A recent study suggests American consumers would be prepared to pay on average up to $600 for a predictive genetic test where no direct treatment is available.
Research from Tufts Medical Centre examined the willingness of individuals to take and pay for predictive medical tests. The findings showed that on average 76 percent of participants would take a hypothetical predictive test in order to find out the likelihood of developing four stipulated conditions: Alzheimer's disease, breast cancer, prostate cancer or arthritis.
The randomised national survey was conducted online. Of the 1,463 people who responded 82 percent expressed a willingness to be tested for prostate cancer and 72 percent for Alzheimer's. The average price an individual was willing to pay varied from $300 for an arthritis test to $600 for a prostate test.
The growing demand for genetic testing worldwide has raised questions about the value of such tests. As reported in BioNews, concerns have been expressed by the US Government Accountability Office and the Food and Drugs Administration that there needs to be tighter regulation as predictive tests of this sort were often 'inaccurate and misleading'.
When looking at the utility of diagnostic tests, typical measures take into account the accuracy of the test results, cost effectiveness or improved health outcomes. The Tufts Medical Centre study suggests that different measures may be needed to assess the value of predictive testing such as the individual's willingness to make lifestyle changes based on the test results and the value of knowledge for its own sake.
Commenting on the study, lead author Professor Peter Neumann, director of the Centre for the Evaluation of Value and Risk in Health at the Institute for Clinical Research and Health Policy Studies at Tufts Medical Centre, said: 'This study brings us a step closer to understanding people's preferences and motivations for wanting a diagnostic test, even if it has no bearing on subsequent medical treatment'.
He went on to say that 'by taking into account all implications of these tests - including the risks, costs, potential cost offsets, and the value the have outside of medical outcomes - we can build better policies and make better decisions about coverage and reimbursement so that we may more accurately reflect patient preferences and appropriate uses of societal resources'.
The study was published in the medical journal Health Economics.