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 (D 2 CSM) 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.

  Utilizes five scenario-based studies to demonstrate how to use the D2CSM approach to address the real-world problems in healthcare services, which make the proposed approach easy to understand and to follow. Readers can learn and practice the D2CSM approach by following the demonstrated studies, which enable them to grasp and appreciate all the technical details about the systematic approach Presents an iHDS system to demonstrate how the D2CSM approach can be implemented to address practical decision analytics and support problems. Following the two walk-through examples for the iHDS system, readers can know how to put the D2CSM into practice Contents are self-contained and thus easy to read. The demonstrated studies (as shown in Chapters 3-7) for illustrating the working of the D2CSM approach, as well as the iHDS system for implementing the D2CSM approach practically in healthcare service management (as shown in Chapter 8), can be read separately and independently

  Inhalt
  Table of Contents ii.- List of Tables vii.- List of Figures.- Chapter 1 Introduction 1.- Chapter 2 Data Analytics and Modeling Methods for Healthcare Service Systems 35.- Chapter 3 Effects of Demand Factors on Service Utilization 52.- Chapter 4 Effects of Supply Factors on Wait Times 71.- Chapter 5 Integrated Prediction of Service Performance 95.- Chapter 6 An Adaptive Strategy for Wait Times Management 115.- Chapter 7 Spatio-Temporal Patterns in Patient Arrivals and Wait Times 130.- Chapter 8 An Intelligent Healthcare Decision Support System 176.- Bibliography 209.- Notation Index 237.- List of Abbreviations 240.