Models and methods of work system design need to be developed and implemented to advance research in and design for patient safety. In this paper we describe how the Systems Engineering Initiative for Patient Safety (SEIPS) model of work system and patient safety, which provides a framework for understanding the structures, processes and outcomes in health care and their relationships, can be used toward these ends. An application of the SEIPS model in one particular care setting (outpatient surgery) is presented and other practical and research applications of the model are described. 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. 1-3Emphasis 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. A comparison of the strengths and weaknesses of the SEIPS model, the Reason/Vincent model, and Donabedian's quality model is shown in table 1. The SEIPS model explains how the design of the work system can impact not only the safety of patients but also employee and organizational outcomes. Employee outcomes include safety, health, satisfaction, stress and burnout; organizational outcomes include rates of turnover, injuries and illnesses, and organizational health (profitability).In this paper we describe the SEIPS model and its research and pra...

Healthcare practitioners, patient safety leaders, educators, and researchers increasingly recognize the value of human factors/ergonomics and make use of the discipline’s person-centered models of sociotechnical systems. This paper first reviews one of the most widely used healthcare human factors systems models, the Systems Engineering Initiative for Patient Safety (SEIPS) model, and then introduces an extended model, “SEIPS 2.0.” SEIPS 2.0 incorporates three novel concepts into the original model: configuration, engagement, and adaptation. The concept of configuration highlights the dynamic, hierarchical, and interactive properties of sociotechnical systems, making it possible to depict how health-related performance is shaped at “a moment in time.” Engagement conveys that various individuals and teams can perform health-related activities separately and collaboratively. Engaged individuals often include patients, family caregivers, and other non-professionals. Adaptation is introduced as a feedback mechanism that explains how dynamic systems evolve in planned and unplanned ways. Key implications and future directions for human factors research in healthcare are discussed.

Human factors systems approaches are critical for improving healthcare quality and patient safety. The SEIPS (Systems Engineering Initiative for Patient Safety) model of work system and patient safety is a human factors systems approach that has been successfully applied in healthcare research and practice. Several research and practical applications of the SEIPS model are described. Important implications of the SEIPS model for healthcare system and process redesign are highlighted. Principles for redesigning healthcare systems using the SEIPS model are described. Balancing the work system and encouraging the active and adaptive role of workers are key principles for improving healthcare quality and patient safety.

No abstract

FMEA was useful in identifying potential problems in the medication-use process with the implementation of new smart i.v. pumps. Monitoring for system failures and errors after implementation remains necessary.