A Tutorial for Pharmacogenomics Implementation Through End-to-End Clinical Decision Support Based on Ten Years of Experience from PREDICT

Vanderbilt University Medical Center implemented pharmacogenomics (PGx) testing with the Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment (PREDICT) initiative in 2010. This tutorial reviews the laboratory considerations, technical infrastructure, and programmatic support required to deliver panel-based PGx testing across a large health system with examples and experiences from the first decade of the PREDICT initiative. From the time of inception, automated clinical decision support (CDS) has been a critical capability for delivering PGx results to the point-of-care. Key features of the CDS include human-readable interpretations and clinical guidance that is anticipatory, actionable, and adaptable to changes in the scientific literature. Implementing CDS requires that structured results from the laboratory be encoded in standards-based messages that are securely ingested by electronic health records. Translating results to guidance also requires an informatics infrastructure with multiple components: (1) to manage the interpretation of raw genomic data to star allele results to expected phenotype, (2) to define the rules that associate a phenotype with recommended changes to clinical care, and (3) to manage and update the knowledge base. Knowledge base management is key to processing new results with the latest guidelines, and to ensure that historical genomic results can be reinterpreted with revised CDS. We recommend that these components be deployed with institutional authorization, programmatic support, and clinician education to govern the CDS content and policies around delivery.

Automated summary

This article discusses the implementation of pharmacogenomic testing at Vanderbilt University Medical Center in 2010, highlighting the importance of automated clinical decision support in delivering PGx results to point-of-care. It emphasizes the role of knowledge base management in processing new results and ensuring the reinterpretation of historical genomic results.