Monday, October 25, 2010: 4:30 PM
Grand Ballroom West (Sheraton Centre Toronto Hotel)
Peter Neumann, ScD1, Joshua T. Cohen, PhD1, James K. Hammitt, PhD2, Thomas W. Concannon, PhD1, Hannah R. Auerbach, BA1, ChiHui Fang, MPH, MS1 and David M. Kent, MD, MSc1, (1)Tufts Medical Center, Boston, MA, (2)Harvard University, Boston, MA

Purpose: We assessed how much, if anything, people would pay for laboratory testing to predict their future disease status, even if the test had no immediate consequences for treatment.

Method: We administered a questionnaire via an internet-based survey to a random sample of 2,223 adult U.S. respondents.  Respondents were asked whether they would pay for a new blood test that would determine whether they would one day develop a particular disease. Each respondent answered questions about two different hypothetical scenarios, each of which specified:  1 of 4 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, which presented respondents with a binary bidding game, with respondents randomized to one of several starting bids.

Result: Most respondents were inclined to take the test across all diseases (70-88%, depending on the scenario).  Inclination for testing was highest for prostate cancer (85-88% of respondents, depending on disease risk and test accuracy) and lowest for Alzheimer’s disease (71-74%).  WTP was lower for Alzheimer’s and higher for prostate cancer compared with arthritis, and rose somewhat with the stated disease prevalence and for the perfect vs. imperfect test.  Median WTP varied from $109 for the imperfect arthritis test to $263 for the perfect prostate cancer test.  Regarding what they would do with a positive test, respondents most frequently stated that they would obtain a second medical opinion; seek medical care from a medical specialist; sign an advance directive; spend more time with family; and get their finances in order.

Conclusion: Most people preferred diagnostic tests even in the absence of direct treatment consequences -- and were willing to pay reasonably large amounts for the opportunity.  People valued diagnostic information for a host of health and non-health related reasons.  The results held across multiple diseases and across different magnitudes of disease prevalence, test accuracy, and adverse events.  This “value of knowing” seems in part a desire for reassurance, and a desire for information even in light of possible bad news, and suggests that conventional cost-effectiveness analyses may underestimate the value of diagnostics.