Healthcare is noted for using leading-edge technologies and embracing new scientific discoveries to enable better cures for diseases and better means to enable early detection of most life-threatening diseases. However, the healthcare industry globally, and in the US specifically, has been extremely slow to adopt technologies that focus on better practice management and administrative needs. Presently, healthcare is grappling with many challenges both nationally and globally, including escalating costs, a move to a preventative care environment, and a technologically savvy patient with high expectations. The Handbook of Research on Optimizing Healthcare Management Techniques is a pivotal reference source that provides an extensive and rich compilation of various ICT initiatives and examines the role that ICT plays and will play in the future of healthcare delivery. It represents ways in which healthcare delivery can be made superior and the healthcare industry can begin to address the major challenges it faces in the 21st century so that ultimately the most important person in the web of healthcare players, the patient, can be confident about receiving high-quality, cost-effective healthcare. While highlighting topics such as e-health, medical informatics, and patient value, this publication explores the role of supportive technologies as well as the methods of focused, patient-centric outcomes. This book is ideally designed for doctors, nurses, hospital administrators, medical staff, hospital directors, medical boards, IT consultants, health practitioners, academicians, researchers, and students.

The digital transformation of healthcare delivery is in full swing. Health monitoring is increasingly becoming more effective, efficient, and timely through mobile devices that are now widely available. This, as well as wireless technology, is essential to assessing, diagnosing, and treating medical ailments. However, systems and applications that boost wellness must be properly designed and regulated in order to protect the patient and provide the best care. Optimizing Health Monitoring Systems With Wireless Technology is an essential publication that focuses on critical issues related to the design, development, and deployment of wireless technology solutions for healthcare and wellness. Highlighting a broad range of topics including solution evaluation, privacy and security, and policy and regulation, this book is ideally designed for clinicians, hospital directors, hospital managers, consultants, health IT developers, healthcare providers, engineers, software developers, policymakers, researchers, academicians, and students.

From the Preface: Collectively, the chapters in this book address application domains including inpatient and outpatient services, public health networks, supply chain management, and resource constrained settings in developing countries. Many of the chapters provide specific examples or case studies illustrating the applications of operations research methods across the globe, including Africa, Australia, Belgium, Canada, the United Kingdom, and the United States. Chapters 1-4 review operations research methods that are most commonly applied to health care operations management including: queuing, simulation, and mathematical programming. Chapters 5-7 address challenges related to inpatient services in hospitals such as surgery, intensive care units, and hospital wards. Chapters 8-10 cover outpatient services, the fastest growing part of many health systems, and describe operations research models for primary and specialty care services, and how to plan for patient no-shows. Chapters 12 – 16 cover topics related to the broader integration of health services in the context of public health, including optimizing the location of emergency vehicles, planning for mass vaccination events, and the coordination among different parts of a health system. Chapters 17-18 address supply chain management within hospitals, with a focus on pharmaceutical supply management, and the challenges of managing inventory for nursing units. Finally, Chapters 19-20 provide examples of important and emerging research in the realm of humanitarian logistics.

As healthcare, culture, and the environment remain crucial aspects of modern society, the current issues and opportunities within each sector must be examined and considered in order to ensure their success in the future. These critical fields should be studied in relation to each other as they must work in tandem to create a better society. The Handbook of Research on Interdisciplinary Studies on Healthcare, Culture, and the Environment presents innovative ideas and emerging research to highlight critical trends focusing on the relationship between healthcare, environmental wellbeing, and society and culture. Covering a range of topics such as sustainability, leadership, and food security, this reference work is ideal for industry professionals, researchers, academicians, practitioners, instructors, and students.

Artificial intelligence (AI) is revolutionizing every aspect of human life including human healthcare and wellbeing management. Various types of intelligent healthcare engineering applications have been created that help to address patient healthcare and outcomes such as identifying diseases and gathering patient information. Advancements in AI applications in healthcare continue to be sought to aid rapid disease detection, health monitoring, and prescription drug tracking. TheHandbook of Research on Advancements of Artificial Intelligence in Healthcare Engineering is an essential scholarly publication that provides comprehensive research on the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in the design, implementation, and optimization of healthcare engineering solutions. Featuring a wide range of topics such as genetic algorithms, mobile robotics, and neuroinformatics, this book is ideal for engineers, technology developers, IT consultants, hospital administrators, academicians, healthcare professionals, practitioners, researchers, and students.

There are many advantages to incorporating digital services in business, including improved data management, higher transparency, personalized customer service, and cost reduction. Innovation is a key driver to how digital services are formed, developed, delivered, and used by consumers, employees, and employers. The largest differentiator comes from having a digitally empowered workforce. Companies increasingly need digital workers to establish greater digital skills to bear on every activity. Business leaders especially need to steer digital priorities, drive innovation, and develop digital platforms. Leadership, Management, and Adoption Techniques for Digital Service Innovation is an essential reference source that discusses the adoption of digital services in multiple industries and presents digital technologies to address and further advance innovation to drive successful solutions. Featuring research on topics such as cloud computing, digital business, and value creation, this book is ideally designed for managers, leaders, executives, directors, IT consultants, academicians, researchers, industry professionals, students, and practitioners.

Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.