The growing epidemic of type 2 diabetes affects over 8.3% of the US population and presents a major challenge to healthcare systems and public health. An additional 7 million people have undiagnosed diabetes and over 79 million have pre-diabetes, which if unrecognized and untreated can progress to full-blown diabetes. Although screening and diagnostic tests are routinely available, health systems struggle to diagnose patients with diabetes in a timely manner. In fact, clinical diagnosis lags 8-12 years behind the onset of glucose dysregulation, resulting in diagnostic delays and the presence of diabetes complications at the time of diagnosis. Among patients engaged in clinical care without a known diagnosis of diabetes, nearly all patients have random plasma glucose (RPG) data available which potentially provides valuable, early warning safety signals regarding the need for further diabetes testing. However, elevated glucose values are commonly unrecognized and over 60% of abnormal values are not followed-up with diabetes testing in a timely fashion. Opportunities exist to leverage existing data within electronic medical records (EMR) to identify patients in need of further diabetes testing and develop systems-based solutions to reduce: 1) failures in following-up abnormal glucose tests, 2) delays in diagnosing diabetes, and 3) frequency of missed diagnoses of diabetes.