Advanced illness patients represent only about 6.5% of the Medicare population yet they drive the majority of cost, utilization, and negative outcomes, specifically about 35% of adverse events, 50% of readmissions, and more than half of inpatient deaths.
Predictive models help to identify these specific patients early on in their hospital journey. This enables proactive clinical decision making, timely follow-up care, reduced readmissions, and higher quality care.
Raphael Cohen
VP AI and Engineering
With expertise in machine learning, cloud computing, and healthcare, Raphael translates complex technical challenges into practical healthcare solutions. He’s pioneered ML platforms to drive innovations in radiology, pathology, and anesthesia while simultaneously improving operational efficiency and scale. Outside of work, he’s an avid cyclist who regularly participates in the Pan-Mass Challenge, enjoys hiking the White Mountains, and is often found playing guitar. He received a BS in Computer Science and Applied Mathematics from Brandeis University.