Demystifying Integrated Care E Book

Integrated care aims to address inequality through removing fragmented health and social care. It is being adopted worldwide, including in the UK, where the NHS is undergoing significant transformation as it introduces integrated care for all providers. This new book aims to equip students and practitioners to take the lead in this new model of care delivery. It will help them understand the key principles of integrated care and then apply these to the design, implementation and practice of integrated care in their own work. Written by academics and operational healthcare leaders, this book is ideal for final year students of nursing, allied health and social care, postgraduates, and all nursing and allied health professionals who will be required to work within the UK’s new integrated care systems. Comprehensive coverage of the design, implementation and practice of integrated care Covers theory and concepts of integrated care as well as applicability to practice for individuals, organisations and systems Presents a comprehensive and up-to-date evidence base for integrated care Accessible to a range of practitioners Wide range of case studies provide real-life examples of how integrated care has been applied in different areas Contributions from academics across disciplines, including nursing, occupational therapy, social care and public health Co-written with business partners, clinical leads or specialists within their field – reflects the realities of practice Includes an international focus, with examples from countries which have a strong history in integrated care such as the Netherlands, New Zealand, USA and Finland

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics Unique case study approach provides readers with insights for practical clinical implementation

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

The management of COVID-19 is challenging due to the lack of clear information about the Sars-Cov2 and recommendations for specific treatment regimens. The scale of the pandemic has also exacerbated the situation, with health care systems under stress from the high volume of COVID-19 patients. In Demystifying COVID-19: Understanding the Disease, Its Diagnosis, and Treatment, medical experts explain many aspects about the COVID-19 pandemic, including guidelines to minimize risk of infection, diagnostic methods, treatment, real scenarios in the course of the disease and issues that need attention in specific patient groups. The book equips both general readers and healthcare professionals with key information required to understand COVID-19 and navigate a situation typical to a pandemic. Public health officials who wish to mobilize awareness campaigns for the benefit of the general public can also find value in the comprehensive information presented in this reference.

This book presents an emerging new vision of the brain, which is essentially expressed in computational terms, for non-experts. As such, it presents the fundamental concepts of neuroscience in simple language, without overwhelming non-biologists with excessive biological jargon. In addition, the book presents a novel computational perspective on the brain for biologists, without resorting to complex mathematical equations. It addresses a comprehensive range of topics, starting with the history of neuroscience, the function of the individual neuron, the various kinds of neural network models that can explain diverse neural phenomena, sensory-motor function, language, emotions, and concluding with the latest theories on consciousness. The book offers readers a panoramic introduction to the “new brain” and a valuable resource for interdisciplinary researchers looking to gatecrash the world of neuroscience.

This handbook shares profound insights into the main principles and concepts of integrated care. It offers a multi-disciplinary perspective with a focus on patient orientation, efficiency, and quality by applying widely recognized management approaches to the field of healthcare. The handbook also highlights international best practices and shows how integrated care can work in various health systems. In the majority of health systems around the world, the delivery of healthcare and social care is characterised by fragmentation and complexity. Consequently, much of the recent international discussion in the fields of health policy and health management has focused on the topic of integrated care. “Integrated” acknowledges the complexity of patients’ needs and aims to meet them by taking into account both health and social care aspects. Changing and improving processes in a coordinated way is at the heart of this approach. The second edition offers new chapters on people-centredness, complexity theories and evaluation methods, additional management tools and a wealth of experiences from different countries and localities. It is essential reading both for health policymakers seeking inspiration for legislation and for practitioners involved in the management of public health services who want to learn from good practice.

Written by one of the premier scholars on the European Union and hailed as the best undergraduate text on the subject, this book has been thoroughly updated, revised, and streamlined. Clear and comprehensive, it is dedicated to demystifying one of the world's most important and least-understood institutions. Ginsberg begins with the foundation blocks of history, law, economics, and politics to provide the context for understanding integration. He then breaks the EU down into its individual elements so that they easily can be understood on their own, as well as in relation to one another and to the whole. Ensuring that students' knowledge of the EU rests on a solid foundation, the author challenges them to see it as a remarkable experiment in regional cooperation with profound implications for the peaceful resolution of conflict in many of the world's troubled regions.