Multi-Site Methods and Coordination

Designing and leading large-scale real-world evidence across distributed data networks.

Our Approach

We design and lead multi-site studies that generate rigorous real-world evidence on the safety, effectiveness, and use of medical products.

Our multi-site work is grounded in a distributed data model, where analytic programs are developed centrally and executed locally within partner dataenvironments.

This approach enables:

  • Standardized analytics across sites while preserving local data control
  • Direct engagement with data partners, including access to clinical expertise and source data context
  • Scalable study execution across care settings

The Distributed Data Advantage

Distributed data networks offer advantages beyond traditional common protocol approaches and centralized data models.

Compared with site-by-site implementation using a common protocol:

  • Improved consistency through centrally developed analytic programs
  • Reduced variability in implementation across sites
  • More efficient quality assurance and reproducibility

Compared with centralized data aggregation:

  • Data remain within source environments, supporting privacy, governance, and stewardship
  • Enhanced flexibility to include partners who cannot share patient-level data externally
  • Ability to validate outcomes and algorithms through site-level access

Together, these features enable large-scale research with scientific rigor and operational efficiency.

Quality Assurance

Data quality is as critical as study design. We work closely with data partners to ensure that underlying data are fit for purpose, through:

  • Data curation and harmonization across sites
  • Systematic data quality assessment and documentation
  • Standardized analytic pipelines with embedded checks
  • Transparent, reproducible workflows

This approach ensures that evidence generated across sites is valid, consistent, and reliable.

Sentinel Initiative Methods

Many of the methods used in our multi-site studies have been developed and refined through our leadership of the Sentinel Initiative, a national distributed data network established by the U.S. Food and Drug Administration to monitor the safety of medical products.

The Sentinel System has helped advance methods for distributed data analysis, active safety surveillance, and large-scale observational studies using healthcare data. These methodological foundations inform the design and execution of many of the multi-site studies conducted by our team.

About Sentinel methods and infrastructure

Explore Publications

Explore our full publication library to learn more about the studies and methods that inform our work.