Mousumi Banerjee is Anant M. Kshirsagar Collegiate Research Professor of Biostatistics in the School of Public Health and Director of Biostatistics at the Center for Healthcare Outcomes and Policy at the University of Michigan. She is also faculty in the Rogel Cancer Center and the Center for South Asian Studies at U-M.

What are your research interests, broadly?

My broad interests are in developing and applying statistical methodology for health care delivery and outcomes research. My methods research focuses on predictive modeling, machine learning, multilevel models, longitudinal analyses, survival analyses, and competing risks. I study fundamental issues related to disease prognostication, as well as optimal quality and equitable care delivery, and disparities in health care outcomes. I work closely with collaborators in the fields of cancer, pediatric heart disease, neurology, surgery, and social determinants of health. I am a Fellow of the American Statistical Association, and an elected member of the International Statistical Institute.

Please talk a little about your most recent projects and/or publications.

Cancer recurrence is a critically important issue for patients, their families, and their providers. Yet, population-based cancer registries currently do not capture information about recurrence. I am currently developing a machine-learning-based tandem approach, integrating data from population-based cancer registries, claims data, and electronic health records to identify cancer recurrence at the population level. Findings from our study will enable recurrence risk prediction and risk stratification at the population level. We recently published a study using similar methods to identify missed cases of bladder cancer in the US cancer registry (Noone et al., JCO Clinical Cancer Informatics, 2021).

I have also been working with the Pediatric Cardiac Critical Care Consortium (PC⁴), a quality collaborative, for the last six years. PC⁴ aims to improve the quality of care to patients with critical pediatric and congenital cardiovascular disease in North America and abroad. Formed in 2009 with National Institutes of Health funding, PC⁴ is a unique collaborative of leaders in pediatric cardiac critical care, cardiac surgery, and cardiology, representing a diverse group of centers caring for these vulnerable patients.  Infants with critical heart disease that requires surgery are at increased risk for subsequent neurodevelopmental delays. Leveraging data from PC⁴ and the Cardiac Neurodevelopment Outcomes Collaborative (CNOC), I am currently developing new statistical methods to determine critical thresholds of inadequate cerebral oxygen delivery that may put these infants at risk for neurologic injury and poor neurodevelopmental outcomes.

How does your research help people? Whom does it help?

My research has always been motivated by questions that are critically important for clinical decision-making by patients, providers, and patient families.

How do a precision health approach and methods enrich your work?

By using unique and reusable data sources and developing innovative strategies, I am better positioned to obtain a comprehensive view toward creating individualized, actionable decisions that ultimately benefit a patient.

What do you like to do when you aren’t doing research?

When I am not doing research, I like to sing, read and write poetry, travel, cook, and generally enjoy the little pleasures of life with my family and friends.