title: Characterizing Pharmacogenomic-Guided Medication Use With a Clinical Data Repository.
abstract: The extent to which pharmacogenomic-guided medication use has been adopted in various health systems is unclear. To assess the uptake of pharmacogenomic-guided medication use, we determined its frequency across our health system, which does not have a structured testing program. Using a multisite clinical data repository, we identified adult patients' first prescribed medications between January 2011 and December 2013 and investigated the frequency of germline and somatic pharmacogenomic testing, by the Pharmacogenomics Knowledgebase level of the US Food and Drug Administration label information. There were 268,262 medication orders for drugs with germline pharmacogenomic testing information in their drug labels. Pharmacogenomic testing was detected for 1.5% (129/8,718) of medication orders with recommended or required testing. Of the 3,817 medication orders associated with somatic pharmacogenomic testing information in their drug labels, 20% (372/1,819) of required tests were detected. The low rates of detectable pharmacogenomic testing suggest that structured testing programs are required to achieve the success of precision medicine.
authors.affiliation: Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA.
authors.forename: P C
authors.initials: PC
authors.lastname: Mathias
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, Washington, USA.
authors.forename: N
authors.initials: N
authors.lastname: Hendrix
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, Washington, USA.
authors.forename: W-J
authors.initials: WJ
authors.lastname: Wang
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, Washington, USA.
authors.forename: K
authors.initials: K
authors.lastname: Keyloun
authors.affiliation: Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.
authors.forename: M
authors.initials: M
authors.lastname: Khelifi
authors.affiliation: Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.|Department of Pediatrics, Division of Neonatology, University of Washington, Seattle, Washington, USA.|Department of Computer Science and Engineering, University of Washington, Seattle, Washington, USA.
authors.forename: P
authors.initials: P
authors.lastname: Tarczy-Hornoch
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, Washington, USA.|Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.|Department of Health Services, University of Washington, Seattle, Washington, USA.
authors.forename: B
authors.initials: B
authors.lastname: Devine
mesh_terms: D000328:Adult; D000368:Aged; D015331:Cohort Studies; D016208:Databases, Factual / Q000639:trends; D004363:Drug Utilization / Q000639:trends; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010597:Pharmacogenetics / Q000379:methods* / Q000639:trends; D000071185:Pharmacogenomic Testing / Q000379:methods* / Q000639:trends; D057285:Precision Medicine / Q000379:methods* / Q000639:trends; D012189:Retrospective Studies