A joint Carlson School/School of Public Health student team won first place in the graduate division of the MinneMUDAC data science/data analytics competition. The competition, hosted by MinneAnalytics, took place November 4 at Optum in Eden Prairie.
Team members included Carlson MSBA students Aastha, Hemanth Rao Natarajan, and Srihari Gopi and health policy management doctoral student Alex Everhart. Hundreds of students from the Midwest attended the competition, and they all had a big challenge: to identify the most costly 6,000 of 40,000 diabetes patients using a complex health insurance claims database from Optum. The students received the data on October 2 and had to present their results on November 4.
“Our team worked hard the last few weeks,” said Associate Professor Pinar Karaca-Mandic, who was the team’s faculty advisor. “With their presentation to the judges and to the whole packed auditorium, not only did they demonstrate their big data skills and use of machine learning tools, but they were able to fantastically illustrate their knowledge on diabetes as a disease, and how they went about figuring out useful variables in a database with thousands of variables.”
Three Carlson School teams ending up making it to the finals. Tempo Li, Bryce Quesnel, Kevin Sorenson, Andrew Tsai, and Kyle Stahl were members of one of the teams, and the third team included Alex Sweet, Aneesh Mathur, Nikhil Goyal, Siddart Rangachari, and Jithin Matthews. This latter team received a “Serendipitous Discovery” award from the judges for going beyond the problem space of the core case to present some findings in the data set about potential claims fraud.