Genomics and electronic health record systems

Abstract

Several reviews and case reports have described how information derived from the analysis of genomes are currently included in electronic health records (EHRs) for the purposes of supporting clinical decisions. Since the introduction of this new type of information in EHRs is relatively new (for instance, the widespread adoption of EHRs in the United States is just about a decade old), it is not surprising that a myriad of approaches has been attempted, with various degrees of success. EHR systems undergo much customization to fit the needs of health systems; these approaches have been varied and not always generalizable. The intent of this article is to present a high-level view of these approaches, emphasizing the functionality that they are trying to achieve, and not to advocate for specific solutions, which may become obsolete soon after this review is published. We start by broadly defining the end goal of including genomics in EHRs for healthcare and then explaining the various sources of information that need to be linked to arrive at a clinically actionable genomics analysis using a pharmacogenomics example. In addition, we include discussions on open issues and a vision for the next generation systems that integrate whole genome sequencing and EHRs in a seamless fashion.

Figure 1.

Schematic illustration of API for genomics and EHR. (A) Generic user-server communication using an API. (B) Translation of words into API request URLs against real servers in EPIC, NIH and WashU. (C) An example response, or output, from DGIdb in JSON format. Given a gene, HLA-B, drug ABACAVIR is returned based on PharmGKB and FDA data, as described in this article.

Figure 2.

Workflow of the perioperative process and integration of pharmacogenomics. PGx, pharmacogenomics.