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Trucking firm characteristics, driver injury and outcome.
Oleinick-A; Horrocks-J; Blower-DF; Guire-KE
Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, R01-OH-003804, 2005 Sep; :1-20
Problem: In the period 1993-2001(later years are not directly comparable) truck drivers had the highest number of injuries and illnesses producing days away from work of any occupation in the Bureau of Labor Statistics Annual Survey of occupational injury and illness (BLS Survey). Counts were 50-100% higher than those in the next two highest groups (laborers, non-construction, and nursing aides and orderlies). In addition to the specialized occupational risks attributable to driving large vehicles and road accidents, truck drivers are also exposed to risks of traumatic and repetitive motion injuries from materials handling as they load, rearrange and unload shipments. However, aside from the greater risk of back injuries among professional drivers and the obvious risk of vehicular accidents, very little is known about whether truck drivers are at higher risk for injuries at other sites, or the days away from work produced by the injuries. There are two reports that truckers' erratic work schedules may affect receipt of health services. Approach: Ohio is one of only five jurisdictions that designate a state agency as the exclusive provider of workers' compensation insurance under state law. In Ohio, employers may qualify for self-insurance based on size of the company (> or = 500 employees) and financial criteria. Data indicate that the Ohio Bureau of Workers' Compensation (OBWC) insured employers employ at least two-thirds of the civilian employed population in Ohio. In the 2000 census, the civilian employed population totaled 5.4 million individuals or about 4.2% of the U.S. total. In FY2002, OBWC reported that there were 213,227 allowed claims for medical and/or wage loss associated with work injuries or illnesses. After review and approval of the proposal by the Ohio Bureau of Workers' Compensation (OBWC) legal department and the University's Institutional Review Board, the OBWC provided a data extract in nine files for 24,131 claims (35,688 diagnoses accepted for payment) from the for-hire carrier industry. Most cases were from for-hire trucking firms, although bus, taxi and emergency medical companies were included. The complexity of the extraction process for the required data was reflected in the fact that it took nine months from the grant start date before we received the final study files. After removing what appeared to be duplicate claims and claims from the same individual with the same date of injury but with differing diagnoses accepted for payment, the initial study population consisted of 23,965 cases with 35,501 separate diagnoses accepted for payment. As we worked with the data extract, it became clear that the data could be used to achieve two of the three original aims: 1. To identify factors associated with the incidence of injuries by occupation, the use of medical care for such injuries and the duration of lost worktime produced by these injuries; and, 2. To evaluate the predictive value of various types of models (an exercise now grouped under the rubric of "concordance statistics"). 3. The data identifying medical care providers by type of organization and specialty were simply too sparse for use in achieving objective three, i.e., detecting associations between regularity of job schedules as reflected by occupation and source of services. The final study population was further reduced to 23,491 cases with 34,165 diagnoses by removing superficial injury diagnoses (910.*-919.*). These diagnoses were excluded to avoid diluting the effort to classify more serious diagnoses by functional area affected. Substantial technical editing was required to convert the nine administrative files into analytic files suitable for modern modeling techniques. This editing consumed almost all the grant time from receipt of the data extract through the one-year no-cost extension, a period of three years and three months. The completed work included seven software modules plus a partial module (all ©University of Michigan) that link multiple claims to a single claimant (20,802 individuals/23,491 claims over three years), track claim number changes over time (approximately 800 changes), remove duplicate or inconsistent claims (166 claims/187 diagnoses), classify diagnoses on several dimensions (functional area affected, severity and whether index injuries had comorbidities) and link diagnostic groups to health services use (the last is the partial module). In addition, manual coding of occupation and industry from text narratives, assignment of race using geocoding and 2000 census data and more complete ascertainment of occupation for truck drivers by using additional Ohio and federal files was completed. The ninth module, under construction, will yield summary tables of health services utilization by diagnosis and permit analysis of the course of diagnosis and treatment. A tenth module, not begun, would provide estimates of another outcome variable, the number of days away from work derived from wage compensation paid. This last problem is not trivial technically because of the number and legal definition of payment codes used. All software requires only that specified data elements be available somewhere in the data file.
Epidemiology; Injuries; Quantitative-analysis; Risk-analysis; Statistical-analysis; Surveillance-programs; Workplace-studies; Work-practices; Truck-drivers; Trucking
Final Grant Report
NTIS Accession No.
National Institute for Occupational Safety and Health
University of Michigan at Ann Arbor
Page last reviewed: September 2, 2020
Content source: National Institute for Occupational Safety and Health Education and Information Division