Mednition, makers of machine learning-powered software solutions for healthcare, today announced an early sepsis detection initiative. As one of the leading causes of death in the U.S. and a condition that drives the highest cost of hospitalization each year, sepsis is responsible for more than $27 billion in hospital costs annually.
This coming week at ACEP19, the premier industry event for emergency medicine professionals and the flagship event for the American College of Emergency Physicians, Mednition will demonstrate a beta version of the machine learning powered solution, KATE, which is designed specifically to improve sepsis identification while decreasing sepsis-related mortality. Preliminary results of this new prototype model have a sensitivity (True Positive Rate) of 90% and specificity (True Negative Rate) of 87% with an AUC of 0.949. This high-performance result is achieved with only Emergency Department triage data and does not include laboratory test results.
As part of its sepsis initiative, Mednition also announced that it has appointed Stephen Liu, MD, FACEP, a leading emergency medicine physician, educator and researcher, to the company’s clinical advisory board and to help lead the sepsis program. Dr. Liu is an Emergency Physician with VEP Healthcare, Inc., as well as Medical Director and Attending Staff Physician, Emergency Services, at Adventist Health White Memorial (AHWM) in Los Angeles where he was named Physician of the Year in 2016. He has served in a similar capacity at other hospitals.
Each year, approximately 1.7 million people in the U.S. develop sepsis resulting in more than 275,000 deaths. Along with being the number one cost of hospitalization in the U.S., it is the leading cause of hospital readmissions. Additionally, one in three in-hospital deaths is caused by sepsis.
“Sepsis doesn’t generate public attention like cancer or heart disease does,” said Steven Reilly, CEO and co-founder of Mednition. “But when people understand how prevalent it is, how many lives it claims each year and how much it costs us as a society, they see why we need to get it under control. Our early sepsis detection initiative is a major step in that direction, and we are thrilled to have Stephen join us to help drive this program throughout the emergency medicine community nationwide.”
Dr. Liu was previously a member of the Board of Directors of Cal/ACEP and VEP Healthcare, Inc. He also was instrumental in the implementation of KATE, Mednition’s machine learning powered clinical decision support solution, at AHWM. The hospital’s emergency department (ED) nurses have been using KATE in triage since December 2018. Additionally, Dr. Liu has been on the AHWM sepsis steering committee for the last six years.
“Sepsis is a quiet killer,” said Dr. Liu. “I’ve been working hands on with the team at Mednition and the emergency clinicians at AHWM for the past year, and I’ve seen the promise of machine learning delivered to ED nurses on a daily basis right where it is needed most, in real-time at the point of care. Mednition’s early sepsis detection prototypes show high accuracy with a low false positive rate. We’re going to use machine learning to turn the tables on sepsis!”