News|Ultrasound Imaging| May 24, 2022

Butterfly Blueprint to enable MUSC clinicians, students, and researchers to redefine how AI-powered, handheld ultrasound can be used in innovative ways to benefit patients at the point-of-care

Butterfly Blueprint to enable MUSC clinicians, students, and researchers to redefine how AI-powered, handheld ultrasound can be used in innovative ways to benefit patients at the point-of-care

May 24, 2022 —Butterfly Network, Inc., a digital health company transforming care with handheld,whole-body ultrasound, andThe Medical University of South Carolina(MUSC) announced that MUSC will leverageButterfly Blueprint,the company’s system-wide ultrasound platform. Together with Butterfly, MUSC aims to transform patient care, health education, and medical research by empowering its clinicians, students, and researchers with point-of-care access to AI-powered, handheld ultrasound.

“At MUSC, we strive to stay on the front-end of innovation to advance how we educate and train healthcare providers and serve the people of South Carolina,” saidPatrick Cawley, M.D., MUSC Health CEO and executive vice president of Health Affairs, University. “With Butterfly’s technology, we’re empowering care teams to know more about what’s going on with a patient sooner by quickly and easily gaining visibility inside the body so they can make more informed care decisions. We’re excited to bring such an evolved point-of-care ultrasound tool to our health system. We believe it will have tremendous impact across all care settings and especially in our rural and underserved settings, where access to specialists and imaging can be very difficult for some patients to manage or afford.”

As the world’s first and only whole-bodyUltrasound-On-Chip technologyButterfly能够将兼容的智能手机或平板电脑变成成像工具,使超声信息能够实际应用到所有医疗从业者的临床工作流程中。Butterfly能够对身体不同部位的图像进行采集和解释,可以用3D可视化技术自动计算膀胱体积,并简化和指导中心线的放置和注射。The device fits in a healthcare professional’s pocket and is powered by a unique combination of cloud-connected software and hardware technology, easily accessed through a mobile app.

MUSC executive vice president for Academic Affairs and provostLisa K. Saladin, PT, PhD, agreed, adding: “It is critical that we provide our students opportunities to train with advanced technologies that they will be using to assess and treat patients both during their clinical rotations as students and after graduation as healthcare providers. We are excited about this collaboration and the opportunities it will provide for our students.”

MUSC will begin its Butterfly rollout initially focusing on practitioners and clinicians atMUSC Health Florence Medical Center,MUSC Health Marion Medical Center, and at the No. 1 hospital in South Carolina as named by U.S. News & World Report, Charleston-based University Medical Center. A major component of the affiliation will be defining new models of care in rural settings with the help of this technology, hence the immediate deployment at two of the hospitals in MUSC’s Regional Health Network: Marion Medical Center and Florence Medical Center. At the same time, MUSC will also work with Butterfly to incorporate point-of-care ultrasound training across the organization, including within its education curriculum for medical students, nurse practitioners, and physicians’ assistants, in addition to exploring areas for clinical research.

“It is an incredible opportunity to partner with MUSC in our shared objective of improving clinical decision-making with an easy-to-use, AI-enabled imaging tool that is accessible at the point-of-care," saidTodd M. Fruchterman, M.D., Ph.D., Butterfly Network’s president and CEO. “Together with MUSC, we’re thrilled to explore how Butterfly can enhance patient care, advance medical education, and model a new standard of care delivery for the next generation of clinicians and care teams. We believe the information that becomes available when Butterfly is deployed at scale has the power to improve diagnostic accuracy and efficiency across care settings and throughout an enterprise.”

For more information:musc.edu


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