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1.  Human factors systems approach to healthcare quality and patient safety 
Applied ergonomics  2013;45(1):14-25.
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.
doi:10.1016/j.apergo.2013.04.023
PMCID: PMC3795965  PMID: 23845724
sociotechnical system; macroergonomics; health care; patient safety; SEIPS model; balanced work system; patient-centered care; healthcare team
2.  SEIPS 2.0: A human factors framework for studying and improving the work of healthcare professionals and patients 
Ergonomics  2013;56(11):10.1080/00140139.2013.838643.
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.
doi:10.1080/00140139.2013.838643
PMCID: PMC3835697  PMID: 24088063
healthcare; work system; patient-centered care; patient and family engagement; SEIPS model
3.  Automation and adaptation: Nurses’ problem-solving behavior following the implementation of bar coded medication administration technology 
The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses’ operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA’s impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians’ work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign.
doi:10.1007/s10111-012-0229-4
PMCID: PMC3891738  PMID: 24443642
Adaptation; problem solving; health information technology; bar coded medication administration (BCMA); nursing
4.  Information Chaos in Primary Care: Implications for Physician Performance and Patient Safety 
Purpose
The purpose of this paper is to explore the concept of information chaos as it applies to the issues of patient safety and physician workload in primary care and to propose a research agenda.
Methods
We use a human factors engineering perspective to discuss the concept of information chaos in primary care and explore implications for its impact on physician performance and patient safety.
Results
Information chaos is comprised of various combinations of information overload, information underload, information scatter, information conflict, and erroneous information. We provide a framework for understanding information chaos, its impact on physician mental workload and situation awareness, its consequences, discuss possible solutions and suggest a research agenda which may lead to methods to reduce the problem.
Conclusions
Information chaos is experienced routinely by primary care physicians. This is not just inconvenient, annoying and frustrating; it has implications for physician performance and patient safety. Additional research is needed to define methods to measure and eventually reduce information chaos.
doi:10.3122/jabfm.2011.06.100255
PMCID: PMC3286113  PMID: 22086819
Primary Health Care; Information Management/Informatics; Complexity Science; Medical Errors; Practice Management

Results 1-4 (4)