UMASH researchers presented and engaged with other ag safety professionals at the 2016 ISASH conference in Lexington KY June 26-29, 2016. Megan Roberts,
Dates: 2012 – current
No practical surveillance mechanism exists that collects information on injuries associated with agricultural activities for most farms in the US. Dairy; Wisconsin’s most important agricultural activity, is no exception. This surveillance project focuses on injuries in Wisconsin dairy farmers and workers, with particular emphasis on changes in the dairy industry and the effect these changes have on injury patterns. The goal is to establish an active surveillance process using a recurring survey and linking to electronic health records and various state health data records in order to inform policy and guide interventions designed to reduce the overall burden of injury on this population.
- Establish population-based estimates of incidence of injury and illnesses in dairy farmers and workers;
- Develop and administer a recurring survey to establish estimates of injury and illness among dairy farmers and workers throughout the state of Wisconsin over time; and
- Identify high risk activities and conditions associated with production processes and worker characteristics and track any detectable influence on the frequency of injury or illness in the dairy workforce.
The main objective of this project is to establish and maintain a working injury surveillance system among farmers and farm workers in Wisconsin. The initial data collection was completed in Fall 2014. The survey tool is being prepared for a second round of data collection to identify trends in injury exposure on farms. An effective surveillance program is essential to providing data on the effects of safety programs and policies, among other changes over time.
The project is also evaluating the use of Natural Language Processing (NLP), a tool designed to data mine the electronic medical records of patients in the Marshfield Clinic service area to identify farmers and contribute to ongoing surveillance. The tool would allow disease and injury data to be automatically collected reducing the time and material costs of the surveillance project. After initially defining the search parameters, the research team is continuing to explore more fully the use and efficacy of the NLP tool. Specifically, they have compared the rate of disease and injury in two parts of the Marshfield Clinic service area. One area includes many dairy farms and the comparison area is known to contain very few dairy farms. These may be useful to further refine the NLP tool to identify dairy farm workers in the electronic medical records and track rates of injury and disease.
This study will be the first to establish population-based estimates of incidence and prevalence of work-related injuries and illnesses in dairy in Wisconsin.
UMASH Researchers at 2016 ISASH Conference
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