A distributed research network model for post-marketing safety studies: the Meningococcal Vaccine Study.

PURPOSE: We describe a multi-center post-marketing safety study that uses distributed data methods to minimize the need for covered entities to share protected health information (PHI). Implementation has addressed several issues relevant to creation of a large scale post-marketing drug safety surveillance system envisioned by the FDA's Sentinel Initiative. METHODS: This retrospective cohort study of Guillain-Barré syndrome (GBS) following meningococcal conjugate vaccination incorporates the data and analytic expertise of five research organizations closely affiliated with US health insurers. The study uses administrative claims data, plus review of full text medical records to adjudicate the status of individuals with a diagnosis code for GBS (ICD9 357.0). A distributed network approach is used to create the analysis files and to perform most aspects of the analysis, allowing nearly all of the data to remain behind institutional firewalls. Pooled analysis files transferred to a central site will contain one record per person for approximately 0.2% of the study population, and contain PHI limited to the month and year of GBS onset for cases or the index date for matched controls. RESULTS: The first planned data extraction identified over 9 million eligible adolescents in the target age range of 11-21 years. They contributed an average of 14 months of eligible time on study over 27 months of calendar time. MCV4 vaccination coverage levels exceeded 20% among 17-18-year olds and 16% among 11-13 and 14-16-year-old age groups by the second quarter of 2007. CONCLUSION: This study demonstrates the feasibility of using a distributed data network approach to perform large scale post-marketing safety analyses and is scalable to include additional organizations and data sources. We believe these results can inform the development of a large national surveillance system.

Duke Scholars

Author Judith Mae Kramer Medicine, General Internal Medicine