Related Experiment Video
Updated: Apr 25, 2026
Mapping Infant Immunity with Minimal Input: Integrative Single-cell and Multiomic Profiling
Published on: April 3, 2026
A Systematic Process to Accurately Link Large-Scale Research Consents to State Public Health Newborn Screening
Emily Cheves1, Hannah E Frawley1, Angela You Gwaltney1
1RTI International, Genomics and Translational Research Center, Research Triangle Park, 3040 East Cornwallis Road, Durham, NC 27713, USA.
Insights
Genomic newborn screening (gNBS) research requires linking consent forms to blood samples. A combined fuzzy matching and decision tree approach accurately linked 98.6% of samples, ensuring data integrity in public health research.
Area of Science:
- Genomics
- Public Health
- Bioinformatics
Background:
- Genomic newborn screening (gNBS) research necessitates robust methods for linking parental consent to newborn screening (NBS) specimens.
- Protecting sensitive participant data is paramount while facilitating research innovation.
- The Early Check program in North Carolina utilizes residual dried bloodspot (DBS) samples for gNBS research.
Purpose of the Study:
- To develop and evaluate a systematic approach for accurately matching parental consents with NBS DBS samples in a gNBS research program.
- To ensure the integrity of data linkage for newborns participating in the Early Check study.
- To assess the feasibility of using probabilistic matching and decision trees for sample identification.
Main Methods:
- Implemented a systematic approach combining a fuzzy matching algorithm with a decision tree for manual review of potential matches.
- Utilized residual dried bloodspot (DBS) samples from the North Carolina State Laboratory of Public Health (NCSLPH).
- Analyzed discrepancies between consent forms and NBS DBS samples, including name, infant sex, and contact details.
Main Results:
- Over a defined period, 4279 newborns' consents were received, with 614 (14%) requiring further review due to discrepancies.
- Manual review and outreach were necessary for 349 (57%) of these discrepancies.
- The combined method successfully identified samples from consented participants with high accuracy.
Conclusions:
- A systematic approach using probabilistic matching, a decision tree, and structured staff review is a feasible and accurate method for linking research consents to NBS DBS samples.
- This methodology supports the ethical and efficient conduct of genomic newborn screening research.
- The Early Check program demonstrates a successful model for data linkage in public health research initiatives.
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.
