This chapter will look at the present state and challenges of integrating genomic test results and genomic decision support (GDS) into an electronic health record (EHR). The fundamental premise of this chapter is that EHRs are becoming increasingly prevalent and that any intervention that seeks to change clinical outcomes will have to do so through the EHR. Where possible in this chapter, the present state and challenges will be compared and contrasted in commercial and internally developed EHRs. Commercial EHRs while significantly more prevalent may have initially less flexibility to accept genomic test results and to provide GDS especially in the age of regulated meaningful use. The meaningful use of EHRs is defined by the CMS EHR incentive program funded through the HITECH acts as part of the American Recovery and Reinvestment Act of 2009. For purposes of this chapter, we define GDS as a form of computerized clinical decision support or clinical decision support system (CDSS). This chapter will also examine the present state of and challenges with usability in regards to genomic test results and genomic CDS.
Opportunities and Need for Genomic Decision Support
Until recently, the use of genetic and genomic information was largely restricted to diagnostic guidance or esoteric treatment guidance, in which the only consumer of the information is an expert in that field (eg, oncology, genetic medicine for rare diseases). One of the earliest examples of implementation of genetic medicine is with azathioprine and thiopurine methyltransferase (TPMT) activity, which can be tested through genetics as well as enzyme activity. However, a recent growing body of evidence points to common medications as targets for genomic guidance, including clopidogrel, warfarin, and simvastatin. Each of these has been a top grossing medication worldwide within the last decade, and can be commonly prescribed by a diverse group of practitioners, including specialists and primary care physicians. Indeed, the body of genetic evidence is growing, and, as of first-quarter 2012, the US Food and Drug Administration lists pharmacogenetic information in the structured product labels of 99 medications. The future of personalized medicine envisions a time in which many medications have potential pharmacogenetic influences. Given a growing list of medications with pharmacogenetic influences and more individuals exposed to potential prescribing conditions, there is a need to develop and maintain genomic CDS that will enable easy access to the current evidence-based practices for safe and effective prescribing. Indeed, one can argue that the diversity and complexity of genomic testing and results is an ideal candidate for CDS for several reasons: (1) the complexity is difficult for a broad community to maintain, (2) proper interpretation of genetic test results requires knowledge of specific allele changes and combinations that currently are not expressed in self-evident nomenclature (eg, CYP2C19*2 represents a poor metabolizing variants while CYP2C19*17 is a hypermetabolizing variant), (3) the ability to incorporate, within CDS, drug-genome, drug-drug, and drug-drug-genome interactions to a level of ...