Better Care at Affordable Cost
Our Mission, Goals and Deliverables:
Our mission is to carry out state-of-the-art research in healthcare delivery, focusing on the operational and systems problems but also including related public health issues. The objective is to help develop a quality-and-efficiency driven healthcare delivery system in Hong Kong that is built upon data analytics and compatible to the Internet Age. Our research plan calls for in-depth studies on applying optimization and data analytics technologies to address the theme of the proposal, “better care at affordable cost, for a healthier life”, in three topical areas:
Planned deliverables from our studies include:
One of the major benefits from this project is to create a strong healthcare management research community in Hong Kong, which will help raise the level of local healthcare management practice to a world-class level, as well as stimulate the synergistic collaborations among researchers in operations management, systems engineering, and public health.
Tasks and Plan
What are our research tasks? Below we highlight the problems we plan to study and our proposed approaches, organized into three subject areas:
(1) hospital resource planning,
(2) healthcare data analytics, and
(3) population life-cycle studies.
ll studies in the three areas will be carried out based on healthcare practices and data in Hong Kong. Collectively, they will address the theme of this proposal, “better care at affordable cost, for a healthier life.”
Quality- and Efficiency-Driven Hospital Resource Planning and Management
Here, “hospital resource planning and management” includes that of both a single hospital and, more broadly, a cluster of hospitals. In Hong Kong, the latter refers to those managed by the Hospital Authority (HA).
Healthcare Data Analytics
Healthcare data analytics refers to the use of data mining, machine learning, and statistical learning techniques to process the vast amounts of data in healthcare delivery and management systems so as to identify customer/patient preferences and behavior patterns, spot hospital admission trends, and segment markets. Data analytics can be used to unlock new sources of economic value in healthcare delivery and provide fresh insights into better management of the healthcare value chain. However, grand challenges remain in how to process the ever-growing amount of patient-care data and information in a most efficient and cost-effective manner while preserving a high level of security and privacy protection and in how to best utilize these data to make better decisions. Another challenge is to provide intelligence over censored data: how to incorporate the intelligence garnered from data into decision tools to optimize the operations and logistics of the healthcare value chain. How can we fully appreciate clinical risks and provide a fair evaluation of hospitals, healthcare units, and healthcare professionals? How can we assess our quality of care and be sure that it is improving and not deteriorating?