Development of clinical decision support alerts for pharmacogenomic incidental findings from exome sequencing.
OBJECTIVE
Electronic health records (EHRs) and their associated decision support tools are potentially important means of disseminating a patient's pharmacogenomic profile to his or her health-care providers. We sought to create a proof-of-concept decision support alert system generated from pharmacogenomic incidental findings from exome sequencing.


METHODS
A pipeline for alerts from exome sequencing tests was created for patients in the New EXome Technology in (NEXT) Medicine study at the University of Washington. Decision support rules using discrete, machine-readable incidental finding results were programmed into a commercial EHR rules engine. An evaluation plan to monitor the alerts in real medical interactions was established.


RESULTS
Alerts were created for 48 actionable pharmacogenomic variants in 11 genes and were launched on 24 September 2014 for University of Washington inpatient care. Of the 94 participants enrolled in the NEXT Medicine study, 49 had one or more pharmacogenomic variants identified for return.


CONCLUSIONS
Reflections on the process reveal that while incidental findings can be used to generate decision support alerts, substantial resources are required to ensure that each alert is consistent with rapidly evolving pharmacogenomic literature and is customized to fit in the clinical workflow unique to each incidental finding.
Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.
Adam A
AA
Nishimura
Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA.
Brian H
BH
Shirts
Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA.|Department of Genome Sciences, University of Washington, Seattle, Washington, USA.|Department of Pathology, University of Washington, Seattle, Washington, USA.
Michael O
MO
Dorschner
Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, Washington, USA.
Laura M
http://orcid.org/0000-0002-5506-6168
LM
Amendola
Department of Pharmacy, University of Washington, Seattle, Washington, USA.
Joe W
JW
Smith
Department of Genome Sciences, University of Washington, Seattle, Washington, USA.|Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, Washington, USA.
Gail P
http://orcid.org/0000-0002-6710-8708
GP
Jarvik
Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.|Department of Pediatrics, University of Washington, Seattle, Washington, USA.|Department of Computer Science and Engineering, University of Washington, Seattle, Washington, USA.
Peter
P
Tarczy-Hornoch
D020000:Decision Support Systems, Clinical; D057286:Electronic Health Records; D059472:Exome; D056726:Genetic Association Studies; D014644:Genetic Variation; D005826:Genetics, Medical; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D033162:Incidental Findings; D050316:Medical Order Entry Systems; D010597:Pharmacogenetics