In hospitals around the world, ICU hospital beds and ventilators are reserved for patients—regardless of age—who are in critical condition and require mechanical support to keep their bodies functioning and to fight the onset of sepsis. This condition is a complication caused by the human body’s response to infection, and it can lead to organ failure and death, accounting for 1 in 5 deaths globally.
Though hospitals have a nurse-led sepsis screening approach in place that is effective, safe, and sustainable, sepsis continues to be the leading cause of death in the USA. The Global Sepsis Alliance even considers it a global health crisis, with close to 50 million cases and 11 million deaths every year—that’s 1 death every 2.8 seconds. What’s more, experts have suggested a link between sepsis and COVID-19, with respiratory failure as the predominant organ failure in COVID-associated deaths.
Must-read: Can predictive analytics help COVID-19 deaths from rising with early sepsis intervention?
COVID-19 affects both the young and the old, and although an elderly person’s chance of recovery is lower, it’s not impossible. With a pandemic rippling across the globe today, it has become even more important to accelerate the detection and diagnosis of patients at risk of sepsis. Through rapid diagnosis and treatment, sepsis or a septic shock can be prevented.
The role of predictive analytics in early sepsis care
Sepsis is a disease that acts quickly. To illustrate: Mortality from sepsis increases by as much as 8% for every hour that treatment is delayed. By the time sepsis is diagnosed with a manual process, it is often too late to prevent the patient’s death.
This is why proactive and timely intervention is critical, and predictive analytics plays a crucial role in this regard. Through machine learning, medical frontliners can identify patients at risk of developing sepsis using patient data such as demographics, vitals, and lab results.
Fortunately, the medical field is no stranger to the importance of analytics capabilities. According to the Society of Actuaries 2017 survey, 93% of healthcare organizations say predictive analytics is important to the future of their business, with 89% of providers currently using predictive analytics or planning to do so by 2022. There are some hurdles to full implementation—lack of budget is considered one of the top setbacks, followed by regulatory issues (e.g. HIPAA), incomplete data, lack of skilled employees, lack of sufficient technology, too much data, patient matching, and lack of confidence. Despite this, 57% of healthcare executives at organizations currently using predictive analytics expect to save 15% or more of their total budget, while 26% forecast saving 25% or more over the next five years by using predictive analytics processes.
At the end of the day, lives can be saved with advanced tools in place—whether we are in a pandemic or not.
Implementing analytics solutions
Analytics can serve as a trusted advisor when making a decision that has significant consequences, and having access to predictive analytics at the point of care is key to early sepsis intervention.
Here at Ducen IT, we are passionate about identifying patients at risk of developing sepsis—early in the process—in critical healthcare areas like in emergency departments, surgical units, and the NICU. With predictive modeling applied to real-time patient data, proactive treatment and early intervention is made possible with real-time insights of patient at risk of sepsis.
We are happy to demonstrate how we have used Analance™ Predictive Analytics to make early sepsis care possible. Contact us for more information.