Launching Insights: A Pilot Study on Leveraging Real-World Observational Data from the Mayo Clinic Platform to Advance Clinical Research
Journal:
arXiv
Published Date:
Mar 21, 2025
Abstract
Backgrounds: Artificial intelligence (AI) is transforming healthcare, yet
translating AI models from theoretical frameworks to real-world clinical
applications remains challenging. The Mayo Clinic Platform (MCP) was
established to address these challenges by providing a scalable ecosystem that
integrates real-world multiple modalities data from multiple institutions,
advanced analytical tools, and secure computing environments to support
clinical research and AI development. Methods: In this study, we conducted four
research projects leveraging MCP's data infrastructure and analytical
capabilities to demonstrate its potential in facilitating real-world evidence
generation and AI-driven clinical insights. Utilizing MCP's tools and
environment, we facilitated efficient cohort identification, data extraction,
and subsequent statistical or AI-powered analyses. Results: The results
underscore MCP's role in accelerating translational research by offering
de-identified, standardized real-world data and facilitating AI model
validation across diverse healthcare settings. Compared to Mayo's internal
Electronic Health Record (EHR) data, MCP provides broader accessibility,
enhanced data standardization, and multi-institutional integration, making it a
valuable resource for both internal and external researchers. Conclusion:
Looking ahead, MCP is well-positioned to transform clinical research through
its scalable ecosystem, effectively bridging the divide between AI innovation
and clinical deployment. Future investigations will build upon this foundation,
further exploring MCP's capacity to advance precision medicine and enhance
patient outcomes.
