Process Mining Techniques for Managing and Improving Healthcare Systems

✍ Scribed by Maha Zayoud

• Publisher: CRC Press
• Year: 2023
• Tongue: English
• Leaves: 215
• Edition: 1
• Category: Library

✦ Synopsis

This book discusses a new process mining method along with a detailed comparison between different techniques that provide a complete vision of the process of data acquisition, data analysis, and data prediction.

Process Mining Techniques for Managing and Improving Healthcare Systems offers a new framework for process learning which is probabilistic and enables the process to be learned in an accumulative manner. The steps of prediction modeling and building the required knowledge are highlighted throughout the book, along with a strong emphasis on the correlation between the healthcare domain and technology including the different aspects, such as: managing records, information, and procedures; early detection of diseases; and the improvement of accuracy in choosing the right treatment procedures.

This reference provides a wealth of knowledge for practitioners, researchers, and students at the basic and intermediary levels working within the healthcare system, computer science, electronics and communications, as well as medical providers and also hospital management entities.

✦ Table of Contents

Cover
Half Title
Title Page
Copyright Page
Contents
List of Figures
List of Tables
List of Abbreviations
Acknowledgments
Preface
Introduction
Objectives and Overview
Chapter 1: Healthcare System
1.1. Definition of Healthcare System
1.2. Basic Components in Healthcare Systems
1.3. Healthcare System Main Issues
1.4. State of the Art in the Healthcare System
1.5. Healthcare Industry Management System
1.6. Conclusion
Chapter 2: Data Mining and Management Information Systems
2.1. Basic Elements of the Management Process
2.2. Management Information Systems (MIS)
2.3. Management Information Systems and Strategies
2.4. Innovating Business Process
2.5. The State of the Art of Data Mining (DM) Techniques
2.6. Data Mining vs. Process Mining
2.7. Data Mining IEEE Algorithms
2.8. Process Mining Techniques
2.9. Conclusion
Chapter 3: Process Mining and Big Data in Healthcare
3.1. Introduction
3.2. Description of Process Mining
3.3. Petri Nets
3.4. Algorithms Survey
3.5. Process Mining Algorithms Selections
3.6. Big Data (BD) and Healthcare System
3.7. Problems Definitions
3.8. Conclusion
Chapter 4: The Proposed β Algorithm for Healthcare System
4.1. Introduction
4.2. Process Mining Classifications
4.3. Applications of Process Mining Algorithms
4.4. Process Mining Challenges
4.5. A Differentiation Study on Learning Processes Approaches
4.6. Proposed Framework β Algorithm
4.7. Prediction toward Knowledge
4.8. Applying the β Algorithm in Healthcare
4.9. Learning Events Probabilities
4.10. Petri Nets of the β Algorithm
4.11. Data Manipulation
4.12. Basic Outlines of β Algorithm
4.13. Conclusion
Chapter 5: Building a Hospital Management Platform
5.1. “MYL” Platform Overview
5.2. Applying “MYL” in Emergency Departments of a Hospital
5.3. Optimizing the Emergency Room Example Using the “MYL” Platform
5.4. Using the “MYL” Platform to Improve Health Awareness
5.5. The Impact of Process Mining for Building Knowledge
5.6. Conclusion
Chapter 6: The Advantages of Using the MYL Platform
6.1. The Economic Benefits of Using Process Mining
6.2. Quality Improvement of the Medical Service
6.3. Analysis of Patient Satisfaction
6.4. Conclusion
Conclusion and Limitations
Appendix A: Appendix: The β Algorithms
Appendix B: Appendix: Rational Database
Appendix C: Appendix: The β Algorithm Using Hadoop Big Data Concept
Appendix D: Appendix: An Overview of the MYL Framework’s Source Code
Appendix E: Appendix: MYL Software Output Examples
References
Index