Elsevier

Accident Analysis & Prevention

Volume 82, September 2015, Pages 257-262
Accident Analysis & Prevention

Evaluating adverse rural crash outcomes using the NHTSA State Data System

https://doi.org/10.1016/j.aap.2015.06.005Get rights and content

Highlights

  • The National Highway Traffic Safety Administration State Data System (NHTSA-SDS) is a potentially useful collection of police-reported crash data from participating U.S. states.

  • Analysis of traffic crashes using the NHTSA-SDS shows that mortality is more likely in rural areas, even after restricting to persons with a severe (incapacitating or fatal) injury and controlling for other known factors.

  • The estimated effects of rural location in this study were similar to effect estimates previously obtained using the NHTSA National Automotive Sampling System.

  • The NHTSA-SDS is currently limited by data inconsistencies among the states, but as these become more uniform and more states participate the value of NHTSA-SDS for injury epidemiology should increase.

Abstract

Introduction

The population-based rate of motor vehicle crash mortality is consistently higher in rural locations, but it is unclear how much of this disparity might be due to geographic barriers or deficiencies in emergency medical services (EMS). We sought to analyze separately factors associated with the occurrence of a severe injury and those associated with death after injury had occurred.

Methods

Data from all police-reported crashes in 11 states from 2005–2007 were obtained through the National Highway Traffic Safety Administration (NHTSA) State Data System (SDS). Logistic regression was used to estimate factors associated with (1) death; (2) severe (incapacitating or fatal) injury; and (3) death given severe injury. Models included covariates related to the person, vehicle, and event; county location was specified using Rural–Urban Continuum Codes (RUCC).

Results

Older age, not wearing a belt, ejection, alcohol involvement, high speed, and early morning times were associated with increased risk of both severe injury and death. Controlling for these factors, and restricting analysis to persons who had suffered a severe injury, the adjusted odds ratio (aOR) associated with death was higher for counties classified rural (RUCC 6–7, aOR 1.23, 95% CI 1.16–1.31) or very rural (RUCC 8–9, aOR 1.31, 95% CI 1.18–1.46).

Conclusions

Persons severely injured in crashes are more likely to die if they are in rural locations, possibly due to EMS constraints. As NHTSA-SDS data become more available and more uniform, they may be useful to explore specific factors contributing to this increased risk.

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.

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