Based on careful analysis of burden of disease and the costs ofinterventions, this second edition of 'Disease Control Priorities in Developing Countries, 2nd edition' highlights achievable priorities; measures progresstoward providing efficient, equitable care; promotes cost-effectiveinterventions to targeted populations; and encourages integrated effortsto optimize health. Nearly 500 experts - scientists, epidemiologists, health economists,academicians, and public health practitioners - from around the worldcontributed to the data sources and methodologies, and identifiedchallenges and priorities, resulting in this integrated, comprehensivereference volume on the state of health in developing countries.

A guide for everyone involved in medical decision making to plot a clear course through complex and conflicting benefits and risks.

Decision Making in Health Care, first published in 2000, is a comprehensive overview of the field of medical decision making.

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.

In today’s modernized world, the field of healthcare has seen significant practical innovations with the implementation of computational intelligence approaches and soft computing methods. These two concepts present various solutions to complex scientific problems and imperfect data issues. This has made both very popular in the medical profession. There are still various areas to be studied and improved by these two schemes as healthcare practices continue to develop. Computational Intelligence and Soft Computing Applications in Healthcare Management Science is an essential reference source that discusses the implementation of soft computing techniques and computational methods in the various components of healthcare, telemedicine, and public health. Featuring research on topics such as analytical modeling, neural networks, and fuzzy logic, this book is ideally designed for software engineers, information scientists, medical professionals, researchers, developers, educators, academicians, and students.

In financially constrained health systems across the world, increasing emphasis is being placed on the ability to demonstrate that health care interventions are not only effective, but also cost-effective. This book deals with decision modelling techniques that can be used to estimate the value for money of various interventions including medical devices, surgical procedures, diagnostic technologies, and pharmaceuticals. Particular emphasis is placed on the importance of the appropriate representation of uncertainty in the evaluative process and the implication this uncertainty has for decision making and the need for future research. This highly practical guide takes the reader through the key principles and approaches of modelling techniques. It begins with the basics of constructing different forms of the model, the population of the model with input parameter estimates, analysis of the results, and progression to the holistic view of models as a valuable tool for informing future research exercises. Case studies and exercises are supported with online templates and solutions. This book will help analysts understand the contribution of decision-analytic modelling to the evaluation of health care programmes. ABOUT THE SERIES: Economic evaluation of health interventions is a growing specialist field, and this series of practical handbooks will tackle, in-depth, topics superficially addressed in more general health economics books. Each volume will include illustrative material, case histories and worked examples to encourage the reader to apply the methods discussed, with supporting material provided online. This series is aimed at health economists in academia, the pharmaceutical industry and the health sector, those on advanced health economics courses, and health researchers in associated fields.

Over the past decade health care systems around the world have placed increasing importance on the relationship between patient choice and clinical decision-making. In the years since the publication of the second edition of Shared Decision Making in Health Care, there have been significant new developments in the field, most notably in the US where 'Obamacare' puts shared decision making (SDM) at the centre of the 2009 Affordable Care Act. This new edition explores shared decision making by examining, from practical and theoretical perspectives, what should comprise an effective decision-making process. It also looks at the benefits and potential difficulties that arise when patients and clinicians share health care decisions. Written by leading experts from around the world and utilizing high quality evidence, the book provides an up-to-date reference with real-word context to the topics discussed, and in-depth coverage of the practicalities of implementing and teaching SDM. The breadth of information in Shared Decision Making in Health Care makes it the definitive source of expert knowledge for healthcare policy makers. As health care systems adapt to increasingly collaborative patient-clinician care frameworks, this will also prove a useful guide to SDM for clinicians of all disciplines.

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.