Enterprise imaging and informatics firm Fujifilm has announced a new partnership with Tiger Health Technology, a leading provider of hybrid cloud solutions, to optimise data lifecycle management and address key storage-related challenges in digital pathology.
This technology integration will streamline the management and accessibility of digital pathology data managed through Synapse Pathology, Fujifilm’s picture archiving and communication system (PACS) for pathology, ensuring that healthcare providers can more efficiently handle the large volumes of information involved in pathology workflows. Further bolstering Fujifilm’s Synapse Enterprise Imaging strategy and capabilities, this partnership will enable the full integration of all digital pathology content into a healthcare organisation’s vendor-neutral archive (VNA), addressing any potential challenges with proprietary file format integrations.
“Our partnership with Tiger Health Technology will empower our customers to manage large whole-slide images in the most effective ways. This will have a significant and positive impact on the cost of digital pathology file storage without degrading or delaying the clinical utility of these images,” said Dr Mark Lloyd, Vice President, Pathology, FUJIFILM Healthcare Americas Corporation. “Together, we are committed to providing rapid access to pathology information so patients can receive the most rapid and accurate diagnosis possible.”
“Digital health platforms offer promising solutions to key challenges in healthcare systems worldwide, particularly regarding costs, productivity, and accessibility,” said Nikola Apostolov, CEO of Tiger Health Technology. “We share Fujifilm’s vision, and our partnership is a natural fit. Collaboration is the key to building sustainable healthcare platforms.”
Fujifilm and Tiger Health Technology will also collaborate to develop new solutions aimed at facilitating the wider adoption of digital pathology across healthcare systems. These solutions are intended to help resolve challenges related to the efficient storage and retrieval of medical data, while also improving overall data availability for more accurate, efficient, and scalable options for diagnosis and treatment planning.