Literature DB >> 29261180

Preemptive pharmacogenetic testing: exploring the knowledge and perspectives of US payers.

Nicholas J Keeling1,2, Meagen M Rosenthal1, Donna West-Strum1, Amit S Patel1,3, Cyrine E Haidar2, James M Hoffman2.   

Abstract

PurposePreemptive pharmacogenetic testing aims to optimize medication use by having genetic information at the point of prescribing. Payers' decisions influence implementation of this technology. We investigated US payers' knowledge, awareness, and perspectives on preemptive pharmacogenetic testing.MethodsA qualitative study was conducted using semistructured interviews. Participants were screened for eligibility through an online survey. A blended inductive and deductive approach was used to analyze the transcripts. Two authors conducted an iterative reading process to code and categorize the data.ResultsMedical or pharmacy directors from 14 payer organizations covering 122 million US lives were interviewed. Three concept domains and ten dimensions were developed. Key findings include clinical utility concerns and limited exposure to preemptive germ-line testing, continued preference for outcomes from randomized controlled trials, interest in guideline development, importance of demonstrating an impact on clinical decision making, concerns of downstream costs and benefit predictability, and the impact of public stakeholders such as the Food and Drug Administration and Centers for Medicare and Medicaid Services.ConclusionBoth barriers and potential facilitators exist to developing cohesive reimbursement policy for pharmacogenetics, and there are unique challenges for the preemptive testing model. Prospective outcome studies, more precisely defining target populations, and predictive economic models are important considerations for future research.GENETICS in MEDICINE advance online publication, 26 October 2017; doi:10.1038/gim.2017.181.

Year:  2017        PMID: 29261180      PMCID: PMC5920773          DOI: 10.1038/gim.2017.181

Source DB:  PubMed          Journal:  Genet Med        ISSN: 1098-3600            Impact factor:   8.822


  32 in total

1.  Qualitative data analysis for health services research: developing taxonomy, themes, and theory.

Authors:  Elizabeth H Bradley; Leslie A Curry; Kelly J Devers
Journal:  Health Serv Res       Date:  2007-08       Impact factor: 3.402

2.  Challenges in the development and reimbursement of personalized medicine-payer and manufacturer perspectives and implications for health economics and outcomes research: a report of the ISPOR personalized medicine special interest group.

Authors:  Eric Faulkner; Lieven Annemans; Lou Garrison; Mark Helfand; Anke-Peggy Holtorf; John Hornberger; Dyfrig Hughes; Tracy Li; Daniel Malone; Katherine Payne; Uwe Siebert; Adrian Towse; David Veenstra; John Watkins
Journal:  Value Health       Date:  2012-09-07       Impact factor: 5.725

Review 3.  Pharmacogenomics in the clinic.

Authors:  Mary V Relling; William E Evans
Journal:  Nature       Date:  2015-10-15       Impact factor: 49.962

4.  Clinical pharmacogenetics implementation: approaches, successes, and challenges.

Authors:  Kristin W Weitzel; Amanda R Elsey; Taimour Y Langaee; Benjamin Burkley; David R Nessl; Aniwaa Owusu Obeng; Benjamin J Staley; Hui-Jia Dong; Robert W Allan; J Felix Liu; Rhonda M Cooper-Dehoff; R David Anderson; Michael Conlon; Michael J Clare-Salzler; David R Nelson; Julie A Johnson
Journal:  Am J Med Genet C Semin Med Genet       Date:  2014-03-10       Impact factor: 3.908

5.  PG4KDS: a model for the clinical implementation of pre-emptive pharmacogenetics.

Authors:  James M Hoffman; Cyrine E Haidar; Mark R Wilkinson; Kristine R Crews; Donald K Baker; Nancy M Kornegay; Wenjian Yang; Ching-Hon Pui; Ulrike M Reiss; Aditya H Gaur; Scott C Howard; William E Evans; Ulrich Broeckel; Mary V Relling
Journal:  Am J Med Genet C Semin Med Genet       Date:  2014-03-11       Impact factor: 3.908

6.  Clinically actionable genotypes among 10,000 patients with preemptive pharmacogenomic testing.

Authors:  S L Van Driest; Y Shi; E A Bowton; J S Schildcrout; J F Peterson; J Pulley; J C Denny; D M Roden
Journal:  Clin Pharmacol Ther       Date:  2013-11-19       Impact factor: 6.875

7.  Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network.

Authors:  W S Bush; D R Crosslin; A Owusu-Obeng; J Wallace; B Almoguera; M A Basford; S J Bielinski; D S Carrell; J J Connolly; D Crawford; K F Doheny; C J Gallego; A S Gordon; B Keating; J Kirby; T Kitchner; S Manzi; A R Mejia; V Pan; C L Perry; J F Peterson; C A Prows; J Ralston; S A Scott; A Scrol; M Smith; S C Stallings; T Veldhuizen; W Wolf; S Volpi; K Wiley; R Li; T Manolio; E Bottinger; M H Brilliant; D Carey; R L Chisholm; C G Chute; J L Haines; H Hakonarson; J B Harley; I A Holm; I J Kullo; G P Jarvik; E B Larson; C A McCarty; M S Williams; J C Denny; L J Rasmussen-Torvik; D M Roden; M D Ritchie
Journal:  Clin Pharmacol Ther       Date:  2016-06-01       Impact factor: 6.875

8.  Assessment of pharmacogenetic tests: presenting measures of clinical validity and potential population impact in association studies.

Authors:  E C M Tonk; D Gurwitz; A-H Maitland-van der Zee; A C J W Janssens
Journal:  Pharmacogenomics J       Date:  2016-05-10       Impact factor: 3.550

9.  Scientific challenges and implementation barriers to translation of pharmacogenomics in clinical practice.

Authors:  Y W Francis Lam
Journal:  ISRN Pharmacol       Date:  2013-02-28

10.  Incorporation of pharmacogenomics into routine clinical practice: the Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline development process.

Authors:  Kelly E Caudle; Teri E Klein; James M Hoffman; Daniel J Muller; Michelle Whirl-Carrillo; Li Gong; Ellen M McDonagh; Katrin Sangkuhl; Caroline F Thorn; Matthias Schwab; Jose A G Agundez; Robert R Freimuth; Vojtech Huser; Ming Ta Michael Lee; Otito F Iwuchukwu; Kristine R Crews; Stuart A Scott; Mia Wadelius; Jesse J Swen; Rachel F Tyndale; C Michael Stein; Dan Roden; Mary V Relling; Marc S Williams; Samuel G Johnson
Journal:  Curr Drug Metab       Date:  2014-02       Impact factor: 3.731

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