Managerial Predictors of Traffic Injuries in Tabriz Hospitals

Abstract

SUMMERY Background: Motor vehicle accidents are the leading cause of death in adolescents and young adults worldwide. Road traffic fatality is in critical situation in our country nowadays and about 28000 individuals die from road traffic accidents annually. Previous studies on trauma care in Iran have mainly focused on prehospital trauma care. This paper deals with the predictors of traffic injury deaths and distribution in hospitals. Objectives: the objectives of the present study were to investigate the survival and predictors of 2-wheel vehicle and pedestrian traffic injury outcomes (recovery, deaths, refers and discharge without medical advice) in hospitals of Tabriz, Iran. We aimed these objectives with focus on outcome differences in various owned hospitals. Methods: This longitudinal study reviewed about 15,331 injures in 21 hospitals in Tabriz city over the time period between March 2012 and March 2013 and the needed data on motorcycle, bicycle and pedestrian (MBP) traffic injuries referred to hospitals were collected from hospital Information Systems (HISs). Operation codes were extracted according to ICD10 codes and the data were analyzed using STATA 13 statistical software package. Descriptive statistical methods and appropriate graphs were used to summarize the data. Chi-square and Cogrank tests were used for bi-variate analysis. Relative risk to investigate the association between variables, relative risks along with 95% confidence intervals was also reported. The confidence intervals for relative risks were evaluated using Exact Estimation. ظ Results: The total death of traffic injuries was 266 of them 184 were among all inpatient traffic injured, 166 among MBP inpatients and 82 were among outpatients. Young MBPs (<20<40 years of age), experienced higher injury rate than older ones (48.4%), (p < 0.05) and 26% were pedestrian, 32% motorcyclist, 4.6% cyclist and 37.1% non-MBPs. Most of the 266 deaths, 251 deaths (2.2% of all traffic injuries) happened in public teaching hospitals. Fourteen deaths (0.4%) happened in other public hospitals and 1 death (0.35%) in private hospitals. The difference, using the Fisher's exact test, was significant (p<0.01). Hazard ratio for death of the victims referred to public teaching hospitals 5.8 times more than other hospitals. RR=5.7 CI=0.95 3.4 – 9.6. Likelihood of admission for victims transported by EMS was 1.13 times more than victims not transported by EMS (RR=0.95 1.13-1.22, CI: 1.05-1.2). From 266 death, 265 (99.62%) happened in rank1 hospitals and 1 (0.38%) in rank 2. Conclusion: A precision attention of all these predictors will enable Officials in planning for effective training programs and death control measures. These can also be used in the legislation of traffic laws and regulations and managerial plans of hospitals and pre-hospitals. Keywords: “Traffic”, “Accident”, “Hospital Administration”, “traffic victims”, “injuries” , “traffic injuries”, “length of stay”, “mortality “