{"id":16511,"date":"2020-10-15T10:26:55","date_gmt":"2020-10-15T14:26:55","guid":{"rendered":"https:\/\/healthit-gov.go-vip.net\/buzz-blog\/?p=16511"},"modified":"2025-09-12T04:08:17","modified_gmt":"2025-09-12T04:08:17","slug":"a-strong-start-enhancing-newborn-screening-for-precision-public-health","status":"publish","type":"post","link":"https:\/\/healthit.gov\/blog\/insights-updates\/a-strong-start-enhancing-newborn-screening-for-precision-public-health\/","title":{"rendered":"A Strong Start: Enhancing Newborn Screening for Precision Public Health"},"content":{"rendered":"\n
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As the capability to sequence an individual\u2019s genome or exome<\/a> continues to expand\u2014and the cost continues to fall\u2014more states are considering how next generation sequencing (NGS) could support their newborn screening programs<\/a>, which test approximately four million babies born in the United States each year for congenital, treatable diseases.<\/p>\n\n\n\n

Results from NGS can help enhance newborn screening programs by providing more information beyond traditional biochemical and other tests. Not all states have the expertise needed to interpret NGS results, but the Centers for Disease Control and Prevention (CDC) is developing the Enhancing Data-driven Disease Detection in Newborns (ED3N) system, which has the potential to help. ED3N is being designed to enable secure upload of NGS data in any format and could benefit from data standards that address efficiency and interoperability. A recent pilot project supported by the Department of Health and Human Services Office of the National Coordinator for Health Information Technology (ONC), confirmed that an existing open-source data standard (Health Level 7 International\u00ae (HL7\u00ae) Fast Healthcare Interoperability Resources\u00ae (FHIR\u00ae) can successfully be used to transmit newborn screening NGS data.<\/p>\n\n\n\n

A Pilot Project on FHIR\u00ae<\/h2>\n\n\n\n
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The pilot project was conducted by the Utah Department of Health as part of ONC\u2019s Sync for Genes<\/a> project, which supports the Precision Medicine Initiative<\/a>. Sync for Genes aims to advance data standards that support sharing NGS information to help patients and providers make better decisions. For example, providers can use NGS data to help patients and families\u2014including parents of newborns\u2014plan the best type of care based on the patient\u2019s unique genetic information.<\/p>\n\n\n\n

Utah is currently in the process of expanding the state\u2019s newborn screening program by adding NGS for second-tier testing following an initial result that indicates a baby may have a genetic disorder. This second analysis only includes genes that are involved in that specific genetic disorder. If no unusual results are identified, the analysis can be expanded with parental consent to other genes and the entire exome sequence. Results from this NGS method may require interpretation by a clinical specialist to determine the best course of treatment.<\/p>\n\n\n\n

Most genomic diagnostic reports are still provided in paper or PDF format, but the Sync for Genes pilot project tested whether FHIR\u00ae could be used to transmit the raw NGS data electronically. While diagnostic reports include result interpretations, they do not include raw data. This makes it difficult for patients and providers to share these data with a care team or specialists. FHIR\u00ae can be used to send various types of health information in a format that supports interoperability and that is increasingly being implemented across clinical and research environments. Since these data are machine readable, specialists can more easily use knowledge bases or visualization software to detect relationships and patterns that would have been difficult to previously identify.<\/p>\n\n\n\n

The Utah pilot project team successfully tested the process of sending FHIR\u00ae messages from one server to another with five use cases that can arise in newborn screening:<\/p>\n\n\n\n