PatientGraph provides a proven, plug-and-play Healthcare Knowledge Graph solution designed for Providers, Payers, Pharmaceutical, BioTech, and Medical Device manufacturers. It serves as a digital twin of a healthcare organization, enabling rapid demonstration to stakeholders of the power of connecting disparate healthcare data silos. This connectivity leads to better patient outcomes and significant downstream cost savings. A key advantage is its use of AI-generated, completely synthetic patient data, which eliminates HIPAA or PHI concerns, allowing for safe experimentation and development. When ready, real patient data can be easily swapped into the proven model. The solution is data-centric, offering a unified data infrastructure for all data analytics, which is significantly more cost-effective than building separate data marts for each new type of analysis. It features a Security First Architecture with cell-level security and a fully compliant HIPAA/PHI security model. PatientGraph is data science-ready and extensible, including Jupyter notebooks for custom development. It also incorporates built-in AI discovery and an LLM Prompt Engine for crafting additional realistic Patient Health Records for data mining simulations. The base includes 10,000 patients and 100,000 clinical notes, expandable to 10 million patients or more for scalability testing. The system is extendable with over 200 public healthcare and life science data sources and is based on industry standards for medical and life science terminologies. PatientGraph can be deployed as a fully hosted solution or installed on-premise, and its model is directly portable to real hospital data once proven and tested.

Features & Benefits

• Synthetic Data for Compliance
  • Utilizes AI-generated, realistic, and completely synthetic patient data, eliminating HIPAA and PHI concerns for safe development and demonstration.
• Benefits for Healthcare Decision Makers
  • Enables improved financial insight and management, enhanced operational efficiency, better patient outcomes, and more informed decision-making.
• Benefits for Hospital CIOs & IT Groups
  • Offers a data-centric solution with a single data infrastructure for all analytics, significantly reducing costs compared to building multiple data marts.
  • Features a Security First Architecture with cell-level security.
• Benefits for Clinical Staff, Research, & Data Science
  • Provides a Knowledge Graph data shape that is easier to understand and query, an event-based model for improved predictions, and a library of pre-built analytics.
• Benefits for Pharma R&D
  • Supports FAIR (Findable, Accessible, Interoperable, Reusable) design and implementation, with built-in AI discovery.
• Extensibility & Data Integration
  • Data science-ready and extensible with included Jupyter notebooks, allowing users to extend or build their own analytics.
  • Extendable with over 200 public healthcare and life science data sources.
  • Based on industry standards for medical and life science terminologies.
• AI-Powered Data Generation
  • Includes an LLM Prompt Engine for crafting additional realistic Patient Health Records for data mining simulations.
  • Base of 10,000 patients and 100K clinical notes, expandable to 10 million patients or more.
• Flexible Deployment & Portability
  • Available as a fully hosted solution or for on-premise installation, with the model directly portable to real hospital data once proven and tested.