While not widely recognized or understood by the general population, sepsis, a serious medical condition caused by an immune response to infection according to the National Institute of General Medical Sciences, has a significant impact on U.S. healthcare. Not only is sepsis a major patient safety concern, but it is also the leading cause of hospital mortality and the nation’s third leading cause of death. In fact, sepsis contributes to one in every two to three deaths, resulting in 258,000 patient deaths each year. Moreover, it’s considered the most expensive condition to treat in the U.S. healthcare system, costing more than $24 billion each year.
With these staggering statistics, it is shocking that only 55 percent of U.S. adults even know about sepsis. September is Sepsis Awareness Month, and as such, its goal is to not only improve overall education on this condition and its risks with the general population, but also to encourage clinical discussions on ways to treat sepsis more effectively, such as leveraging early warning technology to drive earlier detection for timely clinical intervention.
Nurses Can’t Get Any Faster
One of the greatest challenges related to sepsis is that once symptoms become apparent, the patient is already in a critical physiological state. The risk of death from sepsis increases by 7.6 percent each hour that passes before treatment begins. This rapid decline demonstrates the importance of detecting signs of sepsis earlier, even before they become visible.
Nurses are already moving as fast as they can to keep up with a patient population that continues to get sicker and sicker. While speed of care is critical to controlling sepsis and reducing related mortality rates, it’s not a matter of asking nurses to work faster, but rather leveraging validated technological tools to work smarter. Real-time clinical surveillance can help detect subtle signs of patient deterioration that may indicate sepsis, enabling nurses and care teams to intervene sooner and prevent further clinical deterioration as a result of sepsis.
Symptoms and Other Factors to Analyze
Predictive technology and tools that analyze health data, can help clinicians predict and detect declining patient conditions in a timely fashion. Under normal circumstances, when determining whether a patient is septic, body temperature, heart rate, respiratory rate, level of consciousness and white blood cell count are factors that are currently considered. While the aforementioned are valuable clinical variables to assess, they provide a fragmented view of the patient, whereas the nursing assessment in conjunction with other diagnostics provides a comprehensive assessment of the patient.
Patient assessments, conducted from head-to-toe, enable nurses to holistically examine the linked systems of the human body. When systematic patient assessments are used in conjunction with diagnostic findings (labs, imaging, etc.), clinical care teams can identify clinical deterioration trends and take action when symptoms of sepsis are first apparent, before the patient further deteriorates.
Data Driving Decisions
The healthcare industry at large stands to benefit greatly from leveraging data and analytics to provide better care and reduce costs. Not only will leveraging data and predictive analytics technology make the delivery of care more proactive, but it can also transform care team workflow. Real-time and predictive clinical surveillance tools synthesizing available clinical data can paint a detailed picture of a patient’s condition, signaling broad signs of deterioration before they’re otherwise noticeable. Early warning signs of these changes enable care teams to react to these types of changes before further progression occurs, and situations become urgent or emergent, thereby proactively reducing the need of a rapid response or code blue.
Not only will this effective use of data drive more proactive delivery of healthcare broadly, but it is the key to preventing and treating sepsis. Experts predict that 80 percent of sepsis-related deaths may have been prevented with more rapid diagnosis and treatment. Predictive analytics can accelerate delivery of care to patients with signs of deterioration before their conditions become critical, ensuring the patient receives timely and appropriate care for their respective clinical scenario.
Learning the signs and symptoms of sepsis, or even learning about the disease itself, is a much needed step towards improved sepsis awareness and education in the general population, while considering the impact of technology in order to detect and timely intervene is imperative for clinicians and healthcare leaders. Envision a world in which all clinicians leverage available healthcare data to predict and recognize subtle changes in patient conditions, eliminating late-stage treatment of sepsis entirely. The potential for existing and future healthcare technology is exciting and powerful, and this month it will be front and center in the fight against sepsis.