| Description |
1 online resource (xvii, 168 pages) : illustrations |
| Series |
Health information science, 2366-0988 |
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Health information science.
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| Contents |
Intro; Contents; List of Abbreviations; List of Figures; List of Tables; 1 Introduction; 1.1 Complex Healthcare Service Systems; 1.1.1 A Conceptualization of Healthcare Service Systems; 1.1.2 Complexity and Self-Organizing Nature; 1.1.3 Interactions; 1.2 Practical Healthcare Service Management Problems; 1.2.1 Discovering the Effects of Impact Factors on Wait Times; 1.2.2 Estimating the Changes in Wait Times; 1.2.3 Designing and Evaluating Strategies for Shortening Wait Times; 1.2.4 Characterizing Spatio-Temporal Patterns in Wait Times; 1.3 A Data-Driven Complex Systems Modeling Approach |
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1.3.1 SEM-Based Analysis1.3.2 Integrated Prediction; 1.3.3 Service Management Strategy Design and Evaluation; 1.3.4 Behavior-Based Autonomy-Oriented Modeling; 1.4 Research Context: A Cardiac Care System in Ontario; 1.5 Structure of This Book; 2 Data Analytics and Modeling Methods for Healthcare Service Systems; 2.1 Basic Notations and Concepts; 2.2 Empirical Identification of the Relationships Between Variables; 2.2.1 Types of Relationships; 2.2.2 Multivariate Analysis; 2.3 Characterization of System Behavior; 2.3.1 Stochastic Modeling and Simulation; 2.3.2 System Dynamics |
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2.3.3 Individual-Based Modeling2.4 Summary; 3 Effects of Demand Factors on Service Utilization; 3.1 Introduction; 3.2 The Effects of Geodemographic Profiles; 3.2.1 Hypotheses; 3.2.1.1 The Direct Effect of Population Size on Service Utilization; 3.2.1.2 The Direct Effect of Age Profile on Service Utilization; 3.2.1.3 The Moderating Effects of Service Accessibility; 3.2.1.4 The Moderating Effects of Educational Profile; 3.2.2 The Conceptual Model; 3.3 SEM Tests and Results; 3.3.1 Aggregated Data; 3.3.2 Two-Step SEM Tests; 3.3.3 Test Results; 3.3.3.1 Measurement Model |
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3.3.3.2 The Effects of Population Size and Age Profile on Service Utilization3.3.3.3 The Effects of Service Accessibility and Educational Profile on Service Utilization; 3.4 Discussion; 3.5 Summary; 4 Effects of Supply Factors on Wait Times; 4.1 Introduction; 4.2 The Effects of a Unit's Characteristics on Wait Times in a Subsequent Unit; 4.2.1 Hypotheses; 4.2.1.1 Within-Unit Relationships; 4.2.1.2 Cross-Unit Relationships; 4.2.2 The Conceptual Model; 4.3 SEM Tests and Results; 4.3.1 Aggregated Data; 4.3.2 SEM Tests; 4.3.3 Test Results; 4.3.3.1 Within-Unit Relationships |
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4.3.3.2 Cross-Unit Relationships4.4 Discussion; 4.5 Summary; 5 Integrated Prediction of Service Performance; 5.1 Introduction; 5.2 Integrated Prediction; 5.2.1 SEM-Based Analysis; 5.2.2 Prediction; 5.2.3 Queueing Model Simulation; 5.3 Estimating the Performance of Cardiac Surgery Services; 5.3.1 Aggregated Data; 5.3.2 Relationships Between Demographic Factors and Service Characteristics; 5.3.3 Service Performance Prediction; 5.3.4 The MSMQ-EC Queueing Model; 5.3.5 Prediction Results; 5.3.5.1 The Results of SEM Tests and Service Utilization Estimation |
| Summary |
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 |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Health services administration.
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Health services administration -- Data processing
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Mathematical models.
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Health Services Administration
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Medical Informatics
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Data Analysis
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Models, Theoretical
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mathematical models.
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POLITICAL SCIENCE -- Public Policy -- Social Security.
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POLITICAL SCIENCE -- Public Policy -- Social Services & Welfare.
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Mathematical models
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Health services administration
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Health services administration -- Data processing
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| Form |
Electronic book
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| Author |
Liu, Jiming, 1962- author.
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| ISBN |
9783030153854 |
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3030153851 |
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9783030153847 |
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3030153843 |
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