Towards a Newborn Screening Common Data Model: The Utah Newborn Screening Data Model

Area of Science:

• Public Health
• Health Informatics
• Biomedical Data Standards

Background:

• Newborn screening programs are shifting from paper-based to electronic data exchange.
• Significant challenges exist in achieving seamless electronic data exchange.
• Standardization is crucial for effective data sharing and analysis.

Purpose of the Study:

• To outline a data model for standardizing newborn screening data.
• To map newborn screening data elements to established healthcare standards.
• To facilitate electronic data exchange and improve data interoperability.

Main Methods:

• Developed a data model for newborn screening.
• Mapped data elements (demographics, facilities, labs, results, follow-up) to LOINC, SNOMED CT, ICD-10-CM, and HL7 standards.
• Framework designed for automated electronic data exchange.

Main Results:

• A comprehensive data model is proposed.
• Established mapping to key healthcare standards (LOINC, SNOMED CT, ICD-10-CM, HL7).
• Framework supports standardized electronic data exchange.

Conclusions:

• The proposed data model provides a foundation for standardized electronic data exchange in newborn screening.
• Implementation can accelerate data exchange between providers and programs.
• Improved interoperability will enhance newborn health outcomes and program standardization.