title: Willingness-to-pay for predictive tests with no immediate treatment implications: a survey of US residents.
abstract: We assessed how much, if anything, people would pay for a laboratory test that predicted their future disease status. A questionnaire was administered via an internet-based survey to a random sample of adult US respondents. Each respondent answered questions about two different scenarios, each of which specified: one of four randomly selected diseases (Alzheimer's, arthritis, breast cancer, or prostate cancer); an ex ante risk of developing the disease (randomly designated 10 or 25%); and test accuracy (randomly designated perfect or 'not perfectly accurate'). Willingness-to-pay (WTP) was elicited with a double-bounded, dichotomous-choice approach. Of 1463 respondents who completed the survey, most (70-88%, depending on the scenario) were inclined to take the test. Inclination to take the test was lower for Alzheimer's and higher for prostate cancer compared with arthritis, and rose somewhat with disease prevalence and for the perfect versus imperfect test [Correction made here after initial online publication.]. Median WTP varied from $109 for the imperfect arthritis test to $263 for the perfect prostate cancer test. Respondents' preferences for predictive testing, even in the absence of direct treatment consequences, reflected health and non-health related factors, and suggests that conventional cost-effectiveness analyses may underestimate the value of testing.
authors.affiliation: Center for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA. pneumann@tuftsmedicalcenter.org
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Neumann
authors.forename: Joshua T
authors.initials: JT
authors.lastname: Cohen
authors.forename: James K
authors.initials: JK
authors.lastname: Hammitt
authors.forename: Thomas W
authors.initials: TW
authors.lastname: Concannon
authors.forename: Hannah R
authors.initials: HR
authors.lastname: Auerbach
authors.forename: Chihui
authors.initials: C
authors.lastname: Fang
authors.forename: David M
authors.initials: DM
authors.lastname: Kent
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis / Q000191:economics; D001168:Arthritis / Q000175:diagnosis / Q000191:economics; D001943:Breast Neoplasms / Q000175:diagnosis / Q000191:economics; D002755:Choice Behavior; D002908:Chronic Disease / Q000191:economics* / Q000523:psychology*; D003362:Cost-Benefit Analysis; D003955:Diagnostic Tests, Routine / Q000191:economics* / Q000523:psychology; D005260:Female; D005382:Financing, Personal; D006306:Health Surveys; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000191:economics; D018570:Risk Assessment / Q000191:economics / Q000379:methods; D012307:Risk Factors; D011795:Surveys and Questionnaires; D014481:United States; D055815:Young Adult