Assesses ways to determine how well medical treatments actually work. Presents a new strategy for medical effectiveness research called "cross design synthesis" which represents an important step in advancing knowledge about the effectiveness of medical treatments, based not only on the results of randomized clinical trials but also on data reflecting wide experience in the field. Charts and tables.

Providing state-of-the-art perspectives on what evaluation is, its purpose, and how to ensure it is done well, this book brings together major evaluation researchers from a variety of social and behavioral science disciplines. Each chapter identifies a fundamental issue facing the field today; considers its implications for theory, method, practice, or the profession; and explores one or more approaches to dealing with the issue. Among the topics addressed are the nature of expertise in evaluation, how to build a better evidence base for evaluation theory, promoting cultural competence in evaluation, how to synthesize evaluation research findings, ways to involve stakeholders in decision making, and much more.

The biggest challenge in any marketplace is uncertainty. The major changes taking place in world economies, politics, and demographics has raised market uncertainty to its highest level in the past 50 years. However, with new markets opening up in emerging and developing economies, the opportunities have never been better. To compete in this challe

READ ALL ABOUT IT! David Spiegelhalter has recently joined the ranks of Isaac Newton, Charles Darwin and Stephen Hawking by becoming a fellow of the Royal Society. Originating from the Medical Research Council’s biostatistics unit, David has played a leading role in the Bristol heart surgery and Harold Shipman inquiries. Order a copy of this author’s comprehensive text TODAY! The Bayesian approach involves synthesising data and judgement in order to reach conclusions about unknown quantities and make predictions. Bayesian methods have become increasingly popular in recent years, notably in medical research, and although there are a number of books on Bayesian analysis, few cover clinical trials and biostatistical applications in any detail. Bayesian Approaches to Clinical Trials and Health-Care Evaluation provides a valuable overview of this rapidly evolving field, including basic Bayesian ideas, prior distributions, clinical trials, observational studies, evidence synthesis and cost-effectiveness analysis. Covers a broad array of essential topics, building from the basics to more advanced techniques. Illustrated throughout by detailed case studies and worked examples Includes exercises in all chapters Accessible to anyone with a basic knowledge of statistics Authors are at the forefront of research into Bayesian methods in medical research Accompanied by a Web site featuring data sets and worked examples using Excel and WinBUGS - the most widely used Bayesian modelling package Bayesian Approaches to Clinical Trials and Health-Care Evaluation is suitable for students and researchers in medical statistics, statisticians in the pharmaceutical industry, and anyone involved in conducting clinical trials and assessment of health-care technology.

Every year a vast number of research studies and a myriad of other forms of ‘evidence’ are produced that have potential to inform policy and practice. Synthesis provides a way of bringing together diverse kinds of evidence to bridge the so called ‘gap’ between evidence and policy. This book provides a comprehensive overview of the range of approaches and methods available for synthesising qualitative and quantitative evidence and a detailed explanation of why this is important. It does this by: Looking at the different types of review and examining the place of synthesis in reviews for policy and management decision making Describing the process of conducting and interpreting syntheses Suggesting questions which can be used to assess the quality of a synthesis Synthesising Qualitative and Quantitative Health Evidence is essential reading for students and professional researchers who need to assemble and synthesise findings and insights from multiple sources. It is also relevant to policy makers and practitioners in the field of health, and those working in other areas of social and public policy.

Comparative effectiveness research (CER) is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care (IOM 2009). CER is conducted to develop evidence that will aid patients, clinicians, purchasers, and health policy makers in making informed decisions at both the individual and population levels. CER encompasses a very broad range of types of studies—experimental, observational, prospective, retrospective, and research synthesis. This volume covers the main areas of quantitative methodology for the design and analysis of CER studies. The volume has four major sections—causal inference; clinical trials; research synthesis; and specialized topics. The audience includes CER methodologists, quantitative-trained researchers interested in CER, and graduate students in statistics, epidemiology, and health services and outcomes research. The book assumes a masters-level course in regression analysis and familiarity with clinical research.