Download or read book Decision Making under Deep Uncertainty written by Vincent A. W. J. Marchau and published by Springer. This book was released on 2019-04-04 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work. The publication of this book has been funded by the Radboud University, the RAND Corporation, Delft University of Technology, and Deltares.

Download or read book Operations Research and Health Care written by Margaret L. Brandeau and published by Springer Science & Business Media. This book was released on 2006-04-04 with total page 870 pages. Available in PDF, EPUB and Kindle. Book excerpt: In both rich and poor nations, public resources for health care are inadequate to meet demand. Policy makers and health care providers must determine how to provide the most effective health care to citizens using the limited resources that are available. This chapter describes current and future challenges in the delivery of health care, and outlines the role that operations research (OR) models can play in helping to solve those problems. The chapter concludes with an overview of this book – its intended audience, the areas covered, and a description of the subsequent chapters. KEY WORDS Health care delivery, Health care planning HEALTH CARE DELIVERY: PROBLEMS AND CHALLENGES 3 1.1 WORLDWIDE HEALTH: THE PAST 50 YEARS Human health has improved significantly in the last 50 years. In 1950, global life expectancy was 46 years [1]. That figure rose to 61 years by 1980 and to 67 years by 1998 [2]. Much of these gains occurred in low- and middle-income countries, and were due in large part to improved nutrition and sanitation, medical innovations, and improvements in public health infrastructure.

Download or read book Decision Making Under Uncertainty written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2015-07-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.

Download or read book Reinforcement Learning and Stochastic Optimization written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2022-04-25 with total page 1090 pages. Available in PDF, EPUB and Kindle. Book excerpt: REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION Clearing the jungle of stochastic optimization Sequential decision problems, which consist of “decision, information, decision, information,” are ubiquitous, spanning virtually every human activity ranging from business applications, health (personal and public health, and medical decision making), energy, the sciences, all fields of engineering, finance, and e-commerce. The diversity of applications attracted the attention of at least 15 distinct fields of research, using eight distinct notational systems which produced a vast array of analytical tools. A byproduct is that powerful tools developed in one community may be unknown to other communities. Reinforcement Learning and Stochastic Optimization offers a single canonical framework that can model any sequential decision problem using five core components: state variables, decision variables, exogenous information variables, transition function, and objective function. This book highlights twelve types of uncertainty that might enter any model and pulls together the diverse set of methods for making decisions, known as policies, into four fundamental classes that span every method suggested in the academic literature or used in practice. Reinforcement Learning and Stochastic Optimization is the first book to provide a balanced treatment of the different methods for modeling and solving sequential decision problems, following the style used by most books on machine learning, optimization, and simulation. The presentation is designed for readers with a course in probability and statistics, and an interest in modeling and applications. Linear programming is occasionally used for specific problem classes. The book is designed for readers who are new to the field, as well as those with some background in optimization under uncertainty. Throughout this book, readers will find references to over 100 different applications, spanning pure learning problems, dynamic resource allocation problems, general state-dependent problems, and hybrid learning/resource allocation problems such as those that arose in the COVID pandemic. There are 370 exercises, organized into seven groups, ranging from review questions, modeling, computation, problem solving, theory, programming exercises and a "diary problem" that a reader chooses at the beginning of the book, and which is used as a basis for questions throughout the rest of the book.

Download or read book Improving Diagnosis in Health Care written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2015-12-29 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.

Download or read book Decision Making in Health and Medicine written by M. G. Myriam Hunink and published by Cambridge University Press. This book was released on 2014-10-16 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision making in health care involves consideration of a complex set of diagnostic, therapeutic and prognostic uncertainties. Medical therapies have side effects, surgical interventions may lead to complications, and diagnostic tests can produce misleading results. Furthermore, patient values and service costs must be considered. Decisions in clinical and health policy require careful weighing of risks and benefits and are commonly a trade-off of competing objectives: maximizing quality of life vs maximizing life expectancy vs minimizing the resources required. This text takes a proactive, systematic and rational approach to medical decision making. It covers decision trees, Bayesian revision, receiver operating characteristic curves, and cost-effectiveness analysis, as well as advanced topics such as Markov models, microsimulation, probabilistic sensitivity analysis and value of information analysis. It provides an essential resource for trainees and researchers involved in medical decision modelling, evidence-based medicine, clinical epidemiology, comparative effectiveness, public health, health economics, and health technology assessment.

Download or read book Clinical Uncertainty in Primary Care written by Lucia Siegel Sommers and published by Springer Science & Business Media. This book was released on 2013-07-05 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Power of Colleagues What happens when primary care clinicians meet together on set aside time in their practice settings to talk about their own patients? .....Complimenting quality metrics or performance measures through discussing the actual stories of individual patients and their clinician-patient relationships In these settings, how can clinicians pool their collective experience and apply that to ‘the evidence’ for an individual patient? .....Especially for patients who do not fit the standard protocols and have vague and worrisome symptoms, poor response to treatment, unpredictable disease courses, and/or compromised abilities for shared decision making What follows when discussion about individual patients reveals system-wide service gaps and coordination limitations? .....Particularly for patients with complex clinical problems that fall outside performance monitors and quality screens How can collaborative engagement of case-based uncertainties with one’s colleagues help combat the loneliness and helplessness that PCPs can experience, no matter what model or setting in which they practice? .....And where they are expected to practice coordinated, evidence-based, EMR-directed care These questions inspired Lucia Sommers and John Launer and their international contributors to explore the power of colleagues in “Clinical Uncertainty in Primary Care: The Challenge of Collaborative Engagement” and offer antidotes to sub-optimal care that can result when clinicians go it alone. From the Foreword: “Lucia Sommers and John Launer, with the accompanying input of their contributing authors, have done a deeply insightful and close-to-exhaustive job of defining clinical uncertainty. They identify its origins, components and subtypes; demonstrate the ways in which and the extent to which it is intrinsic to medicine...and they present a cogent case for its special relationship to primary care practice...‘Clinical Uncertainty in Primary Care’ not only presents a model of collegial collaboration and support, it also implicitly legitimates it.’’ Renee Fox, Annenberg Professor Emerita of the Social Sciences, University of Pennsylvania.

Download or read book Encyclopedia of Medical Decision Making written by Michael W. Kattan and published by SAGE. This book was released on 2009-08-18 with total page 1281 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of Medical Decision Making presents state-of-the-art research and ready-to-use facts sorting out findings on medical decision making and their applications.

Download or read book Human Factors in Simulation and Training written by Dennis A. Vincenzi and published by CRC Press. This book was released on 2023-08-30 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human Factors in Simulation and Training: Application and Practice covers the latest applications and practical implementations of advanced technologies in the field of simulation and training. The text focuses on descriptions and discussions of current applications and the use of the latest technological advances in simulation and training. It covers topics including space adaptation syndrome and perceptual training, simulation for battle-ready command and control, healthcare simulation and training, human factors aspects of cybersecurity training and testing, design and development of algorithms for gesture-based control of semi-autonomous vehicles, and advances in the after-action review process for defence training. The text is an ideal read for professionals and graduate students in the fields of ergonomics, human factors, computer engineering, aerospace engineering, occupational health, and safety.

Download or read book Fundamentals of Evidence Based Health Care and Translational Science written by Francesco Chiappelli and published by Springer Science & Business Media. This book was released on 2014-03-18 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comparative effectiveness research – the conduct and synthesis of systematic research in order to compare the benefits and harms of alternative treatment options – is of critical importance in enabling informed health care decisions to be made. This user-friendly, practical handbook examines in depth how best to perform such comparative effectiveness research. A wide range of topics and methods are discussed, including research synthesis, sampling analysis, assessment of evidence design, systematic evaluation of statistical analysis, and meta-analysis. The discussion extends well beyond the fundamentals by encompassing “complex” systematic reviews, “cumulative” meta-analyses, and logic-based versus utility-based decision making. Health care providers, researchers, instructors, and students will all find this to be an invaluable reference on the compelling current issues and important analytical tools in comparative effectiveness research.

Download or read book Uncertainty Information Management and Disclosure Decisions written by Tamara Afifi and published by Routledge. This book was released on 2015-12-22 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides an in-depth exploration of two key processes in communication research: uncertainty and information regulation. It integrates scholarly work on disclosure and uncertainty with cutting edge research, theories, and applications. Offering contributions from renowned scholars, this volume is a unique and timely resource for advanced study in interpersonal, health, and family communication, and it will also appeal to scholars interested in applied research.

Download or read book Encyclopedia of Health Economics written by and published by Newnes. This book was released on 2014-02-21 with total page 1663 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of Health Economics offers students, researchers and policymakers objective and detailed empirical analysis and clear reviews of current theories and polices. It helps practitioners such as health care managers and planners by providing accessible overviews into the broad field of health economics, including the economics of designing health service finance and delivery and the economics of public and population health. This encyclopedia provides an organized overview of this diverse field, providing one trusted source for up-to-date research and analysis of this highly charged and fast-moving subject area. Features research-driven articles that are objective, better-crafted, and more detailed than is currently available in journals and handbooks Combines insights and scholarship across the breadth of health economics, where theory and empirical work increasingly come from non-economists Provides overviews of key policies, theories and programs in easy-to-understand language

Download or read book Managing Uncertainty in Organizational Communication written by Michael W. Kramer and published by Routledge. This book was released on 2014-04-04 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines uncertainty reduction theory (URT) and research applicable to organizational settings; it proposes a model for a Theory of Managing Uncertainty (TMU). For scholars/students in organizational/interpersonal/group communication.

Download or read book Identification for Prediction and Decision written by Charles F. Manski and published by Harvard University Press. This book was released on 2009-06-30 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a full-scale exposition of Charles Manski's new methodology for analyzing empirical questions in the social sciences. He recommends that researchers first ask what can be learned from data alone, and then ask what can be learned when data are combined with credible weak assumptions. Inferences predicated on weak assumptions, he argues, can achieve wide consensus, while ones that require strong assumptions almost inevitably are subject to sharp disagreements. Building on the foundation laid in the author's Identification Problems in the Social Sciences (Harvard, 1995), the book's fifteen chapters are organized in three parts. Part I studies prediction with missing or otherwise incomplete data. Part II concerns the analysis of treatment response, which aims to predict outcomes when alternative treatment rules are applied to a population. Part III studies prediction of choice behavior. Each chapter juxtaposes developments of methodology with empirical or numerical illustrations. The book employs a simple notation and mathematical apparatus, using only basic elements of probability theory.

Download or read book Evidence based Decisions and Economics written by Ian Shemilt and published by John Wiley & Sons. This book was released on 2011-09-22 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: The need for evidence-based decisions that take account of botheffectiveness and economics is greater now than ever. Using casestudies and illustrative examples throughout the authors describehow the activities and outputs of evidence synthesis, systematicreview, economic analysis and decision-making interact within andacross different spheres of health and social policy and practice. Expanding on the first edition the book now covers approaches toevidence synthesis that combine economics and systematic reviewmethods in the applied fields of social welfare, education andcriminal justice, as well as health care. Written by economists andhealth services researchers closely involved in developingevidence-based policy and practice it showcases currentstate-of-the-art methodology and will be an invaluable read for allpolicy-makers and practitioners using evidence to inform decisions,analysts conducting research to support decisions and studentsdiscovering the need for evidence-based decisions to incorporateeconomic perspectives and evidence.

Download or read book Handbook of Healthcare Delivery Systems written by Yuehwern Yih and published by CRC Press. This book was released on 2016-04-19 with total page 798 pages. Available in PDF, EPUB and Kindle. Book excerpt: With rapidly rising healthcare costs directly impacting the economy and quality of life, resolving improvement challenges in areas such as safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity has become paramount. Using a system engineering perspective, Handbook of Healthcare Delivery Systems offers theoretical foundation

Download or read book Uncertain Judgements written by Anthony O'Hagan and published by John Wiley & Sons. This book was released on 2006-08-30 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elicitation is the process of extracting expert knowledge about some unknown quantity or quantities, and formulating that information as a probability distribution. Elicitation is important in situations, such as modelling the safety of nuclear installations or assessing the risk of terrorist attacks, where expert knowledge is essentially the only source of good information. It also plays a major role in other contexts by augmenting scarce observational data, through the use of Bayesian statistical methods. However, elicitation is not a simple task, and practitioners need to be aware of a wide range of research findings in order to elicit expert judgements accurately and reliably. Uncertain Judgements introduces the area, before guiding the reader through the study of appropriate elicitation methods, illustrated by a variety of multi-disciplinary examples. This is achieved by: Presenting a methodological framework for the elicitation of expert knowledge incorporating findings from both statistical and psychological research. Detailing techniques for the elicitation of a wide range of standard distributions, appropriate to the most common types of quantities. Providing a comprehensive review of the available literature and pointing to the best practice methods and future research needs. Using examples from many disciplines, including statistics, psychology, engineering and health sciences. Including an extensive glossary of statistical and psychological terms. An ideal source and guide for statisticians and psychologists with interests in expert judgement or practical applications of Bayesian analysis, Uncertain Judgements will also benefit decision-makers, risk analysts, engineers and researchers in the medical and social sciences.