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Unlocking Practice Patterns at Scale: A Framework for Developing Clinical Insights Using Epic's Cosmos.

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We developed an adaptable workflow for retrospective clinical research using Epic's Cosmos platform. This approach enables rapid, reproducible cohort construction and analysis for improved patient care evidence.

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Area of Science:

  • Clinical Informatics
  • Health Data Science
  • Retrospective Research

Background:

  • Real-world data from vendor-aggregated health information exchanges are valuable for retrospective clinical research.
  • Epic's Cosmos platform provides access to deidentified electronic health record (EHR) data for large-scale studies.

Purpose of the Study:

  • To describe the iterative development of a generalizable clinical informatics workflow for retrospective studies utilizing the Cosmos platform.
  • To refine a collaborative research process for secondary data analysis.

Main Methods:

  • The Plan-Do-Study-Act (PDSA) cycle was applied to iteratively refine the research process.
  • Focus areas included study setting, team composition, technical preparation, and workflow optimization.
  • The SlicerDicer interface within Cosmos was used for cohort exploration and construction.

Main Results:

  • Multiple areas for improvement were identified to streamline collaborative studies.
  • Key insights were gained for defining research teams across clinical and informatics domains.
  • Optimized processes for query building, cohort construction, data analysis, validation, and communication were established.

Conclusions:

  • The developed collaborative approach supports the creation of clinical evidence for high-quality patient care.
  • The workflow facilitates rapid, reproducible cohort construction and analysis.
  • This adaptable model can be applied across clinical domains and scaled for multi-organizational collaboration.