Estimating occupation-related crashes in light and medium size vehicles in Kentucky: A text mining and data linkage approach

IF 5.7 1区工程技术 Q1 ERGONOMICS

Accident; analysis and prevention Pub Date : 2024-08-17 DOI:10.1016/j.aap.2024.107749

Caitlin A. Northcutt , Nikiforos Stamatiadis , Michael A. Fields , Reginald Souleyrette

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引用次数: 0

Abstract

Occupational motor vehicle (OMV) crashes are a leading cause of occupation-related injury and fatality in the United States. Statewide crash databases provide a good source for identifying crashes involving large commercial vehicles but are less optimal for identifying OMV crashes involving light or medium vehicles. This has led to an underestimation of OMV crash counts across states and an incomplete picture of the magnitude of the problem. The goal of this study was to develop and pilot a systematic process for identifying OMV crashes in light and medium vehicles using both state crash and health-related surveillance databases. A two-fold process was developed that included: 1) a machine learning approach for mining crash narratives and 2) a deterministic data linkage effort with crash state data and workers compensation (WC) claims records and emergency medical service (EMS) data, independently. Overall, the combined process identified 5,302 OMV crashes in light and medium vehicles within one year’s worth of crash data. Findings suggest the inclusion of multi-method approaches and multiple data sources can be implemented and used to improve OMV crash surveillance in the United States.

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估算肯塔基州轻型和中型车辆中与职业相关的碰撞事故：文本挖掘和数据链接方法

在美国，职业机动车（OMV）碰撞事故是造成职业相关伤亡的主要原因。全州范围内的碰撞数据库为识别涉及大型商用车辆的碰撞事故提供了一个很好的来源，但对于识别涉及轻型或中型车辆的职业机动车碰撞事故却不那么理想。这就导致各州之间的OMV碰撞次数被低估，对问题的严重程度也无法全面了解。本研究的目标是利用各州的碰撞和健康相关监控数据库，开发并试行一套系统流程，用于识别轻型和中型车辆中的OMV碰撞事故。开发的流程包括两个方面：1) 采用机器学习方法挖掘碰撞叙述；2) 与碰撞州数据、工人赔偿 (WC) 索赔记录和紧急医疗服务 (EMS) 数据进行独立的确定性数据链接。总之，在一年的碰撞数据中，综合流程识别出了 5,302 起轻型和中型车辆的机动车碰撞事故。研究结果表明，可以采用多种方法和多种数据源来改进美国的机动车碰撞监测工作。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accident; analysis and prevention Multiple-

CiteScore

11.90

自引率

16.90%

发文量

264

审稿时长

48 days

期刊介绍： Accident Analysis & Prevention provides wide coverage of the general areas relating to accidental injury and damage, including the pre-injury and immediate post-injury phases. Published papers deal with medical, legal, economic, educational, behavioral, theoretical or empirical aspects of transportation accidents, as well as with accidents at other sites. Selected topics within the scope of the Journal may include: studies of human, environmental and vehicular factors influencing the occurrence, type and severity of accidents and injury; the design, implementation and evaluation of countermeasures; biomechanics of impact and human tolerance limits to injury; modelling and statistical analysis of accident data; policy, planning and decision-making in safety.