This ground-breaking book addresses the critical, growing need among health care administrators and practitioners to measure the effectiveness of quality improvement efforts. Written by respected healthcare quality professionals, Measuring Quality Improvement in Healthcare covers practical applications of the tools and techniques of statistical process control (SPC), including control charts, in healthcare settings. The authors' straightforward discussions of data collection, variation, and process improvement set the context for the use and interpretation of control charts. Their approach incorporates "the voice of the customer" as a key element driving the improvement processes and outcomes. The core of the book is a set of 12 case studies that show how to apply statistical thinking to health care process, and when and how to use different types of control charts. The practical, down-to-earth orientation of the book makes it accessible to a wide readership. "Only authors who have used statistics and control charts to solve real-world healthcare problems could have written a book so practical and timely." - Barry S. Bader, Publisher The Quality Letter for Healthcare Leaders "Many clinicians and other healthcare leaders underestimate the great contributions that better statistical thinking could make toward reducing costs and improving outcomes. This fascinating and timely book is a fine guide for getting started." - Donald M. Berwick, M.D. President and CEO, Institute for Healthcare Improvement Associate Professor of Pediatrics, Harvard Medical School Contents: Planning Your CQI Journey, Preparing to Collect Data, Data Collection, Understanding Variation, Using Run and Control Charts to Analyze Process Variation, Control Chart Case Studies, Developing Improvement Strategies, Using Patient Surveys for CQI, Formulas for Calculating Control Limits

With today's growing emphasis on quality improvement, training individuals in fundamental quality control skills is a major challenge. Professionals in manufacturing industries need to bring processes into statistical control – and maintain them. This book is designed to help readers learn the statistical tools and concepts needed to develop and use quality control effectively.

For freshman/sophomore level introductory courses in SPC (Statistical Process Control), Statistical Quality Control or Quality Control found in two and four-year college curriculums, and in industrial training programs. This mathematics-friendly text introduces students to basic concepts and applications of Statistical Process Control (SPC). Students get a solid foundation in control charts-including setting scales, charting, interpreting, and analyzing process capability. Problem-solving techniques are emphasized, and all learning is linked to the implementation of SPC in the workplace.

The business, commercial and public-sector world has changed dramatically since John Oakland wrote the first edition of Statistical Process Control – a practical guide in the mid-eighties. Then people were rediscovering statistical methods of ‘quality control’ and the book responded to an often desperate need to find out about the techniques and use them on data. Pressure over time from organizations supplying directly to the consumer, typically in the automotive and high technology sectors, forced those in charge of the supplying production and service operations to think more about preventing problems than how to find and fix them. Subsequent editions retained the ‘took kit’ approach of the first but included some of the ‘philosophy’ behind the techniques and their use. The theme which runs throughout the 7th edition is still processes - that require understanding, have variation, must be properly controlled, have a capability, and need improvement - the five sections of this new edition. SPC never has been and never will be simply a ‘took kit’ and in this book the authors provide, not only the instructional guide for the tools, but communicate the management practices which have become so vital to success in organizations throughout the world. The book is supported by the authors' extensive and latest consulting work within thousands of organisations worldwide. Fully updated to include real-life case studies, new research based on client work from an array of industries, and integration with the latest computer methods and Minitab software, the book also retains its valued textbook quality through clear learning objectives and end of chapter discussion questions. It can still serve as a textbook for both student and practicing engineers, scientists, technologists, managers and for anyone wishing to understand or implement modern statistical process control techniques.

A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control describes many recent SPC methods that improve upon