Advances in FHIR Standards for Clinical Genomics and Precision Medicine

Presentation Time: 01:45 PM - 02:00 PM

Abstract Keywords: Data Standards, Knowledge Representation and Information Modeling, Interoperability and Health Information Exchange, Omics (genomics, metabolomics, proteomics, transcriptomics, etc.) and Integrative Analyses
Primary Track: Foundations
Programmatic Theme: Clinical Research Informatics

Structured and interoperable genetic data are a cornerstone of personalized medicine, where data can flow seamlessly between various information systems and medical settings. HL7 Clinical Genomics Information Modeling Subgroup is working to model genetic concepts in alignment with other workgroups. This work presents the developed FHIR Molecular Definition Resource and its four profiles: Sequence, Allele, Haplotype, and Genotype. These advances will boost genetic data exchange for clinical, research, and knowledge representation purposes.

Speaker(s):
Robert Freimuth, PhD
Mayo Clinic

Author(s):
Aly Khalifa, PhD - Mayo Clinic; Xianfeng Chen, Ph.D; Robert Freimuth, PhD - Mayo Clinic;

A Novel Model to Support Genomic Interpretations and Knowledge within Clinical Electronic Systems

Presentation Time: 02:00 PM - 02:15 PM

Abstract Keywords: Precision Medicine, Knowledge Representation and Information Modeling, Pharmacogenomics, Clinical Decision Support
Primary Track: Foundations
Programmatic Theme: Clinical Research Informatics

Implementations in genomic medicine are increasingly supported by advances in assay technology and in electronic health record (EHR) systems. Many institutions implemented pharmacogenomic (PGx) testing paired with recommendations delivered via CDS, and similar approaches are now being taken for hereditary disease. While those implementations demonstrate the potential of using patient genomic data at the bedside, they are almost exclusively based on static interpretations that are included in or derived from the lab report, which means changes in knowledge related to either the interpretation of genomic variation or clinical recommendations could result in a cascade of impacts through patient charts and CDS implementations. To achieve genomic medicine at scale, robust knowledge management systems that are integrated into the EHR and that can provide up to date interpretations and recommendations to caregivers are needed.

We developed a novel model that addresses limitations in current approaches, which rely on relational tables and/or complex rule logic that may be tedious and expensive to maintain or update. We reviewed genomic CDS implementations from several institutions and current consortia guidelines and surveyed how changes in genomic knowledge and test result reporting practices have impacted CDS logic and the derived data maintained on patient records. The model was validated using example data from real implementations. We predict this model will prove to be a more semantically robust, computable, and resilient model to support genomic medicine.

Speaker(s):
Robert Freimuth, PhD
Mayo Clinic

Author(s):
Sarah Senum, MS - Mayo Clinic; Michael Panzer, MA - Mayo Clinic; Tim Bridwell, MS - Mayo Clinic; Salem Bajjali, MS - Mayo Clinic; Aly Khalifa, PhD - Mayo Clinic;

OCTOPUS: Disk-based, Multiplatform, Mobile-friendly Metagenomics Classifier

Presentation Time: 02:15 PM - 02:30 PM

Abstract Keywords: Bioinformatics, Mobile Health, Computational Biology, Omics (genomics, metabolomics, proteomics, transcriptomics, etc.) and Integrative Analyses
Primary Track: Foundations
Programmatic Theme: Public Health Informatics

Portable genomic sequencers such as Oxford Nanopore’s MinION enable real-time applications in both clinical and environmental health. However, there is a bottleneck in the downstream analytics when bioinformatics pipelines are unavailable, e.g., when cloud processing is unreachable due to absence of Internet connection, or only low-end computing devices can be carried on site. In this work, we present a platform-friendly software for portable metagenomic analysis of Nanopore data, the Oligomer-based Classifier of Taxonomic Operational and Pan-genome Units via Singletons (OCTOPUS). OCTOPUS is written in Java, reimplements several features of the popular Kraken2 and KrakenUniq software, with original components for improving metagenomics classification on incomplete/sampled reference databases, making it ideal for running on smartphones or tablets. OCTOPUS obtains sensitivity and precision comparable to Kraken2, while dramatically decreasing (4- to 16-fold) the false positive rate. OCTOPUS is available along with customized databases at https://github.com/DataIntellSystLab/OCTOPUS and https://github.com/Ruiz-HCI-Lab/OctopusMobile.

Speaker(s):
Simone Marini, PhD
University of Florida

Author(s):
Simone Marini, PhD - University of Florida; Alexander Barquero, Mr - University of Florida; Anisha Ashok Wadhwani, MSc - University of Florida; Jiang Bian, PhD - University of Florida; Jamie Ruitz, PhD - University of Florida; Christina Boucher, PhD - University of Florida; Mattia Prosperi, PhD, FAMIA - University of Florida;

Translating Evidence-Based Guidelines Into Clinical Decision Support Tools to Improve Identification and Management of Familial Hypercholesterolemia

Presentation Time: 02:30 PM - 02:45 PM

Abstract Keywords: Informatics Implementation, Clinical Decision Support, Precision Medicine, User-centered Design Methods
Primary Track: Applications
Programmatic Theme: Clinical Informatics

Evidence-based clinical guidelines serve to support clinical decision making, but implementing such guidelines into practice remains a challenge. Familial hypercholesterolemia (FH) is a high impact clinical condition that exemplifies this disconnect. Using implementation science methods, we designed clinical decision support tools embedded into the electronic health record, including a FH-focused Epic® Smart Set and clinic note template, to improve the care of adult and pediatric patients at high-risk of FH. End-user feedback gathered through direct observations, semi-structured interviews, and deliberative engagement sessions was used to inform the development of the tools before and after pilot-testing. Clinicians desired comprehensive, guidelines-based tools that promoted collaborative care. During pilot testing, end-users provided insights into technical issues encountered with the tool’s first iteration and suggested regular check-in sessions to monitor issues moving forward. This methodology can be used to surmount challenges that prevent the uptake of evidence-based guidelines into practice.

Speaker(s):
Timothy Shuey, DO
Geisinger

Tyler Schubert, BA
Geisinger

Author(s):
Timothy Shuey, DO - Geisinger; Tyler Schubert, BA - Geisinger; Katrina Romagnoli, PhD, MS, MLIS - Geisinger; Dylan Cawley, MPH - Geisinger; Laney Jones, PharmD, MPH - Geisinger; Samuel Gidding, MD - Geisinger; Marc Williams, MD - Marc S. Williams;

Genomic clinical decision support in nephrology: a user-centered design and prototype analysis

Presentation Time: 02:45 PM - 03:00 PM

Abstract Keywords: Clinical Decision Support, Precision Medicine, Omics (genomics, metabolomics, proteomics, transcriptomics, etc.) and Integrative Analyses, Bioinformatics, Workflow
Primary Track: Applications
Programmatic Theme: Clinical Informatics

We developed a prototype genomic clinical decision support (gCDS) system to help aid nephrologists in the diagnosis of genetic conditions. The prototype is based on findings from qualitative interviews with nephrologists and design specifications from a design thinking workshop with nephrologists, genetics and informaticians.

Speaker(s):
Darren Johnson
Geisinger Medical Center

Author(s):
Darren Johnson - Geisinger Medical Center; Katrina Romagnoli, PhD, MS, MLIS - Geisinger; Marc Williams, MD - Marc S. Williams; Zachary Salvati, MS - Geisinger; Heather Ramey, MS - Geisinger; Alexander Chang, MD - Geisinger;