professional education and continuing education curricula (IOM and NAE, 2005; Spear, 2006).
Numerous examples of effective uses of systems-based problem solving show how engineering principles can be applied to embed quality, safety, and patient-centeredness into care delivery. A variety of such methods are available for achieving improvement in health care, including Total Quality Management, Six Sigma, Lean, Plan-Do-Study-Act cycles, and hybrid approaches, their success depending on various contextual factors (Chassin and Loeb, 2011; Kaplan et al., 2010). One application of systems engineering principles is for standardizing care protocols. Through multiple iterations of problem-solving cycles, learning organizations have been able to elucidate standard protocols and guidelines for a variety of clinical conditions and processes. In so doing, they have streamlined patient care while allowing for the variation in practice required to tailor treatment to each patient’s unique circumstances.
For example, a team at Intermountain’s LDS Hospital created a clinical practice guideline for managing ventilator settings in the treatment of acute respiratory distress syndrome. The guideline underwent multiple iterations, with 125 changes being made within the first 4 months of use, now down to 1-2 changes per month. Implementing this guideline has increased patient survival from 9.5 to 44 percent while saving physicians time and the hospital money (James and Savitz, 2011). Standard protocols for clinical processes also can improve safety. In 2009, Kaiser Permanente’s Sepsis Care Performance Initiative established protocols for early intervention and treatment for sepsis; the result was a more than 50 percent decrease in sepsis mortality (Cosgrove et al., 2012). Additionally, in response to variations in practice and failures to follow evidence-based protocols, checklists have been developed to improve care for ventilated patients, for central venous catheterized intensive care unit patients, for surgical patients, and for patients with catheter-related blood stream infections (Berenholtz et al., 2004a,b; Hales and Pronovost, 2006; Haynes et al., 2009; Pronovost et al., 2006a). Such interventions are prime examples of system redesign to prevent human error in complex systems—errors that can cause downstream effects such as patient harm, poorer outcomes, and potential malpractice claims (Gawande, 2007; Hales and Pronovost, 2006; IOM, 2001; Kohn et al., 2000; Winters et al., 2011). Systems-based problem solving also has been applied off the front lines, as illustrated in Box 9-3.
Systems engineering methods have been used as well to reduce variability in hospital admissions. In response to mismatches between available resources and patient demand that result in long wait times for patients and empty beds for hospitals, learning organizations have implemented methods for decreasing the variability in patient admissions from emergency departments and elective procedures. Not only does the smoothing of peaks and