Submission Type



collaboration, collaborative, comparative effectiveness research (CER), distributed data networks, FDA Sentinel, health plans, learning health care system, Mini-Sentinel, PCORnet, safety surveillance, Vaccine Safety Datalink (VSD)


Introduction: Large-scale distributed data networks consisting of diverse stakeholders including providers, patients, and payers are changing health research in terms of methods, speed and efficiency. The Vaccine Safety Datalink (VSD) set the stage for expanded involvement of health plans in collaborative research.

Expanding Surveillance Capacity and Progress Toward a Learning Health System: From an initial collaboration of four integrated health systems with fewer than 10 million covered lives to 16 diverse health plans with nearly 100 million lives now in the FDA Sentinel, the expanded engagement of health plan researchers has been essential to increase the value and impact of these efforts. The collaborative structure of the VSD established a pathway toward research efforts that successfully engage all stakeholders in a cohesive rather than competitive manner. The scientific expertise and methodology developed through the VSD such as rapid cycle analysis (RCA) to conduct near real-time safety surveillance allowed for the development of the expanded surveillance systems that now exist.

Building on Success and Lessons Learned: These networks have learned from and built on the knowledge base and infrastructure created by the VSD investigators. This shared technical knowledge and experience expedited the development of systems like the FDA’s Mini-Sentinel and the Patient Centered Outcomes Research Institute (PCORI)’s PCORnet

Conclusion: This narrative reviews the evolution of the VSD, its contribution to other collaborative research networks, longer-term sustainability of this type of distributed research, and how knowledge gained from the earlier efforts can contribute to a continually learning health system.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.