• H Y Chen, S Jan, S Boufous, A L C Martiniuk, R Ivers, T Senserrick, R Norton, and D Muscatello.
• The George Institute for Global Health, The University of Sydney, Australia. huei-yang.chen@curtin.edu.au
• Injury. 2012 Sep 1;43(9):1593-9.

BackgroundThis study aims to examine factors associated with variation in crash-related hospitalization costs for young adults in New South Wales (NSW), Australia with a particular focus on types of vehicle occupant, rurality of residence and socioeconomic status (SES).MethodsData on patients aged 17-25 years, admitted to public hospitals due to a crash during July 2000-June 2007 were extracted from the NSW Health Admission Collection database. The hospitalization cost of each admission was calculated based on published charges for specific Australian Refined-Diagnosis Related Groups (AR-DRG). Multivariable analyses using generalized estimating equations were used to estimate costs by vehicle occupant type (driver, passenger and other occupants), rurality of residence (urban, regional and rural areas) and SES (low, moderate and high SES areas).ResultsDuring 2000-2007, there were 11,892 crash-related hospitalizations involving young adults, aged 17-25 years, in NSW. These cost the health sector about A$87.6 million or on average, A$7363 per hospitalization (mean length of stay (LOS) 5.3 days). Compared to drivers, passengers had significantly longer LOS (<0.01) as well as higher hospitalization costs (p = 0.04). Regional and rural young adults had significantly longer LOS and higher hospitalization costs compared to urban young adults (p<0.05). Compared with young adults from high SES areas, young adults from moderate SES areas had significantly higher costs (p = 0.02), whilst the higher costs for young adults of low SES areas was borderline significant (p = 0.06), although differences in LOS by SES were not significant.ConclusionAnnually, young adults' crashes in NSW were estimated to cost the health sector at least A$14.6 million between 2001 and 2007. The higher hospitalization costs and LOS for young adults living in regional and rural vs. urban areas, and those living in moderate and low SES vs. high SES areas partly reflects the severity of these crashes and challenges for treatment. Based on these findings, a strong economic argument can be made for targeting prevention strategies to young people living in rural and low SES areas. The area variations in costs also suggest some scope for policy makers to consider potentially more efficient ways of targeting both treatment and preventative programmes.Copyright © 2011 Elsevier Ltd. All rights reserved.

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