Digital health is a rapidly expanding area of interest for both research, policy and practice, and within that area digital technologies (DTs) for health financing receive increasing attention. DTs can change the nature and business processes of health financing functions and tasks and modify the interactions between health financing actors. Depending on their design features and actual implementation as well as broader contextual factors, DTs can affect the health financing tasks and functions (positively or negatively). However, little robust evidence exists on the impact of DTs specifically on health financing and universal health coverage (UHC) objectives. More rigorous evaluations in this area is urgently needed. The aim of this guide is to support the evidence generation on DTs for health financing. The guide provides orientation to analyse a country use case of digital technology and its (positive and negative) effects for health financing, i.e. whether, how and why it contributes to the realization of desirable health financing attributes and UHC intermediate and final objectives or whether, how and in which circumstances it is actually harmful to these.

Patients with unmet needs will continue to increase as no viable nor adequate treatment exists. Meanwhile, healthcare systems are struggling to cope with the rise of patients with chronic diseases, the ageing population and the increasing cost of drugs. What if there is a faster and less expensive way to provide better care for patients using the right digital solutions and transforming the growing volumes of health data into insights? The increase of digital health has grown exponentially in the last few years. Why is there a slow uptake of these new digital solutions in the healthcare and pharmaceutical industries? One of the key reasons is that patients are often left out of the innovation process. Their data are used without their knowledge, solutions designed for them are developed without their input and healthcare professionals refuse their expertise. This book explores what it means to empower patients in a digital world and how this empowerment will bridge the gap between science, technology and patients. All these components need to co-exist to bring value not only to the patients themselves but to improve the healthcare ecosystem. Patients have taken matters into their own hands. Some are equipped with the latest wearables and applications, engaged in improving their health using data, empowered to make informed decisions and ultimately are experts in their disease(s). They are the e-patients. The other side of the spectrum are patients with minimal digital literacy but equally willing to donate their data for the purpose of research. Finding the right balance when using digital health solutions becomes as critical as the need to develop a disease-specific solution. For the first time, the authors look at healthcare and technologies through the lens of patients and physicians via surveys and interviews in order to understand their perspective on digital health, analyse the benefits for them, explore how they can actively engage in the innovation process, and identify the threats and opportunities the large volumes of data create by digitizing healthcare. Are patients truly ready to know everything about their health? What is the value of their data? How can other stakeholders join the patient empowerment movement? This unique perspective will help us re-design the future of healthcare - an industry in desperate need for a change.

Health systems have to meet the changing needs of an increasingly assertive population and an ever more complex health policy context. Digitalisation, population ageing, chronic diseases, new pandemic threats, and evolving expectations of what health services should deliver – and how – have raised questions of whether health systems meet the needs and facilitate engagement of the people.

Resilient Health: Leveraging Technology and Social Innovations to Transform Healthcare for COVID-19 Recovery and Beyond presents game-changing and disruptive technological innovations and social applications in health and mental health care around the world for the post-COVID age and beyond, addressing the urgent need for care. In this first-of-its kind comprehensive volume, experts and stakeholders from all sectors - government and the public and private sectors - offer models and frameworks for policy, programming, and financing to transform healthcare, address inequities, close the treatment gap, and “build back better,” especially for under-resourced vulnerable communities globally, to “leave no one behind” and advance development globally. Contributions from world experts cover 8 essential parts: The context and challenges for resilient health systems to shape the future; developments and directions (AI, VR, MR, IVAs and more); an innovations toolbox, also targeted for special populations and settings (women, youth, ageing, migrants, disabled persons, indigenous peoples, in the workplace); the role of stakeholders (governments, the public and private sector); forums and networks; innovative financing; resources, lessons learned and the way forward. Addresses the “hot” topic today in the ever-emerging landscape of disruptive digital healthcare delivery, covering critical issues and solutions in digital health, big data, and artificial intelligence as well as benefits and challenges, and ethical concerns Provides case examples of transformative and radical solutions to urgent health needs, especially in remote low-resource settings as well as in less well-covered regions of Central and South America and MENA (Middle East and North Africa) Positions health innovations at the nexus of the global framework of Universal Health Coverage and of the United Nations Sustainable Developing Goals to achieve SDG3 - good health and well-being –at the intersection with climate action, gender equality, quality education, eradication of poverty and hunger, sustainable cities, environmental protection and others. Serves as an exceptional resource, reference, teaching tool, and guide for all stakeholders including civil society and NGOs, government, think tanks, investors, academia, researchers and practitioners, product developers and all policymakers and programmers involved in planning and delivering healthcare, including an extensive section of resources in the digital health space in various categories like publications, conferences, and collaboratives. Provides examples of, and encourages, multi-stakeholder partnerships essential to re-imagine health systems, delivery and access, and to achieve intended healthcare objectives

A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system’s perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems. Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book’s website. Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarter This book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which include both basic and advanced concepts.

Digital Health: A Transformative Approach is designed to prepare Australia and New Zealand’s future health and social care workforce for the rapidly evolving digital health landscape. It is the first local health informatics title reflecting Australasia-specific contexts and its learning objectives are aligned to National Digital Health Strategies and Frameworks. A scaffolded approach to learning, makes this text suitable for all health and social care professionals, from early learners developing skills, to those more capable who want to adapt and lead in digital health. The text is supported by online case studies that will assist development of digital professionalism and understanding requirements of digital technology across clinical, research, education and administration in diverse health and social care environments. Information presented across four units and 12 chapters that support learning and teaching and help build learners’ work readiness Scaffolded approach across three levels of capability – empowered, transitional, and entrusted - suitable for undergraduate, postgraduate and ongoing professional development Supported by an Elsevier Adaptive Quizzing (EAQ) to provide formative assessment across the three levels Includes telehealth, electronic medical/health records, clinical technologies, disaster planning, interoperability and precision health care Additional online case studies to support advanced learning.

Blockchain is a technology that transcends cryptocurrencies. There are other services in different sectors of the economy that can benefit from the trust and security that blockchains offer. For example, financial institutions are using blockchains for international money transfer, and in logistics, it has been used for supply chain management and tracking of goods. As more global companies and governments are experimenting and deploying blockchain solutions, it is necessary to compile knowledge on the best practices, strategies, and failures in order to create a better awareness of how blockchain could either support or add value to other services. Cross-Industry Use of Blockchain Technology and Opportunities for the Future provides emerging research highlighting the possibilities inherent in blockchain for different sectors of the economy and the added value blockchain can provide for the future of these different sectors. Featuring coverage on a broad range of topics such as data privacy, information sharing, and digital identity, this book is ideally designed for IT specialists, consultants, design engineers, cryptographers, service designers, researchers, academics, government officials, and industry professionals.

This report explores how data and digital technology can help achieve policy objectives and drive positive transformation in the health sector while managing new risks such as privacy, equity and implementation costs. It examines the following topics: improving service delivery models; empowering people to take an active role in their health and their care; improving public health; managing biomedical technologies; enabling better collaboration across borders; and improving health system governance and stewardship.