Mapping a National Clinical Research Network’s Infrastructure

A research team applied system mapping methods to visualize the architecture of a national clinical research network focused on patient-centered comparative effectiveness research. The project aimed to identify key actors, relationships, and data exchanges that underpin multisite and multinetwork studies. Maps and methods were developed to show commonalities and differences across clinical research network infrastructures, especially in data management and sharing. The work offers a new tool to make the network more accessible to investigators, patient partners, and funders and to improve transparency and dialogue about infrastructure strengths and limits.

What the study examined

This work examined how system mapping methods can be used to characterize the architecture of a national clinical research network for data activities. The focus was on identifying the main actors, the relationships between them, and the kinds of exchanges that enable multisite and multinetwork research. The effort centered on making the infrastructure visible and better understood for patient-centered comparative clinical effectiveness research.

Key findings

The project produced maps and a methodological approach that reveal how the network supports distributed queries and other data activities. These visualizations highlight both shared features and heterogeneity across constituent clinical research networks, particularly around data management and data sharing practices. By translating complex structures into clear diagrams, the maps help clarify how actors interact and where variations in infrastructure exist.

Why it matters

The mapping approach provides a practical tool to increase accessibility and transparency of a national research infrastructure. It can support clearer conversations among investigators, patient partners, research funders, and other collaborators by showing where strengths and potential limitations lie in the system that generates evidence. More broadly, the methodology offers a path for networks to enhance collaboration and to function more effectively as a learning health system by fostering dialogue about design and architecture.