Common data model for sickle cell disease surveillance: considerations and implications
Matthew P. Smeltzer, Sarah L. Reeves, William O. Cooper, Brandon K. Attell, John J. Strouse, Clifford M. Takemoto, Julie Kanter, Krista Latta, Allison Plaxco, Robert L. Davis, Daniel Hatch, Camila Reyes, Kevin J. Dombkowski, Angela Snyder, Susan Paulukonis, Ashima Singh, Mariam Kayle
Abstract
Objective: Population-level data on sickle cell disease (SCD) are sparse in the United States. The Centers for Disease Control and Prevention (CDC) is addressing the need for SCD surveillance through state-level Sickle Cell Data Collection Programs (SCDC). The SCDC developed a pilot common informatics infrastructure to standardize processes across states. Materials and Methods: We describe the process for establishing and maintaining the proposed common informatics infrastructure for a rare disease, starting with a common data model and identify key data elements for public health SCD reporting. Results: The proposed model is constructed to allow pooling of table shells across states for comparison. Core Surveillance Data reports are compiled based on aggregate data provided by states to CDC annually. Discussion and Conclusion: We successfully implemented a pilot SCDC common informatics infrastructure to strengthen our distributed data network and provide a blueprint for similar initiatives in other rare diseases.