Healthcare Systems Management Methodologies And Applications

This edited volume focuses on research conducted in the area of healthcare systems management. Chapters are extensions of works presented at the International Conference on Management of Ergonomic Design, Industrial Safety and Healthcare Systems. The book addresses the need to have the knowledge of technological and resource management, clinical performances and quality of healthcare delivery systems in order to make hospital systems well and adequately designed and operationally effective ensuring the quality of healthcare to patients. It is a useful resource for students, researchers, industrial professionals and design engineers.

As health care organization leaders use data more consistently in decision making, it is important they understand the quantitative methods that help convert data to information. Quantitative Methods in Health Care Management provides important insights into the various quantitative methods, detailing many different problems and their solutions. It contains numerous helpful exhibits and graphics that explain and demonstrate the methods presented. It also provides a readable narrative for the manager who wants a high-level refresher on quantitative methods.”

The book discusses concepts and theories of general management and their specific applications related to public health and health care. Each chapter highlights the ideas and usefulness of different approaches in the context of health management. It addresses problems in different areas of healthcare systems management. It offers solutions in improving the performance, efficiency, and effectiveness of health programs and systems. Some of the topics covered in the book include health systems and policy, epidemiology, biostatistics, population dynamics, health economics and finance, logistics and supply chain, health research, health communication, quality management in health, and legal and ethical issues in health. The book serves as an indispensable resource for the faculties and students of health management or public health globally as well as healthcare professionals and researchers.

This Briefs Series book illustrates in depth a concept of healthcare management engineering and its domain for hospital and clinic operations. Predictive and analytic decision-making power of management engineering methodology is systematically compared to traditional management reasoning by applying both side by side to analyze 26 concrete operational management problems adapted from hospital and clinic practice. The problem types include: clinic, bed and operating rooms capacity; patient flow; staffing and scheduling; resource allocation and optimization; forecasting of patient volumes and seasonal variability; business intelligence and data mining; and game theory application for allocating cost savings between cooperating providers. Detailed examples of applications are provided for quantitative methods such as discrete event simulation, queuing analytic theory, linear and probabilistic optimization, forecasting of a time series, principal component decomposition of a data set and cluster analysis, and the Shapley value for fair gain sharing between cooperating participants. A summary of some fundamental management engineering principles is provided. The goal of the book is to help to bridge the gap in mutual understanding and communication between management engineering professionals and hospital and clinic administrators. The book is intended primarily for hospital/clinic leadership who are in charge of making managerial decisions. This book can also serve as a compendium of introductory problems/projects for graduate students in Healthcare Management and Administration, as well as for MBA programs with an emphasis in Healthcare.

Effective healthcare delivery is a vital concern for citizens and communities across the globe. The numerous facets of this industry require constant re-evaluation and optimization of management techniques. The Handbook of Research on Healthcare Administration and Management is a pivotal reference source for the latest scholarly material on emerging strategies and methods for delivering optimal healthcare opportunities and solutions. Highlighting issues relating to decision making, process optimization, and technological applications, this book is ideally designed for policy makers, administrators, students, professionals, and researchers interested in achieving superior healthcare solutions.

Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. Covers data analysis, management and security concepts and tools in the healthcare domain Highlights electronic medical health records and patient information records Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining Includes multidisciplinary contributions in relation to healthcare applications and challenges

This book covers the introduction, theory, development and applications of type-2 fuzzy logic systems, which represent the current state-of-the-art in various domains such as control applications, power plants, health care, image processing, mathematical applications etc. The book is also rich in discussing different applications in order to give the researchers a flavor of how type-2 fuzzy logic is designed for different types of problems. Type-2 fuzzy logic systems are now used extensively in engineering applications for many purposes. In simple language, this book covers the practical use of type-2 fuzzy logic and its optimization through different training methods. Furthermore, this book maintains the relationship between mathematics and practical implementations in the real world. This book chapter also contains the proper comparisons with available literature work. It shows that the presented enhanced techniques have better results. This book would serve as a handy reference guide for a variety of readers, primarily targeting research scholars, undergraduate and postgraduate researchers and practicing engineers working in Type-2 fuzzy logic systems and their applications.

The scientific theme of the book is “Virtualisation – a multifaceted key enabler of Industry 4.0 from holonic to cloud manufacturing” which is addressed in the framework of cyber-physical system development. The book approaches cyber-physical systems for manufacturing with emergent digital technologies: Internet of Things, digital twins (based on the virtualization of production models embedded in the design, virtual commissioning, optimization and resilience of processes and fault tolerance of resources), big data, cloud control and computing, machine learning and cobots, that are applied in the book’s chapters to industry and service sectors such as manufacturing, energy, logistics, construction and health care. The novelty of this approach consists in interpreting and applying the characteristics of RAMI4.0—the reference architecture model of the Industry 4.0 framework—as combinations of virtualized cyber-physical system elements and IT components in life cycle value stream models. The general scope of the book is to foster innovation in smart and sustainable manufacturing and logistics systems and in this context to promote concepts, methods and solutions for the digital transformation of manufacturing through service orientation in holonic and agent-based control with distributed intelligence. The book’s readership is comprised by researchers and engineers working in the manufacturing value chain area who develop and use digital control solutions in the “Industry of the Future” vision. The book also addresses to master’s and Ph.D. students enrolled in Engineering Sciences programs.