Prestige Medical Imaging (PMI), one of the top suppliers of medical imaging equipment and services in the United States has formed a partnership with global manufacturer of medical diagnostic systems Esaote and data analytics firm Glassbeam.
Prestige Medical Partners With Esaote and Glassbeam
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Secondary#digitalimaging#esaote#glassbeam#prestivemedicalimaging
By partnering with Esaote and Glassbeam, Newburgh, New York-based Prestige Medical Imaging expects to expand its range of analytics software, ultrasound, and MRI systems to customers all through the eastern half of the United States. Current customers include such professional sports teams as the New York Mets, Miami Heat, Cleveland Indians and the New York Islanders in addition to major orthopedic clinics and hospitals.
Bill Haussmann, CEO of Prestige Medical Imaging, explained how PMI chose its new partners. “Our customers have asked for Ultrasound, MRI and Analytic solutions, and we selected Esaote and Glassbeam after an extensive market analysis and product review process. These solutions were in high demand by our customers and we were actively working to add them to our product portfolio.”
Esaote is a Genoa, Italy-based global manufacturer of medical diagnostic systems. It is recognized as a world leader in extremity MRI. Esaote offers a variety of solutions, including its recently launched MyLab9 eXP ultrasound system, equipped with a new Ultra-engine platform designed to offer ultra-clarity, performance, workflow for radiology, cardiology, and women’s health. Haussmann said, “Esaote has shown itself as a real trailblazer with its Ultrasound and MRI systems. Partnering with them to expand our portfolio is a significant step for PMI, which results in even better products for our customers.”
Based in Santa Clara, California, Glassbeam is a machine data analytics company. It analyzes data generated from any connected industrial IoT [internet of things] machine and focuses its efforts on medical and data center equipment. Glassbeam’s cloud-based platform is designed to transform, analyze, and build AI [artificial intelligence] applications from multi-structured data logs. Haussmann said, “With the Glassbeam partnership, we’re able to expand our software offerings to our clients, Glassbeam machine data analytics solution is a game changer for the healthcare market. This software provides enhanced analytics to view device uptime and utilization reports and improving the patient experience through increased uptime.”
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This is a fascinating development. In my practice we've seen similar outcomes with the revised protocol. The key differentiator seems to be patient selection criteria. Has anyone else noticed the correlation with BMI thresholds?
Great point. I'd push back slightly on the conclusion, the sample size in the cited study is too small to draw population-level inferences. That said, the directional signal is compelling and worth a larger RCT.
We implemented a similar approach last year. Early results are promising but we're still gathering 12-month follow-up data. Happy to share our protocol if anyone is interested.
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