The challenge: Predict the likelihood of heart attack among a group of Medicare patients. It may sound like a job for a medical team, but it was a team of Bentley graduate students who analyzed data to tackle how this challenge would affect a health insurance company. And their efforts won national accolades – the team of three students in Bentley’s Master of Business Analytics program placed second in the Humana-Mays Health Care Analytics Case Competition at Texas A&M University. They competed against more than 700 graduate students from 200 teams and 42 universities nationwide, beating out teams in the final round from the University of California at Los Angeles, Northwestern University and the University of California at Berkeley.
Teamwork and time management were keys to success for Bentley students Hanyin Ni, Uyanga Sumiya and Qi Xu in solving the assigned problems. With limited time, the students simultaneously ran 19 models with 40 combinations of data wrangling, variable selections and machine learning algorithms. (“Machine learning” is when computer programs process data and automatically improve their processes without being programmed to do so.)
To prepare for the competition, the students held regular team meetings where they identified, discussed and adjusted step-by-step analytics goals. “We researched the company and specific disease-related information and structured our interpretation of analysis based on business functions, stakeholders and key performance indicators,” Ni says.
What set the Bentley team apart from other teams, according to Associate Professor of Mathematical Sciences Mingfei Li, was each student’s ability to apply a broad knowledge of analytics, solid business thinking, business interpretation and communication skills to the competition.
Ni attributes many of the data analytics skills she’s learned to Bentley’s Master of Science in Business Analytics program and her work assisting Professor Li. As a research assistant, she has helped to analyze proteins and bio-markers related to Alzheimer’s disease and evaluated hospitals’ data to identify patterns in service quality and seasonal usage. The work has sharpened her ability to determine conditions required for certain predictive models.
A native of Shanghai, China, Ni became interested in analytics after working in marketing, operations and supply chain management. She recognized how important analytics were to plan marketing campaigns, production, inventories and logistics.
“Future managers will need to understand not only how to pick the right analytical tool for their business scenario but also to show how the statistical results will impact business,” Ni says. “I chose Bentley’s Analytics master’s program because it highlights the link between data science and business.”
Ni was introduced to health care analytics by Bentley alumnus Tyler Miguel MSBA ‘17, a data analyst at Blue Cross Blue Shield of Massachusetts. It is a field where Ni feels she can make a difference. “My analysis could help in the process of diagnosing diseases earlier or creating efficient medicine for targeted diseases,” she says. “It’s a meaningful way that I can contribute to human health.”