Advancing Newborn Screening Long-Term Follow-Up: Integration of Epic-Based Registries, Dashboards, and Efficient Workflows

Author:

Raboin Katherine1ORCID,Ellis Debra1,Nichols Ginger1,Hughes Marcia2ORCID,Brimacombe Michael34ORCID,Rubin Karen1

Affiliation:

1. Connecticut Newborn Screening Network, Connecticut Children’s, Hartford, CT 06106, USA

2. Center for Social Research, University of Hartford, Hartford, CT 06105, USA

3. Research Operations and Development, Connecticut Children’s, Hartford, CT 06106, USA

4. Department of Pediatrics, University of Connecticut School of Medicine, Hartford, CT 06106, USA

Abstract

The Connecticut Newborn Screening (NBS) Network, in partnership with the Connecticut Department of Public Health, strategically utilized the Epic electronic health record (EHR) system to establish registries for tracking long-term follow-up (LTFU) of NBS patients. After launching the LTFU registry in 2019, the Network obtained funding from the Health Resources and Services Administration to address the slow adoption by specialty care teams. An LTFU model was implemented in the three highest-volume specialty care teams at Connecticut Children’s, involving an early childhood cohort diagnosed with an NBS-identified disorder since the formation of the Network in March 2019. This cohort grew from 87 to 115 over the two-year project. Methods included optimizing registries, capturing external data from Health Information Exchanges, incorporating evidence-based guidelines, and conducting qualitative and quantitative evaluations. The early childhood cohort demonstrated significant and sustainable improvements in the percentage of visits up-to-date (%UTD) compared to the non-intervention legacy cohort of patients diagnosed with an NBS disorder before the formation of the Network. Positive trends in the early childhood cohort, including %UTD for visits and condition-specific performance metrics, were observed. The qualitative evaluation highlighted the achievability of practice behavior changes for specialty care teams through responsive support from the nurse analyst. The Network’s model serves as a use case for applying and achieving the adoption of population health tools within an EHR system to track care delivery and quickly fill identified care gaps, with the aim of improving long-term health for NBS patients.

Funder

Health Resources and Services Administration

Publisher

MDPI AG

Reference13 articles.

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5. Long-term follow-up after diagnosis resulting from newborn screening: Statement of the US Secretary of Health and Human Services’ Advisory Committee on Heritable Disorders and Genetic Diseases in Newborns and Children;Kemper;Genet. Med.,2008

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