A New Framework and Prototype Solution for Clinical Decision Support and Research in Genomics and Other Data-intensive Fields of Medicine

James P Evans, Kirk C Wilhelmsen, Jonathan Berg, Charles P Schmitt, Ashok Krishnamurthy, Karamarie Fecho, Stanley C Ahalt, James P Evans, Kirk C Wilhelmsen, Jonathan Berg, Charles P Schmitt, Ashok Krishnamurthy, Karamarie Fecho, Stanley C Ahalt

Abstract

Introduction: In genomics and other fields, it is now possible to capture and store large amounts of data in electronic medical records (EMRs). However, it is not clear if the routine accumulation of massive amounts of (largely uninterpretable) data will yield any health benefits to patients. Nevertheless, the use of large-scale medical data is likely to grow. To meet emerging challenges and facilitate optimal use of genomic data, our institution initiated a comprehensive planning process that addresses the needs of all stakeholders (e.g., patients, families, healthcare providers, researchers, technical staff, administrators). Our experience with this process and a key genomics research project contributed to the proposed framework.

Framework: We propose a two-pronged Genomic Clinical Decision Support System (CDSS) that encompasses the concept of the "Clinical Mendeliome" as a patient-centric list of genomic variants that are clinically actionable and introduces the concept of the "Archival Value Criterion" as a decision-making formalism that approximates the cost-effectiveness of capturing, storing, and curating genome-scale sequencing data. We describe a prototype Genomic CDSS that we developed as a first step toward implementation of the framework.

Conclusion: The proposed framework and prototype solution are designed to address the perspectives of stakeholders, stimulate effective clinical use of genomic data, drive genomic research, and meet current and future needs. The framework also can be broadly applied to additional fields, including other '-omics' fields. We advocate for the creation of a Task Force on the Clinical Mendeliome, charged with defining Clinical Mendeliomes and drafting clinical guidelines for their use.

Keywords: clinical decision support; electronic medical records; genomics.

Figures

Figure 1.
Figure 1.
Proposed Framework for Genomic Clinical Decision Support Notes: CDSS = Clinical Decision Support System. Source: Image courtesy of RENCI.
Figure 2.
Figure 2.
Overview of NCGENES Operations and Capabilities Notes: ELSI Researcher = Ethical, Legal, and Social Implications Researcher; EMR = electronic medical record; GMW Engine = Genetic Medical Workflow Engine; PHI = protected health information. Source: Image courtesy of RENCI
Figure 3.
Figure 3.
Schematic Showing the Workflows Managed by the GMW Engine Notes: Arrows depict the information flow. AnnoBot = Annotation Bot; BSP lab = BioSpecimen Processing laboratory; CANVAS = CAroliNa Variant Annotation Store; CLIA lab = a laboratory certified to meet United States Congressional Clinical Laboratory Improvements Amendments; Dx = diagnostic; ELSI Researcher = Ethical, Legal, and Social Implications Researcher; EMR = electronic medical record; GMW Engine = Genetic Medical Workflow Engine; iRODS = integrated Rule-Oriented Data System; MaPSeq = Massively Parallel Sequencing system; PHI = protected health information; QC = Quality Control; Wet lab = basic science laboratory. Source: Image reprinted with permission from Owen et al.
Figure 4.
Figure 4.
NCGENES CDSS User Interface Showing Study Status and Results for a Study Participant Notes: Dx = Diagnostic; ID = identifier. Source: Image courtesy of NCGENES.
Figure 5.
Figure 5.
Prototype NCGENES CDSS User Interface (Termed “Carnac”) Notes: Carnac provides detailed views of the implicated gene and genetic locus (panel A); the American College of Medical Genetics current body of evidence regarding the identified genomic variant (panel B); and a comparative, population-level overview of all alleles at that genetic locus (left side of panels A and B). Source: Images courtesy of NCGENES.

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