Identifying Work-Related Motor Vehicle Crashes in Multiple Databases

Abstract

Objective: To compare and estimate the magnitude of work-related motor vehicle crashes in Utah using 2 probabilistically linked statewide databases.

Methods: Data from 2006 and 2007 motor vehicle crash and hospital databases were joined through probabilistic linkage. Summary statistics and capture–recapture were used to describe occupants injured in work-related motor vehicle crashes and estimate the size of this population.

Results: There were 1597 occupants in the motor vehicle crash database and 1673 patients in the hospital database identified as being in a work-related motor vehicle crash. We identified 1443 occupants with at least one record from either the motor vehicle crash or hospital database indicating work-relatedness that linked to any record in the opposing database. We found that 38.7 percent of occupants injured in work-related motor vehicle crashes identified in the motor vehicle crash database did not have a primary payer code of workers’ compensation in the hospital database and 40.0 percent of patients injured in work-related motor vehicle crashes identified in the hospital database did not meet our definition of a work-related motor vehicle crash in the motor vehicle crash database. Depending on how occupants injured in work-related motor crashes are identified, we estimate the population to be between 1852 and 8492 in Utah for the years 2006 and 2007.

Conclusions: Research on single databases may lead to biased interpretations of work-related motor vehicle crashes. Combining 2 population based databases may still result in an underestimate of the magnitude of work-related motor vehicle crashes. Improved coding of work-related incidents is needed in current databases.

Keywords:

• Work-related injury
• Motor vehicle crash
• Capture–recapture
• Probabilistic linkage

ACKNOWLEDGMENT

This study was partially supported by the Utah Crash Outcome Data Evaluation System (CODES) project (grant number 55600023).

Partially presented at the American Public Health Association Annual Meeting, November 2011, Washington, DC.