, consumable cost constituted the highest percentage. Male, a longer length of stay, more severe injuries, two or more comorbidities, surgical treatment, and admission to tertiary hospitals were significantly associated with higher hospitalization costs, and the regression coefficients increased with increasing of quartile points. Costs were lower in the 0-14 years group than in the other groups across all quartiles. At the median, occupants of heavy transport vehicle incurred the highest costs, $44.18 higher than pedestrians; injuries at lower extremities generated higher costs than those at any other site; and vascular injuries caused the greatest costs, $786.24 higher than superficial injuries.

CONCLUSIONS

Road traffic injuries cause huge healthcare costs for victims, most of whom are vulnerable road users. The total cost of hospitalization is incurred mainly for medicine, consumables, diagnosis, medical services, and treatment. Patients' demographic factors (gender and age), clinical factors (injury severity, location, nature, and number of comorbidities), treatment factors (surgery, length of stay, and hospital level), and road user type are all significantly associated with hospitalization costs.

Unraveling preference heterogeneity in willingness-to-pay for enhanced road safety: A hybrid approach of machine learning and quantile regression

Investing in road safety enhancement programs highly depends on the economic valuation of road traffic accidents and their outcomes. Such evaluation underpins road safety interventions in cost-benefit analysis. To this end, understanding and modeling public willingness-to-pay for enhanced road safety have received significant attention in the past few decades. However, despite considerable modeling efforts, some issues still persist in earlier studies, namely, (i) using standard regression approaches that assume a homogeneous impact of explanatory variables on willingness-to-pay, not accounting for heterogeneity, and depends on a priori distribution of the dependent variable, and (ii) the absence of higher-order interactions from models, leading to omitted variable bias and erroneous model inferences. To overcome this critical research gap, our study proposes a new modeling framework, integrating a machine learning technique (decision tree) to identify a priori relationships for higher-order interactions and a quantile regression model to account for heterogeneity along the entire range of willingness-to-pay. The proposed framework examines the determinants of willingness-to-pay for enhanced road safety using a sample of car drivers from Peshawar, Pakistan. Modeling results indicate that variables not significant in a linear model become significant at specific quantiles of the willingness-to-pay distribution. Further, including higher-order interactions among the explanatory variables provides additional insights into the complex relationship between willingness-to-pay and its determinants. In addition, willingness-to-pay for fatal and severe injury risk reductions is estimated at different quartiles and used to calculate the values of corresponding risk reductions. Overall, the proposed framework provides a better understanding of public sensitivities to willingness-to-pay for enhanced road safety.

Effects of transport-carbon intensity, transportation, and economic complexity on environmental and health expenditures

Health and the environment are complex components of the countries, influenced by several factors, especially transport, and economics. Thus, this paper assesses the role of transportation and economic complexity in the environment and public health for the Organization for Economic Co-operation Development (OECD) countries from 2001 to 2020. This study also focuses on the relationship between transport and economic complexity with environmental and healthcare expenditures. Precisely, transport and economic activities stimulate healthcare expenditures through multiple channels. The current study employs the STIRPAT model to investigate the association with transportation, economic complexity, transport-carbon intensity, and healthcare expenditure. Besides, the current research confirms the plausible cross-sectional dependency across countries, and it adopts a second-generation technique. Analytical findings suggest that transportation-carbon intensity is positively and significantly associated with healthcare expenditures. Healthcare and transport-household expenditures increase transport-carbon intensity (TCI) by 75% and 45%, respectively, in the long run. In the contrast, TCI and transport-household expenditures have also a remarkable impact on healthcare expenditures and are estimated approximately 95% in the long run. Moreover, economic growth also upsurges TCI and healthcare expenditures through multiple economic activities. Besides, transport-household expenditures (THE) drastically impact transport-carbon intensity and healthcare expenditures (HEX) through passenger traffic (PTF). Diagnostic upshots unveil that the joint effect of THE and PTF increases TCI and HEX by 4 and 3%, respectively. Finally, findings recommend some policy implications and future research directions for the countries based on empirical outcomes. Countries should regulate economic activities to reduce transport carbon emissions.

Hospitalization costs of injury in elderly population in China: a quantile regression analysis

BACKGROUND

Trauma in the elderly is gradually growing more prevalent as the aging population increases over time. The purpose of this study is to assess hospitalization costs of the elderly trauma population and analyze the association between those costs and the features of the elderly trauma population.

METHODS

In a retrospective analysis, data on trauma patients over 65 who were admitted to the hospital for the first time due to trauma between January 2017 and March 2022 was collected from a tertiary comprehensive hospital in Baotou. We calculated and analyzed the hospitalization cost components. According to various therapeutic approaches, trauma patients were divided into two subgroups: non-surgical patients (1320 cases) and surgical patients (387 cases). Quantile regression was used to evaluate the relationship between trauma patients and hospitalization costs.

RESULTS

This study comprised 1707 trauma patients in total. Mean total hospitalization costs per patient were ¥20,741. Patients with transportation accidents incurred the highest expenditures among those with external causes of trauma, with a mean hospitalization cost of ¥24,918, followed by patients with falls at ¥19,809 on average. Hospitalization costs were dominated by medicine costs (¥7,182 per capita). According to the quantile regression results, all trauma patients' hospitalization costs were considerably increased by length of stay, surgery, the injury severity score (16-24), multimorbidity, thorax injury, and blood transfusion. For non-surgical patients, length of stay, multimorbidity, and the injury severity score (16-24) were all substantially linked to higher hospitalization costs. For surgical patients, length of stay, injury severity score (16-24), and hip and thigh injuries were significantly associated with greater hospitalization costs.

CONCLUSIONS

Using quantile regression to identify factors associated with hospitalization costs could be helpful for addressing the burden of injury in the elderly population. Policymakers may find these findings to be insightful in lowering hospitalization costs related to injury in the elderly population.

Global, Regional, and National Burden of Road Injuries from 1990 to 2019

(1) Background: Understanding occurrence can help formulate effective preventative laws and regulations. However, the most recent global burden and road injuries (RIs) trends have not been reported. This study reports the burden of RIs globally from 1990 to 2019. (2) Methods: RIs data were downloaded from the Global Burden of Disease 2019. Incidence, deaths, and disability-adjusted life years (DALYs) described the trend and burden of RIs. We calculated age-standardized rates (ASRs) and estimated annual percentage change (EAPC) for the above indexes to evaluate the temporal trend of RIs. We evaluated the social-demographic index (SDI) with epidemiological RI parameters and reported proportions of age-standardized rates due to RI. (3) Results: In 2019, the global incidence of RIs reached 103.2 million. The EAPC of RI incidence increased, whereas deaths and DALYs decreased. Age-standardized incident rate (ASIR) was highest in low-middle SDI regions, age-standardized death rate (ASDR) was high in middle SDI regions, and age-standardized DALYs increased in low SDI regions. The highest accident rates were found in those aged 20-24 years old. Cyclist injuries were the leading RIs (34%), though pedestrian and motor vehicle accidents were the leading cause of death (37.4%, 37.6%) and DALYs (35.7%, 32.3%), respectively. (4) Conclusions: Over the past 30 years, RIs incidence increased annually, though death and DALY rates decreased. RIs places a considerable burden on public health in low SDI countries. Data should be used to develop and implement effective measures to reduce the burden of RIs.