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Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Developments in Healthcare Information Systems and Technologies: Models and Methods presents the latest research in healthcare information systems design, development, and deployment, benefiting researchers, practitioners, and students. Contributions investigate topics such as clinical education, electronic medical records, clinical decision support systems, and IT adoption in healthcare.
"This reference set provides a complete understanding of the development of applications and concepts in clinical, patient, and hospital information systems"--Provided by publisher.
Previously published as Strategic Information Management in Hospitals; An Introduction to Hospital Information Systems, Health Information Systems Architectures and Strategies is a definitive volume written by four authoritative voices in medical informatics. Illustrating the importance of hospital information management in delivering high quality health care at the lowest possible cost, this book provides the essential resources needed by the medical informatics specialist to understand and successfully manage the complex nature of hospital information systems. Author of the first edition's Foreword, Reed M. Gardner, PhD, Professor and Chair, Department of Medical Informatics, University of Utah and LDS Hospital, Salt Lake City, Utah, applauded the text's focus on the underlying administrative systems that are in place in hospitals throughout the world. He wrote, "These challenging systems that acquire, process and manage the patient's clinical information. Hospital information systems provide a major part of the information needed by those paying for health care." their components; health information systems; architectures of hospital information systems; and organizational structures for information management.
This book provides a practical guide to the design and implementation of health information systems in developing countries. Noting that most existing systems fail to deliver timely, reliable, and relevant information, the book responds to the urgent need to restructure systems and make them work as both a resource for routine decisions and a powerful tool for improving health services. With this need in mind, the authors draw on their extensive personal experiences to map out strategies, pinpoint common pitfalls, and guide readers through a host of conceptual and technical options. Information needs at all levels - from patient care to management of the national health system - are considered in this comprehensive guide. Recommended lines of action are specific to conditions seen in government-managed health systems in the developing world. In view of common constraints on time and resources, the book concentrates on strategies that do not require large resources, highly trained staff, or complex equipment. Throughout the book, case studies and numerous practical examples are used to explore problems and illustrate solutions. Details range from a list of weaknesses that plague most existing systems, through advice on when to introduce computers and how to choose appropriate software and hardware, to the hotly debated question of whether patient records should be kept by the patient or filed at the health unit. The book has fourteen chapters presented in four parts. Chapters in the first part, on information for decision-making, explain the potential role of health information as a managerial tool, consider the reasons why this potential is rarely realized, and propose general approaches for reform which have proved successful in several developing countries. Presentation of a six-step procedure for restructuring information systems, closely linked to an organizational model of health services, is followed by a practical discussion of the decision-making process. Reasons for the failure of most health information to influence decisions are also critically assessed. Against this background, the second and most extensive part provides a step-by-step guide to the restructuring of information systems aimed at improving the quality and relevance of data and ensuring their better use in planning and management. Steps covered include the identification of information needs and indicators, assessment of the existing system, and the collection of both routine and non-routine data using recommended procedures and instruments. Chapters also offer advice on procedures for data transmission and processing, and discuss the requirements of systems designed to collect population-based community information. Resource needs and technical tools are addressed in part three. A comprehensive overview of the resource base - from staff and training to the purchase and maintenance of equipment - is followed by chapters offering advice on the introduction of computerized systems in developing countries, and explaining the many applications of geographic information systems. Practical advice on how to restructure a health information system is provided in the final part, which considers how different interest groups can influence the design and implementation of a new system, and proposes various design options for overcoming specific problems. Experiences from several developing countries are used to illustrate strategies and designs in terms of those almost certain to fail and those that have the greatest chances of success
Modern technology has impacted healthcare and interactions between patients and healthcare providers through a variety of means including the internet, social media, mobile devices, and the internet of things. These new technologies have empowered, frustrated, educated, and confused patients by making educational materials more widely available and allowing patients to monitor their own vital signs and self-diagnose. Further analysis of these and future technologies is needed in order to provide new approaches to empowerment, reduce mistakes, and improve overall healthcare. Impacts of Information Technology on Patient Care and Empowerment is a critical scholarly resource that delves into patient access to information and the effect that access has on their relationship with healthcare providers and their health outcomes. Featuring a range of topics such as gamification, mobile computing, and risk analysis, this book is ideal for healthcare practitioners, doctors, nurses, surgeons, hospital staff, medical administrators, patient advocates, researchers, academicians, policymakers, and healthcare students.
This is a systematic review on how innovations in health service practice and organisation can be disseminated and implemented. This is an academic text, originally commissioned by the Department of Health from University College London and University of Surrey, using a variety of research methods. The results of the review are discussed in detail in separate chapters covering particular innovations and the relevant contexts. The book is intended as a resource for health care researchers and academics.
Each year, hospital-acquired infections, prescribing and treatment errors, lost documents and test reports, communication failures, and other problems have caused thousands of deaths in the United States, added millions of days to patients' hospital stays, and cost Americans tens of billions of dollars. Despite (and sometimes because of) new medical information technology and numerous well-intentioned initiatives to address these problems, threats to patient safety remain, and in some areas are on the rise. In First, Do Less Harm, twelve health care professionals and researchers plus two former patients look at patient safety from a variety of perspectives, finding many of the proposed solutions to be inadequate or impractical. Several contributors to this book attribute the failure to confront patient safety concerns to the influence of the "market model" on medicine and emphasize the need for hospital-wide teamwork and greater involvement from frontline workers (from janitors and aides to nurses and physicians) in planning, implementing, and evaluating effective safety initiatives. Several chapters in First, Do Less Harm focus on the critical role of interprofessional and occupational practice in patient safety. Rather than focusing on the usual suspects-physicians, safety champions, or high level management-these chapters expand the list of "stakeholders" and patient safety advocates to include nurses, patient care assistants, and other staff, as well as the health care unions that may represent them. First, Do Less Harm also highlights workplace issues that negatively affect safety: including sleeplessness, excessive workloads, outsourcing of hospital cleaning, and lack of teamwork between physicians and other health care staff. In two chapters, experts explain why the promise of health care information technology to fix safety problems remains unrealized, with examples that are at once humorous and frightening. A book that will be required reading for physicians, nurses, hospital administrators, public health officers, quality and risk managers, healthcare educators, economists, and policymakers, First, Do Less Harm concludes with a list of twenty-seven paradoxes and challenges facing everyone interested in making care safe for both patients and those who care for them.
This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.