Authors: Keifer MC, Sandberg S, Reyes IA, Waring SC, Alexander B, Gerberich SG.

Journal of Agromedicine. Wisconsin. June 9, 2014

ABSTRACT:
The objective of this project is to establish, as well as maintain, a comprehensive working surveillance system designed to identify illness and injury among dairy farmers and farmworkers throughout the state of Wisconsin. Emphasis is to capture occupational, technological and workforce changes within the industry to determine the impact on health and safety. Procedures are underway to establish the first population-based estimates of incidence of injury and illness in Wisconsin dairy farmers utilizing available resources. Additionally, the project plans to create a surveillance instrument which will include questions regarding illness and injury among workers and their families, and farm owners, as well as process changes within their operation. Subsequent surveying will be used for the identification of both high and low risk activities on the farm and establish if the approach to certain farming related tasks influence risk. Initial estimates of our population cohort have been generated. In addition, as part of a sub-study the manual clinical text abstraction procedure has provided listings of common farm terminology for Natural Language Processing (NLP) development to efficiently and electronically define farmers within medical records that might be missed by matching medical records against other sources. The surveillance instrument design is in final stages awaiting piloting. Change in this industry, including the modernization of equipment, a shift in the demographic of workers as well as the increase in facility size to account for current market demands will surely have an impact on occupational risk factors. Results from our project may impact factors from medical expenditures and hospitalization rates to future agricultural safety policies and procedures. This modifiable surveillance instrument will provide continual disease and injury monitoring and potentially serve as a template for the surveillance of a wide variety of agriculturally based occupations. As well, the cohort will be able to provide additional population-based research projects. A prospective birth cohort study is currently in development. In addition, the novel approach of NLP to efficiently define farmers within medical record text can be applied to other occupations once development and training are complete.

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