Exploring Complexity in Health: An Interdisciplinary Systems Approach


Book Description

The field of health is an increasingly complex and technical one; and an area in which a more multidisciplinary approach would undoubtedly be beneficial in many ways. This book presents papers from the conference ‘Health – Exploring Complexity: An Interdisciplinary Systems Approach’, held in Munich, Germany, from August 28th to September 2nd 2016. This joint conference unites the conferences of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), the German Society for Epidemiology (DGEpi), the International Epidemiological Association - European Region, and the European Federation for Medical Informatics (EFMI). These societies already have long-standing experience of integrating the disciplines of medical informatics, biometry, epidemiology and health data management. The book contains over 160 papers, and is divided into 14 sections covering subject areas such as: health and clinical information systems; eHealth and telemedicine; big data and advanced analytics; and evidence-based health informatics, evaluation and education, among many others. The book will be of value to all those working in the field of health and interested in finding new ways to enable the collaboration of different scientific disciplines and the establishment of comprehensive methodological approaches.




Exploring Complexity in Health


Book Description

The field of health is an increasingly complex and technical one; and an area in which a more multidisciplinary approach would undoubtedly be beneficial in many ways.This book presents papers from the conference 'Health - Exploring Complexity: An Interdisciplinary Systems Approach', held in Munich, Germany, from August 28th to September 2nd 2016. This joint conference unites the conferences of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), the German Society for Epidemiology (DGEpi), the International Epidemiological Association - European Region, and the European Federation for Medical Informatics (EFMI). These societies already have long-standing experience of integrating the disciplines of medical informatics, biometry, epidemiology and health data management.The book contains over 160 papers, and is divided into 14 sections covering subject areas such as: health and clinical information systems; eHealth and telemedicine; big data and advanced analytics; and evidence-based health informatics, evaluation and education, among many others. The book will be of value to all those working in the field of health and interested in finding new ways to enable the collaboration of different scientific disciplines and the establishment of comprehensive methodological approaches.










Complexity and Healthcare


Book Description

This book illustrates the relevance of chaos and complexity theory to healthcare organisations, public health, clinical governance and the consultation. It explains the terms and ideas at the heart of complexity, the unfamiliar science behind it, and how it applies to the real world. In healthcare, the NHS is a complex adaptive system. So are hospitals, general practices, diseases and patients. The book describes how insights from complexity can help us better understand how organisations, patients or disease develop over time, in an often unpredictable manner. Contributors set out the benefits of applying complexity to their own particular areas of healthcare. Complexity and Healthcare will be of special interest to clinicians and managers in primary and secondary care, researchers and academics, and in particular, general practitioners and public health professionals.




Transdisciplinary Perspectives on Complex Systems


Book Description

This book presents an internationally comprehensive perspective into the field of complex systems. It explores the challenges of and approaches to complexity from a broad range of disciplines, including big data, health care, medicine, mathematics, mechanical and systems engineering, air traffic control and finance. The book’s interdisciplinary character allows readers to identify transferable and mutually exclusive lessons learned among these disciplines and beyond. As such, it is well suited to the transfer of applications and methodologies between ostensibly incompatible disciplines. This book provides fresh perspectives on comparable issues of complexity from the top minds on systems thinking.




Complexity in Healthcare and the Language of Consultation


Book Description

This book provides an important contribution to the new and growing field of 'narrative-based medicine'. It specifically addresses the largest area of medical activity primary care. It provides both a theoretical framework and practical skills for dealing with individual consultations family work clinical supervision and teamwork and offers a comprehensive approach to the whole range of work in primary care. Using a wide range of clinical examples it shows how professionals in primary care can help clarify patients' existing stories and elucidate new stories. It can be used as a training resource and includes exercises and summaries of key points to consider. It is based on and describes an established evaluated training method and is of immediate and significant practical use to readers. It is essential reading for general practitioners practice nurses and others in the primary care team psychologists family therapists counsellors and other professionals attached to primary care. GP trainers tutors and course organisers will find it a valuable educational tool. Professionals elsewhere in primary care such as pharmacists dentists and optometrists and academics in medical sociology and medical anthropology will also find it very useful.




Applied Interdisciplinary Theory in Health Informatics


Book Description

The American Medical Informatics Association (AMIA) defines the term biomedical informatics (BMI) as: The interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health. This book: Applied Interdisciplinary Theory in Health Informatics: A Knowledge Base for Practitioners, explores the theories that have been applied in health informatics and the differences they have made. The editors, all proponents of evidence-based health informatics, came together within the European Federation of Medical Informatics (EFMI) Working Group on Health IT Evaluation and the International Medical Informatics Association (IMIA) Working Group on Technology Assessment and Quality Development. The purpose of the book, which has a foreword by Charles Friedman, is to move forward the agenda of evidence-based health informatics by emphasizing theory-informed work aimed at enriching the understanding of this uniquely complex field. The book takes the AMIA definition as particularly helpful in its articulation of the three foundational domains of health informatics: health science, information science, and social science and their various overlaps, and this model has been used to structure the content of the book around the major subject areas. The book discusses some of the most important and commonly used theories relevant to health informatics, and constitutes a first iteration of a consolidated knowledge base that will advance the science of the field.




Embracing Complexity in Health


Book Description

This detailed volume illustrates the transformative nature of systems and complexity sciences for practice, research, education, and health system organization. Researchers highlight the fresh perspectives and novel approaches offered by these interdisciplinary fields in addressing the complexities of global, national, and community health challenges in the 21st century. With the implications that these emerging fields hold for health still relatively underexplored, researchers from a wide variety of disciplines, including physiological, social, environmental, clinical, prevention, educational, organizational, finance, and policy domains, aim in this book to suggest future directions in health care and highlight recent advances in basic and clinical physiology, education, policy-making, and leadership. Among the topics discussed: Impact of genomic heterogeneity on bio-emergent properties Harnessing Big Data to improve health services Decision-making of women in violent relationships Co-producing healthcare interventions A socio-ecological solution to physician burnout Embracing Complexity in Health: The Transformation of Science, Practice, and Policy is a highly relevant resource to practitioners in the field, students, instructors, and policy makers, and also should find an engaged audience among health and disease researchers, healthcare planners, health system financiers, health system administrators, health services administrators, health professional educators, and other health professionals. The trans- and interdisciplinary natures of health and health care are fostering a broad discourse amongst all concerned with improving patient care in an equitable and sustainable way.




Encyclopedia of Data Science and Machine Learning


Book Description

Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.