Fred Trotter

Graph Theory can be applied to networks of doctors and hospitals in order to improve care coordination and protect profits. This course will go over the basic concepts of graph science, with the intention of applying the concepts to the DocGraph data set. Learning Points: Understand notions of centrality and graph traversal. Understand influence patterns Understand what a network motif is and why you would want to search for them Understand how to translate healthcare issues to solvable graph problems.

In this class Fred Trotter will provide a baseline explanation of what big data is in the context of the health care system, as well as a basic framework for modeling health care effectively. Specifically, he will demonstrate how to model the health care system using a graph, and will explain how to use a graph to elucidate patterns, to examine interoperability, and to analyze and predict operational trends in the coordination of care both across groups and within ACO�s. Fred is renown for his singular expertise in data visualization, modeling, and open source security. Learning objectives for students taking this class are: � What is big data? The reasons to avoid big data sets and tools (and some reasons to embrace them). � How to and how not to model the health care system � The ethical issues surrounding using big data on doctors and patients In this online course series from Health 2.0, four leading industry experts will teach how new applications of big data are transforming their corner of health care. This is an opportunity to gain practical insights on how to use data intelligently and think about it strategically in your particular area of disruption. Each class is 60 minutes followed by 30 minutes of Q&A. Each class is live, interactive, and personal, and takes advantage of Learn It Live's cutting edge virtual classroom platform. This course is for entrepreneurs, executives, data scientists, and clinical leaders. Sign up now!