TORONTO, March 5, 2018 /PRNewswire/ -- AICloudQA™ is a new secure, expandable healthcare quality-assurance system that combines Google Cloud Platform (GCP) infrastructure, Client Outlook's eUnity™ viewer and Real Time Medical's (RTM) Intelligent Peer Review solution. The system combines AI-assisted peer learning and AI-assisted workload balancing to increase clinical efficacy and improve acute care performance. AICloudQA™ is currently available for Radiology and Pathology.
In order to deliver on the promise of AI-assisted peer learning, Real Time Medical (RTM) is creating large-scale, anonymized, peer learning networks. RTM is making access to such networks simple with its Google Cloud Platform offering that combines the best of RTM's advanced peer learning solution with the latest from Client Outlook's eUnity™ viewer. Now healthcare organizations and practices of any size can access the best in peer learning through a cost efficient, easy to use platform.
Ian Maynard, Real Time Medical CEO, explains: "We understand that clients are seeking to implement solutions capable of both prospective and retrospective peer review while also providing the advanced learning opportunities for physicians and quality improvement for patients that artificial intelligence enables. With Google Cloud Platform regions located in the USA, Canada, Brazil, UK, Germany, Finland, Netherlands, India, Singapore and Australia, the solution will enable large-scale peer learning networks while providing flexibility to deploy resources in specific locations or address multi-regional and global needs."
Dr. Manohar Shroff, Professor of Radiology Radiologist-in-Chief, Ontarian Chair of Pediatric Radiology Hospital for Sick Children and University of Toronto, is a current client of Real Time Medical. He adds: "The Real Time Medical system already makes it possible to combine several functions that allows us to derive the greatest value from our investment in peer learning and quality improvement and the system is applicable across medical disciplines. We can't wait to see what they do next."
Real Time Medical's award-winning AICloudQA™ platform will help clients lead peer learning and review initiatives to improve physician skills and patient outcomes through:
- AI-Assisted Peer Learning: to improve peer learning potential by enabling a much broader and rapid scope and scale of review, analysis and user-specific recommendations.
- AI-Assisted Workload Balancing: leverages RTM's patented and context-aware workload balancing algorithms developed over the past ten years. AI assisted workload balancing will profoundly increase the 15-35% diagnostic productivity improvement already possible with the Real Time Medical solution.
- Increase in Clinical Efficacy: AICloudQA™ will improve both the clinical efficacy of peer learning for the benefit of patients and physicians, while also improving the efficiency of the peer learning process.
Real Time Medical will be presenting AICloudQA™ at HIMSS18. US, Canadian and EU clients have already booked meetings to view the solution.
About Real Time Medical
Real Time Medical is a diagnostic imaging workflow innovation company. It develops vendor-neutral, context-aware workflow management software solutions. These solutions organize the reporting services in diagnostic organizations more efficiently and productively. Real Time Medical's platform, DiaShare™, significantly improves the efficiency, quality and accuracy of service delivery to patients.
Real Time Medical also operates the only nationwide, round-the-clock radiology service in Canada, using the DiaShare™ workload balancing platform.
For more information, visit www.realtimemedical.com