【Time】July 18, 2013 (Thursday)  13:30~14:30

【Venue】Room N412, Shunde Building

【Speaker】Mr.Xiaolei Xie, University of Wisconsin, Madison.

【Title】Hospital Rapid Response System: Modeling, Analysis and Improvement

【Abstract】The number of preventable death in U.S. is astonishingly high, upward of 100,000 per year. This has prompted a national initiative to create and deploy rapid response team (RRT) to quickly evaluate, triage, and treat patients with clinical signs of deterioration to reduce the frequency and severity of negative outcomes. However, research studies show that improvement after RRT implementation is not consistent. Since multiple departments are involved in the acute care delivery process, the study of rapid response system (RRS), rather than focusing on RRT only, is of crucial importance. We present analytical models from systems perspective to address such issues. Analytical formulas to evaluate the proposed measures are developed. System-theoretic properties are investigated. A bottleneck analysis method is introduced. Indicators based on the data collected on the hospital floor are discovered to facilitate the identification and mitigation of bottleneck responses. Finally, a case study at a U.S. hospital is introduced to illustrate the applicability of this work. The models and methods developed in this study will provide a quantitative tool to analyze and improve hospital rapid response operations from a system point of view.

【Biography】Xiaolei Xie is currently a Ph.D. candidate in Department of Industrial and Systems Engineering at University of Wisconsin, Madison. He received the B.S. degree in Mechanical Engineering from Beihang University, China and the M.S. degree in Industrial and Operations Engineering from the University of Michigan, Ann Arbor. His research area is in healthcare systems engineering, focusing on developing analytical models for care delivery systems. He has worked as a summer research trainee at Mayo Clinic and has been collaborating with University of Wisconsin Health Systems and University of Kentucky Hospital, working on problems such as hospital rapid response study, discharge process improvement and advanced access scheduling design.