Healthcare Service Management

A Data-Driven Systems Approach

  • Li Tao
  • Jiming Liu

Part of the Health Information Science book series (HIS)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Li Tao, Jiming Liu
    Pages 1-22
  3. Li Tao, Jiming Liu
    Pages 35-49
  4. Li Tao, Jiming Liu
    Pages 51-68
  5. Li Tao, Jiming Liu
    Pages 69-84
  6. Li Tao, Jiming Liu
    Pages 85-96
  7. Li Tao, Jiming Liu
    Pages 131-154
  8. Back Matter
    Pages 155-168

About this book


Healthcare service systems are of profound importance in promoting the public health and wellness of people. This book introduces a data-driven complex systems modeling approach (D2CSM) to systematically understand and improve the essence of healthcare service systems. In particular, this data-driven approach provides new perspectives on health service performance by unveiling the causes for service disparity, such as spatio-temporal variations in wait times across different hospitals.

The approach integrates four methods -- Structural Equation Modeling (SEM)-based analysis; integrated projection; service management strategy design and evaluation; and behavior-based autonomy-oriented modeling -- to address respective challenges encountered in performing data analytics and modeling studies on healthcare services. The thrust and uniqueness of this approach lies in the following aspects:

  • Ability to explore underlying complex relationships between observed or latent impact factors and service performance.
  • Ability to predict the changes and demonstrate the corresponding dynamics of service utilization and service performance.
  • Ability to strategically manage service resources with the adaptation of unpredictable patient arrivals.
  • Ability to figure out the working mechanisms that account for certain spatio-temporal patterns of service utilization and performance.

To show the practical effectiveness of the proposed systematic approach, this book provides a series of pilot studies within the context of cardiac care in Ontario, Canada. The exemplified studies have unveiled some novel findings, e.g., (1) service accessibility and education may relieve the pressure of population size on service utilization; (2) functionally coupled units may have a certain cross-unit wait-time relationship potentially because of a delay cascade phenomena; (3) strategically allocating time blocks in operating rooms (ORs) based on a feedback mechanism may benefit OR utilization; (4) patients’ and hospitals’ autonomous behavior, and their interactions via wait times may bear the responsible for the emergence of spatio-temporal patterns observed in the real-world cardiac care system. Furthermore, this book presents an intelligent healthcare decision support (iHDS) system, an integrated architecture for implementing the data-driven complex systems modeling approach to developing, analyzing, investigating, supporting and advising healthcare related decisions.

In summary, this book provides a data-driven systematic approach for addressing practical decision-support problems confronted in healthcare service management. This approach will provide policy makers, researchers, and practitioners with a practically useful way for examining service utilization and service performance in various ``what-if" scenarios, inspiring the design of effectiveness resource-allocation strategies, and deepening the understanding of the nature of complex healthcare service systems.


Complex healthcare service systems Healthcare Decision Support System Autonomy-oriented computing (AOC) Data-driven complex systems modeling D2CSM Wait time management Structural Equation Modeling (SEM)-based analysis, integrated prediction service management strategy design and evaluation behavior-based autonomy-oriented modeling

Authors and affiliations

  1. 1.Southwest UniversityBeibei, Chong QingChina
  2. 2.Hong Kong Baptist UniversityKowloonHong Kong

Bibliographic information

  • DOI
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-15383-0
  • Online ISBN 978-3-030-15385-4
  • Series Print ISSN 2366-0988
  • Series Online ISSN 2366-0996
  • Buy this book on publisher's site
Industry Sectors
Chemical Manufacturing
Finance, Business & Banking
IT & Software
Consumer Packaged Goods
Energy, Utilities & Environment