IE Seminar: Inverse Optimization for Measuring Clinical Pathway Concordance
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Clinical pathways outline standardized processes in the delivery of care for a specific disease. Clinical pathway concordance (CPC) refers to the degree of alignment between the actual care patients receive and the ideal care described in a clinical pathway. Measuring CPC is essential in monitoring variations in the healthcare system, identifying bottlenecks, providing data-driven evidence to inform health policy decisions, and ultimately improving care delivery. We develop a general methodology for measuring CPC based on inverse optimization, apply our novel concordance metric to a real dataset of colon cancer patients, and show that it has a statistically significant association with survival. Finally, we analyze the sources of variations in the patient population and discuss potential initiatives to improve the healthcare system.
Bio: Nasrin Yousefi is a Ph.D. Candidate in the Department of Mechanical and Industrial Engineering at the University of Toronto. Her research interests are data-driven optimization and decision-making under uncertainty with applications in healthcare operations management. In her PhD, she has used inverse optimization to measure the degree of alignment between standard care and actual care. She completed her MSc at Koc University, Istanbul, and her BSc at the Sharif University of Technology, Tehran, both in Industrial Engineering.
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Google Scholar: https://scholar.google.com/citations?user=yijd6bUAAAAJ&hl=en