Peter Neumann
Institute for Clinical Research and Health Policy Studies
Tufts Medical Center
Peter J. Neumann, Sc.D., is Director of the Center for the Evaluation of Value and Risk in Health at the Institute for Clinical Research and Health Policy Studies at Tufts Medical Center, and Professor of Medicine at Tufts University School of Medicine. Prior to joining Tufts, he was on the faculty of the Harvard School of Public Health for ten years, most recently as Associate Professor of Policy and Decision Sciences. His research focuses on the use of cost-effectiveness analysis in health care decision making. He has conducted numerous economic evaluations of medical technologies, including evaluations of treatments for Alzheimer’s disease. He is the founder and director of the Cost-Effectiveness Registry (www.cearegistry.org), a comprehensive database of cost-effectiveness analyses in health care. Dr. Neumann has contributed to the literature on the use of willingness to pay and quality-adjusted life years (QALYs) in valuing health benefits. His other research has focused on the Food and Drug Administration's regulation of health economic information, and the role of clinical and economic evidence in informing public and private sector health care decisions, including those made by the Medicare program. He is the author or co-author of over 150 papers in the medical literature, and the author of Using Cost-Effectiveness Analysis to Improve Health Care (Oxford University Press, 2005). He is a member of the editorial boards of Health Affairs and Value in Health. Dr. Neumann has served as President of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR), and as a trustee of the Society for Medical Decision Making. He has also held several policy positions in Washington, including Special Assistant to the Administrator at the Health Care Financing Administration. He received his doctorate in health policy and management from the Harvard University.
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.
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 answ... (more »)
In June 2009, the Federal Coordinating Council for Comparative Effectiveness Research submitted a report to the President and Congress in which the Council described the purpose of comparative effectiveness research (CER) as developing evidence-based information for interventions and determining under what circumstances an intervention is effective (1). With the enactment of the Patient Protection and Affordable Care Act, a Patient-centered Outcomes Research Institute (PCORI) was established to assist decision makers in making evidence-based health decisions through synthesis and dissemination of clinical CER of health interventions (2). Its founding has underscored a heightened need for health policy makers to consider the impact of health care technologies on final outcomes of interest-for example, functional status, quality of life, disability, major clinical events, and mortality (3-5).
In June 2009, the Federal Coordinating Council for Comparative Effectiveness Research submitted a report to the President and Congress in which the Council described the purpose of comparative effectiveness research (CER) as developing evidence... (more »)
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 rest 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. 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
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 answ... (more »)
Harvard School of Public Health







