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Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Newborn Screening Long Term Follow-Up in the Medical Home
Deborah Badawi1, Katharine Bisordi2, Marilyn J Timmel1
1Maryland Department of Health, Baltimore, MD 21201, USA.
Pediatric primary care data is not sufficient for evaluating long-term outcomes in children with newborn screening (NBS) disorders. Challenges in data sharing and care coordination limit its current use as a sole evaluation source.
Area of Science:
- Pediatric Health
- Public Health
- Health Informatics
Background:
- Newborn screening (NBS) identifies infants with serious genetic, metabolic, and functional disorders.
- Effective long-term outcome evaluation is crucial for children with NBS disorders.
- Current data sources for outcome assessment may be fragmented.
Purpose of the Study:
- To explore the feasibility of using pediatric primary care data for evaluating long-term outcomes of children with NBS disorders.
- To assess compliance with care guidelines and morbidity in this population.
- To examine the accuracy of primary care data compared to other sources.
Main Methods:
- Recruited primary care practices and enrolled patients with sickle cell disease or hearing loss.
- Collected data on medical home quality via practice records and family surveys.
- Assessed clinical outcomes through medical record review and patient surveys.
- Explored electronic data sharing using Clinical Document Architecture (CDA) files.
Main Results:
- Care coordination proved challenging, even in accredited medical homes.
- Providers lacked complete clinical outcome information.
- Children did not consistently receive recommended preventive care.
- Electronic data sharing faced interface challenges.
Conclusions:
- Pediatric primary care providers in the USA are not currently a suitable sole source for evaluating long-term outcomes of children with NBS disorders.
- Improvements in data sharing and care coordination are necessary.
- Further research is needed to optimize outcome evaluation strategies.
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