The model combines four measurements to support real-time decision-making: stroke severity, frailty risk score, timing of intervention and thrombolysis utilization, according to a Jan. 28 news release from Ochsner.
When integrated into an EMR, the model can proactively identify which stroke patients would “benefit from immediate surgery and who may need ‘pre-habilitating’ before surgery to achieve better outcomes,” Hernan Bazan, MD, a senior author of the study and the John Ochsner Professor of Cardiovascular Innovation at Ochsner Health, said in the release.
Read the full study here.
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.
