P092 Algorithmic approach to injured workers: designed for dairy and pork, applicable across industries. (1st September 2016) - Weichelt, Bryan; Reyes, Iris; Mahnke, Andrea; Verhagen, Laurel; Ray, Will; Keifer, Mathew; Liebman, Amy King
Abstract : Background: Agriculture has again been listed as the most dangerous U.S. industry in 2015. Like other large animal production, dairy and pork operations consistently account for serious, restrictive, non-fatal injuries. This project was designed to develop a return to work software application to produce applicable light duty job assemblies based on worker limitations and available tasks on the farm. Methods: Farm task data were collected by physical and occupational therapists at dairy and pork farms in Minnesota and Wisconsin. The collection included heights, weights, and environmental considerations such as slippery surfaces. Narrative data from therapist collection had to be converted to a structured format to make most use of algorithmic functionality. Results: The system, in prototype form, has been tested with workers, employers and clinicians. The application outputs suggested job tasks based on the limitations entered. Rather than a typical proscriptive output from physician to patient and employer, this application provides a prescriptive recommendation allowing the injured worker to get back to work sooner and safer. Farmers/employers still have the discretion to adjust the recommended tasks so long as they stay within the physical limitations outlined by the physician (e.g. cannot lift more than 10 lbs.). Conclusions: The tool in prototype appears to be appealing to Insurance companies that offer Workers' Compensation coverage and Farmers/employers who appreciate the guidance it offers in navigating a safe return to work of injured employees. Though few farmers realise the financial ramifications of keeping someone on time-loss, they quickly discern the value of the system, and often request more information about farm safety and injury prevention.