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AI-powered analytics for Healthcare

OpenText AI-powered analytics for Healthcare

Solutions for Healthcare

Healthcare providers are facing increasing pressure to digitize, driven by factors, such as access to more sophisticated medical and diagnostic tools with digital outputs and regulatory deadlines to adopt electronic health records (EHR). Organizations are also balancing the expanding care needs of an aging population, while simultaneously striving to reduce costs and treat more patients. But, enormous amounts of data, in terms of number of records and large file sizes; diverse data types, both structured and unstructured; fragmented IT ecosystems; and strong regulations to protect patient privacy, such as HIPAA, are creating roadblocks. To succeed in the changing landscape of healthcare, providers must be able to access increasing amounts of information from various sources, organize and visualize this data and apply predictive modeling and planning.

OpenText AI and Analytics

OpenText™ Magellan™ Analytics Suite and OpenText™ Magellan™, the AI-powered analytics platform, allows organizations to quickly and easily connect all of their healthcare data from multiple sources for comprehensive and predictive analysis, while safeguarding the quality, security and availability of information. Health care providers become empowered through machine learning, which consistently improves to facilitate better decision-making and optimal patient care. With OpenText AI and Analytics, organizations in the Healthcare industry can:

  • Integrate data from unstructured sources, including free-form text and images, such as CAT scans with AI-enhanced content capture
  • Connect structured data, such as payment records and test results, for a 360-degree view of patient records
  • Use data-driven insights captured through machine learning to make better point-of-care decisions
  • Streamline operations by eliminating time-consuming, paper-based systems
  • Reduce costs by delivering more accurate diagnoses and cost-effective treatments
  • Uncover risks in patient populations from patterns that were previously unidentifiable
  • Increase transparency in the organization by publishing and sharing performance metrics
  • Support improved decision-making from the back office to in-patient care with accurate data
  • Improve patient engagement through secure, dynamic web and mobile portals
  • Achieve better insight into patient needs for improved satisfaction
  • Maintain regulatory compliance with enhanced data management for streamlined reporting