Catalyzing Young Driver Research via Data Linkage: Development of a Comprehensive Traffic Safety Data Warehouse

通过数据链接促进年轻驾驶员研究：开发综合交通安全数据仓库

• 批准号: 9533637
• 负责人: Allison Elizabeth Curry
• 金额: $ 26.34万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9533637
• 关键词: Address; Adolescent; Age; Area; Automobile Driving; Birth Certificates; Cause of Death; Cessation of life; Child; Collaborations; Critical Illness; Data; Data Analytics; Data Element; Data Linkages; Data Reporting; Data Sources; Databases; Death Certificates; Development; Ensure; Ethnic Origin; Event; Fostering; Foundations; Funding; Future; Goals; Government; Grant; Hospitals; Incidence; Income; Individual; Injury; Knowledge; Lead; Licensing; Licensure; Link; Methodology; Methods; National Institute of Child Health and Human Development; Neighborhoods; New Jersey; Outcome; Police; Policies; Population; Process; Public Health; Race; Recording of previous events; Reporting; Research; Research Priority; Research Support; Resources; Risk; Safety; Scientist; Source; Suspensions; Time; Variant; Vehicle crash; Young driver; data resource; data warehouse; disability; experience; impaired driving performance; improved; innovation; multidisciplinary; novel; older driver; pediatric trauma; profession allied to medicine; programs; racial and ethnic; racial and ethnic disparities

Project Abstract High-quality linkage of motor vehicle crash data to other existing data sources has the potential to catalyze advancements in our understanding of crashes—the leading cause of death among US adolescents. However, the field of young driver safety relies heavily on studies that analyze only publically available de-identified crash data. Analyzing crash data in isolation restricts the study period to essentially a few minutes and has important limitations that hinder the ability to utilize crash data to validly conduct critical research. Thus, the long-term goal of this R21 project is to harness the power of linked crash data to enhance knowledge of the contributors to and burden of young driver crashes. Over the last five years, the project team has developed a unique linked database—the New Jersey Traffic Safety Outcomes (NJ-TSO) database—that contains the full driver licensing, police-reported crash, and traffic citation data of all NJ drivers (10 million) from 2004 through 2014. The overall objective of the proposed project is to extend this program of research by integrating three additional statewide sources of data in NJ: birth certificate, hospital discharge, and death certificate data. The resultant NJ-TSO data warehouse, which will include individual-level longitudinal data that span the continuum from underlying contributing factors and relevant previous events to injury outcomes and death, is innovative as it will be the most comprehensive data resource focused on young drivers to date. The project has three specific aims. First, the NJ-TSO data warehouse will be created by fully integrating the three additional statewide data sources using established probabilistic linkage methods. Second, key analytic data elements will be derived for all licensed drivers and all crash-involved drivers. These will include: (1) geocoded residential addresses in order to increase the utility of the warehouse to support future spatial and neighborhood-level analyses; (2) race and ethnicity— data elements that are not included in NJ licensing or crash data but are critical to the conduct of foundational and policy-relevant young driver research—using a combination of the newly-integrated data sources and Bayesian Improved Surname Geocoding methods; and (3) crash injuries/fatalities using a combination of data sources. Third, the project will make a unique methodological contribution by quantifying the magnitude and direction of bias introduced by using crash report data (vs. hospital/death) to ascertain crash-related injuries. The proposed research is significant in that the resultant warehouse will be fully primed to directly address critical, high-priority research questions in young driver safety. As the NJ-TSO warehouse will include drivers of all ages, it will also have the potential to serve as a data resource for collaborations on a wide array of high-priority areas of traffic safety, including: impaired driving; unlicensed driver crashes; older driver (> age 65) crashes; pedestrian and pedalcyclist injuries; and child passenger safety. This will ensure that the project optimizes the ability of the NJ-TSO data warehouse to improve public health and the safety of all road users.

项目摘要 汽车撞车数据与其他现有数据源的高质量连接有可能催化 我们对撞车事故的理解的进步 - 美国青少年死亡的主要原因。然而， 年轻驾驶员安全领域在很大程度上依赖研究，该研究仅分析公开可用的撞车事故 数据。孤立分析崩溃数据将研究期限限制为基本上几分钟，并且很重要 限制了利用崩溃数据来进行有效进行重要研究的限制。那是长期目标 这个R21项目是利用链接的碰撞数据的力量，以增强对和的知识 年轻驾驶员的负担坠毁。在过去的五年中，项目团队建立了独特的链接 数据库 - 新泽西州的交通安全结果（NJ-TSO）数据库，其中包含完整的驱动程序许可， 从2004年到2014年，警方报告了撞车事故和所有新泽西州司机的交通引用数据。 拟议项目的目的是通过整合全州三个额外的研究计划 新泽西州的数据来源：出生证明，出院和死亡证明数据。最终的NJ-TSO数据 仓库，其中将包括跨越基础连续体的个人级纵向数据 贡献因素和以前的事件导致伤害结果和死亡，这是创新的，因为这将是 迄今为止，最全面的数据资源集中在年轻的驱动程序上。该项目具有三个特定的目标。第一的， NJ-TSO数据仓库将通过使用三个额外的全州数据源来创建 建立的概率链接方法。其次，将为所有许可的关键分析数据元素得出 驾驶员和所有碰撞驱动程序。这些将包括：（1）地理编码居民地址以增加 仓库支持未来的空间和邻里水平分析的实用性； （2）种族和种族 - NJ许可或崩溃数据中未包含的数据元素，但对于基础的进行至关重要 以及与政策相关的年轻驾驶员研究 - 结合新成立的数据源和 贝叶斯改进的姓氏地理编码方法； （3）使用数据组合的崩溃伤害/死亡 来源。第三，该项目将通过量化大小和 通过使用崩溃报告数据（与医院/死亡）来确定与崩溃有关的伤害引入偏见的方向。 拟议的研究很重要，因为由此产生的仓库将被充分掌握，以直接解决关键， 年轻驾驶员安全方面的高优先研究问题。由于NJ-TSO仓库将包括各个年龄段的驾驶员 它还有可能作为在各种高优先级领域进行合作的数据资源 交通安全，包括：驾驶受损；无执照的驾驶员坠毁；较老的驾驶员（> 65岁）崩溃；行人 和小骑士受伤；和儿童乘客安全。这将确保项目优化 NJ-TSO数据仓库，以改善公共卫生和所有道路使用者的安全。

项目成果

Missed opportunities to advance knowledge on traffic safety: Accessibility of driver licensing and crash data for scientific research.

错过了提高交通安全知识的机会：驾驶执照和碰撞数据的可获取性以用于科学研究。

• DOI: 10.1016/j.aap.2020.105500
• 发表时间: 2020
• 期刊: Accident; analysis and prevention
• 作者: Carey,MeghanE;Anderson,EvanD;Mansour,Rania;Sloan,Jason;Curry,AllisonE
• 通讯作者: Curry,AllisonE

Pediatric Health Care Provider Perspectives on Injury Prevention Counseling in Acute and Primary Care Settings.

• DOI: 10.1177/0009922820941237
• 发表时间: 2020-11
• 期刊: CLINICAL PEDIATRICS
• 影响因子: 1.6
• 作者: Gaw, Christopher E.;Berthet, Ellora;Curry, Allison E.;Zonfrillo, Mark R.;Arbogast, Kristy B.;Corwin, Daniel J.
• 通讯作者: Corwin, Daniel J.

Facilitating research on racial and ethnic disparities and inequities in transportation: Application and evaluation of the Bayesian Improved Surname Geocoding (BISG) algorithm.

• DOI: 10.1080/15389588.2021.1955109
• 发表时间: 2021
• 期刊: Traffic injury prevention
• 影响因子: 2
• 作者: Sartin EB;Metzger KB;Pfeiffer MR;Myers RK;Curry AE
• 通讯作者: Curry AE

Improving identification of crash injuries: Statewide integration of hospital discharge and crash report data.

• DOI: 10.1080/15389588.2022.2083612
• 发表时间: 2022
• 期刊: TRAFFIC INJURY PREVENTION
• 影响因子: 2
• 作者: Lombardi, Leah R.;Pfeiffer, Melissa R.;Metzger, Kristina B.;Myers, Rachel K.;Curry, Allison E.
• 通讯作者: Curry, Allison E.

Vehicle safety characteristics in vulnerable driver populations.

• DOI: 10.1080/15389588.2020.1805445
• 发表时间: 2020-10-12
• 期刊: Traffic injury prevention
• 影响因子: 2
• 作者: Metzger KB;Sartin E;Foss RD;Joyce N;Curry AE
• 通讯作者: Curry AE