COVID-19 research by PeraHealth, Inc., Yale New Haven Health (YNHHS), and LifeBridge Health’s Sinai Hospital of Baltimore, has found that the Rothman Index score, a measure of patient acuity, helps identify COVID-19 patients with high risk of mortality, including those who may not be obvious or in a known high-risk category. A study of 1,669 COVID-19 patients across four hospitals in Connecticut and Maryland demonstrated that Rothman Index (RI) score, which can be calculated upon patient admission using the patient’s current health characteristics, accurately groups the majority of COVID-19 patients into high-risk (43% mortality rate) and low-risk (less than 5% mortality rate) categories.
A subset of COVID-19 patients experience sudden and severe deterioration which can be a challenge for front-line clinicians to judge using standard metrics. The Rothman Index offers a real-time, objective clinical tool for hospitals to rapidly identify COVID-19 patients that are at the highest risk of expiring. The Rothman Index’s patented algorithm uses machine learning/AI to calculate a patient’s health score using vital signs, lab results, and nursing assessments of a variety of bodily systems.
With COVID-19 cases in the United States surging to their highest levels, many hospital ICUs are starting to reach capacity and care providers are looking for a rapid, automated, and objective measure to help triage COVID-19 patient risk. Using the Rothman Index, high-risk patients can be assigned to the ICU or higher levels of care, while low-risk patients can be treated in lower levels of care or from home. While providing the appropriate level of care can help improve quality outcomes for COVID-19 patients, understanding the volume of high-risk patients can also help predict and plan for ICU capacity, ventilator requirements, clinical staffing and other resource requirements.
When discussing unmet medical challenges for COVID-19, Dr. Jaime Barnes, chair of the Department of Medicine at Sinai Hospital and Northwest Hospital and a critical care medicine physician at LifeBridge Health states, “One of the challenges with COVID-19 is the identifying of patients who have a higher risk of subsequent deterioration. With these research results, we are interested to see how having validated predictive analytics can play a role in how we manage these complex cases of people with COVID-19.”
Up until this point in the COVID-19 pandemic, efforts to identify “at-risk” patients have frequently focused on the patient’s age and pre-existing conditions. The Rothman Index goes beyond this by directly capturing the patient’s acuity, regardless of their age or condition. Recent analysis shows that the Rothman Index can segment out the 20-25% of admitted COVID-19 patients who are at significantly elevated risk for deterioration and most likely to need ventilation, ICU level of care, or who may ultimately expire in the hospital. These are the patients who need extra attention and may warrant placement in a higher level of care from the time of admission. Those decisions can improve a patient’s chances of survival.
Thomas Donohue, MD, Cardiologist and vice president for Medicine Services with Yale New Haven Health states, “At our peak, we had more than 800 COVID positive patients throughout our health system all with varying levels of patient needs. A tool like this, that can help risk stratify these patients and facilitate appropriate levels of care, can have a significant impact on outcomes.”
“We are very encouraged by the results of the COVID-19 patient analysis at YNHHS and LifeBridge Health,” said PeraHealth CEO Greg White. “The dedication these institutions show through their continuous innovation and research to combat COVID-19 is remarkable. We are standing alongside them to use the best technology we have to improve a patient’s chances of surviving this disease. Our collective efforts will no doubt save lives, as well as help plan for required resources as the Rothman Index solution is expanded in clinical practice.”
Would you like to connect with the research team? Join us for the upcoming live webinar, “How to Identify High Risk COVID-19 Patients upon Hospital Admission.”
The scientific article detailing the COVID patient analysis can be found in the following link: https://www.medrxiv.org/content/10.1101/2020.08.13.20171751v1