OSU researchers turn to Oracle EHR Real-World Data to develop clinical tools
University researchers create clinical decision algorithms with Oracle EHR Real-World Data to help physicians identify diseases in rural markets.
“Millions of Americans in rural areas face limited access to quality healthcare, resulting in shorter average lifespans compared to their urban counterparts. Our algorithms are designed to help address this disparity. The insights we derived from Oracle’s Real-World Data were essential to developing these models.”
Oklahoma State University Center for Health Systems Innovation (OSU-CHSI) conducts data-driven research for rural and Native American communities that lack clinical care resources and representation in research. To help address these disparities, the organization needed robust healthcare data to develop actionable insights and tools. OSU-CHSI implemented Oracle EHR Real-World Data while developing important machine learning risk models. These algorithms help clinicians better manage patients with high-risk chronic diseases by detecting risk factors earlier. This helps prevent cases of irreversible morbidity, such as diabetes-related blindness or tobacco-related lung cancer. Using Oracle EHR Real-World Data, OSU was able to deliver more intelligent care with fewer resources, thereby reducing reliance on scarce medical specialists and resources.