Mousumi Banerjee, PhD
- Anant M. Kshirsagar Collegiate Research Professor of Biostatistics
- Research Professor, Global Public Health
- Director, Global StatCore
- Director of Biostatistics, Pediatric Cardiac Critical Care Consortium (PC4) Analytic Center
Mousumi Banerjee is Anant M. Kshirsagar Collegiate Research Professor, Department
of Biostatistics; Research Professor, Global Public Health, University of Michigan
School of Public Health (UM-SPH); Faculty Affiliate, Michigan Institute for Data Science
(MIDAS), University of Michigan (UM). She is also a member of the UM Rogel Cancer
Center, the Institute for Healthcare Policy and Innovation, and the Center for Global
Health Equity. Dr. Banerjee serves as Director of Biostatistics, Pediatric Cardiac
Critical Care Consortium (PC4) Analytic Center, a federally funded multi-institution
collaborative committed to improving the quality of care for patients with critical
pediatric and congenital cardiovascular disease in North America. She is also Director
of Global StatCore, an initiative intended to enhance biostatistical support of global
public health research, education, and training at UM-SPH, and in collaboration with
international partners across the globe.
Dr. Banerjee received her Bachelor’s and Master’s degrees in Statistics from the Indian Statistical Institute in Kolkata, India and her PhD in Statistics from the University of Wisconsin-Madison. Her methodological research focuses on predictive modeling, machine learning, causal inference, correlated data, survival analyses, and competing risks with primary applications to health services and outcomes research. She studies health disparities and fundamental issues related to optimal quality and equitable care delivery in the population. Dr. Banerjee works closely with collaborators in the fields of cancer, pediatric heart disease, neurology, surgery, and social determinants of health. She is a Fellow of the American Statistical Association, and an elected member of the International Statistical Institute..
American Statistical Association
International Biometric Society
International Indian Statistical Association
International Statistical Institute
- PhD, Statistics, University of Wisconsin, Madison, 1994
- MStat, Statistics, Indian Statistical Institute, Calcutta, India, 1988
- BStat, Statistics, Indian Statistical Institute, Calcutta, India, 1986
I have broad interests and expertise in developing statistical methodology and applying it in biomedical research, particularly cancer and pediatric heart disease. My methodological research focuses on predictive modeling, machine learning, causal inference, correlated data, survival analysis, and competing risks, with applications to health services and outcomes research.
I study fundamental issues related to cancer care delivery and outcomes in the population, using national registries such as the SEER and National Cancer Database (NCDB), claims data such as Medicare and Optum, and the linked SEER-Medicare database. Since 2016, I have been engaged in developing statistical methods for quality assessment to drive quality improvement initiatives within the Pediatric Cardiac Critical Care Consortium (PC4), a multi-institutional quality collaborative for children with critical cardiovascular disease.
Reynolds EL, Callaghan BC, Gaies M, Banerjee M. Regression Trees and Ensemble for Multivariate Outcomes. Sankhya B. 2023; 10.1007/s13571-023-00301-z.
Gaies M, Olive MK, Owens GE, Charpie JR, Zhang W, Pasquali SK, Klugman D, Costello JM, Schwartz SM, Banerjee M. Methods to enhance causal inference for assessing impact of clinical informatics platform implementation. Circulation: Cardiovascular Quality and Outcomes. 2023;16(2):e009277.
Chen DW, Banerjee M, He X, Miranda L, Watanabe M, Veenstra CM, Haymart MR. Hidden Disparities: How Language Influences Patients' Access to Cancer Care. J Natl Comprehensive Cancer Network. 2023; (9):951-959.e1. doi: 10.6004/jnccn.2023.7037. PMID: 37673110.
Alten JA, Cooper DS, Klugman D, Zhang W, Banerjee M, Gaies M. Preventing Cardiac Arrest in the Cardiac Intensive Care Unit through Multicenter Collaboration. JAMA Pediatrics. 2022;176(10):1027-1036..
Xia R, Friese CR, Banerjee M. Residual-based Tree for Clustered Binary Data. Statistics and Its Interface, 14 (3), 295-308, 2021.
Noone AM, Lam C, Smith A, Nielsen M, Boyd E, Mariotto A, Banerjee M. Machine Learning Methods to Identify Missed Cases of Bladder Cancer in Population-Based Registries. JCO Clinical Cancer Informatics, 5: 641-653, 2021.
Pasquali SK, Banerjee M, Romano JC, Normand ST. Hospital Performance Assessment in Congenital Heart Surgery: Where Do We Go From Here? Ann Thorac Surg, 109(3):621-626. doi:10.1016/j.athoracsur.2020.01.002, 2020.
Reynolds E, Callaghan B, Banerjee M. SVM-CART for Disease Classification. Journal of Applied Statistics, 46:16, 2987-3007, doi:https://doi.org/10.1080/02664763.2019.1625876, 2019.
Banerjee M. Reynolds E, Andersson HB, Nallamothu B. Tree-based Analysis: A Practical Approach to Create Clinical Decision Making Tools. Circulation: Cardiovascular Quality and Outcomes, 12(5):e004879, https://doi.org/10.1161/CIRCOUTCOMES.118.004879, 2019.
Stenmark MH, Shumway D, Guo C, Vainshtein J, Mierzwa M, Jagsi R, Griggs JJ, Banerjee M. Influence of Human Papillomavirus on Clinical Presentation of Oropharyngeal Carcinoma in the United States. The Laryngoscope, 127:2270-2278, 2017.
Banerjee M, Weibel J, Guo C, Gay B, Haymart M. Use of Imaging Tests after Primary Treatment of Thyroid Cancer in the United States: Population Based Retrospective Cohort Study Evaluating Death and Recurrence. British Medical Journal, 2016, 354:i3839, doi: https://www.bmj.com/content/354/bmj.i3839
Friese CR, Xia R, Ghaferi AA, Birkmeyer JD, Banerjee M. Magnet hospital recognition and surgical mortality. Health Affairs, 34:6986-6992, 2015.
Veenstra CM, Regenbogen SE, Hawley ST, Abrahamse P, Banerjee M, Morris AM. Association of paid sick leave with job retention and financial burden among working patients with colorectal cancer. JAMA, 314:2688-2690, 2015.
Chen LM, Wilk AS, Thumma JR, Birkmeyer JD, Banerjee M. Use of medical consultants for hospitalized surgical patients: an observational cohort study. JAMA Intern Med, 174:1470-1477, 2014.
Banerjee M, Filson CP., Xia R., Miller DC. Logic Regression for Provider Effects on Kidney Cancer Treatment Delivery. Computational and Mathematical Methods in Medicine, 2014. Article ID 316935, 9 pages, https://www.hindawi.com/journals/cmmm/2014/316935/
Areas of Expertise: Biostatistics