A Multi-State Integrated Data Approach to Analyzing Older Occupant Motor Vehicle Crash and Injury Risk Factors

项目摘要/摘要 老年人是美国增长最快的年龄段，车祸是 对于这个年龄段来说，这是一个严重的公共卫生问题。2014年，有超过6800人死亡，超过19.1万人死于 致命伤害在美国老年人急诊科接受治疗。为了充分了解 较老的乘员机动车碰撞伤害问题数据需要覆盖整个电机跨度 车辆碰撞，从事前因素和行为到事后伤害后果。警方撞车报告 提供有关道路状况和驾驶员在撞车前的行为的详细信息。警方撞车报告 还提供有关事件本身的信息，如涉及的车辆速度、撞车事件 配置、乘员座椅位置和安全带使用。医院账单数据库还包含有价值的 有关机动车碰撞结果的信息。ICD-9-CM代码提供了关于以下方面的描述性数据 伤情细节。此外，伤害严重程度的衡量标准，如简化伤害等级(AIS)和伤害 严重程度评分(ISS)可以从ICD-9-CM代码中得出，以帮助衡量 乘客的伤势造成。不幸的是，这两个数据库之间的一个公共、唯一的关键字，如Social 安全号码，很少被收集。因此，需要采用概率关联等创新方法 将事故报告中的事前和事件数据与医院账单数据中的结果数据进行集成 创建一个包含受伤事件所有时间点信息的数据库。 这项建议的总体目标是更好地了解事故和其他导致事故的风险因素 增加了老年乘客的撞车风险和受伤严重程度。以下三个目标将用于 支持此目标：1)使用已映射的变量创建多状态概率链接数据集 标准化和统一的定义；2)确定以下人群的特征、风险因素和行为趋势 并量化每个风险因素对持续高血压的可能性的贡献 车祸的伤害和经济影响；以及3)确定车祸和老年乘员的特征 可能会增加受伤的风险或成本，而不是典型的撞车报告中包含的内容，包括 引证病史及合并症和医疗条件。 该项目将创建一个多年、多个州的概率链接数据库，以实现这些目标。在……里面 除了传统的警察撞车和医院账单数据库之间的联系外，这个项目还将包括 与其他公共卫生数据库的集成项目，如驾驶执照文件、毒理学数据和引文 和定罪数据库。

PROJECT SUMMARY/ABSTRACT Older persons represent the fastest-growing age group in the United States and motor vehicle crashes represent a serious public health problem for this age group. In 2014, there were over 6,800 deaths and over 191,000 non- fatal injuries treated in emergency departments for older persons in the United States. In order to fully understand the older occupant motor vehicle crash injury problem data are needed that cover the full span of the motor vehicle crash, from pre-event factors and actions through post-event injury outcomes. Police crash reports provide great detail about the roadway conditions and driver actions proceeding a crash. Police crash reports also give information regarding the event itself, such as the speed of the vehicles involved, the crash configuration, occupant seating placement, and restraint use. Hospital billing databases also contain valuable information regarding a motor vehicle crash outcomes. ICD-9-CM codes provide very descriptive data regarding injury specifics. Additionally, measures of injury severity such as the Abbreviated Injury Scale (AIS) and Injury Severity Score (ISS) can be derived from the ICD-9-CM codes helping to measure the threat to life that an occupant's injuries pose. Unfortunately, a common, unique key between these two databases, such as Social Security Number, is rarely collected. Therefore, innovative methods, such as probabilistic linkage, are needed to integrate the pre-event and event data from the crash report with the outcome data from hospital billing data to create a database which contains information from across all time points of the injury event. The overall goal of this proposal is to gain a better understanding of crash and other risk factors that contribute to increased risk of crashes and injury severity for older occupants. The following three aims will be used to support this goal: 1) to create a multi-state probabilistically linked data set with variables that have been mapped to standardized and uniform definitions; 2) to determine characteristics, risk factors, and behavioral trends among older passengers and drivers and to quantify each risk factor's contribution to the likelihood of sustaining an injury and economic impact of crashes; and 3) to determine characteristics of crashes and older occupants which may contribute to an increased risk or cost of injury beyond what is contained on a typical crash report including citation history and the presence of comorbidities and medical conditions. This project will create a multi-year, multi-state probabilistically linked database to address these aims. In addition to the traditional linkage between police crash and hospital billing databases, this project will also include integration projects with other public health databases such as driver license files, toxicology data, and citation and conviction databases.