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Per Med. 2017 May;14(3):203-211. doi: 10.2217/pme-2016-0075. Epub 2017 May 23.

The price of whole-genome sequencing may be decreasing, but who will be sequenced?

Author information

1
Department of Community Health Sciences, Room 3C56 Health Research Innovation Centre, University of Calgary, Calgary, Alberta, Canada.
2
Center for Medical Ethics & Health Policy, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, USA.
3
Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA.
4
Center for Clinical Genetics and Genomics at Providence Health & Services Southern California, 181 South Buena Vista Street - Suite 240, Burbank, CA 91505, USA.
5
Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Broad Institute & Harvard Medical School, Boston, MA, USA.
6
Department of Clinical Pharmacy, Center for Translational & Policy Research on Personalized Medicine (TRANSPERS), University of California, San Francisco, CA, USA.
7
Department of Biology, College of Science & Engineering, San Francisco State University, San Francisco, CA, USA.
8
UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA.

Abstract

AIM:

Since whole-genome sequencing (WGS) information can have positive and negative personal utility for individuals, we examined predictors of willingness to pay (WTP) for WGS.

PATIENTS & METHODS:

We surveyed two independent populations: adult patients (n = 203) and college seniors (n = 980). Ordinal logistic regression models were used to characterize the relationship between predictors and WTP.

RESULTS:

Sex, age, education, income, genomic knowledge and knowing someone who had genetic testing or having had genetic testing done personally were associated with significantly higher WTP for WGS. After controlling for income and education, males were willing to pay more for WGS than females.

CONCLUSION:

Differences in WTP may impact equity, coverage, affordability and access, and should be anticipated by public dialog about related health policy.

KEYWORDS:

access to healthcare; attitude to health; healthcare costs; human genome; personalized medicine; whole genome sequencing; willingness-to-pay

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