TRUCKING FIRM CHARACTERISTICS, DRIVER INJURY AND OUTCOME

说明： 卡车司机的职业伤害和疾病数量最多。 造成1992-97年间的休假时间，是第三高的比率。 除了背部受伤，几乎没有关于风险因素的信息。 对这样的伤害负责。既不是个人因素的作用，也不是动力因素的作用 承运人(卡车运输公司)的经营特点和车辆特征是 明白了。这项研究汇集了卡车运输业的专家， 劳资关系、职业医学/流行病学和生物统计学 链接和分析以前未合并的数据集，以 调查与卡车司机受伤和结果相关的因素。 这项研究将：1)通过机动车辆操作来计算发病率 特点、车队规模和卡车配置；2)估计医疗保健 在不同的医疗保健环境中使用-由社会人口统计、卡车公司和 用Logistic或Poisson进行特定医学诊断和建模 回归；3)用损失的工作时间衡量的结果模型使用Logistic， 泊松和考克斯模型；以及4)计算结果的预测值 通过适当的方法建立模型。 薪酬信息将从一家主要的工业化企业获得 该州的工人补偿局。这些数据覆盖了大约60%-65%的 国家工作人员，包括拥有2-500名工人的公司的所有工人， 由自我保险的雇主承保的劳动力余额。数据来自 工人赔偿机构包括社会人口统计、事故 特点、医疗用途和损失工作时间的补偿。这个 研究人群由大约12,000名与工作相关的工人组成 在1996-98年度发生的受伤或疾病。后续跟进将可用 直至2001年年中。汽车运输车的运行特性和车辆特性 将从联邦或州监管机构获得。卡车相撞 信息也将从联邦或州来源获得。 发病率是通过将薪酬和卡车公司的数据联系起来计算的。 Logistic模型、泊松模型和考克斯模型用于检验假设和识别 影响发病率、医疗服务使用和预后的重要因素。预测性 通过ROC曲线、贝叶斯信息标准或其他方法来评估价值 推荐的方法。

DESCRIPTION: Truck drivers had the highest number of occupational injuries and illnesses causing time away from work during 1992-97 and the third highest rates. Except for back injuries, almost no information is available on risk factors for such injuries. Neither the role of personal factors nor that of motor carrier (trucking firm) operating characteristics and vehicle features is understood. This study brings together experts from truck transportation, industrial relations, occupational medicine/epidemiology and biostatistics to link and analyze data sets that have not been combined previously to investigate factors associated with truck driver injury and outcome. The study will: 1) calculate incidence rates by motor carrier operating characteristics, fleet size and truck configuration; 2) estimate medical care use in different medical care settings by social-demographic, truck firm and specific medical diagnosis and model such use with logistic or Poisson regression; 3) model outcome measured by lost work-time using logistic, Poisson and Cox models; and 4) calculate the predictive value of the resulting models by appropriate methodology. The compensation information will be obtained from a major industrialized State's workers' compensation bureau. The data covers about 60-65% of the state workers, including all workers in firms with 2-500 workers, with the balance of the workforce covered by self-insured employers. Data from the workers' compensation agency include social-demographic, accident characteristics, medical care use and compensation for lost work-time. The study population consists of about 12,000 workers who had work-related injuries or illnesses occurring in 1996-98. Follow-up will be available through mid-2001. Motor carrier operating characteristics and vehicle features will be obtained from federal or state regulatory agencies. Truck crash information will also be obtained from federal or state sources. Incidence rates are calculated by linking compensation and truck firm data. Logistic, Poisson and Cox models are used to test hypotheses and identify significant factors in incidence, medical care use and outcome. Predictive value is evaluated by ROC curves, the Bayes Information Criteria or other recommended approaches.