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

项目概要/摘要 老年人是美国增长最快的年龄组， 这对这个年龄段的人来说是一个严重的公共卫生问题。2014年，有6,800多人死亡，191,000多人非 在美国，在急诊室为老年人治疗的致命伤害。为了充分了解 需要覆盖电动机的整个跨度的老年乘坐者机动车碰撞伤害问题数据 车辆碰撞，从事件前的因素和行动，通过事件后的伤害结果。警方车祸报告 提供有关道路状况和驾驶员在撞车前的行为的详细信息。警方车祸报告 还提供有关事件本身的信息，例如所涉车辆的速度，碰撞 配置、乘员座椅放置和约束使用。医院账单数据库还包含有价值的 关于机动车碰撞结果的信息。ICD-9-CM编码提供了关于以下方面的非常描述性的数据： 受伤细节此外，伤害严重程度的测量，如简化伤害量表（AIS）和伤害 严重程度评分（ISS）可以从ICD-9-CM代码中推导出来，帮助衡量患者对生命的威胁。 乘客受伤的姿势。不幸的是，这两个数据库（如Social）之间的公共唯一密钥 安全号码，很少被收集。因此，需要创新的方法，如概率联系 整合来自事故报告的事件前和事件数据与来自医院账单数据的结果数据 以创建包含来自伤害事件的所有时间点的信息的数据库。 该提案的总体目标是更好地了解导致事故的碰撞和其他风险因素， 增加了老年人撞车和受伤的风险。以下三个目标将用于 支持这一目标：1）创建具有已映射变量的多态概率链接数据集 标准化和统一的定义; 2）确定特征，风险因素和行为趋势， 老年乘客和司机，并量化每个风险因素对维持 事故的伤害和经济影响; 3）确定事故和老年乘客的特征， 可能会导致伤害风险或伤害成本的增加，超出典型碰撞报告中的内容，包括 引用史以及合并症和医疗状况的存在。 该项目将创建一个多年期、多州概率链接的数据库，以实现这些目标。在 除了传统的警察事故和医院帐单数据库之间的联系外，该项目还将包括 与其他公共卫生数据库（如驾驶执照文件、毒理学数据和引文）的集成项目 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.