are carried out. These ambiguities are compounded by the natural tendency to work around problems rather than engage in problem solving to address the underlying causes (Senge, 1990; Spear and Schmidhofer, 2005). Systematic problem solving, grounded in the scientific method, requires that staff work in teams to identify a problem, discover the underlying factors behind the problem, create a plan to address those factors, implement the solution thus generated, and measure whether the solution is achieving the desired results (Furman and Caplan, 2007; Spear, 2005; Young et al., 2004). Sometimes a team’s first approximation of a solution to an identified problem will fail, but this, too, presents a learning opportunity. Through multiple iterations, these closed-loop learning cycles have the potential to yield answers as to how the unit, the department, and ultimately the whole institution can standardize complex processes for optimal effectiveness and efficiency and the highest quality of care (Garvin, 1993; Lukas et al., 2007; Spear, 2006; Toussaint, 2009). They represent a tool organizations can use to learn from errors and inefficiencies to drive improvement. The benefits can be substantial. For example, Denver Health introduced Lean process improvement across the organization in 2006 and by 2012 had realized $151 million in financial benefits, as well as the lowest observed-to-expected hospital mortality rate in the University Healthsystem Consortium, a consortium of academic medical centers and affiliated hospitals (Cosgrove et al., 2012).

This sort of systems-based problem solving requires that employees be willing to experiment, seek out new knowledge, and anticipate problems instead of addressing only problems immediately at hand. It requires an organizational culture that incentivizes experimentation among staff—one that recognizes failure as key to the learning process and does not penalize employees if their experiments are unsuccessful. Further, because these projects are undertaken by employees, they require that employees possess skills that include experiment design, workflow analysis, storyboarding, and statistical analysis (Garvin, 1993).

This kind of employee engagement has been found to be effective in sustaining quality improvement efforts in leading organizations. In a study of four high-value hospitals, the most efficient organizations translated the tools of systems-based problem solving beyond their quality improvement departments, training their clinical and nonclinical staff in process improvement methods (Edwards et al., 2011). Such training yields a staff that is more engaged in problem solving and that, in solving problems, gains a sense of accomplishment and enthusiasm and generates forward momentum for further efforts (Edwards et al., 2011; Lukas et al., 2007). To encourage a spirit of continuous learning and improvement among health care employees, systems tools such as organizational management, human factors engineering, and process improvement could be incorporated into

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