County Trauma Systems and Outcomes Disparities

描述（由申请人提供）：利用现有的国家特定数据，识别和评估与机动车碰撞后更好的健康结果相关的潜在可修改的院前因素。研究设计：一系列相关的研究，使用多年的政府数据库相互联系，并使用确定性和概率方法与其他数据相关联。将描述小区域（县）的变异性和随时间的变化。结果分析将使用多水平回归来解释聚类数据结构（例如，人<县<州<年）。背景和参与者：来自受伤美国人的普查和样本数据，记录在国家生命统计系统（NVSS）、死亡分析报告系统（FARS）、国家汽车抽样系统（NASS）和其他文件中。解释变量：按县（或相关邮政编码）描述当地创伤系统的结构和过程变量，包括：EMT能力水平；状态创伤系统特征；有效的交通安全法例；到空中救护车或创伤中心的平均距离；致命交通事故的平均紧急医疗服务响应时间和运输时间。这些潜在可改变因素的变化将根据地理、人口和驾驶暴露的测量结果进行报告；随着时间的推移，一个县的变化将被视为当地可改变因素的进一步证据。结果测量：基于人口的交通死亡率（NVSS/FARS）；车祸死亡率、住院时间和工作损失时间（NASS）；除首次死亡（FARS）外，FARS受试者的生存率。在控制固定的地理/人口因素和随机的个人/事件因素的同时，结果将被建模为上述院前解释变量（特别是那些确定为可修改的变量）的可能函数。公共卫生相关性：该项目提供了一个机会，收集已有的数据，并应用现代统计方法来评估创伤系统的院前组成部分。通过结合来自多个来源的数据，并在不同的汇总水平上适当控制变量的影响，拟议的项目将为政策制定者和创伤系统管理人员提供有关系统改进的宝贵信息，这些改进可以使个人受益，特别是那些生活在农村地区的人。

DESCRIPTION (provided by applicant): To identify and evaluate potentially modifiable pre-hospital factors associated with better health outcomes after motor vehicle collisions, using existing county-specific data. Study Design: A series of related studies using multiple-year government databases linked to each other and to additional data using deterministic and probabilistic methods. Small-area (county) variability and changes over time will be described. Outcome analysis will use multilevel regression to account for clustered data structures (e.g., persons < counties < states < years). Setting and Participants: Census and sample data from injured Americans, as recorded in National Vital Statistics System (NVSS), Fatality Analysis Reporting System (FARS), National Automotive Sampling System (NASS), and other files. Explanatory variables: Structural and process variables describing local trauma systems by county (or related ZIP code) including: Levels of EMT capability; state trauma system characteristics; traffic safety legislation in effect; mean distance from air ambulances or trauma centers; mean EMS response and transport times for fatal traffic crashes. Variation in these potentially modifiable factors will be reported with respect to measures of geography, demography, and driving exposure; changes over time in a county will be considered further evidence of a locally modifiable factor. Outcome Measures: Population-based traffic mortality (NVSS/FARS); crash-based mortality, length of hospitalization, and time lost from work (NASS); and survival of FARS subjects other than the first fatality (FARS). Outcomes will be modeled as possible functions of the above pre-hospital explanatory variables (especially those identified as modifiable), while controlling for fixed geographic/demographic factors and random personal/event factors. PUBLIC HEALTH RELEVANCE: This project presents an opportunity to assemble data already available and apply contemporary statistical methods to evaluate the pre-hospital component of trauma systems. By combining data from multiple sources and controlling properly for the effects of variables at different levels of aggregation, the proposed project will provide valuable information to policy makers and trauma system managers about system improvements that can benefit individuals, particularly those living in rural areas.