title: Adoption of a clinical pharmacogenomics implementation program during outpatient care--initial results of the University of Chicago "1,200 Patients Project".
abstract: Pharmacogenomic testing is viewed as an integral part of precision medicine. To achieve this, we originated The 1,200 Patients Project which offers broad, preemptive pharmacogenomic testing to patients at our institution. We analyzed enrollment, genotype, and encounter-level data from the first year of implementation to assess utility of providing pharmacogenomic results. Results were delivered via a genomic prescribing system (GPS) in the form of traffic lights: green (favorable), yellow (caution), and red (high risk). Additional supporting information was provided as a virtual pharmacogenomic consult, including citation to relevant publications. Currently, 812 patients have participated, representing 90% of those approached; 608 have been successfully genotyped across a custom array. A total of 268 clinic encounters have occurred at which results were accessible via the GPS. At 86% of visits, physicians accessed the GPS, receiving 367 result signals for medications patients were taking: 57% green lights, 41% yellow lights, and 1.4% red lights. Physician click frequencies to obtain clinical details about alerts varied according to color severity (100% of red were clicked, 72% yellow, 20% green). For 85% of visits, clinical pharmacogenomic information was available for at least one drug the patient was taking, suggesting relevance of the delivered information. We successfully implemented an individualized health care model of preemptive pharmacogenomic testing, delivering results along with pharmacogenomic decision support. Patient interest was robust, physician adoption of information was high, and results were routinely utilized. Ongoing examination of a larger number of clinic encounters and inclusion of more physicians and patients is warranted.
authors.forename: Peter H
authors.initials: PH
authors.lastname: O'Donnell
authors.forename: Keith
authors.initials: K
authors.lastname: Danahey
authors.forename: Michael
authors.initials: M
authors.lastname: Jacobs
authors.forename: Nisha R
authors.initials: NR
authors.lastname: Wadhwa
authors.forename: Shennin
authors.initials: S
authors.lastname: Yuen
authors.forename: Angela
authors.initials: A
authors.lastname: Bush
authors.forename: Yasmin
authors.initials: Y
authors.lastname: Sacro
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Sorrentino
authors.forename: Mark
authors.initials: M
authors.lastname: Siegler
authors.forename: William
authors.initials: W
authors.lastname: Harper
authors.forename: Andrea
authors.initials: A
authors.lastname: Warrick
authors.forename: Soma
authors.initials: S
authors.lastname: Das
authors.forename: Don
authors.initials: D
authors.lastname: Saner
authors.forename: Christopher L
authors.initials: CL
authors.lastname: Corless
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Ratain
mesh_terms: D000046:Academic Medical Centers / Q000379:methods* / Q000639:trends; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000553:Ambulatory Care / Q000379:methods*; D002641:Chicago; D005260:Female; D005838:Genotype; D006801:Humans; D008297:Male; D008875:Middle Aged; D010597:Pharmacogenetics / Q000379:methods* / Q000706:statistics & numerical data / Q000639:trends; D016730:Program Development / Q000379:methods* / Q000706:statistics & numerical data
keywords: genomic medicine; implementation; pharmacogenomics; precision medicine