Road traffic injuries in one local health unit in the Lazio region: results of a surveillance system integrating police and health data

OBJECTIVE Different sources are available for the surveillance of Road Traffic injuries (RTI), but studied individually they present several limits. In this paper we present the results of a surveillance integrating healthcare data with the data gathered by the municipal police in the southeastern area of Rome (630,000 inhabitants) during the year 2003. METHODS The Municipal police RTI reports, which list the exact location, circumstances and some risk factor of the crash, were searched in the emergency visit, hospitalization and mortality databases, to integrate them with the information on health consequences. A multivariate analysis was conducted to evaluate risk factors (crash circumstances, age ad gender of the casualty) associated with hospital admission following a RTI. Mapping of RTI locations was created. The locations with higher risk of accidents with severe health consequences and at higher risk for pedestrians were identified. RESULTS According to police records 4571 RTI occurred in 2003, 75% of which led to emergency department admissions. Sixteen percent of these emergency visits ended in hospitalization, and 44 deaths were reported within 30 days of the event, most of which occurred in young men. The people with the highest risk of hospitalization after an RTI were the cyclists, pedestrians and followed by people on two-wheeled vehicles. The type of crash with the highest risk of hospitalization was head-on collision. Geographical analyses showed four clusters with higher severity of RTI. Specific attention was paid to pedestrian injuries. Analyzing the locations of RTIs involving pedestrians permitted us to rank the most dangerous streets. The roads at high risk for pedestrians identified problems in the bus stop constructions and in the placement of the zebra pedestrian crossings. CONCLUSION This study proves the feasibility of an integrated surveillance system of RTI by using routinely collected local data. The high-risk locations identified with the geographic analyses method in this study highlighted infrastructural problems, suggesting immediate preventive interventions.