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Most errors and inefficiencies in patient care arise not from the solitary actions of individuals but from conflicting, incomplete, or suboptimal systems of which they are a part and with which they interact. To improve the design of these systems, the US Institute of Medicine (IOM) has proposed the application of engineering concepts and methods-in particular, human factors and systems engineering. 1- 3 Emphasis on system design was promoted in a recent report by the National Academy of Engineering and the IOM: "... it is time to... establish a vigorous new partnership between engineering and health care and hasten a transition to a patient-centered 21st century health care system ". 4 Our research program, the Systems Engineering Initiative for Patient Safety (SEIPS, http://www2.fpm.wisc.edu/seips/ ), originally funded by the Agency for Healthcare Research and Quality, meets this challenge through a novel integration of human factors and healthcare quality models and proposes the SEIPS model of work system 5- 7 and patient safety.
Patient safety researchers clearly recognize the need for human factors engineering and systems approaches to patient safety research, analysis, and improvement. However, noticeably missing from the patient safety literature are models to guide studies to empirically examine system design in relation to patient safety and medical errors. The model described by Reason, 8 often referred to as the "Swiss cheese" model, is probably the most well known system model used within the patient safety community. Vincent et al 9 have expanded Reason's model and described seven categories of factors that influence clinical practice, such as organizational and management factors, work environment, team factors, task factors and patient characteristics. The Haddon model, which is used commonly in epidemiology and injury prevention, has been proposed for use in quality and safety. 10 It defines three categories of the environment as potential contributors to patient safety: physical (e.g. noise), social (e.g. poor communication), and biological (e.g. patient factors). Our SEIPS model 5- 7 goes further by clearly specifying the system components that can contribute to causes and control of medical errors, incidents and adverse events, showing the nature of the interactions between the components, showing how the design of the components and their interactions can contribute to acceptable or unacceptable processes, and nesting itself in...