Technical University of Denmark, Department of Technology, Management and Economics, Division of Transport, DK-2800 Kgs. Lyngby, Denmark.
Technical University of Denmark, Department of Technology, Management and Economics, Division of Transport, DK-2800 Kgs. Lyngby, Denmark.
J Safety Res. 2021 Feb;76:36-43. doi: 10.1016/j.jsr.2020.11.004. Epub 2020 Dec 10.
In this study we explore the added value of bicycle crash descriptions from open text fields in hospital records from the Aarhus municipality in Denmark. We also explore how bicycle crash data from the hospital complements crash data registered by the police in the same area and time period.
The study includes 5,313 Danish bicycle crashes, of which 4,205 were registered at the hospital and 1,078 by the police. All crashes occurred from 2010 to 2015. We performed an in-depth analysis of the open text fields on hospital records to identify factors associated with each crash using four categories: bicyclist, road, bicycle, and the other party. We employed the chi-squared test to compare the distribution of variables between crashes registered at the hospital and by the police. A binary logit model was used to estimate the probability that a crash factor is identified, and that each crash factor is associated with a single-bicycle crash.
The open-ended text fields in hospital records provide detailed information about crash factors not available in police records, including riding speed, inattention, clothing, specific road conditions, and bicycle defects. The factors alcohol and curb had the highest odds of being identified in relation to a single-bicycle crash. Crash data registered at the hospital included a larger number of bicycle crashes, particularly single-bicycle crashes and crashes with slight injuries only.
Crash information registered at the hospital in Aarhus Municipality contributes to a better understanding of bicycle crashes due to detailed information about crash-associated factors as well as information about a larger number of bicycle crashes, particularly single-bicycle crashes. Practical implication: Efforts to improve access to detailed information about bicycle crashes are needed to provide a better basis for bicycle crash prevention.
本研究旨在探讨丹麦奥胡斯市医院记录中的自行车事故描述的附加价值，这些描述来自开放文本字段。我们还探讨了医院记录中的自行车事故数据如何补充同一地区和时间段内警方登记的事故数据。
本研究包括 5313 例丹麦自行车事故，其中 4205 例在医院登记，1078 例由警方登记。所有事故均发生在 2010 年至 2015 年期间。我们对医院记录中的开放文本字段进行了深入分析，使用四个类别（骑车人、道路、自行车和对方）来识别每个事故的相关因素：骑车人、道路、自行车和其他方。我们使用卡方检验比较了在医院和警方登记的事故之间变量的分布。使用二项逻辑回归模型估计事故因素被识别的概率，以及每个事故因素是否与单一自行车事故相关。
医院记录中的开放文本字段提供了有关警察记录中未包含的事故因素的详细信息，包括骑行速度、注意力不集中、衣物、特定道路状况和自行车缺陷。酒精和路缘等因素与单一自行车事故相关的可能性最高。医院登记的事故数据包括更多的自行车事故，特别是单一自行车事故和仅轻微受伤的事故。
奥胡斯市医院登记的事故信息有助于更好地了解自行车事故，因为它提供了有关事故相关因素的详细信息，以及更多自行车事故的信息，特别是单一自行车事故。实际意义：需要努力改善获取有关自行车事故的详细信息的途径，以为自行车事故预防提供更好的基础。
