2019 John M. Eisenberg Patient Safety and Quality Awards: A Model Cell for Transformational Redesign of Sepsis Identification and Treatment: Aligning Digital Tools with Innovative Workflows

Background: Readmission after hospitalization, increased morbidity, and high levels of mortality are not uncommon in patients diagnosed with sepsis. Sepsis bundles designed to mitigate the deleterious effects have been recommended for nearly a decade. Despite this, mortality remains high, sepsis bundle requirements controversial, and bundle compliance low. Methods: A health system implemented a multidisciplinary project to decrease the mortality rate of sepsis. A Model Cell mental model was adopted. Data on mortality and compliance were gathered from four acute care hospitals in the system and analyzed. The observed mortality data were compared to predictive data based on comparable acute care facilities. Results: Regression analysis showed significant increases in bundle compliance rates at each site (p < 0.05), reflecting the continuous use of the methods described above. Mortality systemwide decreased significantly in response to increased bundle compliance (r = 0.80, r(2) = 0.64, p < 0.001), with compliance alone accounting for nearly two thirds of the variance in the linear model. The observed results revealed a median mortality rate of 5.7% (95% confidence interval [CI] = 5.1%-7.3%, n = 23), 1.9 percentage points lower than predicted when compared to similar institutions. When using only the final 12 months of the project, the median mortality drops further to 5.3% (95% CI = 3.9%-5.6%, n = 12), 2.5 percentage points less than predicted. Conclusion: The Model Cell intervention was successful in increasing bundle compliance, which then decreased mortality. This model can be enhanced as technology improves and is well positioned for artificial intelligence to help drive further success.