|First Author (Year)||Conceptual Framework||Design/ |
|Major Variables Studies (and Their Definitions)||Sample and Setting||Measurement||Data Analysis||Findings||Appraisal: Worth to Practice|
|Armen (2016)||There is a possibility to reduce sepsis mortality by providing evidence-based guidelines for early recognition and proper treatment. The objective is to create an educational program on sepsis identification and treatment and to spread it throughout the hospitals to reduce the odds of dying.||A case-control study||The independent variable is the absence/presence of an educational guideline, and the dependent variable is the fatal outcome caused by the disease.||The study included 1401 patients in intensive care units from January 2009 to September 2010 for the control period and 1331 patients in intensive care units from October 2010 to December 2011 for the intervention period. The participants had similar basic demographic and severe sepsis; however, intervention patients had higher expected mortality.||Ordinal scale||The odds of mortality during the intervention period were 30% lower than during the control period. Patients during the intervention period spent 1-2 fewer days on average in hospitals. The multidisciplinary sepsis control initiative and introduction of educational guidelines reduced the overall mortality by 4,6%, which is statistically significant.||The study demonstrated the efficiency of proper educational programs on early identification and treatment of sepsis compared to traditional hospital care methods. The introduction of sepsis treatment bundles also has been shown to improve guideline adherence and sepsis survival for intensive care unit patients.||Yes.|
|Fleischmann (2016)||The issue with high sepsis mortality rates can be solved by providing comprehensive data from multiple countries on incidence and outcomes. Comparative data analysis will be able to identify knowledge gaps in sepsis treatment.||A systematic databases review and meta-analysis||The independent variable is the observed country, the dependent variable is the fatal outcome caused by the disease.||The research examined 1553 reports from 1979 to 2015, and 27 published studies were used for meta-analysis. The final results include observations from seven high-income countries and provide separate tables for sepsis and severe sepsis.||Ordinal scale||The incidence of hospital-treated sepsis was the lowest in Northern Europe (from 3 to 49 cases per 100,000 person-years) and the highest in the United States (over 1000 cases per 100,000 person-years). The estimated fatality rates in the years 2003-2015 were 18% for sepsis and 26% for severe sepsis.||The study provided a detailed presentation on sepsis incidence in high-income countries. A knowledge gap was found in the absence of data or epidemiological studies from low- and middle-income countries. Additionally, a variety of sepsis and severe sepsis definitions appeared to cause heterogeneity between single-study estimates.||Yes.|
|Manaktala (2017)||A computerized system of sepsis alerting algorithms was created to establish precise detection of sepsis and highly sensitive support via a mobile application. A hypothesis was made that this approach will result in the reduction of sepsis mortality.||A case-control study||The independent variable is the absence/presence of sepsis alerting algorithms, and the dependent variable is the fatal outcome caused by the disease.||The study included 5414 patients from January 2011 to October 2013 for the control period and 1974 patients from March 2014 to December 2014 for the intervention period. The site of research was Huntsville Hospital in Huntsville, Alabama. The average age for participants was 63 years, and 49% of the patients were female, with no significant differences between control and study periods.||Ordinal scale||A 53% decrease in mortality was noticed during the intervention period, and the patients examined by the electronic system appeared to have a 2.1 times lower risk of death. The computerized system seemed to have excellent detection accuracy with 95% sensitivity and 82% specificity for sepsis cases in comparison to gold standard chart physician review.||The implementation of a computer-based surveillance system proved to be precise in the early detection of sepsis and establishing decision support for specific cases. The fatality rates significantly reduced after introducing an electronic system; therefore, it could be considered highly efficient for hospitals.||Yes|
|Moore (2016)||There is a need to assess the community characteristics associated with sepsis mortality in the United States. It can be achieved by identifying counties with the highest sepsis mortality rates.||A retrospective study||The independent variable is the community characteristics, and the dependent variable is the fatal outcome caused by the disease.||The study included 3108 counties and observed a total of 1,451,986 sepsis-related deaths in the years from 2003 to 2012. The patients were categorized by demographic and divided by the level of clustering.||Ordinal scale||The average age-adjusted mortality rate in the US was 59.6 deaths per 100,000 persons, while the mortality rate in strongly clustered counties was 93.1 deaths per 100,000 persons. Areas categorized as strongly clustered were likely to be located in the South. They had lower education, a higher percentage of poverty and unemployment, and a common absence of medical insurance.||Since the highest rates of sepsis mortality clustering were found to be in Southern US, the study identified such community characteristics as lower education, income, employment, and insurance coverage to be influential on sepsis mortality.||Yes|
|Rhee (2017)||Clinical data from hospitals can be used to identify the changes in sepsis incidence and sepsis mortality in recent years and estimate the general tendencies to increase or decrease.||A retrospective cohort study||The independent variable is the incidence of sepsis, and the dependent variable is the fatal outcome caused by the disease.||The study included clinical data from 409 hospitals and observed a total of 173,690 cases of sepsis from 2009 to 2014.||Nominal scale||Sepsis incidence from 2009-2014 was stable; while in-hospital mortality reduced by 3.3%, there was no significant change in the combined outcome of death or discharge to hospice (it reduced by 1,3%).||Despite in-hospital mortality decreasing, the overall incidence and the number of deadly outcomes do not change significantly. This disproves studies that suggest sepsis incidence to increase over time.||Yes.|
Armen, S. B., Freer, C. V., Showalter, J. W., Crook, T., Whitener, C. J., West, C., Terndrup, T. E., Grifasi, M., DeFlitch, C. J., & Hollenbeak, C. S. (2016). Improving outcomes in patients with sepsis. American Journal of Medical Quality, 31(1), 56-63. Web.
Fleischmann, C., Scherag, A., Adhikari, N. K., Hartog, C. S., Tsaganos, T., Schlattmann, P., Angus, D. C., & Reinhart, K. (2016). Assessment of global incidence and mortality of hospital-treated sepsis. Current estimates and limitations. American Journal of Respiratory and Critical Care Medicine, 193(3), 259-272. Web.
Manaktala, S., & Claypool, S. R. (2017). Evaluating the impact of a computerized surveillance algorithm and decision support system on sepsis mortality. Journal of the American Medical Informatics Association, 24(1), 88-95. Web.
Moore, J. X., Donnelly, J. P., Russell Griffin, D., Howard, G., Safford, M. M., & Wang, H. E. (2016). Defining sepsis mortality clusters in the United States. Critical Care Medicine, 44(7), 1380-1387. Web.
Rhee, C., Dantes, R., Epstein, L., Murphy, D. J., Seymour, C. W., Iwashyna, T. J., Kadri, S. S., Angus, D. C., Danner, R. L., Fiore, A. E., Jernigan, J. A., Martin, G. S., Septimus, E., Warren, D. K., Karcz, A., Chan, C., Menchaca, J. T., Wang, R., Gruber, S., & Klompas, M. (2017). Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009-2014. JAMA, 318(13), 1241-1249. Web.