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This comprehensive reference delves into the complex process of medical decision making—both the nuts-and-bolts access and insurance issues that guide choices and the cognitive and affective factors that can make patients decide against their best interests. Wide-ranging coverage offers a robust evidence base for understanding decision making across the lifespan, among family members, in the context of evolving healthcare systems, and in the face of life-changing diagnosis. The section on applied decision making reviews the effectiveness of decision-making tools in healthcare, featuring real-world examples and guidelines for tailored communications with patients. Throughout, contributors spotlight the practical importance of the field and the pressing need to strengthen health decision-making skills on both sides of the clinician/client dyad. Among the Handbook’s topics: From laboratory to clinic and back: connecting neuroeconomic and clinical mea sures of decision-making dysfunctions. Strategies to promote the maintenance of behavior change: moving from theoretical principles to practices. Shared decision making and the patient-provider relationship. Overcoming the many pitfalls of communicating risk. Evidence-based medicine and decision-making policy. The internet, social media, and health decision making. The Handbook of Health Decision Science will interest a wide span of professionals, among them health and clinical psychologists, behavioral researchers, health policymakers, and sociologists.
Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don’t realize is that data science is in fact quite multidisciplinary—useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Maker’s Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker’s Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide. What You Will Learn Understand how data science can be used within your business. Recognize the differences between AI, machine learning, and statistics.Become skilled at thinking like a data scientist, without being one.Discover how to hire and manage data scientists.Comprehend how to build the right environment in order to make your organization data-driven. Who This Book Is For Startup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. A secondary audience includes people looking for a soft introduction into the subject of data science.
Currently, informatics within the field of public health is a developing and growing industry. Clinical informatics are used in direct patient care by supplying medical practitioners with information that can be used to develop a care plan. Intelligent applications in clinical informatics facilitates with the technology-based solutions to analyze data or medical images and help clinicians to retrieve that information. Decision models aid with making complex decisions especially in uncertain situations. The Handbook of Research on Applied Intelligence for Health and Clinical Informatics is a comprehensive reference book that focuses on the study of resources and methods for the management of healthcare infrastructure and information. This book provides insights on how applied intelligence with deep learning, experiential learning, and more will impact healthcare and clinical information processing. The content explores the representation, processing, and communication of clinical information in natural and engineered systems. This book covers a range of topics including applied intelligence, medical imaging, telehealth, and decision support systems, and also looks at technologies and tools used in the detection and diagnosis of medical conditions such as cancers, diabetes, heart disease, lung disease, and prenatal syndromes. It is an essential reference source for diagnosticians, medical professionals, imaging specialists, data specialists, IT consultants, medical technologists, academicians, researchers, industrial experts, scientists, and students.
Looking for a brief but authoritative resource to help you manage the types of complex cardiac, pulmonary, and neurological emergencies you encounter as a resident or attending emergency room physician? Look no further than Decision Making in Emergency Critical Care: An Evidence-Based Handbook. This portable guide to rational clinical decision-making in the challenging – and changing – world of emergency critical care provides in every chapter a streamlined review of a common problem in critical care medicine, along with evidence-based guidelines and summary tables of landmark literature. Features Prepare for effective critical care practice in the emergency room’s often chaotic and resource-limited environment with expert guidance from fellows and attending physicians in the fields of emergency medicine, pulmonary and critical care medicine, cardiology, gastroenterology, and neurocritical care. Master critical care fundamentals as experts guide you through the initial resuscitation and the continued management of critical care patients during their first 24 hours of intensive care. Confidently make sustained, data-driven decisions for the critically ill patient using expert information on everything from hemodynamic monitoring and critical care ultrasonography to sepsis and septic shock to the ED-ICU transfer of care.
A guide for everyone involved in medical decision making to plot a clear course through complex and conflicting benefits and risks.
This book is an introduction to health care as a complex adaptive system, a system that feeds back on itself. The first section introduces systems and complexity theory from a science, historical, epistemological, and technical perspective, describing the principles and mathematics. Subsequent sections build on the health applications of systems science theory, from human physiology to medical decision making, population health and health services research. The aim of the book is to introduce and expand on important population health issues from a systems and complexity perspective, highlight current research developments and their implications for health care delivery, consider their ethical implications, and to suggest directions for and potential pitfalls in the future.
The Data Science Handbook is a curated collection of 25 candid, honest and insightful interviews conducted with some of the world's top data scientists.In this book, you'll hear how the co-creator of the term 'data scientist' thinks about career and personal success. You'll hear from a young woman who created her own data scientist curriculum, subsequently landing her a role in the field. Readers of this book will be left with war stories, wisdom and
Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies.
′This handbook is an excellent reflection of the growing maturity and methodological sophistication of the field of Health Technology Assessment. The Handbook covers a spectrum of issues, from primary evidence (clinical trials) through reviews and meta-analysis, to identifying and filling gaps in the evidence. Up-to-date, clearly written, and well-edited, the handbook is a needed addition to any personal or professional library dealing with Health Technology Assessment.′ Professor David Banta, TNO Prevention and Health, The Netherlands ′This text presents the most advanced knowledge on methodology in health care research, and will form the backbone of many future studies′ - Paula Roberts, Nurse Researcher The `effectiveness revolution′ both in research and clinical practice, has tested available methods for health services research to the extreme. How far can observational methods, routine data and qualitative methods be used in health care evaluation? What cost and outcome measures are appropriate, and how should data be gathered? With the support of over two million pounds from the British Health Technology Assessment Research Programme, the research project for this Handbook has led to both a synthesis of all of the existing knowledge in these areas and an agenda for future debate and research. The chapters and their authors have been selected through a careful process of peer review and provide a coherent and complete approach to the field. The handbook has been a unique collaboration between internationally regarded clinicians, statisticians, epidemiologists, social scientists, health economists and ethicists. It provides the most advanced thinking and the most authoritative resource for a state of the art review of methods of evaluating health care and will be required reading for anyone involved in health services research and management.
How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21st century? Editors Tinglong Dai and Sridhar Tayur, aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers a wide range of macro-, meso- and micro-level thrusts—such as market design, competing interests, global health, personalized medicine, residential care and concierge medicine, among others—and structures what has been a highly fragmented research area into a coherent scientific discipline. The handbook also provides an easy-to-comprehend introduction to five essential research tools—Markov decision process, game theory and information economics, queueing games, econometric methods, and data science—by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts. The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook: Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective—a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable—can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately. Facilitates collaboration between healthcare experts and analytics scholar to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose. The handbook is designed to be accessible to the independent reader, and it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course.