CHICAGO – With the recent launch of its fourth phase, the federally funded Sync for Genes program has taken a key step toward increasing patient engagement in molecularly informed precision medicine.
Two weeks ago, the Office of the National Coordinator for Health IT (ONC) — the health IT advocacy arm of the US Department of Health and Human Services —announced that the Utah Newborn Screening Program and Children's Hospital of Philadelphia (CHOP) will serve as demonstration sites for Phase 4 of the Sync for Genes.
Phase 4 is focusing on electronic exchange of genomic data between healthcare organizations and patients and caregivers. Both chosen sites will be following various aspects of the Health Level Seven International (HL7) Fast Healthcare Interoperability Resources (FHIR) standard, with the goal of improving pediatric care.
"How do we inform or help our providers make the best-informed decisions or be able to have those conversations with patients?" Kevin Chaney, senior program manager for the Scientific Advancement Branch within ONC, said of the goal of Phase 4.
ONC chose the new demonstration sites from a pool of applicants in part because the Utah Newborn Screening Program and CHOP were already sharing or at least testing the sharing of clinical genomic data, according to Chaney. The two organizations also committed to remain involved with the HL7 Clinical Genomics Working Group.
"It's super helpful for both HL7 as well as the genomics community to continue to broaden folks' interest as well as involvement with standards development processes," Chaney said. "We want to make sure we have good buy-in from the organizations, and we certainly felt that we had that when we selected each of these programs."
Sync for Genes as a whole seeks to standardize methods for communicating genomic information from next-generation sequencing and other tests to clinicians and patients in a usable and consistent manner. Sync for Genes is an extension of the Sync for Science data standardization and sharing effort, which itself is part of the National Institutes of Health's All of Us research program.
Chaney described Sync for Genes and Sync for Science as a "three-legged stool of data" to support precision medicine. Those legs include clinical data from electronic health records, genomes, and then other data types like those from wearable sensors and social determinants of health. The latter was covered by a recently concluded project called Advancing Standards for Precision Medicine.
Phase 1 of Sync for Genes demonstrated the usefulness of the FHIR Genomics standard for interchanging genomic data. It did not include any integration with electronic health records or patient portals. Phase 2, which Chaney called the foundation for future stages, looked at the integration of genomic data through standards-based exchange and represented the first example of Sync for Genes in action in live healthcare settings.
Specifically, the second phase tested interchange of health data using the FHIR Clinical Genomics standard, a component of the current FHIR version 4.0.1.
Phase 3 tried to engage laboratories by testing the HL7 FHIR Genomics Reporting Implementation Guide for sharing genomic data generated by testing labs. In that phase, for example, the National Marrow Donor Program looked at converting human leukocyte antigen reports into FHIR format for incorporation into EHRs.
"Our fourth phase is trying to take it that extra mile," bringing genomic data to care providers and, ultimately, individuals, Chaney said. This involves FHIR application programming interfaces, as called for by the 21st Century Cures Act.
The Cures Act and the anti-information-blocking rule it spawned encouraged the use of APIs and standards such as FHIR to encourage the interoperability of health information to support coordinated care and, indirectly, the practice of precision medicine.
New regulations addressing information blocking took effect April 5 and will become mandatory for electronic health data exchange on Oct. 6, 2022. By then, American healthcare entities will have to adopt the United States Core Data for Interoperability (USCDI), a standardized set of data elements for data interoperability.
Chaney said that a lot of what ONC piloted in Sync for Science related to accessing and sharing clinical data showed up in the final USCDI, including a requirement that EHRs and other health IT systems support APIs and data standards like FHIR to pull in outside data, though it contains nothing specific to genomics. "Potentially some future version of the USCDI will see the fruits of our labor as it relates to Sync for Genes and maybe incorporate a certain component or aspect," he said.
Demonstration projects like the ones just announced for Phase 4 are helping ONC figure out what works and what doesn't in real-world settings from both clinical and research perspectives. "Ultimately we're hopefully leveraging each other's work and driving the field forward to get to … a true learning healthcare system," Chaney said.
According to ONC, CHOP has identified about 400 patients with brain tumors for whom the hospital will electronically exchange genomic diagnostic data between treatment sites. CHOP's Center for Data Driven-Discovery in Biomedicine will work with bioinformaticians in the organization's Division of Genomic Diagnostics to structure data according to FHIR Genomics specifications and will make the information available to clinicians on the other side of the country at the University of California, San Francisco.
Currently, CHOP has to custom-format such reports and send files via email. This demonstration will facilitate exchange of FHIR-formatted information directly between EHR systems.
CHOP's Sync for Genes demonstration coordinator did not respond to interview requests.
The Utah Newborn Screening Program, run by the state government's Utah Public Health Laboratory, participated in Phase 2 in 2018-19.
In the earlier phase, according to Nicole Ruiz-Schultz, a bioinformatician at the Utah Public Health Laboratory, the newborn screening program built FHIR resources for cases involving cystic fibrosis and phenylketonuria (PKU). For example, a newborn who screens positive for cystic fibrosis would go through an under-development pipeline for sequencing — part of another pilot not directly related to Sync for Genes — that would attach a VCF file to that infant's medical record.
The program built similar FHIR resources for patients who were negative for CF and for the highly unlikely scenario in which a newborn screened abnormal for two diseases like CF and PKU.
"We were able to demonstrate that we could create the message, we could enter in all of the data for that message, and we could also attach that VCF file to the message," Ruiz-Schultz said.
The Utah Newborn Screening Program mostly employs biochemical tests such as mass spectrometry and some immunoassays. Only for second-tier, third-tier, and confirmatory testing does the program turn to genotyping if initial screening suggests an abnormality, according to Andreas Rohrwasser, director of the Utah Public Health Laboratory.
If a newborn tests abnormal on primary or secondary biochemical analyses, the program then runs whole-exome sequencing on the same biospecimen, or a new sample for confirmatory purposes.
The Utah lab is essentially building a statewide infrastructure for analysis. Hospitals run their own tests, but follow a standard set of protocols for abnormal results.
In Sync for Genes Phase 4, the Utah Newborn Screening Program will be exploring messaging standards to move genomics data between the clinicians and families who need to see such information, Rohrwasser said.
This project dovetails with a pilot the Utah Public Health Laboratory is running to test a methodology that expedites analysis of sequencing-based newborn screening by focusing bioinformatics on the gene associated with a potential disorder, such as CFTR for cystic fibrosis.
"We can basically use whole-exome sequencing as the universal method and then bioinformatically just target the pipeline to this gene or this gene or a set of genes," Ruiz-Schultz said. If there is still a question in the mind of a specialist physician, the screening program could then expand analysis to the entire exome.
"We want to see if using next-generation sequencing methods as a secondary analysis method in newborn screening would be effective," Ruiz-Schultz said. "Would it be informative and would our clinical partners like it?"
Rohrwasser said that this targeted screening and genomic analysis can help shorten the "diagnostic odyssey" for a small group of newborns who might not outwardly show classic symptoms of certain disorders.
"It's really a practice component that reduces the time to diagnosis," he said. "Sometimes these babies and families, they struggle for years to get a proper diagnosis and ultimately the right clinical care."
The Utah Public Health Laboratory team developed a proof-of-concept application to test the sending of results from this analysis to families of newborns. Working with University of Utah researchers, they described their method in a paper published in Genetics in Medicine last month.
The methodology that Ruiz-Schultz and colleagues developed allows parents or guardians to authorize the electronic transmission of genotyping results and analysis to specific physicians, but Rohrwasser said that data exchange is a secondary benefit.
It just so happened that Sync for Genes Phase 4 had a similar goal, so the Utah Newborn Screening Program applied. Ruiz-Schultz said that the state lab is looking to apply for an NIH RL1 grant to help advance this work to and put the technology into production as soon as this year.
Meantime, ONC is looking ahead to a potential fifth phase of Sync for Genes, though Chaney was not ready to discuss what it might entail. He said that all of the earlier Sync for Genes work has informed plans for subsequent phases.
Chaney said that ONC has identified six "challenge areas" related to genomics data: standards, standards implementation, infrastructure to support standards, utilization of genomics data, education, and public policy related to genomic data standards. "This will serve as a great framework, not just for ONC, but hopefully the rest of our federal colleagues and the research community on areas in which we can continue to bridge gaps that are there and advance genomic data standards," he said.