Assignent Solutionnurs

Using predictive analytics to identify possible sepsis patients early in their hospital stays suggests focusing on sepsis. Provide research on how some organizations are addressing sepsis with predictive analytics. Choose one organization and give some data from their use of predictive analytics for sepsis. What risk assessments were used? Did they employ a pre-existing/published algorithm or create their own? Describe the model components used to identify patients at high risk for sepsis. Summarize the model’s strengths and weaknesses. Would you recommend using this model? What is your reasoning?
Chosen organization: UI Health hospital uses The Epic Sepsis Model (ESM). The ESM is a proprietary sepsis prediction model developed by Epic Systems Corporation using data routinely recorded within the EHR. This data includes elements from SIRS, SOFA, qSOFA, MEWS, and other variables. A sepsis risk score is generated based on risk factors identified by the prediction model. The threshold score to trigger a Sepsis Best Practice Advisory (BPA) at Hospital is set at 6 or higher.
Please refer to the CLINICAL MANAGEMENT OF SEPSIS IN THE ADULT PATIENT POPULATION pdf attachment. It describes the components used by UI Health hospital for their Sepsis predictive analytics.
I would recommend this model as it combines different components to predict sepsis more accurately.
Some helpful articles:
SIRS, SOFA, qSOFA, and MEWS — The Alphabet Soup-
https://www.dascena.com/articles/sirs-sofa-qsofa-and-mews-the-alphabet-soup
Comparison of qSOFA, SIRS and NEWS-
Wang C, Xu R, Zeng Y, Zhao Y, Hu X (2022) A comparison of qSOFA, SIRS and NEWS in predicting the accuracy of mortality in patients with suspected sepsis: A meta-analysis. PLOS ONE 17(4): e0266755. https://doi.org/10.1371/journal.pone.0266755
SOFA vs SIRS
Harimtepathip, P., Lee, J. R., Griffith, E., Williams, G., Patel, R. V., Lebowitz, D., & Koochakzadeh, S. (2018). Quick Sepsis-related Organ Failure Assessment Versus Systemic Inflammatory Response Syndrome Criteria for Predicting Organ Dysfunction and Mortality. Cureus, 10(10), e3511. https://doi.org/10.7759/cureus.3511
SOFA
Hendricks, R. M. (2019) Process Mining of Incoming Patients with Sepsis. Online Journal of Public Health Informatics, 11(2). https://journals.uic.edu/ojs/index.php/ojphi/article/view/10151/8093
SOFA
Hewett, J. N., Rodgers, G. W., Chase, J. G., Le Compte, A. J., Pretty, C. G., & Shaw, G. M. (2012). Assessment of SOFA score as a diagnostic indicator in intensive care medicine. IFAC Proceedings Volumes, 45(18), 467-472. https://doi.org/https://doi.org/10.3182/20120829-3-HU-2029.00035