title: Serious injury prediction algorithm based on large-scale data and under-triage control.
abstract: The present study was undertaken to construct an algorithm for an advanced automatic collision notification system based on national traffic accident data compiled by Japanese police. While US research into the development of a serious-injury prediction algorithm is based on a logistic regression algorithm using the National Automotive Sampling System/Crashworthiness Data System, the present injury prediction algorithm was based on comprehensive police data covering all accidents that occurred across Japan. The particular focus of this research is to improve the rescue of injured vehicle occupants in traffic accidents, and the present algorithm assumes the use of an onboard event data recorder data from which risk factors such as pseudo delta-V, vehicle impact location, seatbelt wearing or non-wearing, involvement in a single impact or multiple impact crash and the occupant's age can be derived. As a result, a simple and handy algorithm suited for onboard vehicle installation was constructed from a sample of half of the available police data. The other half of the police data was applied to the validation testing of this new algorithm using receiver operating characteristic analysis. An additional validation was conducted using in-depth investigation of accident injuries in collaboration with prospective host emergency care institutes. The validated algorithm, named the TOYOTA-Nihon University algorithm, proved to be as useful as the US URGENCY and other existing algorithms. Furthermore, an under-triage control analysis found that the present algorithm could achieve an under-triage rate of less than 10% by setting a threshold of 8.3%.
authors: Nihon University, College of Engineering, Biomechanics Research Unit, 1 Nakagawara, Tokusada, Tamuramachi, Koriyama, Fukushima 963-8642, Japan. Electronic address: tnishi@mech.ce.nihon-u.ac.jp.
authors: Tetsuya
authors: T
authors: Nishimoto
authors: Nihon University, College of Engineering, Biomechanics Research Unit, 1 Nakagawara, Tokusada, Tamuramachi, Koriyama, Fukushima 963-8642, Japan.
authors: Kosuke
authors: K
authors: Mukaigawa
authors: Nihon University, College of Science and Technology, 1-8-14 Kanda-surugadai, Chiyoda, Tokyo 101-8308, Japan.
authors: Shigeru
authors: S
authors: Tominaga
authors: Toyota Motor Corporation, Vehicle Safety Development, 1200, Mishuku, Susono, Shizuoka 410-1193, Japan.
authors: Nils
authors: N
authors: Lubbe
authors: Toyota Motor Corporation, Vehicle Safety Development, 1200, Mishuku, Susono, Shizuoka 410-1193, Japan.
authors: Toru
authors: T
authors: Kiuchi
authors: Nippon Medical School, Chiba Hokusoh Hospital, Department of Critical Care Center, 1715 Kamagari, Inzai-shi, Chiba 270-1694, Japan.
authors: Tomokazu
authors: T
authors: Motomura
authors: Nippon Medical School, Chiba Hokusoh Hospital, Department of Critical Care Center, 1715 Kamagari, Inzai-shi, Chiba 270-1694, Japan.
authors: Hisashi
authors: H
authors: Matsumoto
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000465:Algorithms; D006801:Humans; D007564:Japan; D016015:Logistic Models; D008297:Male; D011446:Prospective Studies; D018570:Risk Assessment / Q000706:statistics & numerical data; D014218:Triage; D014947:Wounds and Injuries
keywords: Advanced automatic collision notification; Automobile safety; Injury prediction; Occupant injury