Data-driven approaches to augment clinical decision in EMR Era

Patient data in electronic medical record systems can serve as an incredible source of evidence on the real-world evaluation of the relationship between medicine treatments and the well-being of the patient. However, the vast amount of raw data presents a significant bottleneck for physician to make sense from it, thus limiting its use in a time pressured clinical setting. A niche exists to develop approaches to enhance a physician´s ability to process large volume of data with the use of `external aids´ in an effort to augment their data cognition capabilities. In this paper, we present how a symbiotic relationship between analysis and visualization techniques can be used to help make sense of a large patient data set. Using examples, we demonstrate our data-driven approach, and show how it can serve a physician in the clinical decision support role at the point of care.