Speaker: Seokjun Youn, Department of Information and Operations Management, Texas A&M University
Title: Examining Impacts of Clinical Practice Variation on Operational Performance
Abstract: This study explores whether and how lower variations in clinical practice improve hospital operational performance. The extant literature discusses geographical variations in healthcare but often ignores clinical variations that may be prevalent in a hospital. To fill this research gap, we define practice variation as all variation not resulting from patient-mix, and we observe a broad practice variation spectrum across hospitals. Using statistical process control as a theoretical lens, we hypothesize that such practice variation adversely affects operational performance. This study tests this hypothesis using six years of a high-volume inpatient data from New York and Florida, and after accounting for the dynamic endogeneity of practice variation and operational performance, we find supporting evidence that greater practice variation is associated with longer patient stays and higher total cost per capita. Interestingly, this phenomenon is even stronger when a hospital provides a higher-quality patient experience because such a hospital tends to provide more responsive care, which is often resource-intensive. To suggest actionable improvement plans, we also delve into the granular level of practice variation, including the risk associated with under-ordering laboratory/radiology tests. This study highlights the importance of measuring and understanding practice variation and suggests how managers and policy-makers can use the findings to design better payment reform models.
Bio: Seokjun Youn is a PhD candidate in the Department of Information and Operations Management, Mays Business School at Texas A&M University. His research to date focuses on the domains of healthcare operations and supply chain management. His research interests in healthcare domain include 1) healthcare payment models and applications to operations, 2) clinical practice variation, its causes, and impacts, and 3) capacity planning and scheduling in healthcare. He enjoys exploiting large, granular datasets and leveraging the emerging field of data analytics combined with optimization tools. He holds a Master’s degree in Industrial Engineering from Texas A&M University and a Bachelor’s degree in Industrial Engineering from Seoul National University, South Korea. Prior to starting his graduate studies, Seokjun worked as an Air Force officer from South Korea with a specialty in aircraft armament systems maintenance.