A COMBINATION OF GEOSPATIAL AND CLINICAL ANALYSIS IN PREDICTING DISABILITY OUTCOME AFTER ROAD TRAFFIC INJURY (RTI) IN A DISTRICT IN MALAYSIA

Abstract. This was a Prospective Cohort Study commencing from July 2011 until June 2013 involving all injuries related to motor vehicle crashes (MVC) attended Emergency Departments (ED) of two tertiary centers in a district in Malaysia. Selected attributes were geospatially analyzed by using ARCGIS (by ESRI) software version 10.1 licensed to the institution and Google Map free software and multiple logistic regression was performed by using SPSS version 22.0. A total of 439 cases were recruited. The mean age (SD) of the MVC victims was 26.04 years (s.d 15.26). Male comprised of 302 (71.7%) of the cases. Motorcyclists were the commonest type of victims involved [351(80.0%)]. Hotspot MVC locations occurred at certain intersections and on roads within borough of Kenali and Binjai. The number of severely injured and polytrauma are mostly on the road network within speed limit of 60 km/hour. A person with an increase in ISS of one score had a 37 % higher odd to have disability at hospital discharge (95% CI: 1.253, 1.499, p-value < 0.001). Pediatric age group (less than 19 years of age) had 52.1% lesser odds to have disability at discharge from hospital (95% CI: 0.258, 0.889, p-value < 0.001) and patients who underwent operation for definitive management had 4.14 times odds to have disability at discharge from hospital (95% CI: 1.681, 10.218, p-value = 0.002). Overall this study has proven that GIS with a combination of traditional statistical analysis is still a powerful tool in road traffic injury (RTI) related research.