GE HealthCare Signs $44 Million Contract with BARDA to Develop AI-Enhanced POCUS Technology for Mass Casualty Events
GE HealthCare has entered into a $44 million contract with the Biomedical Advanced Research and Development Authority (BARDA), part of the Administration for Strategic Preparedness and Response (ASPR) within the U.S. Department of Health and Human Services. The collaboration aims to develop advanced point-of-care ultrasound technology with new artificial intelligence (AI) applications, focusing on the rapid diagnosis and treatment of lung pathologies and traumatic injuries to the abdomen, chest, and head in preparedness for potential mass casualty events.
Point-of-care ultrasound (POCUS) plays a vital role in emergency situations by providing clinicians with quick answers to aid in patient triage. GE HealthCare’s collaboration with BARDA seeks to leverage ultrasound and AI applications to develop innovative solutions for identifying a range of traumatic injuries and lung pathologies. The goal is to enhance clinicians’ ability to deliver timely care to trauma patients, even in the most-dire circumstances.
As part of this collaboration, GE HealthCare plans to build new technology designed to expedite trauma triage and treatment, potentially transforming the standard of care. The project will include the development of an advanced probe and ultrasound system, combined with novel AI technology to facilitate the acquisition and interpretation of ultrasound exams for users of all skill levels. This approach aims to increase the number of capable users and make care delivery more efficient. The devices developed will cover indications for various injury types, including blunt and penetrating trauma, head trauma, lung injuries, and multiple lung pathologies.
GE Healthcare is a market leader in imaging solutions and notably in point of care ultrasound systems. The company currently ultrasound sales at a run rate of over $3 billion a year with multiple point-of-care systems and has been working on the integration of AI technology into its devices to improve clinical functionality.