Empowering Interoperable Genomics-Enabled Learning Health Systems at Scale
Project Number1U01HG013784-01
Contact PI/Project LeaderKAWAMOTO, KENSAKU Other PIs
Awardee OrganizationUNIVERSITY OF UTAH
Description
Abstract Text
PROJECT SUMMARY/ABSTRACT
There is significant potential for patient care enabled by genomics to enable transformational improvements in
health. However, the actual uptake of genomic medicine into clinical care has been limited to date. The
University of Utah (UU) Genomics Learning in the Utah Ecosystem (GLUE) Center will contribute to a
Genomics-Enabled Learning Health Systems (gLHS) Network that will catalyze the wide implementation of
genomic medicine. The GLUE Center will offer the gLHS Network unique expertise, collaborations, and
resources to address key areas of need, including the UU ReImagine EHR Initiative, which has been a pioneer
in leveraging electronic health record (EHR) interoperability standards to improve patient care and the provider
experience at scale; Value-Driven Outcomes, an enterprise platform for assessing and improving care value and
efficiency; the Genetic Cancer Risk Detector (GARDE), a standards-based platform for population-level genetic
screening; the Mendelian Phenotype Search Engine (MPSE), which continuously analyses the EHR to identify
patients most likely to benefit from rapid whole genome sequencing (rWGS); and extensive experience working
with safety-net clinics to reduce healthcare disparities through scalable informatics interventions. As a gLHS
Network site, the GLUE Center will pursue three Aims to contribute our expertise and ensure the success and
broad impact of the network. First, we will provide vision, infrastructure and expertise to the gLHS Network
and enable Network-wide implementation of interoperable interventions, including for pharmacogenomics
(PGx). We will contribute open-source tools and interoperability expertise to enhance the scalability of
interventions chosen for Network-wide dissemination, including for providing PGx guidance. Second, we will
support Network-wide dissemination of the standards-based GARDE clinical decision support platform for
population-based genetic testing. An open-source, standards-based tool that leverages AI and chatbot
technologies, GARDE has been successfully used in a multi-site pragmatic clinical trial to identify, reach,
educate, and facilitate at-home genetic testing of hereditary cancer syndromes. GARDE can be adapted to
facilitate genetic testing for any condition chosen by the Network. Given its public health importance, we
propose the Network focuses on genetic testing for familial hypercholesterolemia. Third, we propose the real-
time identification of critically ill newborns most likely to benefit from rWGS. At Rady Children’s Hospital-
San Diego and the UU Neonatal Intensive Care Unit (NICU), we deployed an automated, open-source pipeline
(MPSE) that prioritizes patients for rWGS using Human Phenotype Ontology terms derived directly from the
EHR. Here, we propose a pilot deployment of MPSE at NICUs across the network for daily, automatic review
of evolving medical records to prioritize newborns for clinically indicated rWGS. Through these efforts, the
GLUE Center will contribute critical and unique expertise that will help ensure the Network is successful in its
mission to discover and disseminate effective and equitable strategies for enabling genomic medicine at scale.
Public Health Relevance Statement
PROJECT NARRATIVE
While it is now possible to rapidly and efficiently characterize our genetic makeup to guide our health and
healthcare, the routine use of our genetics in clinical care – what is known as “genomic medicine” – remains
limited. In this project, the University of Utah (UU) and its Genomics Learning in the Utah Ecosystem (GLUE)
Center will contribute to the establishment of a Genomics-Enabled Learning Health Systems Network that aims
to spark the much wider implementation of genomic medicine, including for using our genetic makeup to
identify what medications are likely to be most safe and effective to use; providing a chatbot-facilitated
approach to enable widespread education and mail-in testing for genetic conditions that significantly increase
our risk of common and potentially preventable diseases such as cancer and heart disease; and automatically
identifying critically ill newborns who may benefit from genetic testing that identifies treatable causes for their
life-threatening conditions. Ultimately, the UU GLUE Center aims to collaborate with like-minded peers across
the nation to discover and disseminate the most effective and fair strategies for enabling genomic medicine at
scale to improve health and healthcare in the United States and beyond.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AddressAreaArtificial IntelligenceCaringCenters for Disease Control and Prevention (U.S.)ClinicClinicalCollaborationsDiseaseDisparityEcosystemEducationEffectivenessElectronic Health RecordEnsureEquityEvaluationEvidence based interventionFamilial HypercholesterolemiaGeneticGenetic DiseasesGenetic ScreeningGenomic medicineGenomicsGuidelinesHealthHealth systemHealthcareHeart DiseasesHereditary Neoplastic SyndromesHomeHumanInformaticsInfrastructureInstitutionInterventionInvestmentsLaboratoriesLeadershipLearningLifeMalignant NeoplasmsMedical RecordsMendelian disorderMindMissionMulticenter StudiesNational Human Genome Research InstituteNeonatal Intensive Care UnitsNewborn InfantOntologyOutcomePatient CarePatientsPediatric HospitalsPharmaceutical PreparationsPharmacogenomicsPhenotypePhysician ExecutivesPilot ProjectsPopulationPragmatic clinical trialProviderPublic HealthResearchResourcesRiskSiteTechnologyTestingTimeTranslational ResearchUnited StatesUniversitiesUtahVisioncancer geneticscancer riskchatbotclinical careclinical decision supportcritically ill newborndetectordigital healthelectronic health record systemempowermentexperiencegenetic approachgenetic makeupgenetic testinggenome sequencinghealth care disparityimplementation scienceimprovedinteroperabilitylearning progressionmembermultidisciplinaryopen sourceopen source toolpeerpopulation basedpragmatic trialsafety netsearch enginestandard of caresuccesssupport networktooluptakewhole genome
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