Background: Road accidents are a major public health problem that affect all age groups but their impact is most striking among the young. The aim of this study is to quantify the burden of road traffic injuries, their mortality and direct in-patient economic costs and to identify the age classes at highest risk for severe road traffic injuries, through analysis of data collected by information systems of an Italian Local Health Authority.
Methods: The study was conducted in a Local Health Authority of Veneto Region. Injured people were selected from Emergency Department (2006-2010). Data were linked to the Hospital Information System for hospital admissions and to the Mortality Registry to check 30-day mortality. The direct costs associated to hospitalizations were estimated through Diagnosis Related Group reimbursement rates. Multivariate analysis was performed using hospitalization and mortality as the dependent variables and gender, age, day of week when accident occurred as the independent variables. Traffic injury, hospitalization and mortality incidence rates were calculated by gender and age per 100,000 residents per year.
Results: The road traffic injuries were 9,192, decreasing from 2,112 in 2006 to 1,980 in 2010. Among injured persons 55.3% were male (68.1% among 15-19 age class); 41.7% young people aged 15-34 years (43.9% among male, 39.0% among female). Total hospitalisation rate was 5.9%. Overall mortality rate was 0.3% (0.9% among aged 65 or older). The cost of hospital admission was euro 2,742,505 (hospitalization mean cost euro 5,097). Risk of hospitalization and death was higher in male, in elderly and during week end. Young people aged 15-19 had the highest incidence of visits (2,258.4 per 100,000) and high hospitalisation weekend and mortality rates (respectively 101.5 and 8.5).
Conclusions: Analysis at local level, using current data sources, permits to estimate the burden of injuries caused by road-traffic, to describe the characteristics of injured persons and finally to estimate costs of care. All this information could be used to make the population aware of its own risk for road accidents. Linkage of these data with police and transport data is required to focus prevention on higher risk groups and to adopt effective local road safety strategies.