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Traffic Inj Prev. 2012;13(4):348-54. doi: 10.1080/15389588.2012.658480.

Identifying work-related motor vehicle crashes in multiple databases.

Author information

1
Intermountain Injury Control Research Center, University of Utah School of Medicine, Department of Pediatrics, Salt Lake City, Utah, USA. andrea.thomas@hsc.utah.edu

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.

PMID:
22817549
DOI:
10.1080/15389588.2012.658480
[Indexed for MEDLINE]

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