Human Performance Considerations
in Medical Systems Design

Lawrence J. Hettinger, PhD

Senior Human Factors Engineer
Northrop Grumman Information Technologies

Failures in the performance of human-machine systems can generally be attributed to one of two causes (and sometimes both) – limitations and/or failures in the technical performance of the system, and limitations and/or failures in human performance in the operation of the system.  The optimization of technical and human use considerations are both essential in ensuring safe and effective system performance.  However, traditional paradigms for the design of complex sociotechnical systems have largely focused on technical considerations while drastically underemphasizing the impact of human performance limitations.  As a result, the potential for human error is often literally designed into new systems, and potential insights on achieving superior system performance are left unexplored.

            How can emerging computer-based medical technologies (e.g., computer-aided surgery, virtual environment training systems, image guided surgery systems, etc.) be designed to achieve a functional balance between good technical design and good design with respect to the performance requirements and limitations of the user?  What methods and principles can be applied to the design process to reduce the likelihood of human error while also enhancing overall system performance?

            In this talk I will address these issues from the perspective of several related disciplines, all devoted to varying degrees on developing principles for the design of safe and effective human-machine systems – human factors/cognitive systems engineering, engineering psychology, and human-systems integration.  While traditionally focused on problems associated with aviation, the nuclear industry, and assorted Department of Defense applications, in recent years the attention of these fields has increasingly turned to the medical domain.  I will discuss methods, findings, and ongoing issues in these fields as they related to the area of medical systems design.