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.

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.

Evidence-Based Decision-Making: How to Leverage Available Data and Avoid Cognitive Biases examines how a wide range of factual evidence, primarily derived from a variety of data available to organizations, can be used to improve the quality of business decision-making, by helping decision makers circumvent the various cognitive biases that adversely impact how we all think. The book is built on the following premise: During the past decade, the new ‘data world’ emerged, in which the rush to develop competencies around business analytics and data science can be characterized as nothing less than the new commercial arms race. The ever-expanding volume and variety of data are well known, as are the great advances in data processing/analytics, data visualization, and related information production-focused capabilities. Yet, comparatively little effort has been devoted to how the informational products of business analytics and data science are ‘consumed’ or used in the organizational decision-making processes, as the available evidence shows that only some of that information is used to drive some business decisions some of the time. Evidence-Based Decision-Making details an explicit process describing how the universe of available and applicable evidence, which includes organizational and other data, industry benchmarks, scientific studies, and professional experience, can be assessed, amalgamated, and funneled into an objective driver of key business decisions. Introducing key concepts in relation to data and evidence, and the history of evidence-based management, this new and extremely topical book will be essential reading for researchers and students of data analytics as well as those working in the private and public sectors, and in the voluntary sector.

For the past few years, the author, a renowned economist, has been applying the statistical tools of economics to decision making under uncertainty in the context of patient health status and response to treatment. He shows how statistical imprecision and identification problems affect empirical research in the patient-care sphere.

This book is based on the International Conference on Decision Economics (DECON 2019). Highlighting the fact that important decision-making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, psychology, small and international business, management, operations, and production, the book focuses on analytics as an emerging synthesis of sophisticated methodology and large data systems used to guide economic decision-making in an increasingly complex business environment. DECON 2019 was organised by the University of Chieti-Pescara (Italy), the National Chengchi University of Taipei (Taiwan), and the University of Salamanca (Spain), and was held at the Escuela politécnica Superior de Ávila, Spain, from 26th to 28th June, 2019. Sponsored by IEEE Systems Man and Cybernetics Society, Spain Section Chapter, and IEEE Spain Section (Technical Co-Sponsor), IBM, Indra, Viewnext, Global Exchange, AEPIA-and-APPIA, with the funding supporting of the Junta de Castilla y León, Spain (ID: SA267P18-Project co-financed with FEDER funds)

This book provides a robust set of health economic principles and methods to inform societal decisions in relation to research, reimbursement and regulation (pricing and monitoring of performance in practice). We provide a theoretical and practical framework that navigates to avoid common biases and suboptimal outcomes observed in recent and current practice of health economic analysis, as opposed to claiming to be comprehensive in covering all methods. Our aim is to facilitate efficient health system decision making processes in research, reimbursement and regulation, which promote constrained optimisation of community outcomes from a societal perspective given resource constraints, available technology and processes of technology assessment. Importantly, this includes identifying an efficient process to maximize the potential that arises from research and pricing in relation to existing technology under uncertainty, given current evidence and associated opportunity costs of investment. Principles and methods are identified and illustrated across health promotion, prevention and palliative care settings as well as treatment settings. Health policy implications are also highlighted.

This text recognises the need for evidence-based principles in economic evaluation, and that they should be based themselves on health economics. It discusses systematic review in economic analysis and suggests how to perform analyses in an evidence-based way.