OBJECTIVE: Different data sources are available for the surveillance of road traffic accidents. Taken separately all have important limits. Therefore the integration of medical and non medical data are essential for the construction of a surveillance system able to direct preventive and repressive actions. DESIGN: Cross sectional study. A computerized system for the rapid and precise unification of medical data with data collected by the police force has been realized. The model is embedded in a Geographic Information System (WebGIS), providing the facility for additional spatial data analysis and modelling. Maps of the spatial density of the accidents which consider also the severity of the injuries from a medical point of view have been developed. Risk factors associated with the severity of the injuries have been evaluated by uni- and multivariate statistical analysis. The statistical significance of the associations have been tested with Pearson's test. Confidential intervals of the Odds ratios were calculated with a probability of 95%. SETTING: Province of Trento, Italy. MAIN OUTCOME MEASURES: Number, dynamics and localization of road traffic accidents, activity of ambulance services, access to emergency departments and hospital admissions RESULTS: For 805/930 injured persons it was possible to link the medical data to those collected by the police forces. 111 (16%) accidents have been classified as severe (with hospital admission) and 694 as moderate (without hospital admission). The most important risk factors associated with the severity are represented by the frontal crash and by being a vulnerable road user (pedestrian, cyclist and motorcyclist), specially those <15 years of age. The classification of the most important sites of road traffic accidents in the Trento municipality was significantly modified by the integration of the medical data giving more importance to the more dangerous sites in terms of severity of the injuries. CONCLUSION: This study shows the feasibility of an integrated surveillance of road traffic accidents by using routinely collected data on a local basis.
OBJECTIVE: Different data sources are available for the surveillance of road traffic accidents. Taken separately all have important limits. Therefore the integration of medical and non medical data are essential for the construction of a surveillance system able to direct preventive and repressive actions. DESIGN: Cross sectional study. A computerized system for the rapid and precise unification of medical data with data collected by the police force has been realized. The model is embedded in a Geographic Information System (WebGIS), providing the facility for additional spatial data analysis and modelling. Maps of the spatial density of the accidents which consider also the severity of the injuries from a medical point of view have been developed. Risk factors associated with the severity of the injuries have been evaluated by uni- and multivariate statistical analysis. The statistical significance of the associations have been tested with Pearson's test. Confidential intervals of the Odds ratios were calculated with a probability of 95%. SETTING: Province of Trento, Italy. MAIN OUTCOME MEASURES: Number, dynamics and localization of road traffic accidents, activity of ambulance services, access to emergency departments and hospital admissions RESULTS: For 805/930 injured persons it was possible to link the medical data to those collected by the police forces. 111 (16%) accidents have been classified as severe (with hospital admission) and 694 as moderate (without hospital admission). The most important risk factors associated with the severity are represented by the frontal crash and by being a vulnerable road user (pedestrian, cyclist and motorcyclist), specially those <15 years of age. The classification of the most important sites of road traffic accidents in the Trento municipality was significantly modified by the integration of the medical data giving more importance to the more dangerous sites in terms of severity of the injuries. CONCLUSION: This study shows the feasibility of an integrated surveillance of road traffic accidents by using routinely collected data on a local basis.
Authors: Christian C Madubueze; Christian O Onyebuchi Chukwu; Njoku I Omoke; Odion P Oyakhilome; Chidi Ozo Journal: Int Orthop Date: 2010-07-11 Impact factor: 3.075
Authors: Francesco Chini; Sara Farchi; Ivana Ciaramella; Tranquillo Antoniozzi; Paolo Giorgi Rossi; Laura Camilloni; Massimo Valenti; Piero Borgia Journal: Int J Health Geogr Date: 2009-04-22 Impact factor: 3.918