Abstract
Cognitive systems engineering (CSE), systems engineering, and additional human factors methodologies for the design and improvement of health-care systems are paramount to safe, effective, and efficient health care. Given the complex nature of sociotechnical health-care systems requiring significant cognitive work, the use of CSE approaches is much needed but not well integrated into the design and continued improvements of health systems.
This book provides readers with an opportunity to examine numerous examples of CSE approaches. Four broad themes are described: (a) consistent focus on the impact of CSE, (b) CSE to inform design of information technology, (c) adaptation and application of CSE in the medical domain, and (d) the idea that in-depth CSE analysis can lead to demonstrated system improvements.
The book is not overly long and does not focus on describing different CSE methodological approaches. Case studies depict findings and how data were analyzed and utilized. For specific methodologies, readers are referred to other references, such as journal articles, giving more information, including outcomes. Each of 8 chapters begins with a discussion of the importance of CSE, which, after several chapters, tends to become repetitious. However, the examples for each case study are different enough to illustrate ways in which CSE can be applied.
Examples across chapters include information technology and techniques for improving decision support, teaming, displays for emergency departments, and other cognitive work in hospitals or surgical centers. The chapter “Information Modeling for Cognitive Work in a Health Care System” provides an in-depth discussion of the methodology of the Information Trail Model. The examples are important given their real-world applications, and the book provides information useful for health-care system improvement and design – which is important to human factors specialists for assisting in advancing good-quality health care.
The editors argue that the case examples and research studies provide evidence of the impact of CSE. However, although the examples take place in real-world environments, most described case studies do not end with indications of adoption of suggested changes. For the few indicating adoption, there were no data to illustrate system improvement or impact after adoption. This is not to say that impact did not occur; just that there is a lack of evidence. Also not provided are case studies in clinics, where most health care occurs in the United States, which may be more difficult to study due to the need to access and coordinate among many different facilities.
Primary audiences for this book include (a) health-care professionals who support process improvement within their organizations and who are interested in learning about techniques beyond the more traditional six sigma training often provided in hospital organizations; (b) health-care professionals and designers of new health-care technologies or those working to improve existing technologies; and (c) students of human factors. Readers with little or no experience in CSE or human factors will gain an understanding of the advantages of including considerations of human cognitive capabilities when designing work and technologies in health systems. These are particularly important because professionals focused on health care may be less interested to read case studies from other domains, such as aviation, manufacturing, and process control.
The content supports a broad overview; therefore, health-care professionals would need in-depth training, or support from CSE and human factors professionals to support projects. Human factors students will benefit because this book provides specific case study examples within health systems and can prompt ideas for projects or research. Experienced human factors professionals may review the case studies to learn of techniques they may not have considered, or to serve as examples to health-care stakeholders with whom they are working to illustrate work in other organizations.
Footnotes
Jennie J. Gallimore, PhD, is a professor of industrial and human factors engineering and associate dean of research and graduate studies in the College of Engineering and Computer Science at Wright State University, Ohio. Her research focuses on human factors and systems engineering in complex systems. She teaches courses and conducts research in health systems, including specific process improvement and the use of virtual training simulation with the Dayton Veterans Administration Medical Center. Jennie also has extensive human factors research experience in the domain of aviation.