Using EHR-based clinical decision support tools, there’s an opportunity for system-wide intervention to present real-time information in the routine care workflow to improve laboratory ordering decisions. To enable rapid identification of relevant historical analyte results, this pilot will develop and validate clustering algorithms to automatically classify analytes under a unified “Common Name”. These algorithms will provide reference points to pull relevant information to present providers at the point of analyte order entry. Furthermore, this pilot will prototype several user interface iterations to identify the best way to present historical information to providers to drive high value clinical decisions.