Patient Electronic Health Data-Driven Approach to Clinical Decision Support

Ketan K. Mane, Chris Bizon, Phillips Owen, Ken Gersing, Javed Mostafa, Charles Schmitt
2011 Clinical and Translational Science  
This article presents a novel visual analytics (VA)-based clinical decision support (CDS) tool prototype that was designed as a collaborative work between Renaissance Computing Institute and Duke University. Using Major Depressive Disorder data from MindLinc electronic health record system at Duke, the CDS tool shows an approach to leverage data from comparative population (patients with similar medical profi le) to enhance a clinicians' decision making process at the point of care. The initial
more » ... work is being extended in collaboration with the University of North Carolina CTSA to address the key challenges of CDS, as well as to show the use of VA to derive insight from large volumes of Electronic Health Record patient data.
doi:10.1111/j.1752-8062.2011.00324.x pmid:22029811 pmcid:PMC5439904 fatcat:sofyg64l3zdltjrnxdqbe3l3t4