Every day, numerous decisions must be made in healthcare systems, addressing a wide range of issues, including patient admissions, physician assignments, operating room scheduling, pharmaceutical inventory control, and ambulance dispatch. Conventionally, these decisions are made by experienced experts. However, human decision-makers may face challenges such as the unavailability of complete information, rapidly changing healthcare environments, personal biases, and prompt responses to medical emergence. Additionally, decision-makers often struggle to evaluate the effectiveness and possible consequences of their decisions.
This talk will introduce a set of scientific and systematic tools that leverage operations research techniques (originally developed to solve decision-making problems during World War II) and data collected in healthcare systems. The talk will begin with an overview of traditional healthcare decision-making approaches before delving into data-driven methodologies that have emerged in recent years. Subsequently, the speaker will share his experience over the years in tackling decision-making problems in healthcare systems in Hong Kong and the region, including emergency department patient flow modelling and optimization, medical appointment scheduling, vaccination strategies, and healthcare logistics. Finally, potential future directions for addressing healthcare decision-making challenges will be explored.
The supports by HKRGC (Refs: 27200419; 17204823; F-HKU704/22) and HMRF of the Health Bureau (Refs: 14202115; 21222881) for the projects to be presented in this talk are greatly acknowledged.
Professor Yong-Hong Kuo is Assistant Professor in the Department of Industrial and Manufacturing Systems Engineering, the University of Hong Kong. His current research focus is on the integration of systems modelling, discrete optimization, and data analytics for solving decision-making problems in service systems, where most of his applications are in the domains of healthcare service delivery and logistics and transportation services. His research, with his role as Principal Investigator, has been supported by a number of funding agencies, including Hong Kong Research Grants Council, Health and Medical Research Fund, Smart Traffic Fund, Innovation and Technology Fund, MTR Research Funding, Microsoft Research Asia, and Macao Science and Technology Development Fund. He has served the Operational Research Society of Hong Kong as President, on the Editorial Advisory/Review Boards of Decision Sciences Journal and Transportation Research Part E, and as Managing Guest Editor for several academic journals.
Clean water and clean air are vital for public health. This project focuses on developing high-efficiency and environmentally sustainable filters for removing harmful air/water pollutants. The team has developed novel architectures and functionalities for the filters to achieve high permeance, high removal efficiency, and excellent reusability.
