Data Analytics & IT work will be focused on software tools necessary for data cleaning, retrieval, and management; data analyses and visualization; and analytics reporting for evaluation and implementation. The group will also source data networks and warehouse solutions for seamless and cost-effective access to the research community.
Brahmajee Nallamothu is Professor in the Division of Cardiovascular Diseases and the Department of Internal Medicine at the University of Michigan. He received his MD from Wayne State University and completed his residency at the University of Michigan. He also completed research training through an Agency for Healthcare Research and Quality (AHRQ) fellowship at the University of Michigan School of Public Health. Dr. Nallamothu’s research interests focus on improving the use and performance of coronary angioplasty and stenting in acute myocardial infarction and the care of patients with cardiac arrests. His work has led to long-term collaborative efforts with investigators in various Divisions in Internal Medicine and other Departments and Schools across campus. Most recently his team has become interested in examining new analytic tools and methods for measuring quality and costs of cardiovascular services.
Jenna Wiens is Assistant Professor of Computer Science and Engineering (CSE) in the College of Engineering at the University of Michigan and heads the MLD3 research group. Her primary research interests lie at the intersection of machine learning, data mining, and healthcare. The overarching goal of her research is to develop the computational methods needed to help organize, process, and transform patient data into actionable knowledge. Her work has applications in modeling disease progression and predicting adverse patient outcomes. Prof. Wiens has been focused for several years on developing accurate patient risk stratification approaches with the goal of reducing the rate of healthcare-associated infections among US hospital patients.
Sebastian Zöllner is a Professor of Biostatistics. He also holds an appointment in the Department of Psychiatry. Dr. Zöllner joined the University of Michigan after a postdoctoral fellowship in the Department of Human Genetics at the University of Chicago. His research effort is divided between generating new methods in statistical genetics and analyzing data. The general thrust of his work is problems from human genetics, evolutionary biology, and statistical population biology.
- Develop a secure, robust, flexible, and adaptable research analytics platform for precision health at U-M
- Facilitate a working group of faculty and researchers representing diverse perspectives within precision health
- Pursue corporate partnerships/external funding to strengthen U-M’s reputation as a leader in this space
- Design and create an accessible, secure computational environment
- Encourage and facilitate the development and sharing of reusable data analytics tools
- Develop IT infrastructure for the integration of clinical decision support tools, to enable real-time prospective validation capabilities
- Coordinate with Cohort Development on the integration, storage, and organization of multimodal data within the platform, to allow for broader campus-wide use.
- Coordinate with Health Implementation to enable fast dissemination of results, e.g., validated treatments and corresponding protocols
- Build a broader community of researchers and students with interests in data analytics for health, and establish interdisciplinary partnerships to tackle precision health challenges in new ways