TY - CHAP
T1 - An Intelligent Healthcare Decision Support System
AU - Tao, Li
AU - Liu, Jiming
PY - 2019/5/9
Y1 - 2019/5/9
N2 - In the previous chapters, we showed how to systematically utilize the four specific methods, i.e., Structural Equation Modeling (SEM)-based analysis, integrated prediction, service management strategy design and evaluation, and behavior-based autonomy-oriented modeling, to address practical healthcare service management problems. This chapter presents an intelligent healthcare decision support (iHDS) system that implements the four methods to develop, analyze, investigate, support, and provide advice for healthcare-related decisions. The iHDS system provides the architecture and components for user interactions, data collection and processing, data-driven inferences and simulations, and decision analytics and support to generate solutions for various healthcare analytics and decision-making problems. This chapter also describes two cases to illustrate how the iHDS system works to address practical healthcare analytics problems. One case illustrates how the components and methods work to generate adaptive solutions for allocating time blocks in operating rooms (ORs), while the other addresses the need for adaptive decision support in regional healthcare resource allocation that has the advantage of reducing healthcare performance disparities.
AB - In the previous chapters, we showed how to systematically utilize the four specific methods, i.e., Structural Equation Modeling (SEM)-based analysis, integrated prediction, service management strategy design and evaluation, and behavior-based autonomy-oriented modeling, to address practical healthcare service management problems. This chapter presents an intelligent healthcare decision support (iHDS) system that implements the four methods to develop, analyze, investigate, support, and provide advice for healthcare-related decisions. The iHDS system provides the architecture and components for user interactions, data collection and processing, data-driven inferences and simulations, and decision analytics and support to generate solutions for various healthcare analytics and decision-making problems. This chapter also describes two cases to illustrate how the iHDS system works to address practical healthcare analytics problems. One case illustrates how the components and methods work to generate adaptive solutions for allocating time blocks in operating rooms (ORs), while the other addresses the need for adaptive decision support in regional healthcare resource allocation that has the advantage of reducing healthcare performance disparities.
U2 - 10.1007/978-3-030-15385-4_8
DO - 10.1007/978-3-030-15385-4_8
M3 - Chapter
SN - 9783030153830
T3 - Health Information Science
SP - 131
EP - 154
BT - Healthcare Service Management: A Data-Driven Systems Approach
A2 - Tao, Li
A2 - Liu, Jiming
PB - Springer Cham
ER -