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Rev. ed. of: Practical approach to analyzing healthcare data / Lynn Kuehn. c2009.
The Health Care Data Guide is designed to help students and professionals build a skill set specific to using data for improvement of health care processes and systems. Even experienced data users will find valuable resources among the tools and cases that enrich The Health Care Data Guide. Practical and step-by-step, this book spotlights statistical process control (SPC) and develops a philosophy, a strategy, and a set of methods for ongoing improvement to yield better outcomes. Provost and Murray reveal how to put SPC into practice for a wide range of applications including evaluating current process performance, searching for ideas for and determining evidence of improvement, and tracking and documenting sustainability of improvement. A comprehensive overview of graphical methods in SPC includes Shewhart charts, run charts, frequency plots, Pareto analysis, and scatter diagrams. Other topics include stratification and rational sub-grouping of data and methods to help predict performance of processes. Illustrative examples and case studies encourage users to evaluate their knowledge and skills interactively and provide opportunity to develop additional skills and confidence in displaying and interpreting data. Companion Web site: www.josseybass.com/go/provost
The field's bestselling reference, updated with the latest tools, data, techniques, and the latest recommendations from the Second Panel on Cost-Effectiveness in Health and Medicine Cost-Effectiveness Analysis in Health is a practical introduction to the tools, methods, and procedures used worldwide to perform cost-effective research. Covering every aspect of a complete cost-effectiveness analysis, this book shows you how to find which data you need, where to find it, how to analyze it, and how to prepare a high-quality report for publication. Designed for the classroom or the individual learner, the material is presented in simple and accessible language for those who lack a biostatistics or epidemiology background, and each chapter includes real-world examples and "tips and tricks" that highlight key information. Exercises throughout allow you to test your understanding with practical application, and the companion website features downloadable data sets for students, as well as lecture slides and a test bank for instructors. This new third edition contains new discussion on meta-analysis and advanced modeling techniques, a long worked example using visual modeling software TreeAge Pro, and updated recommendations from the U.S. Public Health Service's Panel on Cost-Effectiveness in Health and Medicine. This is the second printing of the 3rd Edition, which has been corrected and revised for 2018 to reflect the latest standards and methods. Cost-effectiveness analysis is used to evaluate medical interventions worldwide, in both developed and developing countries. This book provides process-specific instruction in a concise, structured format to give you a robust working knowledge of common methods and techniques. Develop a thoroughly fleshed-out research project Work accurately with costs, probabilities, and models Calculate life expectancy and quality-adjusted life years Prepare your study and your data for publication Comprehensive analysis skills are essential for students seeking careers in public health, medicine, biomedical research, health economics, health policy, and more. Cost-Effectiveness Analysis in Health walks you through the process from a real-world perspective to help you build a skillset that's immediately applicable in the field.
Have gaps in health outcomes between the poor and better off grown? Are they larger in one country than another? Are health sector subsidies more equally distributed in some countries than others? Are health care payments more progressive in one health care financing system than another? What are catastrophic payments and how can they be measured? How far do health care payments impoverish households? Answering questions such as these requires quantitative analysis. This in turn depends on a clear understanding of how to measure key variables in the analysis, such as health outcomes, health expenditures, need, and living standards. It also requires set quantitative methods for measuring inequality and inequity, progressivity, catastrophic expenditures, poverty impact, and so on. This book provides an overview of the key issues that arise in the measurement of health variables and living standards, outlines and explains essential tools and methods for distributional analysis, and, using worked examples, shows how these tools and methods can be applied in the health sector. The book seeks to provide the reader with both a solid grasp of the principles underpinning distributional analysis, while at the same time offering hands-on guidance on how to move from principles to practice.
Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. - Covers data analysis, management and security concepts and tools in the healthcare domain - Highlights electronic medical health records and patient information records - Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining - Includes multidisciplinary contributions in relation to healthcare applications and challenges
Healthcare is changing, and data is the catalyst Data is taking over in a powerful way, and it's revolutionizing the healthcare industry. You have more data available than ever before, and applying the right analytics can spur growth. Benefits extend to patients, providers, and board members, and the technology can make centralized patient management a reality. Despite the potential for growth, many in the industry and government are questioning the value of data in health care, wondering if it's worth the investment. Data-Driven Healthcare: How Analytics and BI are Transforming the Industry tackles the issue and proves why BI is not only worth it, but necessary for industry advancement. Healthcare BI guru Laura Madsen challenges the notion that data have little value in healthcare, and shows how BI can ease regulatory reporting pressures and streamline the entire system as it evolves. Madsen illustrates how a data-driven organization is created, and how it can transform the industry. Learn why BI is a boon to providers Create powerful infographics to communicate data more effectively Find out how Big Data has transformed other industries, and how it applies to healthcare Data-Driven Healthcare: How Analytics and BI are Transforming the Industry provides tables, checklists, and forms that allow you to take immediate action in implementing BI in your organization. You can't afford to be behind the curve. The industry is moving on, with or without you. Data-Driven Healthcare: How Analytics and BI are Transforming the Industry is your guide to utilizing data to advance your operation in an industry where data-fueled growth will be the new norm.
In this age of information, the manipulation, analysis, and interpretation of data have become a fundamental part of professional life; nowhere more so than in the delivery of healthcare. From the understanding of disease and the development of new treatments, to the diagnosis and management of individual patients, the use of data and technology is now an integral part of the business of healthcare. Those working in healthcare interact daily with data, often without realising it. The conversion of this avalanche of information to useful knowledge is essential for high-quality patient care. R for Health Data Science includes everything a healthcare professional needs to go from R novice to R guru. By the end of this book, you will be taking a sophisticated approach to health data science with beautiful visualisations, elegant tables, and nuanced analyses. Features Provides an introduction to the fundamentals of R for healthcare professionals Highlights the most popular statistical approaches to health data science Written to be as accessible as possible with minimal mathematics Emphasises the importance of truly understanding the underlying data through the use of plots Includes numerous examples that can be adapted for your own data Helps you create publishable documents and collaborate across teams With this book, you are in safe hands – Prof. Harrison is a clinician and Dr. Pius is a data scientist, bringing 25 years’ combined experience of using R at the coal face. This content has been taught to hundreds of individuals from a variety of backgrounds, from rank beginners to experts moving to R from other platforms.
The only data visualization book written by and for health and healthcare professionals. In health and healthcare, data and information are coming at organizations faster than they can consume and interpret it. Health providers, payers, public health departments, researchers, and health information technology groups know the ability to analyze and communicate this vast array of data in a clear and compelling manner is paramount to success. However, they simply cannot find experienced people with the necessary qualifications. The quickest (and often the only) route to meeting this challenge is to hire smart people and train them. Visualizing Health and Healthcare Data: Creating Clear and Compelling Visualizations to "See how You're Doing" is a one-of-a-kind book for health and healthcare professionals to learn the best practices of data visualization specific to their field. It provides a high-level summary of health and healthcare data, an overview of relevant visual intelligence research, strategies and techniques to gather requirements, and how to build strong teams with the expertise required to create dashboards and reports that people love to use. Clear and detailed explanations of data visualization best practices will help you understand the how and the why. Learn how to build beautiful and useful data products that deliver powerful insights for the end user Follow along with examples of data visualization best practices, including table and graph design for health and healthcare data Learn the difference between dashboards, reports, multidimensional exploratory displays and infographics (and why it matters) Avoid common mistakes in data visualization by learning why they do not work and better ways to display the data Written by a top leader in the field of health and healthcare data visualization, this book is an excellent resource for top management in healthcare, as well as entry-level to experienced data analysts in any health-related organization.