To identify and evaluate potentially modifiable pre-hospital factors associated with better health outcomes after motor vehicle collisions, using existing county-specific data. Study Design: A series of related studies using multiple-year government databases linked to each other and to additional data using deterministic and probabilistic methods. Small-area (county) variability and changes over time will be described. Outcome analysis will use multilevel regression to account for clustered data structures (e.g., persons This project presents an opportunity to assemble data already available and apply contemporary statistical methods to evaluate the pre-hospital component of trauma systems. By combining data from multiple sources and controlling properly for the effects of variables at different levels of aggregation, the proposed project will provide valuable information to policy makers and trauma system managers about system improvements that can benefit individuals, particularly those living in rural areas.Public Health Relevance
Peura, Christine; Kilch, Joseph A; Clark, David E (2015) Evaluating adverse rural crash outcomes using the NHTSA State Data System. Accid Anal Prev 82:257-62 |
Clark, David E; Hannan, Edward L (2013) Inverse propensity weighting to adjust for bias in fatal crash samples. Accid Anal Prev 50:1244-51 |
Haskins, Amy E; Clark, David E; Travis, Lori L (2013) Racial disparities in survival among injured drivers. Am J Epidemiol 177:380-7 |
Travis, Lori L; Clark, David E; Haskins, Amy E et al. (2012) Mortality in rural locations after severe injuries from motor vehicle crashes. J Safety Res 43:375-80 |
Goldstein, Gregory P; Clark, David E; Travis, Lori L et al. (2011) Explaining regional disparities in traffic mortality by decomposing conditional probabilities. Inj Prev 17:84-90 |
Clark, David E; Hannan, Edward L; Wu, Chuntao (2010) Predicting risk-adjusted mortality for trauma patients: logistic versus multilevel logistic models. J Am Coll Surg 211:224-31 |