title: Influence of injury risk thresholds on the performance of an algorithm to predict crashes with serious injuries.
abstract: This paper presents methods to estimate crash injury risk based on crash characteristics captured by some passenger vehicles equipped with Advanced Automatic Crash Notification technology. The resulting injury risk estimates could be used within an algorithm to optimize rescue care. Regression analysis was applied to the National Automotive Sampling System / Crashworthiness Data System (NASS/CDS) to determine how variations in a specific injury risk threshold would influence the accuracy of predicting crashes with serious injuries. The recommended thresholds for classifying crashes with severe injuries are 0.10 for frontal crashes and 0.05 for side crashes. The regression analysis of NASS/CDS indicates that these thresholds will provide sensitivity above 0.67 while maintaining a positive predictive value in the range of 0.20.
authors.affiliation: Impact Research, Inc. The William Lehman Injury Research Center.
authors.forename: George
authors.initials: G
authors.lastname: Bahouth
authors.forename: Kennerly
authors.initials: K
authors.lastname: Digges
authors.forename: Carl
authors.initials: C
authors.lastname: Schulman
mesh_terms: D000063:Accidents, Traffic; D000465:Algorithms; D006801:Humans; D012044:Regression Analysis; D014481:United States; D014947:Wounds and Injuries