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 将机动车碰撞数据与其他现有数据源高质量地联系起来， 我们对车祸--美国青少年死亡的主要原因--的理解有了进步。然而，在这方面， 年轻驾驶员的安全性领域在很大程度上依赖于只分析可识别的碰撞的研究 数据孤立地分析碰撞数据将研究时间限制在几分钟内， 阻碍利用碰撞数据有效进行关键研究的能力的限制。因此，长期目标 这个R21项目的目的是利用链接的碰撞数据的力量来增强贡献者的知识， 年轻司机撞车的负担。在过去的五年里，项目团队开发了一种独特的 数据库-新泽西交通安全结果（NJ-TSO）数据库-包含完整的驾驶执照， 从2004年到2014年，警方报告的撞车事故，以及所有新泽西州司机（1000万）的交通引用数据。整体 拟议项目的目标是通过整合全州范围内的三个额外的研究项目， 新泽西州的数据来源：出生证明、出院证明和死亡证明数据。NJ-TSO数据 数据仓库，它将包括从底层到跨连续体的各个级别的纵向数据 致伤因素和相关既往事件对损伤结局和死亡的影响是创新性的，因为它将是 最全面的数据资源集中在年轻的司机到目前为止。该项目有三个具体目标。第一、 新泽西州交通安全办公室数据仓库将通过全面整合另外三个全州范围的数据源来创建， 建立了概率链接方法。第二，将为所有获得许可的 司机和所有涉及车祸的司机。这些措施将包括：（1）地理编码的住宅地址，以增加 仓库的效用，以支持未来的空间和邻里水平的分析;（2）种族和民族- 不包括在NJ许可或崩溃数据中，但对进行基础 和政策相关的年轻司机研究-使用新集成的数据源和 贝叶斯改进的姓氏地理编码方法;以及（3）使用数据组合的碰撞伤害/死亡 源第三，该项目将通过量化数据的规模和 通过使用碰撞报告数据（与医院/死亡）确定碰撞相关伤害而引入的偏倚方向。 拟议的研究是重要的，因为由此产生的仓库将完全准备好直接解决关键， 年轻驾驶员安全的高优先级研究问题。由于NJ-TSO仓库将包括所有年龄段的司机， 它还将有潜力作为一个数据资源，用于在一系列高优先级领域进行合作 交通安全，包括：受损驾驶;无证驾驶员碰撞;老年驾驶员（> 65岁）碰撞;行人 以及儿童乘客安全。这将确保该项目优化的能力 NJ-TSO数据仓库可改善公共健康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