Abstract. This study applied a text string search algorithm to ascertain suspect farm tractor or agricultural machinery-related injuries in data sources available for 2000-2014 in the state of Arkansas. The occurrences of tractor or other agricultural machinery-related injuries were compared with data available from the Centers for Disease Control and Prevention’s National Center for Health Statistics (NCHS) and the Bureau of Labor Statistics’ Census of Fatal Occupational Injuries (CFOI). For death certificates that assigned an external cause of death, the authors first collected all those that were coded as related to agricultural machinery, based on search strings for occupation and industry and a description of how the injury occurred. They then inspected each case individually and removed those that were likely unrelated to agricultural machinery. This approach significantly increased (by 7.8 times) the number of suspect agricultural machinery-related fatalities compared to the number reported to CFOI, but there was only a 17% (not statistically significant) increase compared to NCHS. All hospital records with any discharge diagnosis coded as related to agricultural machinery were selected. Descriptive analysis of the fatalities and hospital records showed a significantly increased risk among men above retirement age, peaks during the summer, and an increased risk in the Mississippi delta region. About one-third of the agricultural machinery-related fatalities were due to overturns. The use of the algorithm can improve ascertainment of fatal agricultural machinery-related injuries in Arkansas. The death records were found to be rich in data on the circumstances of the injuries, which can be used to screen for tractor-related fatalities and, if confirmed, translated into action to improve the safety of Arkansas farmers. Keywords: Agricultural machinery, Farm, Farming, Injury, Risk, Statistics, Tractors.
A computer system supporting agricultural machinery and farm tractor purchase decisions
