Common data model for sickle cell disease surveillance: considerations and implications

Area of Science:

• Public Health Surveillance
• Health Informatics
• Rare Disease Research

Background:

• Population-level data on sickle cell disease (SCD) in the U.S. is limited.
• The Centers for Disease Control and Prevention (CDC) initiated state-level Sickle Cell Data Collection Programs (SCDC) to address this gap.
• Standardization of data collection processes across states is crucial for effective SCD surveillance.

Purpose of the Study:

• To describe the establishment and maintenance of a common informatics infrastructure for SCD surveillance.
• To identify key data elements essential for public health reporting of SCD.
• To develop a standardized approach for rare disease data collection.

Main Methods:

• Development of a pilot common informatics infrastructure for the SCDC programs.
• Implementation of a common data model to standardize data across participating states.
• Identification of key data elements for public health reporting.

Main Results:

• A pilot common informatics infrastructure was successfully implemented.
• The infrastructure allows for pooling of data across states for comparative analysis.
• Annual Core Surveillance Data reports are compiled using aggregate data submitted by states to the CDC.

Conclusions:

• The pilot SCDC common informatics infrastructure strengthens the distributed data network.
• This initiative provides a blueprint for similar data collection and surveillance efforts in other rare diseases.
• Standardized informatics infrastructure is key to enhancing rare disease surveillance and research.