Rate My Professor Kathryn Colborn

Her research interests include the design and analysis of randomized controlled trials and cluster randomized trials, analysis of electronic health record data, health services and outcomes research, automated surveillance of postoperative infections, and development and validation of statistical methodologies for clinical prediction models involving machine learning and high-dimensional model selection. She has received extramural funding as principal investigator for NIH grants including R01HS027417, Automated Surveillance of Postoperative Infections (September 2020 to July 2025), and R03HS026019, Identification of postoperative infections using electronic health record and administrative claims data (April 2018 to March 2020). She has collaborated on numerous extramural research grants. Key publications include "Massage therapy versus simple touch to improve pain and mood in patients with advanced cancer: a randomized trial" (Annals of Internal Medicine, 2008), "Force of infection is key to understanding the epidemiology of Plasmodium falciparum malaria in Papua New Guinean children" (Proceedings of the National Academy of Sciences, 2012), "Assessment of a machine learning model applied to harmonized electronic health record data for the prediction of incident atrial fibrillation" (JAMA Network Open, 2020), "The association between obesity and postoperative outcomes in a broad surgical population: a 7-year American College of Surgeons National Surgical Quality Improvement analysis" (Surgery, 2023), and "Predicting intracranial pressure monitor placement in children with traumatic brain injury: a prospective cohort study to develop a clinical decision support tool" (Journal of the American Medical Informatics Association, 2026).