Utilizing Nursing Informatics in Sepsis Quality Improvement According to the Centers for Disease Control and Prevention (CDC) (2016) from 1999-2014 over 2 million Americans have died with sepsis listed as a contributing cause, making sepsis the 11th leading cause of death in the United States. Jones et al. (2016) and Jones et al. (2015) report sepsis costing hospitals over 20 billion dollars in 2011, and Medicare and Medicaid reimbursed over 17 billion of those costs. Thus, the CMS initiated the SCIP program in an effort to mediate sepsis events. In addition to mediation, the Centers for Medicare & Medicaid Services (CMS) (2015) has started tracking sepsis and sepsis care as a part of value based purchasing, in an effort to improve safe quality
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Though, post-operative sepsis has remained refractory to this initiative. Therefore, Giuliano, Lecardo, and Staul (2011) statistics regarding prompt treatment outlined by the SSC decreasing sepsis mortality by virtually 16% becomes imperative. Dellinger et al. (2013) evidence-based diagnostic criteria for the SSC includes general (temperature, tachypnea, tachycardia, etc.), inflammatory (altered WBC counts), hemodynamic (low blood pressure, map, etc.), organ dysfunction (creatinine, ileus, oliguria, etc.), and tissue perfusion (lactate, decreased capillary refill) signs and symptoms, and was developed from systematic review of randomized controlled trials. As Nelson and Staggers (2014) explain evidence based practice as a function of health informatics systems, by providing the right information at the right point in time to provide safe, timely, effective, efficient, equitable, and patient-centered care. Consequently, through utilizing clinical decision support tools formatted on evidence-based practice meaningless data points are transformed into information, which can be utilized to provide the knowledge necessary for early sepsis recognition adherent to the Blum Model for …show more content…
Gyang, Shieh, Forsey, and Maggio (2015) implemented and tested the sensitivity and specificity of a SSC derived screening tool, and found an accuracy of 92%, which remains compliant with informatics need for effective systems (Nelson & Staggers, 2014). Jones et al. (2015) fully integrated a nurse-driven screening tool derived from the SSC into an EHR, and found the system to reduce transcription error, provide improvements in data interpretation, and was completed by nurses in less than one minute adherent to informatics need of efficiency (Nelson & Staggers, 2014). Jones et al. (2016) added a time component to the point-of-care CDS sepsis screening tool, which prompted nurses to complete necessary data entry every 12 hours creating increased satisfaction due to decreased cognitive load. Consequently, through implementing evidence based screening early recognition process within an EHR results show an effective efficient, and satisfactory point-of-care CDS
Though, post-operative sepsis has remained refractory to this initiative. Therefore, Giuliano, Lecardo, and Staul (2011) statistics regarding prompt treatment outlined by the SSC decreasing sepsis mortality by virtually 16% becomes imperative. Dellinger et al. (2013) evidence-based diagnostic criteria for the SSC includes general (temperature, tachypnea, tachycardia, etc.), inflammatory (altered WBC counts), hemodynamic (low blood pressure, map, etc.), organ dysfunction (creatinine, ileus, oliguria, etc.), and tissue perfusion (lactate, decreased capillary refill) signs and symptoms, and was developed from systematic review of randomized controlled trials. As Nelson and Staggers (2014) explain evidence based practice as a function of health informatics systems, by providing the right information at the right point in time to provide safe, timely, effective, efficient, equitable, and patient-centered care. Consequently, through utilizing clinical decision support tools formatted on evidence-based practice meaningless data points are transformed into information, which can be utilized to provide the knowledge necessary for early sepsis recognition adherent to the Blum Model for …show more content…
Gyang, Shieh, Forsey, and Maggio (2015) implemented and tested the sensitivity and specificity of a SSC derived screening tool, and found an accuracy of 92%, which remains compliant with informatics need for effective systems (Nelson & Staggers, 2014). Jones et al. (2015) fully integrated a nurse-driven screening tool derived from the SSC into an EHR, and found the system to reduce transcription error, provide improvements in data interpretation, and was completed by nurses in less than one minute adherent to informatics need of efficiency (Nelson & Staggers, 2014). Jones et al. (2016) added a time component to the point-of-care CDS sepsis screening tool, which prompted nurses to complete necessary data entry every 12 hours creating increased satisfaction due to decreased cognitive load. Consequently, through implementing evidence based screening early recognition process within an EHR results show an effective efficient, and satisfactory point-of-care CDS