Evaluating adverse rural crash outcomes using the NHTSA State Data System
Introduction
The increased risk for rural residents to die from a motor vehicle crash has been recognized for many years (Baker et al., 1987, Brodsky and Hakkert, 1983). While this disparity may be partly due to an increased incidence of severe crashes, it appears to be attributable more to the difference in outcome for persons who have been injured (Goldstein et al., 2011, Muelleman et al., 2007). This disparity in outcomes may raise questions about the quality of care delivered by emergency medical services (EMS) and emergency departments (ED), as well as the obvious problems of communication, transportation, and scarce resources in more remote locations (Cummings and O’Keefe, 2000). We sought to explore these issues in order to help identify any factors that might be modified to improve outcomes.
The National Highway Traffic Safety Administration (NHTSA) has developed several crash databases and made them available to researchers at no cost. The best known is the Fatality Analysis Reporting System (http://www.nhtsa.gov/FARS), a census of all crashes since 1975 in which at least one person died. A stratified random sample of similar (but less detailed) information about nonfatal crashes has been provided since 1988 by the National Automotive Sampling System (http://www.nhtsa.gov/NASS). These databases have been used extensively by traffic and automotive engineers, and occasionally for epidemiologic or health services research.
A less frequently used NHTSA database is the State Data System (http://www.nhtsa.gov/Data/State+Data+Program+&+CODES), which is a compilation of state based police accident reports from participating states, including information about the event, vehicles, and persons similar to that available in the National Automotive Sampling System (NASS). Studies using the NHTSA State Data System (NHTSA-SDS) have been infrequently published outside of NHTSA (Cheung and McCartt, 2011, Eisenberg and Warner, 2005, Karaca-Mandic and Ridgeway, 2010, Lyon et al., 2012), but it records data from a much larger number of rural counties than the few sampled by the NASS. NHTSA-SDS is therefore a potentially valuable database for EMS research, which could help overcome some of the limitations and complement the findings from the other NHTSA databases.
A primary goal of this study was to investigate further the rural/urban outcome disparities in traffic crashes and the effects of post-crash factors on outcomes. We were most interested in the person, vehicle, and location factors associated with mortality among persons who had been severely injured in a crash, since this would be the outcome most likely to be affected by EMS or trauma care systems. We also intended to compare findings using NHTSA-SDS to published results based on estimates from the NASS General Estimates System (GES).
Section snippets
Methods
NHTSA-SDS data for 2005–2007 were obtained at nominal cost through the NHTSA Office of Data Acquisitions. Access to the data from each state required specific approval of an official in that state, and in some cases there were additional state-specific requirements. At the time, 33 states were participating in NHTSA-SDS, and we attempted to obtain data from 20 of them; seven explicitly denied access except to internal NHTSA researchers, and two others did not respond to repeated requests. The
Results
The 11 contributing states provided data from a total of 654 counties, distributed over the nine RUCC categories in proportions roughly similar to those seen in the US as a whole (Table 1). For the 11 states over three years, a total of 11,008,057 persons were involved in a motor vehicle crash as an occupant of a car or light truck: Only 187,199 (1.7%) of these had a severe injury, including 127,680 (1.46%) reported by the police to have an incapacitating injury and 26,582 (0.24%) reported by
Discussion
Injury research generally uses the conceptual model proposed by Haddon (1972), separating the analysis both with respect to the timing (before, during, after an event) and the level of observation (host, agent, and environment). While crash prevention is clearly the most cost-effective approach, the post-event, environmental cell of the Haddon Matrix is also important. Part of the increased crash mortality in rural areas may result from reduced access to an effective trauma care system
Conclusions
This study found that individuals in rural and very rural crashes have a significantly increased risk of death, increased risk of severe injury, and increased risk of death after being severely injured even with models that control for person, vehicle, and crash characteristics. On the whole, these effects were similar to those found in a study using NASS-GES (Travis et al., 2012). As NHTSA-SDS data become available from more states, and become more uniform, they may be even more valuable than
Acknowledgement
This study was funded in part by an NIH grant R21HD061318: “County trauma systems and outcomes disparities”. However, the NIH had no other role in the collection, analysis, and interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication.
References (27)
The call for help after an injury road accident
Accid. Anal. Prev.
(1993)- et al.
Highway fatal accidents and accessibility of emergency medical services
Soc. Sci. Med.
(1983) - et al.
Rural vs urban motor vehicle crash death rates: 20 years of FARS data
Prehosp. Emerg. Care
(2000) - et al.
Declines in fatal crashes of older drivers: changes in crash risk and survivability
Accid. Anal. Prev.
(2011) - et al.
Scene disposition and mode of transport following rural trauma: a prospective cohort study comparing patient costs
J. Emerg. Med.
(2000) - et al.
Behavioral impact of graduate driver licensing on teenage drivign risk and exposure
J. Health Econ.
(2010) - et al.
National evaluation of the effect of graduated driver licensing laws on teenager fatality and injury crashes
J. Saf. Res.
(2012) - et al.
Mortality in rural locations after severe injuries from motor vehicle crashes
J. Saf. Res.
(2012) - et al.
Qualification discrepancies between urban and rural emergency department physicians
J. Emerg. Med.
(2005) - et al.
An inter-regional comparison: fatal crashes in the southeastern and non-southeastern United States: preliminary findings
Accid. Anal. Prev.
(1999)
Determinants of motor vehicle deaths in the United States: a cross-sectional analysis
Accid. Anal. Prev.
Geographic variations in mortality from motor vehicle crashes
N. Engl. J. Med.
Proxy measures in accident countermeasure evaluation: a study of emergency medical services
J. Saf. Res.
Cited by (10)
The relationship between geographic location and outcomes following injury: A scoping review
2019, InjuryCitation Excerpt :One study adjusted for age and injury severity [56]. Nine studies adjusted for age as well as three or more additional confounders including injury severity, speed, time of day, comorbidities, socioeconomic status, time to first responder input and alcohol [37,38,40,42,57–61] (see Supplementary Material Table 1 for specific details). In summary, despite variation in the mortality statistics reported, a significantly higher risk of mortality was reported for rural populations and this was particularly notable in regards to pre-hospital mortality statistics.
Smooth associations between the emergency medical services response time and the risk of death in road traffic crashes
2019, Journal of Transport and HealthCitation Excerpt :It is a key performance indicator reflecting the time traffic crash victims wait to be rescued and serving as a measurable quantity for evaluating and managing dispatch operations of EMS vehicles (Amorim et al., 2017). Mainstream opinions (e.g. Gonzalez et al., 2009; Wilde, 2013) acknowledge the considerable influence the EMS response time has on death likelihood, in that an increased EMS response time will lead to an elevated risk of fatality for general emergent events (Bunn et al., 2012; Heestermans et al., 2010; Saver et al., 2010) and traffic crashes (Delmelle et al., 2005; Li et al., 2008; Petzäll et al., 2011; Sánchez-Mangas et al., 2010; Arroyo et al., 2013; Peura et al., 2015). Thus, the emergency medical handling of the injured has become an acknowledged tactical approach for reducing the mortality rate from traumas, as many deaths would have been preventable if the victims had received quicker medical responses (Hussain and Redmond, 1994), especially in cases of brain- or heart-injured victims (MacLeod et al., 2007) or those requiring open airways or hemorrhage controls (Bansal et al., 2009; Bakke and Wisborg, 2017; Oliver et al., 2017).
The impact of rurality on child road traffic death in high-income countries
2023, Australian Journal of Rural HealthThe nature of paramedic practice in rural and remote locations: A scoping review
2022, Australasian Journal of ParamedicineMechanism of injury and special considerations as predictive of serious injury: A systematic review
2022, Academic Emergency MedicineEnhanced Image Processing and Fuzzy Logic Approach for Optimizing Driver Drowsiness Detection
2022, Applied Computational Intelligence and Soft Computing