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Defining the Minimal Long-Term Follow-Up Data Elements for Newborn Screening.

Yvonne Kellar-GuentherLauren BarringerKatherine RaboinGinger NicholsKathy Y F ChouKathy NguyenAmy R BurkeSandy FawbushJoyal B MeyerMorna J DorseyAmy M BrowerKee ChanMei LietschJennifer L TaylorMichele CagganaMarci K Sontag
Published in: International journal of neonatal screening (2024)
Newborn screening (NBS) is hailed as a public health success, but little is known about the long-term outcomes following a positive newborn screen. There has been difficulty gathering long-term follow-up (LTFU) data consistently, reliably, and with minimal effort. Six programs developed and tested a core set of minimal LTFU data elements. After an iterative data collection process and the development of a data collection tool, the group agreed on the minimal LTFU data elements. The denominator captured all infants with an NBS diagnosis, accounting for children who moved or died prior to the follow-up year. They also agreed on three LTFU outcomes: if the child was still alive, had contact with a specialist, and received appropriate care specific to their diagnosis within the year. The six programs representing NBS public health programs, clinical providers, and research programs provided data across multiple NBS disorders. In 2022, 83.8% (563/672) of the children identified by the LTFU programs were alive and living in the jurisdiction; of those, 92.0% (518/563) saw a specialist, and 87.7% (494/563) received appropriate care. The core LTFU data elements can be applied as a foundation to address the impact of early diagnosis by NBS within and across jurisdictions.
Keyphrases
  • public health
  • electronic health record
  • big data
  • healthcare
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  • deep learning