PCORnet®: An Infrastructure Supporting Innovation in Clinical Study Design

Overview

PCORnet is a national research infrastructure funded by the Patient-Centered Outcomes Research Institute to enhance capacity for efficient, patient-centered health research. The network operates through a robust and adaptable framework that accommodates diverse study designs. A subset of research conducted through this infrastructure qualifies as PCORnet Studies, designated through specific approval criteria and distinguished by rigorous adherence to standards that enhance research quality and impact. Over a decade of operation, more than 300 studies have utilized the PCORnet infrastructure, with 58 achieving the designation of meritorious PCORnet Study and 19 of these reaching completion. This body of work provides evidence of the infrastructure's capacity to support varied research approaches while maintaining patient-centered principles.

Methods and approach

The PCORnet infrastructure provides a structured framework designed to accommodate multiple study archetypes and therapeutic areas. The network establishes specific criteria for studies seeking designation as official PCORnet Studies, creating a tiered system that distinguishes research meeting elevated quality standards. The infrastructure integrates data from participating institutions across the network, enabling both observational and interventional research designs. The framework incorporates mechanisms for continuous learning, drawing on accumulated experience from completed studies to refine operational processes and expand capabilities. Analysis of the completed studies encompasses examination of study design archetypes, clinical therapeutic areas addressed, funding sources supporting the research, and the breadth of institutional participation across the network.

Results

Over the 10-year operational period, the PCORnet infrastructure supported completion of more than 300 studies across diverse therapeutic areas and research designs. Of these, 58 studies met criteria for designation as PCORnet Studies, with 19 reaching completion at the time of reporting. The completed research demonstrates the infrastructure's capacity to accommodate multiple study archetypes and spans varied clinical therapeutic areas. The network engaged a broad range of institutional users and secured funding from multiple sources. Experience accumulated through these studies yielded operational insights regarding infrastructure optimization, study implementation challenges, and opportunities for methodological innovation. The infrastructure demonstrated adaptability in supporting both traditional and novel study designs while maintaining patient-centered research principles throughout implementation.

Implications

The PCORnet infrastructure establishes a scalable model for conducting patient-centered research across diverse clinical contexts and study designs. The distinction between general infrastructure use and designated PCORnet Studies creates quality benchmarks that may influence standards for network-based research. Lessons derived from 10 years of operational experience inform development of a continuously learning framework, positioning the infrastructure to adapt to evolving research needs and methodological innovations. The infrastructure's demonstrated capacity to support varied study archetypes while maintaining patient-centered principles suggests potential for broader application in clinical research settings. Accumulated operational knowledge and established institutional partnerships provide foundation for expansion of research capabilities and support for increasingly complex trial designs. The network's evolution reflects iterative refinement based on empirical experience, offering a template for infrastructure development in collaborative research environments.

Disclosure

• Research title: PCORnet®: An Infrastructure Supporting Innovation in Clinical Study Design
• Authors: Adrian F. Hernandez, Elizabeth Shenkman, Kathleen McTigue, Lisa Kepler, Lisa P. Gwyther, Stephen Kimmel, Russell L. Rothman, Jason P. Block, Casey L. Daniel, Jonathan N. Tobin, Elisa L. Priest, Crystal Evans
• Publication date: 2026-01-08
• DOI: https://doi.org/10.1097/mlr.0000000000002245
• OpenAlex record: View
• Disclosure: This post was generated by artificial intelligence. The original authors did not write or review this post.