Operational Implementation of Prospective Genotyping for Personalized Medicine: The Design of the Vanderbilt PREDICT Project

Pulley, Jill M.; Denny, Joshua C.; Peterson, JF; Bernard, Gordon R.; Vnencak-Jones, C. L.; Ramirez, Andrea H.; Delaney, Jessica; Bowton, Erica; Johnson, Kevin B.; Crawford, Dana C.; Schildcrout, J.; Masys, Daniel R.; Dilks, Holli H.; Wilke, Russell A.; Clayton, Ellen Wright; Shultz, Edward K.; Laposata, Michael; McPherson, John; Jirjis, Jim; Roden, Dan M.

doi:10.1038/clpt.2011.371

Cited by 369 publications

(357 citation statements)

References 44 publications

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“…In addition, clinical decision support could be developed to prompt providers to discuss key features of PGx testing with patients. Clinical decision support has already been developed to alert providers about patients for whom for PGx testing is clinically indicated (e.g., based on prescription ordered), or recommendation for adjustments to dosing or drug selection based on test results [47,70]. Considering the increased utilization of electronic medical records and patient portals, it may be possible to easily provide supplementary patient educational materials about testing or to print and distribute to the patient without online access to enhance patient understanding and optimize the limited time in an office visit.…”

Section: Discussionmentioning

confidence: 99%

“…PGx testing requires consent particularly if it reveals secondary information [46], whereas others stated a preference for a brief verbal notification about testing from their provider instead of a formal signed consent form [47]. Some evidence suggests that patients may have difficulty understanding concepts of PGx [48,49].…”

Section: Consent Practices For Pgx Testing Systematic Reviewmentioning

confidence: 99%

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A Review of Consent Practices and Perspectives for Pharmacogenetic testing

Haga

Mills

2016

Pharmacogenomics

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Aim:We aimed to understand consent practices for pharmacogenetic (PGx) testing. Methods: We conducted a literature review and analysis of consent forms from clinical laboratories offering PGx testing. Results: Our review of the literature shows a lack of consensus about the need for and type of informed consent for PGx testing. We identified 35 companies offering PGx testing and were able to confirm consent practices for 22 of those. We found a range of variability in the consent practices regarding the consent approach and information disclosed. Conclusion: Variability in the consent practices among laboratories offering PGx testing mirrors the ambiguous practices and recommendations reported in the literature. Establishing a minimal set of information to be disclosed to patients may help address the disparities in consent practice.

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Section: Discussionmentioning

confidence: 99%

Section: Consent Practices For Pgx Testing Systematic Reviewmentioning

confidence: 99%

A Review of Consent Practices and Perspectives for Pharmacogenetic testing

Haga

Mills

2016

Pharmacogenomics

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“…Currently, the routine use of clinical pharmacogenomics is limited to centers with resources to overcome these obstacles [5][6][7][8][9].…”

Section: Background and Significancementioning

confidence: 99%

“…[1] Nonetheless, the translation of pharmacogenomic testing into routine clinical practice has been slow due to several obstacles towards its implementation [2][3][4]. Currently, the routine use of clinical pharmacogenomics is limited to centers with resources to overcome these obstacles [5][6][7][8][9].…”

Section: Background and Significancementioning

confidence: 99%

Iterative Development and Evaluation of a Pharmacogenomic-Guided Clinical Decision Support System for Warfarin Dosing

Melton¹,

Zillich²,

Saleem³

et al. 2016

Appl Clin Inform

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SummaryObjective: Pharmacogenomic-guided dosing has the potential to improve patient outcomes but its implementation has been met with clinical challenges. Our objective was to develop and evaluate a clinical decision support system (CDSS) for pharmacogenomic-guided warfarin dosing designed for physicians and pharmacists. Methods: Twelve physicians and pharmacists completed 6 prescribing tasks using simulated patient scenarios in two iterations (development and validation phases) of a newly developed pharmacogenomic-driven CDSS prototype. For each scenario, usability was measured via efficiency, recorded as time to task completion, and participants' perceived satisfaction which were compared using Kruskal-Wallis and Mann Whitney U tests, respectively. Debrief interviews were conducted and qualitatively analyzed. Usability findings from the first (i.e. development) iteration were incorporated into the CDSS design for the second (i.e. validation) iteration. Results: During the CDSS validation iteration, participants took more time to complete tasks with a median (IQR) of 183 (124-247) seconds versus 101 (73.5-197) seconds in the development iteration (p=0.01). This increase in time on task was due to the increase in time spent in the CDSS corresponding to several design changes. Efficiency differences that were observed between pharmacists and physicians in the development iteration were eliminated in the validation iteration. The increased use of the CDSS corresponded to a greater acceptance of CDSS recommended doses in the validation iteration (4% in the first iteration vs. 37.5% in the second iteration, p<0.001). Overall satisfaction did not change statistically between the iterations but the qualitative analysis revealed greater trust in the second prototype. Conclusions: A pharmacogenomic-guided CDSS has been developed using warfarin as the test drug. The final CDSS prototype was trusted by prescribers and significantly increased the time using the tool and acceptance of the recommended doses. This study is an important step toward incorporating pharmacogenomics into CDSS design for clinical testing. Research ArticleBL Background And SignificancePersonalized medicine is an emerging field with the fundamental objective to predict a patient's response in order to individualize drug therapy for improved medication effectiveness and safety. Pharmacogenomic-guided drug therapy is at the forefront of personalized medicine with over 150 United States Food and Drug Administration (FDA) approved drug labels incorporating pharmacogenomic information.[1] Nonetheless, the translation of pharmacogenomic testing into routine clinical practice has been slow due to several obstacles towards its implementation [2][3][4]. Currently, the routine use of clinical pharmacogenomics is limited to centers with resources to overcome these obstacles [5][6][7][8][9].A major obstacle in the implementation of clinical pharmacogenomics is the rapid pace that science has identified genetic polymorphisms that can predict drug response. Th...

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“…1,[25][26][27] The PREDICT project, which was launched institutionally in 2010, provides patients with a pharmacogenomic profile of possible sensitivities to these specific medications. 25 There were over 14,000 genotyped patients within the PREDICT database, panels which included genotypes of both VKORC1 and CYP2C9. For warfarin and other drugs, this information has greatly assisted practitioners manage medications in the inpatient and clinical settings.…”

Section: S147mentioning

confidence: 99%