Funded by a $1.2 million Agency for Healthcare Research and Quality grant, Montefiore Health System is building a new artificial intelligence (AI) screening tool to help doctors better identify and treat acute respiratory distress syndrome (ARDS), a deadly, but under-recognized, form of lung failure. Acute respiratory distress syndrome (ARDS) is a rapidly progressive disease occurring in critically ill patients.
The main complication in ARDS is that fluid leaks into the lungs making breathing difficult or impossible. Approximately 200,000 people in the United States suffer from ARDS and is often fatal as risk increases with age and severity of illness. The biggest challenge for doctors is that up to 40 percent of the time it can be missed.
To resolve this, researchers and data and computer scientists are building off of Montefiore Einstein’s existing AI platform, combing through years of de-identified patient data to determine dozens of critical, objective data points for ARDS. After developing a profile, the AI screening tool will run in the background of the electronic medical record system, flagging any patients who match the profile created for ARDS. This ARDS-specific tool is an extension of the work already conducted by the Critical Care and health data teams at Montefiore Einstein, which shows that AI can improve outcomes for people with another lung condition—severe acute respiratory failure.
“ARDS is under-recognized because these patients are often extremely ill and have other life-threatening conditions, such as shock, pneumonia, or trauma. Since diagnosis depends on the patient meeting a number of criteria, it is easy for one of the criteria to be attributed to another acute condition, rather than to ARDS,” said Dr. Michelle Ng Gong, chief of Research, Critical Care at Montefiore Health System and professor of medicine and of epidemiology & population health at Albert Einstein College of Medicine. “By using new technology we hope to help clinicians identify ARDS as early as possible, when treatment may be most effective.”
