Faculty Profile

Mousumi  Banerjee, PhD

Mousumi Banerjee, PhD

  • Anant M. Kshirsagar Collegiate Research Professor of Biostatistics
  • Director of Biostatistics, Center for Healthcare Outcomes & Policy
  • Member, Rogel Cancer Center
  • Affiliated Faculty, Michigan Institute for Data Science
  • Affiliated Faculty, Center for South Asian Studies
  • M4150 SPH II
  • 1415 Washington Heights
  • Ann Arbor, Michigan 48109-2029

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 a faculty in the Rogel Cancer Center, Michigan Institute for Data Science, and the Center for South Asian Studies at Michigan. Dr. Banerjee received her Bachelors and Masters 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 machine learning, prognostic modeling, correlated data, survival analyses, competing risks with applications to healthcare delivery and outcomes research. She studies fundamental issues related to optimal quality and equitable care delivery, and disparities in healthcare outcomes. 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.

  • BIOSTAT524: Biostatistics for Clinical Researchers
  • BIOSTAT581: Longitudinal Models and Repeated Measures
  • BIOSTAT650: Applied Statistics I: Linear Regression

  • 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 machine learning, prognostic modeling, 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.

  • Xia R, Friese CR, Banerjee M. Residual-based Tree for Clustered Binary Data. Statistics and Its Interface, 14 (3), 295-308, 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.
  • Haymart MR, Reyes-Gastelum D, Caoili E, Norton EC, Banerjee M. The Relationship Between Imaging and Thyroid Cancer Diagnosis and Survival. Oncologist, 10.1634/theoncologist.2020-0159. doi:10.1634/theoncologist.2020-0159, 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.
  • Banerjee M, Reyes-Gastelum D, Haymart MR. Treatment-free Survival in Patients with Differentiated Thyroid Cancer. Journal of Clinical Endocrinology and Metabolism, 103:2720-2727, 2018
  • 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: http://dx.doi.org/10.1136/bmj.i3839
  • Banerjee M, Lao CD, Wancata LM, Muenz DG, Haymart MR, Wong SL. Implications of age and conditional survival estimates for patients with melanoma. Melanoma research, 26:77-82, 2016.
  • Davis M., Nallamothu B., Banerjee M., Bynum J.  Identification of four unique spending patterns among older adults in the last year of life challenges standard assumptions Health Affairs 1316-1323, 2016.
  • 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.
  • Helvie M, Chang J, Hendrick R, Banerjee M. Reduction in late-stage breast cancer incidence in the mammography era: Implications for overdiagnosis of invasive cancer. Cancer, 120: 2649-2656, 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, http://dx.doi.org/10.1155/2014/316935

  • American Statistical Association
  • International Biometric Society
  • International Indian Statistical Association
  • International Statistical Institute