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Cohort Creation and Visualization Using Graph Model in the PREDIMED Health Data Warehouse.

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Summary

Grenoble Alpes University Hospital is deploying PREDIMED, a secure health data warehouse. Its data model enables medical experts to build and visualize patient cohorts for research and management.

Keywords:
Complex and massive datacohortsdata visualizationhealth data warehousemedical informatics

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Area of Science:

  • Health Informatics
  • Medical Data Management
  • Clinical Research Infrastructure

Background:

  • Grenoble Alpes University Hospital (CHUGA) is implementing PREDIMED, a comprehensive health data warehouse.
  • PREDIMED integrates diverse patient data, including healthcare, administrative, and external sources, under strict security protocols.
  • The platform supports research, education, and institutional management objectives.

Purpose of the Study:

  • To present the data model developed for the PREDIMED health data warehouse at CHUGA.
  • To demonstrate the utility of this data model for medical experts.
  • To showcase interactive patient cohort building and visualization capabilities.

Main Methods:

  • Deployment of a health data warehouse (PREDIMED) at CHUGA.
  • Definition and implementation of a specific data model for patient data integration.
  • Development of interactive tools for cohort construction and data visualization.

Main Results:

  • The PREDIMED data model facilitates the interactive creation of patient cohorts.
  • Medical experts can effectively visualize these patient cohorts using the developed tools.
  • The system supports data integration from various sources within a secure environment.

Conclusions:

  • The PREDIMED data model is a valuable asset for medical experts at CHUGA.
  • Interactive cohort building and visualization enhance research and management capabilities.
  • PREDIMED promotes collaboration with similar health data initiatives globally.