Title: Hospital Capacity Planning during COVID-19
Inpatient hospital capacity has been a major focus and concern for many healthcare systems across the world throughout the COVID-19 pandemic. Despite numerous efforts to predict the number of COVID-19 infections over time, the uncertainty surrounding these predictions present an especially difficult challenge in the context of hospital capacity planning. In this work at the Massachusetts General Hospital (MGH), we demonstrate how our team leveraged data and analytics to help the hospital formulate both its plan for the surge in COVID-19 patients as well as its return back to "normal" operations as the COVID-19 population decreased.
Cecilia Zenteno is the Data & Analytics Senior Manager in the Healthcare Systems Engineering Department at Massachusetts General Hospital. Her team partners with providers and administrators to develop and apply data-driven models to optimize patient care processes. Cecilia received her Ph.D. in Operations Research from Columbia University and worked as post-doctoral fellow for the MGH-MIT Collaboration for two years before joining MGH full time in 2014.
Martin Copenhaver is an Operations Research Scientist at Massachusetts General Hospital. His research interests lie in the design and implementation of new health care systems with the use of tools from optimization and statistics. Martin received his Ph.D. from MIT's Operations Research Center where he was advised by Dimitris Bertsimas.