Glassbeam Launches Ground Breaking Functionalities in Clinsights Service Analytics Application for the Healthcare Provider Market
SANTA CLARA, Calif., Nov. 26, 2019 — Glassbeam today announced new functionalities in its AI-powered Clinsights™ Service Analytics offerings that are targeted at healthcare providers to help improve patient care by minimizing machine downtime and operational costs. In production sites across 100+ facilities across United States, Clinsights Service Analytics now allows clinical engineering staff to remotely access and diagnose machine health issues instead of spending precious hours going to the hospital sites and performing reactive maintenance. In addition, coverage of modality expands to provide proactive and predictive alerts for Cath Lab equipment.
The current paradigm of reactive maintenance is not scalable in dynamically changing healthcare provider environments. From the time an issue is reported on an imaging machine’s quality and its performance to the time the problem is diagnosed and fixed, there is a tremendous waste of human capital. The remote access and management feature from Glassbeam is targeted to resolve this impending and persistent challenge. What used to take hours to fix can now be done proactively in a few minutes. These new features not only save operational costs but also propels forward patient care and safety to the next level by minimizing disruption and the unplanned downtime of expensive assets such as MRI, CT Scanners and Cath Lab equipment.
“Glassbeam has once again delivered on its promise to be the healthcare industry’s leading analytics platform,” said Chad Brown, President, and CEO of Brown’s Medical Imaging (BMI). “I am certain that the new functionalities of remote access and management will further strengthen our partnership offerings with Glassbeam, providing healthcare customers with unsurpassed benefits to increase machine uptime and improved patient care.”
Glassbeam Clinsights delivers remote access capabilities for imaging equipment scanners for both remote service access allowing engineers to view logs, run backups, and execute commands as well as remote screen access aka Screen Sharing. These functionalities are delivered by leveraging existing features available on the scanner (without the need to install additional software) and by applying the state-of-the-art networking that is firewall-friendly and secure. With encrypted web sockets, timed single-use sessions, secure tunneling, and audit trails, coupled with support for Single Sign On (SSO), Role-Based Access (RBAC) and mobile phone-based 2-factor authentication (2FA), Glassbeam ensures that only authorized personnel will ever have the restricted access to these features.
“Changing the rules of the game has been Glassbeam’s forte since the launch of the Clinsights app as healthcare industry’s first AI/ML powered application.” said Puneet Pandit, Co-founder & CEO of Glassbeam. “With remote access and management, we have now taken a step further to provide field engineers the capability to do their homework, like a pre-flight checklist, and as a result dramatically increase the efficacy of support programs and improve patient care.”
Additional Resources;
The new features of Glassbeam Clinsights are commercially available immediately. Go to https://www.glassbeam.com/clinsights/for a more detailed description. We are conducting live demos of these features at the RSNA 2019, Chicago, IL, Booth #5160, Dec 1-5.
About Glassbeam
Glassbeam is the premier machine data analytics company bringing structure and meaning to complex data generated from any connected machine in the Industrial IoT with a strong focus on medical and data center equipment. Funded by several ultra-high net worth investors, Glassbeam’s next generation cloud-based platform is designed to transform, analyze, and build Artificial Intelligence applications from multi-structured logs, delivering powerful solutions on customer support, machine intelligence & utilization for companies such as IBM, UCSF Medical, Novant Health, Scripps Health, and Dimension Data.
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