A Systematic Process to Accurately Link Large-Scale Research Consents to State Public Health Newborn Screening Samples

将大规模研究知情同意书与州公共卫生新生儿筛查样本准确关联的系统流程

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Abstract

Research programs can interface with public health programs to generate innovation, yet it is critical to ensure processes that support research activities without infringing on protected data. Genomic newborn screening (gNBS) research programs require reliable methods to link parental consents to the correct newborn screening (NBS) specimen. Early Check is a gNBS research program in North Carolina that uses the residual dried bloodspot (DBS) samples stored at the North Carolina State Laboratory of Public Health (NCSLPH) to screen babies for serious health conditions. Early Check created a systematic approach to match research consents with NBS DBS samples utilizing a fuzzy matching algorithm and manual review of prospective matches utilizing a decision tree. Between 28 September 2023, and 10 June 2025, Early Check received parental consents for 4279 newborns. Of those, 614 (14%) had discrepancies that required further review. More than half of these (349, 57%) required outreach to the consenting parent to resolve differences in information such as name, infant sex, or contact details. The use of probabilistic matching, a decision tree, and structured staff review provides a feasible approach for accurately identifying samples from consented NBS participants.

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