I lead the Medication Data Science (MeDS) lab in the College of Pharmacy. The MeDS lab focuses on studying the effect of machine learning and other forms of artificial intelligence on provider well-being, health outcomes, patient experience, and costs (i.e., Quadruple Aim) in medication use systems. This research approach is purposefully composed of engineers, information scientists, statisticians, and clinicians in order to foster creative and disruptive innovations that improve human health.  A data science supported approach to the quadruple aim of medication use systems, combined with domain knowledge expertise, leads to significant breakthroughs in both the theoretical and applied research areas. Human-machine learning teams need to work interdependently to achieve routine, reliable, and resilient improvements in medication use systems. The MeDS lab is achieving this ambitious goal by partnering with industry and academia to create novel solutions that directly impact the Quadruple Aim. Our concept (see figure below) was recently published in the Journal of the American Pharmacists Association, check it out here:

Lester CA, Coe TB, Dorsch MP, Farris KB, Flynn AJ. A Learning Pharmacy Practice Enabled by the Pharmacists Patient Care Process. J Am Pharm Assoc, 2020