Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a larg...

This brief uses California’s CURES (Controlled Substance Utilization Review and Evaluation System) 2.0 data to analyze county-level opioid prescribing rates in California from 2012 to 2017 from multiple perspectives. The book summarizes California’s county-level opioid prescribing trends, examines potential correlates of opioid prescribing rates, and assesses the association of opioid prescribing on both criminal justice and public health outcomes. Finally, the authors discuss their princi...

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 re...

Now in its fourth edition, Medical Statistics at a Glance is a concise and accessible introduction to this complex subject. It provides clear instruction on how to apply commonly used statistical procedures in an easy-to-read, comprehensive and relevant volume. This new edition continues to be the ideal introductory manual and reference guide to medical statistics, an invaluable companion for statistics lectures and a very useful revision aid.This new edition of Medica...

Statistics for the Health Sciences is a highly readable and accessible textbook on understanding statistics for the health sciences, both conceptually and via the SPSS programme. The authors give clear explanations of the concepts underlying statistical analyses and descriptions of how these analyses are applied in health science research without complex maths formulae.The textbook takes students from the basics of research design, hypothesis testing and descriptiv...

This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased...

This comprehensive workbook contains a variety of self-assessment methods that allow readers to test their statistical knowledge, put it into practice, and apply it in a medical context, while also providing guidance when critically appraising published literature. It is designed to support the best-selling third edition of Medical Statistics at a Glance, to which it is fully cross-referenced, but may ...

A clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studiesThe first edition of this text was widely acclaimed for the clarity of the presentation, and quickly established itself as the definitive text in this field. The fully updated second edition includes new and expanded content on avoiding common mistakes in meta-analysis, understanding heterogeneity in effects, publication bias, and more. Several bran...

This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-...

This concise book will help you to interpret the statistical evidence provided by quantitative studies and to plan how to work with data in your own clinical research. Following the successful format of the Toolkit series, Statistics Toolkit guides the reader through statistical concepts using flowcharts, diagrams and real life examples to reflect concepts in a simple and practical manner.Sections include:Clear explanation of basic concepts in the contex...

This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modelling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasises problem solving strategies that address the many issues arising when developing multi-variable models using real data and not standard t...

Having an understanding of critical appraisal and evidence-based medicine is a prerequisite to being an effective clinician. However, critical appraisal is often taught by people not involved in day-to-day clinical care, meaning the clinical relevance is not always brought to the fore.This book takes a different approach. It is written by clinicians, for clinicians. It takes the reader step by step through the process so that any journal article can be easily read, evidence evaluat...