Patricia C. Conroy
Papers
1
Total Citations
7
H-Index
1
About
Patricia C. Conroy is a surgical outcomes researcher whose work sits at the intersection of data science and clinical decision-making. Her primary research focuses on developing predictive models to improve patient outcomes in colorectal surgery, with a particular emphasis on defining and forecasting "textbook outcomes"—the ideal postoperative recovery without complications. Her most cited work, "A Novel Machine Learning Approach to Predict Textbook Outcome in Colectomy" (2023, 7 citations), addresses a critical gap in surgical risk assessment. While existing tools focus on predicting complications, Conroy’s model instead identifies patients most likely to achieve an uncomplicated recovery, empowering surgeons to better counsel high-risk individuals and optimize perioperative care. This shift from risk-averse to goal-oriented prediction represents a meaningful contribution to personalized surgical planning. Though early in her career, Conroy’s work has already been recognized for its practical clinical utility, and her approach is being explored for application in other low-mortality procedures. Her research exemplifies how machine learning can refine surgical benchmarks and improve shared decision-making at the bedside.
Research Focus
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Top Papers
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