International Journal for Quality in Health Care 14:427-428 (2002)
© 2002 International Society for Quality in Health Care
Book Review |
Statistical Process Control for Health Care
Center for Quality of Care Research and Education, Harvard School of Public Health, Boston, MA, USA
Statistical Process Control for Health Care
Published in 2002 by Wadsworth Group, Pacific Grove, CA, USA.
ISBN 0-534-37865-X, 343 pp, Price: $77.95.
In health care, there are common concerns about cost, quality, and effectiveness. Hospitals and health care providers are expected to maintain the highest possible levels of quality without contributing unnecessarily to the continuing escalation of health care costs. In this context, appropriate tools are required to help hospitals and service providers monitor and assess aspects of service and to guide them to make better decisions.
The central problem in quality improvement is to determine the nature and sources of variation in a process or an outcome measure and to determine which of these variations need to be addressed in order to improve service quality. Large variation indicates that an aspect is out of control, so that there is a need to determine the sources of the variation and to identify the best method of correction. In a complex health care system, if we do not wholly understand the causes of variation existing in a process or outcome measure we cannot properly and appropriately improve the process.
In Statistical Process Control for Health Care, authors Marilyn K. Hart and Robert F. Hart discuss Statistical Process Control (SPC) methods to be used for quality control. Process-focused quality control utilizes statistical methods to determine the sources of variability in a process or outcome measure, and this approach has been successfully used in the industrial context. Over the past two decades, there has been growing interest in health care for the adoption of the kind of quality improvement approach that is the focus of this book.
The book is divided into 10 chapters. Chapter 1 provides a brief introduction to useful quality improvement tools, e.g. pareto charts, cause-and-effect diagrams, run charts, control charts, and so forth. The concept of variation in quality control, i.e. special cause and common cause of variation, is also introduced.
Chapter 2 discusses basic descriptive statistical concepts, e.g. average, range, variance, standard deviation, and normal distribution, in order to understand and use the process examination tools to be introduced later in the book. Anyone who is not yet familiar with quality improvement strategies and tools, but who intends to use SPC in practice, needs to read this chapter to overcome any lack of knowledge of basic statistical ideas that may hinder understanding of more complicated SPC application examples in later chapters.
Chapters 3–6 cover the following: the run chart, I-chart, Xbar and s-chart, and process capability, the tools used for continuous variables. These chapters provide a variety of examples of SPC applications, ranging from a relatively simple run chart to the more complicated Xbar and s-chart. A new user of SPC will undoubtedly benefit a great deal from these chapters.
Chapters 7 and 8 discuss the c-chart, u-chart, and p-chart, these tools being used for attribute (i.e. discrete) data.
A major area of discussion that many experienced SPC users might find helpful is that of data transformation, which is covered in Chapter 9. In the real world, the near-normal assumption is often not met. The purpose of data transformation is to make data near-normal so that the statistical approaches that make this assumption are appropriate. Hence, this chapter is useful not only for those who are relatively unfamiliar with the topics, but also for those who are experienced with SPC methods but unfamiliar with data transformation.
Chapter 10 provides a simple and quick guide on how to choose a specific control chart for a particular application. A benchmarking example is also provided, which gives the reader a good grasp of how quality improvement techniques can be used for such purposes.
This book provides health care providers and quality managers with the basic skills they need to carry out quality improvement projects using quantitative SPC methods. It is written as a practical guide for applying SPC (i.e. applications and illustrations of SPC) in health care settings. Although the authors have chosen to use the Minitab and Statit programs for the practical applications of SPC, these datasets can be downloaded in other data formats (e.g. SPSS, SAS, Excel) and thus the reader can easily practice using other statistical programs.
The book is quite comprehensive in its illustration of SPC analytical strategies, and throughout, Hart and Hart place emphasis on a hands-on approach. The examples and case studies illustrating the selection of appropriate techniques, interpretation, and use of results are from real hospital data sets. There is no question that these real examples give the readers a very realistic taste of the SPC process, and guide them through particular aspects and/or tools. Overall, the authors clearly explain the statistics in basic terms, and illustrate calculations with very practical short examples.
A successful quality improvement program is determined by the availability of quality data, knowing how to turn such data into valuable information, then using this information to make timely decisions and take appropriate actions. When faced with a pile of data, not knowing what to do with it or how to make sense of it, this book can provide a useful resource in helping practitioners and quality managers to successfully adopt SPC in health care settings. The book is also a useful guide for ways to improve service processes and outcomes through transforming data into valuable information, displaying variation and determining lack of control, understanding what is happening in the process, and determining which variations need to be addressed and how to inform decision-makers.
In summary, this book provides a comprehensive illustration of how SPC can be applied in the real world, and can be used to identify special cause variation and to improve service processes and outcomes. It should be particularly useful for those who have little or no knowledge of SPC. For health care providers who want to improve their service processes and outcomes, this book provides a valuable guide to how they may achieve their goals. For health care practitioners and quality managers who wish to adopt SPC methods effectively and accurately, this is a useful resource and practical guide with helpful illustrations of SPC analytical strategies, which includes a useful discussion of practical issues related to management considerations.
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