Methods: We evaluated patients in annual intervals before and after bundle implementation in March 2013. We evaluated bundle compliance and compared outcome measures across groups with multivariable logistic regression. Because of their perceived risk for iatrogenic fluid overload, we also evaluated patients with a history of heart failure and/or chronic kidney disease.Measurements and Main Results: We identified 18,122 patients with sepsis and intermediate lactate values, including 36.1% treated after implementation. Full bundle compliance increased from 32.2% in 2011 to 44.9% after bundle implementation (P , 0.01). Hospital mortality was 8.8% in 2011, 9.3% in 2012, and 7.9% in 2013 (P = 0.02). Treatment after bundle implementation was associated with an adjusted hospital mortality odds ratio of 0.81 (95% confidence interval, 0.66-0.99; P = 0.04). Decreased hospital mortality was observed primarily in patients with a heart failure and/or kidney disease history (P , 0.01) compared with patients without this history (P . 0.40). This corresponded to notable changes in the volume of fluid resuscitation in patients with heart failure and/or kidney disease after implementation.Conclusions: Multicenter implementation of a treatment bundle for patients with sepsis and intermediate lactate values improved bundle compliance and was associated with decreased hospital mortality. These decreases were mediated by improved mortality and increased fluid administration among patients with a history of heart failure and/or chronic kidney disease.

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Abstract:Improving quality and safety across an entire healthcare system in multiple clinical areas within a short time frame is challenging. We describe our experience with improving inpatient quality and safety at Kaiser Permanente Northern California. The foundations of performance improvement are a “four-wheel drive” approach and a comprehensive driver diagram linking improvement goals to focal areas. By the end of 2011, substantial improvements occurred in hospital-acquired infections (central-line–associated bloodstream infections and Clostridium difficile infections); falls; hospital-acquired pressure ulcers; high-alert medication and surgical safety; sepsis care; critical care; and The Joint Commission core measures.

Background: Most clinical trials of sepsis treatment modalities fail at their primary objective of establishing superiority over placebo when added to background standard of care. While there is no definitive explanation for the high failure rate, it might be stated that our attempts to insert a new therapeutic agent into standard of care encounters severe problems with definition of exactly what stage is ongoing, and what are the criteria for progression or resolution from that time point onwards. Clearly there is need for a means of defining steps in the septic process that would apply to individuals, and to better define the course of sepsis in each patient after they are enrolled in a trial. Methods: For core model development, 30 septic patients were studied for time-related progression in relation to biomarkers, employing a Load Model in a neural net algorithm in MatLab. Causative bacterial infections were linked to primary infection sites. In order to minimize overparameterization, the model was allowed to estimate outputs using the best three input parameters. Bacterial load was tracked from origin using clinical and microbiologic data to provide an estimate at the start of sepsis. The bacterial load as well as clinical and laboratory parameters were model inputs with the output parameter being organ failures and/ or mortality. Results: At onset of sepsis, human bacterial load estimates ranged from between 10 8 and 10 11 CFU, which is consistent with inocula in animal models of sepsis. Sepsis proceeds to organ failures and mortality in a series of steps that are initially linked to bacterial load and inflammatory response, followed by coagulopathy, ischemia, oxygen deprivation in organs and tissues, and culminating in organ failures. The later stages of sepsis are all driven by metabolic parameters, and there seems to be little benefit to blocking inflammation at later stages. Substrate and oxygen deficiencies must be addressed first. Conclusion: Neural net progression models based on biomarkers and physiological markers are able to describe the evolution of sepsis to septic shock, organ failures, and provide some evidence that mortality may be a consequence of the stages of sepsis. Overall, these models appear useful to the task of sorting out organ failure endpoints and mechanisms in individual patients with sepsis progression across sepsis to septic shock. P2 Extracellular matrix turnover, angiogenesis and endothelial function in acute lung injury: relationship to pulmonary dysfunction and outcome

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