2023 Fiscal Year Final Research Report
An Australian Pilot Study of an Injury Prediction Algorithm for Early Rescue in Word Car Accidents
| Project/Area Number |
21H01578
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Review Section |
Basic Section 25020:Safety engineering-related
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| Research Institution | Nihon University |
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Principal Investigator |
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Keywords | 自動車安全 / 救命救急 / 傷害予測 / 事故自動緊急通報システム |
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| Outline of Final Research Achievements |
Most injury prediction algorithms used for determining injury severity do not include the effect of emergency transport time, that is, the time taken to transport an injured person from a road crash to an emergency trauma centre. Therefore, we developed an injury prediction algorithm that incorporates the influence of emergency transport time as a risk factor.
The base model of the injury prediction algorithm was constructed by applying logistic regression analysis to the South Australian Traffic Accident Reporting System (TARS) data. The TARS data, which are statistical data on traffic accidents, do not contain time-related data. Therefore, we quantified the effect of transport time on the fatality and serious injury rate as odds ratios using the Serious Injury Database derived from a trauma centre. Finally, the odds ratios were converted into regression coefficients and mixed with the base model to construct an injury prediction algorithm that takes into account the transport time.
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| Free Research Field |
自動車工学
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| Academic Significance and Societal Importance of the Research Achievements |
救命救急センターに搬送すべき重症交通事故であった場合，治療開始までの時間を短縮することができれば，死亡リスクを大きく削減できる．本研究の傷害予測アルゴリズムを用いることにより，搬送時間が長期化することで重症となる可能性が高い負傷者に対して早期搬送を促すことが可能となり，救命率の向上に寄与できるものと考える．本研究で定量化した搬送時間が死亡重傷リスクに及ぼす影響は，国や地域に依存するものではないため，日本の傷害予測アルゴリズムに混成が可能である．
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