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Related Experiment Video

Updated: Jan 13, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Visualizing the Complexity of the PCORnet® Infrastructure and Implications for Designing PCORnet® Studies.

Nikolas Koscielniak1, Stacey Chang2, Natalie Privett2

  • 1Patient-Centered Outcomes Research Institute, Washington, District of Columbia.

Medical Care
|January 8, 2026
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Summary

Visualizing clinical research networks like PCORnet® using system mapping improves data sharing and collaboration. This approach enhances transparency and accessibility for researchers and patient partners in national health research.

Keywords:
infrastructurelearning health systemssystems designsystems mapping

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Area of Science:

  • Health Services Research
  • Health Informatics
  • Clinical Research Infrastructure

Background:

  • National clinical research networks require adaptable architectures for multisite and multinetwork research.
  • Visualizing the infrastructure of clinical research networks is crucial for enhancing their utility in national-scale research.

Purpose of the Study:

  • To present a system mapping methodology for characterizing actors, relationships, and data exchanges within the PCORnet infrastructure.
  • To describe findings from mapping the PCORnet infrastructure and analyze commonalities and heterogeneity in data management and sharing across clinical research networks (CRNs).

Main Methods:

  • System mapping methods were employed to visualize the complex infrastructure of health research networks.
  • This methodology was applied to PCORnet to support national-scale patient-centered comparative clinical effectiveness research (CER).

Main Results:

  • The mapping methods and resulting visualizations offer a novel tool for understanding PCORnet's design and architecture.
  • These visualizations aim to improve accessibility for investigators, patient partners, funders, and collaborators, facilitating distributed queries.

Conclusions:

  • System mapping provides a new approach to support collaboration within networks, fostering a learning health system (LHS).
  • Improved transparency and dialogue with patient partners regarding infrastructure capabilities and limitations are key outcomes.
  • This methodology aids in evidence generation and informs healthcare decisions.