Implementation of Universal Diagnostic Data Standards Will Improve Response to Emerging Disease

When a new disease emerges, accurate and timely information is critical to optimizing control and response plans. Having diagnostic labs recording and communicating information on emerging disease is a critical part of this coordinated and timely action. To fill this need, the Swine Health Information Center (SHIC) has initiated a veterinary diagnostic lab consortium to further develop and adopt the use of universally recognized diagnostic data and electronic messaging standards across the full-spectrum of swine diagnostic testing routinely conducted.  Having these diagnostic standards and electronic messaging capabilities in place will help producers and their veterinarians manage the break of disease in a geographic area as well as across the U.S. Standardizing the recording and communicating of swine veterinary diagnostic laboratory tests and results will help lead to better detection, management, and response to diseases significantly affecting the US swine industry. More information about SHIC and other initiatives can be found at www.swinehealth.org. The big picture is to create a way to electronically unite the US swine industry through standardizing swine veterinary diagnostic lab tests and data. One of the project investigators, Rodger Main of Iowa State University, recently explained to the American Association of Swine Veterinarians at their annual conference, “Ultimately […] these tools that are being developed have to provide value for day-to-day use [..] to producers, veterinary clinics, and how they are managing their systems on a day-to-day basis.” He continues, “Very importantly as an outbreak occurs, it will allow us to aggregate data for analysis and summary.” SHIC executive director Paul Sundberg explains it is critical for labs to partner and adopt a common, standardized lab test and results data recording and communication system. The diagnostic labs at Iowa State University, Kansas State University, South Dakota State University, and the University of Minnesota are collaborating on the project.  Once done in those laboratories, the model is transferrable to other labs.